Froceedmgs of the Second US-USSR
             Symposium om

               edited by
          Reginald D. Noble
Juri L. Martin            Keith F. Jensen

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Proceedings of an International Conference
Corvallis, Oregon; Raleigh, North Carolina; Gatlinburg, Tennessee
September 13-25, 1988
Organized in connection with the 1972 US-USSR Environmental Protection
Agreement (Project 02.03-21)

and sponsored by the

US Department of Agriculture-Forest Service
US Environmental Protection Agency
 Northeastern Forest Experiment Station
 370 Reed Road, Broomall, PA 19008

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                                             95OR89002
AIR POLLUTION EFFECTS ON VEGETATION
            Including Forest Ecosystems

       Proceedings of the Second US-USSR Symposium
                         Edited by

                   REGINALD D. NOBLE
                       US Project Leader
             Bowling Green State University, Bowling Green, Ohio


                     JUKI L. MARTIN
                     Soviet Project Leader
      Tallinn Botanical Garden, Estonian SSR Academy of Sciences, Tallinn, Estonia
                     KEITH F. JENSEN
          US Department of Agriculture, Forest Service, Delaware, Ohio
                     September 1989

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                                        Preface
      At the Tenth Meeting of the US-USSR Joint Committee on Cooperation in the Field of Envi-
ronmental Protection, held in Washington, D.C. in 1986, Dr. Juri Martin and I agreed that our proj-
ect (Project 02.03-21) should organize a symposium in the United States to commemorate the tenth
year of cooperation on this project.  The major objectives of  the symposium were to acquaint
scientists on the two sides with project accomplishments, to promote understanding of the nature
of environmental problems that relate to air pollution effects on vegetation on a more global scale,
to share research priorities, interests, and methodologies and to plan future research cooperation.

      It was decided that holding a "traveling" symposium at three different locations would make
it possible to expose a greater number of the U.S. scientists to the Soviet delegation as well as
increase the exposure of the Soviet scientists to a broad spectrum of research endeavors and
research facilities in the U.S. The Corvallis site offered a U.S.  Environmental Protection Agency
research facility, and a U.S. Department of Agriculture, Forest Service Research Station; the Raleigh
site offered a U.S.  Department of Agriculture Research Service Facility; and the Gatlinburg site
offered an intensively studied national park and a national laboratory.  Furthermore, all were near
major universities where relevant research is also being conducted.

      Planning for the symposium began in earnest in 1987 with the formation of a Symposium
Planning Committee.  Upon the advice of the committee, the symposium  sites were selected, the
themes were identified, programs were planned, speakers were selected, and funding sources were
sought.  By spring,  1988, funding was committed and by early summer, major arrangements were
complete.

      I wish to express my gratitude to the Symposium Planning Committee for the expert job they
did. The committee members were: Ann Bartuska, Roger Blair, Keith Jensen, and David Shriner.
I am pleased to have had the opportunity to  have chaired this committee,  and count it an honor to
have worked with such dedicated and capable individuals.
                                                                         Reg Noble

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                                  Acknowledgements
      The success of this symposium can be attributed, in large part, to the local organizers:Roger
Blair, Ann Bartuska, Dave Shriner, and their associates. Their thoughtful contribution to develop-
ment of the program, their expert assistance in selection of speakers, and their careful handling of
local arrangements were vital to the success of this conference. Technical assistance with prepa-
ration of the manuscripts for publication was provided by Lorraine DeVenney, Tom Howe,  Dan
Lange, Diana Peh, and Jane Trumbull. Editorial assistance was provided by Leon Dochinger, Roy
Ration, Beverly Stearns, and Mary Buchanan.

      Financial support for the symposium, which included hosting the Soviet participants,  was
provided by the U.S. Environmental Protection Agency, the U.S. Department of Agriculture Forest
Service (Northeastern, Southeastern and Pacific Northwestern stations),  the Environmental Sci-
ences Division of the Oak Ridge National Laboratories, Bowling Green State  University,  Oregon
State*University, the National Council of the Paper Industry for Air and Stream Improvement, the
Edward Lamb Foundation, Dr. Anthony Joseph, the Electric Power Research Institute, the National
Park Service, and BP America.  Publication of the proceedings was made possible by funding pro-
vided by the Forest Response Program, Bowling Green State University and the U.S. Environmental
Protection Agency.

      The editors extend sincere thanks to each (named and unnamed) for their support.  Without
their help, the symposium and publication of its proceedings could not have occurred. Also, thanks
are extended to our Soviet colleagues for their participation with special thanks to Soviet Project
Leader Martin for coordinating arrangements for the Soviet side.

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                            Contents
Preface

Acknowledgements

Introduction   	    1
      Juri Martin, Reginald Noble

   Session I   Dendrochronology—Tree Rings and Environment

Introduction    	    8
      Roger Blair
U.S. Forests and Atmospheric Deposition   	    9
      Jack K. Winjum

Comparative  Analysis of the  Standardization Methods  of  Tree-Ring
Chronologies   	   13
      Stepan G. Shiyatov, Harold C. Fritts, Robert G. Logfren

Spatial Patterns  of Climatic Response for Eastern  Hemlock and  the
Potential  Impact of Future Climatic Change   	   27
      Edward R.  Cook, Julie Cole

A 1009 Year Tree-Ring Reconstruction of Mean June-July Temperature
Deviations in the  Polar Urals 	   37
      Donald A. Graybill, Stepan G. Shiyatov

Dendrochronology and Spatial Analyses  	   43
      Gregory A. Reams

100-Year Records of Forest Productivity at High Elevations in Western
Washington, USA  	   49
      Linda B. Brubaker,  Lisa J. Graumlich

Selecting Analysis  Procedures  for Exogenous Disturbance  Tree-Ring
Studies   	   57
      Michael J. Arbaugh

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Air Pollution Effects on Vegetation
                  Session II   Mechanisms and Alternative Hypotheses

            Introduction   	   64
                 Ann Bartuska

            Air Pollutants, Plants, and Mechanisms  of  Interaction:  A Historical
            Perspective   	   65
                 Ellis B. Cowling, Walter W. Heck

            The  Impact  of  Sulfur  Dioxide  Fumigation  on  Photosynthetic  and
            Ultrastructural  Responses of  Mesophyll Cells  from Developing Pinus
            strobus Needles. 1.  Mesophyll Cells   	   71
                 /. M. Kravkina, E. A. Miroslavov, R. E. Crang

            The Impact of Sulfur Dioxide Fumigation on the Ultrastructure and Pho-
            tosynthesis of Pine Needles. II. Resin Duct Epithelial Cells  	   83
                 A. E. Vassilyev, R. E. Crang

            The  Impact  of  Sulfur  Dioxide  Fumigation  on  Photosynthetic  and
            Ultrastructural Responses of Mesophyll Cells in Developing Pinus strobus
            Needles.  III. Transition Zone	   91
                 R. E. Crang, A. E. Vassilyev, I. M. Kravkina

            Ozone Concentration in Leaf Intercellulars is Close to Zero    	   97
                 Agu Laisk, Heino Moldau, Olevi Kull

            Ozone and the Winter Injury Hypothesis in Forest Decline  	  105
                 J. R. Gumming, J. Fincher, R. G. Alscher

            Comparative Physiology and Morphology of Seedling and Mature Forest
            Trees   	.'...  Ill
                 B. M. Cregg, J. E. Hatpin, P. M. Dougherty, R.  O. Teskey

            Mechanisms by which Regional Air Pollutants Affect Forested Soils and
            Rhizospheres: The Significance of Long-Term Perspectives   	  119
                 Daniel D. Richter, Michele M. Schoeneberger

            Mechanisms of Genetic Control  of Air Pollution  Tolerance  in  Forest
            Trees	  127
                 David F. Karnosky

            Forest Health  Diagnosis  and  its  Application in  Air  Pollution  Impact
            Studies   	  135
                 Vladislav Alexeyev

            Modeling Tree Level  Processes  	  143
                 Cheryl Aeschbach Gay

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                                                                     Contents
     Session III   Bioindication and Protected Area Monitoring

Introduction   	  160
      David Shriner

Welcome and Charge to the Conference   	  161
      David E. Reichle

Monitoring the Environment in the 21st Century   	  165
      Stanley I. Auerbach

Managing the Great Smoky Mountains National Park Biosphere Reserve
for Biological Diversity   	  173
      John Peine

The Effect of Nitrate on CO2 Exchange in the Epiphytic Lichens Ramalina
menziesii Tayl. and Pseudocyphellaria anthraspis  (Ach.)  Magn. from
Central California   	  181
      Oleg B. Blum, Thomas H. Nash III, Renate Gebauer

Environmental Monitoring of Biological Markers in Animals and Plants  	  187
      John F McCarthy, S. M. Adams, B. D. Jimenez, L. R. Shugart

Comparative  Estimates of the  Effects of Ozone, Sulphur  Dioxide and
Nitrogen Dioxide on Plant Productivity  	  197
       Yu. A. Izrael, I. M. Kunina, S. M. Semjenov

Indigenous and Cultivated Plants as Bioindicators of Air Pollution Injury  	  201
      L. H. Weinstein, J. A. Laurence

Element Accumulation in Lichens, Mosses and Soils Connected with Mud
Volcano Activity   	  205
      J. Martin, V. Alexeyev,  N. Alexeyeva, L.  Martin, K. Tamm,
      A. Kazachevsky, V. Atnashev

A National Program for Environmental Monitoring and Assessment  	  211
      Jay J. Messer, Rick A.  Linthurst, Courtney Riordan

Biological  Diversity and Global  Change:   Habit Fragmentation and
Extinction   	  217
      Christine Schonewald-Cox, Thomas J. Stohlgren

Relations Between Forest Conditions and Atmospheric Deposition Along
the   Northwestern  Minnesota-to-Southeastern  Michigan  Deposition
Gradient    	  225
      Lewis F- Ohmann, Stephen R.  Shifley

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Air Pollution Effects on Vegetation
           CO2-lnduced Climate Change and Forest Resources   	 233
                 Robin L. Graham, Monica G. Turner, Virginia H. Dale

           Direct  Responses  of  Forest  Trees to  Rising  Atmospheric Carbon
           Dioxide   	 243
                 Richard J. Norby

           Models for Analysis of Vegetation Responses to Global Environmental
           Change   	 251
                 William R. Emanuel, I. Colin Prentice, Thomas M. Smith,
                 Herman H. ShugartJr., Allen M. Solomon

           Brief Reports   	 261

           Symposium Program   	 294

           Session I Participants   	 296

           Session II Participants   	 301

           Session III Participants  	 308

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                                   Introduction


                                      Juri Martin
                                    USSR Project Leader

                                    Reginald Noble
                                    U.S. Project Leader
     The Agreement between the USA and the
USSR on Cooperation in the Field of Environ-
mental Protection was signed  in Moscow on
May 23, 1972.  This treaty-level  agreement
states that "the sides will develop cooperation in
the field of  environmental  protection on  the
basis of equality, reciprocity and mutual bene-
fit" and that  "this cooperation will be directed
towards solving the  most important aspects of
environmental problems and will be dedicated
to the development of measures for preventing
environmental pollution, to the study of pollution
and its effect on the environment, and to  the
development of the bases for  controlling  the
impact of man's activity on  nature."

     The results of this cooperative effort since
its inception  were reviewed at the Tenth Joint
Committee meeting  which was  held in Wash-
ington, D.C., USA, December 1986, and again
in Moscow, USSR, February 1988. A construc-
tive review of environmental problems of inter-
national significance was held during both meet-
ings.  The two  sides  confirmed the  declaration
made by the Joint Committee  in  September
1972 in which it is stated: "The people and  the
governments of both countries consider it of
utmost importance to ensure the responsible
use of natural resources and the protection of
nature under conditions of technical and eco-
nomic progress. The sides will cooperate with
each other and with other interested countries
with the objective  of the joint use of research
results and in advancing the environmental pro-
tection effort in general."

    The Joint Committee acknowledged the
special importance of cooperation on selected
global problems such as stratospheric ozone
depletion and other possible climate  change
associated with anthropogenic impacts, pollu-
tion of the world oceans, and the problem of acid
rain and  forest decline.  Consistent with this
declaration,  efforts were  initiated in 1977 to
establish a  project on  "Interactions Between
Forest Ecosystems and Pollutants." In 1978,
this project was formally established (Project
02.03-21) and the  first cooperative exchanges
took place.  A US  delegation composed of Dr.
Leon Dochinger, the US Project Leader, USDA
Forest Service, Dr. Leonard Weinstein, Boyce
Thompson Institute of Plant Research  and Dr.
Walter Heck, North Carolina State University,
visited the USSR. Later that year, a Soviet
delegation composed  of  Project Leader Dr.
Vladislav Alexeyev, Komarov Botanical Institute
of the Academy of Sciences, USSR,  Dr. Juri
Martin, Tallinn Botanical Garden of the Acad-
                                                                                    1

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Juri Martin and Reginald Noble
emy of Sciences of Estonian SSR, Dr. Alexan-
der Salov, Academy of Sciences of USSR and
Nicolai Prilepo, Ministry of Forestry of the Rus-
sian FSSR visited the  United  States for two
weeks. The major goals of this exchange were
the following:  to acquaint the  two sides with
current research activities and to identify those
areas of research that have greatest potential
for future cooperation; to observe field research
sites and laboratories; to plan cooperative  re-
search activities and identify areas of coopera-
tion to be focused  upon for the next year and
following five year period.

     The  objectives of the project  were dis-
cussed in these early meetings and have evolved
into a set of cooperative endeavors between the
two countries,  which are contributing to the
furthering of our understanding of the impact of
air pollution on the biosphere.  They include:

  —  the impact of air pollution on vegetation
  —  the mechanism of action of pollutants on
      vegetation
  —  the role of vegetation in amelioration of
      air pollution
  —  the management of ecosystems  dam-
      aged by  air pollution
  —  the response of plants to air pollutants in
      conjunction with other environmental vari-
      ables such as light, moisture, nutrition,
       CO2 and temperature

     In 1979, there were two  exchanges.  A
two-member American delegation composed
of Drs. Dochingerand Reginald Noble, Bowling
Green State University, visited the USSR  for
two weeks.  They visited research laboratories
and air  pollution  impact  sites  in  Moscow,
Leningrad, Donetsk and Kishinev.   Later in
1979, Soviet Project Leader, Dr. Alexeyev along
with Dr. Yevgeny Miroslavov of the Komarov
Botanical Institute of the Academy of Sciences,
USSR in Leningrad, were hosted by Dr. Noble
at Bowling Green State University where they
engaged in physiological research for six weeks.
They also had an opportunity to visit  other
university research laboratories for the purpose
of identifying other possible joint projects. Among
the working groups to be established, it was
conceived  that anatomical, and particularly
ultrastructural, studies would  comprise one
important research thrust in understanding the
environmental impact of  air pollutants on
vegetation  -  especially  forest  species and
agricultural crop plants. During, and subsequent
to these two exchanges, Drs. Richard Crang
and Jong Yoon of Bowling Green State University
(Ohio) were invited to take specimens of sulfur
dioxide-fumigated  hybrid  poplar  (Populus
deltoidesx P. trichocarpa) leaves to the Komarov
Botanical Institute laboratories in  Leningrad for
ultrastructural study.  That work, which was
conducted  in 1980, set the stage for productive
collaborative investigations that have continued
to the present. The original Soviet participants
from the Komarov Botanical Institute were Drs.
Maria  Danilova,  Miroslavov   and Andrey
Vassilyev.  Later Dr. Irina Kravkina, also from
the Komarov Botanical Institute, became active
in the project.

     In May,  1981, US Project Leader Dr.
Dochinger  and Dr. Noble  visited the  USSR.
They were acquainted with laboratories and
field  research sites in  Leningrad,  Tallinn
(Estonian SSR) and Dushanbe  (Tadjk SSR).
During this visit, the American delegation worked
with Drs.  Alexeyev and  Martin on a  book
manuscript planned for publication in 1982.
They also worked on plans for the First US/
USSR  Symposium  on  project  02.03-21,
scheduled for autumn 1982. Following the visit
of the American delegation, a Soviet delegation
visited the USA between October and November
of 1981. The delegation was headed by project
leader Dr.  Alexeyev  and  consisted of Drs.
Danilova and Kravkina.  During  this visit, Dr.
Alexeyev conducted physiological research in
the laboratories of Drs. Noble (Bowling Green
State University, Ohio) and Dochinger (USDA
Forest Service   Research  Laboratories,
Delaware, Ohio).  Drs. Danilova and Kravkina
continued  ultrastructural investigations  in the

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                                                                              Introduction
laboratories of Drs. Crang (University of Illinois)
and Noble (Bowling Green State University,
Ohio).  SO2-fumigated plant  materials were
prepared for transfer to the USSR for further
investigations.  The results of this work have
since been published.

     In October of 1982, a ten-member Ameri-
can delegation visited the USSR to participate
in the First USSR/US Symposium on "Interac-
tions Between Forest Ecosystems and Air Pol-
lutants."   The delegation consisted  of  Drs.
Dochinger (US Project Leader), Noble, Crang,
Jay Jacobson, Donald Davis, David Karnosky,
David Shriner, William Smith, Daniel Houston,
and James McClenehan.

     The Symposium was held in the cities of
Leningrad, Tallinn and Puschino-on-Oka.  The
Symposium permitted scientists from the two
sides to discuss current air pollution problems
and to exchange results of recent independent
and cooperative research.  There were 24 for-
mal paper presentations, ten by Americans and
14 by Soviets.  Five additional reports were
given by the American  scientists upon the re-
quest of the Soviet side. Three volumes con-
taining research reports and  abstracts were
published  by the organizers  and distributed
during the symposium. Reports presented at
symposium were received with  great interest
and generated provocative and intense discus-
sion.

     The USSR was represented  by Drs. Al-
exeyev (USSR Project Leader), Martin, George
Jlkua, Victor Tarabain, Valeri Uchvatov, Ljudmila
Martin, Eva Nilson, Nikita Glarovsky, and Oleg
Chertov.

     After the discussion at the symposium, the
main areas of collaborative research were iden-
tified. They included plant physiology, anat-
omy, forest ecology, soil sciences and lichenol-
ogy. During the symposium, a desire to con-
tinue the exchange of delegations during 1983-
1984, and beyond, was jointly expressed. Also,
it was agreed that a second symposium should
be held in the United States in 1985.  None of
these objectives was accomplished.

     In 1985, two  American scientists, Drs.
Noble and Crang visited the USSR. Dr. Crang
worked at the Komarov Botanical  Institute in
Leningrad to continue  research and review
previously collected anatomical data and elec-
tron micrographs and to organize materials for
a joint article with Drs. Danilova, Vassilyev, and
Kravkina.

     Dr. Noble also visited Komarov Botanical
Institute to finalize and edit two papers on light
and SO2 effects on photosynthesis based upon
work performed jointly with Dr. Alexeyev in  Dr.
Noble's laboratory  in 1981.  In  addition,  Dr.
Noble worked at the Tallinn Botanical  Garden,
Estonian SSR Academy of Sciences, Tallinn,
with  Dr. Martin.  While in Tallinn,  Dr.  Noble
visited Tartu State University and the laboratory
of  biophysics at the Institute of Astrophysics
and Atmospheric Physics, Estonian SSR Acad-
emy of Sciences.  Dr. Agu Laisk, head of this
laboratory, demonstrated unique instrumenta-
tion for photosynthesis research.   During the
discussions, the two sides reaffirmed the impor-
tance of continuing  and expanding their efforts
in the areas mentioned above.

     The 1985 year closed with the  Ninth Ses-
sion of the Joint Committee Meeting in Moscow
where the program for cooperation in 1986 was
prepared.   At this  Joint Committee Meeting,
Drs. Noble and Martin assumed their new roles
as project leaders (Noble had been appointed
to this position in November 1982).

     In September 1986, an American delega-
tion consisting of Drs. Noble, Crang and Tho-
mas Nash visited the USSR for a period of two
weeks. The objective of Dr. Crang's visit was to
continue the anatomical research in Komarov
Botanical Institute with the plant anatomy group
headed by Dr. Danilova. Dr. Crang spent most
of his time conducting research and preparing

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Juri Martin and Reginald Noble
manuscripts in cooperation with Drs. Danilova,
Vasilyev, Kravkina and Miroslavov. Dr. Nash
had an opportunity to study at the lichenological
herbarium at Komarov Botanical Institute in
Leningrad and then, with Drs. Noble and Martin,
to visit field sites in Tallinn and Tartu in Estonia
and Sochy (Caucasus area).  In Sochy, the
American delegation was accompanied by Drs.
Oleg Blum (Holodny Botanical Institute, Ukrain-
ian SSR Academy of Sciences, Kiev) and Stepan
Shiyatov (Institute for Plant and Animal Ecol-
ogy, USSR Academy of Sciences, Ural's Divi-
sion) to discuss possibilities of future continued
cooperation  in the field of lichenology and to
institute new cooperation in dendrochronology.

     Project leaders from both sides took part in
the Tenth Joint Committee Meeting in Washing-
ton, D.C. in December, 1986. At this meeting,
the new title of Project 02.03-21 was changed
to: "Air Pollution Effects on Vegetation -Includ-
ing Forest Ecosystems." In addition, Dr. Martin
visited the Arizona State University,  Tempe,
Arizona, where he had productive discussions
with Dr. Nash on continuing joint efforts in liche-
nology. He also visited the University of Arizona
(Tucson, Laboratory  of Tree-Ring Research)
for planning cooperative  research in  dendro-
chronology with Dr. Malcomb Hughes, Director
of the Laboratory of Tree-Ring Research, Ha-
rold Fritts, and Donald Graybill.

     In  1987, the first exchange occurred in
April when Drs. Miroslavov and Kravkina from
the Komarov Botanical Institute were hosted by
Dr. Crang at the University of Illinois. Their visit
was for the purpose of fumigation and prepara-
tion of specimens for ultrastructural investiga-
tions. It was agreed that the current efforts on
sulfur dioxide effects on foliar structures should
be concluded as soon as appropriate speci-
mens were examined.  It was also anticipated
that the work would be presented as part of the
second US/USSR Symposium held in 1988 in
the United States.

     In accordance with joint activities planned
in 1987, a Soviet delegation composed of Drs.
Martin,  Laisk, Molley Mandre (Head of Eco-
physiology Laboratory, Tallinn Botanical Gar-
den, Estonian SSR Academy of Sciences) and
Rodion Karaban (Head of Forest Ecology Re-
search Group, Institute of Applied Geophysics,
USSR State Committee of Hydrometeorology,
Moscow), visited the United States. The major
goals of this exchange were to acquaint the two
sides with current research activities, and to
observe and  participate in field and laboratory
research that might lead to major cooperative
research efforts.

     The delegation visited the US EPA Envi-
ronmental Protection Laboratory, USDA Forest
Service and the Oregon State University, Corval-
lis, Oregon. Drs. Laisk and Mandre engaged in
research at Corvallis in cooperation with Drs.
Roger Blair and William Hogsett on the influ-
ence of SO2  on photosynthetic gas exchange
and the effects of SO2 on carbohydrate metabo-
lism.  They continued this work after two weeks
at the USDA Forest  Service Laboratories in
Delaware, Ohio with Dr. Keith Jensen and Dr.
Ken  Loats.

     During this time, Drs. Martin and Karaban
were visiting field sites and research laborato-
ries at the Great Smoky Mountains National
Park, and the  Ohio State University at Wooster.
In Wooster, they visited field research sites in a
high  pollution impact  region  along the Ohio
River, and in  the Great Smoky Mountains Na-
tional Park, they visited some of the most ad-
vanced air monitoring facilities currently in op-
eration, and visited sites where red spruce is in
a state of decline. The full delegation then came
together and proceeded to the Boyce Thompson
Institute in Ithaca, New York.  The delegation
then  traveled to Whiteface Mountain and  to
Burlington, Vermont, to visit field sites, including
Camel's Hump where  evidence of red spruce
decline was observed.  At each of these loca-
tions, seminars were presented by scientists
from  both sides and free interchange of ideas
and information occurred.

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                                                                               Introduction
     In September, a Soviet delegation consist-
ing of Drs. Blum from Holodny Institute of Bot-
any of the Ukrainian SSR Academy of Sciences
and  Shiyatov from the Institute for Plant and
Animal  Ecology of the Ural's Division of the
Academy of Sciences of the USSR arrived in
the US  for a 90-day stay.  Dr. Blum's work at
Arizona State University and the Oak Ridge
National Laboratory went very well. While at the
Arizona State University, Dr. Blum learned the
CO2 depletion technique for quantifying photo-
synthesis and respiration in lichens. During his
visit at ORNL, laboratory work was completed
for a project that compared the trace metal
contents of lichen species collected in the Great
Smoky Mountains National Park in 1939, 1966
and 1982. This work was done with the support
and  collaboration of Drs. Shriner and  Lorene
Sigal.

     Dr. Shiyatov's work at the University of
Arizona's Laboratory of Tree-Ring Research is
one of the highlights of cooperation to this date.
The principal objectives of this exchange were
to compare various standardized methods, in
particular the Corridor Method, developed and
used by Dr. Shiyatov to obtain the Ural chro-
nologies, with the methods developed and used
at the Laboratory of Tree-Ring Research, and to
cooperate in analyzing and evaluating the ef-
fects of pollutants on the radial growth of trees
at various distances from point pollution sources.
This exchange resulted in the exchange of data,
statistical models and  ideas that proved ex-
tremely valuable to both parties.

     In  accordance with activities planned in
1988, an American delegation  comprised of
Drs. Noble and Jensen visited the USSR for two
weeks in June. This delegation visited Tallinn
Botanical Garden  and the laboratory of Dr.
Laisk in Tartu. In Estonia, final plans were made
for the second symposium.  Next, the US dele-
gation traveled to Irkutsk where Drs. Noble and
Jensen were acquainted with the research work
in the Siberian Institute of Plant Physiology and
Biochemistry.  Of particular interest was the
current research on the impact of fluoride emis-
sions on forest trees. Drs. Noble and Jensen
gave seminars at this institute, and problems
connected with air pollution impact  research
were discussed. The American delegation had
a one-day tour of the region, including a boat ex-
cursion  on Baikal Lake.  Finally, the American
delegation visited Kiev. This visit was hosted by
Dr. Blum from the Central Botanical Garden of
the Ukrainian Academy of Sciences.

     Two other American visits to the USSR oc-
curred in 1988 under Project 02.03-21.  Joint
field work in the Kirgisian mountains for the col-
lecting of dendrochronological core samples by
Drs.  Graybill  from the University  of Arizona's
Laboratory of Tree-Ring Research and Shiyatov
from the Institute of Plant and Animal Ecology of
the Ural's Department of the USSR Academy of
Sciences, Sverdlovski, took place for one month.
This  exchange  was very successful and  will
result in  publication. At approximately the same
time, Dr. Crang was in Leningrad at the Koma-
rov Botanical  Institute where he presented leaf
samples fumigated in his  laboratory. These
samples were subjected to analysis by electron
microscopy.  The two sides also worked on
manuscripts which were being  prepared  for
publication. In Leningrad, Dr. Crang discussed
the possibility for collaborative work with U.
Kallavus from Tallinn Technical University.

     Over the past ten  years, cooperative ef-
forts by the two sides have been productive; and
possibly more importantly, they have laid  the
groundwork for very important future coopera-
tion.  It  is expected that work will intensify in
those research areas already identified and that
it will expand into new areas such as global
climate change.

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                       Session
                         I
Dendrochronology—Tree Rings and Environment
=^^^^^^^^^^^^^^^^^^^= Roger Blair, Jeff Brandt, Beverly Law, Local Organizers

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                                      Introduction
     The field of dendrochronology was chosen
for the theme of the first portion of the USSR/
USA Symposium. The choice was appropriate
in that both countries have made substantial re-
cent progress in developing the tools and tech-
niques of dendrochronology to help unlock the
influence of climate and other factors on  tree
growth. The meetings began with formal pres-
entations covering the state of the  science of
dendrochronology as well as the appropriate
use of statistical procedures in dendrochronol-
ogical analysis.  These presentations set the
stage for lively discussions about the use of
dendrochronology in future analyses of stresses
on forested ecosystems.

    The scientific interchange begun several
years ago in this field continues today. New
data sets  and new analytical procedures  will
continue to improve the international effort in
understanding the potential impacts of the green-
house effect (global climate change) and air
pollution in the world's forest resources.  The
symposium  provided  both  an opportunity to
summarize existing  research as well as plan
future cooperation.
                                                                         Roger Blair

-------
              U.S.  Forests and Atmospheric Deposition

                                    Jack K. Winjum
                            EPA Environmental Research Laboratory,
                                  Corvallis, Oregon, U.S.A.
     Forests in the United  States occupy 33
percent of the nation's land area and exist on
some lands in all fifty states  (USDA Forest
Service, 1982).  In total,  they  cover  approxi-
mately  299 million  hectares and are rich in
essential resources  such as  water, wildlife,
timber and  recreation opportunities.

     In  general, U.S. forests may be divided
into three large regions (Figure 1):

1. The Eastern forests consisting of the north-
ern mixed conifer-hardwood type, the central
mixed hardwood type  and the southeastern
pine type. The total area is 156 million hectares.

2. The  Western forests  which are  predomi-
nately coniferous types divided between the
Rocky Mountains and the areas along the Pacific
Coast. These forests occupy  94 million  hec-
tares.

3. The Alaska forests which are a combination
of coastal conifer types and interior mixed with
conifer-hardwood types for a total of 49 million
hectares.

    The Eastern and Western forests lie be-
tween the 30th and  49th latitudinal parallels
and, therefore, are predominantly in the tem-
perate vegetation zone  (Good, 1964). How-
ever, small areas of tropical forests  exist in
southern Florida and in Hawaii, and the interior
forests of Alaska are boreal.

     Historically, climates and mountain ranges
have had a major influence on forming forests.
In the U.S., the West Coast climate is maritime
with cool winters of  heavy precipitation and
short dry summers. Eastward across the 48
contiguous states, the  climate is  continental
with quite cold  winters and hot, humid  sum-
mers. Major mountain complexes are the Appa-
lachian Mountains which parallel the East Coast,
the stairstep order (low-to-high) of the Pacific
Coast Range, the Cascade Range-Sierra Ne-
vadas and  the  Rockies in the West, and  the
Aleutian-Alaska Ranges along the Pacific coast
of Alaska with the Brooks Range in the northern
interior.

     In total, the U.S. forests represent about
10 percent of the world's 2.85 billion hectares of
forests.  By comparison, the USSR has 790
million hectares of forest lands or nearly 28
percent of the world's total (USDA Forest Serv-
ice, 1973).

     Superimposed over the natural distribu-
tions of U.S. forests is the human infrastructure.
Ownerships include federal, state, municipal
and private lands. In broad terms,  the federal

-------
Jack K. Winjum
                         WESTERN  REGIONS
                          Pacific Northwest
                            [^\j Douglas fir/hemlock/lir
                          California
                            [^2 Pine/lie/redwood
                          Northern  Rockies
                            HH Pine/lir/birch
                          Southern  Rockies
                            •I Pinyon/juniper/pine
EASTERN  REGIONS
 Northeast
  IgJJI Spruce/lir
       Uople/beech/birch
 Central
  H Mople/beech/birch
  g-Tj Ook/hictory
 Southeast
  HI Soulhern pint

 Lake Slates
                                                            Mople/beeck/birch
               Figure 1. Major Forest Regions of the United States and Their Primary Tree Groups
  10

-------
                                                         U.S. Forests and Atmospheric Deposit/on
government owns 21 percent of nation's forest
lands, state and municipal represent 8 percent,
large private ownership (i.e. the forest industry),
14 percent, and small private ownership, the
largest at 57 percent. Much of the latter consists
of parcels less than 200 hectares in size. Such
a complex system of multiple ownerships is rare
among the forested nations of the world and,
while fundamental to a free society, often pres-
ents a significant obstacle to developing and im-
plementing nation-wide forest policies.

     Overall, U.S. forests are highly productive,
providing a high degree of ecological diversity
as well as abundant wood, water and recreation
to meet basic human needs. Forest health, with
few exceptions, has generally been good through
the first two- thirds of this century.   Indeed,
forest science has developed the technology to
double or triple the wood yields in many areas
of commercial forest land over that of  natural
stands while maintaining  or increasing the pro-
ductivity of other forest resources.

     However, in recent decades, several cases
of forest decline on a regional scale have oc-
curred in the U.S. which are not easily explained
by normal  natural  causes. Examples are the
pine-fir forests of the southern Sierra Nevadas
in California and red spruce-true fir forests of the
Appalachian Mountains in the  East (NAPAP,
1987). In these cases, significant foliar damage
has occurred and in some instances this has led
to growth losses and increased mortality through-
out many stands. To a lesser degree, the same
symptoms  have been noted in several other
forest regions.

     Atmospheric deposition of air pollutants is
suspected to play a causal role in many of these
cases. The evidence, however, is largely cir-
cumstantial  in that forest areas with  decline
symptoms  are frequently located where the
deposition  of pollutants  is high.  It must be
remembered, though, that in many of these
areas, stresses due to natural factors such as
drought or winter cold extremes  also  occur.
Pollutants of concern are compounds resulting
from anthropogenic emissions of sulfur dioxide
(SO2),  oxides  of nitrogen  (NOx) and volatile
organic compounds (VOCs) including associ-
ated oxidants such as ozone (O3). Both wet and
dry depositions may be involved. Furthermore,
combinations of these pollutants with natural
factors, as mentioned above, are likely possi-
bilities.

     Proof of cause and effect has  been illu-
sive. Ozone  at  concentrations elevated  by
human  activities has been  proven  to cause
declines in the ponderosa-jeffrey pine stands in
the southern Sierra Nevadas in California and in
the eastern white pine throughout the eastern
U.S. But  many  other wide-spread declines
remain unresolved.

     Forestry  research  programs  have  ad-
dressed the issue over the last 25 years  and
most intensively during this decade. A compre-
hensive summary document on the air pollution
situation in the U.S. is under preparation by the
National Precipitation Assessment  Program
(NAPAP). Plans call for publications in  1990.
Sections on forest effects will form some of the
fundamental portions of the 1990 Assessment
Document. Based on this information, U.S. pol-
icy makers will make new decisions  about the
need for more intensive regulation of air pollut-
ant emissions.

             Literature Cited

Good, R. 1964. The geography of the flowering plants.
   John Wiley & Sons, NY. 518 pp.

USDA Forest Service. 1982. An analysis of the timber
   situation in the U.S. 1952-2030. Forest Resources
   Report No. 23. 499 pp.

USDA Forest Service. 1973. Outlook for timber in the
   United States. Forest Resources Report No. 20.350
   PP-

NAPAP  (National Acid Precipitation Assessment Pro-
   gram). 1987. Forest Effects. Interim Assessment,
   Volume IV, Chapter 7. p. 1 -7 to 7-59.
                                                                                       11

-------
   Comparative Analysis of the Standardization Methods of
                          Tree-Ring  Chronologies

                                  Stepan G. Shiyatov
         Institute of Plant and Animal Ecology of the Ural Division of the USSR Academy of Sciences,
                                    Sverdlovsk, USSR

                         Harold C. Fritts and Robert G. Lofgren
                      Laboratory of Tree-Ring Research, University of Arizona,
                               Tucson, Arizona  85717, U.S.A.
     Many variations in tree-ring widths can be
attributed to fluctuating climatic conditions, but
forest stand conditions, increasing tree age and
various disturbances also produce marked ring-
width variations. These nonclimatic sources of
variations  usually  produce slowly  changing
trends in growth through time.  It is important in
climatic reconstruction work that the noncli-
matic trends be identified as much as possible,
separated from the effects of climatic factors,
and removed so that the remaining  variations
are faithful representations of the climatic fac-
tors.

     The most popular method  of  ring-width
standardization is to fit a curve, either graphi-
cally or mathematically, to the ring widths plot-
ted as a function of time (Fritts, 1976).  This
method can be subjected to rigorous computer
analysis and objective statistics can be used to
describe the results.   The ring widths are  di-
vided by the value of the fitted curve to obtain
standardized growth indices.  This method is
used at the Laboratory  of Tree-Ring Research,
University  of Arizona  (programs  INDEX and
ARSTAN).
     Program INDEX fits a negative exponen-
tial curve, a straight line or a polynomial curve to
the data and then calculates the arithmetic
mean of the indices to obtain the final chronol-
ogy (Graybill, 1982). Program ARSTAN begins
by fitting a similar exponential curve and straight
line.  It calculates the indices and can fit a
second spline curve to the indices if there are
any remaining low-frequency features.  This
second curve is generally a ridged spline re-
moving 50% of the variance at periods of 2/3 the
length of  a  ring-width  record (Cook,  1985;
Holmes et a/., 1986).   In addition, ARSTAN
applies  ARMA modeling and  uses a robust
estimation of the mean to combine the indices
of individual cores and trees into a single chro-
nology.

     Shiyatov (1972, 1986) proposed another
method for calculating the growth indices. It
uses the maximum and minimum possible range
of the ring-width data, which are estimated from
curves fit to these two extremes of the data.
These curves form a strip or a "corridor," so it is
referred to as the CORRIDOR method. The
width  of the corridor varies regularly with the
tree  age,  reaching its maximum during the
                                                                                   13

-------
Stepan G. Shiyatov, Harold C. Fritts and Robert G. Lofgren
period of greatest growth. The corridor displays
a range of growth in response to environmental
fluctuations at different times throughout the life
span  of the tree. The location of the actual
growth for each year within the corridor is taken
into account by subtracting the minimum curve
from the ring width, multiplying by 2 (for a range
of 0 to 200) and dividing  the  result by the
difference between the curves for the maximum
and minimum.  Until now, plots of ring widths
were estimated using human judgment, and the
maximum and minimum possible curves were
drawn by hand.  The technique also has a
mathematical solution.

     If tree ring chronologies from the  US and
the USSR were to be compared or used jointly
in project 02.03-21, "Air Pollution Effects on
Vegetation," it was necessary to evaluate any
differences in the methodology. While Shiyatov
was visiting the Laboratory  of Tree-Ring Re-
search  in 1987,  we carefully examined and
compared these three methods of standardiza-
tion.  The ring-width data came from Siberian
larch  (Larix sibirica Lbd.) growing at the upper
timberline  in various provinces of the Ural
Mountains  (Polar, Subpolar, North and South
Urals), but all grew on relatively moist sites (with
running water). The mean chronology indices
(Table 1) basically reflect the thermal conditions
of the summer months (Shiyatov, 1986).

    The three methods were used to generate
                           three chronologies from each of the four sites
                           (Table 2).   The spline stiffness used in the
                           second detrending of ARSTAN was 100% of
                           the series length so maximum low frequency
                           information was retained in these chronologies.

                                A visual comparison of the plots of indices,
                           an analysis of the main chronology statistics,
                           and a power and cross-power spectrum analy-
                           sis (Blackman and Tukey, 1958) were used to
                           evaluate the similarities and dissimilarities be-
                           tween the tree-ring chronologies.

                                The signal-to-noise ratio (the chronology
                           variance/error variance)  (Table 2) is approxi-
                           mately the same (from 22.9 to 29.2) for the three
                           chronologies from the Polar, Subpolar and North
                           Urals. The ratio was only 8.9 for the chronology
                           from the South Urals. This difference in signal-
                           to-noise ratio allowed us to evaluate the effects
                           of standardization techniques on chronologies
                           with varying amounts of climatic variation.

                                One can see from Table 2 that the chro-
                           nologies developed by the CORRIDOR method
                           have a little higher mean sensitivity and stan-
                           dard deviation as compared  with the chronolo-
                           gies developed by the INDEX and ARSTAN
                           programs. This difference is connected with the
                           fact that the lower limits of the CORRIDOR
                           method must pass through the minimum val-
                           ues, which are zero or positive values, while the
                           lower limits for INDEX and ARSTAN are always
      Table 1.  Characteristics of the mean tree-ring chronologies
       Series
       Code
Province
                  Latitude Longitude
                   North    East
Altitude     Trees   Chronology
 meters    sampled   time span
      S01

      SOS

      S11

      S29
Polar Urals

Subpolar Urals

North Urals

South Urals
66°50'
64'40'
59°35'
54"30'
65"30'
59'50'
59'10'
58'50'
150-300
550-700
800-950
1000-1100
            21

            20

            25

            11
1541-1968

1691-1969

1590-1969

1770-1972
 14

-------
                            Comparative Analysis of the Standardization Methods of Tree-Ring Chronologies
        Table 2.  Statistics of the mean chronologies developed by the various standardization methods (C-
                CORRIDOR, I-INDEX, A-ARSTAN)
Series
Code

S01


SOS


S11


S29

Standardiza-
tion Method
C
I
A
C
I
A
C
I
A
C
I
A
Mean
Sensitivity
0.41
0.40
0.40
0.39
0.35
0.36
0.35
0.33
0.35
0.31
0.24
0.24
Standard
Deviation
0.42
0.42
0.42
0.43
0.40
0.39
0.38
0.37
0.36
0.37
0.29
0.28
Autocorrela-
tion Order!
0.43
0.46
0.47
0.45
0.45
0.39
0.47
0.48
0.39
0.52
0.50
0.45
Signal-to-Noise
Ratio


22.8


27.3


29.2


8.9
zero. Thus, the divisor used for the index of the
CORRIDOR method is smaller making the range
of variability larger.  The chronology with the
weakest climatic signal (South Urals) has the
greatest differences in mean sensitivity and
standard deviation.

     First order autocorrelation values are prac-
tically the same in the chronologies developed
by the CORRIDOR and INDEX methods. These
statistics are lower for three of the ARSTAN
chronologies and higher for one chronology.
These differences probably reflect the fact that
ARSTAN  removes the autocorrelation  as it
prewhitens the individual tree data, averages
the prewhitened data and then adds the  aver-
age autocorrelation for the trees to obtain the
ARSTAN chronology while the other two meth-
ods ignore the autocorrelation.

     The correlations between the developed
chronologies are very high (from 0.917 to 0.981)
(Table 3).  This indicates that the tree-ring chro-
nologies developed by the three standardiza-
tion methods are very similar. The differences
between the correlations of the CORRIDOR
Table 3.  Correlation coefficient values between the tree-ring chronologies developed by various standardization
        methods
Province
Series Code
Standardization
Method
CORRIDOR
INDEX
Polar Urals
S01
INDEX
0.960
ARSTAN
0.965
0.951
Subpolar Urals
SOS
INDEX
0.950
ARSTAN
0.937
0.966
North Urals
S11
INDEX
0.955
ARSTAN
0.932
0.965
South Urals
S29
INDEX
0.917
ARSTAN
0.928
0.981
                                                                                       15

-------
Stepan G. Shiyatov, Harold C. Fritts and Robert G. Lofgren
chronologies with the other two methods de-
crease slightly in the direction from the Polar to
South Urals.  However, the correlations be-
tween the INDEX and ARSTAN chronologies
increase in this direction. A visual comparison
of the index plots also shows the high degree of
similarity between all chronologies.

     The power  spectra of the twelve mean
chronologies are plotted in Figures 1 -4.  Each
spectrum was computed from  100 lags of the
autocorrelation function. The spectral estimates
at each wavelength are expressed as percent
total variance, and as a continuous distribution
of wavelengths throughout the entire spectrum.
The spectrum estimates can show the degree
of similarity in variance of chronologies at differ-
ent wavelengths.

     The spectra of the Polar  Urals chronolo-
gies (S01) are almost identical at all frequen-
cies. The INDEX chronology has slightly more
variance  at  the  lowest frequencies and the
ARSTAN chronology has  slightly more vari-
ance around 0.05 cycles per year.

     The spectra of the Subpolar Urals chronol-
ogy (SOS) show more differences, although
they are very similar especially for the INDEX
and CORRIDOR chronologies. The ARSTAN
method appears to have removed more vari-
ance at very low frequencies.

     The spectra of the North  Urals chronolo-
gies (Fig. 3) are also similar with  some vari-
ations at low frequencies.  Somewhat different
peaks are significant and the CORRIDOR chro-
nology has the highest variance of the three at
0.005 cycles per year.  Fig. 4 for the South Urals
shows the same significant peaks, but as noted
in Fig. 3, the CORRIDOR chronology had the
most variance at the very lowest frequencies.

    The three standardizing methods produce
chronologies with very similar spectra.  Differ-
ences can be noted only at frequencies of 0.05
cycles per year or less. Sometimes the CORRI-
DOR method preserves somewhat more low-
frequency variation, but the differences may not
be large enough to be significant. This differ-
ence seemed to be more apparent in the chro-
nologies that contained a weak climatic signal
(S29).

     The coherence spectra estimate the simi-
larities in variance of two chronologies expressed
as the percent agreement (coherence square)
at different frequencies (Figs. 5-8). All spectra
confirm the  high agreement among the chro-
nologies  at all frequencies. Most of the esti-
mates exceed the 95% significance level (co-
herency =0.93). Occasionally, some estimates
at higher frequencies were markedly low and
insignificant (Figs.  5-7) due to chance or to a
small percent variance in the estimate at that
particular frequency (Fig. 1-3).

     As was noted for the power spectra, the
greatest differences were at the lowest frequen-
cies. The coherence at low frequencies for the
Polar Urals is highest  for the CORRIDOR-
ARSTAN comparison (Fig. 5); it is not so high
for the other three areas, but the lack of agree-
ment is often at frequencies with little variance
(Figs. 2-4). The phase angle plots for all series
indicated that there is no evidence of any lag
problems with these data.

     We conclude that the tree-ring chronolo-
gies developed by the CORRIDOR method and
the INDEX and ARSTAN programs are very
similar and statistically indistinguishable. Any
of the three methods can be  used and the
results compared to the others without restan-
dardizing. If it is necessary to preserve the very
lowest frequencies, the  CORRIDOR method
may be superior. The ARSTAN method may be
the most practical method to use because it can
be altered to remove the variance at different
frequencies.

    However, the ARSTAN program is rather
complex and it should be used with care as the
available  options allow one to  alter the fre-
 16

-------
                             Comparative Analysis of the Standardization Methods of Tree-Ring Chronologies
quency distribution markedly.  The INDEX pro-
gram is less flexible, simpler to operate, and
tends to have more variance at low frequencies
than the ARSTAN program.  This may  arise
from the fact that the exponential function esti-
mated by the INDEX program is better fit to the
early portions of the chronology with the most
ring-width  variability than to the late portions.
This creates more error variance and low-fre-
quency trends in the outer part of the chronol-
ogy.  This  low-frequency error can be reduced
to some extent by the double detrending option
of ARSTAN (Holmes et al., 1986). A follow-up
study of this phenomenon has been conducted
by Fritts and Holmes but this will be the topic of
another paper.

               Literature Cited

Blackman, R.B., and J.W. Tukey. 1958. The Measure-
    ment of Power Spectra. Dover Publications, New
    York.

Cook, E.R.  1985.  A time-series analysis approach to
    tree-ring standardization.  Ph.D.  Dissertation,  De-
    partment of  Geosciences, University of Arizona,
    Tucson, 175 pp.
Fritts, H.C. 1976. Tree rings and climate.  Academic
   Press, London, 567 pp.

Graybill,  D.A.  1982.  Chronology development and
   analysis, pp. 21 -30, /n Hughes, M.K., P.M. Kelly, J.R.
   Pilcher, and V.C. LaMarche  (ed.s),  Climate From
   Tree Rings. Cambridge University Press, Cambr-
   idge.

Holmes, R.L, R.K.Adams, and H.C. Fritts. 1986. Tree-
   ring chronologies of Western North America: Califor-
   nia, Eastern Oregon and Northern Great Basin with
   procedures used in the  chronology development
   work including users manuals for computer pro-
   grams COFECHA and ARSTAN. University of Ari-
   zona, Tucson, Arizona, 182 pp.

Shiyatov, S.G.  1972.  Dendrochronological study of
   Picea obovata in  the Lower Taz River, pp. 76-81, In
   Dencroclimatology and Radiocarbon. Kaunas. (In
   Russian)

Shiyatov, S.G. 1986. Dendrochronology of the upper
   timberline in the Urals. Moscow: Nauka, 136pp. (In
   Russian)
                                                                                             17

-------
Stepan G. Shiyatov, Harold C. Fritts and Robert G. Lofgren
            4>
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Figure 1. Polar Urals Chronology S01 Comparison of Percent Variance, Period: 1550 to 1968 with 100 Lags
  18

-------
                               Comparative Analysis of the Standardization Methods of Tree-Ring Chronologies

           
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                                                                                                   19

-------
Stepan G. Shiyatov, Harold C. Fritts and Robert G. Lofgren
               0.0
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  20

-------
                               Comparative Analysis of the Standardization Methods of Tree-Ring Chronologies
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Figure 4. South Urals Chronology S29, Comparison of Percent Variance, Period: 1770 to 1972 with 100 Lags
                                                                                                  21

-------
Stepan G. Shiyatov, Harold C. Fritts and Robert G. Lofgren
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 22

-------
                               Comparative Analysis of the Standardization Methods of Tree-Ring Chronologies
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                                                                                                23

-------
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                                                          -0.2
                                                                                      •0.0
                                                                                    0.5
                                         Index - Arstan
                                          0-2
                                                        0.3
                                                                      0.4
                                                                                      •i.o
                                                                                      -0.8
                                                                                      -0.6
                                                                                      -0-4
                                                                                     -0.2
                                                                                      -0.0
                                                                                    0.5
                                      Frequency cycle/year


Figure 7. North Urals Chronology S11, Comparison of Coherence Square, Period: 1590 to 1969 with 100 Lags
 24

-------
              Comparative Analysis of the Standardization Methods of Tree-Ring Chronologies

u
a
3
a-

u
c
/^v\A/vrV\rv
HA/ v v YV yy
°H r
J /
i /
0.6-
.

0.4-



0-2-
n n

/ Corridor - Index

I




— i • u.
-0.8


-0-6


-0-4



-o-z
r» r»
\J - u ~T 1 	 1 	 1 	 T 	 1 	 1 	 1 	 1 	 1 — U - U
0.0 0.1 0.2 0-3 0.4 0.5

3
o-
^
u
1
ti
•§
U

0.8-
-
0.6-


0-4-

'
0-2-
n n —
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Index - Arstan





	 . 	 1 i 1 	 n 	 1 1 1 	 — 	 1
-0-8
*
-0.6


-0-4


-0.2
-0.0
0.0
               0-1
                                                        0.4
                                                                      0.5
                                             0.2           0.3




                                         Frequency cycle/year





Figure 8. South Urals Chronology S29, Comparison of Coherence Square, Period: 1770 to 1972 with 100 Lags
                                                                               25

-------
 Spatial  Patterns of Climatic Response for Eastern Hemlock
      and the Potential Impact of Future Climatic Change
                            Edward R. Cook and Julie Cole
                                  Tree-Ring Laboratory
                            Lamont-Doherty Geological Observatory
                             Palisades, New York 10964, U.S.A.
                Abstract

     The empirical climatic response of eastern
hemlock is modeled over most of its geographic
range using tree-ring analysis. The structure of
the temperature response shows broad spatial
coherence from Wisconsin to New England
indicating  a genetics- and/or habitat-based
predispostion to respond to climate in a predict-
able way.  Prior July and current March tem-
peratures are the most important variables fol-
lowed by current June rainfall. These climate
variables increase in importance as the north-
ern and western range limits of hemlock are ap-
proached. This suggests that they are influen-
tial in determining the distribution of hemlock in
those regions. Should future climatic changes
affect these influential months, hemlock distri-
bution along the northern and western limits of
its range may change accordingly.

              Introduction

     By the middle of the next century, significant
global climatic change is expected from warming
caused by increased CO2 in the atmosphere
(Manabe and Wetherald, 1980). Although the
regional patterns of CO2-induced climatic change
are uncertain (Schlesinger and Mitchell, 1985),
both  general  circulation model estimates
(Mitchell, 1983) and climatic scenarios (Wigley
etal., 1980) indicate that eastern North America
will be significantly affected.

     These climatic changes should have a
large impact on the deciduous/evergreen for-
ests of this region. Vegetation/climate classifi-
cation schemes (Emanuel et a/., 1985)  and
forest stand simulations (Solomon, 1986) sug-
gest that there will be substantial changes in the
range limits of many tree species, concomitant
changes  in species composition and impor-
tance in  forest  communities, and, for some
areas, significant declines in live tree biomass.
If these  studies are  correct, the ecological
consequences will  be enormous.

     To  predict how  the eastern deciduous
forests will be altered by future climatic change,
we  first need to know how climate presently
affects the growth and  range limits of the major
tree species  in  these forests. To this end, we
have used tree-ring analysis to study the spatial
properties of climatic response  of eastern
hemlock (Tsuga canadensis [L] Carr.), a widely
distributed tree  species in the eastern decidu-
ous forests.
                                                                                  27

-------
 Edward R. Cook and Julie Cole
                                                             Eastern Hemlock
                                                              Site and Range
                                                                Distributions
                   200   400   600kil
Figure 1. Map of the 42 eastern hemlock tree-ring sites used in this study. Each site is marked by a solid black dot.
        In some cases, more than one chronology is located at a dot. The range limits of hemlock are shown by
        the line of small black dots on the map.
             Eastern Hemlock

     Eastern hemlock  is an  evergreen  tree
species native  to  eastern North  America. Its
present northern and western range limits (Fig.
I) were reached around 1000-2000 years ago
based on pollen evidence (Davis, 1981).  The
lack of  more recent  migration suggests  that
28
hemlock is at equilibrium with climate and other
factors affecting  its  distribution (Davis et a/.,
1986).

     Hemlock typically grows in cool,  humid
environments where adequate soil moisture is
usually available. It is one of the most shade-
tolerant tree species (Powells, 1965) and can

-------
    Spatial Patterns of Climatic Response for Eastern Hemlock and the Potential Impact of Future Climatic Change
grow for decades as a suppressed understory
tree before attaining canopy status. The foliage
of eastern hemlock is extremely dense, allow-
ing  little light to penetrate to the  forest floor.
Thus, the environment beneath a well-devel-
oped  hemlock canopy is cooler and damper
than that found under hardwood canopies in the
same region (Powells, 1965).

     How much climate determines the range
of eastern hemlock is difficult to infer from the
available studies of the species. In the Great
Lakes region,  Davis (1981) suggests that the
halt of hemlock migration south of Lake Michi-
gan about 6000 years ago was due to excessive
dryness in the Midwest. Solomon (1986) uses a
minimum growing degree day (GDD) isotherm
of 1324 GDD as the potential northern range
limit. This isotherm approximates  the present
northern boundary of the species. However,
Kavanagh and Kellman (1986) propose  that
competition is more important than temperature
due to the preference of hemlock for northerly
and westerly facing slopes. In the Southern Ap-
palachians and for disjunct stands in the Mid-
west, hemlock is probably limited  more by the
existence of suitable microhabitats controlled
by physiography than  by any special  set of
macroclimatic variables (Powells, 1965). Thus,
the range limit of  hemlock in the Midwest is
probably determined by drought frequency and
the existence of suitable microhabitats, but the
importance of climate in determining the north-
ern range limit is less clear.

     Over the past several  years, 42 annual
tree-ring chronologies (Fritts, 1976) have been
developed for eastern hemlock over most of its
natural range (Fig.  1). All of the chronologies
are mean-value functions of cross-dated  and
standardized ring-width series from 15 to 30
trees in a stand. These chronologies were origi-
nally developed for reconstructing  past climate
from tree rings, and all are at least 262 years in
length. Although the stands are not a true  ran-
dom sample, there was no selectivity in choos-
ing sites having defined intrinsic characteristics
such as slope aspect, soil type, or elevation.
Rather, the principal criterion for site selection
was that the stand was "old-growth."

     Prior to statistical analysis, the hemlock
chronologies were prewhitened with autore-
gressive  models (Box and Jenkins, 1970) to
remove autocorrelation due largely to internal
biological  processes  of the trees and unique
stand  characteristics and  histories.  The
prewhitened chronologies have the advantage
of being cleaner reflections of the original envi-
ronmental inputs that affect  tree growth. In
addition,  the lack  of autocorrelation greatly
simplifies statistical significance tests between
tree rings and climate.
       Spatial Properties of Eastern
           Hemlock Tree Rings

     To determine if some potentially useful
spatial information was contained in the tree-
ring data, principal components analysis (PCA)
with  analytical rotation (Richman, 1986) was
applied to the 42 chronologies for 207 years
covering the time period 1770-1976. We con-
jectured that if no reasonably coherent spatial
patterns were found in the tree-ring data, then
local (i.e. microclimatic and nonclimatic) influ-
ences would probably be the dominant source
of variance in the chronologies. If so, the search
for macroclimatic controls on hemlock growth
and distribution would probably be futile.

     PCA was applied to the correlation matrix
of the  chronologies. The first 6 factors had
eigenvalues greater than 1.0, which explained
66 percent of the total variance. These factors
were then analytically rotated using Harris-Kai-
ser oblique rotation (Richman, 1986).  Figure 2
shows the maps of these hemlock spatial fac-
tors. Only regions with sites having factor load-
ings >0.60 have been contoured. The square of
the factor loading  can be interpreted as the
percent variance in common between the origi-
nal variable and the particular factor. Thus,

                                        29

-------
 Edward R. Cook and Julie Cole
 loadings of 0.70 indicate -50 percent variance
 in common between the variable and the factor.
 The factors show very clear  geographic pat-
 terns, which is strong evidence for some macro-
 environmental influences on hemlock growth in
 eastern North America.

     From these results, we hypothesized that
 the observed spatial structure could be caused
 by two different, but not necessarily exclusive,
 phenomena. These were:

 I) The factor patterns were caused by inherent
 regional patterns  of climate that are indepen-
 dent of hemlocks's response to climate.  If this
 were the case, then the climatic response mod-
 els may be similar both within and between the
 factor regions. A similar climatic response be-
 tween factors would argue for a genetics- and/
 or habitat-based  predispostion of hemlock  to
 respond to climate in a specific way.

 2) The factor patterns were  caused by geo-
 graphic dependence in the climatic response of
 hemlock. If this were  so, then the climatic re-
 sponse models of hemlock should be the  same
 within  each  geographic factor, but different
 between factors. This condition would argue for
 climate exerting a more local control on  hem-
 lock distribution with  different sets of limiting
 factors controlling growth in each factor region.

     These two hypotheses will be discussed in
 the next section where the spatial properties of
 climatic response by  eastern hemlock will be
 examined.

  Spatial Patterns of Climatic Response
            in Eastern Hemlock

     Monthly temperature  and  precipitation
 records (Boden,  1987;  Bradley et a/., 1985)
were used to model the climatic response  of
eastern hemlock.  Although these meteorologi-
cal variables are not perfect surrogates for the
true macroclimatic  inputs affecting hemlock
growth, they are the only ones available with the
necessary spatial and temporal coverage.

     We used a "nearest neighbor" approach in
pairing meteorological station records with the
tree-ring chronologies. In most cases, we were
able to  use unique pairs of chronologies and
station records. However, in  some areas like
Maine, the small number of  suitably  located
meteorological  stations forced us to use the
same climatic data for  several chronologies.
This reduced the number of unique pairs to 36
or 85.7% of the total number of chronologies.

     The product-moment correlation coefficient
was used to characterize the climatic response
of hemlock. This method does not offer any
predictive capability in the sense of regression
analysis. However, the information gleaned from
correlation analysis will be useful in construct-
ing future regression-based response models.

     A dendroclimatic year beginning in May of
the previous year and ending in September of
the  current year of growth was used in the
correlation analyses. This 17-month year  in-
cludes two radial growth seasons and the inter-
vening cold season months when climatically
induced physiological preconditioning can oc-
cur (Fritts, 1976). The simple correlations were
computed for the 1931-1976 period. This time
period was chosen because one station begins
in 1929, and the data not used from the other
stations will allow us to validate the regression-
based models to be developed in the future.
With these degrees-of-freedom (df=44), any
correlation >|±0.30| (p<0.05) is potentially mean-
ingful.

     The temperature analyses revealed spa-
tially coherent patterns of negative correlation
for the prior July (22 out of  42  <-0.30) and
positive correlation  for March of the  current
growth year (27 out of 42 >+0.30). These signifi-
cant correlations are especially apparent for
sites in the central and  northern  parts of the
range (Figs. 3A & B) where the correlations are
highest. Significantly, the consistency of the
30

-------
 Spatial Patterns of Climatic Response for Eastern Hemlock and the Potential Impact of Future Climatic Change
        GREAT LAKES FACTOR
NEW YORK -NEW ENGLAND FACTOR
          MAINE FACTOR
SOUTHEASTERN NEW YORK-EASTERN
       PENNSYLVANIA FACTOR
Figure 2. The eastern hemlock spatial factors based on tree rings.
                                                                               31

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Edward R. Cook and Julie Cole
                                                 SOUTHERN APPALACHIAN FACTOR


Figure 2. The eastern hemlock spatial factores based on tree rings (continued).
PENNSYLVANIA-NORTHERN VIRGINIA
               FACTOR
July and March temperature correlations ex-
tends across the spatial factors in Fig. 2. This
suggests that hypothesis #1 is largely correct.
That is, eastern hemlock is  predisposed  by
genetics and/or habitat to respond to tempera-
ture in a similar way over much of its range. This
finding is also consistent with Fowells (1965)
who noted the similarity of the microclimate in
hemlock stands over wide geographic areas.

     The results of the precipitation analyses
were less successful. Only one weak geographic
pattern was indicated for June of the  current
growth year (5 out of 42 >+.30). However, the
pattern of these correlations (Fig. 3C) indicates
that the importance of June rainfall increases as
the northwestern range limit is  approached.
The weakness of the precipitation results may
be due, in part, to using single station records
instead of regionally averaged records, which
have been shown to be better correlated with
tree rings (Biasing etal., 1981).
32
                                                To examine the spatial consistency of the
                                            overall monthly  temperature  response, we
                                            subjected the full suite of correlations to PCA
                                            with analytical rotation. In this case, the first two
                                            eigenvalues explained 75 percent of the vari-
                                            ance,  with eigenvalue #l accounting for the
                                            most at 62 percent. This indicates that the pat-
                                            tern of correlations between  hemlocks and
                                            monthly temperatures are also much more
                                            spatially consistent than the patterns in the tree
                                            rings themselves. After the two eigenvectors
                                            were obliquely  rotated,  an extremely  broad
                                            northern temperature response emerged, fol-
                                            lowed by a more southerly Pennsylvania-North-
                                            ern  Virginia response (Fig. 4).  The Southern
                                            Appalachian hemlock sites are not represented
                                            in either factor  probably because of greater
                                            heterogeneity in the temperature  response
                                            patterns seen there and  because of the rela-
                                            tively small number of sites from that region.
                                            The monthly factor scores of these patterns
                                            (Fig. 5) are extremely similar, with a correlation

-------
     Spatial Patterns of Climatic Response for Eastern Hemlock and the Potential Impact of Future Climatic Change
 of 0.98. Thus, the existence of different spatial
 patterns of temperature response is question-
 able. The only apparent difference in the scores
 is a  slightly  higher  emphasis on prior June
 temperature in  the more southerly factor #2.
 There is  some  indication that November and
 February temperatures also have a weak influ-
 ence on hemlock growth when viewed  across
 the region, even though on a site-specific basis
 they are rarely statistically significant.

                 Discussion

     The results of this  study  indicate  that
 eastern hemlock is  strongly and predictably
influenced by climate in a broad geographic
way.  There is  effectively only one  pattern of
temperature response in the tree-ring chronolo-
gies studied here, with the exception of the
Central and Southern Appalachian sites. There-
fore, the existence of 6 spatial tree-ring patterns
can be largely explained by the regionality of
climate, not by regional differences in hem-
lock's  response to climate. The exceptions to
this conclusion are the Central and Southern
Appalachian sites and, to a lesser degree, the
Maine sites. While the monthly structure of the
temperature response is spatially stable over a
very large part of hemlock's range, the magni-
tudes  of the correlations  show distinct geo-
      A. Prior July Temperature Correlation Map           B. March Temperature Correlation Map

 4B 0  ,	,	,	1	,   46 0
 454
 40.2
 37.6
 350
                                                426
                                                40.2
                                                37.6
                                                350
    -91
              -85
                       -79       -73        -67       -91       -65        -79

                               C. June Precipitation Correlation Map
                        45.4   :
                        428
                        376
                        35.0
                                                                                -73
                                                                                          -67
                                     -B5
                                               -79
                                                         -73
                                                                  -67
Figure 3. Contoured maps of the correlations between the 42 hemlock chronologies and prior July (A) temperature,
        March (B) temperature, and June (C) precipitation. The maps have been smoothed and contoured using
        distance-weighted least squares. Only those contours exceeding ±0.30 are shaded. The solid black dots
        denote the locations of the tree-ring sites.
                                                                                          33

-------
Edward R. Cook and Julie Cole
                                              EASTERN HEMLOCK
                                              SITE AND RANGE
                                               DISTRIBUTIONS
                     TEMPERATURE FACTOR PATTERN #1
                                             EASTERN HEMLOCK
                                              SITE AND RANGE
                                               DISTRIBUTIONS
                     TEMPERATURE FACTOR PATTERN #2

              Figure 4.  The spatial patterns of temperature response for eastern hemlock.
34

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    Spatial Patterns of Climatic Response for Eastern Hemlock and the Potential Impact of Future Climatic Change
                       TEMPERATURE RESPONSE FACTOR #1 SCORES
        F
        A
        C
        T
        O
        R

        S
        C
        O
        R
        E
        S
                   M   JJ   ASONDJ   FMAMJ   J   AS
                                            MONTHS
                        TEMPERATURE RESPONSE FACTOR #2 SCORES
        F
        A
        C
        T
        O
        R

        S
        C
        O
        R
        E
        S
 2 -
-1  -
              -2
                   M   JJ   ASONDJ   FMAMJ   J
                                            MONTHS
                                                           A  S
Figure 5. The factor scores of the two principal temperature factors for hemlock. The factors, themselves, are
          shown in Fig. 4.
graphic variations. For July and March, these
variations increase as the northern and western
range limits are approached. This is especially
true for the hemlock sites in the Great Lakes
region.
                                    The strong negative correlations between
                               prior July temperatures and hemlock growth in
                               the Great Lakes region argue for this variable
                               being very important in determining the range
                               limits of the species there, probably through its
                               effect on evapotranspiration demand. This sug-
                                                                                    35

-------
Edward R. Cook and Julie Cole
gests that persistent increases in July tempera-
tures coupled with decreases in  June rainfall
will have a negative effect on hemlock growth,
which could ultimately lead to an eastward con-
traction  of  its range. The spatially coherent
March temperature response was totally unex-
pected.  We cannot say from these analyses
how it relates to the northern range limits of
hemlock because the physiological basis for
the March temperature effect is obscure. How-
ever, it is possible that if future climatic change
results in warmer March temperatures, then this
effect may  provide the necessary margin for
hemlock to extend its range limits northward.

             Acknowledgements

     This research was made possible through
a grant from the U.S.  Environmental Protection
Agency, Grant No. EPA 814691. We thank Jon
Overpeck, Dorothy Peteet, Paul Sheppard and
Al Solomon  for  helpful  comments. Lamont-
Doherty Geological Observatory Contribution
No. 4482.

               Literature Cited

Biasing, T.J., D.N. Duvick, and D.C. West. 1981. Dendro-
   climatic calibration and verification using regionally
   averaged and single station precipitation data. Tree-
   Ring Bulletin 41:37-44.

Boden.T.A. 1987.  United States Historical Climatology
   Network (HCN) Serial Temperature and Precipita-
   tion Data.  Carbon  Dioxide  Information Analysis
   Center, Oak Ridge National Laboratory, Oak Ridge,
   Tennessee.

Bradley, R.S., P.M. Kelly, P.O. Jones,  H.F. Diaz, and
   G.M.  Goodess.  1985.  A Climatic Data Bank For
   Northern Hemisphere Land Areas, 1851-1980. Car-
   bon Dioxide Research Division, U.S. Department of
   Energy, Washington, D.C.

Box,  G.E.P and G.W. Jenkins.  1970.  Time Series
   Analysis: Forecasting and Control. Holden-Day, New
   York.
Davis, M.B. 1981. Quaternary history and stability of
   deciduous forests. In: D.C. West, H.H. Shugart &
   D.B. Botkin (eds.) Forest Succession. Springer-Ver-
   lag, New York. pp. 132-177.

Davis, M.B., K.D. Woods, S.L. Webb, and R.P. Futyma.
   1986. Dispersal versus climate: Expansion of Fagus
   and  Tsuga into the upper Great Lakes region. Vege-
   tatio 67:93-103.

Emanuel, W.R., H.H. Shugart, and M.P. Stevenson.
   1985. Climatic change and the broad-scale distribu-
   tion  of terrestrial  ecosystem  complexes. Climatic
    Change 7:2Q-43.

Powells, H.A.  1965. Silvics of Forest Trees of the United
    States. Agricultural Handbook No. 271, U.S. Depart-
    ment of Agriculture, Washington, D.C.

Fritts, H.C.  1976. Tree Flings and Climate. Academic
    Press, New York.

Kavanagh, K. and M. Kellman. 1986. Performance of
    Tsuga canadensis (L.) Carr. at the centre and north-
   ern edge of its range: a comparison. Journal of Bio-
   geography 13:145-157.

Manabe, S. and R.T. Wetherald. 1980.  On the distribu-
   tion  of climate change resulting from an increase in
    CO2-content of the atmosphere. Journal of the At-
    mospheric Sciences 37:99-118.

Mitchell, J.F.B.  1983.  The seasonal  response of a
   general circulation model to changes in CO2 and sea
   temperatures. Quarterly Journal of the Royal Mete-
   orological Society 109:113-152.

Richman, M.B. 1986. Rotation of principal components.
   Journal of Climatology 6:293-335.

Schlesinger, M.E. and J.F.B. Mitchell.  1985.  Model
   projections of the equilibrium  climatic response to
   increased carbon dioxide. In: M.C. MacCracken and
   F.M. Luther, eds. U.S. Department of Energy Docu-
   ment DOE/ER-0237. pp. 81-148.

Solomon, A. 1986. Transient response of forests to CO2-
   induced climatic change:  simulation modeling ex-
   periments  in  eastern North America.  Oecologia
   68:567-579.

Wigley, T.M.L., P.O. Jones,  and P.M. Kelly.   1980.
   Scenario for a warm, high-CO., world. Nature283:17-
   21.
36

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   A 1009 Year Tree-Ring Reconstruction of Mean June-July
             Temperature Deviations in the Polar Urals
                                   Donald A. Graybill
                               Laboratory of Tree-Ring Research
                                    University of Arizona
                                   West Stadium, Rm. 105
                                 Tucson, AZ 85721, U.S.A.

                                  Stepan G. Shiyatov
                           Institute of Plant and Animal Ecology of the
                         Ural Division of the USSR Academy of Sciences
                                 Sverdlovsk, 620008 USSR
     We have made a reliable reconstruction of
 average June-July temperature departures for
 the period of A.D. 961-1969 using  tree-ring
 width variation of Lam sibirica from the north
 Polar Urals of the USSR. This is the first dendro-
 chronological reconstruction of seasonal tem-
 perature over the past millennium for the sub-
 Arctic. It is of considerable interest,  not only
 because of its length,  but also for the reason
 that it may contain information about trends and
 long-term  variation in temperature  over large
 areas. The tree-ring chronology (Shiyatov #1 -
 4a, 1986) was developed from ring-width series
 taken from both living and dead individuals near
 treeline at elevations of 150-380m just south of
 the Kara Sea. The region around the Kara Sea
 is thought to be one that is particularly sensitive
 to  long-term trends and variations in tempera-
 ture over  the Arctic and  even the Northern
 Hemisphere. This is based on an analysis of
 instrumented values of surface  air tempera-
tures for the period of 1881-1980 (Kelly et al.,
 1982).
     Individual tree-ring  series were initially
crossdated with each other and all rings were
assigned calendar years  based on the known
collection dates of the living series. Ring-widths
were  measured to the nearest 0.01mm and
then each series was treated with the Corridor
Method of Standardization (Shiyatov and Maz-
epa, 1987). Seventy-six of  these series were
combined by simple averaging to form a tree-
ring index chronology for  the region.

    Changes  in the strength of the common
signal  in  chronologies  such as these are of
interest. As sample size  per year decreases,
usually near the early part of one, generaliza-
tions about the reliability of a reconstruction de-
veloped from it during those years may need to
be tempered. A useful measure for considera-
tion of this is the Subsample Signal Strength
(SSS) (Wigley et al., 1984).  This estimates the
variance agreement that might be obtained with
reduced numbers of a fuller sample of series. It
was possible to make an  estimate of the SSS
with a subset of 13 ring-width index series that
                                                                                  37

-------
Donald A. Graybill and Stepan G. Shiyatov
Table 1. Chronology subsample signal strength.
     N of series
Variance agreement
First year with this N
1
2
3
4
5
6
7
8
9
10
11
12
13
.69
.83
.89
.92
.94
.96
.97
.98
.98
.99
.99
.99
1.00
960
1017
1018
1042
1086
1089
1094
1108
1141
1142
1170
1172
1190
were included  in this  chronology during  the
period of 1800-1960. The results presented in
Table  1 also include the earliest  years in  the
chronology where the numbers of series range
from one to thirteen. This provides an approxi-
mate guide to the reliability of the reconstruction
in those early years. The overall strength of the
common signal is estimated by two other  fig-
ures that includes the amount of variance held
in common (61 percent) and the signal-to noise
ratio (25.8:1). These values are in the upper-
most range for chronologies considered to be
useful  as temperature indicators (Fritts, 1976;
Graybill, 1982,  1985; and Wigley et al., 1984).

     Instrumented temperature series used in
this study are from a monthly mean value data
set that is available for the  Northern Hemi-
sphere on a grid of 5° latitude by 10° longitude
(Jones et al., 1985). These are expressed as
departures in degrees Celsius from  a 1951-
1970 normal period. Values for the period of
1881-1969 were selected from the grid point
nearest the tree-ring data, latitude  65°N, longi-
tude 70°E.

     The relationship between tree growth and
monthly  mean temperature departures was

 38
                 investigated with simple correlation procedures.
                 The strongest  relationship occurs during the
                 months of June and July, essentially the grow-
                 ing season at this latitude. The correlation for
                 the early summer average of values with the
                 tree-ring series is +0.78 (p
-------
            A 1009 Year Tree-Ring Reconstruction of Mean June-July Temperature Deviations in the Polar Urals
1976). The resultant white noise residuals are
normally distributed. The temperature series
exhibits  slight but significant autocorrelation
and is normally  distributed. This  series was,
however, not prewhitened due to the  limited
amount of persistence involved and to uncer-
tainty about the representativeness  of this 89
year data set as a realization of the longer term
autocorrelation structure.

     Several calibration-verification trials using
simple linear  regression were made to deter-
mine how adequately the white noise residuals
of the tree-ring indices could predict the tem-
perature departures. The first set of two analy-
ses successively used one half of the data over
                                 the period of 1882-1969 for calibration and the
                                 other half for verification. A set of three trials
                                 successively used two-thirds of the data for cali-
                                 bration and the remaining one-third for verifica-
                                 tion.  A set of four  trials was conducted in a
                                 similar fashion. Results of these  trials were
                                 acceptable in terms of the evaluation of stan-
                                 dard goodness-of-fit criteria, and in terms of the
                                 characteristics  of the regresion residuals. The
                                 results of several associated  tests commonly
                                 used in dendroclimatic  research  that are pre-
                                 sented in Table 2 also suggested that the tree-
                                 ring white noise residual series was a reliable
                                 estimator of the temperature series (Fritts, 1976).
                                 Given the high quality of these results and a
                                 desire to consider the fullest possible range of
Table 2. Calibration and verification test summary. (Symbols explained below)
Calibration period

1926-1969
1882-1925
r\
.42a
.75a
Verification period

1882-1925
1926-1969
r2 s P t W
.75a a a a a
.42a a a a a
RE
.60
.18
  1912-1969
  1883-1911,
                 .58a
                            1883-1911    .56a   a
                                                                             .61
1941-1969
1883-1940
.54a
.62a
1912-1940
1941-1969
.66a
.51a
a
a
a
a
a
a
a
a
.67
.52
  1904-1969

  1882-1903,
  1926-1969

  1882-1925,
  1948-1969

  1882-1947
.59a
.48a
.65a
.66a
           1882-1903
           1904-1925
1926-1947
1948-1969
                        .54a
                        .86a
                        .45a
                        .36a
                                          a    a

                                          a    a
.64


.77


.15

.40
 FINAL CALIBRATION 1881-1969 r4 = .60
 ra2 = r2 adjusted for degrees of freedom, alpha = .01
 r2 = variance explained, alpha = .01
 s = first difference sign test, alpha = .01
 P = product means test, alpha = .01
 t = Student t-test, alpha = .10
 W = Wilcoxon matched pairs signed ranks test, alpha - .10
 RE = reduction of error test
 a = null hypothesis not rejected
 r = null hypothesis rejected
                                                                                           39

-------
Donald A. Graybill and Stepan G. Shiyatov
covariation in developing the final calibration
equation used for reconstruction, data for the
full 89 years of common period were analyzed.
Sixty percent of the variance in the two series is
in common, the covariance is significant at the
0.001 level and the regression residuals do not
show abnormal outliers or significant autocorre-
lation.  A reconstruction of average June-July
                       Degrees C
              Degrees C
                        —    o
     Figure 1. Reconstructed mean June-July temperature departures, North Polar Urals, A.D. 961-1969
40

-------
            A 1009 Year Tree-Ring Reconstruction of Mean June-July Temperature Deviations in the Polar Urals
        D
        E
        G
        R
        E
        E
        S
                    1000
1200
1400
                                                     1600
                                 1800
 Figure 2.  Twenty year averages of reconstructed mean June-July temperature departures, North Polar Urals, A.D.
         961-1969.
temperature departures was then developed
for the period of A.D. 961 -1969.

     Reconstructed early summer temperature
deviations over the past millennium are illus-
trated in Figure 1. Twenty year non-overlapping
averages of those values are shown in Figure 2
to aid  in recognition of predominant kinds of
trends. One of the more striking patterns is the
rise in values from near 1100 to the highs of the
1200's-1300's, followed on the long term by an
overall decline in values, but with some in-
crease since the lows of the 1600's. This larger
pattern as well as several of the major peaks in
values (near 1200,  1300, the mid-1500's and
near 1700) are reminiscent of Lamb's  (1966)
reconstructed  temperature record  for central
England. Additionally, certain major features of
our reconstruction such as the low values of the
1600's, and those of  the 1800's that are  fol-
lowed  by a sharp  increase  in  20th century
values are seen in many other high latitude and
altitude tree-ring chronologies.  Space  limita-
tions here preclude further discussion of this.

     Now, most of the constituent tree-ring
               series forming the chronology range in age from
               about 220-400 years, although  a few are of
               shorter length.  Given this, and the fact that
               standardization can remove trends that are at
               the same or greater length than the series in
               question, the  ability of this reconstruction to
               mirror longer term trends may be questioned.
               There are, however,  important field observa-
               tions that bear on this issue. Dead series in this
               chronology  are from  elevations  of  100-120m
               above the highest currently living trees. All of
               the former that were living in the early mid-
               1600's had dramatic growth decline at that time
               and their demise occurred then or shortly there-
               after. This is also the time period when  the
               majority of the oldest living trees found at  the
               current elevational treeline germinated, although
               some found here date to the mid-1500's. There-
               fore, it is possible that the longer term trends in
               temperature departures are at least reasonably
               estimated. The two different elevational group-
               ings of  trees provided continuous monitors of
               temperature variation at their respective loca-
               tions and sequentially their records may have
               captured those trends.
                                                                                      41

-------
Donald A. Graybi/l and Stepan G. Shiyatov
     Further evaluation of the results obtained
here may be possible as the development and
analysis of other long tree-ring chronologies in
the sub-Arctic proceeds (Bartholin, 1984). Quan-
titative i nformation derived from a spatial field of
long tree-ring chronologies should prove useful
for evaluating models of  long-term  climatic
variation on regional and hemispheric scales,
or even for testing hypotheses about the global
nature of phenomena such as the Little Ice Age
(Grove,  1988).

               Literature Cited

Bartholin, T. S. 1984.  Dendrochronology in Sweden. In
   Climatic Changes on a Yearly to Millennial Basis.  N.
   A. Morner and W. Karlen (eds). Reidel Publishing
   Company.

Briffa, K. Ft., P. D. Jones, J. R. Pilcher and M.K. Hughes.
   n.d. Reconstructing Summer Temperatures in North-
   ern  Fennoscandia Back to 1700 A.D. Using Tree-
   Ring  Data from Scots Pine.  In press, Arctic and
   Alpine Research.

Box,  G. E. P., and G. M. Jenkins.  1976.  Time Series
   Analysis forecasting and Control. Holden-Day, San
   Francisco.

Fritts, H. C.  1976.  Tree Rings and Climate. Academic
   Press, London.

Graybill, D. A.  1982.  Chronology Development and
   Analysis. In Climate from Tree Rings.  M. K. Hughes,
   P. M. Kelly,  J. R. Pilcher, and  V. C.  LaMarche,  Jr.
   (eds).  pp. 21-28. Cambridge University Press, Lon-
   don.

Graybill, D. A.  1985.  Western U. S.  Tree Ring Index
   Chronology Data for Detection of Arboreal Response
   to Increasing Carbon Dioxide. No. 026 in the U. S.
   Department  of Energy Green Book Reports on the
   Response of Vegetation to Carbon Dioxide series.
   Laboratory of Tree-Ring Research, University of Ari-
   zona, Tucson.
Grove, J. M.  1988.  The Little Ice Age. Methuen.

Jacoby, G. C. and E. R. Cook. 1981. Past Temperature
   Variations Inferred From a400 Year Tree-Ring Chro-
   nology from Yukon Territory, Canada.  Arctic and
   Alpine Research 13(4):409-418.

Jones, P. D., S. C. B. Raper, B. D. Santer, B. S. G. Cherry,
   C. Goodess, R. S. Bradley, H. F. Diaz, P. M. Kelly and
   T. M. L. Wigley. 1985. A Grid Point Surface Air Tem-
   perature Data Set for  the Northern  Hemisphere,
    1851-1984. U.S. DOE Technical Report, TR022, U.
   S. Department of Energy Carbon Dioxide Division,
   Washington D.C.

Kelly, P. M., P. D. Jones, C. B. Sear, B. S. G. Cherry and
    R. K. Tavakol. 1982.  Variations in Surface Air Tem-
   peratures: Part 2, Arctic Regions, 1881-1980. Monthly
    Weather Review 110:71 -83.

Lamb, H. H.  1966.  The Changing Climate. Methuen.

Shiyatov, S. G. 1986. Dendrochronology of the Upper
    Forest Boundary in the Urals.  Nauka, Moscow (in
   Russian).

Shiyatov, S. G. and V. S. Mazepa.  1987.  Some New
   Approaches in the Construction of More Reliable
   Dendrochronological  Series and in the Analysis of
   Cycle Components. Methods of Dendrochronology-
    I, Proceedings of the Task Force Meeting on Method-
   ology of Dendrochronology: East/West Approaches.
    NASA, Laxenberg, Austria.

Wigley, T. M. L., K.R. Briffa and P. D. Jones. 1984.  On
   the Average Value of Correlated Time Series with
   Applications  in  Dendroclimatology  and Hydro-
   meteorology.   Journal  of  Climate and  Applied
   Meteorology 23:201-213.

Wonnacott, T. H. and R. J. Wonnacott.  1981.  Regres-
   sion: A Second Course in Statistics.  Wiley. New
   York.
 42

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               Dendrochronology and Spatial Analyses

                                   Gregory A. Reams
                               Environmental Research Laboratory
                           Oregon State University, 200 S.W. 35th Street
                                Corvallis, Oregon 97333, U.S.A.
                 Abstract

     The linear aggregate model (Cook, 1987)
 is proposed as a statistical tool to separate
 sources of variability inherent in tree-ring se-
 ries.  Use of  multivariate spatial  statistics is
 introduced as a technique to investigate the
 spatial covariation of  atmospheric deposition
 and tree-ring indices.

               Introduction

     Tree ring data offers a unique historic
 record of past  endogenous and exogenous in-
 fluences on tree growth.  It is  this historical
 tracking that can be exploited to assess the
 possible impacts of atmospheric deposition on
 forests.  To adequately address  the  atmo-
 spheric deposition impact hypothesis, it is nec-
 essary that other ecological and environmental
 variables that influence tree growth be accounted
 for. How to extract the signal of interest is not a
 simple concept.  Signal is defined here as that
 information in the tree ring series which is rele-
 vant to the study of a particular problem (Cook,
 1987). A tree ring series can be thought of as
 consisting of several to many unobserved sig-
 nals. Some of these signals will be of no interest
or cannot be  accounted for, as such  these
sources or variation will be considered as noise.
We thus wish to decompose the observed growth
rings into a number of signals which represent
the environmental influences on tree growth.

     Cook (1987) gives an excellent account of
the likely sources of variation in tree ring series
and provides a conceptual framework for the
decomposition of growth rings in the form of a
linear aggregate model. This model allows the
identification  of the  likely signals influencing
tree growth. Following Cook, a possible aggre-
gate series can be expressed as:
       R, = At + Ct+A.D1t + a.D2, + E(

where Rt is the observed ring-width series, A,,
the age-size related trend in ring-width, Ct, the
climatic signal, D1t, a pulse caused by a local
(endogenous) disturbance, D2t, a pulse caused
by  a standwide  (exogenous)  disturbance, X,
either 1  or 0 indicating presence or absence of
a disturbance, and E,, unexplained year-to-year
variability.

     At  is the growth trend of the tree and,
therefore, is a nonstationary process. The type
of trend model chosen largely depends upon
the situation.  For open grown trees, a negative
exponential curve can  portray the expected
growth trend.  However, for trees strongly influ-
enced by competition and disturbances in the
forest, more flexible  models are needed.   For
further insight, refer to Cook (1987).
                                       43

-------
Gregory A. Reams
     Ct is the climatically related environmental
variable.  Precipitation, temperature,  and the
Palmer Drought Severity Index (Palmer, 1965)
which are computed from average monthly tem-
perature and  precipitation data, are variables
that can be obtained from the Historical Clima-
tology Network  (HCN)  produced by NOAA
(Boden, 1987).  Ct is a common signal to all
trees in  a stand.  The modeling methods of Ct
are beyond the  scope  of this paper, but the
following references are some suggested read-
ings: Fritts et a/., 1 971 ; Fritts, 1 976; Guiot, 1 985;
Cook, 1988; Van Deusen, 1988.
        1, is a pulse that represents endoge-
nous disturbance on a given tree.  Such distur-
bances are common where stand development
creates opportunities for release of trees that
are in a state of suppression. This is commonly
referred to as a gap-phase dynamic (White,
1 979).  An endogenous disturbance for a given
tree will be considered a random event which is
uncorrelated with endogenous disturbances in
other trees.   Thus, X=1 or 0, depending on
whether a disturbance has taken place or not.

     ID2{ is the variable representing a stand-
wide (exogenous)  disturbance effect on tree
growth.  Insect and disease  epidemics, fire,
wind storms, forest management practices, and
natural and anthropogenic deposition of chemi-
cals are possibilities.  Because A.D2, operates
on a standwide basis, it should be present in all
trees, quite unlike  A.D1, which operates as a
largely random pulse among trees.  X is either 1
or 0, depending on  whether an  exogenous
disturbance has occurred or not.

     Et is  the error term and represents  the
sources of variation not accounted for by the
other model terms.  It is assumed that the error
term is  uncorrelated in time and space between
trees in the stand.

             Standardization

    There are a  variety of  standardization
techniques available. It is beyond the scope of
this paper to thoroughly discuss the implica-
tions of alternative standardization techniques.
The following, however, are excellent places to
start:  Fritts et a/., 1969, 1976; Warren, 1980;
Cook,  1985; Monserud, 1986; Shiyatov and
Mazepa, 1987; Van Deusen, 1987.

    The  essence  of standardization is  the
estimation and  removal of growth trend  (A,)
from the ring-width series. Once this is accom-
plished, the original nonstationary ring widths
are transformed  into relative tree-ring  indices
that have a mean of 1.0 and constant variance.
The relative index is computed by dividing each
original ring width by its expected growth trend
value, which is estimated by At (lt = R,/ At). The
expected value of I, is 1.0. Clearly how close the
growth trend mimics the ring widths determines
the degree of homogeneity of variance about l(.
Care should be taken that the possible pollution
signal is not removed by using a growth trend
function that is much too flexible (Cook, 1985).

    After standardization, a mean-value func-
tion can be computed based on averaging the
index series for all trees in a given stand. At this
point,  the estimation of the climatic  signal can
begin.  Past studies (Fritts, 1976) have gener-
ally used the arithmetic mean.  I advocate the
use of a robust mean.  Cook (1987) indicates
that  the use of the biweight mean  (Mosteller
and Tukey, 1977) is a reasonable choice. The
robust mean will discount the influence of outli-
ers and thus reduce the variance  and bias.
Endogenous effects will cause outliers to ap-
pear in the index series, and can confound the
estimation of the climate signal. The robust
mean is one way to deal with these random
pulses (outliers) and enable cleaner  estimation
of the climatic signal.

    In the context  of finding an air pollution
signal, the purpose of estimating the climatic
signal is to predict values of tree indices based
on a climate model. This can then be used to
test for nonclimatic  influences on growth, for
 44

-------
                                                           Dendrochronology and Spatial Analyses
 example, pollutant deposition.

       Autoregressive Disturbances

     It is generally known that a certain amount
 of physiological preconditioning is  present in
 tree-ring widths. This means that present growth
 is autocorrelated with past tree growth. These
 autocorrelated structures can be addressed by
 use of statistical models that  account for this
 process.   The general  autoregressive  (AR)
 process has the form (Box and Jenkins, 1 970):
 where, Zt is the observed process for year t, e,
 is a random shock that is not autocorrelated,
 and b. are  autoregressive coefficients of the
 AR(p) pro- process. Past work by Cook (1 985),
 and Monserud (1986) indicate that the best AR
 models generally fall in the AR(I)-AR(3) classes.

     The consequence of autocorrelation is that
 the effect will be to degrade the signal to noise
 ratio. Thus, before estimating the climatic model,
 it is best to remove this component. The indices
 can be modelled and prewhitened as explained
 above.

              Pollution Signal

     Assume an enlightened estimation of the
 linear aggregate model (1 ). Suppose, however,
 a modification is made such that X.D2, is not es-
 timated,  but, instead, is now part of Et, that is,
 R, = A, + C, +  A.DI, + E(. If Et does, in fact, contain
 an exogenous disturbance effect that is spa-
 tially correlated on  a large scale, hypotheses
 can be constructed to test for spatial correlation
 with a gradient in pollutant deposition.  If the
 impact of pollution on radial growth  is suffi-
 ciently strong, it should be possible to detect the
 signal after  accounting for the influence of cli-
 mate through the estimation of Ct.  It is neces-
 sary that there is enough spatial coverage in
 2-d (latitude and longitude) or 3-d (plus eleva-
tion) space,  such that a range of ambient depo-
sition rates and tree-ring indices are available to
develop a spatial response model between the
pollution signal within E, and the spatially corre-
lated deposition variable.

              Spatial Analysis

     First, it must be demonstrated that enough
pollutant deposition information exists in time
and space to produce a reliable spatial model in
at least 2-d space over a period of years.  This
time-space replication  is necessary so that a
clear picture of areas with high, moderate and
low levels of deposition become evident. Sec-
ondly, there must also  be enough geographic
coverage of tree-ring chronologies.  Given this,
the problem of how to  model spatial variation
can proceed.

     The use of regionalized variables (geosta-
tistics) is a reasonable  first step to investigate
spatial variation and covariation.  Those unfa-
miliar with regionalized variables can reference
Journel and Huijbregts (1978). Geostatistical
theory is  based on the observation that  the
variabilities of all regionalized variables have a
particular structure.  For this particular problem,
the interest is in quantifying the spatial correla-
tion that exists for a particular  pollutant. That
can  be accomplished as follows:  Consider
observations of a pollutant of interest,and refer
to these observations  as  z. The relation  be-
tween pairs of points h intervals apart (distance
of h between adjacent monitoring stations), can
be expressed  as the differences between all
such pairs. The per-observation  variance be-
tween  pairs (Yates, 1948) is half this value:
y(h) = 1/2 var[z, - zi+h], where -y(h) is known as the
semivariance,  and is a  measure of the similar-
ity, on average, between  points a given dis-
tance, h, apart. The more alike the points, the
smaller-y(h) is.

     The  semivariance  has  characteristics
which reveal the nature of the geographic vari-
ation in the variable of interest. In most instances,
•y(h) increases with increasing h to a maximum,
                                                                                       45

-------
Gregory A. Reams
                          (a)
                     (b)
                         a           h                            2/3  a     ah

Figure 1. Theoretical semivariograms for (a) a linear model and (b) spherical model, illustrating the range, a, the sill
        co+c, and the nugget variance c0. The tangent to the curve at h+O in (b) meets the horizontal for the total
        variance at 2/3 a.
which is approxi mately the variance of the data.
This maximum usually will occur at a moderate
value of h, say "a" (Figure 1).  The distance "a"
is known as the range. If y(h) approaches the
maximum asymptotically  then "a" may be cho-
sen where y(h) becomes sufficiently close to the
total variance. Points closer together than the
range are spatially dependent; points further
away have no relation to one another, unless
periodic variation exists.

     By definition, y(h)=0 when h=0. However,
any  smooth function that  approximates the
semivariance is  unlikely  to pass  through the
origin.  Instead, a positive finite value for y(h) is
present as h approaches 0. This intercept is the
nugget variance, "co" and is a measure of fluc-
tuations over distances shorter than the sam-
pling interval, and limits the precision of predic-
tion.

     The value at which y(h) levels out is known
as the sill. It consists of the nugget variance plus
a component "c" that represents the range of
variance due to spatial dependence.
     There is no general formulate describe the
shape of semivariograms; a linear model y(h)=
co + mh is the simplest, and often can describe
y(h) within the range, (i.e. h=0 to h=a). Various
nonlinear models can be used, and a spherical
model proposed by Matheron (1963) is often
applicable:
y(h) = cn + c{3/2(h/a) - 1/2(h/a)3} for 0 < h < a
y(h) = c0 + cforh>a
     With the background information above,
an investigation into the possible spatial covari-
ation of tree-ring indices and pollutant deposi-
tion can proceed.

               An Example

     Monitoring of atmospheric deposition in
Pennsylvania indicates that precipitation here
can be characterized as a dilute aqueous solu-
tion of sulfuric and nitric acids.  This precipita-
tion generally produces a west (high deposition)
to east (low deposition) gradient of H+ across
the state (Lynch and Corbett, 1983). The pat-
tern  of SO4 deposition  is less distinct, but evi-
dent. Air quality monitoring has shown a similar
 46

-------
                                                            Dendrochronology and Spatial Analyses
deposition pattern from 1982-85. This indicates
that the same areas have perennially received
higher deposition rates than others;thus, if nec-
essary, we can likely  collapse over years as
long as local emission sources and long-range
transport are relatively stable.

     Presently, there are 16 atmospheric moni-
toring stations in Pennsylvania where data are
available. Additional NADP sites are available
from surrounding states. Precipitation amount
(cm), concentrations (mg/1)  of H+,  SO4,  NO3
and annual deposition (g/m2) of the same ions
are measured at each station. Tree-ring data
are available at 200  forest survey  plots that
meet the criteria of 1) having two prior measure-
ment occasions, 2) being free from disturbance
throughout their history, and 3) being classified
as either  oak-hickory  or northern hardwoods
forest types.  The forest plots were systemati-
cally selected to assure good spatial distribution
for the western and central portions of the state.

     The  covariance  analysis  of the atmo-
spheric deposition and concentration data with
the tree-ring data should investigate both spa-
tial and intervariable correlation.  This can be
done through co-kriging where  the  data from
one or more auxiliary variables (i.e. deposition
or concentration of pollutants) is used to esti-
mate the  response variable  (i.e.  tree-ring in-
dex).

     Suppose now that an analysis  to investi-
gate the spatial covariation of tree-ring indices
and SO4 is proposed.  Specifically, the term E,
from the linear aggregate model that hopefully
contains an exogenous pollution signal will be
correlated with  SO4. The test of spatial covari-
ation is provided by computing the cross sem-
ivariogram.  The cross semivariogram can be
estimated by:
                  N(h)
     Y12(h) =
where N(h) is the number of pairs  of values
{[z,(x), z,(x+h)], [z2(x), z2(x+h)]} separated by a
distance h.

     Estimation of a particular variable for an
unsampled location is done as follows.  Con-
sider an estimate of variable z2 is needed. This
can be done by using the co-kriging equation,
where, X^ and X2  are the weights associated
with Z, and Z2, and N, and N2 are the number of
neighbors of Z, and Z2 involved in the estimation
of the unsampled location xo.  As  the  actual
mathematics are beyond the scope of this paper,
those unfamiliar with co-kriging and cross semi-
variogram estimation are directed to the follow-
ing references (Vauclin etal., 1983; Journel and
Huijbregts, 1978).

     An extension to other pollutant variables
can proceed as above, and  there is also the
possibility of combining multivariate techniques
with co-kriging.

              Literature Cited

Boden.T.A.  1987. United States historical climatology
    network (HCN) serial temperature and precipitation
    data. Carbon Dioxide Information Analysis Center,
    Oak Ridge National Laboratory, Oak Ridge, Tennes-
    see.

Box, G.E.P. and G.Jenkins. 1970. Time series analyses:
    forecasting and control.  San Francisco. Holden-
    Day. 553 pp.

Cook,  E.R. 1985.  A  time series approach to tree-ring
    standardization. Ph.D. dissertation. The University
    of Arizona, Tucson.

Cook,  E.R. 1985.  The use and limitations of dendro-
    chronology in studying effects of air pollution on
    forests.  In Proceedings of NATO Advanced Re-
    search Workshop: Effects of Acidic Deposition on
    Forests, Wetlands, and Agricultural Ecosystems.
    Toronto, Canada.
                                                                                         47

-------
Gregory A. Reams
Cook, E.R.  1987.  The decomposition of tree-ring
series  for  environmental  studies.    Tree-Ring
Bulletin  47:37-59.

Cook, E.R. 1988. Atree ring analysis of red spruce in the
   southern Appalachian mountains. P.C. Van Deusen,
   (ed).  In Analyses  of Great Smoky Mountain Red
   Spruce Tree Ring  Data.  Gen. Tech. Rep. 50-69.
   New Orleans, LA: USDA-FS, Southern For. Exp. Sta.
   67 p.

Fritts, H.C., J.E. Mosimann, and C.P. Bottorff. 1969. A
   revised computer program for standardizing tree-
   ring series.  Tree-Ring Bulletin 29:15-20.

Fritts, H.C..T.J. Biasing, B.P. Hayden, and J.E. Kutzbach.
   1971.   Multivariate techniques for specifying tree
   growth and climate relationships and for reconstruct-
   ing anomalies in paleoclimate. Journal of Applied
   Meteorology10:845-864.

Fritts, H.C.  1976. Tree Rings and Climate. Academic
   Press. London.

Guiot, J. 1985. The extrapolation of recent climatologi-
   cal series with spectral canonical regression.  Jour-
   nal of Climatology 5:325-335.

Journel, A.G.,  and Ch. J. Huijbregts.  1978. Mining
   Geostatistics. Academic Press. New York.

Lynch, J.A., and  E.S. Corbett.  1983.  Atmospheric
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    approaches in  the consideration of more reliable
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    Systems Analysis/Polish Academy of Science-Sys-
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    1983.  The use of co-kriging with limited field soil
    observations. Soil Sci. Soc. Am. J. 47:175-184.

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    241:345-377.
  48

-------
 100-Year Records of Forest Productivity at High  Elevations
                      in Western Washington, USA
                                  Linda B. Brubaker
                                College of Forest Resources
                                  University of Washington
                              Seattle, Washington 98195, U.S.A.

                                  Lisa J. Graumlich
                          Department of Ecology and Behavioral Biology
                                  University of Minnesota
                             Minneapolis, Minnesota 55455, U.S.A.
               Introduction

     Recent variations in forest productivity are
a major interest in North America and Europe as
concern grows over reports of forest declines
due to acid rain and atmospheric deposition
(Johnson and Siccama, 1983,1984; Krause et
al., 1983; Morrison, 1984; Prinz era/., 1983).
The accurate assessment of production losses
from these factors requires a knowledge of the
productivity of forest stands in the absence of
air pollution and the natural variability of produc-
tion over time.   Unfortunately, estimates of
forest production  require intensive research
projects (Grier and Logan, 1977; Sprugel, 1984;
Cooper, 1981)  and, as a  consequence, the
productivity of many forest types in these re-
gions are not well known.

     Net primary productivity (annual produc-
tion of biomass per unit area) has been studied
more intensely  in  conifer forests than in any
other forest type (Sprugel, 1985).   Empirical
studies of several different species in different
climatic and geologic settings have documented
productivity changes following major stand
disturbances (Grier and Logan, 1977;Tadaki et
al., 1977; Yarie and Van Cleve, 1983; Sprugel,
1984). Although the absolute rates of change
differ  among forest  types depending on the
lifespans of the species  involved, all studies
show  generally similar trends  during stand
development and aging.  These trends are
summarized  below as described by Sprugel
(1985).

    Annual productivity decreases immediately
after disturbance, but increases rapidly as new
trees  become  established on  the site.  The
largest component of production during early
stages of stand development comes from the
production of leaf biomass.  Following crown
closure, leaf production stabilizes and the rela-
tive contribution  of woody tissue increases.
Total  stand productivity  stabilizes  in mature
stands, but generally decreases as stands reach
old age. Production declines in old stands are
presumably due to increased stand respiration
related to the  increasing biomass of  woody
tissue, or to a decrease in nutrient availability.
                                                                                   49

-------
Linda B. Brubaker and Lisa J. Graumlich
     The objective of our study was to assess
the natural variability of net primary production
of old-growth conifer stands on upper slopes of
the Cascade Mountains, Washington. We were
particularly interested in the effect of annual
variations in climate on the forest production, as
prior work (Grier  and Running, 1977; Gholz,
1979) suggests that these forests should be
susceptible to annual variations in temperature.
Our study also provides baseline information
for assessing present and future pollution ef-
fects in these mountains.

               Study Area

                 Geology

     The Cascade Range, WA, is a north-south
trending mountain chain with maximum eleva-
tions typically reaching 2000 to 3000 m.  Sev-
eral  volcanic cones rise more  than 1000 m
above the  major peaks of these mountains
(Highsmith, 1973). This range was covered by
extensive alpine glaciers during the most recent
glaciation (Porter, 1984).  Soils are generally
thin  and developed  in glacial till capped  by
numerous tephra layers originating from nearby
volcanoes (Franklin and Dyrness, 1973).

                 Climate

     Westerly air from the Pacific Ocean domi-
nates the western slopes of the Cascades dur-
ing all seasons of the year (Highsmith, 1973).
Orographic lifting of moist air results in high pre-
cipitation in the mountains, particularly as snow
in the winter.  Annual snowfall is commonly
more than 1500 cm at upper elevations (1500-
2000 m)  in these  mountains.  Snow often re-
mains on the ground at upper elevations until
early July.  Precipitation is strongly seasonal,
however, with only 20 percent of the average
annual precipitation occurring during the grow-
ing season.

     The proximity of the Pacific Ocean has a
mitigating effect on seasonal temperature fluc-
tuations in the western Cascades.  At upper
elevations in these mountains, minimum Janu-
ary temperatures are  approximately -10 to
-15°C and average maximum July tempera-
tures are generally +15°C.

     A recent dendroclimatic reconstruction for
the west  Cascade  Mountains shows a  1°C
increase in mean annual temperature between
the mid-19th and 20th  centuries (Graumlich
and Brubaker, 1986). This warming trend has
caused a  rapid  recession  of alpine glaciers
(Burbank,  1981) and recent increase in tree
establishment at treeline (Franklin etal., 1971)
in these mountains.

                  Forests

     Three major forest zones  (Franklin and
Dyrness, 1973) cover the western slopes of the
Cascade Mountains. The Tsuga heterophylla
zone extends from  lowland areas to approxi-
mately 700 m. Old-growth: forests in this zone
are dominated by  Pseudotsuga  menziensii
(Douglas-fir) and/or Tsuga heterophylla (west-
ern hemlock), with lesser importance of Thuja
plicata (western red  cedar).  These species are
generally long-lived (600-1000 years) and reach
massive sizes  (3 m in diameter,  100 m in
height).  Stands within  this zone have shown
some of the highest biomass and annual pro-
duction rates recorded for coniferous forests in
the world (Lassoie etal., 1985).

     The Abies amabilis zone, extending from
approximately 700  to 1500 meters, is domi-
nated almost exclusively by Abies amabilis
(Pacific silver fir). Trees in this zone are smaller
than those of the Tsuga heterophylla zone and
net primary productivity is generally two-thirds
that of the Tsuga heterophylla zone (Lassoie et
al., 1985).   The lower productivity of Abies
amabilis forests is thought  to result from the
detrimental effects of shorter and cooler grow-
ing seasons on rates of net photosynthesis and
nutrient release by decomposition and minerali-
zation at high elevations (Lassoie etal., 1985).
 50

-------
                     100-Year Records of Forest Productivity at High Elevations in Western Washington, USA
     The Tsuga mertensiana zone  (1000 to
 1500 m) is the highest forest zone of the west-
 ern  Cascade Mountains.   These forests  are
 dominated by  Tsuga mertensiana (mountain
 hemlock) with varying  proportions  of  Abies
 amabilis, Chamaecyparis nootkatensis (Alaska
 yellow cedar) and Abies lasiocarpa (subalpine
 fir).   Old trees  (600-1000 yrs) are  relatively
 common; however, tree sizes are generally
 small compared to those of lower forest zones.
 The productivity of these forests has  not been
 previously studied, but is considered to be less
 than that of lower forest zones.

                 Methods

               Field Sampling

     The following criteria were used to select
 plots for sampling:  I) tree ages of at least 300
 years, 2) no evidence of tree mortality within the
 plot and within 10 meters of the plot perimeter,
 and 3) no evidence of unusual crown damage to
 trees within the plot.  In each plot, increment
 cores were collected  at 1.4 m height from all
 trees greater than  15 cm  in diameter.   The
 diameters of all sample trees were measured at
 1.4 m height. The  locations of the plots ana-
 lyzed in this study are shown in Figure 1.
Figure 1:  Locations of sites analyzed for net primary
         production and the Seattle climatic station.
         The dashed line represents the crest of the
         Cascade Mountain Range.
             Laboratory analysis

     All  cores were  mounted  in permanent
 holders,  sanded to a high polish and cross-
 dated with other cores from the plot and with
 existing tree-ring chronologies  from the west
 Cascade Mountains (Brubaker,  1980; Graum-
 lich and Brubaker, 1986). Annual ring widths
 were measured to the nearest 0.01 mm using a
 Bannister incremental measuring machine.

     Estimation of Net Primary Production

     Net primary production (NPP) is defined
 as the excess of annual gross photosynthesis
 over respiration (Odum, 1969).  In practice,
 gross photosynthesis and respiration are diffi-
 cult to measure in field situations and few stud-
 ies have attempted to quantify these processes
 in forest stands (Assman, 1970; Sprugel, 1984).
 More commonly, NPP is estimated by the equa-
 tion  (Grier and Logan, 1977; Fujimori  et a/.,
 1976):
              NPP = B + D + G
 where,
     B = annual increment of living biomass of
 trees, shrubs and herbaceous plants
     D = annual loss of living biomass of trees,
 shrubs and herbaceous plants due to  natural
 mortality
     G = annual loss of living biomass of trees,
 shrubs and herbaceous plants due to grazing.

     Several simplifying assumptions enabled
 us to use this equation to reconstruct NPP back
 in time. Biomass losses to grazing were consid-
 ered negligible because insect defoliation and
 grazing by mammals are unimportant in  mature
 stands of western Cascade forests (Grier and
 Logan, 1977).  Similarly, the contribution of un-
 derstory species and small trees (<15 cm di-
 ameter at 1.4 meters) to total primary produc-
tion of old stands is negligible (Grier and  Logan,
 1977).  Estimating NPP was thus reduced to de-
termining the biomass increment and mortality
of large trees.
                                                                                     51

-------
Linda B. Brubaker and Lisa J. Graumlich
     The major difficulty in assessing NPP by
this equation is in determining the dates of tree
mortality and sizes of such trees at the time of
their death. In order to avoid the uncertainties
of characterizing  tree mortality, we selected
plots free of signs of mortality (downed logs and
raised linear surfaces). The death of trees less
than 15-20 cm in diameter may  have gone
undetected, but trees of this size are unimpor-
tant in production budgets of old-growth forest
stands (Grier and Logan, 1977).

     We were thus able to estimate past NPP
solely by determining the past biomass incre-
ments  of trees alive at the time of sampling.
Biomass increments were calculated by sub-
tracting the estimates of total tree biomass of
the plots  between  successive years.   The
components of tree biomass (foliage, stem wood,
stem bark, and living and dead branches) for
each year were  calculated from standard re-
gression equations (Gholz etal., 1979) relating
stem diameters to tree biomass components.
These  equations are of the form:

            1nY = a + b1nX

     Tablcl.  Characteristics of sample plots.
where,
     Y = biomass of foliage, stem wood, stem
bark, or branches
     X = stem diameter
     a, b = regression coefficients

     We  used  species-specific  regression
coefficients  established in previous studies
(Gholz et a/., 1979), which had destructively
sampled trees of each species and compared
tree diameters to  weights of tree  biomass
components. The total plot biomass for each
year was calculated by summing the biomass
components across all trees in the plot, as
calculated from the diameters of trees in that
year.

   Comparisons of Productivity and Climate

     The variations  in NPP at the four sites
were summarized  by  principal components
analysis.  Factor scores of the  first principal
component,  representing the  most important
common variation in NPP among the  series,
were used as a record of variations in regional
forest productivity for comparisons with climatic
Forest Zone Tsuga
heterophylla
Site TR
Latitude 45°52'
Longitude 122°05'
Elevation (m) 1200
Plot size (ha) 0.032
No. Trees 27
Oldest Trees (yrs) 630
Abies
amabilis
TL
47°45'
121°15'
1400
0.046
20
510
Tsuga
mertensiana
RL
47°02'
121°50'
1440
0.051
14
370

JR
46°45'
121°56'
1460
0.026
24
560
      Percent of total biomass by species (1979) data:
      T. heterophylla    100               —
      A. amabilis        —                 52
      T. mertensiana    —                 48
      Chamaecyparis    —                 —
        nootkatensis
             27
             69
              4
 4
96
 52

-------
                     100-Year Records of Forest Productivity at High Elevations in Western Washington, USA
data. These scores were compared to climatic
data from Seattle, WA (47 39, 122 18) using
simple correlation and cross-spectral analyses.
Seattle is the closest station to the sampling
sites having a long meteorological record (1983-
1980).  Climatic data were summarized as av-
erage summer (June-September) temperatures
and water year totals (the sum of precipitation
from the preceding October through the Sep-
tember  of   the
growth year).           ,   **° 190°  19l° 192°
     Results

     The sampled
stands come from
each of the three
major forest zones
of the  west Cas-
cade  Mountains,
WA  (Table  1).
Stand ages, as in-
dicated by the age
of the oldest tree,
ranged from 370 to
630 years.
     Current
(1980) net primary
production ranged
from   approxi-
mately 5 to 10 met-
ric tons per hectare
per year. The rec-
ords  NPP  at  all
sites  shows strik-
ingly similar trends
(Fig. 2): 1) increasing
from  1880-1980,  2)
decreasing or remain-
ing  stable from 1910
to 1935, 3) increasing
from  1935  to 1960,
                    6-
                    2-
                                   "T
                                              the record was 60 percent. Correlations of NPP
                                              among sites are positive and highly significant,
                                              ranging from .46 to .83. The first principal com-
                                              ponent explains 81 percent of the variation in
                                              the data and represents the positive correlation
                                              of NPP among all sites.

                                                   The time series of factor scores for the first
                                              component represents the common variation in
                                                                       NPP  at  the four
                                           1930  1940 ,950  I960 1970 198O
                                                ~T
                        B

                          \     I
                         1890 1900
 I
191O
                                      1920
 i     i
193O 194O
  Year
                                                    195O 196O
 I
197O
                                                                 1980
                      Figure 2. Annual estimates of NPP for forest stands on
                              the upper slopes of the Cascade Range, Wash
                              ington. (A-D) NPP estimates for four individual
                              sites (see Table 1). (E) Factor scores obtained
                              from the principal component analysis of the
                              four series (A-D).
           In
   quent analyses, this
   series was consid-
   ered to be a record
   of  regional  NPP,
   which  represents
   diverse forest types
   in the west Cascade
   Mountains. The re-
   gional NPP record
   shows strong simi-
   larity  to summer
   temperature trends
   (r = .46). The corre-
   lation of NPP with
   precipitation,   al-
   though significant,
   is less strong  (r=
   .21).

         The purpose
   of the cross  spec-
   tral analysis was to
   identify those tem-
   poral  frequencies
   that  most closely
   associate NPP with
temperature and pre-
cipitation. The squared
coherency, analogous
to the  square of the
correlation coefficient
between two time se-
and 4) remaining relatively stable from 1960 to
1980. The average increase in NPP at each
sites between the first three decades (1880-
1909) and last three decades (1950-1979) of
                                              ries calculated atdifferent frequencies, revealed
                                              that NPP is associated with temperature over
                                              periods of 6 years and greater and with precipi-
                                              tation at periods of 3 years and less. In agree-
                                                                                      53

-------
 Linda B. Brubaker and Lisa J. Graumlich
 ment with the re-
 sults of the corre-
 lation   analyses,
 the association of
 NPP  with tem-
 perature  is much
 stronger than that
 of NPP with pre-
 cipitation.

   Discussion
   1200-1
   1000-
   800-
   600-
     20-,
0
o
                        15-
                        2-
                        0-
                       -2-
                                   Annual Precipitation
                                         1
                                                                1
                I
                              I
                I
                              r
     The  net  pri-
mary productivity
of stands sampled
in this study  are
similar to  values
reported   else-
where in the west
Cascades (Las-
soie etal., 1985).
Thus, the current
and,  by implica-
tion, past produc-
tivity of our stands
appears to be rep-
resentative of for-
ests in much of the western Cascade Moun-
tains.
                                                     Summer Temperature
T
T
T
                                                       NPP Factor Score
                          I
                             1900  1910 1920 1930 1940 1950 1960
                                               Year
                                            1970
                                                 1980
                           Figure 3. Annual precipitation and summer tempera-
                                   ture, Seattle, Washington, (1893-1979) and
                                   time series of NPP factor scores, as in Figure
                                   2E.
carbon  dioxide
have apparently
not  directly  af-
fected forest pro-
ductivity  in  this
region (Graumlich
et al., in review).
Likewise, no evi-
dence exists for a
production  de-
cline  due  to  air
pollution (Graum-
lich  et al., in  re-
view).

     Tempera-
ture  and precipi-
tation can  influ-
ence       NPP
through a variety
of   processes
(Lassoie  et al.,
1985). Precipita-
tion   variations
predominantly
affect short-term
processes  regu-
     The similarity of NPP trends at the four
sites is strong evidence that factors operating at
a regional scale are important in determining
the productivity of forests in these mountains.
Although local disturbances and processes of
stand dynamics may be important determinants
of productivity in  individual stands, these fac-
tors cannot explain the consistent productivity
trends that we have observed in stands of differ-
ent ages, species, and  geographic locations.
The significant statistical association of regional
NPP records with temperature and precipitation
records suggests that recent climatic variations,
particularly variations in  summer temperature,
have been important factors controlling the pro-
ductivity of western Cascade forests over the
past century.  Variations in global atmospheric
                            lating tree water balance, such as stomatal re-
                            sponses to xylem pressure potential and vapor
                            pressure deficits.  The effects of temperature
                            are more complex, including short-term influ-
                            ences on photosynthesis, cell division, and wa-
                            ter and nutrient uptake, as well as longer-term
                            controls over leaf production, allocation of car-
                            bon to above- and below-ground parts, and
                            rates of decomposition and mineralization. Dif-
                            ferences in the way temperature and precipita-
                            tion affect production-limiting processes may
                            be responsible for the differences in the time
                            scales over which NPP is correlated with these
                            factors.

                                Our results also have implications for other
                            studies of forest productivity in this region, and
                            possibly in other regions where productivity re-
                            sponds  strongly to temperature  variations.
                            Because the strongest  relationship between
 54

-------
                       100-Year Records of Forest Productivity at High Elevations in Western Washington, USA
temperature and productivity is over long time
periods  (greater  than  6  years),  short-term
measurements of temperature and productivity
may not adequately specify the nature of the
relationship between these variables.  In addi-
tion, since NPP at each site varies substantially
over short time periods, conventional practices
of estimating NPP based on 1 -to-5 year records
of biomass increment may not accurately reflect
long-term forest production  rates.

                 Conclusions

     The natural variability of  productivity of
upper elevation Cascade Mountain sites is great
and controlled primarily by variations in summer
temperature.  NPP increased  by 60  percent
over the period 1880-1979. Thus, prior to 1980
these forests showed no evidence of a substan-
tial decline in  productivity that  could be attrib-
uted to atmospheric pollution.

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    tivity of white spruce stands in interior Alaska. Cana-
    dian Journal of Forest Research 13:767-772.
  56

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 Selecting Analysis Procedures For Exogenous Disturbance
                              Tree-Ring Studies

                                By Michael J. Arbaugh
                      Pacific Southwest Forest and Range Experiment Station
                        USDA Forest Service, Riverside, California, U.S.A.
                 Abstract

     Analysis procedures used in dendroecol-
ogical  studies are commonly selected from
techniques developed  for  dendroecological
analysis. These techniques, however, are usu-
ally limited by factors such as software availabil-
ity and prior usage. Furthermore, the relation-
ship between the objectives of dendroecologi-
cal study and the analysis technique is often
poorly defined. Conclusions from study objec-
tives, data characteristics, and exogenous dis-
turbance expression indicate that detecting and
characterizing nonstationary behavior  is the
most important ability of the analysis procedure
for dendroecological studies.  Analysis tech-
niques using constant parameter models do not
have this ability. Recursive least squares tech-
niques are promising, but will need further de-
velopment.

               Introduction

     Acid deposition, ozone damage, and car-
bon  dioxide increases  have focused  forest
condition questions on the estimation of growth
changes through time, and over regions. The
data needed to address these questions often
must start 50 to 100 years prior to the time of the
study.
     Traditionally, fixed  plot  measurements
have been used to assess forest condition.
These data, however, are rarely of sufficient
length, or are available only for local areas. The
data sets often are small and contain unknown
measurement resolution.

     Tree-ring series represent an alternative.
Tree cores carefully collected provide inexpen-
sive, highly accurate information on the forest
condition.  They are inexpensive to collect and
process.  As many as 1500 cores can be col-
lected, read, and cross-dated in a single year by
small research groups. Core reading and cross-
dating systems are computerized for consis-
tency and accuracy.

     The consistency of data gathering and
processing is offset by the confusion and dis-
agreement on analytical techniques useful for
this data.  Historically, analysis techniques for
tree-ring data have been developed to isolate
signals, or patterns of  tree-ring growth that
reflect information pertaining to environmental
disturbances, rather than forest condition. At-
tempts have been made to adapt these tech-
niques to forest condition  questions, but the
results have been questionable. Most of these
analysis procedures examine  only  the short-
term variability (residuals determined by sub-
                                                                                   57

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Michael J. Arbaugh
tracting or dividing the observed  ring width
values by  smoothed  values)  of  the  series.
Growth changes expressed in the smoothed
trend portion of the tree-ring series are often ne-
glected.

     Some researchers have  proposed new
techniques in favor of the traditional techniques
(Vissar and Molenar, 1986; Van Deusen, 1986;
Peterson and  Arbaugh, 1988).  These new
techniques relax the assumption of constant
parameters for the model, which allows evolv-
ing systems to  be modeled. The techniques
have been used in a few studies, but mostly as
a  slight modification of dendrochronological
techniques (Vissar  and Molenar,  1986; Van
Deusen, 1986).  The analysis techniques are
also complicated to use and interpret.

     The lack of a clear connection between
statistical  attributes of the analysis process
chosen and the study objectives is a major
problem for this field.   Often, the relationship
between the analysis technique and the study
objective is either missing, or only haphazardly
addressed in studies.  Techniques commonly
selected are due to availability of software, or
prior usage. Consequently, conclusions from
these studies may be incomplete, dependent
on unstated assumptions, or applied to regions
not adequately defined or sampled.

     This  discussion will attempt to motivate
some desirable traits of analytical techniques
based on the study objectives, analytical char-
acteristics, and the expression of disturbances
in tree-ring series. Statistical aspects of tree-
ring series and  disturbance expression will be
examined.   The  general types of  analytical
procedures presently used in dendroecological
studies will be discussed with reference to the
conclusions obtained.

    Study Objectives in Dendroecology

     Individual tree-ring series contributes in-
formation on the onset and extent of individual
tree growth changes through time. Patterns of
ring-width increase, decrease and growth inter-
ruptions are recorded in these series.  Localized
factors, site specific factors and regional distur-
bances may cause observed short-  and long-
term changes in growth.

     Groups of tree-ring series contribute infor-
mation on changes in tree growth for sites and
regions.   The  observation of synchronous
changes in many series from an area, not ob-
served in past portions of the series or in groups
of series from other areas, can be used to infer
regional  environmental  disturbances on tree
growth.

     The region, or population, that the sample
trees represent are dependent upon the sam-
pling strategy used.  Sample trees growing
without competition in exposed locations can
only yield information about trees growing in
exposed locations. Meaningful extrapolation of
the results to a more general forest population
may not be possible. Similarly, sampling inte-
rior forest trees will yield information on the
majority of trees in the region of interest, but not
the trees most likely to be affected by the distur-
bance.

     The growth changes of interest are de-
fined by the objectives of the study. Changes in
short-term variability have been the focus of the
dendrochronological studies. Associations with
climatic changes or exogenous event times
often are the primary  goals. Studies seek to
characterize the event or pattern of events by its
expression in tree-ring series.

     Studies concerned with assessing forest
condition have different goals. In these studies,
tree-rings are used as growth indicators to
assess regional trends and changes in forest
growth.  Characterizing stand  condition, as-
sessing the effect of known disturbances, and
evaluating  the impact of growth changes on
stand composition for sites and regions are the
primary study objectives.
 58

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                              Selecting Analysis Procedure For Exogenous Disturbance Tree-Ring Studies
    Characteristics of Tree-Ring Series

     Characteristics of the data being analyzed
are important for selecting an analytical tech-
nique.  Tree-ring series are particularly difficult
in this way.  Each series is an equally spaced
discrete time series. They are nonperiodic and
nonstationary through time. The first moment of
the distribution function of the observations
may be nonstationary, the mean growth chang-
ing through time, or the second central moment
may change through time indicating the pres-
ence of heteroscadasticity in the data, or both
moments  may vary through time.   For most
analysis purposes, these two central moments
are the most important. Series with stationary
first and second moments are said to be weakly
stationary.

     The nonstationarity may arise from a vari-
ety of  causes.  Natural disturbances  in the
environment, gradual biological aging processes
and management practices may all be contrib-
uting factors. An additional nonstationarity, due
to taking linear measurements on a concentri-
cally increasing system, is present if growth is
expressed as tree-ring widths.

     To simplify the discussion, tree-ring series
are assumed to be composed of two compo-
nents,  the long-term trend and the  short-term
variability.  Long-term trend is defined as the
smoothed estimates of ring-area values through
time.   It can  roughly  be  thought  of as the
nonstationarity of the first moment of the distri-
bution function of the observations. Short-term
variability  is defined as the residuals formed
from differencing  (or dividing) the  smoothed
and actual ring-area estimates.  They form a
process with a stationary first moment. Nonsta-
tionarities in these series are expressed as
heteroscadasticity.

         Disturbance Expression

     A disturbance, endogenous or exogenous,
affecting tree growth can be expressed in indi-
vidual tree-ring series in several ways. It may
cause a gradual or abrupt change in long-term
trends without a corresponding change in the
short-term variability. It may cause a change in
the short-term variability either relative to envi-
ronmental factors, or to previous growth without
a change in the trend. Combinations trend and
short-term variability may also occur.  Fluctua-
tions in both the trends and short-term variabil-
ity are common in tree-ring series.

     The particular disturbance expression, or
disturbance onset, may be modified for individ-
ual trees by interacting influences unique to the
tree or site locality.  Microclimate, soil charac-
teristics, genetics, or topography may influence
individual or site expression of the disturbance.

     It is believed that concentric growth is not
a stationary process for some species (D. L.
Peterson, personal communication).  Rather,
growth rapidly increases, then becomes sta-
tionary or slightly decreasing for a longer pe-
riod, then decreases more rapidly as the tree
ages. It is unknown if short-term variability in
concentric growth also varies with time.

     Trend changes, both abrupt and gradual,
were observed with little evidence of change in
short-term  variability  in forest  interior trees
sampled in the Sierra Nevada (Peterson and
Arbaugh, 1988).   Changes in short-term vari-
ability were observed when little change in the
trend was present.  Synchronous changes of
the trend and short-term variability were often
observed.

    Selecting Analytical Methodologies

     A tree-ring series is a  process  evolving
through time. Disturbances are expressed as
changes, abrupt or gradual, in this process.
The  ability to characterize the  nonstationary
aspects of the series, thus, becomes an impor-
tant  characteristic of an  adequate  analysis
procedure. Detecting the time, and the extent of
change in both long-term trends and short-term
                                                                                      59

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Michael J. Arbaugh
variability are the primary objectives of the
analysis. Without this information, the associa-
tion of tree-ring patterns with exogenous distur-
bances is not possible.

     If time is available, all types of nonstation-
ary behavior could be examined. This would
ensure the  detection of disturbance  effects
expressed in the series that, while not obviously
causing a long-term growth decline, could be
altering the composition of the forest affected.
The analysis might be accomplished using a
single  technique, or by  utilizing several  tech-
niques, each for a different aspect of the  data.

     This would be an exhaustive process, and
might be impractical for large studies. At  pres-
ent, prioritization of the importance of the non-
stationarities may be necessary. Little informa-
tion is available pertaining to the pattern of
exogenous disturbance expression in  individ-
ual series, nor is information available  indicat-
ing the uniqueness of such signals.  If  such
information were available, it might considera-
bly shorten the  analysis process.

     Obviously, techniques which a priori as-
sume  that  parameters  are constant through
time will not be effective for this type of analysis,
since nonstationary changes in the series  could
not be  isolated.  Unfortunately, this includes the
majority of techniques developed for dendro-
chronological analysis. These analytical  tech-
niques consist  of ordinary least squares mul-
tiple regression, principal components  regres-
sion, ARIMA, or a mixture of techniques.  All
these techniques assume that the time series is
weakly stationary, which precludes estimating
nonstationaries in even the short-term variabil-
ity.

     Alternate techniques such as intervention
detection and analysis (Box and Jenkins, 1976),
and switching regressions (Goldfeld and Quandt,
1973)  can be used to compensate for these
deficiencies when simple nonstationary trends
are present. They are not capable of modeling
all types of nonstationary trends, or heterosca-
dasticity in short-term variability (without intro-
ducing arbitrary power transformations).

     More recently, the Kalman filter (Kalman,
1960; Kalman and Bucy, 1961) analysis tech-
nique  was  introduced  to  dendrochronology
(Visser and Molenar, 1986; Van Deusen, 1986).
This general class of techniques assumes that
model parameters evolve through time accord-
ing to a function of past parameter values. The
simplest form of this transition function, the
random walk, is presently utilized in most analy-
sis.

     Because the parameters are allowed to
vary with time, this class of model is able to track
changes in trends, and in short-term variability.
Both linear regression models and ARMA model
formulations can be  constructed for use with
this technique. Recursive least squares is also
easily extrapolated to the multivariate case.

     Although this class of techniques is prom-
ising, several general problems exist. Prior to
using the model, several parameters and vari-
ances  must  be estimated.  There is little con-
sensus on how this is best done. The form of the
parametertransition equation must be selected.
The simpler forms are easily estimated; how-
ever, they restrict the rate of parameter change
more than may be desired.

     Statistical inference procedures are largely
undeveloped forthe Kalman filter. This reduces
study conclusions to the interpretation  of pa-
rameter values or confidence intervals  based
on expert knowledge of the system rather than
distributional results.

     Recursive least squares procedures are
also more complex, less available in standard
analysis packages, and more difficult to inter-
pret than the stationary models. Only one study
has applied this to the trend portion of the series
(Peterson and Arbaugh, 1988). Additional stud-
ies using this technique by other researchers
 60

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                                Selecting Analysis Procedure For Exogenous Disturbance Tree-Ring Studies
are needed before its strengths and limitations
will be completely known.

     Recursive  least squares  is a promising
technique.  The difficulties in application and
interpretation can be addressed with further
research.  However, additional analysis tech-
niques need to  be developed as alternatives.
Reliance on a single technique could restrict the
types of information that can be obtained from
tree-ring series. Future  techniques might in-
clude process oriented models, different statis-
tical analysis procedures, or even an  expert
system approach.

     New conceptual approaches to analysis
might also be possible.  One such  approach
might be to consider both the long- and short-
term variability  as a single pattern of growth.
Patterns associated with exogenous influences
could then be identified by control studies, or
sensitive series, and used to identify patterns of
interest in  interior forest trees.  This could re-
duce the analysis time and the uncertainty of
results.

     In summary, the primary analysis goal is
the detection of nonstationary behavior in the
tree-ring series  when detection of the expres-
sion of cumulative exogenous disturbances in
tree-ring series  is the study objective. This will
consist of examining the  long-term trends and
short-term variability for  points or patterns of
change.   Techniques developed for dendro-
chronological analysis are generally not ade-
quate, since they examine short-term variability
exclusively, and assume parameter to be con-
stant.  Recursive least squares techniques are
promising, but will need more refinement before
being widely applicable. Techniques other than
recursive least squares might be developed to
give a  more balanced approach  to  analysis
efforts in the future.

              Literature Cited

Box, G. E.  P., and G. M. Jenkins. 1976. Time series
    analysis:  forecasting and control. Holden-day Inc.,
    San Francisco, CA.

GoldfeldS. M.,andR. E. Quandt.  1973. The estimation
    of structural shifts by switching regressions. Ann. of
    Econ. andSoc. Meas., 2:475-485.

Kalman, R. E. 1960. A new approach to linear filtering
       and prediction problems. Trans. ASMEJ. Basic
       Engrg. (ser. D) 82:35-45.

Kalman, R. E., and R. S. Bucy. 1961.  New results in
    linear filtering and prediction problems. Trans. ASME
    J. Basic Engrg. (Ser. D) 82:35-45.

Peterson, D.L., and M. A. Arbaugh. 1988.  Growth trends
    in the mixed conifer forest of the Sierra Nevada: A
    final report.  Report to Western Conifers Research
    Cooperative, EPA, Corvallis, OR.

Van Deusen,  P  C.  1986.  Some applications of the
    Kalman filter to tree-ring analysis. In: Proc. Interna-
    tional Symposium on Ecological Aspects of Tree-
    Ring Analysis. Lamont-Dohert Geological Observa-
    tory, Columbia Univ., Palisades, NY.

Visser,  H.,  and J. Molenaar.  1986. Time dependent
    responses of trees to weather variations: an applica-
    tion of the Kalman filter.  N. V. Tot Keuring Van El-
    ektrotechnische Materialen, Research and Develop-
    ment Division, Arnhem, The Netherlands.
                                                                                            61

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                Session
                II
Mechanisms and Alternative Hypotheses
                          ; Ann Bartuska, Local Organizer

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                                     Introduction
      While research on air pollution effects on
plants has been conducted in the United States
for 2 decades, it has only been in the last 5 years
that a  coordinated National  effort has been
pursued.  A principal focus of this effort has
been   understanding  the  mechanisms of
response at the whole plant, organ and cellular
levels.   Studies of mechanisms of response
have been an area of research in the Soviet
Union for many years.  Accordingly, the theme
of the Raleigh session was "Mechanisms and
Alternative Hypotheses" with  a subtheme of
"Linkages: SeedlingsvsTrees vs Ecosystems."
      Each day of the 2-day session began
with a series of formal presentations, followed
by workshop-format discussions developed from
the formal presentations.  Presentations from
both countries were very complementary, cov-
ering the  entire  range of mechanisms from
ultrastructural changes due to SO,,, to forest
structural changes as a result of ambient envi-
ronmental conditions. In total, 14 presentations
and 20 scientific  posters greatly stimulated
discussions regarding the differences in  the
pollutant environment and the similarity in af-
fected processes between the two countries.
                                                                   Ann Bartuska
 64

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   Air Pollutants, Plants, and Mechanisms of Interaction: A

                           Historical Perspective*

                                    Ellis B. Cowling
                                College of Forest Resources
                                         and
                        Natural Resources, North Carolina State University
                             Raleigh, North Carolina 27695, U.S.A.

                                    Walter W. Heck
                    U.S. Department of Agriculture, Agriculture Research Service
                                North Carolina State University
                             Raleigh, North Carolina 27695, U.S.A.
     This paper was designed to provide a brief
historical perspective on scientific research on
the interactions  between  airborne pollutant
chemicals and both crop and forest plant spe-
cies. The two of us have been engaged in air
pollution  research in the United States for a
combined total of nearly 50 years. Based on
this experience, we have developed a few per-
spectives  which  we share with  other partici-
pants in this USA-USSR Workshop.  We hope
these ideas will be of some value in encourag-
ing a more complete understanding of the inter-
actions between  plants and airborne pollutant
chemicals in our two countries.

     Our paper is organized in three parts:

     A summary  of general trends in scientific
     understanding
     A list of major conclusions regarding ef-
     fects of air pollutants on crop and forest
     plant species in the United States
     A 'Literature Cited' list which contains some
     of the most valuable scientific reviews and
     original papers dealing with air pollution
     research in North America.

     General Trends in Scientific and
         Technical Understanding

     Scientific  understanding  of the interac-
tions between phytotoxic air pollutants and both
agricultural  crops and forest vegetation in Eu-
rope (including the Soviet Union) and the United
States has evolved mainly during the 20th
century. Eville Gorham (NRC, 1981) has given
an excellent summary of early  European and
North American developments in scientific
understanding of plant-atmosphere interactions.
Gorham's summary clearly shows that severe
air pollution problems were addressed in the
I9th century.
'Keynote paper presented by Dr. Cowling on September 19, 1988
                                                                                    65

-------
B//S B. Cowling and Walter W. Heck
    Crocker (1948) and Thomas (1951,1961)
have given similarly valuable accounts of stud-
ies of air pollution injury to vegetation near the
metal smelters at Selby, California; Copper Hill,
Tennessee; and Salt Lake  City,  Utah in the
United States and at Sudbury, Ontario in Can-
ada.  Katz (NRC of Canada, 1939)  has also
given a remarkably detailed account of the
observational and experimental investigations
during the most intensively studied  of these
early smelter release problems—the case  of
plant injuries  caused by sulfur dioxide emis-
sions from the smelter at Trail, British Columbia.
This latter case-study led to the formation of the
International Joint Commission which has helped
resolve transboundary air pollution  conflicts
between  Canada and the United States for
nearly 50 years.

     These early investigations were based
mainly on field surveys of direct injury to foliage
of both crop plants and natural vegetation. The
injuries were induced by toxic gases dispersed
in the immediate   vicinity  of strong  point
sources—mainly metal smelters.  Sulfur diox-
ide and later fluoride were the principal pollut-
ants of concern (NCR of Canada, 1939; Crocker,
1948; Thomas, 1951; Brandt and Heck, 1967;
NRC, 1981; Shupe, 1983). Although measure-
ments of air pollution concentrations were very
crude at first, both  pollutant-monitoring meth-
ods and  equipment for controlled exposures
with known concentrations of these toxic gases
became progressively more sophisticated dur-
ing the early decades of this century (NRC of
Canada, 1939; Crocker, 1948; Thomas, 1969).

     Controlled exposures with known concen-
trations of specific pollutants in  greenhouse
chambers were first used to quantify suspected
pollutant  dose/plant-response  relationships
(Crocker, 1948). Later, closed field chambers,
then open-top field chambers, both using char-
coal-filtered air as  a control, were used with
ambient air augmented with controlled addi-
tions of specific pollutants to quantify dose-
response relations.  Continuous  stirred tank
reactor (CSTR) chambers were developed for
studying physiological effects undergreenhouse
and controlled environment conditions (Heck et
a/., 1978). Pollutant-specific bioindicator plants
were also developed to augment field observa-
tions (Heck, 1966; Heck and Heagle, 1970).

     During the late 1940's and early 1950's,
photochemical oxidants, especially ozone and
later peroxyacetyl nitrate (PAN) were shown to
be highly toxic constituents of the smog for
which the Los Angeles area of southern Califor-
nia has become famous (Haagen-Smit, 1952;
Haagen-Smit, etal., 1953). These substances
were  soon discovered  to  be highly toxic  to
plants as well as humans. We now recognize
that ozone is one of the most common toxic
gases that affect plants in fields and forests in
many parts of the world (Middleton, 1961; NRC,
1977b;EPA, 1986).

     During the early 1950's, power plants were
shown to be sources of phytotoxic air pollutants
(especially sulfur dioxide), and they also con-
tributed  to the mix of  volatile organic com-
pounds and nitrogen oxides that lead to forma-
tion of ozone and other photochemical oxidants
(Brandt and Heck, 1967; NRC,  1977b; EPA,
1973).

     Gaseous nitrogen oxides have been shown
to cause foliar injury to  some crop plants and
forest trees in  controlled exposure  tests both
alone and in combination with other toxic gases.
But important  injuries at  ambient concentra-
tions have not been observed in either fields or
forests in North America (NRC, 1977c; EPA,
1982).

     At present, the airborne chemicals known
to affect  vegetation in the field include sulfur
dioxide, fluoride, ozone, PAN, chlorine, hydro-
gen sulfide, ammonia,  aniline, ethylene, and
aerosols  containing   herbicidal   chemicals
(Crocker, 1948; Brandt and Heck, 1967; Jacob-
son and Hill,  1970).  Much of  the available
information on the effects of these air pollutants
 66

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                             Air Pollutants, Plants, and Mechanisms of Interaction: A Historical Perspective
is summarized in the so-called Criteria Docu-
ments used by the Environmental Protection
Agency of the United States in establishing the
air  quality standards  for this  country (EPA,
1973,1982,1986). Table 1 contains a compos-
ite of the threshold doses (air concentration and
time of exposure) necessary to induce visible
injury by sulfur dioxide, nitrogen oxides, and
ozone. The data shown are for a variety of crop
plants that are sensitive, intermediate,  and tol-
erant of each of these major pollutants (EPA,
1973, 1982, 1986).

     During the  1970's and 1980's,  extensive
research on the phenomenon and  effects of
acid deposition has been done in North Amer-
ica. This research has included studies of the
emission,  transport, deposition, and biological
effects of  acidic substances including gases,
aerosols,  and acidic substances dissolved in
precipitation (Cowling, 1985). Cowling (1982)
has also prepared a summary of the historical
roots  of the acid  deposition issue in North
America and Europe. Effects on the chemistry
and biology of surface waters have been docu-
mented and both direct and indirect effects on a
wide variety of crop and forest plants have been
studied.  Present evidence suggests  that ef-
fects on agricultural crops and forest trees are
mediated mainly through interference with nu-
trient uptake processes or aluminum toxicity in
soils rather than by direct toxicity to foliar organs
(NAPAP, 1987).

     The physiological and biochemical mecha-
nisms by which air pollutants injure plants are
still poorly understood. Stomata on foliage and
stem  surfaces have been  shown  to  be the
principal avenue of entrance of gaseous pollut-
ants into plants  (NRC 1977a,  1977b, 1977c;
EPA 1973, 1982, 1986).  Differences  in sto-
matal behavior may account for an  important
part of the natural variation observed  in plant
resistance  or susceptibility to  most gaseous
pollutants.  Sulfur dioxide, fluoride, ozone, and
nitrogen oxides all appear  to be general
metabolic poisons that disrupt cell membranes
and  interfere with a wide array  of metabolic
processes in plants (NCR 1977a, 1977b, 1977c;
EPA 1972, 1982, 1986; Shupe etal., 1983).

     In the United States, recent studies of the
economic impact of air pollutants indicate that
injury by locally dispersed sulfur dioxide and
fluoride are now very rare and that regionally
dispersed ozone is the principal air pollutant of
concern  (Heck et a/., 1986).  Decreases in
emissionsof volatile organic compounds (VOCs)
from industrial and commercial sources are the
principal control strategy for ozone. Very recent
studies indicate that this policy is not adequate
in the southern United States.  Here, natural
emissions of VOCs from forest and crop plants
are so large that it probably will be necessary
also to  limit  emissions of nitrogen oxides if
ambient  concentrations  of  ozone  are to be
maintained below phytotoxic concentrations.

     In the Soviet Union, locally dispersed sul-
fur dioxide and fluoride continue to be of con-
cern in some heavily industrialized areas. Here,
significant progress is being made in the devel-
opment of crop varieties and forest trees that
are resistant to gaseous pollutants or can pro-
duce reasonable yields under prevailing pollut-
ant loads.

Major Conclusions Regarding Effects of Air
Pollutants on Vegetation in North America.

     The major conclusions enumerated below
were developed as a synthesis  of about 60
years of experience in research on the effects of
air pollutants on plants in  the United States.

I)    Ozone is responsible for most of the crop-
yield losses from air pollutants on  both  a re-
gional and national scale within North America.
2)   Losses from other pollutants are minimal,
relative to ozone, and primarily occur very close
to sources, or are induced by joint effects with
ozone.
3)   Ozone may be the most important cause
of air pollution injuries in forests in the United
                                                                                      67

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0>
       Table 1.  Critical concentrations of gaseous pollutants that induce visible injury to vegetation in Eastern North America (all concentrations are in ppm).
Time of
Exposure
(hours)
0.5
1.0
2.0
4.0
8.0
Sulfur Dioxide1
Sensitive
1.0 - 4.0
0.5 - 3.0
0.25- 2.0
0.1 - 1.0
0.05- 0.5
Intermediate
3.5 -
2.5 -
1.5 -
0.5 -
0.2 -
12.0
10.0
7.0
5.0
2.5
Tolerant
>10.0
> 8.0
> 6.0
> 4.0
> 2.0
Sensitive
6.0 -
4.0 -
3.0 -
2.0 -
2.0 -
10.0
8.0
7.0
6.0
5.0
Nitrogen Dioxide^
Intermediate
9.0-17.0
7.0-14.0
6.0-12.0
5.0-10.0
4.0- 9.0
Tolerant
>16.0
>13.0
> 9.0
> 8.0
Sensitive
0.35-0.50
0.15-0.25
0.09-0.15
0.04-0.09
0.02-0.04
Ozone3
Intermediate
0.55-0.70
0.35-0.40
0.15-0.25
0.10-0.15
0.07-0.12

Tolerant
>0.7
>0.4
>0.3
>0.25
>0.2
       1EPA 1973.
       2EPA1982.
       3EPA1986.

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                              Air Pollutants, Plants, and Mechanisms of Interaction: A Historical Perspective
States and Canada.  Strong evidence has been
obtained for foliar injury by ozone to white pine
and many other conifer and  hardwood  tree
species in large parts of eastern North America.
In southern California, ozone can predispose
forest tree species to attack by bark beetles and
root-rotting fungi and, thus, can cause impor-
tant changes in the species composition  of
forests. Although foliar injury to individual trees
is well documented in many tree species, losses
in productivity of whole  forests has not been
demonstrated in North America (Woodman and
Cowling, 1987).
4)   Mathematical response functions that re-
late pollutant dose to crop yield are essential for
predicting  yield losses  in agricultural crops;
nonlinear models give the best fit to available
field data for ozone.
5)   A descriptive analysis of regional variation
in ozone concentration  using a  kriging tech-
nique is a useful and necessary part of  eco-
nomic assessment efforts. These same tech-
niques are not suitable for sulfur dioxide or other
point-source related pollutants.
6)   Foliar symptoms  on agricultural crops
under field conditions often are similar to early
senescence.  For this reason, they are often
difficult to quantify.
7)   Although  the  physiological and/or  bio-
chemical mechanisms of plant response to most
air  pollutants are not  well  understood,  cell
membranes appear to be a principal site  of
initial impact in the case of ozone.
8)   Both ozone and sulfur dioxide affect  pho-
tosynthesis and carbon allocation; decreased
allocation of carbon to root and reproductive
structures  is common.   Similar physiological
mechanisms may also be involved in  interac-
tions between plants and other gaseous pollut-
ants.
9)   Synergistic interactions in the  effects  of
ozone, sulfur dioxide, nitrogen oxides, and  fluo-
ride have  been documented  in a number  of
species of  crop plants.
10)  Interactions are also known to  occur be-
tween air pollutants and other abiotic stresses
such as water stress and nutrient deficiencies,
and biotic stresses such as pathogens and
insects.
11)  Most agricultural crops show decreases in
growth, biomass, and yield when the crops are
grown under air concentrations of these pollut-
ants that  are commonly found in the eastern
United States and Canada.
12)  The data on agricultural crop losses, accu-
mulated in connection with the National Crop
Loss Assessment Network (NCLAN), has given
a reasonable first estimate  of ozone-induced
injury to crop production in the United States.
The total economic value of these losses on the
most important crops of the  United States are
estimated to be from $1 to 5 billion annually.  If
known damage induced  by ozone on less im-
portant crops were added, the total economic
impact  of tropospheric ozone on agricultural
crop production in this country could be as high
as $7 billion annually. Changes in meteorologi-
cal conditions from year to year is the principal
source  of annual variations  in the  economic
impact of ozone.

              Literature Cited

Brandt,  C. S., and W. W. Heck.  1967.  Effects of air
    pollutants on vegetation, pp. 401 -443, In Stern, A.A.
    (ed.), Air Pollution. Volume 1. Academic Press, New
    York.

Crocker W.  1948.  Growth of Plants: Twenty Years'
    Research at Boyce Thompson Institute. Rheinhold
    Publishing Co., New York. 459 pp.

Cowling, E. B.  1982.  Acid precipitation in historical
    perspective. Environmental Science & Technology
    16:110A-123A.

Cowling, E.B. 1985.  Pollutants in the Air and Acids in the
    Rain: Influences  on our Natural Environment and a
    Challenge for Every Industrial Society.  XXVth Ho-
    race M. Albright Conservation Lecture, College of
    Natural Resources, University of California, Berkeley,
    California. 26 pp.

Environmental Protection Agency.  1973.   Air Quality
    Criteria for Sulfur Oxides. EPA-R3-73-030. National
    Environmental Research Center, Research Triangle
    Park, North Carolina.
                                                                                        69

-------
Ellis B. Cowling and Walter W. Heck
Environmental Protection Agency.  1982.  Air Quality
    Criteria for Nitrogen Oxides.   EPA-600/8-82-026.
    National Environmental Research Center, Research
    Triangle Park, North Carolina.

Environmental Protection Agency.  1986.  Air Quality
    Criteria for Ozone and other Photochemical Oxi-
    dants.  EPA-600/8-84-0200F.  National  Environ-
    mental  Research Center, Research Triangle Park,
    North Carolina.

Haagen-Smit, A. J. 1952.  Chemistry and physiology of
    Los Angeles smog. Industrial & Engineering Chem-
    istry 44:1342-1346.

Haagen-Smit, A. J., C. E. Bradley, and M. M. Fox. 1953.
    Ozone  formation in photochemical oxidation of or-
    ganic substances. Industrials Engineering Chemis-
    try 45:2086-2089.

Heck, W. W. 1966. The use of plants as indicators of air
    pollution.  Air & Water Pollution International Jour.
    10:99-111.

Heck, W. W., and A. S. Heagle.  1970. Measurement of
    photochemical air pollution with a sensitive monitor-
    ing plant.  Journ. Air Pollution Control Assoc. 20:97-
    99.

Heck, W. W., A.  S.  Heagle, and D. S. Shriner.  1986.
    Effects on vegetation: Native, crops, forest,  pp. 247-
    350, In: Stern, A.A. (ed), Air Pollution, Vol. 6. Aca-
    demic Press Inc., New York, New York.

Heck, W. W., S. V. Krupa, and S. H. Linzon, eds. 1979.
    Handbook of Methodology for the Assessment of Air
    Pollution  Effects on  Vegetation.  Upper  Midwest
    Section, Air Pollut. Control Assoc., Specialty Confer-
    ence Proceedings. April 1978. 392pp.

Jacobson, J. S., and C. Hill, eds. 1970.  Recognition of
    Air Pollution Injury to Vegetation: A Pictorial Atlas.
    Air Pollution Control Assoc. Pittsburgh, Pennsylva-
    nia. 90 pp.

Middleton, J.  T.   1961.   Photochemical  air  pollution
    damage to plants. Annual Review Plant Physiology
    12:431-448.
National Acid Precipitation Assessment Program. 1987.
    Interim Assessment:  The Causes and Effects of
    Acidic Deposition.  Volumes I, II, III, and IV.  Council
    on Environmental Quality, Washington, DC.

National Research Council. 1977a. Fluorides. National
    Academy Press, Washington, DC. 295 pp.

National Research Council.  1977b.  Ozone and Other
    Photochemical Oxidants. National Academy Press,
    Washington, DC. 718 pp.

National Research Council.   1977c.  Nitrogen  Oxides.
    National Academy Press, Washington, DC.  333 pp.

National Research  Council.   1981.  Atmosphere-Bio-
    sphere Interactions: Toward a Better Understanding
    of the Ecological Consequences of Fossil Fuel Com-
    bustion. National Academy Press, Washington, DC.
    263 pp.

National Research Council of Canada.  1939.  Effect of
    Sulphur Dioxide on Vegetation.  National Research
    Council of Canada, Ottawa, Canada. 447 pp.

Shupe, J.  L, H. B.  Peterson, and N. C. Leone. 1983.
    Fluorides:  Effects on Vegetation, Animals, and Hu-
    mans. Paragon Press, Salt Lake City, Utah.  369 pp.

Thomas, M. D.  1951.  Gas damage to plants.  Annual
    Review Plant Physiology 2:293-322.

Thomas, M. D. 1961.  Effects of Air Pollution on Plants.
    Air Pollution. World Health Organization Monograph
    Series 46:233-278.

Thomas, M. D. 1969. Photochemical smog. Air Quality
    Monograph 69-6. American Petroleum  Institute, New
    York. 40 pp.

Woodman, J. N., and  E. B.  Cowling.  1987. Airborne
    chemicals and forest health. Environmental Science
    & Technology 21:120-126.
 70

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 The Impact of Sulfur Dioxide Fumigation on Photosynthetic
    and  Ultrastructural Responses of Mesophyll  Cells from
    Developing Pinus strobus Needles.  1.  Mesophyll Cells
                          I. M. Kravkina and E. A. Miroslavov
                               Komarov Botanical Institute
                               USSR Academy of Sciences
                                Leningrad 197022, USSR

                                    R. E. Crang
                                  University of Illinois
                                 Urbana, Illinois, U.S.A.
                Abstract

     Two-year-old eastern white pine (Pinus
strobus) seedlings were fumigated with sulfur
dioxide (SO2) two hours each day for five days
during the time of new needle emergence. The
needles from the SO2-treated plants were shorter
than controls, but otherwise showing no macro-
scopic signs of damage. Photosynthetic meas-
urements taken during the times of fumigation
showed a steady decline during each two hour
exposure to SO2, and a reduced level of activity
on each succeeding day of the experiment.
Ultrastructural studies revealed three stages of
degradation which were consistent among cells
throughout the young needles. Special atten-
tion was directed at the degradation of chloro-
plasts, mitochondria, peroxisomes, ribosomes
and nuclei. The  Ultrastructural changes are
related to recorded changes  in size and photo-
synthetic activity of the needles, and shows that
severe microscopic and physiological damage
may be present  before obvious macroscopic
damage is evident.
              Introduction

    This study seeks to reveal specific physio-
logical and Ultrastructural responses in the meso-
phyll cells of developing pine needles prior to
visible damage when fumigated with sulfur
dioxide (SO2). These changes are documented
both by means of transmission electron micros-
copy, and by measurements of carbon dioxide
utilization. It may be noted that in recent years,
there  have  been  several studies of  gymno-
sperm foliar structures in which the plants have
been exposed to SO2 (Smith and Davis, 1978;
Soikkeli, 1981; Soikkeli and Tuovinen, 1979;
vonParameswaranefa/., 1985; Soikkeli, 1981).
However, most studies have been directed spe-
cifically at the structural responses of chloro-
plasts to atmospheric pollutants (e.g. Malhotra,
1976; Soikkeli, 1981). Little attention has been
directed towards the responses of other cellular
components to the influence of air pollutants,
and no reports are known regarding the specific
effects on nuclear structures. This study, there-
fore, is directed at varied aspects of the ultra-
                                                                                71

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/. M. Kravk/na, E. A. Miroslavov, and R. E. Crang
structural response of P/ntvssfrofai/smesophyll
cells to SO2 fumigation with regard to the photo-
synthetic responses during experimental fumi-
gation.
          Materials and Methods

    Two-year old seedlings of eastern white
pine (Pinus strobus) were grown in soil under
greenhouse conditions and, in mid-spring (April),
representative plants were introduced into
environmental chambers illuminated with 300
uE/m2/sec (slightly red) light, at 53-58% relative
humidity, and at a temperature of 23°C (±1 °C).
Plastic bags were tied around the pots to the
stems  of the plants in order to prevent SO2
absorption into the soil which might affect respi-
ratory measurements.  Carbon dioxide  (CO2)
levels were monitored continuously during each
two hour experimental period using a Beckman
infra-red gas analyzer. The measure of CO2
consumed at the  end of each 24 minute period
over the course of the two hours as a function of
the total needle dry weight of the plants, be-
came a measure of the photosynthetic capacity
of the plants for each day.  Dry weights were
taken of all green needles at the conclusion of
the experiment on the fifth day. For the control
plants, the average wet and dry weights of the
needles were 14.92 g and 5.68 g respectively,
and for the experimental material, the values
were 14.15 and 5.47 g respectively.

     In the experimental chamber, atmospheric
SO2 was maintained at 1.0 ppm for two  hours
each day  over the course of five  days.  The
control chamber was  maintained under identi-
cal conditions except for the presence of only
ambient levels of SO2 (0.03 —0.05 ppm).  At the
end of 3 and 5 days, small segments of the
newly-developing needles were taken from their
tips and from their bases for electron micros-
copy fixation. Segments as similar as possible
were prepared from  both  experimental and
control  plants.   The  fixation procedure was
conventional for the ultrastructural preservation
of plant material except that 1.0% caffeine was
added  to the  initial (glutaraldehyde) fixative in
order to prevent the leaching of vacuolar tan-
nins into cytoplasmic structures (Mueller and
Greenwood, 1978).  The samples were dehy-
drated  in a graded ethanol series and embed-
ded in  a Spurr-Epon resin mixture.  Sections
were stained with lead citrate and subsequently
examined with  a  Hitachi  H-600 transmission
electron microscope operating at 75 kv.

          Results and Discussion

     Following either three or five days of S02
fumigation, the newly-expanding needles on
the exposed plants showed no visible macro-
scopic  damage.  However, needles from the
SO2-fumigated  plants were demonstratively
shorter at the end of the five day period than the
corresponding control needles (Fig. 1). Whereas
the average length of control needles was 26.0
mm, the needles from fumigated plants were 5-
6 mm shorter.

     Figure 2 shows the CO2 uptake  in control
and SO2-treated pine plants as a function of the
total needle  dry weight.  Control ratios varied
between 6.7 and 7.1 ug CO2 uptake/g dry weight,
but very large differences were noted in the
SO2-treated  plants.  The results showed a
general decline in the starting photosynthetic
levels each day over the course of the five day
fumigation period, indicating that there  is a
certain  amount  of  accumulative  permanent
damage  to the photosynthetic system which
can be carried over from one day to the next.
Furthermore, there was a steady decline  in
photosynthetic activity at each 24 minute time
period  during the  course of the daily two hour
experimental exposure to SO2 fumigation. This
was demonstrated by a "leveling-off" of CO2
consumption to a very low level between 96
minutes and 120 minutes each day.  Although
the decline in photosynthetic activity each day
was rather dramatic, starting levels the follow-
ing day were always significantly higher than
the final measurement of the previous  day,
indicating that  a certain  component of the
damage was reversible.
72

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     The Impact of Sulfur Dioxide Fumigation on Photosynthetic and Ultrastructural Responses of Mesophyll Cells
     While the exposure to SO2 may have inhib-
ited cellular elongation in the developing needles,
our ultrastructural observations indicate  that
severe damage was occurring. Examination of
basal and tip-region plicate  mesophyll cells
showed similar  results in the SO2-fumigated
specimens. The only difference was that similar
damage to  mesophyll cells was  delayed by
about two days in the base  as opposed to the
tip. No observable damage  occurred to meris-
tematic cells—even after the full five days of the
experiment (compare Figs. 5 and 11). Thus, we
presume that SO2 fumigation did not interfere
with mitotic development. The results revealed
three stages of  cellular degradation in meso-
phyll cells prior to their complete destruction. A
summary  of these stages  of degradation  is
presented in Table 1. It is important to note that
these stages of cellular alteration and degrada-
tion occurred when there was no direct visible
damage to the needles. It should also be noted
that damage was random throughout the plicate
mesophyll with severely damaged cells some-
times adjacent to evidently healthy cells.
                           The following is a description of the se-
                      quential damage which occurred to specific
                      cellular components within the mesophyll tis-
                      sue  from  SO2-treated  specimens.   Control
                      material remained in a healthy-appearing state,
                      both macroscopically and microscopically, and
                      all following references made to the controls are
                      strictly for comparative purposes.

                           Chloroplasts within cells showing stage 1
                      damage were comparable to those of control
                      cells, except that the starch grains were smaller
                      and less abundant (compare Figs. 3 and 9, and
                      Figs. 4 and 10). In sectioned planes, only one
                      or two starch grains could typically be observed
                      in chloroplasts from SO2-treated specimens,
                      whereas up to one-third of the sectional view of
                      control plastid profiles were occupied by large
                      starch grains.  In the early stage of cellular
                      damage, there were no differences noted in the
                      number, size  or distribution  of  plastoglobuli.
                      Small,  dense, and  often  single plastoglobuli
                      could be observed in the chloroplast matrix, and
                      sometimes three to  seven could be found in
Table 1.  Summary of ultrastructural responses in developing needles of first year growth of SO2-fumigated P.
        strobus .  Changes are noted for the major protoplasmic components of the plicate mesophyll cells.
        Chloroplasts
Mitochondria
Peroxisomes
                                                            Ribosomes
                                                      Nucleus
Control  Nearly 1 /3 starch     Normal
Stage 1  Reduced starch      Normal
                Normal
                                                           Free and RER
                Matrix translucent   Free and RER
Stage 2  Thylakoids swollen  Matrix less dense;   Matrix with
        with dense lumens  reduced cristae     coagulation
Stage 3  Only starch and     Matrix transpa-     Matrix entirely
        plastoglobuli       rent; no cristae     dense
        remain
                                   Large membrane
                                   invaginations

                                   Small membrane
                                   invaginations.
                                   1-2 nucleoli.
                                 Reduced frequency  No euchromatin.
                                                   Only nucleolar
                                                   fibrillar structure.

                                 Completely absent   Small nuclei.
                                                   Heterochromatin
                                                   reticulum formed.
               Complete breakdown with no recognizable morphological structure remaining.
                                                                                          73

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/. M. Kravkina, E. A. Miroslavov, and R. E. Crang
aggregation within  a single plastid  profile.
Likewise,  the  thylakoid  system  appeared
unchanged between control and experimental
specimens with from two to three thylakoids in
small grana, and 25 to 30 in large grana (Fig. 6).
These,  in turn, were  oriented towards  the
vacuolar side  of the plastids within a dense
stroma that was more prominent on the cell wall
side of the plastids. In what may be designated
as a second stage of degradation, the thylakoids
became greatly swollen and the contents of the
thylakoid lumens became more dense (compare
Figs. 6 and 12). Starch grains and plastoglobuli
persisted in adensethylakoid-stroma matrix. In
the third stage of degradation, the chloroplast
integrity was  completely  destroyed, and its
contents became a homogeneous mass in which
only starch grains and plastoglobuli could still
be identified.

     Observations of mitochondria from the first
stage of degradation  showed no differences
from those of the control group.  They pos-
sessed a circular profile with small granules in
the matrix and small cristae.  In the second
stage, the matrix of most mitochondria became
less dense, and the cristae even less prominent
(Fig. 13). By the third stage of degradation, the
mitochondria! matrix became electron-transpar-
ent, and virtually no cristae could be recognized
in the remaining organelle profiles. Beyond this
stage, it was no longer possible to morphologi-
cally identify the mitochondria.

     In stage 1, peroxisome profiles were equal,
or up to three  times greater, in sectional area
than those of mitochondria, although the matrix
was nearly translucent (similar to Fig. 6). While
somewhat larger than mitochondria, there were
fewer numbers of these  organelles per cell.
Typically, only two to four peroxisome profiles
could be observed in each section. In a second
stage of degradation, the peroxisome matrix
began to show coagulation  and, in the third
stage, electron-dense material occupied nearly
the entire content of these organelles. Follow-
ing this, the limiting membrane was no longer
evident and these organelles could no longer be
identified.

     In addition to changes in membrane-bound
organelles, early alterations of ribosomes could
also be observed. In the first stage, both poly-
somes and  free individual  ribosomes were
commonly observed.   In the  second stage,
ribosomes of both types were largely lacking,
and by the third stage, they were completely
absent.

     Major attention was directed at changes
noted in  the nuclear  structure.  In stage 1,
nuclear profiles were circular with occasional
small invaginations of the envelope membranes.
While otherwise similar, nuclei from  control
speci mens possessed more frequent and longer
narrow channels of these invaginations (Figs. 4
and?). Chromatin in diffuse form (euchromatin)
and  in  condensed form (heterochromatin),
appeared rather uniformly dispersed through-
out the nuclei. One or two prominent nucleoli
could be found in each nuclear profile of control
and stage 1  specimens (Fig. 8). These struc-
tures possessed large, but not deep, lobes and,
at times, nucleolarvacuoles. Both granular and
fibrillar components were present with granular
ones predominating. By stage 2, the nuclear
chromatin was only found in the condensed
form with no evidence of euchromatin being
present. Only fibrillar structures and irregularly-
shaped electron-dense granules remained of
the nucleolar structures. In the third stage, the
size of the nuclei noticeably decreased.  The
contents  appeared to  be comprised of only a
reticulum of condensed heterochromatin which
possessed a rather "fuzzy" or "melted" appear-
ance (Fig. 14). Following this stage, the remain-
ing nuclear substance became a homogeneous
mass of  moderately dense material.  These
changes  in  nuclear structure  during  cellular
degradation are believed to be related to a great
decrease in the biosynthesis of ribosomal RNA
as evidenced by the sudden reduction of ribo-
somes in stage 2.
74

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     The Impact of Sulfur Dioxide Fumigation on Photosynthetic and Ultrastructural Responses of Mesophyll Cells
     Thus, even when no visible damage could
be observed after five days of SO2 fumigation,
considerable Ultrastructural damage could  be
identified. The needles, while macroscopically
appearing healthy, could  be shown to have
large numbers of mesophyll cells in  various
stages of damage. Only two of the stages of
degradation were found in basal  cells as op-
posed to the needle tip after five  days of SO2
fumigation.  Presumably,  the same levels of
degradation would, in time, occur in the basal
mesophyll cells.  It is possible that stage 1 of
degradation represents the level of damage
which is reparable, and which may correspond
to the demonstrated recovery in photosynthetic
activity from the end of one day's fumigation to
the start of the next day's fumigation time. The
continuing day-to-day decline in photosynthe-
sis may correspond with  the  Ultrastructural
changes shown in stages  2 and  3 and, obvi-
ously, in the total destruction of the cells. While
no evidence indicates structural damage of the
meristematic tissue, the shorter average needle
length in the SO2-fumigated plants (compared
with the control) suggests that some of the
damage must contribute to the stunted growth
of the needles.  If the meristem is not directly
affected, then an inhibition of cell elongation
may be a factor in reduced growth along with the
random destruction of mesophyll cells.  This
study strongly suggests that episodic events of
SO2 pollution in the atmosphere reaching levels
of approximately 1.0 ppm may, in  a short time,
cause significant and lasting damage to pine
trees—particularly in  new foliar growth.
            Acknowledgments

     The authors thank Drs. Roger Carlson and
Anthony Endress of the University of Illinois at
Urbana for their assistance in the fumigation of
plant specimens. Partial support for this inves-
tigation was provided by a grant from the Elec-
tric Power Research  Institute (Palo Alto,  CA),
and by a grant from Dr.  Anthony Joseph  (Co-
lumbus, OH).

              Literature Cited

Malhotra, S.S.  1976.  Effects of sulfur dioxide on bio-
    chemical activity Ultrastructural organization of pine
    needle chloroplasts.  New Phytol. 76(2):239-245.

Mueller, W C., and A.D. Greenwood. 1978.  The ultras-
    tructure of phenolic-storing cells fixed  with caffeine.
    J. Exp. Bot. 29:757-764.

Smith, H. J, and D. D. Davis. 1978. Histological changes
    induced in Scotch pine needles by sulfur dioxide.
    Phytopath. 68(12):1711-1716.

Soikkeli, S. 1981. Comparison of cytological injuries in
    conifer needles from several polluted industrial envi-
    ronments in Finland.  Ann. Bot Perm.  18:47-61

Soikkeli, S.  1981. The types of Ultrastructural injuries in
    conifer needles of northern industrial environments.
    Silva Fennica 16:399-404.

Soikkeli, S., and T. Tuovinen. 1979. Damage in meso-
    phyll ultrastructure of needles of Norway spruce.
    Ann. Bot. Fenn/c/'16(1):50-64 .

von Parameswaran, N., S. Fink, and W.  Liese.  1985.
    Feinstrukturelle untersuchungen an  nadeln ges-
    chadigterjannen und fichten aus waldschadensgebi-
    eten im Schwarzwald. Sonderdruck aus European J.
    Forest Pathol. 15( 3): 168-182 .
                                                                                           75

-------
 /. M. Kravkina, E. A. Miroslavov, and R. E. Crang

Figure 1. Comparison of first year needles from fascicles having similar length prior to the fumigation study. The shorter
          needles are from an SO2-fumigated P. strobus plant. Note millimeter scale.
76

-------
     The Impact of Sulfur Dioxide Fumigation on Photosynthetic and Ultrastructural Responses of Mesophyll Cells
 Q

 $    5
 O"  4
 o
 D)
                                                                        Minutes
                                                                   DO      E3  72

                                                                   E 24    ^96

                                                                   E3 48    ^ 120
             Control
                                      DAY OF FUMIGATION
Figure 2.   Photosynthesis rates of O.Sppm SO2-treated 2 year-old pine seedlings.
           Carbon dioxide uptake in control and SO2-fumigated P. strobus seedlings.  Values on the vertical axis
           represent the numerical ratio of ug CO2 consumed per gm dry weight of green foliar material. Time periods
           up to 2 hr (120 min) are given on the horizontal axis in which control plants and the experimental plants
           are compared for each day (days 1 -5) Since control values were relatively stable each day, only one set
           of average values is given.
                                                                                                 77

-------
/. M. Kravkina, E. A. Miroslavov, and R. E. Crang
           Figures 3-8 show the views of P. strobus control needles imaged with transmission electron microscopy.
           Stage 1 degradation was often unchanged as indicated in the text.

Figure 3   Low magnification view of the basal portion of a first year P. strobus needle in transverse section. Epidermal
           and hypodermal layers lie outside of the plicate mesophyll cells. Large deposits of tannins (T) fill the central
           vacuolar regions of the cells. Chloroplasts can be observed to contain large starch deposits. 15,300 X.

Figure 4.   Nucleus from mesophyll cell in the tip region. Note the invaginations and the random distribution of eu- and
           heterochromatins.  Prominent  starch and plastoglobuli can be seen  in the surrounding chloroplasts.
           5,000 X.

Figure 5.   Meristematic zone at the base of needle. Cells possess large, prominent nuclei. Ch = metaphase chro-
           mosomes.  15.000X.

Figure 6.   Chloroplast with adjacent mitochondria and peroxisome from mesophyll cell in tip region of pine needle.
           Free ribosomes are in the cytoplasmic matrix. Variable thylakoid numbers comprise the chloroplast grana.
           The chloroplast stroma  is more dense relative to milochondrial and  peroxisome  matrices.  Note the
           prominent dark plastoglobuli often appearing in clusters (Pg). 19,400 X.

Figure 7.   Portion  of nucleus and chloroplasts in  control tip.  Note the deep invagination of the nuclear envelope
           (arrow).  20,500 X.

Figure 8.   Nucleolus from nucleus in a control tip mesophyll cell.  Both granular (G) and fibrillar (F) components are
           present, as well as cleared areas referred  to as nucleolar vacuoles (NV). 30,000 X.
78

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The Impact ot Sulfur Dioxide Fumigation on Photosynthetic and Ultrastructural Responses of Mesophyll Cells
                                                                                                 79

-------
/. M. Kravkina, E. A. Miroslavov, and R. E. Crang
           Figures 9-14 show the views of P strobus SO2-fumigated needles imaged with the transmission electron
           microscope. Views represent examples of stages 2 and 3 from random degradation among mesophyll cells
           in all regions of the developing needles.

Figure 9.   Low magnification view of the basal portion of a first year P. strobus needle in transverse section close to
           the meristematic zone. Tannin deposits are extensive.  Chloroplasts contain starch, although in reduced
           quantity, compared with control. 1,500 X.

Figure 10. Tip region (5 days fumigation) showing partial breakdown of the cytoplasm and a clearing of the euchro-
           matin in the nuclei. Starch in Chloroplasts is more sparse than in the control cells.  1,400 X.

Figure 11. Portion of meristematic zone in the basal region of a needle from an SO2-treated plant. Eu- and heterochro-
           matin appear normal. Occasional degraded cells (DC) appear in normal development. Compare with Fig.
           5. 4,500 X.

Figure 12. Portion of chloroplast and mitochondrion representative of stage 2 degradation. Stroma of chloroplast is
           more  dense than unaffected material,  but matrix of  mitochondrion has  become nearly  translucent.
           Significant thylakoid  swelling can be observed in the chloroplast. 16,600 X.

Figure 13. Stage 3 degraded chloroplast from tip cell following five days fumigation. The starch  remains, but the
           stroma and thylakoid membranes are beginning to form a dense mass.  25,000 X.

Figure 14. Stage 3 degradation  of nucleus from SCyaffected mesophyll of needle tip region.  The heterochromatin is
           coagulated into a reticulum showing a "fuzzy "appearance prior to the complete destruction of the organelle.
           20,000 X.
80

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The Impact of Sulfur Dioxide Fumigation on Photosynthetic and Ultrastructural Responses of Mesophyll Cells
                                                                                                 81

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         The Impact of Sulfur Dioxide Fumigation on the
       Ultrastructure and Photosynthesis of Pine Needles
                      II.  Resin  Duct Epithelial Cells
                                   A. E. Vassilyev
                                Komarov Botanical Institute
                                USSR Academy of Sciences
                                 Leningrad 197022, USSR

                                     R. E. Crang
                                   University of Illinois
                                   Urbana, Illinois, USA
                Abstract

     Ultrastructural observations of epithelial
cells from resin ducts in the expanding needles
of Pinus strobus seedlings were made from
control and from green portions of SO2-fumigated
seedlings. Three needle zones were selected:
the basal region (enveloped within the fascicular
sheath), mid-region, and tip. In SO2-fumigated
material, the Ultrastructural appearance of the
epithelial cells was found to vary greatly with the
position of the cells and the length of fumigation
treatment. No visible change  in Ultrastructure
was observed in epithelial cells taken from the
basal region of needles after short fumigation,
but after longer SO2-treatment, no  normal
epithelial cells were found. In the middle needle
portion,  most  samples  contained  normal
epithelial cells, but after longer treatment, there
were signs of premature senescence.  In the
oldest portions of the needle (the tip), some
samples contained normal epithelial cells but
most of the cells exhibited pronounced, but
reversible signs of degeneration.
              Introduction

    Only a few studies on the impact of sulfur
dioxide on the structure of pine needle tissues
other than mesophyll have been conducted.
This is  particularly the case with the epithelial
cells of resin ducts. Based on only light micro-
scope observations, previous studies showed
that the epithelial cells underwent severe hy-
pertrophy resulting in the complete occlusion of
the resin duct canals after a 3-hour exposure to
1.0 ppm SO2 (Smith and Davis, 1978; Stewart et
a/., 1973).  Such reported change was evident
not only in the portion of the needle that dis-
played macroscopic symptoms but, unlike other
tissues, extended far into the apparently healthy
regions. Microscopic injury was observed only
in growing needles which exhibited macroscopic
damage, such as a tan necrosis extending from
the needle tip toward the base. Necrotic areas
were separated from uninjured green ones by
an abrupt line of demarcation, a so-called "tran-
sition zone" (Smith and Davis, 1978).  However,
according to Evans and Miller (1975) in P. pon-

                                      83

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A.E. Vassilyev and R.E. Crang
derosa, SO2 fumigation caused a loss of cellular
constituents and cell wall material from epithe-
lial cells. In most cases,  only cell walls and a
small amount of the  cytoplasm remained in
injured epithelial cells after 9 days of SO2 expo-
sure (0.45 ppm).  Our study was initiated in
order to determine the effects of SO2 exposure
on the ultrastructure of epithelial cells from resin
ducts in elongating Pinus strobus needles.

           Materials and Methods

     Three year-old Pinus strobus seedlings
were exposed to 0.8 ppm of sulfur dioxide (SO2)
for 4 hours daily over  a period of either five or
nine days, respectively. No microscopic symp-
toms of SO2-induced  injury on the elongating
needles were observed after 5 days treatment,
but after 9 days, at the conclusion of the experi-
ment, visible damage  appeared as small chlo-
rotic spots on the needles.  Epithelial cells in
only green, and apparently healthy needle por-
tions of potted seedlings previously maintained
under greenhouse conditions, were studied.

     At the  conclusion  of  either fumigation
period, one mm needle segments were excised
and fixed in phosphate-buffered osmium tetrox-
ide. After ethanolic dehydration and infiltration
with propylene oxide,  the specimens from
fumigated material and controls were infiltrated
and subsequently embedded in a 1:1  Spurr-
Epon epoxy mixture. Specimens were cut into
ultrathin sections, stained with lead citrate, and
observed with  a Hitachi  H-600 transmission
electron microscope operating at 75 kV. Com-
parative observations were made at correspond-
ing magnifications.

                  Results

     The  resin  ducts in pine needles are dual
elongated structures  extending beneath  the
longitudinal axis of the adaxial needle surface
(Fig. 1). They are composed of one layer of thin-
walled, small,  elongated epithelial cells sur-
rounding  a lumen, or canal, where resin is
accumulated.

     The epithelial cells of Pinus resin ducts
display a characteristic fine structure which is
related to the specialization and concentration
of organelles involved in oleoresin synthesis
(Fahn, 1979; Vassilyev, 1977). The cells differ-
entiate very closely to the basal meristematic
region of the needle which gives rise to all of the
leaf  cells.  The epithelial cells  become fully
mature and elongated while they are still en-
closed within the fascicular sheath. The rate of
resin synthesis and  the amount of secretion
gradually diminish in the acropetal direction.

     The most notable feature of the epithelial
cells are the leucoplasts which, in the highly
active portion of the duct, occupy a very large
part  of the cytoplasmic volume  (Fig 1).  The
leucoplasts usually have no internal membranes
and their stroma lack ribosomes. Characteris-
tic of these epithelial leucoplasts is their specific
connection to the endoplasmic reticulum (ER),
the cisterna of which  completely surrounds the
plastid envelope.  The periplastidal reticulum
(or reticular sheath) is continuous with well-de-
veloped agranular and  granular cytoplasmic
profiles of the ER extending throughout the cell,
and  approaching the mitochondria and plas-
malemma.  Synthesis of resin occurs not inside
the matrix  of organelles and in cytosol, but
separately within the intermembranous spaces
of the plastid, nuclear and mitochondrial enve-
lopes, and is presumably transported to the
periplasmic space through the ER which is also
involved in resin synthesis. Resin is eliminated
from periplasmic spaces into the canal through
the thin, loose apical cell wall. In epithelial cells
of the youngest portion of the needle, there are
smaller and less frequent leucoplasts only partly
sheathed by a periplastidal reticulum, and the
number of resin droplets is sparse.

     In the epithelial cells in which resin synthe-
sis has slowed, the amount of intracellular resin
is also reduced as are the number and size of
the leucoplasts.  The resin completely disap-
  84

-------
             The Impact of Sulfur Dioxide Fumigation on the infrastructure and Photosynthesis of Pine Needles
pears from the nuclear envelope; however, the
reticular sheath is still complete. The cell wall
becomes thickened and dense. In the tip region
of P. strobus needles, the epithelial cells remain
intact but quiescent, and the ER sheath around
lipids show large gaps at certain sites.

     In SO2-treated material, the ultrastructural
appearance of  epithelial cells varies greatly
with the position of the cells and the mode of
treatment.  We  could not find changes in the
ultrastructure of the epithelial  cells from  the
basal parts of the growing  needles when the
plants were fumigated for 5 days,  even when
the mesophyll cells in some  parts of the needle
displayed  severe damage.  The  fully-active
epithelial cells were dominated by  leucoplasts
which were completely enveloped by the ER
cisterna. They  also contained abundant free
ribosomes.  However, there were no osmio-
philic substances inside the intermembranous
spaces of organelles (Fig. 2).

     In some samples of 5-day treated speci-
mens, the epithelial cells of the oldest portion of
the needle, the tip, appeared less functional and
contained leucoplasts and resin droplets within
the intermembranous space of the  organelles.
In some samples, however, there were pro-
nounced signs of degeneration. The epithelial
cells were  highly vacuolated and flattened in
radial directions, but  the  nucleus appeared
normal. The number of leucoplasts and other
organelles was significantly  reduced and there
were no reticular sheaths.  The epithelial cells
contained  large  lipid bodies characteristic of
inactive cells. The remaining organelles were
ill-defined.  In some samples,  there was an
aggregation of vesicles containing several dense
granules. The apical cell wall facing the canal
became dense  and thickened and  the plas-
malemma was retracted from the cell wall. No
hypertrophy of the epithelial cells  was found,
although they showed slight plasmolysis. The
lumen of the canal was completely open.

    After longer SO2 treatment (4 hr/day dur-
ing 9 days),  no normal epithelial cells were
found within the youngest portion of the needle
protected by cataphylls of the fascicular sheath.
The ultrastructure of such epithelial cells showed
severe damage. The integrity of the leucoplast
and mitochondrial envelopes as well as the re-
ticular sheath was lost and  the plastid stroma
became flocculent amid small membrane frag-
ments (Fig. 3). Resin droplets were still present
and, unlike control plastids, osmiophilic mate-
rial was precipitated within the stroma of some
leucoplasts. In the most severe damage, only
membrane fragments remained of the plastids
and periplasmic membranes with no evidence
of resin. Occasional starch grains could be
found (Fig.4).

     In spite of the above plastid changes, the
mitochondrial  nucleoids with  DMA fibrils ap-
peared intact.  The cytosol became empty and
the ribosomes were ill-defined. The tonoplast
was broken down and the double outer mem-
branes of the mitochondria were often indistin-
guishable.  Nevertheless, the Golgi apparatus
and the nucleus appeared normal and the plas-
malemma was tightly apressed to the cell wall.
No hypertrophy or collapse of the epithelial cells
described in earlier light optical studies were
noted.

     In mid-region needle  specimens,  it was
found that the periplastidal endoplasmic reticu-
lum disappeared completely (Fig. 5)  and the
number of cytoplasmic  reticular profiles was
significantly reduced.   No  osmiophilic resin
droplets were seen.  Within the normally ap-
pearing nuclei, the nucleoli of such epithelial
cells were almost devoid of the granular compo-
nent (which would indicate  an inactive state),
and their size was smaller than in the nuclei of
the adjacent mesophyll cells where the propor-
tion of the granular  component was much
higher (more active nucleoli). There was great
variation in the physical state of mesophyll cells
within the vicinity of injured resin ducts. In some
samples, the mesophyll cells appeared rela-
tively  normal,  but in some  cases, they were
                                                                                     85

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A.E. Vassilyev and R.E. Crang
severely injured, showing the loss of membrane
integrity of the chloroplasts.

                Discussion

     There were two distinct types of epithelial
cell injury due to SO2-treatment.  First, there
was a disappearance of the ER sheath around
the leucoplasts,  reduction  in organelle fre-
quency, and disappearance of resin droplets
from protoplasts.  The  integrity  of organelles
and membranes was not lost. It follows that,
unlike  mesophyll chloroplasts which are af-
fected first (Huttunen and Soikkeli, 1984; Ste-
wart et a/., 1973), leucoplasts of the epithelia
are less sensitive to SO2 treatment than the ER.
This type of reversible injury (similar to prema-
ture senescence) was observed only in the ep-
ithelial cells of the needle tip region after milder
treatment, whereas the cells in younger (mid-
and basal-needle regions) remained unchanged.
The apical portion of the needle eventually died
even after mild treatment.   After longer SO2-
exposure, a similar type of alteration was ob-
served in the epithelial cells of middle regions of
some needles where the epidermal cells de-
posited thick secondary walls while cells  in
basal portions of the needle underwent irre-
versible changes.

     Secondly, the loss of organelle integrity
(leucoplast and mitochondria) and  membrane
integrity (endoplasmic reticulum and tonoplast),
along with the disappearance of  ribosomes
were found, but with no apparent changes in
Golgi-apparatus,  nucleus and plasmalemma.
The resin droplets remained in surrounding de-
generating cytoplasm.  It follows that, in the ep-
ithelial cells, the  nucleus, plasmalemma and
Golgi-apparatus are most resistant as opposed
to the situation with mesophyll cells, and the
sheathing ER is most sensitive to the SO2 treat-
ment. Unlike mesophyll chloroplasts, leuco-
plasts of the epithelial cells are less sensitive to
SO2 pollution than the endoplasmic reticulum.

     The two different types of ultrastructural
alteration are not different stages of the same
process leading to death of the epithelial cells.
Unlike mesophyll cells (Kravkina et ai, 1989),
epithelial cells are most sensitive to longer S02
treatment in the  basal region of the growing
needle where they are most active in resin
production, and where the epidermal cells have
thin, non-cutinized cell walls, which lacking ep-
icuticular wax, is readily susceptible to injury
from toxic gases.  In this  needle region, the
longer SGytreatment leads to irreversible ul-
trastructural changes of the epithelium.  How-
ever, with shorter treatment (5 days), the ep-
ithelial cells in the basal portion remained un-
changed.- It follows that the pattern of change
depends on  pollutant  exposure.  In shorter
treatment, epithelial cells of the tip region are
sensitive, and in the other regions they are re-
sistant; however, in longer treatment, all parts
of the needle appear affected. In the basal parts
of the needle, the changes  are irreversible,
while in the middle  part they are reversible.
Unlike the mesophyll, where the cells at differ-
ent stages of degradation were randomly dis-
tributed within the tissue (Kravkina etal., 1989),
all the epithelial cells have similar ultrastructure
at a given axis level of the SO2-treated needle.
Likewise,  the  response of organelles, espe-
cially nucleus and mitochondria of the epithelial
cells, to SGytreatment differs distinctly from
that of mesophyll cells.  The results of our study
differ significantly from those of previous light
microscope observations (Smith and  Davis,
1978; Stewart etal., 1973) in which hypertrophy
of the epithelial cells leading to the occlusion of
the resin duct after SO2-treatment was found.
The possible explanation for the discrepancy is
that the previous investigators studied mature
needles of P. sylvestris and P. strobus.  Evans
and Miller (1975), who studied the anatomy of
SO2-fumigated developing needles in P. pon-
derosa, also did not reveal hypertrophy of the
epithelial cells. Thus, SO2 fumigation not only
results in the reduction of the rate of photosyn-
thesis (Kravkina etal., 1989), but also adversely
affects oleoresin synthesis. These results should
be taken  into account in  evaluations of the
 86

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               The Impact of Sulfur Dioxide Fumigation on the Ultrastructure and Photosynthesis of Pine Needles
environmental impact related to SO2 emissions.

             Acknowledgments

       Partial support for this investigation was
provided by a grant from the Electric Power
Research Institute (Palo Alto, CA), and by  a
grant from Dr.  Anthony Joseph  (Columbus,
OH).

               Literature Cited

Evans, L.S., and P.P. Miller. 1975. Histological compari-
    son of single and additive ozone and sulphur dioxide
    injuries to elongating ponderosa pine needles. Am.
    J. Bot. 62:416-421.

Fahn, A.   1979.  Secretory  Tissues in Plants.  Acad.
    Press, London, New York.

Huttunen, S., and S. Soikkeli. 1984. Effects of various
    gaseous pollutants on plant cell Ultrastructure. In:
    Gaseous Air Pollutants and Plant Metabolism. Koziol
    and Whatley (eds). pp. 117-127.
Kravkina, I. M., E. A. Miroslavov and R. E. Crang. 1989.
   The impact of sulfur dioxide fumigation on the ultra-
   structure and  photosynthesis  of pine needles.  I.
   Mesophyll cells. In: EPA/USDA 2nd Int. Symp. on Air
   Pollution Effects on Vegetation. (Raleigh, NC).

Smith, H.J. and D.D. Davis. 1978. Histological changes
   induced in Scotch pine needles by sulfur dioxide.
   Phytopathology 68:1711 -1716.

Stewart, D.,  M.  Treshow  and  F M. Haznez.   1973.
   Pathological anatomy  of conifer needle necrosis.
   Can. J. Bot. 51:983-988.

Sutinen, S.  1987. Ultrastructure of mesophyll  cells of
   spruce needles exposed to  03 alone and together
   with SO2. Eur. J. Forest Pathol. 17:362-368.

Vassilyev, A.E. 1977.  Functional Morphology of Plant
   Secretory Cells. Nauka Publ. House, Leningrad (in
   Russian).
                                                                                                  87

-------
A.E. Vassilyev and R.E. Crang
 Figure 1. Epithelial cell of the basal region of the Pinus strobus needle after short (0.8 ppm, 5 days, 2 hr) SO2-treatment.
          Appearance is similar to control. Note the normal appearance of all organelles, but the lack of resin droplets
          in the extra-cytoplasmic phase of the protoplast. L=leucoplasts, C=canal. 3,500X.

  88

-------
                The Impact of Sulfur Dioxide Fumigation on the infrastructure and Photosynthesis of Pine Needles
                                     .
Figure 2. Portion of an epithelial cell at the base of the needle after long SO2-treatment. Note the lack of resin, the sheath
        of ER (arrows) around leucoplasts (L), and the normal appearance of organelles. 20.000X.

Figure 3. A portion of the epithelial cell in the basal region of the needle after long (0.8 ppm, 9 days, 4 hr.) SO2-treatment.
        Note the loss of the integrity of the Leucoplast, and sheathing ER membranes (thin arrows), and the floccu-
        lation of stroma (white arrow). 30.000X.
                                                                                                      89

-------
A.E. Vassilyev and R.E. Crang

       s
^J  !  "  '..uc«;,_i
f
••*
               /          ,
                       ; j...
     ,.   ; , " ; ,-. ,     ~
Figure 4. Severe damage to plastid induced by strong SO2 treatment. Resin is lost but a starch grain (S) remains.

          30.000X.



Figure 5. Mid-region needle specimen showing loss of periplastidal endoplasmic reticulum. P=plastid. 30.000X.
 90

-------
 The Impact of Sulfur Dioxide Fumigation on Photosynthetic
     and Ultrastructural Responses of Mesophyll Cells in
   Developing Pinus strobus Needles. III.  Transition Zone.
                                    R. E. Crang
                          University of Illinois, Urbana, Illinois, U.S.A.

                          A. E. Vassilyev and I. M. Kravkina
                         Komarov Botanical Institute, Leningrad, USSR
                Abstract

     Three year-old eastern white pine (Pinus
strobus) seedlings were fumigated with sulfur
dioxide (SO2) for 4 hours daily for 9 days during
the time of new needle emergence at levels of
0.5,  0.8 and >1.0 ppm.  Low-level damage
appeared as chlorotic mottled regions in distal
needle portions.  Higher level fumigation re-
sulted in complete necrosis of the needles which
progressed basipetally. The transition between
the necrotic  brown and the living green tissues
was  abrupt.  However, no detectable surface
differences  were noted, the damage being
confined to subepidermal tissues.  Distinct dif-
ferences were observed in the elemental com-
position of affected needles on opposite sides
of the transition zone.

              Introduction

     The alteration of foliar structure due to air
pollution damage generally appears visibly as
lesions, mottling, or as widespread progressive
chlorosis and necrosis.  Such visible changes
often belie the  sudden and drastic  changes
observed in mesophyll tissues at the micro-
scopical level (Kravkina et a/., 1989; Maurice
and Crang, 1989; Crang and McQuattie, 1987).
While few observations have been made at the
cellular and subcellular level  of air pollutant-
induced damage, even fewer have been re-
corded of damage effects in gymnosperms.
Most of these  have  concentrated solely on
chloroplast responses within foliar tissues, or
on epicuticular wax deposits at the foliar surface
(e.g. Sutinen, 1986; Huttenen and Laine, 1983).
It is our intent to couple microscopy and analyti-
cal techniques in order to document the transi-
tion gradient from healthy to damaged first year
foliar structures in Pinus strobus as affected by
sulfur dioxide exposure.

         Materials and Methods

    Three year-old potted Pinus strobus seed-
lings were fumigated with sulfur dioxide (SO2) at
concentrations of 0.5, 0.8 and approx. 1.5 ppm
for 4 hours daily over a 9 day period. Fumiga-
tion was conducted in light-transparent CSTR
chambers under greenhouse  conditions.
Ambient conditions served as  the control.
                                                                                91

-------
R.E. Crang and A.E. Vassilyev and I.M. Kravkina
Needles from first year growth were removed
from plants at the conclusion of the fumigation
schedule and were air-dried (48 hr) for scanning
electron microscopy (SEM) and energy-disper-
sive x-ray microanalysis (EDX), or fixed and
embedded for transmission electron micros-
copy (TEM) as outlined by Kravkina etal. (1989).
1 -2 jam thick sections were obtained for light mi-
croscopy (LM) and were stained with 1 % aque-
ous toluidine blue for 30 seconds. Ultrathin sec-
tionsfor TEM were obtained from regions of em-
bedded specimens which were first observed
by LM.  The transition zone observed visually
was identified in  SEM preparations by a corre-
sponding mark on the supporting mount adja-
cent to the needles.

          Results and Discussion

     At SO2 concentrations of 0.5 and 0.8 ppm,
needle  tip burn  and chlorotic mottling  in the
distal portions were evident at the conclusion of
the experiment.  However, when  the level of
SO2 exceeded 1.0 ppm, a progressive necrosis
extended basipetally, with a sharp line of de-
marcation between it  and green  (apparently
healthy) needle regions (Fig. 1). Examination of
needles showing this  distinct transition zone
was made with the aid of the SEM, and revealed
no evident structural disturbance of the surface
waxes, epidermal integrity, or stomatal appear-
ance  (Fig. 2).  This indicated that all affected
tissues  were subepidermal, and that the route
of entry of SO2 was through normal  channels
(i.e. stomata), and not through disruptions of the
needle surface (Danilova etal., 1987).

     Needle segments taken from the transi-
tion zone were examined both by TEM (Figs.
3,4) and by LM  (Fig. 5).  In most cases, the
transition from healthy to  severely damaged
mesophyll cells was sudden, with adjacent cells
showing dramatic differences in ultrastructural
appearance. Figures 3 and 4showchloroplasts
from  adjacent cells in  which the  healthy-ap-
pearing plastid (Fig. 3) was seemingly identical
to those from control specimens  (ambient air
conditions).  The damaged plastids revealed
swelling and loss of substance within the stroma.
The thylakoid membranes were distended to
the point of disruption, but plastoglobuli per-
sisted (Fig. 4). While starch grains were some-
times found in the affected cells, their frequency
was less than in plastids on the green side of the
transition zone.

    This distinct demarcation within the meso-
phyll was documented in longitudinal sections
taken at  the site of the transition zone and
viewed with LM (Fig. 5).  Damaged cells were
collapsed  and revealed a loss of most proto-
plasmic substance. Details of the damage were
identical to those described by Kravkina et al.
(1989) with the exception that an even more
sudden change was induced by the higher
concentration of SO2 and the longer fumigation
schedule.

     Elemental determinations made by means
of EDX typically showed high levels of potas-
sium (K) on the green side of the transition zone
(Fig. 6) with lesser  emissions for silicon (Si),
chlorine (Cl) and calcium (Ca). Virtually identi-
cal spectra were obtained from control speci-
mens.  Presumably, Cl was complexed with K
and in organic molecules, while Si  and Ca
represented important elements in the cell wall
composition. Adjacent needle segments from
the brown (damaged) side of the transition zone
showed these same elements (with the excep-
tion of Cl), but also with significant quantities of
magnesium (Mg), phosphorus (P) and sulfur (S)
present (Fig. 7). In all cases, the peak-to-back-
ground ratios of the elements were greater than
those in spectra obtained from the green por-
tions of needles. This may be due to the greater
desiccation  in the  brown  region and would
explain why the background  emission  levels
were higher in the green regions (i.e. greater
residual water contributing to greater mass).

     It is entirely possible that Mg, P and S are
natural components of the needle tissues, but
which were not  observed in the green regions
 92

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    The Impact of Sulfur Dioxide Fumigation on Photosynthetic and Ultrastructural Responses of Mesophyll Cells in
                                                Developing Pinus strobus Needles. III.  Transition Zone.
because they simply were not sufficiently con-
centrated for EDX detection.  While it is tempt-
ing to state that the presence of S in the brown
regions is due to binding of that element from
the SO2 fumigation, it cannot be conclusively
determined by these experimental procedures.
However, S  peaks  in fully-desiccated control
needles were only barely perceptible and did
not possess  peak-to-background ratios higher
than 1.2, a value generally not considered to be
significant. No explanation can be given for the
lack of Cl in the brown needle regions.

     This study reveals that the transition of
foliar damage in P. strobus needles is related to
the SO2 dose levels and, at the higher concen-
tration,   surface  structure is unaffected  but
mesophyll collapse is sudden, resulting  in ex-
tensive cytoplasmic damage and a distinctive
change in the pattern of elements detectable by
EDX. The correlation of these results is conclu-
sive. Of particular interest was the recovery of
plants almost completely damaged by fumiga-
tion with >1.0 ppm SO2.  New, normal-appear-
ing needles were found to emerge later in the
same growing season, indicating that the new
growth  and  meristematic activities were  not
permanently damaged.

             Acknowledg ments

     The authors thank Dr. Anthony Endress
and Ms. Sue Post of the University of Illinois for
assistance in the fumigation of plants. Partial
support for this investigation was provided by a
grant from the Electric Power Research  Insti-
tute (Palo Alto, CA), and by  a grant from  Dr.
Anthony Joseph (Columbus, OH).

               Literature Cited

Kravkina, I.M.,  E.A. Miroslavov, and R.E. Crang.  1989.
    The impact of sulfur dioxide fumigation on the ultras-
    tructure and  photosynthesis of pine  needles.  I.
    Mesophyll cells. In: EPA/USDA2ndlnt.Symp.onAir
    Pollution Effects on Vegetation. (Raleigh, NC).

Maurice, C.G., and R. E. Crang.  1989.  Foliar injury and
    shoot growth in response to prolonged acidic misting
    of Pinus strobus seedlings. Arch. Environ. Contam.
    Toxicol. 18:277-284.

Crang, R.E., and  C.J. McQuattie. 1987. A quantitative
    light microscopic technique to assess the impact of
    air pollutants on foliar structure. Trans. Am. Microsc.
    Soc. 106:164-172.

Sutinen.S. 1986. Ultrastructure of mesophyll cells in and
    near necrotic spots on otherwise green needles of
    Norway spruce. Europ. J. Forest Path. 16:379-384.

Huttenen, S., and K. Laine. 1983. Effects of air-borne
    pollutants on the  surface wax structure of Pinus
    sylvestris needles. Ann. Bot. Fennici 20:79-86.

Danilova, M.F., I.M. Kravkina, R. E. Crang, and D. Pechak.
    1987.  Ultrastructure of stomata and leaf surface in
    Populus deltoides (Salicaceae) under SO2 influence.
    Bot. J. USSR Acad. Sci. 72:1187-1194.
                                                                                            93

-------
R.E. Crang and A.E. Vassilyev and I.M. Kravkina
 Figure 1. Macroscopic view of first year needles of P. strobus exhibiting abrupt transition zone (arrow) above fascicular
           sheath.

 Figure 2. Scanning electron microscopic view of transition zone in which no observable surface damage can be found
           in either proximal (P) or distal (D) regions adjacent to the sudden transition of damage (arrows). Bar = 0.1
           mm.

 Figure 3. Normal-appearing plastid in plicate mesophyll cell viewed with transmission electron microscopy Bar = 0.5
          |j.m.

 Figure 4. Highly damaged plastid in adjacent cell to that of Fig. 3.  Bar = 0.5 um

 Figure 5. Light micrograph of longitudinal section of needle as in above figures showing sudden transition from healthy
          cells (left) to damaged cells (right).  Bar = 0.1 mm.
  94

-------
The Impact ot Sulfur Dioxide Fumigation on Photosynthetic and Ultrastructural Responses ot Mesophyll Cells in
                                                 Developing Pinus strobus Needles  III  Transition Zone


                                                                                                  95

-------
R.E. CrangandA.E.  Vassilyev and I.M. Kravkina
                 Figure 6. EDX spectrum of elements found on green portions of SO2-fumigated
                           needle.  Element peaks are (left to right): Si, Cl, K and Ca.
                 Figure 7. EDX spectrum of elements found on brown ( necrotic) portions of
                         SO2-fumigated needle.  Spectrum is from same needle as in Figure 6.
                         Elements (from left to right) are: Mg, Si, P, S, K and Ca. Scale is same
                         as in figure 6.
  96

-------
  Ozone Concentration in  Leaf Intercellulars is close to Zero
                              Agu Laisk and Heino Moldau
                         Institute of Astrophysics and Atmospheric Physics,
                                     202444 Toravere,
                                  Tartu, Estonia, U.S.S.R.

                                       Olevi Kull
                                    Tartu State University
                             Laboratory of Ecosystems, 611 Tiigi St.,
                               202400 Tartu, Estonia, U.S.S.R.
                 Abstract

     Transpiration and ozone uptake rates were
 measured simultaneously in sunflower leaves
 at different stomatal openings  and ambient
 ozone concentrations.   Ozone  uptake rates
 were proportional to the ozone concentration
 up to 1500 ppb. The leaf gas phase (stomatal
 plus boundary layer) resistance for water vapor
 r  was calculated and converted to the resis-
 gw
 tance for ozone r z multiplying it by the theoreti-
 cal ratio of diffusion coefficients for water vapor
 and ozone in air (1.67).  The ozone concentra-
 tion in intercellulars calculated from the ozone
 uptake rate and r z scattered around zero. The
 ozone concentration in intercellulars was meas-
 ured directly by supplying ozone to the leaf from
 one  side and measuring the equilibrium con-
 centration above the other side,  and  it  was
 found to be zero. The total leaf resistance for
 ozone was proportional to the gas phase resis-
tance for water vapor with a coefficient of 1.68.

     It is concluded that ozone enters the leaf
by diffusion through stomata, and  it is rapidly
decomposed in cell walls and the plasmalemma
region.

     Plants are sensitive to atmospheric ozone
which causes the reduction of their growth rate
(Kress and Skelly, 1982; Miller et a/.,  1982).
Photosynthesis was reported to be reduced by
the presence of ozone before the symptoms of
damage were visible in leaves (Lehnherr etal.,
1987). In Scotch pines, the ozone uptake rate
was closely correlated with transpiration, sug-
gesting that the main route of ozone into the leaf
was  through  stomata (Skarby et al.,  1987).
These data suggest that stomata is the main, if
not the only route, of entering ozone into leaf
intercellulars  (Heath, 1980).   Obviously, the
physical process of ozone transport is diffusion,
like it is for water vapor and CO2, and this makes
it possible to calculate the actual concentration
of ozone in leaf intercellulars.

                 Theory

     The method of calculating the intercellular
CO concentration is widespread and we applied
                                                                                    97

-------
Agu Laisk, He/no Moldau and Olevi Kull
the same technique for calculating the inter-    and CO2 in the leaf gaseous pathway was
cellular O3 concentration.  It is based on the
knowledge that in the gas phase of intercellulars,
stomatal  pores, and leaf boundary layer, the
diffusion  pathways  of CO2 and water vapor
coincide to a great extent. The measurements
of the leaf transpiration rate reveal information
about  the diffusion resistance of the whole
gaseous pathway from cell surfaces to ambient
air:
          A -A.
A.-
      E =
                  or
             gw
                                     (1)
where, E is the transpiration rate (minus cuticu-
lar transpiration), r  , the diffusion resistance in
the leaf gaseous phase for water vapor, k., the
water vapor concentration at evaporating cell
surfaces, and Aa, that in the ambient air. Usually
we can assume that A is close to the saturating
water vapor concentration at leaf temperature
                A = A(t,)
          (2)
where A(^) is the saturating water vapor con-
centration as a function of leaf temperature tr
CO2 is a heavier gas (Mw = 44) than water vapor
(Mw = 18), therefore, CO2 is moving more slowly
than water vapor through the same diffusion
pathway and at the same concentration differ-
ences.  The ratio of the diffusion rates of H2O
                   ClI IU  V-'Vo  I" LI IG IC7C1I  IJCIOC7UUO  ^j
                   measured to be 1.62 (Oja, 1972).

                        We could not find a value of the diffusion
                   constant for ozone in  air, Dz, in the literature.
                   However,  diffusion constants for various gas
                   mixtures may be calculated using the molecular
                   parameters of component gases (Chen and
                   Othmer, 1962).
                                                        0.43:
                   °12 =
                        P x
                               10
                 0.1405  |~.     °-4      -°-4T
                         VK1
                               "' 100
                                                        (3)
where, M, T, Tk> Vk, P are, correspondingly, mo-
lecular weight (g/mol), temperature (°K), critical
temperature (°K), critical volume (cnWmol) of a
component gas, and atmospheric pressure (bar).
Indices 1 and 2 denote component gases. Using
values M, = 29 g/mol, Tk1 = 132.3 °K and Vk1 =
87.88 cm3/mol for air  (Hodgman and Weast,
1955-56, p. 2121) and M2 = 48 g/mol, T^ = 260.9
°K, V^ = 147.1 cnWmol for ozone (Weast, 1982-
83, p. F65) we get at p = 1 bar and T = 298 °K
a value of D2 = 0.137 cm2/s.  Inserting parame-
ters for water vapor M2 = 18 g/mol, T^ = 647.1
°K, V^ = 55.56 crrvVmol (Weast,  1982-83, p.

T> T
air — MIX 1 	 (f
T T ci "-
02 N2
LC
/
-y^
<•)—
j^/

ch e xch
I HO CO2 O3
i 111
> * 	 J 	 MIX 2 I*- air
C2 / T T
°2 N2
/
                    	^PS
            Figure 1. Basic circuit of the two-channel leaf gas chamber exchange measurement system
 98

-------
                                            Ozone Concentration in Leaf Interce/lulars is dose to Zero
                                                                 2000    J1000
       Figure 2. Parallel measurement of photosynthesis, transpiration and ozone uptake in a sunflower leaf
 F74) into the same formula yielded  Dw = 0.229
 crrWs. Therefore, Eq. (3) gives the ratio of the
 diffusion coefficients of ozone and water vapor
 Dw/Dz = 1.67 The diffusion resistance for ozone
 in the leaf gas phase can be calculated as
                                     (4)
where rgz and r w are gas phase resistances for
ozone and water vapor, correspondingly, and
Dw and D2 are diffusion constants  for water
vapor and ozone in air. Now it is possible to cal-
culate the ozone concentration in intercellulars
from the measured ozone uptake rate:
            Z , = Z  - Q x r
(5)
where Z is the ozone concentration in ambient
(a) and intercellular (i) air, Q is the ozone uptake
rate, rgz is from Eq. (4).  The ozone uptake rate
Q is measured as
           Q =
                                     (6)
where Z, and Z,, are ozone concentrations at the
inlet and outlet of the leaf chamber, V, gas flow
rate, and S, leaf area. Eq-s (1 to 6) are given in
their basic form. The correction terms were in-
cluded in practical calculations to account for
the bulk flow of gas out of the leaf due to evapo-
ration (Laisk, 1977; Parkinson and Penman,
1970).

          Materials and Methods

     Sunflower (Helianthus  annuus  L) and
Perilla ocymoides L. plants were grown in pots
filled with soil on laboratory windows in summer.
Upper  full-grown  leaves  were used  in
experiments. The apparatus for measuring leaf
CO2 and water vapor exchange rates has been
described  by  Oja  (1983).    For  present
experiments, a  self-made corona-discharge
ozone generator was added to the system.  In
principle,  the  apparatus contains two open
systems for measuring leaf gas exchange (below
referred  to  as  channels) in  which the gas
composition can be adjusted independently by
means of gas mixers MIX (Fig. 1). For adding
CO2 and O3, capillaries are used, and the rate of
injection of these gases into the carrier gas
stream is controlled by pressure differences on
those capillaries. A sandwich type leaf chamber
LC (4.4  x 4.4 x 0.3 cm, flow rate 20 cm3/s) can
rapidly be switched into the chain of either the
first or the second  channel by the "channel
exchange"valve. Infrared CO2 analyzers "Infralyt
IV" (GDR)  are  used for CO2, self-made
                                                                                      99

-------
Agu Laisk, Heino Moldau and Olevi Kull
   Q

   60
                500          1000     Z
              ozone concentration . ppb
    Figure 3.  Dependences of ozone uptake rates Q
             on ozone concentration in two sun-
             flower leaves

micropsychrometers for water vapor, and a
Dasibi model 1003 AH analyzer for ozone.
Volumes in the gas circuit are all reduced to the
minimum.   This  guarantees a full-deflection
response time of the system within 2.3 s (except
for ozone).

                  Results

The measurement of the ozone uptake rate. A
sunflower leaf was fitted into the leaf chamber,
                                              and the chamber was connected to the channel
                                              containing no ozone; CO2 concentration was
                                              320  ul/l,  irradiation density  30 mW/cm2, leaf
                                              temperature 23°C. The chart recording of the
                                              psychrometer line reflected the time course of
                                              the stomatal opening, and the CO2 uptake rate
                                              characterized photosynthesis (Fig. 2).  At the
                                              same time, the ozone analyzer recorded the
                                              ozone concentration in the gas stream, as there
                                              was  no leaf chamber in the circuit of that chan-
                                              nel (a small drift was caused by the instabilities
                                              of the ozone  generator).  Periodically, the leaf
                                              chamber was "flopped over" to the channel with
                                              ozone (points denoted by A to H).  Then the
                                              ozone concentration at the outlet of the leaf
                                              chamber rapidly declined showing its uptake by
                                              the leaf. There was a small uptake of ozone by
                                              chamber walls measured at A without a leaf.

                                              The  dependence of the ozone uptake rate on
                                              the  ozone concentration  was measured by
                                              changing the ozone concentration in the gas
                                              entering the leaf chamber (G, F, H. Fig. 2). The
                                              results are shown in Fig. 3, curve 1; another
                                              similar experiment is shown  by curve 2. In the
                                              first  experiment,  the ozone uptake rate was
                                              exactly proportional to the ozone concentration.
                                              In curve 2, the point at the highest concentration
                                              declined  from the proportionality, but the rea-
                                              son for this was an increase  in the stomatal re-
                                              sistance  (the values of the leaf gas  phase
Table 1.  Calculation of resistances and intercellular ozone concentrations for the experiment in Fig. 2.

      Q is the ozone uptake rate; r^, leaf gas phase resistance for water vapor; r^, gas phase resistance for ozone
calculated from r^ (Eq. 4); rz, resistance for ozone, calculated from the ozone uptake rate; Zj, calculated ozone
concentration in intercellulars.
            [oj    [cy           Q
Point        ppb   pmol/cm3    pmol/cm2/s
                                                  s/cm
s/cm    s/cm
7..
pmol/cm3
A
B
C
D
E
F
G
H
723
733
691
665
675
660
306
1492
29.0
29.42
27.77
26.32
27.12
26.52
12.30
63.98
1.058
6.13
12.36
14.81
16.51
16.51
7.96
37.03

4.15
1.55
1.22
1.07
1.01
1.00
0.98

6.93
2.59
2.04
1.78
1.69
1.67
1.64
27.5
4.83
2.28
1.85
1.69
1.66
1.59
1.67

-4.59
1.32
1.66
-0.35
0.43
-0.16
7.55
  100

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                                             Ozone Concentration in Leaf Intercellulars is close to Zero
Table 2. The measurement of the intercellular ozone concentration in a sunflower leaf.

      Ozone was supplied to the leaf from the lower side, and the evolution of ozone through the upper epidermis
was measured. Denotations: r^, leaf gas phase resistance for water vapor; Q, ozone exchange rate.
s/cm
Lower side of the leaf
      [03]             Q
      ppb	pmol/cm2/s
                                                  s/cm
Upper side of the leaf
      [°J              Q
      ppb	pmol/cm2/s
2.36
2.96
709
1790
8.93
17.96
5.30
4.17
0
0
0
0
resistance are shown at each point). After a cor-
rection for increased resistance, the point (in
parentheses) fits well the proportionality. The
proportionality between  the ozone concentra-
tion  and its absorption rate  shows that the
reaction of ozone degradation in leaf cells is a
simple first-order reaction, and that it does not
involve a saturating (enzymatic) process.

The  dependence between conductances for
ozone and water vapor. The first-order kinetics
of ozone uptake justifies our application of the
resistance/conductance approach and the cal-
culation of total leaf conductances for ozone
                                      (7)
where Za is the ambient ozone concentration,
and  Q is the uptake  rate.   In the linear-flow
chamber, the ambient ozone concentration is
                    Z1+Z2
                                      (8)
where Z1 and Z2 are concentrations at inlet and
outlet ports.  Combining  Eq. (7) with Eqs. (6)
and (8) we find
                  Z1-Z2
          3z = 2xzTz
                  ^-, -I- Z-2
                           xs
                                      (9)
     In our linear-flow chamber, Z2 = 0.5Z1 at
the greatest stomatal openings, and  the as-
sumption that the ambient concentration is the
arithmetic mean between the inlet and outlet is
not absolutely correct, as the actual profile of
concentration in the chamber is closer to expo-
nential than to linear.  Nevertheless, the error
                                              caused by this assumption does not exceed 3%
                                              of g2 calculated from Eq. (9) (personal commu-
                                              nication with V. Oja), and that correction term
                                              was also taken into  account.  The obtained
                                              values of rz are given in Table 1.

                                                   From Fig. 2 one can see that the ozone
                                              uptake  rate increases in parallel with the tran-
                                              spiration rate. The conductance for ozone QZ =
                                              1/rz is plotted against the gas phase conduc-
                                              tance g   = 1/r  in  Fig. 4. The relationship is
                                              fully linear up to the highest stomatal openings
                                              observed.  The ozone conductance extrapo-
                                              lates to zero at a small value for ozone conduc-
                                              tance.  This residual conductance was mainly
                                              caused by the absorption of ozone by chamber
                                              walls and tubing (Fig. 2, A).  After subtracting
                                              this conductivity (0.035 cm/s) from the total, the
                                              slope of the line does not change,  but the inter-
                                              ception point moves very close to the origin of
                                                                   0.5
                                                           conductace for
                                                                           cm/s
                                              Figure 4. Relationship between the leaf gas phase
                                                       conductance for water vapor g^ and the
                                                       conductance for ozone gjn sunflower
                                                       leaves
                                                                                       101

-------
Agu Laisk, Heino Moldau and Olevi Kull
axes. Evidently, there was no, or there was very
little, cuticular uptake of ozone observed in our
experiments with sunflower leaves.  The pro-
portionality between the conductances for wa-
ter vapor and ozone suggests that the diffusion
paths for both gases fully coincide, and that
there is no additional resistance for ozone in the
liquid phase of cells. Evidently, ozone actively
reacts with chemical substances in cell walls
and  plasmalemma, and  it undergoes rapid
degradation.  This means that the ozone con-
centration in leaf intercellulars must be close to
zero.

Ozone concentration in leaf intercellulars. Table
1 lists the  values  of the  intercellular ozone
concentration Z calculated from transpiration
and  ozone  uptake rates and Eq. (5).  Though
there is some scattering of data, one can see
that  at different stomatal openings, Z. stays
quite close  to zero independent of the ambient
ozone concentration applied in the range up to
1.5 ppm.

     Results given in Table 1 were obtained by
using Eq. (4) and the calculated theoretical ratio
of diffusion coefficients for water vapor and
ozone.  Actually, the diffusion rate will not de-
pend only on the diffusion coefficient, but also
on the dimensions of the diffusion pathway if the
latter were getting close to the free path of mole-
cules (so called Knudsen diffusion). The role of
the Knudsen diffusion is quite difficult to esti-
mate theoretically and, therefore, direct meas-
urements of the ozone concentration in leaf
intercellulars are welcome. The method ap-
plied below was first used  by  Oja  (1972) for
determining the CO2 concentration in leaf inter-
cellulars. If an amphistomatous leaf is exposed
to ozone from one side,  some of the ozone
molecules  should  diffuse out from the leaf
through the stomata of the other side if ozone
concentration in intercellular spaces is different
from zero.  The measurements of the ozone
evolution from that side  provide information for
calculating  the real ozone concentration in in-
tercellulars. To carry out  this experiment, the
two-channel system (Fig. 1) was rearranged for
using it together with a two-sided leaf chamber.
One side of the chamber was connected into
the circuit of one channel, and the other side into
the other channel. Ozone was supplied into the
gas stream at the physiologically lower side of
the sunflower  or  perilla leaf while the ozone
analyzer could be reswitched between the chan-
nels.  Stomata on both sides  of the leaf were
open  enough to allow  a  sufficient ozone ex-
change.  There occurred a significant ozone
uptake from the lower leaf side, but no ozone
evolution through the  upper epidermis was
detected in a sunflower (Table 2) as well as in a
Perilla leaf {data not shown).  This shows that
the ozone concentration is really negligibly low
in  intercellular air spaces at the substomatal
cavities of the upper side of  the leaf in case
ozone is supplied from the lower side.

               Discussion

     From these results, we can conclude that
ozone enters the leaf through stomata by diffu-
sion; it confirms a more indirect evidence (Gud-
erian era/., 1987; Skarby eta/., 1987), and is in
accordance with conclusions  drawn by Heath
(1980) in his review. The ozone concentration
in intercellular spaces is extremely low irrespec-
tive of the  ambient concentration of ozone
applied (up to 1.5 ppm).  This means that ozone
is  absorbed and  rapidly  decomposed in cell
walls or plasmalemma region, and it does not
penetrate into the deeper layers of cells. The
ozone uptake rate Q can be calculated from the
conductance for water vapor and the ratio of the
measured diffusion  rates for water vapor and
ozone as
            Q = Z  x
9^1-68
(10)
where Za is the ambient ozone concentration,
and g^, the gas phase conductance for water
vapor. Moldau and Sober (personal communi-
cation) found a significant component of tran-
spiration in bean leaves that was not accompa-
nied by the proportional ozone uptake, and they
 102

-------
                                              Ozone Concentration in Leaf Intercellulars is close to Zero
identified it as the cuticular transpiration.  In our
experiments with short-time exposures to ozone,
the cuticular transpiration of sunflower leaves
was either very small, or it was accompanied by
cuticular ozone  uptake.  Probably long  expo-
sures under high ozone concentrations dam-
age cuticula causing increased cuticular tran-
spiration.

     There occurred no detectable ozone  flux
through the leaf which may mean that ozone is
rapidly decomposed already in stomatal  pores
or substomatal cavities. The rapid decomposi-
tion of ozone must cause oxidation processes
which damage cell  walls and  plasmalemma.
The reflection coefficients of plastid membranes
were  reduced in the presence of ozone,  the
introduction of ozone into a culture of Chorella
cells caused a 15- to  20-fold increase  in  the
efflux of potassium  (review  in  Heath, 1980).
Sober (in press) has shown that the properties
of the cell walls  and/or plasmalemma of bean
leaves changes after rather short exposures to
ozone.  The elasticity modulus of the walls in-
creased, the stretchability of  cells decreased.

     The tolerance of plants  to ozone  has  two
different mechanisms.  One is based on  the
stomatal closure in response to higher ozone
concentrations and  operates on the basis of
suppressing the ozone flux into the leaf. This
brings along  a considerable reduction in  the
CO2 uptake rate and a decrease in the growth
rate and plant yield. The other way to withstand
higher ozone concentrations is to  develop a
mechanism for the neutralization of the damage
caused by ozone for living cells. Evidently,  this
mechanism involves the resynthesis of dam-
aged  enzyme molecules or membrane frac-
tions, and it  causes increased maintenance/
reparation energy costs accompanied by higher
respiration rates (Skarby et  a/., 1987; Heath,
1980). In future perspectives, the studies of the
effect of ozone  on plants should lead to  the
establishment of a reparation cost of one ozone
molecule in a number of respired CO2  mole-
cules.
            Acknowledgements

     This work was carried out under Project
20.03-21 of the joint U.S.A.-U.S.S.R. Commis-
sion,  "Effects of air pollutants  on plant cover
including forest ecosystems." Authors express
their gratitude to the Project leaders, Professor
R. Noble (Bowling Green State University, Ohio,
U.S.A.),  and  Dr. J. Martin (Tallinn Botanical
Gardens, Estonia,  U.S.S.R.) for encouraging
discussions, as well as to Professor. K. Jensen
(U.S. Forest Research Lab., Delaware, Ohio)
for providing the ozone analyzer, and to Dr. V.
Oja for suggesting the design of the ozone gen-
erator.

              Literature Cited

Chen, N.H., and D.F.Othmer. 1962. J. Chem. Eng. Data
   Vol. 7, 1:p. 37.

Guderian, R. et al.  1987. Effects  of photochemical
   oxidants on plants. Ecol. Studies 52.

Heath, R.L. 1980. Initial events in injury to plants by air
   pollutants. Ann. Rev. Plant Physiol. 31:395-431.

Hodgman, C.D., R.C. Weast, and S.M. Selby.  1955-
   1956. Handbook of Chemistry and Physics. Ed. 37.
   Chemical  Rubber  Pub. Co., Cleveland,  Ohio, p.
   2121.

Kress, L.V., andJ.M. Skelly. 1982.  Response of several
   eastern forest tree species to chronic doses of ozone
   and nitrogen dioxide. Plant Dis. 12:1149-1152.

Laisk,  A.  1977.  Kinetics of photosynthesis and pho-
   torespiration in  C3 plants.   Publ. House Nauka,
   Moscow (in Russian).

Lehnherr, B., A. Grandjean, F. Machler, and J. Fuhrer.
   1987. The effect of ozone in ambient air on ribuloseb-
   isphosphate carboxylase/oxygenase activity de-
   creases photosynthesis and grain yield in wheat. J.
   Plant Physiol. 130:189-200.

Miller,  P.R., O.C. Taylor, and R.G. Wilhour. 1982. Oxi-
   dant air pollution in the central valley, Sierra Nevada
   foothills and Mineral King valley of California. Atmos.
   Environ. 6:623-633.
                                                                                         103

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Agu Laisk, Heino Moldau and Olevi Kull
Oja,  V.  1972.  Experimental studies of the CO2 gas
   exchange in plant leaves. Cand. thesis.  Institute of
   Astrophysics and Atmospheric  Physics, Estonian
   Acad. Sci. Tartu (in Russian).

Oja,  V. 1983. A quick-operating gas measuring device
   for studying the kinetics of leaf photosynthesis. Fiziolo-
   gia Rastenii(Soviet Plant Physiol) 30:1045-1052 (in
   Russian).

Parkinson, K.J., and H.L. Penman.  1970.  A possible
   source of error in the estimation of stomatal resis-
   tance. J. Exptl. Bot. 21:405-409.

Skarby, L, E. Troeng, and C-A Bostrom. 1987.  Ozone
   uptake and effects on transpiration, net photosynthe-
   sis, and dark respiration in Scotch pine.  Forest Sci.
   33:801-808.

Sober, A.  Effects of ozone on water relations in  bean
   leaves. Plant Physiol. (in press).

Weast, R.C., ed. 1982-1983.  Handbook of Chemistry
and  Physics. Ed. 63 CRC Press, Boca Raton, Florida.

             Legends to Figures

Fig. 1. Basic circuit of the two-channel leaf gas exchange
measurement system.   LC, leaf chamber;  MIX1  and
MIX2, gas mixers; C, and C2, different CO2,  O2,  O3 and
water vapor concentrations in  the  gas mixtures; CH
EXCH, channel exchange valve for connecting the leaf
chamber into the circuit of either channel 1 or channel 2;
EQ, an equivalent resistance to the leaf chamber; EX, exit
valves for flushing the leaf chamber after channel ex-
changes; GA, infrared gas analyzers; PS, psychrome-
ters;  OA, ozone analyzer.
Fig. 2.  Parallel measurement of photosynthesis, transpi-
ration and ozone uptake in a sunflower leaf. E, transpi-
ration rate, nmol/cm2/s; P, CO2 uptake rate, nmol/cm2/s;
Z, ozone concentration, ppb, recorded by the ozone ana-
lyzer. In A to H, the leaf chamber was connected into the
gas stream of the channel containing ozone for about 3
min.  In A, the chamber was empty, before G the back-
ground ozone concentration was decreased to 400 ppb,
before H increased to 1930 ppb (note that at H the range
of the analyzer extends from 1000 to  2000 ppb). Leaf
temperature  23.1-C, PhAR density 30 mW/cm2.

Fig. 3.  Dependences of ozone uptake rates Q on ozone
concentration in two sunflower leaves. Leaf gas phase
resistance, s/cm shown at each point.

Fig. 4.  Relationship between the leaf gas phase conduc-
tance for water-vapor g^ and the conductance for ozone
gz in  sunflower leaves. Circles are from the experiment
in Fig.  2, crosses are from  other experiments; square
denotes ozone absorption by chamber walls.
  104

-------
   Ozone and the Winter Injury Hypothesis in Forest Decline

                                     J. R. Gumming
                        Department of Natural Resources, Cornell University
                                   Ithaca, New York, U.S.A.

                                       J. Fincher
            Boyce Thompson Institute for Plant Research and Section of Ecology and Systematics
                                     Cornell University
                                   Ithaca, New York, U.S.A.

                                      R. G. Alscher
                     Department of Plant Pathology, Physiology and Weed Science
                         Virginia Polytechnic Institute and State University
                                  Blacksburg, Virginia,  U.S.A.
     It has been proposed that forest declines
 in both Western Europe and North America are
 caused by the interaction of multiple stresses.
 One expression of this phenomenon appears to
 be an alteration  in foliar resistance to frost
 damage or winter desiccation (Johnson and
 Siccama, 1983,  1984; Friedland et al., 1984;
 Blank, 1985; Rehfuss,  1987; Johnson et al.,
 1988). In Germany, it has been suggested that
 ozone plays a central role in the decline phe-
 nomenon (Rehfuss, 1987) and accumulating
 experimental evidence suggests that this may
 be true. Brown etal. (1987) found that exposure
 of Norway spruce  seedlings to ozone levels,
 which produced no visible symptoms during the
 growing season, reduced the subsequent frost
 resistance of certain clones during the following
 autumn.  Air pollutants, then, may act to impair
 the physiological activities which underlie sea-
 sonal rhythms of active growth, dormancy and
 hardening (Davison and Barnes, 1987). How-
ever, to date little has been established con-
cerning effects of ozone on specific physiologi-
cal changes associated with the onset of dor-
mancy and cold tolerance.

     Aronsson et al. (1976)  demonstrated a
strong correlation of frost hardiness with changes
in the foliar carbohydrate content of both pine
and spruce (see also Parker,  1959). Growth
reductions in declining stands of Norway spruce
have  been attributed to changes in carbohy-
drate  source-sink relations (Oren et al., 1988)
and Bosch et al. (1983) showed that needles
harvested in November from  declining  trees
had relatively higher starch and lower raffinose
levels than did comparable needles from healthy
trees.  Because raffinose and other soluble
sugars are believed to act as foliar cryoprotec-
tants, an alteration in the amount or rate of pro-
duction of these compounds may lead to  in-
creased sensitivity to subfreezing temperatures.

    We are accumulating evidence that sup-
ports  the role of ozone exposure  in altering
winter hardening processes in red spruce seed-

                                       105

-------
J.R. Gumming, J. Fincher and R.G. Alscher
lings.  Seedlings exposed to levels of ozone
ranging from 0.4 to 3.0 times ambient ozone
levels in Ithaca, New York, USA, exhibited no
detectable changes in physiology during the
season of active growth. However, in  Decem-
ber, significant anatomical alterations were found
in spite of the fact that no classic visible symp-
toms appeared on the current year foliage. A
cross-section from a needle of a seedling grown
in charcoal-filtered air taken  in  December
showed that many of the vacuoles were  filled
with tannins and multiple layers of chloroplasts
were present (Plate 1).  In contrast, histological
examination of needles taken from the 3 times
ambient treatment indicated extensive  damage
had occurred to mesophyll cells (Plate  2).  This
damage included vesiculation and, at  its  most
extreme, total disruption of cells with breakage
of cell walls and leakage of contents into inter-
cellular spaces. A damage index based on the
proportion of cells injured in cross-sections of
these needles indicated that the proportion of
cells disrupted increased with increasing ozone
dose (P = 0.0175). Disruption of this nature was
not seen earlier in the season prior to  freezing
temperatures, and is hence considered to be
frost damage.

     In contrast to the  histological  evidence,
analysis of foliar pigments in December did not
exhibit  any  pattern suggestive of  an ozone-
freezing temperature interaction (Figures 1-3).
Following one winter in the field, however, chlo-
rophylls  a  and  b and  carotenoids  exhibited
trends which suggest that ozone exposure prior
to overwintering exacerbates the normal loss of
pigments which occur during exposure to freez-
ing temperatures (Figures 1-3).

     Polynomial  regression  analysis  of the
starch and soluble sugar content of foliage over
the seven-month exposure period indicated that
there was  a trend that was  not statistically
significant for decreased rate of change in the
total soluble carbohydrate pool in current year
needles (Table 1). In support of this finding, the
linear rate of accumulation of the sugar raffinose
during the  fall was found to  be significantly
reduced in trees exposed to ozone (P = 0.046;
Table 1). As such, it appears that ozone expo-
sure may impair normal  carbohydrate metabo-
lism  in foliage of red spruce seedlings, which
may contribute to their increased susceptibility
to frost damage.  It should be noted that, for the
entire population of seedlings, severe winter
injury symptoms, loss of foliage or necrosis of
the current year's foliage, did not develop in any
pattern  suggesting an  ozone-mediated re-
sponse.  However, of those plants that were
damaged, there  was a significant quadratic
relationship between  the natural logarithm of
the number of flushes with necrotic needles and
Table 1. Parameter estimates for needle soluble sugar cycling during seven months exposure to ozone.'
ozone
treatment
cf
1x
2x
3x
LSE2
Probability3
total soluble sugars
linear quadratic
8.08
7.59
7.31
7.49
0.44
0.343
0.744
0.558
0.448
0.461
0.094
0.058
raffinose
linear quadratic
0.568
0.323
0.449
0.028
0.136
0.046
0.154
0.444
0.872
0.561
0.275
0.163
      1 Parameter estimates for total soluble sugars determined from cubic polynomial regression over time;
        estimate for raffinose determined from quadratic polynomial regression over time.

      2 LSE = standard error of least square mean estimates.
      3 Probability of parameter estimates following linear dose-response to increasing ozone.
 106

-------
                                   Ozone and the Winter Injury Hypothesis in Forest Decline
         1 000 -
         '800-
        si

        g-600
        o>

        ^400
                                                         -O- May

                                                         -•- December
               0.00.40      1.0            2.0            3.0


                           treatment  (x  ambient  ozone)



Figure 1.  Effect of ozone exposure on chlorophyll a content of red spruce seedling

         foliage in December following fumigation and in May after overwintering

         following exposure.
           250
        3200-


        O>
        =  150H

        .c
        a
        o
        r
        "100-

        01
        a
            50
                   -0-May

                   -•- December
               0.00.40      1.0            2.0            3.0

                            treatment  (x  ambient  ozone)



 Figure 2. Effect of ozone exposure on chlorophyll b content of red spruce seedling

           foliage in December following fumigation and in May after overwinter-

           ing following exposure.
                                                                                  107

-------
J.Ft. Gumming, J. Fincher and R.G. Alscher
                      400 •
                      350-
                    O)

                    en
                    O  300 -
                    CD
                       250 -
                    O) 200 -
                       150
                              -O- May
                              -»- December
                           0.0  0.40      1.0             2.0
                                        treatment  (x  ambient  ozone)
                                                                         3.0
                    Figure 3. Effect of ozone exposure on total carotenoid content of red spruce
                             seedling foliage in December following fumigation and in May after
                             overwintering following exposure.
                      2.5
                   13
                   
-------
                                                  Ozone and the Winter Injury Hypothesis in Forest Decline
ozone level (Figure 4).

     The winter hardening process includes
the breakdown of  accumulated starch to form
raffinose and other soluble sugars which act as
cryoprotectants (Little, 1970; Senser etal., 1971,
1975; Soikkeli, 1978). Bosch etal. (1983) found
higher levels of starch in the needles of declin-
ing trees in the autumn, suggesting that  the
transition from the frost-sensitive to frost-toler-
ant state is impaired in declining trees. Whether
this is the result of exposure to airborne pollut-
ants  leading to increased  frost damage and
decline, or simply a secondary symptom of
declining trees is  yet to be  elucidated.  The
ultrastructural  evidence suggests that  ozone-
exposed needle cells were more susceptible to
winter injury than were cells from needles in the
charcoal-filtered environment.   It is hypothe-
sized that ozone alters carbohydrate metabo-
lism during the early phase of winter hardening
and results in a delay in the increase in cryopro-
tectants. Cells, which were unprepared for the
subfreezing temperatures of  late October and
November, would  be more  susceptible  to frost
injury. Although the root cause of this effect of
ozone is not yet apparent, some direct effect on
the initiation of hardening is possible.

               Literature Cited

Aronson,  A., T.  Ingestad, and L.  Lars-Gorau.  1976.
    Carbohydrate metabolism and frost hardiness in
    pine and spruce seedlings at different photoperiods
    and thermoperiods.  Phys/ologia Plantarum. 36:127-
    132.

Blank, L.W.  1985.   A new type of forest decline  in
    Germany. A/afure314:311-314.

Bosch, C., E. Pfannkuch, U. Baum, and K.E. Rehfuess.
    1983. Uber die Erkrankung der Fichte (Pices abies
    Karst) in den Hochlagen des Bayerischen Walden.
    Forstw. Clb. 102:167-181.

Brown, K.A., T.M. Roberts, and  L.W.  Blank.  1987.
    Interaction between ozone and cold sensitivity  in
    Norway spruce:  a factor contributing to the forest
    decline in Central Europe? New Phytologisl 105:149-
    155.
Davison, A.W., and J.D. Barnes.  1988.  How are the
   effects of air pollutants on agricultural crops influ-
   enced by the interaction with other limiting factors?
   Effects of winter stress on pollutant responses. In
   Proceedings,  1986 Commission of the  European
   Communities and the National Agency of Environ-
   mental Protection; 1986 March 23-25; England, in
   press.

Friedland et al. 1984.  Winter damage to foliage as a
   factor in red spruce decline.  Canadian Journal of
   Forest Research 14:963-965.

Johnson, A.M., E.R. Cook, and T.G. Siccama.  1988.
   Relationships between climate and red spruce growth
   and  decline.  Proc.  Nat. Academy  Sci., in press
   Johnson, A.M., and T.G. Siccama. 1983.   Acid
   deposition and forest decline.  Environmental Sci-
   ence and Technology 17:A294-A305.

Johnson, A.M., and T.G. Siccama.  1984. Decline of red
   spruce in the northern Appalachians: assessing the
   possible role of acid deposition. Tappi Journa/67:68-
   72.

Little, C.H.A.  1970. Seasonal changes in carbohydrate
   and moisture content in needles of balsam fir (Abies
   balsamea). Canadian Journal of Botany 48:2021 -
   2028.

Oren,  R., E.-D. Schutze, K.S. Werk, J. Meyer, B.U.
   Schneider, and H. Heilmeier. 1988. Performance of
   two Picea abies (L.) Karst stands at different stages
   of decline.  Oecologia 75:25-37.

Parker, J. 1959. Seasonal variation in sugars of conifers
   with  some observations on cold resistance. Forest
   Science 5:56-63.

Rehfuess, K.E.  1987. Perceptions on forest diseases in
   Central Europe. Foresfry60(1):1-11.

Senser, M., and E. Beck. 1984. Correlation of chloroplast
   ultrastructure and membrane lipid composition to the
   different degrees of frost resistance  achieved  in
   leaves of spinach, ivy, and spruce. J. Plant Physiol.
   117:41-55.

Senser,  M., F. Schotz, and E. Beck.  1975.  Seasonal
   changes  in structure and  function  of  spruce
   chloroplasts. Planta (Berlin) 126:1 -10.

Senser, M., P. Dittrich, O. Kandler, A. Thanbichler, and B.
   Kuhn.  1971.  Isotopenstudien uber den Einflua der
   Jahreszeit  auf  den  Oligosaccharidumsatz bei
   Coniferen.  Ber. Dtsch. Bot. Ges. Sand 84:445-455.
                                                                                              109

-------
 J.R. Gumming , J. Fincher and R.G. Alscher
 Soikkeli, S.   1978.  Seasonal  changes in mesophyll
    ultrastructure of needles of Norway spruce (Picea
    abies).  Canadian Journal of Botany 56:1932-1940.
 Plate 1.  A cross-section from a needle of a seedling grown in charcoal-filtered air taken in December.


                        5>
                        ,,

I


Plate 2.  Needles taken from the 3 times ambient treatment indicated extensive damage had occurred to mesophyll
         cells .

 110

-------
  Comparative Physiology and Morphology of Seedling  and
                            Mature Forest Trees
               B. M. Cregg, J. E. Halpin, P. M. Dougherty and R. O. Teskey
                              School of Forest Resources
                                 University of Georgia
                               Athens, GA 30602, U.S.A.
                 Introduction

     Much of the knowledge which has been
gained in the past decades concerning physio-
logical responses of forest tree species to their
environment has come from studies of tree
seedlings. This is particularly true in the study of
atmospheric pollutants since controlled expo-
sure of large, mature trees poses many logisti-
cal problems. Although most of the experimen-
tation in environmental physiology  has  been
conducted  on  seedlings, there is concern
whetherthe information can be used to make in-
trepretations for trees in other stages of devel-
opment. Thus, one of the important problems
facing researchers is determining in what re-
spects seedlings and mature trees are similar in
their responses to the environment.

     The objective of this paper is to highlight
differences  in the ecophysiology of seedlings
and  trees  which must be considered when
comparing their physiological or morphological
responses of seedlings and mature trees to
environmental stimuli.  This discussion is not
intended to be an exhaustive literature review of
seedling and mature tree physiology, but rather,
to point out how tree aging and development
might impact the extrapolation of data gathered
using seedlings.
                 Definitions

     According to Harlow and Harrar (1979) a
tree  is defined as "... a woody plant which at
maturity is 20 feet (6.1 m) or more in height with
a single trunk, unbranched for at least several
feet above the ground, and having  a more or
less definite crown." While most foresters and
plant scientists have a good notion of whether to
call a plant a seedling or a mature tree, there are
few formal definitions in the literature. For the
purposes of the present discussion, we shall
consider  a seedling  to be a tree which has
germinated from a seed (i.e. not a root sprout or
cutting), and is less than three years old. A ma-
ture tree  is defined here as a tree which pos-
sesses one or more of the mature traits of that
species,  such as cone or flower production,
natural pruning of lower branches, or the pro-
duction of mature wood. Trees which do not fit
into the either category are defined as saplings
and will not be considered in this article.

         Morphological Considerations

     The most obvious differences between
seedlings and trees are those dealing  with
scale. Seedlings, as  we are considering them
here, are typically less than one meter tall and

                                      111

-------
B.M. Cregg, J.E. Halpin, P.M. Dougherty and R.O. Teskey
   Height Above Ground (m)
u
12
10
           0.2       0.4       0.0
            Transmittance (l/lo)
                                        0.8
Figure 1. Patterns of photosynthetically active radiation
        (PAR) through a Pinustaedacanopy. Adapted
        from Sinclair and Knoerr, 1982.

have had distinct branch morphology for one or
two years. Mature trees, in contrast, may range
from 6 meters to over 100 meters for coast red-
wood (Sequoia sempervirens (D. Don) Endl.),
and typically have a well defined branch archi-
tecture. Light patterns through a tree canopy
within the forest usually follow a defined pattern
depending on the architecture of the species.
Sinclair and Knoerr (1982) examined the pat-
terns of photosynthetically active radiation (PAR)
in the canopy of a fifteen-year-old plantation of
loblolly  pine  (Pinus taeda  L).  As shown in
Figure 1, the proportion of incident radiation ob-
served at a given level relative to the PAR at the
top of the canopy (l/lo) decreased in a curvilin-
ear pattern down through  the canopy.

     Distinct differences in the morphological
and physiological characteristics of tree foliage
which may impact  gas exchange and the up-
take of gaseous pollutants are associated with
canopy position (Kramer and Kozlowski, 1979).
For example, Wong and  Dunin (1987)  found
that  the maximum rate of photosynthesis of
mature sun leaves (upper canopy) of Eucalyp-
tus maculata Hook, was more than  two times
that of shade leaves (lower canopy). Boardman
(1977) has  reported that chlorophyll content
and chloroplast structures differ in shade leaves
as compared to sun leaves. Other differences
include  changes  in specific leaf weight,  sto-
matal density, RUBP concentration, number of
pali sade layers, cuticle thickness and rates of
respiration.

     Sun and shade leaf variation in  seedlings
is small due to lack of mutual shading. However,
pronounced differences exist in the morphology
and physiology of primary and secondary foli-
age of certain conifers. Loblolly pine seedlings,
for example, have two distinct phases of growth.
Prior to the formation of the first terminal bud, a
loblolly pine seedling undergoes a free growth
phase. Subsequent to the formation of the first
terminal bud,  the  seedling enters the cyclic
growth phase (Williams, 1987). Shoot ontogeny
of first year growth includes seed germination,
cotyledon  emergence, primary needle forma-
tion, and subsequently, secondary needle for-
mation. The primary needles are singular while
the secondary needles  are arranged in  fas-
cicles of three. For most species, it is common
for seedlings to have multiple periods or foliage
expansion within a single year, while in trees,
the number of these periods is greatly reduced.
During the growth of foliage, the development of
the cuticle and changes in stomatal  activity
occur. These ontogenic changes are important
to  consider  when  studying the responses of
seedlings and trees to airborne pollutants since
the responses will affect the amount absorbed
by the foliage.

     The rate  of primary needle expansion in
red pine (P. resinosa Ait.) is dependent on the
photosynthetically active tissues of the cotyle-
dons  (Sasaki and Kozlowski,  1970). Bormann
(1956) showed that young pine seedlings with
both primary and  secondary needles reached
maximum rates of photosynthesis at lower light
intensity than those with predominantly secon-
 112

-------
                             Comparative Physiology and Morphology of Seed/ing and Mature Forest Trees
 dary needles. In trees, maximum rates of pho-
 tosynthesis are obtained in current year foliage
 that has fully expanded (Brix, 1971;  Rook and
 Carson, 1978).

       Estimates of the number of stomata per
 leaf indicate large variations in the number of
 stomata per leaf of seedlings and trees due to
 both genetic and environmental  influences. A
 study by Knauf and Bilan (1974) directly com-
 pared  the number of stomata between two-
 year-old seedlings and sixteen-year-old loblolly
 pine trees. The mature trees had approximately
 twice the stomata per leaf than the  seedlings
 due to an increased number  of stomata per
 square millimeter and an increase in the total
 surface area of the leaves. Other studies have
 reported densities between  141-161 stomata
 mm2 surface area for trees and 138-180  sto-
 mata mm"2 surface area for seedlings (Higgin-
 botham, 1974; Thames, 1963). However, it
 should be pointed out that even though the sto-
 matal density may not differ between the seed-
 lings and the trees, the overall number of sto-
 mata will increase with maturity due to an in-
 crease in leaf area. These differences could po-
 tentially impact the uptake  of an air pollutant
 because the stomates represent the point of
 entry of gases into the plant. Positive correla-
 tions have been demonstrated between ozone
 sensitivity and stomatal conductances  in  a
 number of tree species (Reich and Amundson,
 1985).

       In addition to differences in foliage, seed-
 lings and mature trees have roots with different
 abilities to exploit below ground resources. The
 water  relations of seedlings are often tightly
 coupled to the amount of available moisture in
 the uppermost layers of soil. This coupling
 tends to decrease as seedlings age. Sands and
 Nambiar (1984) examined the water relations of
 Pinus radiata D. Don seedlings planted in three
 consecutive years, with and without weed con-
 trol. No differences were found in the diurnal
 patterns of xylem pressure potential (XPP) be-
tween  the seedlings that had been planted in
three years on the weed-controlled and non-
controlled plots. However, seedlings that had
been in the field for only one or two years had
consistently more negative XPP when grown in
competition with weeds. This indicates that the
younger seedlings were unable to utilize water
sources which were available to the three-year-
old plants.

      The differences in seedling and mature
tree rooting intensity and  rooting volume will
also result in  differences  in their  capacity to
extract nutrients from the below ground envi-
ronments. In addition, the supply and demand
for nutrients vary with stand development. Allen
era/. (1988) presented a conceptual analysis of
nitrogen supply and demand over the course of
a typical rotation for P.  taeda (Fig.  2). Several
key points emerge from this  diagram.  Initially,
the nitrogen  supply of the site exceeds the
requirements of seedlings for nitrogen.  How-
ever, as the stand ages, the demand for nitro-
gen  increases while the ability of the site to
supply nitrogen  decreases.  This  results in a
deficit of available nitrogen  to meet the de-
mands of tree growth. Figure 2 also indicates
that as the stand ages, internal remobilization of
nitrogen becomes increasingly important. This
represents  a key difference in the response of
seedlings and trees because stresses such as
drought or air pollution often cause an increase
in  the rate of leaf senescence.  If early senes-
cence alters the amount of nitrogen which is
remobilized, it will significantly reduce the nutri-
ent supply for subsequent growth.

      Another important morphological differ-
ence between seedlings and trees, particularly
in conifers,  is the change which occurs in con-
ducting  elements as a tree matures. Figure 3
shows the  relationship of  earlywood  to  late-
wood production with age for P. echinata Mill.
Earlywood cells are thin-walled and have large
diameters and, therefore, have a greater capac-
ity for conducting water than thicker-walled late-
wood cells. For seedlings  of P. echinata, the
percent of latewood in the annual ring may be as
                                                                                     113

-------
B.M. Cregg, J.E. Halpin, P.M. Dougherty and R.O. Teskey
          100
           so
           60
           40
           20
               kg ha'1 year1
                                Potential requirement
                                            \
                                                    "  —  Actual requirement
               Remobilized
            -i I I I 11 I I 11
                                                              Uptake from soil
             0            5            10           16            20           2
                                       AGE (years)

Figure 2.  Conceptual relationship of soil nitrogen supply, remobilization and demand. Adapted from Allen etal., 1988.
low as 15 percent, while the latewood ratio may
be over 60 percent for trees older than 25 years.
Such large differences in the mature conducting
elements can be expected to exert a profound
influence on resistance to flow and the patterns
of water movement of the plants. Since specific
gravity is linearly related to the percent late-
wood in most species, changes in specific grav-
ity may be inversely related to changes in con-
ductivity  of xylem  elements. Panshin and de
Zeeuw (1980) reported that in most tree spe-
cies, the mature and juvenile xylem  differ in
              Ring Width (mm)
                  earlywood
                                           latewood
                              10               20
                                      Rings From Pith
                30
Figure 3. Relationship of earlywood and latewood with age for Pinus echinata. Adapted from McGinnes, 1963.

 114

-------
                             Comparative Physiology and Morphology of Seedling and Mature Forest Trees
 specific gravity.

         Physiological Considerations

     Many of the differences in seedling and
 mature tree morphology greatly impact physio-
 logical processes. Some of the processes in
 which  seedlings and trees may differ include
 photosynthesis, water relations, and transloca-
 tion.

                 Photosynthesis

     As discussed earlier, one of the primary
 differences between seedlings and trees with
 regard to photosynthesis  is the variation  be-
 tween  sun and  shade foliage.  In seedlings,
 relatively little mutual shading occurs, resulting
 in primarily sun foliage, while in trees,  a mosaic
 of foliage types occurs. Given that shade foliage
 has a  lower photosynthetic capacity  than sun
 foliage, it may be expected that in seedlings, the
 rate of photosynthesis per unit leaf area will tend
 to be greater than that for mature trees. Halpin
 (unpublished data) measured rates of net C°2
 exchange of seedlings and twelve year-old trees
 of  P   taeda  on the University of Georgia's
 Whitehall Forest near Athens, Georgia. Diurnal
 measurements of net C°2 exchange for a mid-
 summer day in 1988 are presented in  Figure 4.
These data suggest that the seedlings had a
higher rate of net photosynthesis in the morning
than the trees. By mid-afternoon, the rate of net
photosynthesis in the trees exceeded that of the
seedlings. The lower rates of photosynthesis in
the trees  were due to lower light levels that
occurred  in the canopy during  the  morning
hours.

      Teskey et  al. (1986) studied the  light
response  of loblolly pine seedlings (Table 1).
These data indicate that light saturation oc-
curred at  a PAR  levels of greater than 1400
umol rrr2s1. Higginbotham (1974) developed a
similar relationship for the net photosynthetic
light response of  fifteen-year-old loblolly pine
trees grown in the central Piedmont of North
Carolina (Table 1). Higginbotham measured
the rate of net photosynthesis for three canopy
levels at different light intensities in the stand. In
these trees, net phototsynthesis continued to
increase with increasing PAR up to 2200 umol
rrv2s1  He determined that the rate of net pho-
tosynthesis was higher in the middle portion of
the canopy than in the upper or lower levels.
This response resulted from greater mutual
shading in the upper branches caused by a
greater leaf area  per  flush  in that part of the
crown.
Table 1. Net photosynthesis of seedlings and tree canopy positions of 15 year old Pinus teada.

                              Net CO  exchange (umol rrr2 s1)
1 5-year-old tree
PAR
200
600
1000
1400
1800
2200
Seedlings
0.63
2.52
3.03
3.15
*
*
Upper
0.14
1.24
1.98
2.42
2.76
3.00
Middle
0.34
1.86
2.71
3.24
3.57
3.75
Lower
0.64
2.10
2.82
3.18
3.43
3.56
Note: PAR in umol m2 s'
Data from Higginbotham (1974) and Teskey et al. (1986)
                                                                                       115

-------
B.M. Cregg, J.E. Hatpin, P.M. Dougherty and R.O. Teskey
            Net Photosynthesis (umol CO2 nrr2
                  10:00
                                  12:00
     U:00
                                                                    16: OO
                                          Time
Figure 4. Diurnal pattern of net carbon gain of Pinus taeda seedlings and 12-year-old trees from Whitehall Forest,
        Georgia. Unpublished data from Halpin, 1988.
                Water relations

     In the summer of 1988, diurnal stomatal
conductance measurements were taken con-
currently on seedlings and trees at Whitehall
Forest, Georgia. The conductance readings for
the seedlings at 1000  h were 0.4 cm s~1 and
declined in a linear fashion to 0.1 cms~1 by 1600
h. The  mid-canopy foliage of the trees had
conductance readings of 0.15 cm s1 at 1000 h
which increased slightly by 1200 h and dropped
off by 1600 h to near zero.  These data indicate
that trees and  seedlings can be expected to
have different diurnal patterns of water use and
carbon gain due to differences in water availa-
bility between the shallowly rooted seedlings
and deeply rooted trees (Halpin, unpublished).

      Another  study  was performed at the
Whitehall  Forest to determine how rapidly the
seedlings  and  trees could recharge to their
predawn xylem pressure potential values after
sunset (Halpin  and Cregg, unpublished). Sto-
matal conductance was  measured from  late
afternoon  until stomatal closure occurred. For
both trees and seedlings, the conductance read-
ings were zero after sunset. The rate  of re-
charge, however, differed  between the  seed-
lings and the trees. By 2100 h, the seedlings
had recharged to their predawn xylem pressure
potential while the trees did not reach equilib-
rium until 2400 h. These results emphasize the
importance of morphological effects on internal
water relations.  The faster recovery  of the
seedlings may be due to several factors, such
as more rapid conductance of waterflow through
the xylem elements and a lower gravitational
potential. Also, the simple  branch structure of
the seedlings allows for relatively easy water
movement  as compared to the trees in  which
water must pass through several points of high
hydraulic resistance (Ewers and Zimmermann,
1984).

                 Translocation

     As with many of the  physiological  proc-
esses discussed  above,  the differences In
translocation of  carbohydrates and growth
regulators of seedlings and trees are largely
related to differences in anatomy and morphol-
ogy. Movement of phloem sap has been esti-
  116

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                               Comparative Physiology and Morphology of Seedling and Mature Forest Trees
mated to range from 100  to 200 cm hour in
angiosperms (Salisbury and Ross, 1969). This
rate represents  nearly instant  movement of
phloem sap for a seedling less than 1 meter tall.
However, assuming an intermediate rate of 150
cm hour1, carbohydrates produced  near the
apical shoot of a 50 meter tall Liriodendron tu-
lipifera L. would require nearly two days to reach
a potential storage site in the roots. Transport
rates of growth regulators, such as auxins, may
be  as low as 0.5 cm hour1 and, thus, require
long periods to move through a large mature
tree.

                    Summary

     At  the  level of physiological processes,
seedlings and trees  often  perform  similarly.
However, great differences exist in the com-
plexity of their structures and form  which may
lead to profound differences in the diurnal rates
of  processes and in their environmental re-
sponses. Another notable difference between
trees and seedlings is their carbon allocation
and use patterns. Mature trees  have a signifi-
cantly higher ratio of respiring to photosynthetic
tissue. Carbohydrate reserves also differ be-
tween trees and seedlings. These  result in
changes in the timing and duration of root and
shoot growth and differences in their ability to
recover from stresses.

     Extrapolation of information gathered on
seedlings must be cautiously used to interpret
tree responses to environmental stresses and
direct  comparisons must be made carefully.
The environments in which the seedlings and
trees grow  are substantially different due to
differences in rooting depth and  canopy struc-
ture. Trees  have the potential to significantly
alter their environments  (i.e. shade) whereas
seedlings do not. Consideration  must be given
to the process being examined since some will
be very similar while others will differ greatly. In
general,  the more gross the process, the larger
the potential for differences to exist between
seedlings and trees.
                 Literature Cited

Allen, H.L., P.M. Dougherty, and R.G. Campbell. 1988.
   Manipulation of Water and Nutrients - Practice and
   Opportunity in  Southern U. S. Pine  Forests. Forest
   Ecology and Management (in press).

Boardman, N.K. 1977. Comparative  photosynthesis of
   sun and shade plants. Annual Review of Plant Physi-
   ology 28: 355- 377.

Bormann, F.H.  1956. Ecological implications of changes
   in the photosynthetic response of  Pinus taeda seed-
   lings during ontogeny. Ecology 37: 70-75.

Brix, H. 1971. Effects of nitrogen fertilization on photosyn-
   thesis and respiration of Douglas-fir. Forest Science
   17:407-414.

Ewers, F.W. and M.H. Zimmermann. 1984. The hydraulic
   architecture of eastern hemlock (Tsuga canadensis).
   Canadian Journal of Botany 62(5):940-946.

Harlow, W.M., E.S. Harrar, and F.M. White. 1979.  Text-
   book of Dendrology. McGraw-Hill Book Company,
   New York,  New York, USA.

Higginbotham,  K.0.1974. The influence of canopy posi-
   tion and the age of leaf tissue on growth and photo-
   synthesis in loblolly pine. PhD. dissertation. Duke
   Univ. Durham, N.C.  USA.

Knauf, T.A. and M.V. Bilan. 1974. Needle variation on
   loblolly pine from mesic and xeric  seed sources.
   Forest Science 20: 88-90.

Kramer,  P.J. and T.T Kozlowski. 1979. Physiology of
   Woody Plants. Academic Press, Inc., Orlando, Flor-
   ida, USA.

McGinnes,  E.A. Jr. 1963. University of Missouri, Agric.
   Ext. Bull. 841. Columbia, Missouri, USA.

Panshin, A.J. andC.de Zeeuw. 1980.  Textbook of Wood
   Technology. 4th edition. McGraw-Hill Book Com-
   pany, New  York, New York, USA.

Reich, P.B. and R.G. Amundson. 1985. Ambient levels of
   ozone reduce  net photosynthesis in tree and crop
   species. Science 230:566-570.

Rook, D.A. and M.J. Carson. 1978.  Temperature and
   irradiance and the total daily photosynthesis of the
   crown of a Pinus radiata tree. Oecologia 36:371 -782.
                                                                                            117

-------
B.M. Cregg, J.E. Halpin, P.M. Dougherty and P.O. Teskey
Salisbury, F.B. and C. Ross. 1969. Plant Physiology.
    Wadsworth Publishing Company, Inc., Belmont, Cali-
    fornia, USA.

Sands, R. and E.K.S. Nambiar. 1984. Water relations of
    Pinus radiata in competition with weeds. Canadian
    Journal of Forest Research 14:233-237.

Sasaki, S. and T.T. Kozlowski. 1970. Effect of cotyledon
    and hypocotyl photosynthesis on growth  of young
    pine seedlings. New Phytologist 69: 493-500.

Sinclair, T.R. and  K.R. Knoerr.  1982. Distribution of
    photosynthetically active radiation in the canopy of a
    loblolly pine plantation. Journal of Applied Ecology
    19:183-191.
Teskey, R.O., J.A. Files, L.J. Samuelson and B.C. Bon-
    garten. 1986. Stomatal and nonstomatal limitations
    to net photosynthesis in Pinus taeda L. under differ-
    ent environmental conditions. Tree Physiology2:131-
    142.

Thames, J.L. 1963. Needle variation on loblolly pine from
    four geographic seed sources. Ecology 44:168-169.

Williams, C.G. 1987. The influence of shoot ontogeny on
    juvenile-mature correlations in loblolly pine. Forest
    Science 33:411-422.

Wong, S.C. and  F.X. Dunin.  1987. Photosynthesis and
    transpiration  in a eucalypt forest stand: CO2, light and
    humidity responses. Australian Journalof Plant Physi-
    ology 14:619-632.
 118

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     Mechanisms By Which Regional Air Pollutants Affect
    Forested Soils and  Rhizospheres:  The Significance of
                         Long-Term Perspectives

                                  Daniel D. Richter
                   School of Forestry and Environmental Studies, Duke University
                               Durham, North Carolina, U.S.A.

                              Michele M. Schoeneberger
                        Forestry Sciences Laboratory, US Forest Service
                         Research Triangle Park, North Carolina, U.S.A.
               Introduction

     The objective of this paper is to develop a
 long-term, broadly applicable, and critical per-
 spective about the mechanisms by which re-
 gional air pollution alters soil resources. The
 paper's intention is not to review the literature,
 but rather to emphasize the necessity for a long-
 term perspective of soil and ecosystem change,
 particularly with respect to those causing  forest
 declines. Long-term perspectives are essential
 to the management of  forest ecosystems in
 areas that are exposed to regional air pollut-
 ants.

     This paper is organized from the relatively
 well known to the unknown, and from the rela-
 tively simple to the complex. Two examples of
 forest declines are described initially to suggest
 the complexity  of evaluating how and why
 ecosystems change.  The paper is then divided
 into three parts to evaluate key mechanisms by
 which soils are affected by pollution. They are:
 (I) The changing chemistry, especially the acidi-
fication, of the bulk (whole) soil since relatively
good information exists for predicting that the
chemistry of most soils changes relatively slowly
in response to regional air pollution; (2) The
changing chemistry of the soil solution, which is
of much greater concern than the gross acidifi-
cation of whole soils, especially in  extremely
acid soils.  Although supported by chemical
theory, relatively little quantitative data exist to
document changes in solution chemistry of ex-
tremely acidic soils; (3) The changing dynamics
of the soil-root system, the rhizosphere, con-
cludes the paper.

     Interactive effects of pollutants on soil-root
relations are poorly understood yet critical to
determining how soil-plant systems respond to
air pollutants.

     Two Examples of Soil-Mediated
              Tree Declines

    We begin by describing two examples of
natural tree declines that are mediated by soil
processes. The examples are used to illustrate
that soil-mediated stresses of perennial eco-
                                                                                  119

-------
Daniel D. Richter and Michele M. Schoeneberger
systems are complex and may be expressed
only over the long term. The two examples also
demonstrate both the power and the limitations
of the scientific mind to  understand soil-plant
systems.

         Decline of Acacia in Kenya

     In the early 1960's, yellow-fever Acacia
trees  (A. xanthophloea) began to  die in  the
savannas at the foot of Mt. Kilimanjaro in the
Massai Amboseli Game Reserve. Trees were
gradually  replaced by sparse  grasses and
bushes. The forest decline was initially blamed
on  elephant damage and on overgrazing  by
Massai herders. A subsequent detailed analy-
sis  of climate, soils, hydrology, and historical
data (Western and Van Praet, 1973) indicated
that high rainfall over several years had ele-
vated saline water tables and increased soluble
salts in the root zone.   Salt-sensitive Acacia
trees  were replaced by relatively salt-tolerant
plants. Because rainfall is markedly  cyclic in
equatorial  Africa,  dominant plants in these
savanna  ecosystems appear to alternate be-
tween grasses and trees over decades-long
periods.

       Western white pine pole blight

     In the middle decades of the 20th century,
many stands of western white pine in the north-
western USA suffered declines associated with
root mortality and crown thinning. Causal fac-
tors for these physiological stresses were un-
certain but symptoms were strongly mediated
by soil conditions, e.g., problems were concen-
trated on sites with shallow, rocky soils (Leaphart
and Copeland, 1957).  Extrapolating the rela-
tion between growth to weather to the long-term
tree ring  record, Leaphart and Stage (1971)
described the years between 1916 and 1940 as
having the most adverse growing conditions in
the  last 300 years. In many stands, the disease
persisted for many years following the initial
environmental stresses, and growth of many
trees that did not die, did not recover from initial
stress. In  some stands the disease  was  not
  120
exhibited above-ground for many years follow-
ing the actual occurrence of stress.  These
examples demonstrate  that perennial  forest
systems, whether savanna woodland or humid
montane forest, require long-term perspective
for understanding basic ecosystem dynamics
and for implementing management.

    The Capacity of Soil Systems: The
     Changing Chemistry of Bulk Soil

     One important reason that dynamics of
forest ecosystems are expressed only over the
long term is that soil materials buffer and resist
chemical change. The capacity concept of soils
is  used to describe how a soil's solid phase
buffers chemical  change.  Capacity is often
contrasted with intensity, a distinction that dif-
ferentiates elemental content of soil solids (in
exchangeable or mineral forms) from the con-
centration or activity of  elements in solution,
respectively.   The concepts  are frequently
associated with soil acidity (i.e., exchangeable
acidity vs pH), but are  also applicable to all
elemental species that are distributed in both
solid and liquid phases.

     In terms of the capacity factors, the most
likely effect of acidic deposition is to increase

                 ANNUAL ATMOS INPUT 1
      EXCHANGEABLE
      BASE CATIONS 65
      EXCHANGEABLE
        ACIDITY 370
Figure 1.  Pool sizes of cations in a relatively poorly
         buffered soil. Exchangeable cations is shown
         in relation to 1 kmol/ha/yr, a moderately high
         input of acid deposition.

-------
                       Mechanisms By Which Regional Air Pollutants Affect Forested Soils and Rhizospheres
exchangeable acidity and to reduce exchange-
able base cations (Fig. 1). Figure 1 illustrates
the relative pool sizes of exchangeable cations
in a  poorly buffered soil  (after Reuss and
Johnson,  1986).   In most  soils,  substantial
changes in total exchangeable acidity cannot
be expected, except in soils that receive high
inputs of acid  over many decades.  Many soil
scientists suggest that acidic deposition affects
exchangeable acidity slowly in most soils, due
to the soils' capacity to buffer the dilute acid
inputs.  Despite the range  of  opinions, it is
important to view the capacity of the mineral soil
system as relatively resistant to change (Rich-
ter, 1986), as is illustrated in Figure 1 based
simply on relative pool sizes of soil cations.

     Although most  soils tend  to buffer soil
environments, not all soils have large buffer
capacities  compared to atmospheric inputs.
Low activity clays with  low cation  exchange
capacities can be acidified at moderate rates.
Such soils are not uncommon in the southeast-
ern USA.  An example of the natural acidifica-
                                  tion of a low activity clay soil is described  in
                                  Table 1  (Wells,  1980).   These unique data
                                  document how twenty years of pine plantation
                                  development  reduced base  saturation from
                                  about 40 to <10% in surface soils. Presumably
                                  acidic deposition would have analogous effects
                                  on similar soils. Other low buffer capacity soils
                                  of concern include extremely acidic soils that
                                  contain virtually no exchangeable nutrient cati-
                                  ons (Table 2).  These acid soils are most com-
                                  mon in high elevation humid ecosystems where
                                  soil  depth restricts rooting volumes.  Although
                                  not widely distributed, they do support unique
                                  and aesthetically valuable forest ecosystems.

                                         The Intensity of Soil Systems:
                                  The Changing Chemistry of Soil Solutions

                                       In terms of intensity factors, the most likely
                                  effects of regional air pollution is to alter cation
                                  chemistry of soil  solutions.  In regions  down-
                                  wind from industrialized  areas,  atmospheric
                                  deposition of sulfate has increased electrolytes
                                  in soil solutions by 0.1 to 0.5 mM/L over wide
Table 1. Chemical properties of an Appling series Udult at 5,11,15, and 20 years after planting of loblolly pine. Letters
       following numbers in each column indicate significant differences in soils sampled at different ages at p - 0.05
       (Wells, 1980).
Stand
 Age
Carbon
Nitrogen     pHw
              Extract             Exchangeable
                P        "Ca        Mg        K"
  5
 11
 15
 20
  0.52a
  0.48ab
  0.44b
  0.46b
                            ug/g
338a
280b
234c
229c
                                                      ug/g
0 to 7.5 cm depth
5.3a          46a        96a
5.0b          34b        63b
4.1 c          35b        37c
3.8d          32b        13d
12a
 8b
 6c
 4d
23a
19b
18b
13c
7.5 to15 cm depth
5
11
15
20
0.37a
0.37a
0.37a
0.38a
267a
21 9b
190c
187c
5.2a
5.0b
4.4c
4.3c
34a
31a
33a
32a
62a
47b
25c
22c
8a
5b
3c
3c
16a
14ab
14ab
11b
Notes: Soil pH was a water paste and extractable P was Bray No.2.
                                                                                       121

-------
Daniel D. Richter and Michele M. Schoeneberger
                                     ,
                                     5 23 30 22
                                 31 .  2B33    29 ,	2«
                                  40
      60           eo
Ezch AltCEC . 55
                        100
      Figure 2.  Release of exchangeable Al to soil solution in response to salt (BaCI2) added at 0.5 meq/L
areas of North America and Europe (Reuss and
Johnson,  1983).  Depending on a soil's  ex-
change complex, such concentrations may
depress pH of soil solutions due to cation  ex-
change reactions and the "salt effect" (Richter
et al., 1987).  In extremely acidic soils, these
increases in electrolytes may substantially ele-
vate aluminum in soil solutions  via cation  ex-
change (Dai and Richter, submitted). Data from
laboratory simulation of this exchange of alumi-
num into solution indicates that extremely acidic
soils have a marked ability to release aluminum
into  solution (Fig. 2).   Thus, although acidic
deposition  may not readily acidify acid soils
further, it may increase solution concentrations
of aluminum via cation exchange.  Short-term
concerns over acidic deposition effects should
be focused mainly on changes in intensity fac-
tors, i.e., soil solution changes, rather than on
changes in capacity. One very significant need,
for example, is to explain the highly variable
aluminum release  from extremely acid soils
(Fig- 2).

     Models are used  to  predict changes  in
intensity factors that result from acidic deposi-
tion. Many such models are based on theoreti-
cal calculations of cation exchange that have
little empirical documentation especially at ionic
concentrations that are  appropriate  to field
Table 2. Chemical concentrations and contents of rock-free soil from high elevation (>1500m) spruce-fir stands in
        the Black Mountains in western North Carolina (Richter et al., submitted).
Statistic

Mean, kMc/ha
CV, %
Exchangeable
Ca
6.4
38
Mg K
3.4 3.0
36 42
Ca
16.6
47
Total
Mg
336
47

K
169
50
Notes: CV % is coefficient of variation of 18 volumetric soil pits 2 in each of 9 stands.

 122

-------
                       Mechanisms By Which Regional Air Pollutants Affect Forested Soils and Rhizospheres
conditions. Figure 2 illustrates a large measure
of unexplained soil variation,  a variation not
accounted for in theoretical models. In contrast,
Figure 3 illustrates that different cations, e.g.,
aluminum  and magnesium, are displaced with
great predictability from soils that range widely
in their chemical properties.   Figure  3 also
indicates with empirical data that as electrolyte
concentrations increase in soil solution (from at-
mospheric deposition orfrom natural processes),
aluminum  is exchanged into solution in greater
proportion  than any other  nutrient  cation.
However, only in extremely acid soils is alumi-
num likely to be a dominant cation of soil solu-
tions (Fig.  2). Of course,  what  is yet to be well
understood is the biological significance of these
changes in the system's intensity.

       The Changing Dynamics of
            Soil-Root Systems

     Tree  health is intimately tied to the health
of its rhizosphere-root system -that narrow but
important continuum linking plant to soil.  Roots
function as the tree's nutrient and water uptake
and anchoring system,  as well  as providing
protection  from  soil-borne  pathogens,  and
sequestering  of potentially toxic elements.
Nutrient availability and root activity are in turn
defined by reactions in the rhizosphere.  Im-
pacts  of pollutants can potentially alter the
chemistry and activity of this region by either
soil-mediated or plant-mediated means (Table
3).  Such change in this soil-plant continuum will
have ramifications on nutrient uptake, disease
protection, water uptake, and nutrient cycling,
and thus on ecosystem stability. Several recent
reviews were used  in the formulation of this
paper  and have  been listed in the reference
section (Anon., 1986; Jansen etal., 1988; Mathy,
1988; NCASI, 1987; Visser etal., 1987).

     Understanding the rhizosphere-root
                 subsystem
     The rhizosphere is a zone of intense and
varied  microbial  activity ranging  from sapro-
phytic  to symbiotic to parasitic.  Soil nutrient
availability and plant uptake are dependent on
these  activities.  The activities  interact  and
fluctuate dramatically in time and space.  As


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                             Al-Mg Activity Ratio(0.46 mM C/L)

    Figure 3. Activity ratios of AI/Mg are relatively constant despite variation in ionic strength of soil solutions
                                                                                        123

-------
Daniel D. Richter and Michele M. Schoeneberger
Table 3. Hypothesized mechanisms of atmospheric deposition impact on rhizosphere-root system.
OZONE

Carbon partitioning effect
on root quantity and quality
    ACIDIC DEPOSITION

    Acid, N, and S inputs:  increased
    solubility of potentially toxic elements;
    increased leaching of nutrients and
    metals; alteration of nutrient balances.
 - Impact within plant without addition of other stresses
 1 Alteration of root growth and function
 ' Alteration of mycorrhizal formation and function
 ' Alteration of nodule formation and function

 - Impact on rhizosphere without addition of other stresses
 * Alteration of quantity and quality of root exudates
 ' Alteration of extracellular enzymes, i.e., phosphotases, siderophores
 ' Alteration of microbial community structure and function

 - Impact on rhizosphere-root system
 ' Alteration on nutrient cycling
 ' Alteration on nutrient availability
 ' Alteration on nutrient uptake
 ' Alteration of buffer/recovery capacity to additional pollutant impact and other stress, i.e., drought and disease
exposure to atmospheric pollutants may be a
temporary,  seasonal, or even an  infrequent
event, the impact to the rhizosphere-root con-
tinuum may last only briefly, for most or all of that
tree's  life or beyond to the  next generation of
trees.  Table 3 lists some of the many hypothe-
sized mechanisms for pollutant impacts on the
rhizosphere-root system.   Although listed  as
separate items, each impactfeedsbackintothe
others potentially causing further impacts  on
the system. The multiple interactions that take
place in the soil-root continuum make interpre-
tation of impacts difficult. Differences caused
by soil type, plant species, plant age, pollutant
composition,  and  exposure  dynamics  add
greatly to the complexity of pollutant  interac-
tions. The many studies of this continuum have
failed  to  produce  a  unified picture  of  how
rhizosphere-root processes  such as N minerali-
zation, soil respiration, and mycorrhizal forma-
tion and function are affected by atmospheric
pollutants.

     Advances   in   understanding   the
rhizosphere-root subsystem have come from
studies that have provided  "puzzle pieces" to

 124
the bigger picture. An example of one puzzle
pieceisworkbyZakefa/. (submitted). Nitrogen
uptake by spring ephemeral plants has previ-
ously been supposed as the mechanism for N
retention in northern  hardwood forests prior to
overstory N uptake in the early spring. Using
15N, microbial immobilization was demonstrated
to be a more significant sink than plant uptake.
Moreover, the strength of  this sink was  en-
hanced by the presence of  the spring ephem-
eral plants. Schoeneberger and Perry (1982)
found that differences in Douglas-fir growth in
two  adjacent old growth forested soils  was
explained by a litter-induced allelopathic reac-
tion  that shifted  differences  in  mycorrhizal
morpho-types.  To understand the impact of
pollutants on system performance, many more
pieces to the rhizosphere and pollution puzzle
need to be evaluated. For example, exposure
of subterranean clover, a nitrogen-fixing plant,
to a range of ozone concentrations (0 to 0.15
ppm) for 8 weeks, did not affect shoot growth.
Root biomass, however, was significantly re-
duced as ozone increased (Schoeneberger and
Shafer, 1987).  And, more importantly, increas-
ing ozone was found to reduce the proportion of

-------
                        Mechanisms By Which Regional Air Pollutants Affect Forested Soils and Rhizospheres
nitrogen in the shoot that was derived by sem-
biotic function, thus altering the plant species
composition from one that fixed more N to one
that relied more heavily on N mineralized from
native soil sources. Such complex interactions
of natural systems need to be better appreci-
ated.
uum. To interpret and predict region-scale at-
mospheric pollutant effects on soil resources,
soil-plant systems, and forest ecosystems, a
coordinated team approach  with  a long-term
perspective is necessary.

              Literature Cited
     The complexity of  putting these  "puzzle
pieces" together to understand the relation-
ships among rhizosphere-root  performance,
forest decline, and chronic air pollution is also
illustrated in a study by Meyer et al. (1988).  In
examining  the  root and  mycorrhizal status of
two 30-yr-old Picea  abies (L.) Karst.  stands
showing various levels of decline, visual decline
symptoms were associated with fewer root and
mycorrhizal tips. Significant correlations were
found between root numbers and ectomycorrhi-
zal tips per m2 ground area and the molar ratio
of root calcium to aluminum in mineral soil
extracts. Further, a positive relation was found
between ectomycorrhizal tips on a per m2 leaf
area basis and foliar calcium and magnesium
contents, and a negative relationship with foliar
aluminum content.  While these data  fit what
others have hypothesized as  causing forest
declines, they can  be interpreted in  several
ways.  One hypothesis is that the acidification
process at the declining site has resulted in soil
conditions (e.g., Ca:AI ratio) that inhibit root and
mycorrhizal tip formation which in turn altered
the foliar nutrient content. However, it may also
be supposed that tip production and foliar nutri-
ent content have both been affected i n the same
manner but independently from each other by
the soil environment.

                Conclusions

     Currently the majority of pollution studies
use short-term, acute dose experimental de-
signs,  often in  order to meet policy-making
deadlines.   Whether  this approach bears an
accurate relationship to current, relatively low-
levels, or not, chronic exposures is problematic,
especially with regard to the soil-plant contin-
Anonymous.  1986.  Indirect effects of air pollution on
   forest trees:  root-rhizosphere  interactions. Proc.,
   COST Workshop, Julich, FRG. Comm. European
   Commun., Environ. Res. Prog.

Dai, K.H., and D.D. Richter.  1989. Ion exchange equili-
   bria involving aluminum in acid forested soils. SoilSci.
   Soc. Am. J. (submitted).

Jansen, A.E., J. Dighton, and A.H.M. Bresser. 1988.
   Ectomycorrh/za and acid rain.  Proc., Workshop on
   Ectomycorrhiza/Expert Meeting, Berg en Dal, Bilt-
   hoven, The Netherlands.

Leaphart.C.D., and O.L Copeland, Jr. 1957. Root and
   soil relationships associated with the pole blight dis-
   ease of western white pine.  So/7 Sci. Soc. Am., Proc.
   21:551-554.

Leaphart, C.D., and A.R. Stage. 1971. Climate: a factor
   in the origin of the pole blight disease of Pinus mon-
   f/co/aDougl. Ecology52:229-239.

Mathy, P. (ed.). 1988.  Air pollution and ecosystems.
   Reidel Publ. Co.,  Dordrecht, Holland.

Meyer, J., B.U. Schneider, K. Werk, R. Oren, and E.-D.
   Schulze. 1988. Performance of two Picea abies (L.)
   Karst. stands at different stages of decline.  V. Root
   tip and ectomycorrhiza development and their rela-
   tions to above-ground and soil nutrients.  Oecologia
   (in press).

NCASI. 1987. Acidic deposition and forest soil biology.
   Techn. Bull. 527.  New York.

Reuss, J.O., and D.W. Johnson. 1986. Acid deposition
   and the acidification of soils and waters.  Springer-
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Richter, D.D. 1986. Sources of acidity in forested Udults.
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  126

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  Mechanisms  of Genetic  Control of Air Pollution Tolerance
                                in Forest Trees

                                   David F. Karnosky
                            School of Forestry and Wood Products,
                              Michigan Technological University,
                              Houghton, Michigan 49931, U.S.A.
                Abstract

    The genetic control of air pollution toler-
ance has been demonstrated in several ways,
viagrafting, parent-offspring correlations, prove-
nance and family variability studies and herita-
bility estimates.  This paper  reviews the evi-
dence for genetic control of air pollution toler-
ance in  trees and summarizes the proposed
mechanisms for differences in tolerance to the
two most thoroughly studied  pollutants, sulfur
dioxide and ozone.

               Introduction

    Ecologists studying point source pollution
problems were the  first to describe  genetic
variability in air pollution tolerances of forest
trees.    They  noted  community changes
attributable to natural selection for air pollution
tolerance that had occurred  in the vicinity  of
smelters and other large factories. More recently,
evidence has been building for regional impacts
of air pollution on the genetic structure of forests
(Berrang ef a/., I986a,b; Kriebel and Leben,
1981; Larsen, 1986; Mejnartowicz, 1983; Miller
et a/., 1963; Muller-Starck, 1985; Scholz and
Bergmann, 1984).   The  implications of air
pollution on the adaptability of forest trees to
other stresses has been discussed by Gregorius
(1986). He concluded that "air pollution impairs
adaptation of forest tree populations in almost
all aspects and fundamentally undermines their
natural bases for  the  preservation  of  adap-
tability."

     From a practical  standpoint, the genetic
control of air pollution tolerance means that bio-
indicators can be developed with varying re-
sponses to air pollution and that tolerant trees
can be selected for planting in polluted areas.
Trees are useful bio-indicators because of the
perennial  growth habit, long-term foliar reten-
tion  (conifers),  and minimal culture require-
ments. While the cleanup of pollution problems
at their sources is the best way to alleviate air
pollution damage to forest trees, the complex
nature of  regional air pollution problems sug-
gests that they will continue to be with us well
into the next century so that planting tolerant
trees is a useful alternative in some situations.

     This  paper will discuss the studies that
have developed the evidence for genetic con-
trol of air pollution tolerance in forest trees and
will describe proposed mechanisms for this
genetic control.
                                                                                     127

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David F. Karnosky
     Evidence for genetic control of air
    pollution tolerance grafting studies

     Some of the first evidence for the genetic
control of air pollution tolerances of forest trees
came from studies where scions of sensitive
and tolerant trees were grafted onto rootstock
and then transplanted back into areas where air
pollution was present. Differential responses of
scions and rootstock are evidence of genetic
control of air pollution response and  are also
evidence for an airborne influence rather than a
soil-related causal agent. Rohmeder and Schon-
born (1965) showed that scions from trees se-
lected for their tolerance to industrial pollutants
were less severely injured by sulfur dioxide
(S02) and hydrogen  fluoride  (HF)  than  were
scions from trees taken in nonpolluted areas.
Similar findings  were reported by  Dochinger
and Seliskar (1965) who utilized grafting  stud-
ies to show that susceptibility  of Pinus strobus
was genetically controlled. This disease was
later found by Dochinger and Seliskar (1970) to
be caused by low levels of ozone (O3) and SO2.
While grafting provided preliminary evidence of
genetic control, it does not indicate whether the
trait will be passed on through a sexual genera-
tion.  Thus, additional lines of evidence  were
needed.

          Provenance, family, and
          parent-offspring studies

     A second type  of evidence  for genetic
control of air pollution tolerance came by  com-
paring the air pollution responses of:  (a) various
populations from across the range of a species
and (b) related  individuals as  compared to
nonrelated individuals in 1/2-sib family, full-sib
family or parent-offspring trials. Seed source or
provenance differences in the response of trees
to ozone  has been  shown for Acer rubrum
(Berrang etal., 1986b; Townsend and Dochin-
ger, 1974), Fraxinus amer/canaand F. pennsyl-
vanica (Karnosky and  Steiner,  1981),  Pinus
strobus (Genys  and  Heggestad, 1983), and
Pinus taeda (Adams etal, 1988; Kress etal.,
1982a,b; Winner et al.,  1987),  and Populus
tremuloidesMichx. (Berrang etal., 1986a).  In
all of these studies, a wide range of sensitivity
was found following artificial fumigation with 03.
Similar  variability has  been  reported for re-
sponse to SO2 by Fraxinus americana and  F.
pennsylvanica (Karnosky and Steiner, 1981),
Picea abies (Bialobok etal., 1980b; Huttunen,
1978), Pinus contorta(Garsed and Flutter, 1982;
Lang etal., 1971), Pinus nigra (Oleksyn etal.,
1987),  Pinus  sylvestris  (Huttunen and  Tor-
malehto, 1982; Karolewski and Pukacki, 1983;
Oleksyn and Bialobok,  1986).

     The studies mentioned above infer ge-
netic control by describing less variability within
families or seed sources than between them.
However, it is well  known  that within  seed
source and within family variation can also be
substantial.  This type of variation, often re-
ferred to as  tree-to-tree variation, can also be
genetically controlled although it is more  diffi-
cult  to  demonstrate.   Clonal propagation  is
useful  in testing variation in tolerance when
tree-to-tree  variation within  seed  sources  is
high, as was the the case for Populus tremuloi-
desstudies by Karnosky (1977) and Wang etal.
(I986).  Heritability estimates are also useful
when large  amounts of tree-to-tree variation
occur.

     Parent-progeny correlations are another
useful means of demonstrating genetic control
of a  given trait. Bialobok  et al. (1978, 1980a)
showed that Pinus sylvestris progeny of scions
tolerant to SO2 and  O3 were generally more
tolerant to these gases  than progeny from
unselected trees.  This same group later re-
ported a high correlation (r=.639 and significant
at the  .01 level) between the degree of SO2
injury to mother clones and the degree of injury
to needles of seedling progenies for Pinus
sylvestris. The authors concluded from these
studies that the heritability of pollution tolerance
appears to be high in Pinus sylvestris. How-
ever, they did not actually calculate heritability
estimates.
 128

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                                Mechanisms of Genetic Control of Air Pollution Tolerance in Forest Trees
           Heritability estimates

    The strongest evidence for genetic control
of air pollution tolerances in forest trees comes
from studies which estimate heritability which is
commonly used in forest genetics  because of
the long generation times involved with trees.
Heritability of air pollution tolerance appears to
be very high as estimates from .32 to .80 have
been developed for many tree species and for
many pollutants (Table 1).

        Mechanisms of tolerance

    There appear to be a number of mecha-
nisms of air pollution tolerance in  forest trees
depending on the species and on the pollutant.
Mechanisms of tolerance have been most thor-
oughly studied for SO2, and O3. The discussion
will address these two pollutants.

               Sulfur dioxide

     Differential depression of photosynthesis
by SO2  has been reported for sensitive  and
tolerant  trees  of  Pinus  strobus  (Eckert  and
                      Houston,  1980),  Pinus  sylvestris  (Oleksyn,
                      1981), and Abies alba (Larsen etal., I988). The
                      reduction in photosynthesis in sensitive clones
                      was about six times greater than in tolerant
                      clones.   Thus,  the  complex photosynthetic
                      apparatus, including stomates, enzymes, chlo-
                      rophyll and/or chloroplasts, may be more sensi-
                      tive to SO2 exposure in some sensitive geno-
                      types. Another proposed mechanism for the
                      increased sensitivity of some genotypes to SO2
                      is that some sensitive trees are more photosyn-
                      thetically active and  so thereby take in  more
                      CO2.  Assimilating more CO2, these individuals
                      may at the same time absorb and assimilate
                      larger quantities of SO2 and as a consequence,
                      be injured to a greater degree by this gas as has
                      been reported by Jensen and Kozlowski (1975),
                      Lorenc-Plucinska (1978a,b,  1982),  Oleksyn
                      (1981), and Oleksyn and Bialobok (1986). Kim-
                      merer and Kozlowski (1981) found  leaf sto-
                      matal conductance to be an important factor in
                      determining the relative sensitivity of Populus
                      tremuloides clones" to SO2.   They suggested
                      that stomatal closure may occur in some tolerant
                      Populus clones while other tolerant clones keep
                      their stomates open in the presence of SO2 and
Table 1. Heritability estimates for air pollution tolerance in forest trees.
       Species
Pollutant
 Heritability     Heritability
Calculation     Estimate
                                                                  Reference
Picea abies
Picea species
Pinus strobus
Pinus strobus
Pinus sylvestris
Populus tremuloides
Populus tremuloides
Pseudotsuga
menziessi
HF hJBS
S°, h!NS
S02 + 03 r
s°2 h2Bs
SO, h2NS
O r
SO2 r
S02 h'NS
.60
.60
.80
.32 to .64
.60
.62
.64
.60
Scholz era/., 1979
Tzchacksch, 1981
Houston & Stairs, 1973
Thor&Gall, 1976
Tzchacksch, 1982
Karnosky, 1977
Karnosky, 1977
Tzchacksch, 1982
'r = repeatability; h? BS = broad sense heritability; h2 NS = narrow sense heritability.
                                                                                      129

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David F. Karnosky
somehow appear to be able to detoxify the gas.

     Higher levels of the reducing sugars glu-
cose  and fructose  in  SO2-sensitive conifer
needles than in needles from tolerant trees are
presumed to be evidence for another mecha-
nism of differential tolerance. This mechanism
is associated with disturbance in translocation
of newly produced photosynthate. Evidence for
this mechanism of tolerance has been shown
for Pinus sylvestris  (Lorenc-Plucinska, 1984,
1986; Mejnartowicz and Lukasiak, 1985), Pinus
strobus  (McLaughlin et al., 1982), and Pinus
banksiana (Malhotra and Sarkar, 1979).

     Schindlbeck (1977) found  that  SO2-
resistant Picea abies clones did not have in-
creased glutathione levels after fumigation with
SO2, while sensitive ones did.  Bortitz (1969)
and Braun (1977a,b,c) found that the pH of the
cell sap in needles of resistant Picea ab/estrees
was  higher than in sensitive trees.  Other re-
searchers have found a good correlation be-
tween buffering capacity and resistance (Grill
and Hartel, 1972; Scholz and Knabe, 1976) in
Picea.  Similar correlations have been found
between SO2 tolerance and drought-stress tol-
erance (Braun, 1978) and between SO2 toler-
ance  and winter hardiness (Huttunen, 1978;
Huttunen and Tormalehto, 1982).

     Differences  in  foliar  peroxidase  levels
between SO2-tolerant and sensitive trees have
been reported for Pinus sylvestris (Kieliszewska-
Rokicka, 1979) and Pinus strobus (Eckert and
Houston, 1982).  While peroxidase enzymes
are a general stress response, other enzyme
systems may be more directly related to SO2
sensitivity.  Geburek et al. (1987) found evi-
dence indicating thatglutamatedehydrogenase
and glutamate oxaloacetate transaminase may
be involved in SO2-sensitivity responses in Pinus
sylvestris.

                 Ozone

     Two types of mechanisms for O toler-
ances of trees have been reported: anatomical
and  physiological.  Evans and Miller (1972)
presented evidence that needle anatomy may
contribute to  differences in O3 tolerance with
four  Pinus species. The secondary leaves of
the more ozone-sensitive species had a larger
number of stomata per cross-sectional area of
mesophyll cells while the number of mesophyll
cells per stoma  was lower.   The number of
hypodermal layers and thickness of epidermal
and hypodermal  layers were  negatively corre-
lated with ozone  sensitivity. In our laboratory,
we found that there was no  relationship of
stomate number per given leaf area and 03
sensitivity for Fraxinus  pennsylvanica  and
Populus tremuloides (Rassatt et al., unpub-
lished).  However, for F. pennsylvanica, we did
find that the proportion of the spongy mesophyll
region relative to all mesophyll was greater for
sensitive trees than for tolerant trees. Since this
spongy mesophyll region contains a great deal
of intercellular space, it appeared that O3 would
have more exposed cell surface to react with in
the sensitive trees.

     Evans and  Miller (1972) suggested that
there was a higher mesophyll  tissue resistance
which limits gas exchange in more tolerant pine
trees. Our results suggest that a similar mecha-
nism may occur in green ash trees.

     Another anatomical feature that may influ-
ence O3 sensitivity in Pinus strobus is needle
wax. Krause and Houston (1982) reported that
the epistomatal  wax was split longitudinally
across the stomatal apertures in  13 sensitive
clones, but was continuous in the 11  tolerant
clones examined. This character was apparent
for ramets grown in either ambient or clean air.
Trimble ef al.  (1982) did not find differences in
wax structure of a sensitive and a tolerant clone
of Pinus strobus.  However, the alkane concen-
tration was greater in the wax of the tolerant
clone.

     Evidence for physiological mechanisms of
tolerance generally center on the  uptake of
 130

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                                   Mechanisms of Genetic Control of Air Pollution Tolerance in Forest Trees
gases  through the  stomates.   Reich  (1987)
believes that among species, differences in
ozone  uptake and response can be predicted
from differences  in  the  inherent  leaf diffusive
conductance.  There has not been  enough
study of leaf diffusive conductance comparing
within  species differences in  O3 tolerance to
determine if this mechanism also is important in
intraspecific variation in  pollution  tolerance.

     Boyer  et al.  (1986)  found another physio-
logical mechanism of tolerance in  Pinus stro-
bus. Ozone consistently depressed photosyn-
thesis  in sensitive clones more than in tolerant
clones. Differences in growth rates  between
sensitive  and  tolerant  Populus  tremuloides
clones has been documented in field trials under
ambient O3 by Berrang  et al. (1988)  and in
chamber tests under various O3 exposures by
Keller  (1988).  Keller noted that  the sensitive
trees lost their leaves prematurely in the pres-
ence of O3 and had less carbohydrate reserves
as determined by shoot dry weights.  He em-
phasized the importance of multiple-year stud-
ies for evaluating growth differences in response
toO3.

                 Summary

     There appears to be a number of different
types  of mechanisms involved in  differential
responses to air pollution by forest trees. Sev-
eral  anatomical features and physiological re-
sponses have been shown to vary  between
sensitive and  tolerant  trees,  with the most
common pollutants SO2 and O3. Little is known,
however, regarding  the biochemical bases for
the tolerance mechanisms, and  even  less is
known about the numbers of genes and types of
gene action involved in determining  pollution
sensitivity.   Thus,  considerable  research re-
mains  to be done in this field.
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                                                           photosynthesis, carbon  allocation, and growth of
                                                           white pine trees. For. Sci. 28:60-70.

                                                       Mejnartowicz, I.E. 1983. Changes in genetic structure
                                                           of Scots pine (PinussylvestrisL.) population affected
                                                           by industrial emission of fluoride and sulphur dioxide.
                                                           Genetica Pol/onica 24:41 -47.

                                                       Mejnartowicz, L.E.,  and H. Lukasiak.   1985.  Level of
                                                           sugars in Scots pine  trees of different sensitivity to
                                                           fluoride  and sulphur dioxide.  Eur.  J. For. Path.
                                                           15:193-198.

                                                       Miller, P.R., J.R. Parmeter, Jr., O.C. Taylor, E.A. Cardiff.
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                                                       Muller-Starck, G.  1985.  Genetic differences between
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                                                           in an environmentally stressed adult forest stand.
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Larsen, J.B. .X.M.Qian, F. Scholz, and I.Wagner. 1988.
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Lorenc-Plucinska, G.   1978a.
    photosynthesis and dark respiration of larch and pine
    differing in resistance to thisgas. Arbor. Korn. 23:121 -
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Lorenc-Plucinska, G. 1978b. Effect of sulphurdioxide on
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Lorenc-Plucinska, G.  1982.  Effect of sulfur dioxide on
    CO2 exchange in SGysusceptible Scots pine seed-
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Lorenc-Plucinska, G.  1984. The uptake and transloca-
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Lorenc-Plucinska, G.  1986. Effect of sulphur dioxide on
    the partitioning of assimilates  in Scots pine (Pinus
    sylvestris L.) seedlings of different susceptibility to
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Oleksyn, J.   1981.  Effect of sulphur dioxide on  net
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Oleksyn, J., and S. Bialobok. 1986.  Net photosynthesis,
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Oleksyn, J., K. Oleksynowa, E. Kozlowska, and L. Rach-
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Reich, P.B. 1987. Quantifying plant response to ozone:
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-------
David F. Karnosky
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    Pollut. 47:205-220.
 134

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 Forest Health  Diagnosis and Its Application  in Air Pollution
                                Impact Studies
                                  Vladislav Alexeyev
                            Institute of Forest and Timber Research,
                       Siberian Division of the USSR, Academy of Sciences
                                660036 Krasnojarsk, USSR
              Introduction

     In developing and monitoring strategies
for forest management, there is a need to define
the health of the basic component of the forest
ecosystem — the tree stand. The long distance
transport of pollutants, including widely spread
regional pollution, contribute  to this need for
methods for diagnosing forest health.

     There have been many studies on diag-
nosing damage from air pollution.  Descriptions
of leaf injury from one pollutant or another are
often accompanied by color photographs that
provide a better understanding of the peculiari-
ties of chlorosis and necrosis and the nature of
the pollutant in question (Env. Prot. Agency,
1978; Malhotra and Blauel, 1980; Skelly et al.,
1987).

     For the grasses, especially annuals, leaf
damage is both an adequate characterization of
a plant's condition at a given moment and  a
reliable indicator of future health.  For trees,
however, this is not the case. For example, leaf
damage or even complete defoliation of decidu-
ous trees in the second half of growing season
has little influence on tree condition the follow-
ing year. Therefore, tree-damage scales based
only on foliage condition (for instance, the IUFRO
scale) have slight predictive value. As a rule,
damage scales are expressed numerically, for
example, 0 to 4 (Dassler,  1981) or 1  to  6
(U.S.S.R. State Comm. of For. Manage., 1970).
In the latter scale, trees are  rated as: healthy
(1), weakened (2), heavily weakened (3), dying
(4), recently dead (up to 1 year after death) (5);
or standing dead (1 year +) (6).

     Due to their arbitrary and artificial nature,
numerical damage scales have been criticized
in the  literature  (Alexeyev,  1982; Muir  and
McCune, 1987; Reuther, 1987). Therefore, the
first task in developing a diagnostic system is
(1)  strengthening the  reliability of criteria for
evaluating tree  health, and (2)  shifting from
numerical  indices  to  their  common sense
meaning.

     The next task is concerned with the method
of calculating the life condition (health) of tree
stands. This usually is done by the number of
trees method,  that is,  multiplying the  corre-
sponding index by the number of trees in that
condition, summarizing the values obtained and
dividing the total by the total number of trees.
However, the use of this method can produce
errors because the role of large and small trees
                                                                                    135

-------
Vladislav Alexeyev
are assigned similar values.

     The objective of this paper was to develop
a method of diagnosing forest health and to
demonstrate its use in a study of northern
forests of the U.S.S.R. affected by air pollution.

          Diagnosing Tree Health

     The proposed categories of tree health are
based on characteristics of the tree crown. The
scale can be used both for forests damaged by
any type of stress (including  air pollution) and
undamaged forests. The resulting information
is not intended to indicate the causes of one or
another condition of the tree — for this, a listing
of additional specific indicators used by phyto-
pathologists would be necessary in each situ-
ation.

            Tree Health Scale

     Healthy.  There are no apparent signs of
crown or stem disturbance.  Crown density is
typical of that of dominant trees (l-ll Classes of
Kraft's classification, if applicable).  Dead and
drying branches are observed mostly  in the
lower part of the  crown; in the upper crown,
there are no large dead branches or they are too
few to be seen in  the  crown edges.  Fully
developed leaves and  needles are  green or
dark green.  Needle life is typical of that in the
region. Leaf damage is negligible (less than 10
percent)  and does not  affect the state of the
whole tree.

     Weakened (damaged)1. At least one of
the following must  be  observed:  a)  crown
density  is decreased by 30  percent  due to
premature shedding of leaves or thinning of the
crown frame; b) dead and/or drying branches
account for 30 percent of the upper crown; c) 30
to 40 percent total leaf  area is damaged (fire,
insects, air pollution, or other agents)  and no
longer participates in photosynthetical activity.
     In this category, there may be trees with
one or more of these features (or parts of them)
and other disturbances (including stem and root
damage), with acumulative effect of weakening
equal to 30 percent.

     Heavily weakened (heavily damaged).
At least one of the following must be observed:
a) crown density is reduced by 60 percent due
to premature shedding of leaves or thinning of
the crown frame; b) dead and/or drying branches
account for 60 percent of the upper crown; c) 60
percent of the total leaf area is damaged (fire,
insects, air pollution, or  other agents)  and no
longer participates in photosynthetic activity.

     In this category, there may be trees with
one or more of these features (or parts of them)
and other disturbances (including stem and root
damage), with a cumulative effect of weakening
equal to 60 percent.

     Dying. The primary signs of dying (drying)
are: a) the crown is destroyed, its density being
20 percent (or less) of that of a healthy tree; b)
more  than 70 percent of the branches in the
upper crown are dry or drying.  The remaining
leaves are chlorotic and  necrotic.

     Dead. There are no living twigs. In the first
year after death, the tree has some residual dry
needles  or  leaves.   Gradually  the  twigs,
branches, and bark fall off.

     As stated earlier, the defoliation of decidu-
ous species or summer-green coniferous spe-
cies  indicates the current state of individual
trees, but does not always affect their health the
following year.  For conifers, the influence of
needle damage (premature shedding) is long
term because quantitative and qualitative re-
generation of the photosynthetic part of a tree
takes at least 3 years.

    The state of the upper twigs and branches
1Since tree decline often is related to damage of the photosynthetic system, hereafter "weakened" trees also are
considered as "damaged."

 136

-------
                                Forest Health Diagnosis and Its Application in Air Pollution Impact Studies
of the crown is the most informative for predict-
ing tree health.  Healthy, dying, or dead trees
usually are easily identified.  The external ap-
pearance of weakened and heavily weakened
trees also is easily distinguished so long as their
condition is near the "center" of the gradation
being used. A tree whose condition does not fall
into a specific category can be recorded as
intermediate or related to the most representa-
tive category.

     The optimal time for inspecting stands is
the beginning of the second half of the growing
season when the majority of species have fin-
ished putting forth leaves and shoots.

         Calculating Stand Health

     After the condition of the trees on the site
plots is determined, the value of a whole stand's
health is calculated.  For this purpose,  coeffi-
cients are assigned to trees  corresponding  to
their vitality level. Healthy trees are assigned a
coefficient of 100 percent; dead trees receive a
coefficient of 0 percent. For trees in intermedi-
ate stages, the coefficients of vitality  corre-
spond to the health ratings that were assigned
during the inventory. In principle, vitality coeffi-
cients may be  assigned to each tree  on  a
fractional basis.   However, because a  tree's
exterior varies due to its genetics, the accuracy
of health ratings is low (usually no more than 10
percent).  For trees in the intermediate  cate-
gory, it is reasonable to assume that weakened
trees have 70 percent potential vitality, heavily
weakened trees, 40 percent, and dying trees, 5
percent.
from:
The estimate for stand health is derived


        10Ov, + 70 v, + 40 v3 + 5 v4

                   V
where Lv is relative to the stand vitality in relation
to tree volume; v, is the stem volume of healthy
(100 percent) trees (m3 ha1); v2, v3, and v4, are
stem volumes forweakened (70percent), heavily
weakened (40 percent), and dying (5 percent)
trees, respectively, and V is total stand volume,
including standing dead trees (m3 ha1).

     At an Lv of 80 to 100 percent, stand vitality
is considered "healthy" (L, = 80 to 90 percent at
the onset of weakening); at an  Lv of  50 to 79
percent, the stand is considered weakened, at
an Lv of 20 to 49 percent, the stand is defined as
heavily weakened, and at an Lv of 19 percent or
less, the stand is assumed to be destroyed.

     Calculations of stand vitality based on the
number of trees are simple and efficient com-
pared to those based on the additional consid-
eration of timber volume; however, the "number
of trees" method  is less accurate because it
assigns the same value to trees of different size
and function.

     Both methods reach the same conclusion
if applied to stands without natu rally suppressed
trees  (for example, under regular thinnings).
For overstocked pole stands with many small,
depressed trees, the "number of trees" method
produces large errors.   However, in  deciding
special problems, estimating the health of
managed  stands  (parks),  for  instance,  the
"number of trees"  method is the only appropri-
ate application.

    Air pollution and the Forests of the
         Northern Kola Peninsula

     In 1978-88, as part of the IUFRO 02.03-21
Project (Alexeyev and  Dochinger, 1981), the
impact of air pollution on the composition, struc-
ture, and productivity of forests was studied.
The field research was carried  out in various
regions of the U.S.S.R.,  primarily in the northern
forest ecosystems of Kola Peninsula near the
active copper-nickel smelter "Severonikel." Daily
emissions from the smelter total 800 to 900 tons
of sulphur dioxide with an admixture of trace
metals (Cu, Ni, Co).
                                                                                      137

-------
Vladislav Alexeyev
100..

 80-

 60-

 40-

 20

   0
                                                                        o—o
                                                                  PI  3>cm
                            4     8    12   16   20   24   28   32   36   40
Figure 1. Effect of air pollution on Scotch pine stands in the U.S.S.R. (1) overstocked pole stand in southern taiga, no
         pollution; (2) fully stocked mature stand in southern taiga, no pollution; (3) understocked, sparse pole stand
         in northern taiga, no pollution; (4) 27 year old pole stand in northern taiga, 50 percent canopy density due to
         effects from copper-nickel smelter; (5) the same site in 1988.
                  V,
                    80-

                    60-

                    40-

                    20-
                                                                   1,3,cm
                40
          4     8     12   16   20   24   28   32
Figure 2. Effect of air pollution on sparse, uneven-aged spruce stands in the U.S.S.R.: (1) healthy (60 to 130 years old);
         (2) weakened (60 to 200 years old); (3) heavily weakened (60 to 200 years old); (4) destroyed (60 to 200 years
         old).
 138

-------
                                    Forest Health Diagnosis and Its Application in Air Pollution Impact Studies
H,m 1-« 4-*
ia 2- A 5-t
8 A
6. AA "3j^
4 f.-4p5V
2 AJfc'**
1 12.
1 10.
??** 6
4'
2.
D cm
H,m
Q.t *
A a
BO On DO • •
AA-via' •»».
a &&AG Q^ >*• ^
QOAQ & • Q
xa •M
O^L j^-^
oo ^^
on-»-
D1i3,cm
                            8    10   12
    0     2
                                                                                8    10
                                           14
Figure 3.  Effect of pollution from copper-nickel smelter
         on northern Scotch pine pole stand after 7
         years: (1) healthy; (2) weakened; (3) heavily
         weakened; (4) dying; (5) dead.
Figure 4. Effect of pollution from copper-nickel smelter
         on northern Scotch pine stands after 14 years.
         Legend- Figure 3.
        100   80   60   40   20    0
                Tree Health, %
                80   60   40   20   0
                Tree Health, %
Figure 5. Age  distribution of healthy  northern Scotch
        pine stands:  (1) 27 years old; (2) 45 years old;
        (3) 300 years old.
Figure 6. Age distribution of damaged northern Scotch
         pine stands and distance from copper-nickel
         smelter:  (1) weakened, 34 years old, 40 km
         from smelter; (2) heavily weakened, 60 to 300
         years old, 40  km from smelter; (3)  heavily
         weakened, 45 years old, 15 km from smelter.
                                                                                                   139

-------
Vladislav Alexeyev
  L,
100,

 80-

 60.

 40

 20
           1^81
                83
                            years
85
Figure 7. Effect of pollution on three-generation north-
        ern Scotch pine stand 70 km from copper-
        nickel smelter: (1)60 to 90 years old; (2) 120
        to 160 years old; (3) 240 to 320 years old.
100-

 80  .

 60  -

 40  -

 20  •

  0
                                                     o	
                                                                                       -o
                                                                                    years
                                              1981
                           85
87
                                         Figure 8.  Effect of pollution on three-generation north-
                                                  ern Scotch pine stand 60 km from copper-
                                                  nickel smelter:  (1) 60 to 90 years old; (2) 120
                                                  to 160 years old; (3) 200 to 260 years old.
     The region features widespread Scotch
pine (Pinus sylvestris  L.)  and spruce  (Picea
obovata Ledeb., P. x fennica (Rgl.) Kom.) for-
ests. The stands generally have low productiv-
ity (growing stock 60 to 140 m3 ha-1). The pine
forests are even-aged or consist of two to three
generations.  The spruce forests are uneven-
aged.  Where there is no pollution, the stands
are healthy or weakened. The latter condition is
primarily the  result  of fires or advanced age
(300 years  or more).

     One of the important peculiarities of stand
structure is small canopy  density (30  to  50
percent,  usually attributed to poor soil condi-
tions).  In this situation, the influence of phyto-
coenosis on tree differentiation and vitality is
minor.   In overstocked or fully stocked  even-
aged forests  of the southern taiga, there are
many stunted,  heavily depressed, and  dying
trees (Fig.1 (1), (2)).  In understocked,  even-
aged or  uneven-aged forests of the northern
taiga, damage was not observed (Fig.1 (3); Fig.
2 (1)) or was less severe (Fig.1  (4); Fig.  3).

     The healthy trees in healthy stands always
control the  above-ground space of the forest:
they are dominant in sparse pole stands (Fig. 5
                                         (1)) and are slightly less dominant in stands of
                                         greater canopy density (Fig. 5 (2)). Their role is
                                         minor in very old forests (Fig. 5 (3)).

                                              Air  pollution  substantially changes the
                                         proportion of healthy, weakened, heavily weak-
                                         ened, and dead trees (Fig. 6). In sparse forests,
                                         tree damage occurs independently of tree size
                                         (Fig. 2 (2),  (3),(4)).

                                              The  literature  contains  data  reporting
                                         mainly damage and death to tall, healthy trees,
                                         or to stunted and depressed trees.  The data,
                                         however,  show  no connection  between tree
                                         damage and tree size. These facts do not con-
                                         tradict one another, as they may seem to do at
                                         first glance.  The following explanations are
                                         possible:  If the slowing down of air turbulence
                                         and the lowering of the rate of deposition (ab-
                                         sorption) of the damage-causing pollutant pro-
                                         ceed at the varied heights of stand more rapidly
                                         than the loss of the health via phytocoenosis
                                         reasons, then the largest trees will suffer more
                                         intensively. On the other hand, if the tree differ-
                                         entiation caused by phytocoenosis is faster with
                                         canopy depth than the changes in damaging
                                         pollutants, then the faster growth causes dam-
                                         age and death to the small, weakened trees.
 140

-------
                                  Forest Health Diagnosis and Its Application in Air Pollution Impact Studies
     An inventory of damaged stands near the
copper-nickel smelter allows us to draw conclu-
sions about the more rapid damage in older
stands.  In 1981, pine stands that were 250 to
300 years old and  15 to 25 km downwind from
the smelter were destroyed (Lv  = 5 to 20  per-
cent); those 30 to 45 km away from the smelter
were damaged (Lv = 40  to  70 percent);  and
stands 70 km from the smelter showed no signs
of pollution injury.  At the same time, pine pole
stands 15 to 25 km from the smelter showed
moderate damage; those 30 to 45 km from the
smelter  suffered only slight damage (Lv = 83 to
90 percent); and stands beyond 45 km had no
visible injury.

     In recent years the spread of pollution and
resulting stand destruction has  continued; the
initial stages of stand weakening have been
observed more than  70 km from the smelter
(Fig. 7). It is important to note that the weaken-
ing of trees — the appearance of chlorosis — is
indicated primarily by the premature shedding
of needles.

     Figures 3, 4, 7, and 8 give some indication
of the rate of change  in the health of trees and
generations of forest.  The rate of health loss for
some trees has reached 15 to 30 percent  in
individual years. For generations of trees and
stands as a whole,  the change in health rates at
the same location  has proceeded more slowly
(rarely 10 percent  per year). Total destruction
of healthy stands  may  be  observed  in  this
region in the next 15 to 20 years.
              Literature Cited

Alexeyev, V.A. 1982. Peculiarities of forest stand de-
   scription under air pollution impacts.  Interactions be-
   tween forest ecosystems and air pollutants. Tallinn,
   U.S.S.R.: Academy of Science of the U.S.S.R. 1:97-
   115.

Alexeyev, V.A., and L.S. Dochinger.  1981    Forest
   ecosystems and air pollution.  Moscow, U.S.S.R.:
   Academy of Sciences of the U.S.S.R. 5:64-71.

Dassler, H.G. ed. 1981. Air Pollution Impacts on Vege-
   tation. Moscow, 181  pp. (in Russian).

Malhotra, S.S., and R.A. Blauel. 1980. Diagnosis of Air
   Pollutant and Natural Stress Symptoms on Forest
   Vegetation in Western Canada.  Inf. Rep. NOR-X-
   228, Ottawa, Ontario. Canadian Forestry Service,
   Forest Research Centre. 84 pp.

Muir, P., and P. McCune.  1987. Index construction for
   foliar symptoms of air pollution injury. Plant Disease
   71(6):558-565.

Reuther, M.   1987.  Wie kvank ist unser wald?  GSF:
   Mensch  + Umself, Sept.

Skelly, J.M.,  D. Davis, W. Merrill, et al. 1987. Diagnos-
   ing Injury to Eastern Forest Trees. University Park,
   PA: The Pennsylvania State University. 122pp.

State Committee of Forest Management of the U.S.S.R.
   1970. Sanitary Rules in Forests of the  U.S.S.R
   Moscow, U.S.S.R.:   State Committee of  Forest
   Management of the U.S.S.R. 16pp. (in Russian)

U.S. Environmental Protection Agency. 1978. Diagnos-
   ing vegetation injury caused by air pollution.  Wash-
   ington, DC: U.S. Environmental Protection Agency,
   Office of Air and Waste Management. 306 pp.
                                                                                           141

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                                                               Modeling Tree Level Processes
                     Modeling Tree Level Processes
                                Cheryl Aeschbach Gay
                          Environmental Research Laboratory - Corvallis
                                    200 SW 35th Street
                               Corvallis, Oregon 97333, U.S.A.
                Abstract

     An overview of three main types of simula-
tion  approach  (explanatory, abstraction, and
estimation) is presented, along with a discus-
sion of their capabilities,  limitations, and the
steps required  for their validation.  A process
model being developed  through the  Forest
Response Program is used as an example.  In
construction of this tree  process model, the
various organs (such as foliage) are simulated
using a modular plan of development.

     The foliar  processes  module is used as a
reference point in the discussion, and is under
development using the explanatory approach.
The lower hierarchical level of processes, such
as photosynthesis  and nutrient allocation,  is
emphasized in  simulation of the activities of the
foliar organ.  A branch  growth module with
which the foliar module will be coupled in the
system, is also a process model, but is under
development using the abstraction approach.
A stand model, with which it will later be coupled,
has been developed empirically, using the esti-
mation approach. The development of modular
simulators of subprocesses, utilizing various of
the three developmental  approaches, then
coupling them is a robust approach to meeting
information needs.  The  resultant aggregate
models  provide tools with the capabilities of
incorporating current scientific knowledge to
provide predictions which possess the charac-
teristics of realism, generality and precision.

               Introduction

     Simulation with mathematical  models is
an analytical tool  whose use  is becoming in-
creasingly widespread.   It is  important that
general  concepts pertaining to  modeling  ap-
proaches and capabilities be realized and stated
explicitly at the onset of any modeling activity.
The objective of this paper is to place in per-
spective various aspects of process and empiri-
cal modeling, and how they relate to the model-
ing endeavors of the Forest Response Program
(FRP) of the National Acid Precipitation  As-
sessment Program.

     The FRP has conducted a large research
effort focused on determining the effects of acid
precipitation on forest development.  Research
within the program has been conducted at vary-
ing levels of  biological organization (Figure 1),
ranging  from seedling to regional  scale.   In
order to structure this acquired information in a
form which would aid understanding of the acid
precipitation phenomenon, a conceptual whole-
tree-physiology modeling system has been de-

                                        143

-------
 Cheryl Aeschbach Gay
                    Natural
                    Factors
                    Natural
                    Factors
Regional Growth
   and Yield
Stand Growth
   and Yiald
                     Stand Growth
                     and Yield  models
Deposition
  Data
                                                                Tree Croirtb.
                                                        and Yield Models
                                   Whole Tree Physiology:
                                     Growth. Mortality
                                       Experimental
                                        Inference
                                        Physiological
                                      — Process  	
                                         Models
                     Seedling Physiology
                                                      Branch Physiology
                               FRP Levels of Organization

       Figure 1. Levels of organization at which research is conducted in the Forest Response Program.
 veloped. The system will act as an explanatory
 interface  between experimental  information
 gained from seedling and branch studies, to aid
 in interpreting  observations  made at  higher
 levels of stand  and forest.

     Systems can be modeled in a way that will
 either provide explanation, estimation,  or ab-
 stract  principles. The choice of a  simulation
 objective, along with the nature of the observa-
 tional information available for model construc-
 tion, together determine the character of infor-
 mation obtained from the completed simulator.
 The  level of biological organization for which
 observational data are available, compared with
 the desired level of prediction, also determines
whether  an  empirical  or process-modeling
 approach will be required. The term "empirical"
 pertains to models which are developed without
direct reference to the biological processes in-
volved. "Process" models, on the other hand,

 144
         are derived by mathematical simulation of the
         underlying physical/chemical processes pre-
         sumed responsible for the activity (activities) of
         interest.

              The purpose of this paper  is to identify
         some of  the required steps in model develop-
         ment.  These steps include defining perform-
         ance criteria, verification techniques and vali-
         dation processes.  In addition, I will focus on the
         importance of defining the scope of a model.
         Since two general modeling approaches are
         commonly used, i.e.,  empirical and  process
         modeling, I will clarify the differences between
         them, and outline advantages and disadvan-
         tages of each. Finally, I will present an overview
         of a modeling system under development to
         evaluate  and predict tree responses to air pol-
         lution.  This system is an  aggregation of sub-
         models utilizing elements  from both empirical
         and process modeling approaches. Combining

-------
                                                                Modeling Tree Level Processes
these techniques  is one way of linking foliar
processes to that of a tree, and tree  growth
processes to that of the stand.

               Model scope

     Before beginning any modeling activities,
the researchers developing the model must
clearly state what output is needed. Will there
be predictions of size? activity? diversity? The
type of  information to  be  provided  must be
stated without ambiguity, prior to designing the
model framework.

     What entities will be of concern?  In this
discussion, emphasis is placed on describing
trees - not leaves, forests, or stomata. What is
the relationship of the model to the data sup-
porting its development? Is the model output to
be within the range of that data, and can thus be
interpolated? Are there measurements  of tree-
level parameters,  such as tree height  and di-
ameter or even whole-tree mass or total photo-
synthesis?  Such  a data  bank would allow
interpolation  between measurements  to pro-
vide tree-level output. In contrast, is the output
outside the range of the database?  Will it be
necessary to extrapolate from what has been
measured or observed, and go beyond the data
to make other predictions.  Answers to these
questions define the scope of the model.

           Model assumptions

     In  stating  the assumptions, all  factors
considered to have a significant effect on the
behavior of the tree (variables and processes)
are listed. The assumptions reveal the essence
of the simplification of the physical system, and
indicate  how the  model  will  represent tree
behavior.  If the goal is, as stated, to model the
effect of pollutants on trees, the assumption will
be made that particular pollutants (defined and
listed) influence tree growth and functioning, af-
fecting in some way the processes addressed in
the model. The question arises then whether
the mode of air pollution action on the physiol-
ogy and growth is understood.

     Another decision that must be made is the
level of hierarchy. The level of hierarchy repre-
sents the level of biological organization, or
complexity, to be modeled. Levels of hierarchy
relevant to modeling forest processes  , in de-
creasing order,  would  be forest-stand-tree-
organ-cell, etc.  In this example, the level of
concern is the individual tree. Information may
be utilized from lower levels, such as that of the
organ (leaves, roots, stems, branches).  One
could also use information from progressively
lower levels of organization - the cell level, the
organelle level, or even the molecular level. In-
formation from higher levels of organization (for
example, the stand or region) will not be as
directly useful in model development, but pro-
vides information characterizing constraints to
system behavior.  In this example, the behavior
of the tree is simulated by aggregating submod-
els simulating behaviors of various organs and
physiological systems. The functioning of these
organs and systems, in some of the submodels,
is represented by the behaviors of their particu-
lar subprocesses.  In the foliar module, the
lower hierarchical processes of ontogeny, nutri-
ent cycling, and photosynthesis are represented.

   Model building: steps, performance,
        verification and validation

     In forestry, seedlings are often used in
experiments as  surrogates for mature trees.
How to make the link between the entity in which
we are interested (tree,  in this case) and the
entity observed  (seedling) is an  unresolved
issue.  How can one go from studies on seed-
lings of the kind so frequently undertaken, to
understanding effects on whole mature trees,
or from seedlings to forests?  How should the
extrapolations be drawn?  We can design ex-
periments, we can test hypotheses on needles,
on branches, but we still  have difficulties in
observing and understanding the  whole  tree,
especially a large whole tree.
                                                                                      145

-------
Cheryl Aeschbach Gay
     Modeling is a technique particularly suited
to providing links between information at vary-
ing levels of biological complexity.  In this case,
the challenging link is from information taken
from seedlings and laboratory studies, to infer-
ences about whole trees and forests.  To prop-
erly apply these modeling tools, a clear under-
standing of the different types  of models is first
needed,  along  with the types of information
provided thorough their use.  Basic strategies
for  simulation apropos  of the creation of a
model-based approach to  tree level investiga-
tions are reviewed here.

     The process of modeling is often difficult to
discuss. The difficulty arises not so much from
its intellectual rigor, but rather from a failure to
define clearly the relevant terms. Thus, one of
my goals will be to focus on concise definition of
terms.  Modeling requires a simplification of
processes and systems of processes, facilitat-
ing analysis of their behavior. The more com-
plex the model, the more difficult the analysis of
the represented system becomes.  The first
concern, therefore, in model development, is to
try to  maintain as much simplicity as possible.
The ultimate utility  of the model  depends on
successful simplification of the problem.

    A typical sequence of activities associated
with scientific research is outlined in Figure 2.
The prelude is the  creation of the proposal,
followed by research and implementation. The
proposal establishing a modeling effort would
be expected to include:

I) defining and bounding of the problem,
2) identification of goals and objectives,
                  PROPOSAL
                     [Definition and  bounding of problem  |

                     I Identification of goals and  obiectivesl
                     [Conceptual  modeling

                     I Data  acquisition!
                     Definition of performance criteria I
                  RESEARCH
                     Construction of working algorithm -  identify:
                        Relevant  elements and  states
                        Interrelationships between elements and states
                        Mathematical relationships
                     Conversion  of  algorithm
                     into formal modeling  language
                     I Model  verification
                     [Systems analysis
                  IMPLEMENTATION


           Figure 2.  Procedural steps in a research program, and their sequence of execution.
 146

-------
                                                                Modeling Tree Level Processes
3) citation of relevant data (whether it resides in
the literature or will be gathered specifically for
purposes of model development),
4) definition of performance criteria

     I will use the Foliar submodel of the whole-
tree  modeling  system as  an  example.   The
objective of the development of this model is to
characterize the effects of acid precipitation on
foliar processes of a mature  conifer.   Lying
within the bounds of the system are the various
foliar processes which are  most likely to show
the  influence  of atmospheric  pollutants, and
external to the system are the environmental
conditions, which act as input.

     Performance criteria are the standards by
which the model will be judged. The specifica-
tion of performance criteria  provides a measur-
able scale against which the  success of the
model will be judged. Before the onset of the
modeling activity,  the levels of precision re-
quired of the model must be defined. Establish-
ing precision identifies the  level of complexity
that must be included, and helps to define the
goal.  The  Foliar  model will be  expected  to
reflect the trends observed  in  experimental
research on acid precipitation, and to provide
that information to the other elements of the
whole tree aggregate model so that the implica-
tions of  these  changes in foliar  behavior on
whole tree growth may be explored. Inthisway,
the Foliar model will act as an aid in interpreting
those experimental  results which may  have
appeared inconclusive.

     Modeling  research begins with construc-
tion of the working algorithm, which  identifies
the basic features of system operation. In this
step, the elements of the system are defined,
along with their state descriptors. The state
variables, when taken together, describe the
status of the system.  The questions addressed
are:

     What element is of concern?
     How does it change?
     What does it change to?
     Where does it start?
     Where does it move to?

     In the Foliar model, the element of concern
is the foliage (needles) present on the various
branch segments of a branch extending from
the main bole of a mature conifer. Of specific
interest is its changing developmental status
from first emergence to death and abscission
from the branch. Foliar functions which reflect
this changing status include growth, aging and
senescence; nutrient dynamics; and net carbon
production.  The states of interest  therefore
include  nutrient  status,  carbohydrate status,
needle age and needle amount.

     Interrelationships between the  elements
of concern and the states of those elements are
defined customarily by expression of the vari-
ous mathematical relationships linking system
elements. The algorithm is then converted into
a formal  modeling language.  Forrester flow
diagrams are common, followed by translation,
through one of many computer languages, into
executable code.

     Model verification follows codification of
the model.  Sometimes this step is attained, yet
unfortunately, it often is not. Model verification
differs radically  from  model  construction.
Through  verification,  the  simulated system
behavior is compared with observations made
in real life,  and adjustments in the model are
made where necessary. This calibration step
provides the final opportunity to modify system
organization before systems analysis and vali-
dation.

     Systems analysis is a systematic approach
fordefining the character of the simulator through
an analysis of the internal interactions  in the
model. The goal is to define the consequences
of  variation in  values of represented system
states and  rates, and predict resultant reper-
cussions throughout the rest of the system.
                                                                                      147

-------
Cheryl Aeschbach Gay
     Verification differs significantly from vali-
dation. Validation is the exercise of proving that
the model is, in fact, true.  It is fairly common
knowledge in the world of science that a theory
can  never be proven true.  The theory can,
rather, only be proven false or fail to be invali-
dated. A model is an aggregation of theories
and  hypotheses.  As the singular  theory, the
model can also never be proven true, but can
only hold up under the tests made against it to
date.

     With planning, work, and luck, the process
of model development reaches the implemen-
tation stage, and the work is finally put to use.

   Empirical  models and process models

     Two general methods are commonly used
in modeling,  the  empirical- and the process-
modeling  technique.   Both  methods  have
strengths and weaknesses, and both are nec-
essary for comprehensively addressing com-
plex systems.  Empirical modeling is an ap-
proach that is frequently used in forestry. Model
  output is at the same level as that of the data. In
  order to model a tree, tree-level information
  would be required. The field of forest science
  has a strong history of very effective empirical
  modeling (Raushcer and Michael, 1987; Bruce,
  1988).

       In the process model, on the other hand,
  the outputs (or the  predicted values) are at a
  higher level than the data.   To  construct a
  process model of trees, we would use informa-
  tion from the level of the organ (or perhaps an
  even lower level).  A general rule of thumb in
  modeling is to  avoid spanning more than three
  levels of hierarchy in a single model.  The lower
  level would provide  insight into system behav-
  iors observed  at the "intermediate" level. The
  highest  level involved  in the simulation reveals
  the impact of  the simulated  activities at the
  intermediate level. The success of an attempt
  to span a number of levels, such as an effort to
  model trees directly from the level of the oTgan-
  elle, for  example, would be questionable.

       The information  embodied in  functional
              Empirical model


              - levels of prediction
                and empiricism coincide


              - correlation between variables
                represented

                   'Top-down"


              - many approximations &
                assumptions hidden
 Process (mechanistic) model

 - level of empiricism lower

  than level of prediction


 - causality between variables
  explicitly represented

      "Bottom-up"
- many more approximations &
  assumptions explicit
                      — initial information content may be no different —


                                             - greater potential for improvement


                Figure 3. Contrasting characteristics of empirical and process models.
 148

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                                                               Modeling Tree Level Processes
relationships of  the  empirical and process
models also differs  (Rauscher and Michael,
1987).  The general  form  in which the ideal
empirical model is expressed is:
y = f (measured factors, non-measured factors,
measurement error)  for a given  response  y.
The form taken by the process model is  y = f
(measured factors, measurement error), with
the assumption that all factors known to influ-
ence y significantly have been accounted for.
The definition is very precise here. All factors
known to influence y significantly. The determi-
nation of significance is a subjective judgment.
The implication is made that the system is well
understood.

    Characteristics  of empirical models and
process models are contrasted in Figure 3. The
level of empiricism is lower than the level  of
prediction in the process  model, whereas they
coincide in the empirical approach. Empiricism
is common  in process models, but the role it
plays is different than in  the empirical model.
The role  of the lower level empiricism in the
process model  is to  explain why a process
occurs, rather than to predict what the process
does. The level of empirical  information is lower
than the level of prediction.

    Correlation between variables is charac-
teristic  of empirical models.  One event has
been observed to accompany another, whether
or not  the  phenomena  have a cause/effect
relationship. Indeed,  it has often been  stated
that correlation  does not imply causality.   In
contrast, the process model emphasizes cau-
sality.  What are the cause/effect relationships?
A great deal of effort is spent determining ulti-
mate causes of the system behavior. A number
of changes have been measured in plant growth
when the plants are exposed to pollutants. But
are those changes causes or are they effects?
It may be possible that a few cause/effect rela-
tionships, coupled with normal linking of feed-
back and regulatory systems within the plant
would  predict all of the changes that are ob-
served.
     Empirical modeling often  utilizes a "top-
down" viewpoint.   A pattern emerges that is
visible in overview.  The process-approach is
more typically "bottom-up"  Based on what is
known about the processes in question, a simu-
lator is constructed, and queried in an attempt to
recreate observed behaviors. These trends are
general, however, and it is possible to use either
of the two perspectives in empirical or process-
based approaches.

     In empirical models, many of the approxi-
mations and the assumptions are hidden. They
are imbedded somewhere in the error terms
and in the coefficients. In a process model the
attempt is made to make more  of the  approxi-
mations and assumptions explicit.  It may be
assumed that the plant is free from most stresses
(such as those due to water or nutrient deficits,
or stressful temperature conditions.  Essen-
tially, one assumes that the plant is in good
shape apart from a  factor that is out of the
beneficial range.

     It is interesting  to note that similarly fo-
cused empirical and process models often ini-
tially provide the same information. However, a
process model has greater potential for refine-
ment and application to subsequent problems.
As more is learned  about the system, more
detail can be included in the simulated pro-
cesses. There is also a difference in what can
be accomplished over time with each approach
(Figure 4;  Leary, 1985).   Empirical models
produce  impressive  results  in  a fairly short
period of time, until the information content of
the data set is fully exploited.  A process model
should provide an informational  underpinning,
providing the ability to go beyond the particulars
of a given data set to general insights applicable
more universally.   The disadvantage is that
initial progress appears much slower.

     An empirical model  usually arises from
statistical analyses of observations taken at a
given point place and time, and of given specific
entities (in this case, trees).  The tremendous
                                                                                     149

-------
Cheryl Aeschbach Gay
              Progress
                                      Empirical
                                                                Process
                                           Time
                 Figure 4. Perceived progress over time in process and empirical models.
                                  Modeing   objectives
                                      and   approaches
                                      PhotoeynthMto
                            Mendels laws of genetic inheritance
                                  'everywhere and nowhere'
                                         Explanation
                          Estimation

                Forestry yield models
precisaon
              Abstraction
                Theoretical
                population dynamics
                'somewhere'

               Figure 5. Objectives and approaches to modeling, with examples of each type.
 150

-------
                                                                Modeling Tree Level Processes
variability in the genetic potential of plants to
respond to  various external factors has often
been stated. There is variation in soil type.
There is  variation  in climate.  The  empirical
model can be difficult to surpass in recreating
observed behavior of particular trees at a given
site, for the time frame for which data was
collected.  What happens when events occur
which those trees have not previously experi-
enced, when the genetic  stock is varied, or
when extrapolations are made beyond the range
of previously observed responses?

   Modeling objectives and approaches

     Objectives and  approaches to modeling
differ, as described by Levins (1966), and range
can be expressed in a triangle (Sharpe, 1988)
(Figure 5).  Objectives range from representa-
tion of reality, to attainment of precision in
prediction, to presentation of general principles.
To achieve these objectives requires diversity
in approach. Estimation approaches are used,
for example, in the formulation of empirically-
based forestry yield models. The model repre-
sents observations that were made "somewhere"
(Trow, 1984), identified at a point in time, and a
place. Models arising from this approach incor-
porate  reality and  precision, and commonly
attain a very impressive degree of precision, but
lack generality.

     A second approach is that of explanation.
Examples of this type of model  are the tradi-
tional process models.  Explanatory models
apply "everywhere and nowhere" (Trow, 1984),
and are represented by models such as the
mechanisms of photosynthesis and Mendel's
laws of genetic inheritance. The models should
apply everywhere,  yet no  one has observed
those specific laws working infallibly in any one
place. Reality is represented, with a degree of
generality, but precision may suffer.

    The third approach is abstraction, charac-
terized by such methodology as that used in the
study of theoretical population dynamics. The
resulting models are  precise, yet describe
general trends in behavior; however, they may
lack the ability to depict reality.

     In brief, with a single approach, one may
reasonably expect to achieve any two of these
three kinds of objectives  but cannot expect to
attain the third. It should be emphasized that
the types of information available from a model
depend on the modeling approach taken.   A
very real concern  is that oftentimes information
will be requested  from models which were not
designed to  provide it, such  as  the  use of
explanatory models for the provision of quanti-
tatively  precise predictions.  In such  an  in-
stance,  on the contrary, the  other two ap-
proaches - abstraction and estimation - should
be  used, since they  are  designed  to provide
precise predictions.

     The description of the validation process is
always a challenge. Validation procedures and
criteria differ for the  three types of modeling
approaches just mentioned, and are outlined in
Figure 6. An empirical validation approach is
suitable for  validation  of estimation  models.
The models are developed  directly from data.
Their validity can  also best be judged through
agreement  of their predictions  with indepen-
dent data. The precision of their predictions can
be  judged via the use of statistical methods
designed for quantifying precision.

     The abstract and explanatory models fall
into the category of process models.  The ab-
stract model is developed independently of a
particular set of data, or of reality.  Since the
interest is not in precision of representation of a
set of data, the validity of these abstract models
is  based instead on the correctness  of the
mathematical manipulations.  Validation be-
comes more of a mathematical exercise. No
particular data sets would  be suitable, because
all data contain various unregulated, compound-
ing effects of genetics and  environment that
may differ from place to place.  For example,
latitude  is often  a very  important influential
                                                                                      151

-------
Cheryl Aeschbach Gay
                Empirical
  Process
^- ^
Estimation models
- developed directly
from data
- validity based on
agreement with
independent data

- judged on basis of
statistical precision
. 	 	 "
Abstract models
- independent of data
- validity based on correctness
of mathematical manipulations
used to develop final
equation set

- judged on basis of
intellectual rigor
consistency
• 	 ^
Explanatory models
- generic concepts based on
supporting evidence
- validity based on
their ability to interpret
observed phenomena in
terms of cause-effect
relationships
- challenging to validate
- judged on basis of
logic
experimental evidence
            Figure 6. Validation criteria and procedures for the three types of modeling approaches.
factor in plant response.  If latitude is influential,
but its effects are not included, data from vari-
ous latitudes would be unsuitable for validation.
One conclusion is that the results of the abstract
model are also abstract.   The worth  of the
abstract  model is based on intellectual rigor.
The predictions are consistent and plausible,
yet are not expressed quantitatively, with pre-
dictable  confidence intervals.   They are not
designed to provide that type of information.

     Explanatory models, again, are a type of
process  model. Data enter into explanatory
models  as supporting evidence, but are not
employed directly in model formulation. Trends
observed in the data are taken into account.
The general observations that repeat time and
again lend the  shape to the processes being
explained.  The validity of these  models  is
based on their  general ability to interpret the
observed phenomena, again not with precision,
but with  a consistent ability to predict trends.
Validation is challenging, due to the question of
how close is "close enough."  The model may
match trends, but a failure to account for all
important trends may not be recognized.  Ob-
served discrepancies could arise from environ-
mentally  or genetically driven normal variation
as well as from systematic shortcomings of the
model. The model structure is based on logic
and experimental evidence.  The  model can
only be validated by its ability to generally track
phenomena that have been observed.

     It is important to note that a model need not
be restricted to a single approach.   Models
which have been developed utilizing different
modeling approaches may be, and often are,
coupled.  This coupling provides the capabili-
ties to create aggregated models  capable of
displaying all three  attributes of reality, preci-
sion, and generality.  King et al., 1988,  have
described a general procedure for integration of
process- and empirically-based models, useful
in linking  physiological and forest dynamics
models.

               An example

     The topic of this paper is the modeling of
whole-tree  processes.  The  structure of the
whole tree modeling system of the FRP can be
seen in Figure 7.  The major processes in the
system are  being addressed by a number of
research groups within the FRP, with the indi-
vidual processes divided along either  discipli-
 152

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                                                                 Modeling Tree Level Processes
                               Nutrient
                               and Wate
                               Uptake
Figure 7. Schematic of a whole tree model under development to address the impact of atmospheric pollution.
nary lines or spatial orientation.  To facilitate
modular  development  efforts, the numerous
processes comprising the system have been
carefully delineated, minimizing required inter-
action between modules.

     The emphasis is to simulate the effect of
pollutants on the growth and changing morphol-
ogy of a tree. The effect of pollutants, however,
is not at the tree level,  but at the levels of the
numerous subprocesses acting in concert  to
form the tree. Research in model development
is focused on determining the process, or proc-
esses, that are directly impacted by the pollut-
ants, or defining the first cause/effect relation-
ships which are ultimately responsible for the
effect of pollutants on tree development.

     One module of the  system, the Foliar
submodel, as mapped out in  Figure 8, will now
be discussed in more detail.
     The major working hypothesis in the foliar
processes model is that normal foliar activities
are modified by deposition of the mineral ele-
ments in acid precipitation that are also used in
normal needle function. Initial effects occur due
to tissue damage and alteration of the efficiency
of the processes  such as photosynthesis and
stomatal control (and ultimately respiration and
transpiration).   Ultimately, revision of the bal-
ances of these normally occurring foliar nutri-
ents could reduce the efficiency of physiological
processes, even without signs of visible dam-
age.

     The activities of foliage located on a given
branch of a mature tree are under scrutiny. The
states of interest in  this subsystem include
nutrient status, carbohydrate status, develop-
mental age,  and needle amount. The location
on the tree,  and its  maturity, are conditions of
the environment of the branch which also influ-
ence the values of these state variables.  Foliar
                                                                                       153

-------
Cheryl Aeschbach Gay
                           ENVIRONMENT/POLLUTANT:
                         Age
                         (ontogeny)
                         growth
                         maturation
                         senescence
             allocation
                           Carbohydrate

                           photosynthesis
                           respiration
                           Export  pool to  branch
                                      and  bole
Figure 8. Diagram of processes addressed in a model of foliar processes designed to address pollution response.
functions which are of major concern in  the
model include growth/maturation, photosynthe-
sis/respiration, and nutrient reallocation (Figure
8).  Although foliage is not limited to these ac-
tivities, the mentioned processes encompass
the major avenues of acid precipitation influ-
ence on foliage.  These states and processes
(and their interactions) define a simplified sys-
tem encompassing the dominant pollutant re-
sponses. Water use through transpiration and
evapotranspiration will be assumed to be non-
limiting, and is not addressed further.

    Input to the system are environmental de-
scriptors including weather and pollutant infor-
mation.  Supply of nutrients from  the roots
through the bole is input.  Branch autonomy is

 154
assumed, providing a zero carbohydrate input.
The Branch model supplies morphological in-
formation on the number of branch segments of
each type (age cohort and their order).

    Output from the system will be net carbo-
hydrate available for branch- and  bole-wood
growth and respiration.  Information generated
within the model are the values of the previously
listed  state  variables. This net carbohydrate is
the main contribution of the foliage to the rest of
the tree, and as such, will be the input to other
processes occurring on the tree.

    Leaf area  is calculated as a function of
thermal time, and constants which characterize
typical growth rates and maximal needle areas

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                                                                Modeling Tree Level Processes
of typical branches. Increase in leaf area occurs
during the expansion period of needle growth.
Leaf mass/unit area changes dynamically with
season and age. Total leaf weight is calculated
by multiplying the area of a particular segment
of needles by its particular mass/unit area.

    Tissue age plays a central role in the leaf
model. "Age" represents physiological age, and
is used as an indicator of tissue integrity. Age
is calculated as af unction of thermal time elapsed
since needle emergence, and the expected life
span of the needle tissue.  At emergence of the
needles, the tissue has an expected life span (in
thermal time) characteristic of the species. Tis-
sue age is predicted as a normalized value, and
is the ratio of elapsed thermal time to the ex-
pected life span.

    Needles grow in the spring as described
above. Carbohydrate is fixed via photosynthe-
sis during the summer growing season. During
autumn, additional branch thickening takes place
(as simulated in the branch growth model).  If
insufficient  branch wood  is  incremented  to
support the foliage present on the branch (de-
termined in the branch growth submodel), loss
of the excess foliage is then predicted to occur
late in the season.

    Tissue nutrient concentration is governed
by the rates of  input and  outflow  from the
needles.  Input of mineral nutrients is from root
uptake and reallocation from older  foliar co-
horts. Root uptake is not  simulated within this
model, but is accepted as input.  A balanced,
ample supply  of  nutrients from  the roots is
assumed, so the variable quantity determining
source strength is the changing quantities of
aging needles.

    The rate of nutrient retranslocation is  a
function of relative sink and source strengths.
The sink is the newly expanding foliage, and the
sources are the soil and the adjacent older
foliage.  Nutrient loss from a foliage cohort is
through reallocation  to a younger needle co-
hort, and leaching. Nutrient movement through
reallocation to the younger foliage is governed
by season change.

     Nutrient leaching is a function of cuticular
resistance, rain amount, and the ion concentra-
tion gradient between foliage and rain.

     A  number  of  excellent photosynthesis
models are already in existence.  They range in
degrees of complexity and aggregation.  Two
models of conifer gas exchange have been
developed by Lohammar et al., (1980) specifi-
cally to provide a suitable biological background
for the modeling of plant growth.  One model is
complex, and operates on a 5-minute time step,
while the simplified model operates on a daily
basis. The simpler version will be employed to
provide photosynthetic calculations required in
the Foliar processes model, providing estimates
of daily net photosynthesis, transpiration rate,
and water potential.

     Photosynthetic capacity declines with leaf
age, and in many cases reflects a reallocation of
nitrogen (Chabot and Hicks, 1982).  Photosyn-
thetic capacity in the model is therefore gov-
erned by leaf age and nitrogen concentration.

     Like the concentrations of mineral  ele-
ments, foliar  supplies of carbon also change
over the growing season. A within-leaf storage
pool of labile carbohydrates contains carbohy-
drate that is not used immediately in growth.
The  rate of movement of this stored carbohy-
drate is a function of season, which governs the
movement between foliage and other tree or-
gans (roots, branch  and bole meristems).

     In the Foliar model, emphasis is placed on
the simulation of chronic damage  by atmos-
pheric pollutants, where foliar  activities  are
hampered, ratherthan irreversibly and radically
altered.  Simulation of the complications of
damage due to more severe disruption are
beyond the scope of the model.
                                                                                      155

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Cheryl Aeschbach Gay
     Changes in net carbohydrate production
induced by pollution are modeled in two ways,
one immediate and the other long-term. Imme-
diately, atmospheric pollution decreases the
photosynthetic efficiency of the foliage for the
day of pollution exposure. Exposures to chronic
levels of pollution decrease the life expectancy
of the tissue. The result of this decreased life
expectancy are that the leaf tissue ages  more
rapidly. Leaf aging, in turn, is associated with
lowered photosynthetic capacities.

     The effect of acid rain on cuticle function is
also simulated as an acceleration  of the aging
process, similar to the method used for chronic
air pollution effects on tissue  maturity.  With
increased age, retention of moisture on the leaf
increases, representative of increased surface
roughness. As the cuticle ages, it also provides
lower resistance to leaching, thus resulting  in
greater rain-induced nutrient loss.

               Conclusions

     A common basic assumption in tree simu-
lation is that of the maintenance of a particular
allometric structure. Maintenance  of a particu-
lar allometry may help to constrain model pre-
dictions to those behaviors most typically ob-
served. However, the constraining effects  of
fixed  allometry may  prove  to  be a serious
downfall in predicting the effects of  environ-
mental changes.  Environmental stresses can
affect the trees in such a way as to disturb their
generally-observed  regular  structure.   This
realization requires the formulation of a  more
mechanistic approach to the regulation of mor-
phology.  The linking of a model simulating
changes in foliar status to the model of branch
morphology as described above, is a step to-
ward  determining the cause-effect nature  of
evolution of tree form.

     The Foliar processes submodel will also
serve to extend a model simulating stand-level
processes. In this role, foliage is addressed  at
the canopy level, rather than a single branch.
Because of their empirical background, stand
models embody the attributes of  reality and
precision. Numerous empirically-derived stand
models are in existence that have a history of
satisfactory performance.

     In the FRP's regulatory objectives, a rea-
sonable level of precision is required. However,
predictions will be made for responses of trees
to air pollution  which are expected  to occur
outside the range of the environmental condi-
tions from which most stand models have been
developed. This predictive proficiency demands
the capabilities of generality, which are outside
the strengths of estimation models. The addi-
tion of the process-level foliar subcomponent to
the empirical stand model should extend the
stand model's capabilities to include generality.
This union of the  two methodologies should
fortify the reliability of the stand model in these
unknown conditions, and provide for defensible
extrapolations beyond the range of  the data
from which the original  stand model was de-
rived.

     These various model components  have
been developed utilizing various of the three
developmental approaches.  Combining them
is a  robust approach to meeting information
needs.  The aggregate models utilize the par-
ticular strengths associated with the approaches
used to assemble the parts, and provide tools
with the capabilities of incorporating current sci-
entific knowledge to provide predictions which
possess the characteristics of realism, general-
ity and precision.

            Acknowledgments

     I would like to thank Dr. Dominique Bache-
let, Dr. William  G.  Warren, and Dr. William E.
Winner for their valuable comments.
 156

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                                                                          Modeling Tree Level Processes
               Literature Cited

Bruce, D., Development of empirical forest growth mod-
   els.  Presented at the conference - Forest Growth:
   Process Modeling of Responses to Environmental
   Stress. Gulf Shores, Alabama, April 19-22, 1988.

Chabot, B. F., and D. J. Hicks.  1982. The ecology of leaf
   life spans. Ann. Rev. Ecol. Syst. 13:229-59.

King, A. W., W. R. Emmanuel, and R. V. O'Neill. Linking
   mechanistic models of tree physiology with models of
   forest dynamics: problems of temporal scale.  Pre-
   sented at the conference - Forest Growth: Process
   Modeling of Responses to Environmental Stress.
   Gulf Shores, Alabama, April 19-22, 1988.

Leary, R.A.  1985.  A framework  for assessing and
   rewarding a scientist's research productivity.  Scien-
   tometrics 7:29-38
Levins, R.  1966.  The strategy of model building in
    population biology. American Scientist54:421 -431.

Rauscher, H. M.  1987.  Comparing empirical and ex-
    planatory models.  IUFRO S6.02 Working  Party
    Newsletter #9. (September, 1987).

Sharpe, P.J.H.  Forest process modeling: scope, limita-
    tions and opportunities. Presented at the conference
    - Forest Growth:  Process Modeling of Responses to
    Environmental Stress. Gulf Shores, Alabama, April
    19-22, 1988.

Trow, G.W.S. 1984. Annals of discourse: the Harvard
    Black Rock Forest. The New Vor/cer(June 11,1984),
    pp. 44-99.
                                                                                                   157

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                  Session
                 III
Bioindication and Protected Area Monitoring
                           -. David Shriner, Local Organizer

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                                     Introduction
     The theme of  the third  session  of the
Second US-USSR Symposium on Air Pollution
Effects on Vegetation was "Bioindication and
Protected Area Monitoring." The session was
held at the Great Smokey Mountains National
Park, an international biosphere reserve. This
theme was chosen in recognition of the interna-
tional need to establish coordinated programs
of long-term ecological monitoring in order to be
able to establish meaningful  baseline  data-
bases against which environmental change in
response to man's activities might be  meas-
ured.

     Papers on the first day of this session were
aimed at a review of past and current approaches
to biological/ecological monitoring and at future
needs to monitor changes in the environment.
     On the second day, a workshop format
was used to focus discussion on the emerging
issue of global climate change as an example of
the need for long-term environmental monitor-
ing. Discussion covered the measured climatic
record, effects of elevated CO2 and climate
change on vegetation, and the methods avail-
able to extrapolate estimates of change to re-
gional, continental and global scales.

     On the third day, participants visited Na-
tional Park Service  and Oak Ridge National
Laboratory research sites in the Great Smokey
Mountains National Park where research on the
effects of atmospheric deposition is being car-
ried out in high elevation spruce-fir forest eco-
systems.


                        David Shriner
 160

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                Welcome and Charge to the Conference
  Bioindicators, biomonitoring, natural area protection and global change—
  the environmental issues, scientific challenges and their interrelationships
                                     David E. Reichle
                             Director Environmental Sciences Division
                               Oak Ridge National Laboratory*
                               Oak Ridge, Tennessee, U.S.A.
    Ladies and gentlemen, workshop partici-
pants, speakers, representatives of sponsoring
federal agencies and particularly our  Soviet
guests...it is my pleasure to welcome you to this
second bilateral  U.S./U.S.S.R. Symposium on
Air Pollution Effects on Vegetation. A number of
the U.S. scientists present here today enjoyed
your hospitality at the first symposium in 1982 in
Tallinn and Leningrad, and it is our pleasure to
return your courtesy at this time.

    I  want to acknowledge the sponsorship of
this symposium by the U.S. Forest Service and
the U.S. Environmental Protection Agency. We
extend our thanks to Superintendent Pope and
his staff of the Great Smoky Mountains National
Park for their local support. I want to thank Dr.
David  Shriner  of the Environmental Sciences
Division at Oak Ridge National Laboratory for
organizing this symposium, and, on his behalf,
express our appreciation to the organizers and
speakers at the symposium today on Bioindica-
tion and Protected Area Monitoring and tomor-
row's  workshop on Global  Climate  Change.
And, finally, we  extend a special welcome to
Oleg Blum who spent several weeks working
with us at Oak Ridge last summer.

    The topics of discussion during the next
two days are extremely appropriate  for this
symposium since they focus on  international
environmental issues and recognize the need
to:

    protect natural resources
    identify the global nature of environmental
    pollution
    appreciate the importance of developing
    bioindicators,  and to  anticipate  global
    change
    understand the importance  of projected
    natural areas for long-term monitoring and
    research

    This is also an extremely appropriate loca-
tion for this  symposium, since the Southern
Appalachian Biosphere Reserve is a model of
natural area protection, monitoring, and experi-
mental research sites, as well as interinstitu-
tional cooperation among all of the major envi-
    'Operated by Martin Marietta Energy Systems,  Inc.,  under contract DE-AC05-840R21400 with the U.S.
 Department of Energy.
                                                                                  161

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David E. Reichle
ronmental institutions in the region.

     You are here in Gatlinburg, Tennessee, in
the heart of the U.S. Eastern Deciduous Forest
Biome glacial refugium and the region of great-
est biotic diversity  in  the  continental  United
States. Along the altitudinal, microclimate and
soils gradients of this region  are found repre-
sentatives of the major forest plant communi-
ties between Florida and northern Canada. The
unique research sites and collaborating institu-
tions are represented by:

     The Great Smoky Mountains National Park
     and central core of the Biosphere Re-
     serve
     The Coweeta Hydrologic Research Labo-
     ratory of the U.S. Forest Service
     The University of Tennessee
     The Oak Ridge Environmental Research
     Park of the U.S. Department of Energy
     The U.S. Forest Service—Cherokee and
     Pisgah National Forests

     We are  faced with a number of global
environmental problems. As scientists, we have
learned that few environmental insults have
only local  consequences—DDT and  ocean
dumping of wastes have clearly illustrated the
global  consequences  of local  environmental
activities.   As one  perspective, there are a
number of potential global environment issues
which the U.S. Department of  Energy has iden-
tified as possible consequences of energy tech-
nology development.

     greenhouse effect (trace gases)
     "Chernobyl" incidents
     acidic deposition
     coastal zone development
     geologic waste disposal
     biomass for energy
     North Slope development
     nuclear winter
     geothermal energy development

    In addressing these pragmatic environ-
mental problems, as scientists, we find that they
all have common  scientific components and
thatourscientificdata, understanding, and meth-
odologies are yet inadequate to resolve these
issues so that sound international environmental
policies can be established. These scientific
components involve  determining mechanistic
processes linking  different subsystems and
temporal and spatial scales of interfaces:

     identification  of interfacial linkages
     quantification of critical processes
     extrapolation across temporal and spa-
     tial scales
     development of hierarchically nested
     global models
     validation and testing of global models

     The  key scientific challenges are those
dealing with  linkages among  environmental
subsystems—the interfaces between the biotic
and abiotic environment—and also those deal-
ing with the incongruities in scales of space and
time over which different environmental proc-
esses  operate. While we  attempt to identify
important global environmental processes, to
understand how the environment works and to
struggle  with how to use  experimental  data
(local site, short-term) to address environmental
issues of broad scale and long-term duration, it
becomes  obvious that (I) we cannot afford to
(nor do we have the time to) study every ecosys-
tem in infinite detail in order to protect it, and (2)
we must devise means to anticipate ecological
damage before it occurs. This is where bioindi-
cators  and biomonitoring  will  play such an
important role in the future for environmental
protection.

     While I do not want  to intrude into the
substance of the presentations at today's sym-
posium on Bioindicators and tomorrow's work-
shop on Global Climate Change. I do want to
stress how interrelated these topics are to the
overall theme of this meeting:

     Protecting natural areas will require eco-
 162

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                                                      Welcome and Charge to the Conference
logical research to understand  mecha-         hopefully avoiding) deleterious ecological
nisms of pollution effects                        effects of human activities.
We are dealing with an issue of global ste-
wardship and global environmental proc-         Again, I welcome you; I hope that you find
esses                                     these topics stimulating; we are eager to ex-
Developing sensitive bioindicators is a nee-    change our thoughts with you.
essary prerequisite to anticipating  (and
                                                                                   163

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        Monitoring the  Environment in the 21st Century1
                                  Stanley I. Auerbach
                               Environmental Sciences Division
                                Oak Ridge National Laboratory
                           Oak Ridge, Tennessee 37831-6036, U.S.A.
     Many years ago when I was a boy, there
was  a  popular science fiction radio program
whose hero fought villains and loved maidens in
a future century. Because the story was derived
from the fertile imaginations of skilled science
writers who could draw on the principles of hard
science and engineering, it was relatively easy
for these writers to come up with rocket ships
made of impervium whose crews were armed
with disintegrator pistols. The plots, of course,
were always variants of good-versus-evil. The
hero, accompanied by his heroine and assisted
by the old and brilliant scientist, fought to save
earth—and usually his heroine—from a wide
assortment of interplanetary villains.

     When Dave Shriner suggested that I talk
about this particular topic— monitoring  in the
21st century—almost immediately I recalled the
radio announcer speaking in a sonorous and
stentorian voice-   "BUCK ROGERS IN THE
25TH CENTURY."  I, however, kept transpos-
ing that phrase to "Stanley Auerbach in the 21 st
century." There are, of course, several signifi-
cant  differences  between those  two futuristic
scenarios, not the least of which is that I dis-
tinctly am not a hero soaring about by means of
a rocket belt. But, more seriously, we are trying
to perceive a future century whose beginning is
only 13 years away, in contrast to one that is half
a millennium ahead of us.  We are also faced
with the challenge that the realities of tomorrow
are inextricably related to the problems of to-
day.  And while it  might  be fun  to use our
imaginations to predict or fantasize about likely
possibilities 25 or 50 years from now, as scien-
tists, we need more than imagination to predict
events or activities in  the future—especially
activities which require the involvement of dif-
ferent societies, multiple governments, and other
manifold social and political pressures.

     There is an old, very familiar observation
that the past serves as a prologue to the future.
I think that this phrase is especially appropriate
for issues of wide social, economic, and political
involvement, such  as those  dealing with the
environment. What we will  be doing in the field
of environmental monitoring, at least in the first
half of the 21st century, is  likely to be derived
from the developments and issues in this latter
part of the 20th century.
'Research sponsored by the office of Health and Environmental Research, U.S. Department of Energy, under contract
DE-AC05-840R21400 with Martin Marietta Energy Systems,  Inc. Publication  No. 3198, Environmental Sciences
Division, ORNL.
                                                                                     165

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Stanley I. Auerbach
     We are now completing the second dec-
 ade of major environmental activity in this cen-
 tury. Prior to 1970, public awareness of envi-
 ronmental issues was nearly nonexistent. Gov-
 ernments had little or no interest or authority to
 deal with environmental problems except where
 connections to matters of public health were too
 obvious to  be ignored.  It took a number of
 dramatic events to arouse public awareness to
 the point that it served as the essential impetus
 to political  action.  Environmental awareness
 rather quickly demonstrated that it knew no
 national borders. Earth Day and the Stockholm
 Conference on the Human Environment both
 catalyzed and crystallized the beginnings  of a
 movement  which  was to transcend political
 boundaries and become an issue of consider-
 able importance in most countries.

     Environmental  actions followed  in  the
 decade of the seventies, not only in the United
 States but in many other countries. New minis-
 tries for environmental  protection were estab-
 lished,  and laws were  passed regulating the
 disposal of residuals and protecting environ-
 mental resources.  Of course, the legitimacy of
 the environmental  issue was questioned in the
 public arena based  on economic, social, or
 other considerations. While this aspect of the
 struggle still goes on, and probably will continue
 for the rest of the century, the  public and,
 therefore, the political bodies in more and more
 countries have recognized the legitimacy of the
 environmental issue.  What tends to be in ques-
 tion  is the extent of effort and resources to be
 used or degrees of control to be applied in the
 protection  of the environment.  Such  broad
 questions of policy require sound information
 widely understandable to the public in order for
 positive political decisions to be made. It is the
 public which drives the system.  I re-emphasize
 this well-known fact because without good in-
 formation it is difficult for the public to reach a
 consensus.

     In  1970, the U.S.  Environmental Protec-
 tion Agency (EPA), charged with protecting the
environment in all its aspects, was established
in the federal government. Enabling legislation
was passed for air, water and soil—all aimed at
either protecting the environment or requiring
cleanup of pollution. Cleanup included a mas-
sive country-wide construction program to build
12,000  new municipal  sewage  treatment
plants—an  absolutely essential  step toward
improvement of water quality in  our streams
and lakes.  Perhaps the most influential law to
be placed on the books at the beginning of this
decade was the National Environmental Policy
Act. This law introduced the concept of environ-
mental i mpact assess ment—a concept that was
initially controversial but eventually served as
the cornerstone of environmental programs in
the United  States and subsequently in many
other countries as well (Hedeman, 1980). Analy-
sis  of baseline  conditions was a part of the
assessment process in most cases. Obviously,
any predicted changes  from baseline would
require  some kinds of systematic  means to
detect  and evaluate change.   This  type of
monitoring was somewhat new. Most monitor-
ing programs of  that time were, and even today
are, for compliance purposes; that is, they serve
a regulatory function, ensuring that standards
governing the release of pollutants or noxious
substances are  adhered to.

     By the end of the decade, environmental
issues had become established as a significant
political and social issue. Much progress had
been made,  including advances in environ-
mental science; however, many problems and
issues were still on national and  international
agendas.   As  Russell Train, EPA's second
Administrator, pointed out, "The energy crisis,
together with the mounting evidence that pollu-
tion is even more widespread and harmful than
the Nation had realized, has increasingly brought
home the fact that environment is not simply
another problem to be solved or crisis to be
surmounted" (1980).   Rather, environment is
the overall  context or framework  within which
we  must work with all the other social, political,
and economic problems—especially energy.
  166

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                                                   Monitoring the Environment in the 21st Century
    We are finishing the second "decade of the
environment." It may be useful to reflect on the
major problems that were identified at the be-
ginning of the 1980s in order to provide  per-
spective on the speed at which environmental
problems are resolved, especially those  that
require new  knowledge to support action.  A
President's Commission (1980)  had  much  to
say about unresolved and developing environ-
mental problems. Here are some examples of
statements issued:
• "The earth's air is seriously threatened.  The
three global atmospheric problems ... are the
increase of carbon  dioxide retained by the at-
mosphere, the formation of acid rain,  and the
depletion of the ozone."
•  "Forests are disappearing at alarming rates
with serious environmental consequences."
•  "Land use problems include the destruction
of coastal wetlands and the loss of prime top-
soil."
    "Another aspect of the chemical  pollution
problem is groundwater contamination."
• "The critical question now is how to anticipate
the consequences of new environmental  haz-
ards, especially those of global scale."

     Now almost a decade later, we know with
greater certainty that these problems are not
only still with us but also will remain as chal-
lenges to both science and  society for the
remainder of the 20th century. The approaches
that we  use to understand and resolve these
problems and issues in  the next 13 years will
provide the foundation for 21st-century activi-
ties.  Moreover, it  is increasingly recognized
that research in and of itself will be insufficient
to answer some of the key global environmental
questions that will  be facing us in the  21st
century.

    More than  ever we recognize earth  as a
complex physical and biological system whose
components  are linked in complex and subtle
fashions and operate through complicated bio-
geochemical processes and cycles. One of the
most exciting developments of the latter half of
this decade is the recognition by increasing
numbers of scientists from all countries of the
need to study earth as a system. To this end, an
international research effort, currently called
the International Geosphere-Biosphere Program
has been established. This program, in turn, is
considered to be part of a broader effort known
as earth system science.  The goal of  earth
system science is to obtain a scientific under-
standing of the entire earth system on a global
scale  by describing how its component parts
have evolved, how they interact, how they func-
tion, and how they may be expected to continue
to evolve (NASA,  1986).

    More than ever, we will need capabilities to
determine changes and trends in ecosystems
or in the environmental parameters that influ-
ence  these  systems.  To understand many
geosphere-biosphere phenomena and their
interactions, monitoring over long periods will
be  necessary.  For example,  to detect and
separate  anthropogenically  caused  climate
changes from natural ones and to understand
the mechanisms involved may require adecade
or more of accurate global monitoring of key
atmospheric physical factors.  Yet in compari-
son, we must recognize that when it comes to
systematic monitoring for ecosystem  change,
we still face enormous challenges. In the ab-
sence of lack of fundamental understanding of
many environmental processes  at  different
scales of complexity and  interaction,  what to
measure routinely and where and how to meas-
ure it are anything but simple questions.

    Long-term  monitoring  strategies  are
deemed essential for determining changes or
trends in ecological systems or in the parame-
ters influencing these systems. Monitoring in-
formation can be made essential to hypothesis
formulation,  hypothesis testing, and ecological
risk analysis. Perhaps the greatest opportunity
lies in developing a strategy that yields informa-
tion of an anticipatory or predictive nature rather
than results  that are retrospective.
                                                                                    167

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Stanley I. Auerbach
     As important as  monitoring efforts are,
 historically, they have  been characterized by
 numerous limitations and  deficiencies.  For
 example, monitoring programs in the past have
 lacked definition and long-termjustification. They
 have failed to recognize temporal and spatial
 dimensions or scale.  Data sets from uncorre-
 lated monitoring programs may not have been
 compatible nor  comparable; and  monitoring
 efforts directed at documenting change in bio-
 logical  systems have  not  adequately distin-
 guished between anthropogenically induced and
 natural  changes.  I am sure that other deficien-
 cies could be added to this listing.

     In  spite of these problems, there is a grow-
 ing  recognition  among  responsible environ-
 mental  scientists that monitoring is too impor-
 tant to be relegated to a scientific version of the
 back burner.  Nor  is this recognition limited to
 American scientists; the same viewpoints are
 being expressed by many of our colleagues in
 the Soviet Union.  A recent US-USSR sympo-
 sium dealing with environmental analysis pro-
 vides a number of thoughts and ideas that bear
 on our future monitoring challenge (Schweitzer
 and Phillips, 1986).

     One of the lessons we have learned as a
 result of the acid precipitation issue is that a
 long-term  monitoring program designed and
 implemented today may not be directly appli-
 cable to environmental issues 50 years from
 now (Linthurst et al., 1986). In an analysis of
 long-term trends in lake acidification,  a major
 difficulty in interpretation arose because of a
 change in analytic procedures from colorimetric
 to electrometric methods.  In addition, earlier
 monitoring records were based on a nonstatis-
 tical sampling scheme that precluded making
 good estimates of precision later.  There are
 many other examples of past monitoring stud-
 ies with which one can find fault.  But in each
 case, one must be careful to distinguish be-
 tween the reasons for initiating the monitoring
 activity  and the success with which it was car-
 ried out. As is true for all aspects of science, we
learn not only by carrying out the work but also
from the mistakes that may be made.

    New approaches to environmental moni-
toring that may have useful applications in the
21st century are  being explored  by our col-
leagues in the Soviet Union. As reported by Va-
silenko  and his associates, a new type  of
monitoring, namely, snowpack pollution moni-
toring, has been underway in the Soviet Union.
It currently is part of the State Environmental
Pollution Observation  and Monitoring Service
and includes observations at 1000 meteorologi-
cal stations. This system provides data on the
quantities of atmospherically deposited pollut-
ants and their spatial distribution.  With this
system, distributional maps (either by region or
for the whole country) are plotted for pollutant
concentration in the snowpack, rates of deposi-
tion, nitrate and sulfate budgets, and regional
maps for  special pollutants  such as heavy
metals,  benzopyrene, ammonia, and other
compounds (Vasilenko et al., 1986).

    Scientists in  the  USSR State Monitoring
Service are developing a philosophy  of a com-
prehensive and integrated system which will
involve the systematic measurement of pollut-
ant levels in the environment with concurrent
hydrometeorological and biological  observa-
tions.  As Anokhin points out, this integrated
approach offers the opportunity to establish an
ecological service in the Soviet Union.  Such a
service  could  provide scientifically  validated
assessments of ecological consequences  of
anthropogenic impacts (Anokhin et al., 1986).

    The use  of long-term measurements to
determine the  assimilative capacity of an eco-
system  is  another area of interest  to Soviet
scientists.  They have been  particularly inter-
ested in ocean ecosystems. In describing stud-
ies on the assimilative capacity of the Bering
Sea  ecosystem,  Izrael and his  colleagues
emphasize the importance of both understand-
ing and quantifying ecosystem biogeochemical
processes in order  to be able to  assess the
  168

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                                                    Monitoring the Environment in the 21st Century
consequences of continued pollutant inputs.
The key to the development of functional as-
similative ecosystem models is a combination
of integrated studies and a system of monitoring
(Izrael et al.,  1986).

    Global-level  monitoring has been  con-
ducted in the Soviet Union since the early 1970s
at four background stations.  Two of these
stations are located within the European part,
and two areas within the Asian part of the Soviet
Union. Global air pollution  monitoring is also
conducted at seven background stations  lo-
cated  in  Russian  biosphere  reserves
(Sokolovsky, 1986).

    These Soviet activities are examples of
widespread and burgeoning interests in and
activities involving environmental monitoring
being carried out in the majority of countries. In
point of fact, there are so many different kinds of
monitoring networks (local,  regional,  country-
wide, and global) that simply obtaining a listing
of all of them would require a significant invest-
ment of time and resources.  It is  precisely
because of this multidimensional array that  I
believe it will be necessary in the last decade of
this century to define and focus on key systems
whose attributes will be related to specific tasks
or areas. During the past year, there has been
an intensive  planning  effort under way within
EPA for a new program in long-term ecological
research. A key component will be an environ-
mental monitoring and assessment program.
But unlike such efforts in the past, what is being
proposed is an environmental monitoring effort
that will be  coupled with  research and risk
assessment.

    Plans are already  under way for the estab-
lishment of new and highly sophisticated earth
system process monitoring that surely will be in
place by the turn  of the century.  In  the next
decade, global  measurements of the atmos-
phere  and ocean surfaces will see increasing
use of both passive and active microwave tech-
niques, of color imaging for ocean chlorophyll,
and of vastly improved spectroscopy for chemi-
cal analyses.  Lasers, remote sensing,  space
observing platforms, and new imaging capabili-
ties offer tremendous  possibilities for  global
scale environmental  monitoring, and I predict
that we will see many of these in operation by
1999.

     But a major challenge in the 21st century
will be to combine the sophisticated technology
of detection, measurement, analysis, and data
storage that will be available into working sys-
tems  which will rapidly synthesize all  these
data.  Literally billions of bits of information will
be collected in hundreds of monitoring systems.
These systems will monitor different media and
different  endpoints and will be hierarchical  in
that they will function at different temporal and
geographic scales with cross linkages between
systems for exchange of data. Moreover, they
will be operated by a variety of organizations in
different countries. Given the multidimension-
ality of this challenge, it does not seem likely
that one should anticipate a single, all-unifying
monitoring system to be functional at the begin-
ning of the century. Therefore, the challenge in
the next decade is to  begin to address in a
realistic fashion the questions of organization,
methods standardization, centralization versus
decentralization, and related aspects of  estab-
lishing such systems.

     How do  we  keep  monitoring  systems
dynamic  and  not  have them  become mere
collections  of numbers and data that are not
utilized  beyond  simple  checking  for compli-
ance? I believe that they will have to be institu-
tionalized in a manner that provides continuing
challenges in the areas of synthesis and inter-
pretation. By doing so, first-rate scientific staff
can be attracted and maintained. Ideally, these
advanced monitoring organizations should be
linked with or be a component of a research unit
that works on environmental problems at levels
of organization that are compatible with those
being surveyed or monitored. Intellectual dyna-
mism needs to be ensured through ongoing
                                                                                      169

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Stanley I. Auerbach
 opportunities for periodic student participation
 in the work of the monitor center either through
 thesis studies or other part-time arrangements.

      It is  tempting  to visualize  large-scale
 monitoring centers in the next century that would
 look like the National Aeronautics and  Space
 Administration (NASA) mission control centers
 or those of the air defense commands.  Banks
 of sophisticated computer terminals  linked
 through high-speed networks to scores of data
 banks would have large screens where  opera-
 tors could bring up local,  regional, continental,
 or even global data that could  be scaled, syn-
 thesized, superimposed,  examined for tempo-
 ral trends, or analyzed in any other way that one
 could conceive.

      The technology  for  such centers  is cer-
 tainly available. Likewise, there are a number of
 monitoring ideas and approaches in environ-
 mental science that hold considerable promise
 for providing data that can be used proactively
 rather than relying  on our current practice of
 retroactive evaluation. Systems ecologists have
 demonstrated that with knowledge of the  dy-
 namics of ecosystem processes and the use of
 coupled nutrient cycling  models whose para-
 meters and structure  are based on field data,
 monitoring points for measurement of key vari-
 ables can  be identified.  For example, it has
 been shown that a key forest ecosystem nutri-
 ent such as calcium can be monitored by peri-
 odic measurements of its concentration in soil
 water (Shugartetal., 1976). These data  are fed
 into a proactive computerized model system
 and are a basis for determining trends in forest
 ecosystem health.

      Another recent approach that shows prom-
 ise is environmental specimen banking  (Lewis
 et al., 1987). This is the  systematic collection
 and storage of environmental specimens for
 future analysis and evaluation. If the bank is
 designed in such a way that the specimens and
 the ecosystems  from  which they are  obtained
 are characterized to reflect system states, then
temporal or geographic trends in chemical pol-
lutants can  be identified.  Retrospective  or
prospective shifts in pollutant distribution can
be evaluated, and perhaps even the capability
to distinguish man-induced changes from natu-
ral environmental dynamics will be developed.

     Another exciting development which could
have widespread application in the 21 st century
is the use of biosensors  in monitoring instru-
ments  (Rechnitz,  1988).  Biosensors are de-
vices that incorporate biological components
such as  the chemoreceptor  structures from
organisms such as crustaceans, fish, or possi-
bly  even plants into an electronic sensor  or
probe.  For example, a flower-blossom-based
biosensor uses a cross-sectional  slice of a
single magnolia petal coupled to a gas-sensing
electrode for amino acid measurements (Rech-
nitz, 1988).  Other plant-based biosensors in-
clude a cabbage-leaf-based sensor to measure
vitamin C, one based on soybean leaves  to
measure metribuzin, a corn kernel sensor that
measures pyruvate, and a squash-based sen-
sor that can be used to determine glutamic acid.
There  is  a whole world of possibilities for the
development of biosensors for the systematic
monitoring  of pollution effects on vegetation
using plant-tissue-based biosensors. This whole
field is still in  its infancy but offers exciting
challenges to science in the next decade be-
cause  the environmental applications of this
area have  yet to  be  developed,  much less
demonstrated. This much is certain:  the next
decade will offer great opportunities to develop
combination biological and  chemical  monitor-
ing  systems that will be unique and certainly
intellectually stimulating if we choose to meet
the challenge.

     We are also going to enterthe 21 st century
with problems that will impact the environment
of the entire planet.  Of these problems, two, it
seems to me, will be major in terms of potential
environmental consequences. What are these
problems? The first is energy and the second,
population growth. These two problems dwarf
  170

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                                                          Monitoring the Environment in the 21st Century
all others in terms of their environmental conse-
quences.  But I believe that with knowledge, all
problems can be addressed in a manner that is
beneficial to both man and his support systems.

     In that respect,  environmental monitoring
can and should be part of the knowledge devel-
opment base in the 21 st century. Since most of
you will be active at least into the first part of the
century, I would urge you to support the devel-
oping new efforts to create betterenvironmental
monitoring systems and to employ the special
knowledge you are gaining about the effects on
the vegetative components of our terrestrial
ecosystems in the design and implementation
of new and  advanced  ideas  for  monitoring
systems in the remaining years of this century.

              Literature Cited

Anokhin, Y. A.,  N. Ladeishchikov, and M.  I. Anisimov.
   1986. A large-scale observation, assessment, and
   forecasting for heavy'metal atmospheric transport, In
   G.E. Schweitzer and A.S. Phillips (eds.), Proceed-
   ings of the Fifth US-USSR Symposium on Compre-
   hensive Analysis of the Environment. National Re-
   search Council, Washington, D.C. pp. 42-51.

Hedeman, W., Jr.  1980.  The National Environmental
   Policy Act. EPA Jouma/6(10):29-30.

Izrael, Y. A., A. V. Tsyban, G. V. Ivanov, M. N. Korsak, V.
   M. Kudryav-tsev, Yu. L. Volodkovich, and S. M. Ch-
   ernyak. 1986. Comprehensive analysis of the Ber-
   ing sea ecosystem.  In G.E.  Schweitzer and A.S.
   Phillips (eds.), Proceedings of the Fifth US-USSR
   Symposium on Comprehensive Analysis of the Envi-
   ronment.  National Research Council, Washington,
   D.C. pp. 58-88.

Lewis, R. A., J. Gillett, J. C. Van Loon, J. M. Hushon, J.
   L. Ludke, and A. P. Watson.  1987.  Guidelines  for
   environmental specimen banking with special refer-
   ence to the Federal Republic of Germany. National
   Park Service, U.S. Department of the Interior, Wash-
   ington, D.C.
Linthurst, R.A., K. Thorton, P. Kellar, and D. Landers.
   1986. Long-term monitoring of acidification trends in
   lakes:  a regional perspective. In G.E. Schweitzer
   and A.S. Phillips (eds.). Proceedings of the Fifth US-
   USSR Symposium on Comprehensive Analysis of
   the Environment. National Research Council, Wash-
   ington, D.C.  pp. 6-16.

National Aeronautics and Space Administration (NASA).
   1988.  Earth System Science—A Closer  View. Re-
   port of the Earth System Sciences Committee NASA
   Advisory Council National Aeronautics and Space
   Administration, Washington, D.C.

President's Commission for a National  Agenda for the
   Eighties. 1980.  Energy, natural resources, and the
   environment in the eighties. In President's Commis-
   sion for a National Agenda for the  Eighties.  U.S.
   Government Printing Office, Washington,  D.C.  , p.
   57.

Rechnitz, G.A. 1988. Biosensors. Chemical  and Engi-
   neering News 66(36) :24-36.

Shugart, H. H., Jr., D. E. Reichle, N. T. Edwards, and J.
   R. Kercher. 1976. A model of calcium-cycling  in an
   East Tennessee Liriodendron forest:  model struc-
   ture, parameters and frequency response analysis.
   Eco/ogy57(1):99-109.

Sokolovsky, V. G. 1986. Monitoring atmospheric pollu-
   tion: norms and standards—policy and practice, pp.
   142-150 In G. E. Schweitzer and A. S. Phillips (eds.),
   Proceedings of the Fifth US-USSR Symposium on
   Comprehensive Analysis of the  Environment. Na-
   tional Research Council, Washington, D.C.

Train, R.E. 1980. EPA'sTask. EP/Uouma/6(10):7,38-
   39.

Vasilenko, V. N., I. M. Nazarov, and Sh. D. Fridman.
   1986.   Monitoring  snowpack  pollution. In  G.E.
   Schweitzer and A.S. Phillips (eds).  Proceedings of
   the Fifth US-USSR Symposium on  Comprehensive
   Analysis of  the Environment. National  Research
   Council, Washington, D.C.  pp. 7-25
                                                                                               171

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      Managing the Great Smoky Mountains National Park
             Biosphere Reserve for Biological Diversity
                                     John Peine
                             Great Smoky Mountains National Park
                             Gatlinburg, Tennessee 37738, U.S.A.
                Abstract

    As  an International  Biosphere Reserve
and World Heritage Site renowned for its bio-
logical diversity and cultural heritage, the Great
Smoky Mountains National Park is one of the
premiere biological reserves in the world. The
regional setting for the park is described, as well
as the natural and cultural resources. Manage-
ment policy and programs dealing with natural
resources and biological diversity are outlined.
The park has long been a center of research,
and for the last 15 years, a research station has
been located in the park to foster research de-
scribing the park fauna and flora and ecosystem
processes.

            Regional Context

    The ancient Appalachian Mountain Range
in the eastern United States extends from Maine
to Georgia, achieving its greatest elevation in
the Southeast due to a massive uplift created by
the collision of continental plates along a zone
which is now represented approximately by the
Carolinas in the  United States and the north-
eastern coast of Africa.  The Southern Appala-
chians form the boundaries  of seven states.
Due to the rugged topography, the mountain-
ous region is relatively sparsely populated. A
large percentage remains in public ownership.
In fact, it represents one of the largest blocks of
contiguously held public lands east of the Rocky
Mountains.

    The Great Smoky Mountains National Park
Biosphere Reserve lies at the heart of the
region.  Two companion biosphere reserves
include   Coweeta Hydrologic  Laboratory
(CHLBR) and Oak Ridge National Environ-
mental Research Park (ORNERP). The 2,185-
ha CHLBR  is part of a long-term ecological
research program of the National  Science
Foundation.  A  variety of experiments  have
been conducted on the six calibrated water-
sheds at the  site  since its establishment in
1934. Research emphasis has shifted from wa-
ter quantity  to water quality as various forest
harvest and reforestation treatments have been
administered. The 5,008-ha ORNERP site was
designated  in 1980.  Experimental  environ-
mental research has been conducted at the site
since the mid-1950s. Present areas of research
include biogeochemical cycling, biomonitoring,
ecosystem dynamics, toxicology and ecologi-
cal effects,  environmental engineering,  envi-
ronmental and soil chemistry, geology and geo-
chemistry, hydrology, physiological ecology and
biomass production.
                                                                                 173

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John Peine
Great Smoky Mountains National Park Bio-
       sphere Reserve (GSMNPBR)

     Great Smoky Mountains National  Park
was established "for the benefit and enjoyment
of the people."  This purpose was stated  by
Congress in  the Act of May 22, 1926, that
provided for establishment of the park. That act
further defined the purpose in reference to the
National Park Service Organic Act of August 25,
1916, which stated that the fundamental pur-
pose of national parks is "to conserve the scen-
ery and the natural and historic objects and the
wildlife therein and to provide for the enjoyment
of the same in such manner and by such means
as will leave them unimpaired for the enjoyment
of future generations."

     The park is distinguished by the extraordi-
nary diversity and abundance of its plants and
animals, the beauty of its mountain terrain and
waterways, the quality of its remnants of pio-
neer culture,  and the sanctuary it affords for
those resources  and for its  modern  human
users. The purpose of the park is to preserve
these exceptionally diverse resources, and to
provide to the public, benefit from and enjoy-
ment  of them in ways  that will  leave the re-
sources — and the dynamic natural processes
of which  they are components — essentially
unaltered. Some benefits and pleasures avail-
able to visitors through  park programs are in-
creased knowledge of the natural environment
and cultural history, aesthetic gratification, and
opportunities  for rewarding recreational activi-
ties that will not seriously impair the resources.

     Included within the states of  Tennessee
and North  Carolina,  the park is  roughly an
elliptical area  of 209,000 ha and is of sufficient
size to sustain  self-perpetuating biological
communities.   The park ranges in  elevation
from 260 m above sea level to 2,025 m, includ-
ing  16 peaks  above 1,800 m, and contains 22
major watersheds, 33 clear mountain streams
totaling 1,180 km, 123 individual  brook  trout
waters, 10 major waterfalls, lesser  falls and
cascades that have  never been enumerated,
 174
and 668 km of foot trails through landscapes
and habitats of uninterrupted natural beauty.

     The area once included the major North
American refuge for the preglacial warm tem-
perate and temperate zone flora during the
Pleistocene glaciation and thus has one of the
nation's richest inventories of such plant groups
as fungi, mosses, lichens, and hepatics. The
park has a high floristic diversity (about 1,450
species of  flowering herbaceous plants and
2,200 other plant species characteristic of the
temperate broadleaf forest biome, with large
numbers of species occurring in  the  same
stands).  Comparable flora diversity in this bi-
ome is found today only in restricted areas of
Eastern China.  The park exhibits almost as
many kinds of native tree species (130 species)
as in all of Europe. One of its major forest types,
the Cove Forest, has 25 to 30 tree species, with
6 to 12 dominant on any one site. A one-tenth
hectare plot may support 40 to 50 species of
herbs through the seasons. The list of endan-
gered plants that grow within the park includes
120 species. There are large expanses of virgin
forest, perhaps totaling about 8,000 ha — the
precise  figure is impossible to calculate be-
cause some areas were logged so selectively
and so long ago.

     Over 70  historic structures, including four
grain  mills from the early European settlement
period of the Southern  Appalachians are lo-
cated in the park, representing the finest collec-
tion of such structures to be found in the United
States today.

     This rich natural and cultural heritage of
the park has  resulted in global recognition of
these values through UNESCO's designation of
the park as a World Heritage site and Interna-
tional Biosphere Reserve.

     GSMNPBR is the  nation's  most visited
national park,  recording a record  10.3 million
visits  last year. National surveys have shown
that 1 of every 10 Americans has visited the
park at least  once.   Again, this is a  larger

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                   Managing Great Smoky Mountains National Park Biosphere Reserve for Biological Diversity
percentage than that  for any other national
park. Visitor facilities include three visitor cen-
ters, one focusing on  natural history and the
other two on cultural history.  There are 516 km
of scenic roadway, 1,024 frontcountry camp-
sites in 10 locations, 9 picnic grounds, 1,422 km
of hiking and  horse  trails (103 km  along the
scenic  Appalachian  Trail), 82  backcountry
campsites, 18 backcountry shelters, and 5 horse
camps.  During the summer season, over 100
weekly interpretive programs are offered (Peine
and Renfro, in press).

    This combination of extraordinary natural,
cultural, and recreational resources in close
proximity to the nation's geographic center of
population results in the enormous popularity of
this park.

           Management Policy

    Federal laws authorizing the  establish-
ment  of the park include  the National Park
Service Organic Act of 1916, the Act of 1925
that authorized planning for the development of
the national park in the Southern Appalachians,
the Act of 1936 that authorized the development
of Great Smoky Mountains National Park, and
the Act of 1942 that further defined park protec-
tion. Other key federal laws dictating policy for
management  include  the  National Environ-
mental Policy Act of I969, the Wilderness Act of
1969, and the Clean Air Act of 1970 and subse-
quent amendments of  1977 (White,  1987).

    The undeveloped portions  of the park,
189,000 ha or 90 percent of the land base in the
park, is currently being managed as wilderness,
since Congress is currently considering wilder-
ness designation of the park. The Wilderness
Act  reaffirms the highest standards of protec-
tion for the natural resources and their naturally
occurring processes.  Policies include no ma-
nipulative management, allowing naturally set
fires to burn, extrapolated species reintroduc-
tion, and the  control or elimination of exotic
species.  Human  impacts are to be  closely
monitored and the development of additional
facilities for visitors are to be highly restricted in
areas zoned as wilderness.

     The primary management policy docu-
ment for the park is the General Management
Plan, which is both a manager's guide for meeting
the objectives established for the park and a
public statement of  NPS management inten-
tions. The plan establishes long-range strate-
gies for resource management, visitor use, and
development of an  integrated  park system,
thereby  creating a framework for all future pro-
grams, facilities, and management actions. This
plan is expected to be in effect for the next 10 to
15 years, although some aspects of it may be
altered from time to time in response to emerg-
ing needs or problems (General Management
Plan, Great  Smoky  Mountains National  Park,
1982).

     In the park's General Management Plan is
a comprehensive planning document called the
Resources Management Plan, which describes
specific programs to achieve the following man-
agement objectives:

      Natural Resources Management

     To protect and  perpetuate the significant
and diverse natural resources and ecosystems
found at Great Smoky Mountains National Park,
as free as possible from the adverse influences
of human intrusion,  consistent with legislative
and executive mandates and Service policies.

     To protect and, where possible, restore
the natural processes as they would proceed if
they had never been influenced by industrial-
ized society.

     To ensure that  cultural resources and
settings are maintained in a manner compatible
with natural resources management objectives..

     To ensure adequate protection for threat-
ened and endangered species, critical habitats,
and unusual or particularly vulnerable natural
resources of the park, such  as virgin forest,
                                                                                     175

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John Peine
brook trout habitat, beech gaps, and outstand-
ing cove hardwood stands.

     To minimize, to the extent possible, the
adverse impact of exotic plants (e.g., mimosa,
kudzu, Japanese honeysuckle, tree of heaven,
etc.) and animals (e.g., wild hog, rainbow and
brown trout) on the park's natural resources and
processes.

     To manage the park as the core unit of the
Great Smoky Mountains International Biosphere
Reserve in accordance with  the objectives of
the Man and Biosphere program.

       Cultural resources management

     To  identify, evaluate, protect, and pre-
serve the park's cultural resources in a manner
consistent  with legislative and  executive re-
quirements and the Service's  historic preserva-
tion policies.

     To reduce, to the degree possible, deterio-
ration of historic structures that are determined,
through objective evaluation, to merit long-term
preservation for interpretive or other purposes.

     To preserve historic structures associated
with pioneer life,  such  as  log residences,
churches, schools, and barns.

     To reduce and, as far as possible, elimi-
nate  the modern   developments  known  to
adversely affect the archaeological resources
of the Oconaluftee-Deep Creek area, and not
necessarily to the direct support of essential
park programs (Resources Management Plan,
Great Smoky Mountains National Park, 1984).

       Resources Management and
             Research Issues

              Exotic Species

     As with almost all natural reserves (Mach-
lis, 1985), exotic species control is a primary
management and research concern. The ob-
jectives for exotic  plant  management within

 176
natural zones of the park are very clear but
somewhat less so in special use zones. The
President's 1977 Executive Order No. 11987
on Exotic Organisms states that agencies shall
"restrict the introduction of exotic species into
the natural ecosystem on lands and  waters
which they own, lease, or hold for purposes of
administration, and, shall encourage the States,
local governments, and private citizens to pre-
vent the introduction of exotic species into natu-
ral ecosystems of the United States."

     In recent years the Service has become
firmly committed to implementing  integrated
pest management (IPM) strategies where pos-
sible.   These strategies employ  a systems
approach to pest control that may use preven-
tive, mechanical, cultural, biological, chemical,
sociological, and other tools to keep target pest
populations below injurious levels. Such strate-
gies maximize the use of natural controls while
minimizing chemical treatments. IPM does not
rule out the use of chemical pesticides, for in
some cases, it may be the preferred approach.
The choice  of a chemical treatment, when
absolutely necessary, should be that which is
the most effective with the  least potential for
harm to human health and environment.

    A total of 288 species of exotic plants
occur in the park. Of those, only 12 are consid-
ered  "problem" exotics  requiring immediate
management action and/or research. To date,
only kudzu  (Pueraria lobata) and mimosa (Al-
biziajulibrissin) are being control led. Research
on control techniques are currently underway
on princess tree (Pawlownia tomentosa) and
Japanese grass  (Microstegium vemineum),
which is common in disturbed forest understory.
Another troublesome exotic plant is Japanese
honeysuckle  (Lonicera japonica), which can
spread at a rate of 15 feet per year. Like most
of our exotics, it was introduced into the park by
early European settlers who planted it near their
homes. There are 86 known patches on the
Tennessee side of the park.

    The exotic plant species of most concern

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                    Managing Great Smoky Mountains National Park Biosphere Reserve for Biological Diversity
is oriental bittersweet (Celastrus orbiculatus)
because it has the ability to cross pollinate with
the native bittersweet, thereby threatening the
genetic base of the native.

     European wild boar  (Sus scrota)  were
introduced into a private  hunting preserve in
North Carolina in  1912. The boar subsequently
escaped and entered the park in the late I940's
or early 1950's. They have since intrabred with
domestic hogs and have spread throughout the
park, being most numerous in the western portion
of the park.

     Past and current research studies demon-
strate that exotic hogs are causing  consider-
able and  demonstrable damage to the natural
ecosystem.   The greatest impacts occur in
mesic areas and  the unique highlands ecosys-
tems; both contain numerous rare and endan-
gered flora and fauna, and plant communities of
special concern.  Negative impacts have been
documented in nutrient cycling, direct disrup-
tion of soils, and changes in community compo-
sition of vegetation by rooting and wallowing.
Changes in vegetative cover and competition
for mast crops with native wildlife are attribut-
able to the presence of exotic hogs as well.

     Accelerated control efforts in the last three
years have resulted in  the removal, by trapping
or shooting, of over 2,000 animals.  The very
high fecundity rate of this animal requires that
pressure continue on the animals so  that hard-
won gains in population reduction not be lost.
This is a problem  that has no ready solution and
will require long-term vigilance (Tate, 1984).

                Air Pollution

     An air quality related research and moni-
toring program has been established in the park
since 1977. Early projects included monitoring
of precipitation chemistry, storm flow, stream
pH, physical and chemical characterization of
park streams, aircraft analysis of ozone con-
centrations, surveys of lead  concentrations in
plant tissues  and soil  litter, and evaluation of
visibility within the park (Eagar et al., 1984).

     Monitoring equipment at the park's Look
Rock Air  Quality Station  has recently  been
upgraded to be included in a newly established
national visibility monitoring network  which
includes 20 areas.  The network employs pho-
tographic systems to monitor views, transmis-
someters to monitor atmospheric optical extinc-
tion, and improved particle monitors to charac-
terize atmospheric aerosols.

     An ozone effects study has been initiated
to complement the four sites  in the park where
ozone is being monitored at different  eleva-
tions.  A system of nine fumigation chambers
has  been  established to accommodate three
dosage levels of ozone.

     Various  native plants are being tested to
document foliar injury.  Extensive injury  oc-
curred this summer on 2 species tested in  the
chambers, and 10 additional  species exhibited
ozone-like foliar injury in the field and  will be
tested later.

     An important research project in the high
elevations is directed by scientists Steven Lind-
berg and Dale Johnson of Oak Ridge National
Laboratory. Significant atmospheric inputs into
the spruce-fir forests are being quantified, in-
cluding precipitation,  cloud  moisture deposi-
tion, and dry deposition of aerosols and particu-
lates. This process-oriented study tracks these
inputs through vegetation and soils.  Several
similar study  sites  in the northwestern and
northeastern  United States have proven to be
valuable points  of  comparison.  Preliminary
results indicate that pollutant loading in general
is similar  to  that found in other parts of  the
country, but there is a much higher rate of the
precipitating out of sulfate and  nitrates in  the
Great Smoky Mountains.  Studies of soil solu-
tions indicate a significant loss of soil nutrients
and the mobilization of aluminum.

     The  Spruce-Fir Research Cooperative
coordinated by the U.S. Department of Agricul-
                                                                                       177

-------
John Peine
ture Forest Service utilizes the Clingmans Dome
area in the park as one of three intensive study
sites of the Southern Appalachian  spruce-fir
forest.  This interdisciplinary research program
involving 35 research projects is investigating
various hypotheses of red spruce decline in the
eastern United States. Not many results are in
on this program  and yet  it  is clear that the
canopy vigor of the  red spruce has declined
sharply since the  study began in 1986.  There
are 66 permanent vegetation plots in place in
the park related to this project. Unfortunately,
these studies came too late to document the
biological diversity and  ecological processes
associated with healthy spruce-fir forest.  An
exotic  European  insect, the  balsam woolly
adelgid, has killed almost all the mature fir trees
in the park in the last 30 years, and the study is
further complicated by four  years of drought
unprecedented in recorded history and some
unusual seasonal temperature fluctuations.

       Long-term Ecological Research
               and Monitoring

     A new initiative by scientists in the park
has been to establish a structured  long-term
ecological research and monitoring program.
This will provide a framework for future studies
that will cumulatively provide baseline data on a
wide variety of population dynamics and eco-
logical processes. Key elements of the pro-
gram include concentrating research in care-
fully managed research areas, thoroughly docu-
mented data  management,  involvement  by
numerous regional research institutions, and a
long-term commitment to monitor key parame-
ters which serve  as indicators of ecosystem
processes, biological diversity, and  anthropo-
genic effects.  A lack of significant funding for
the program may  be a blessing in disguise be-
cause  it will  inspire the cooperation among
scientists in various institutions to become in-
volved.
           Regional Cooperation

     In order to foster cooperation among the
biosphere reserve units in the Southern Appa-
lachian region, an interagency agreement has
recently been signed to establish the Southern
Appalachian Man and Biosphere Cooperative.
Member institutions  include the U.S.  Depart-
ment of the Interior (National Park Service and
the U.S. Fish and Wildlife Service), U.S. Depart-
ment of Agriculture (Forest Service, Southern
Region, National Forest Systems, and South-
eastern Forest Experiment Station), Tennes-
see Valley Authority, Economic Development
Administration, U.S. Department of Energy, and
the Appalachian Regional Commission (South-
ern Appalachian MAB Cooperative, 1988). This
group will work to develop regional programs in
environmental education,  economic develop-
ment that sustains quality natural resources,
and long-term ecological research and monitor-
ing. This program will include a periodic synthe-
sis of research to assess the state of environ-
ment in the Southern Appalachians and sug-
gest actions to improve conditions.

                Conclusion

     All the programs discussed are critical
elements of our overall strategy to manage for
the perpetuation of native biological diversity.
We are learning as we go along. Each new
research project contributes to the cumulative
knowledge necessary to manage our resources
effectively into the 21st century.

              Literature Cited

Eagar, C.E., P. White, and D. Silsbee. 1984. Monitoring
   and research related to atmospheric deposition in
   Great Smoky Mountains National Park, North Caro-
   lina and Tennessee. Paper presented at Nat. Acid
   Precipitation Program, Asheville, TN, Nov. 1984.

General Management Plan, Great Smoky Mountains.
   1982.  USDI, National Park Service, Denver, CO.

Machlis, G.E., and D.L. Tichnell. The state of the world's
   parks. Westview Press, Boulder, CO.  131 pp.
 178

-------
                       Managing Great Smoky Mountains National Park Biosphere Reserve for Biological Diversity
Peine, J.D., and J.R. Renfro.  In press.  Visitor use    White, P.S.  1987.  Terrestrial plant ecology in Great
   patterns at Great Smoky Mountains National Park.        Smoky Mountains National  Park:  A  fifteen-year
   USDI, National Park Service, Southeast Regional        review and a program for future research.  USDI,
   Office Res./Resour. Management Series. 93 pp.          National Park Service, Res./Resour. Management
                                                        Rep. SER-84.  Southeast Regional Office, Atlanta,
Resource Management Plan, Great Smoky Mountains        QA.  70 pp. + app.
   National Park.  1984.  USDI, National Park Service,
   Gatlinburg, TN.

Tate, J.  Techniques for controlling wild hogs in GRSM:
   proceedings of a workshop.  USDI, National Park
   Service, Res./Resour. Management Rep. SER-72,
   Southeast Regional Office, Atlanta, GA. 87 pp.
                                                                                                  179

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     The Effect of Nitrate on CO2 Exchange in the Epiphytic
   Lichens Ramalina menziesii Tay\. and Pseudocyphellaria
          anthraspis (Ach.) Magn. from Central California

                                    Oleg B. Blum
               Central Republican Botanic Garden, Academy of Sciences of Ukranian SSR
                                      Kiev, USSR

                        Thomas H. Nash III and Renate Gebauer
                         Department of Botany, Arizona State University
                               Tempe, Arizona 85287, U.S.A.
     Recent work on the epiphytic I ichen Ramal-
inamenziesiiTay\. in Southern California showed
seasonal effects of air pollution on physiology of
this lichen (Boonpragob, 1987). It was  trans-
planted from a relatively unpolluted area  (Palo-
mar Mountain, 100 miles south of Los Angeles)
to an analogous but highly polluted location in
the Los Angeles area (San Dimas Experiment
Station on the south side of the San Gabriel
Mountains) during three different time intervals
covering a year. During the summer periods
(but not the winter) the transplanted lichen died
over a period of 6-8 weeks, as evidenced by a
decline in photosynthesis to zero and a  virtual
complete conversion of chlorophylls to phaeo-
phytins.  These changes in physiological func-
tion were related to a matrix of 24 pollution
parameters, of which leachable nitrate provided
the highest correlation with decline in photosyn-
thesis.  Although many of the variables were
highly correlated with the decline in physiologi-
cal function, it seemed reasonable to investi-
gate whether nitrate alone might have a detri-
mental effect on R. menziesiiand other lichens
from southern California.
          Materials and Methods

    The epiphytic lichens Ramalina menziesii
Tayl. and Pseudocyphellaria anthraspis (Ach.)
Magn. were collected from branches and trunks
of Quercus aqrifolia Nee in October 1987 at
Hastings Natural History Reservation in central
coastal California. After transport to the labora-
tory the lichen material was stored air-dry in a
growth chamber at  150-200 |aE m2 s ' photo-
synthetically active radiation (PAR), in a 12 h
light/dark photoperiod, and temperatures of 20
+2°C in the dark. Once a day, the lichens were
sprayed with  deionized water to reactivate
physiological activity for 1-2 h in a way roughly
analogous to  heavy dewfall.  All the  experi-
ments were completed within one month from
the time of collection.  Previous experiments
with Ft. menziesii showed that photosynthetic
rates did not  decline  significantly within this
time-period (Matthes-Sears, 1985).

    To study the effect of NO3  ions on the
lichens, 5 replicate samples, each consisting of
approximately 0.5  0.8 g air-dry  mass, were
                                                                                 181

-------
 Oleg B. Blum, Thomas H. Nash and Renate Gebauer
-
| 100-
.c
c
o 60-
0
o.
£ 20-
z •
Ramalina menziesii







T
1













T
T













T
1













T
1





                                                  100-
                                                   60-
                                                   2O-
                                                           Pseudocyphe Maria


                                                                   anthraspis
                                50  500 1000
                                                           C    50  500
                   100-
                    60-
                    20-|
                                                  1OO
                                                   6O-
                                                   20-
                                50  500 1000
                                                          C    50  500
                                Nitrate Concentration   (mM)
Figure 1. Effect of KNO3 solutions on CO2 exchange of the lichens Ramalina menz/es//Tayl. and Pseudocyphellaria
        anthraspis (Ach.) Magn. Bars are plotted for mean (n=5) and 95% confidence intervals are calculated based
        on Tukey's HSD using the results of one-way ANOVA's (Steel and Torrie, 1960). The symbol "c" indicates
        the control.
submerged for 6 h in beakers with deionized
water solution of KNO3 (50 mM, 500 mM and
1000 mM) at 23°C.  Control samples  were
submerged in deionized water under the same
conditions.  Before CO2 exchange measure-
ments were made, the lichen samples  were
removed from KNO3 solutions and blotted to
remove external water droplets. This resulted
in a thallus water content of 120-140% of dry
weight, which is approximately optimal for these
species (Nash and Lange,  1988).

     Net CO2 exchange rates were measured
with the discrete sampling technique (Larson
and Kershaw, 1975), using an ADC 225 infrared
gas analyzer (IRGA). The experimental proce-

  182
dure is described in detail by Matthes-Sears et
al. (1987). All measurements of photosynthesis
and dark respiration were made at a tempera-
ture of 20 ±1°C with (PAR) at 200 ^E rrr2 s1,
provided by 400 W mercury multi-vapor metal
halide lamp. Thallus water content was deter-
mined gravimetrically immediately  after each
gas exchange measurement.  At the end of
each experiment the samples were oven-dried
at 100°C for 24 hours.  All  experiments were
carried out with 5 replications using a program
developed at the Laboratory of Mathematics at
the Institute of Botany, Academy of Sciences of
the Ukrainian SSR.

-------
                      The Effect of Nitrate on CO., Exchange in the Epiphytic Lichens from Central California
                 Results

     On the basis of different CO2 responses,
Ramalina menziesii was more tolerant than
Pseudocyphellaria anthraspis to the 6-h sub-
mersion in different KNO3 solutions (Fig. 1). For
Ramalina, no inhibition of net photosynthesis or
respiration occurred after submersion in 50 or
500  mM solutions (Tukey's multiple compari-
son test based on a one-way ANOVA). On the
contrary,  a slight,  nonsignificant  increase
(approximately 10% as compared to control)
was observed. Even after submersion in 1000
mM  KNO3, net photosynthesis was 75% of the
control and dark  respiration was 72%.

     In  contrast, after submersion  in 50 mM
KNO3, net photosynthesis in P. anthraspis sig-
nificantly declined to 54% while dark respiration
was unaffected. Exposure to 500 mM KNO3 led
to significant declines of net photosynthesis to
35% and dark  respiration to 50%.

                Discussion

     Our results convincingly show differences
in photosynthetic and respiratory responses in
the two  lichens following treatment with potas-
sium nitrates solutions. Although P. anthraspis
was sensitive  to 6-h treatment by  50 mM of
KNO3, R. menziesii demonstrated an unexpect-
edly high tolerance under the same experimen-
tal conditions.  For these species,  the  differ-
ences in photosynthesis  and  dark respiration
were even more significant when the lichens
were treated by 500 mM KNO3. Even if treated
by 1000 mM KNO3 the tolerant R. menziesii de-
creased its photosynthetic and respiratory ac-
tivity only by 25-30%.

     A literature survey  revealed little other
data on  nitrate  impact on lichens. Barashkova
(1961) in her field experiments observed  stimu-
lation by nitrates in Cladonia rangiferina (L.)
Web. In  addition, Kauppi  (1980) found that
increasing nitrogen with either mineral fertiliz-
ers or solutions containing  NH/ or NO3 ions
produced a favorable effect on the develop-
ment of  Hypogymnia physodes (L.) Nyl.  and
Cladonia stellaris(Opiz) Pouzar & Vezda thalli.
Higher contents and both greater number of
phycobiont cells and a higher cell division fre-
quency were observed.  In the latter experi-
ments, an increase in photosynthetic activity of
C. stellaris was established by 10 mM of sodium
nitrate (pH 7.7). On the other hand, the treat-
ment with 10 mM solution of NH^CI (pH 6.8) led
to inhibition of  photosynthesis. Perhaps the
inhibition was related with the effect of chloride
ions in the solution (Kauppi, 1980).

     Nitrates may disturb the lichen symbiosis,
because  stimulation of phycobiont growth leads
eventually to the breakdown of symbiotic rela-
tionships and even to the death of lichens. In
support of this  hypothesis it is noted that the
favorable effect of sodium nitrate in Kauppi's
experiments was observed  only  during  1-2
weeks and thereafter it decreased rapidly.  It is
not clear, however, whether the decrease in
photosynthesis was caused by the impact of
nitrate ions or by unfavorable laboratory condi-
tions during the experiment.

     In general, the results obtained by Kauppi
are in agreement with the experiments of Marti
(1985) who studied the long-time effects of the
nitrates on seven isolated lichen mycobionts.
The dry  mass of  cultivated  phycobionts  in-
creased  when exposed for 20 days to 8  mM
solution of NaNO3 (pH 4.0). Particularly large
increases in dry mass occurred in the phycobi-
onts of nitrophilous lichens Anaptychia ciliaris
(L.)  Korb and  Ramalina  fraxinea (L.) Ach.
According to Marti's experiments,  the  short-
time effect of  8 mM sodium  nitrate  solution
produced no tangible influence on UCO2 assimi-
lation by lichen phycobiont. Similar results were
found by Barashkova (1961)  when Cladonia
rangiferina was exposed to the effect of nitrates
for a short time.

     On the basis of an intensive study of an
isolated phycobiont culture, Marti (1985) also
                                                                                      183

-------
Oleg B. Blum, Thomas H. Nash and Renate Gebauer
came to similar conclusions for nitrites.   He
found severe injury (decreased 14CO2 assimila-
tion by  more than 50%) to the  phycobiont of
Parmelia caperata (L) Ach. after  short-term
treatment with 0.1 mM NaNO2.  Furthermore,
the phycobionts of most of the 29 foliose and
fruticose lichens studied demonstrated a re-
markable decrease in 14CO2 assimilation when
exposed for 2 hours to 0.5 mM  sodium nitrite
(pH 4.0). However, relatively little sensitivity to
the effect of 1 mM NaNO2 was demonstrated by
the phycobiont of Parmelia sulcata Tayl.;  only
concentrations as high as 10 mM  NaNO2 re-
sulted in a decrease of UCO2 assimilation by
more than 70%.  Considerable  differences in
the sensitivity to the NaNO2  in 2 hour experi-
ments with isolated mycobionts  were also de-
scribed by Marti (1985).

     Thus, literature data and our results  pro-
vide evidence for the conclusion that nitrates as
well as  nitrites may induce injury to lichens by
decreasing photosynthesis and respiration at
high concentrations even after short-term incu-
bations. It is well known in  plant leaves  that
nitrates with sulfite reduce the levels of reduc-
tants and consequently reduce the synthesis of
adenosinetriphosphate(Treshow, 1984). How-
ever, the toxicity of nitrates is much less than of
sulfate  and sulfites  (Marti,  1985;  Hill, 1971;
Ferry and Baddeley, 1976).

     Although Boonpragob (1987) established
a high correlation  between absorption of  NO3
ions and photosynthetic decrease and chloro-
phyll degradation in the case of transplanted R.
menziesii, it is now evident that these observa-
tions were not a direct effect of nitrates. Some
experiments demonstrate a stimulating effect of
low nitrate concentration on growth  of other
lichen species  (Barashokova,  1961; Kauppi,
1980).  We do not know if,  in Boonpragob's
experiments, the nitrate  was accumulated as
nitrate perse or whether nitrogen oxide gases
were absorbed  and chemically converted to
nitrate.   Although, Nash (1976), found  little
effect of nitrogen dioxide on lichens, field stud-
ies have correlated disappearance of lichens
when concentration of nitrogen oxides in the at-
mosphere  increased (Stringer  and  Stringer,
1974; Jurging, 1975; Sigal and Nash, 1983).

     The injury observed by Boonpragob (1987)
may be due to other factors. Oxidant injury to
vascular plants is well known in Southern Cali-
fornia, but short-term experiments with ozone
(Ross and Nash, 1983) demonstrated no effect
on R. menziesii even at the highest concentra-
tion ever measured in Los Angeles. Neverthe-
less, injury from other oxidants, such as PAN or
a combination of oxidant gases, may yet prove
important.   Moreover,  toxic accumulation of
other ions  is very likely.   Boonpragob et al.
(1988) and Boonpragob (1987) reported accu-
mulation of 23 other ions. In the case of fluoride
in particular, it is known that accumulation was
sufficiently  high to cause injury in a number of
lichens (Nash, 1971; Gilbert, 1971).

              Literature Cited

Baraskova, E.A. 1961. Some peculiarities of growth of
   the fodder lichen Cladonia rangiferina (L.) Web.
   under the conditions of the Murmansk region. Bot.
   Zhurn. 46:410-413. (In Russian)

Boonpragob, K. 1987. Seasonal effects of air pollution
   on physiology of the lichen Ramalina  menziesii.
   Ph.D. Dissertation, Arizona State University.

Boonpragob, K., T.H. Nash III, and C.A. Fox.  1988.
   Seasonal deposition patterns of acidic ions and am-
   monium to the lichen Ramalina menziesii Tayl. in
   Southern California.  Environ. Expt. Bot, 28 (in
   press).

Ferry, B.W., and M. S. Baddeley. 1976. Sulphur dioxide
   uptake in lichens, pp. 407-418.  InD.H. Brown, D.L.
   Hawksworth, and R.H. Bailey (eds.). Lichenology:
   Progress and Problems. Academic Press, London.

Gilbert, O.L.  1971. The effect of airborne fluorides on
   lichens. Lichenologist 5:26-32.

Hill.D.J. 1971. Experimental study of the effect of sulfite
   on lichens with reference to atmosphere pollution.
   New Phytol. 70:831-836.
 184

-------
                          The Effect of Nitrate on CO,, Exchange in the Epiphytic Lichens from Central California
Hill.D.J. 1974. Some effects of sulphite on photosynthe-
   sis in lichens.  New Phytol. 73:1193-1205.

Jurging, P. 1975.  Epiphytische Flechten als Bioindika-
   toren der Luftverunreiningungen. Bibl. Lichenol. 4:1 -
   164.

Kauppi.M. 1980. The influence of nitrogen-rich pollution
   components on lichens. Acta Univ. Oul., Sci. Rer.
   Natur., N 101, Biol., N 9, 22 p.

Larson, D.W., and K.A. Kershaw. 1975. Measurements
   of CO2 exchange in lichens: a new method. Canad.
   J. Bot. 53:1535-1541.

Marti, J.  1985.   Die toxizitat von Zink,  Schwefel- und
   Stickstofferbindungen auf Flechten-Symbionten. Bibl.
   Lichenol. 21:1-29.
Matthew-Sears,  U.  1985.  The ecology of the lichen,
   Ramalina menziesii.  Ph.D. Dissertation,  Arizona
   State University.

Matthew-Sears,  U.,  T.H.  Nash  III, and D.W. Larson.
   1987. The ecology of Ramalina menziesii VI.  Labo-
   ratory responses of net CO2 exchange to moisture,
   temperature, and light. Canad. J. Bot. 65 N 1:182-
   191.

Nash, T.H. III.   1971.   Lichen sensitivity to hydrogen
   fluoride.  Bull. Torrey Bot. C/ut>98:103-106.
Nash, T.H. III. 1976.  Sensitivity of lichens to nitrogen
    dioxide fumigation. Bryologist 79:103-106.

Nash, T.H. Ill, and O.L. Lange.  1988.  Responses of
    lichens to salinity: concentration and time-course re-
    lationships and variability among  Californian spe-
    cies. New Phytol. 109:361-367.

Ross, L.J., and T.H. Nash III.  1983.  Effect of ozone on
    gross photosynthesis of lichens. Environ. Expt. Bot.
    23:71-77.

Sigal, L., and T.H. Nash III.  1983. Lichen communities
    on conifers in southern California mountains: an eco-
    logical survey relative to oxidant air pollution.  Ecol-
    ogy64:1343-1354.

Steel, R.G.D., and J.H. Torrie.  1960.  Principles and
    Procedures of Statistics.  McGraw-Hill,  New  York,
    Toronto, and London.

Stringer, P.W., and M.H.L. Stringer. 1974. Air pollution
    and the distribution of epipitic lichens and bryophytes
    in Winnipeg, Manitoba.  Bryologist 77:405-424.

Treshow, M. (Ed.).  1984.  Air Pollution and Plant Life.
    John Wiley and Sons Ltd., New York, London, Sydney,
    and Toronto.
                                                                                                       185

-------
 Environmental Monitoring of Biological Markers in Animals
                                   and  Plants*

                    John F. McCarthy, S.  M. Adams, B. D. Jimenez,
                                          and
                                     L. R. Shugart

                               Environmental Sciences Division
                                Oak Ridge National Laboratory
                                  P.O. Box 2008, MS-6036
                              Oak Ridge, TN 37831-6036, U.S.A.
               Introduction

     A plethora of environmental problems, from
loss of trees in forests to massive mortality in
marine mammal populations and declining fish
and shellfish harvests, demonstrates the need
for an integrated  program  of environmental
monitoring.  Such a program will have many
elements,  but one important, integrative com-
ponent that  will indicate the extent and the
biological significance of environmental pollut-
ants is the measurement of biological markers
in animal and plant species. Biological mark-
ers, or "biomarkers," have  been defined as
"measurements of body fluids, cells, or tissues
that indicate in biochemical or cellular terms the
presence and magnitude of toxicants or of host
response" (National Research Council, 1986).
As such, biomarkers are sensitive  indicators
that toxicants have entered the organism, dis-
tributed within the tissues, and elicited a toxico-
logical effect at critical targets (Fig. 1).  Ex-
amples of specific biomarkers that are being
used in this context are discussed in the section
entiled Selection of Suite of Biomarkers.

     In an environmental  monitoring plan, a
suite of biomarkers would be  measured in wild
animal or plant species sampled from areas of
suspected contamination and from pristine ref-
erence environments. Based on the magnitude
and pattern  of the biomarker responses, the
environmental species  offer  the  potential  of
serving as:
1.    Sentinels demonstrating the  presence of
     bioavailable contaminants;
2.    Surrogates indicating  potential human
     exposure and effects; and
3.    Predictors of long-term ecological effects.
 'This work was sponsored by the Oak Ridge National Laboratory Director's Exploratory Studies Program and by the
Oak Ridge Y-12 Plant, Division of Environmental Management, Health and Safety. The Oak Ridge Y-12 Plant and the
Oak Ridge National Laboratory are operated by Martin Marietta Energy Systems, Inc., under Contract DE-AC05-
840R21400 with the U.S. Department of Energy.
                                                                                    187

-------
John F. McCarthy, S. M. Adams, B. D. Jimenez, and L P. Shugart
HI
co
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0
Q.
CO
HI
DC
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<
                      DECREASED
                     REPRODUCTION
BEHAVIOR
CHANGES
                                    FISH KILL
                                     CANCER
         TOXIC EXPOSURE
      CONCENTRATION x TIME

Figure 1. The Biomarker concept. The response of an
animal to toxicant exposure is a function of the concen-
tration of a chemical in the environment and the length of
time the animal is exposed. We would like to avoid the
long-term, irreversible adverse effects indicated in the
upper right hand portion of the figure. The biomarker ap-
proach seeks to measure early responses indicated in
the boxes at the lower left of the figure. These sensitive
biological markers indicate that the  animal has been
exposed to chemicals in the environment and provide an
early warning of future effects.
 Justification for the Biomarker Approach

     Monitoring of Environmental Species

     Why monitor wild animals and plants?
Data from the biological system that is the target
of toxicant action provide important information
that is not readily available from chemical analy-
ses of air, water, or soil.

Temporally and Spatially Integrated Measure
of Bioavailable Pollutants
     Chemical analyses are expensive and pro-
vide data that are not only difficult to relate to a
biological effect but may not even accurately re-
flect the real status of chemical concentrations
overtime and space. Thus, chemical sampling
is like a  snapshot.  Changes can result from
storm events, changes in winds,  or intermittent
releases from industrial plants.  Furthermore,
contamination is often geographically patchy; a
quiet pool in a stream may accumulate highly
contaminated silt, while the gravel bottom a few
feet away may have only trace levels of con-
taminants.

     Pollutants associated with different envi-
ronmental media have different levels of availa-
bility for uptake by organisms.  Sentinel re-
sponses integrate  the relative concentration
and the bioavailability of contaminants,  thus
providing a measure that is more  relevant to
evaluating ecological or health risks.

Effects of realistic, low-level exposures to envi-
ronmental pollutants
     Extrapolation of dose-response curves to
the low  levels of chronic exposure characteris-
tic of a realistic pollution scenario is one of the
greatest challenges in assessing the dangers to
the ecosystem or to human health.  Laboratory
studies  are difficult  and expensive, and  they
lack realism in the complexity of  routes and
types of exposure. Contaminated environments
can function as natural laboratories for explor-
ing the consequences of chronic exposure.
Monitoring the biochemical  and lexicological
responses of naturally exposed animals helps
to provide the type of information needed  to
analyze and interpret the results of nature's ex-
periment.

Significance of different routes of exposure as
indicated by habitat
     Comparison of responses of species with
different habitats, or at different trophic levels
provides information on the significance of dif-
ferent routes of exposure.  Comparisons  of
benthic vs. pelagic fish, foliage- vs. soil-associ-
ated insectivores, and herbivores vs. top carni-
vores provide contrasts in the  extent of  their
exposure to bioavailable contaminants in wa-
ter, soil, or food chain pathways.   Information
about exposure that occurs primarily through
the food chain, for example, or through contact
with sediment can help in prioritizing additional
 188

-------
                                   Environmental Monitoring of Biological Markers in Animals and Plants'
monitoring and may suggest strategies for in-
tervention or remediation.

  Advantages of Biomarker Measurements

     Measurement of biomarker responses to
exposure provides information that cannot be
obtained from measurements of chemical con-
centrations in environmental media or in body
burdens.  It should be recognized,  however,
that limitations in our current understanding of
the molecular and biochemical mechanisms of
toxic action often prevent unequivocal interpre-
tation of biomarker responses, especially in re-
lating them to a specific consequence, such as
eventual development of cancer or increased
susceptibility to disease.

Exposure to rapidly metabolized contaminants
     Biomarkers provide evidence of exposure
to compounds that do not bioaccumulate or are
rapidly metabolized and eliminated, such  as
polynuclear aromatic hydrocarbons.

Integrate pharmacodynamic and toxicological
interactions
     Biomarkers integrate the toxicological and
pharmacokinetic  interactions  resulting from
exposure to complex mixtures of contaminants,
and they present a biologically relevant meas-
ure of toxicant interactions in target tissues.
Direct and indirect interactions of multiple con-
taminants upon the uptake and internal distribu-
tion  of chemicals, as  well as synergism or
antagonism of the toxicants' action, are  inte-
grated within  the  organism.  The  biomarkers
express the cumulative effect of toxicant inter-
actions in molecular or cellular targets.

Early responses causally related to long-term
effects
     Many biomarkers  are measures of early
responses of organisms to toxicant  exposure
and are causally related to the expression of
later irreversible consequences of that expo-
sure.  For example, genetic damage, measured
in early stages by several types of biomarkers,
is understood  to be initiating events causally
related to the  eventual expression of cancer.
Likewise,  early signals  of  impaired immune
system function presage an eventual increased
susceptibility to disease or parasitic infestation.
Biomarkers may therefore serve as short-term
predictors of long-term adverse effects.

Measures of the biological significance of expo-
sure
     Many biomarkers  provide a quantitative
measure of  the  physiological significance of
toxicant exposure. For example, depression of
acetylcholinesterase levels is a biomarker of
exposure, but it also indicates the magnitude of
the  neurotoxic effect of the exposure.  Bio-
marker responses  are, therefore,  relevant to
understanding the relationship between expo-
sure to environmental levels of contaminants
and  the  potential for  adverse  effects  at an
individual or population level.

      Elements of a Biomarker-based
           Monitoring Program

             General approach

     A consistent, comparable, long-term data
base is needed for describing the response of a
suite of biomarkers in selected environmental
species from a range of geographic locations.
Monitoring needs to include not only sites of
known or suspected contamination but also
ecologically comparable reference sites with no
known sources of  pollutant input.   The bio-
marker responses  of species  at the pristine
sites will provide  a reference level for compar-
ing  responses of species from suspect sites.
Statistically significant differences between sites
(qualitative differences in patterns of response
for a suite of biomarkers, as well as quantitative
differences in the magnitude of responses) can
demonstrate differences in the extent or type of
pollutant exposure (Shugart et al., 1987; Loar,
1988). Differences in biomarker response over
time at the same site may provide  information
                                                                                      189

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John F. McCarthy, S. M. Adams, B. D. Jimenez, and L. R. Shugart
on environmental trends and could prove to be
a sensitive and rapidly responding tool for as-
sessing whether intervention  is required  or
remediation has  been  successful.  Because
many of the biomarkers are short-term indica-
tors  of long-term adverse effects, these  data
permit intervention before irreversible adverse
effects become inevitable.

        Selection of Sentinel Species

     Several criteria should be considered in
selecting the specific species to be collected
and  analyzed as environmental sentinels.

Routes of Exposure
     The habitat  and food preferences of ani-
mal sentinels is an important factor that may aid
in identifying the  sources and routes of expo-
sure. For example, where fish and other aquatic
species are exposed through  surface waters
and  sediment, comparison of water-column vs.
sediment-associated species can distinguish
   the contribution of sediment to exposure.

   Spatial Range
       The size of the home range of an animal
   sentinel needs to be matched to the size of the
   study site and the degree of geographic resolu-
   tion required for a  particular study.  For ex-
   ample, voles, whose range is limited to about
   400 m2, were useful for studying a small site
   such as Love Canal. Larger sites might require
   the use of rabbits or groundhogs, which range
   over acres,  and therefore integrate exposure
   over a wider geographic area. Although sessile
   animals, such as clams or mussels, provide ex-
   cellent spatial resolution, there are advantages
   to choosing  an animal that is somewhat motile
   because doing so can avoid anomalous results
   from very isolated "hot spots" of contamination.

        Selection of a Suite of Biomarkers

       Selection of the specific biomarkers  may
   depend on the biochemistry and physiology of
Table 1.  Benzo(a)pyrene adduct formation in DMA isolated from brain tissue of beluga whales3. The whale population
from the St. Lawrence River in Canada is declining and there have been several beached whales with bladder tumors.
The area from which the whales were collected is known to have measurable levels of RGBs and PAHs, including
benzo(a)pyrene. The data below quantify "adducts" [the amount of a carcinogen, such as benzo(a)pyrene (BaP),
chemically attached to DNA].  DMA from the affected population of beluga whales from the St. Lawrence River has been
modified by BaP at levels as high as those observed in mice and fish experimentally exposed to a carcinogenic dose
of the chemical; belugas from a pristine area in Canada's Northwest Territories had no detectable adducts (Martineau,
etal., 1988).
                                                    BaP adduct formation
Sample
Tissue
binding13
                          levelc
St. Lawrence Estuary
#1
#2
#3
MacKenzie Estuary
#1-4
#1-4

Brain
Brain
Brain

Brain
Liver

206
94
69

None detected
None detected

2.15
0.98
0.73



  DNA isolation and quantitation was according to Shugart et al.,1983.
  BaPDE-DNA adducts expressed as nanograms of tetrol 1-1 (resulting from binding to
  DNA of the anti-BaPDE metabolite of benzo(a)pyrene) per gram of DNA (Shugart, et al., 1983).
  Level expressed as number of BaPDE-DNA adducts per 107 DNA nucleotides.
  190

-------
                                   Environmental Monitoring of Biological Markers in Animals and Plants'
                   •  BLUEQILL SUNFISH

                   •  FATHEAD MINNOW
                          _L
                                 _L
            4       8       12      16
            EXPOSURE PERIOD (days)
                                        20
Figure 2. Time course of genetic damage, measured as
the number of single-strand breaks in DNA through the
use of an alkaline unwinding assay, in fish exposed to the
carcinogen benzo(a)pyrene  (BaP) in  the laboratory.
Bluegill  sunfish and  fathead minnows were exposed
under flow-through conditions to an aqueous solution of
BaP (I ug/L) for 20 d.  Results are plotted as the number
of breaks per alkaline unwinding unit (see Shugart, 1988).

the enviromental sentinel. Plants, for example,
are fundamentally different  from animals in
significant ways. However, it is possible to list
several classes of biomarkers that have  been
used  for environmental monitoring and  that
offer promise as sensitive  measures  of expo-
sure.

Biomarkers of Genetic Damage
    Biomarkers  can  include  measures of
damage  from specific chemical  agents (for
example, DNA adducts; Table I; Shugart and
Kao, 1985; Martineau et al., 1988) or can be
nonspecific indicators of damage to the integrity
of DNA (such as numbers of strand breaks in
the DNA; Fig. 2; Shugart, 1988; Shugart et al.,
1989).  Biomarkers of genetic damage can be
considered equally applicable in assessing ef-
fects on plants and animals.
Induction  of  Detoxifying Systems as a  Bio-
marker
     Most contaminants stimulate synthesis of
relatively specific protective detoxication mecha-
nisms; higher levels of these proteins in organ-
isms are evidence of a molecular response to
toxicant exposure.  Mixed-function oxidase sys-
tem enzymes (Fig.  3; Jiminez et al., 1988; Loar,
1988), metal binding proteins  (Table 2; Hamil-
ton and Mehrle, 1986), and oxyradical-scav-
enging enzymes are examples of detoxification
systems used as biomarkers.

Inhibition of Specific Enzymes or Biochemical
Pathways
     Exposure to pollutants that exert their toxic
action by  specific  mechanisms, such as the
neurotoxic effect of many pesticides, may be
indicated by changes in the  target biochemical
activity.

Impairment of Immune System Function
     Specific toxicants or the cumulative ef-
fects of multiple contaminants may reduce the
capacity of the immune system to resist infec-
tion (Anderson and Roberson, 1989).

Impaired Organ or Tissue Function
     Histopathological  analyses  can  detect
neoplastic, necrotic, or parasitic lesions.  Im-
pairment of physiological function can be evalu-
ated by a number of assays, such as analyses
of blood chemistry (Loar et  al.,  1988; Loar,
1988).

Impairment of Reproductive Competence
     In an  ecological context, the adverse ef-
fects of exposure on individuals may be of less
concern than the consequences at the popula-
tion level.  Reproductive success is the key
process linking (I)  molecular and  biochemical
effects of  toxicants within an individual (e.g.,
genetic damage or hormonal aberrations) and
(2) the ecosystem-level effect. Levels of repro-
ductive hormones or observations of atresia in
                                                                                      191

-------
John F. McCarthy, S, M. Adams, B. D. Jimenez, and L. R. Shugart
Table 2. Metal-binding proteins (MBP) in the livers of bluegill sunfish (Lepomis machrochirus) exposed to cadmium in
the laboratory and in redbreast sunfish collected from streams contaminated with metals, including zinc. Fish were
injected intraperitoneally with 2 mg Cd/kg body weight as CdCI2 in 0.9% saline on each of three consecutive days and
then sacrificed on day 6. Control fish were similarly injected with 0.9% saline (50uL/100 g body weight) on each of three
consecutive days and sacrificed on day 6. White Oak Creek drains the southern boundary of the Oak Ridge National
Laboratory and flows into White Oak Lake.  Brushy Fork Creek is used as a reference site because it has no inputs of
industrial or other point source pollutants. MBP concentrations in livers were measured by the use of the Chelex-100/
109Cd procedure [Sloop, et al., 1989], and are reported as nanomoles of 109Cd  bound per gram of soluble protein ± S.E.
M. The asterisk indicates that MBP concentrations are significantly different from those in control or reference animals
at alpha = 0.05.
Sample description
       MBP concentration
Laboratory Exposure (Cd)
       Control
       Exposed
       247 ± 168 (n = 4)
       977 ±133(n = 3)'
Field Collection
       Reference Stream
       (Brushy Fork Creek)
       White Oak Creek
       (3.0-3.4 km)
       White Oak Creek
       (2.5 km)
       White Oak Lake
       631 ±121 (n = 4)

       1900 ±306(n =

       1732 + 368(n =

       1472 + 404(n =
developing oocytes may be useful biomarkers
that can be linked to toxic agents, whereas ob-
servations of oocyte recruitment or other meas-
ures  of reproductive  competence  can  help
quantify the consequences of  pollutant expo-
sure.

    Interpretation of Biomarker  Responses:
      Levels of Biological Organization

     The effects of environmental contamina-
tion can span  a range of  levels of  biological
organization, from the molecular level to the
community level.  Responses at each level
provide information that help  researchers to
understand and interpret biomarker responses.

Exposure Versus Effects
     The lower levels of organization, such as
DNA damage or enzyme activity, often provide
a more sensitive and specific response to par-
ticular toxicants.  These biomarkers offer ad-
vantages as more direct measures of exposure
and may be diagnostic of the type of contami-
nant to which the organism is exposed.  How-
ever,  it is less clear what the biological signifi-
cance of that exposure might be to the overall
structure and function of an ecosystem.

     On  the  other hand, responses at higher
levels of  biological   organization,  such as
changes in species diversity, provide a  much
more direct  indication of ecosystem-level ef-
fects, but cannot  by themselves prove whether
the effect results from pollutants or from natural
ecological  factors.  Some  measures  of toxic
effect, such as reproductive competence, can
be considered to be both biomarkers that can
be more directly tied to toxic exposure and
indicators of the population-level consequences
of that exposure.
 192

-------
                                     Environmental Monitoring of Biological Markers in Animals and Plants'
     500
     400
(
' ' ,„.' '
* >
(3) C
*
6)
II I
K ^
>)
^-' Combined Mean for Control Streams(9)

I l III
II II
1 23456789' 11 12 13 14 15 16 17 18 1£
ndustria
Distance Downstream (km) |
I Outfall Muncipal Outfall
   E
   a
     200
   t-
   u
   <
   Q
   O
   C
   UJ
100
Figure 3. Induction of detoxication enzymes in fish. Fish in a stream contaminated by industrial effluents demonstrate
significantly higher levels of a detoxication system, the mixed-function oxidase system. The levels of one enzyme ac-
tivity of this system, ethoxyresofurin-O-deethylase (EROD), is measured in hepatic microsomes of bluegill sunfish col-
lected in East Fork Poplar Creek (Oak Ridge, Tennessee) at different distances downstream from an industrial source
(New Hope Pond) and compared to EROD levels in fish collected at the same time from Brushy Fork Creek, an unpolluted
reference stream. Each point represents the mean ± S.E.M. (n) for each station. Significant differences (P < 0.01) be-
tween the combined mean (	) ± SEM (	) for the reference stream ("control stream") and for the stations in the
stream receiving the industrial effluents are indicated by asterisks (see Jiminez et al., 1988).
     A comprehensive and integrated monitor-
ing program needs to consider responses at
several levels of organization, using biomark-
ers at the organismic or suborganismic level, as
well as indicators at the population and commu-
nity levels, to answer the two critical questions
that motivate this activity.

1.    Are organisms exposed to levels of toxi-
     cants that exceed the capacity of normal
     detoxication and repair systems?
2.    If there is evidence of exposure, then does
     the pollutant stress have an impact upon
                                                the structure and function of the ecosys-
                                                tem?

                                            Short-term predictors  of long-term ecological
                                            effects
                                                The  ultimate goal  of  an environmental
                                            monitoring program is to prevent deterioration
                                            of the environment and to document recovery of
                                            affected systems. Biomarkers at the molecular
                                            and  biochemical  level  respond  quickly  to
                                            changes in contaminant exposure, whereas a
                                            long latent period may be required before any
                                            change is apparent at a community  level or
                                                                                      193

-------
John F. McCarthy, S. M. Adams, B. D. Jimenez, and L. R. Shugart
ecosystem level. Can these rapidly responding
biochemical level markers serve as short-term
predictors of long-term effects? We cannot yet
make any links with any confidence. However,
the data base derived from an environmental
monitoring program will clarify the relationships
between the response of the biochemical mark-
ers to an exposure and the eventual ecological
consequences of that exposure.  The ultimate
goal would be the establishment of a scientifi-
cally defensible basis for predicting ecosystem-
level consequences through the use of cost-ef-
fective, timely measures of biomarker responses
in exposed individuals.

         Validation of Biomarkers of
        Environmental Contamination

     Monitoring  biomarkers  in environmental
species  presents numerous advantages for
assessing the amount and significance of expo-
sure to hazardous pollutants.   However, the
approach will require the development of an ex-
tensive body of data and testing in a wide variety
of sites for the significance  of the biomarker
responses to be understood and for the full
power of their predictive capabilities to be ap-
plied with confidence. In spite of the hurdles,
there are few reasonable alternatives that can
provide information needed to understand the
complex interactions of chemical toxicants in
the environment. The ultimate validation of the
biomarker concept will require an iterative inter-
action between three crucial  elements.

Field Studies
     Field studies are the core of the environ-
mental monitoring program. A stable monitor-
ing effort  will provide data on biomarker re-
sponses in pristine areas and polluted areas so
that exposure differences both between sites
and over time can be evaluated. Care must be
exercised in  interpreting  and accounting for
"noise" in biomarker responses that results from
ecological and biological complexities of the
real world.
Laboratory Studies
     Field  studies provide only correlations;
ecological complexities and other factors make
it difficult to use field data to establish dose-
dependent causal relationships between expo-
sure and  biomarker responses.  Laboratory
research is necessary to establish these rela-
tionships and to  unravel and document the
shifts in biomarker response that result from
environmental variables,  such as  seasonal
changes in temperature, or from hormonal ef-
fects during reproductive cycles.

Fundamental Toxicological Understanding of
Biomarker Responses
     Selection of the biomarkers used in the
monitoring  program  must be justified on the
basis of a  fundamental  understanding of the
molecular, biochemical, and higher level inter-
actions linking exposure, biomarker responses,
and ultimate adverse effects at individual, popu-
lation, and community levels. Future advances
in the basic toxicology underlying the biomarker
responses  will strengthen and validate the
acceptance of biomarker responses as a scien-
tifically and legally defensible methodology for
evaluating and remediating environmental pol-
lution.

     Eventual success in applying and inter-
preting biomarkers  will  require a continuing
interaction between these three elements: field
studies will raise questions  that must be re-
solved in laboratory experiments; the results of
the experiments will enhance our understand-
ing of the fundamental toxicology and biochem-
istry of the  biomarker response; these new in-
sights will improve our ability to interpret the
field results and refine additional hypotheses to
be tested in the lab and field.

      Status of Current Capabilities
           and Future Directions

     Biomarkers in all the categories or levels of
biological  organization,  listed  in the section
 194

-------
                                     Environmental Monitoring of Biological Markers in Animals and Plants'
entiled "Selection of a  suite  of biomarkers,"
have been demonstrated in at least some labo-
ratory  and field  experiments (e.g., see Mc-
Carthy etal., 1989).  Much of this research has
been limited to either (I) laboratory exposures of
animals to a limited number of well-described
model contaminants or (2) measurements of a
single  biomarker response in field-collected
animals.  However, a handful of research groups
have collaborated to evaluate the responses of
a suite of biomarkers in  animals from polluted
environments.  The results have been encour-
aging:  biomarker responses have  correlated
with the  perceived degree of contamination,
and the relative ranking of  sites on the basis of
molecular and  biochemical responses agrees
well with  community level measures of ecosys-
tem integrity (Loar et al.,  1988; Loar, 1988).
However, the same biomarkers have not been
used in all the studies, repeated monitoring at
the same sites is rare,  and large-scale field
studies have been limited almost exclusively to
marine or aquatic environments.

     Nevertheless, core capabilities for meas-
uring a fairly wide array of candidate biomarkers
do exist at federal agencies, national laborato-
ries, and universities, and sufficient experience
exists for making rational choices about selec-
tion and  sampling of animal species.  The
primary  impediments to  major progress  in
applying  this approach to environmental moni-
toring is the lack of a unifying mandate and the
need for  stable long-term  funding.   Concern
about ensuring the quality of the environment
transcends national boundaries. International
symposia such as this are critical to achieving
the consensus necessary  to  organize and
coordinate  long-term   and  comprehensive
monitoring programs that  include the use  of
sensitive and powerful biomarkers  in sentinel
species as tools to document exposure to, and
effects of, environmental contamination.
              Literature Cited

Adams, S.M.,  and  B.D. Jimenez.  1987.  Biological
    indicators of contaminant-related  stress. In  Loar,
    J.M. (ed.), First Annual Report on the ORNL Biologi-
    cal Monitoring and Abatement Program. ORNL/TM-
    10399, Oak Ridge National Laboratory, Oak Ridge,
    Tenn.

Anderson, D.P., and B.S. Roberson.  1989. Immunologi-
    cal indicators: Effects of environmental stress on im-
    mune protection and disease outbreaks.  In S.M.
    Adams (ed.), Biological Indicators of Stress in Fish.
    American Fisheries Society Symposium Publication,
    Bethesda, Md. (in press).

Hamilton, S.J., and P.M. Mehrle. 1986.  Metallothionein
    in fish:  review of its importance  in assessing stress
    from metal contaminants.  Trans. Am. Fish. Soc.
    115:596-609.

Jimenez, B.D.,  LS.  Burtis, G.H. Ezell, B.Z. Egan, N.E.
    Lee, J.J. Beauchamp and J.F. McCarthy.  1988.
    Effects of environmental variables on the mixed
    function oxidase (MFO) system in  bluegill sunfish
    (Lepomis macrochirus).  Environ.  Toxicol. Chem.
    7:623-634.

Loar, J.M.  (ed.). 1988.  Second annual report on the-
    ORNL  Biological Monitoring and Abatement Pro-
    gram.  ORNL/TM. Oak Ridge National Laboratory,
    Oak Ridge, Tenn.

Loar, J.M., S.M. Adams, H.L. Boston, B.D. Jimenez, J.F.
    McCarthy, J.G.  Smith, G.R. Southworth, and A.J.
    Stewart. 1988. First annual report on the Y-12 Plant
    Biological  Monitoring and  Abatement Program.
    ORNL/TM.  Oak  Ridge  National Laboratory, Oak
    Ridge, Tenn.

Martineau,  D.,  A. Lagace, P. Beland,  R.  Higgins, D.
    Armstron, and L.R.  Shugart.  1988.  Pathology of
    stranded beluga whales (Delphinapterus leucas) from
    the St. Lawrence estuary, Quebec,  Canada.  J.
    Comp.  Pathol. 98:287-311

McCarthy, J.F., L.R. Shugart, and B.D. Jimenez. 1989.
    Biological markers in wild animal sentinels as predic-
    tors of ecological and human health effects from en-
    vironmental contamination.  In  C.W.  Gehrs (ed.),
    Eighth  Life Science Symposium on Bioindicators:
    Exposure and Effects. Oak Ridge National Labora-
    tory, Oak Ridge, Tenn. (in press)

National Research Council.  1986.  Committee on Bio-
    logical Markers. Washington, D.C.
                                                                                           195

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John F. McCarthy, S. M. Adams, B. D. Jimenez, and L. R. Shugart
Shugart, L.R. 1988.  Quantitation of chemically induced
    damage to DNA of aquatic organisms by alkaline un-
    winding assay. Aquat. Toxicol. (in press).

Shugart, L.R., and J. Kao. 1985. Examination of adduct
    formation in vivo'm the mouse between BaP and DNA
    of skin and hemoglobin of red blood cells.  Environ.
    Health Perspect. 62:223-226.

Shugart, L.R., J. McCarthy, B. Jimenez, and J. Daniels.
    1987. Analysis of adduct formation in bluegill sunfish
    (Lepomis macrochiris) between benzo[a]pyrene and
    DNA of the liver and hemoglobin of the erythrocyte.
    Aquat. Toxicol. 9:319-325.

Shugart, L.R., J.M. Holland, and R. Rahn. 1983.  Do-
    simetry of PAH skin carcinogenesis: Covalent bind-
    ing of benzo[a]pyrene to mouse epidermal DNA.
    Carcinogenesis 4:195-199.
Shugart, L.R., S.M. Adams, B.D. Jimenez, S.S. Talmage,
    and J.F. McCarthy. 1989. Biological markers in ani-
    mals can provide information on exposure and bi-
    oavailability of environmental contaminants./nWang,
    R., and C. Franklin (eds.), Chemical Basis for Biologi-
    cal Monitoring. American Chemical Society Sympo-
    sium Series, Washington, D.C. (in press).

Sloop, F.V., L.R. Shugart, J.F. McCarthy, and K.B. Jacob-
    son.   1989.  An assay for  metallothionein using
    Chelex-100 and cadmium-109. Anal. Biochem. (in
    press).
 196

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   Comparative Estimates of the Effects of Ozone, Sulphur
      Dioxide and Nitrogen Dioxide on Plant Productivity

                       Yu. A. Izrael, I. M. Kunina, S. M. Semjenov
                                LAM, Glebovskaya Sir. 20-B
                                 Moscow 107258, USSR
    Atmospheric pollution by industrial emis-
sions  in the recent two decades has spread
beyond local boundaries, and now inflicts sig-
nificant ecological and economic effect on the
state of terrestrial plant cover on regional and
global scales (Guderian, 1985; Treshow, 1985;
Izrael ,1986).

    Agricultural crop damage in the U.S., for
example, due to the atmosphere pollution in
1981,  made up 1.7 billion US $ (Treshow,
1985). The problem gave impetus to physio-
logical and ecological research on biological
effects of  pollution and ecological standard
setting (Rachkovskaya, 1986; Guderian, 1985;
Treshow, 1985; Izrael, 1986).

    Of particular interest among atmospheric
pollutants are SO2> NO2 and O3, since the for-
mer two are characteristic components of in-
dustrial emissions. They are fairly persistent,
phytotoxic, and might be transported in the at-
mosphere  over long distances (-1000 km).
Ozone, also phytotoxic, originates in the tropo-
sphere in the course of photochemical  reac-
tions involving  nitrogen oxide  and hydrocar-
bons.

    To investigate the effect of atmospheric
pollution on plant productivity, many scientists
(A. S.  Heagle, W.  Heck, J. H. Bennet,  V. S.
Runeckles, J. M. Skelly, L W. Kress, K. M.
Niomarkay, and others) set up and implemented
laboratory and field experiments,  observing
plants in special chambers.  Plant seeds and
seedlings, or cuttings were used, and they were
grown in chambers in controlled environments
with prescribed levels of pollution (varying or
constant). By the end of an experiment, the
biomas (B) of a plant, or of its parts (above- or
under- ground), or the yield were measured.

    I. M. Kunin (1 986 and 1 988) has arranged
the published data on the experiment results
into standardized data sets:
where, i is the experiment number, n is the
number of pollution levels in the given experi-
ment, and D.. and  B. , dose and effect, respec-
tively. The data sets are grouped into data files,
set numbers within a data file being independ-
ent; index k refers the data sets to respective
data files. Each data file implies the pollutant
(SO2, NO2 orO3), examined indicator (total bio-
mas of a plant, of its parts, or yield), and plant
group under study (agricultural crops, trees).
Data on the effect of long-term exposure (during
a growing season, or  longer) to low pollutant
                                                                                  197

-------
 Yu. A. Izrael, I. M. Kunina and S. M. Semjenov
concentrations (usually < 0.1 ppm) have been
analyzed; this is relevant to background re-
gional and global problems.

     When analyzing this information, A. H. Os-
tromoguilsky (1988) obtained mathematical ex-
pectation  (mean value)  for the  parameters of
dual-parameter "dose-effect" model. Applying
the method suggested by F. N. Semevsky, I. M.
Kunina (1987) examined the difference of plant
responses to ozone during various phases of
ontogenesis. The difference was insignificant
by the statistical criterion.

     In  this paper, comparative analysis of
average sensitivity of the mentioned groups of
plants to SO2, NO2 and O3 is discused, and the
method for computing changes in annual pro-
duction of higher plants exposed to the pollutant
impact is suggested.

     The  above mentioned files of ecological
information  have been analyzed by a single-
parameter model:

             k    k   k  k     k
          lnB.. = ak-C D. + E,
             IJ    I   •=   IJ   •=!)

where,  ak is mathematical expectation of the
                        measured indicator (logarithm scale) for thej-
                        th  set in the k-th  file under no pollution,C -
                        sensitivity of the group of plants in the k-th file
                        to the respective pollutant kwith respect to re-
                        lated biological indicator,^, -random fluctua-
                        tions, i.e. independent realizations of random
                        value^k, individual for each data file. Value
                        of parameter £  is  computed for each i-th da
                        set within the k-th data file by means of the linear
                        regression method as follows:
                                                   k
                                       Ak    k    9;
                                                 W
                         (Wk)  =
                         v  i/
                                               Iff.
                                                  k
                                                 n.
                        where, mk-the number of data sets within the
                        k-th data file, 9 ,...,6m   -independent reali-
                        zations of the random value 0k whose variance
                        equals variance £.

                             Further, the virtual value £kof parameter
                        ^k and its error <^k are defined by formulae:
Table 1.  Estimates of the sensitivity parameter C of higher plants to pollutant impact
           Data file
           number, k
Pollutant
Estimate
of  k, T*
Estimate of
error S <;_k
Number of data
sets in a file mk
                                  Agricultural crops (total biomass)
                       NO2             1.2          0.3
                       SO2             1.6          0.2
                       O3             15.5          1.1

                                    Agricultural crops (yield)
                       O3             11.3          1.3

                                  Agricultural crops (root biomass)
                       SO2             2.1          0.4

                                      Trees (total biomass)
                       NO2             0.2          0.2
                       SO2             0.7          0.2
                       O.              5.8          1.1
                                               65
                                              199
                                              116
                                               56
                                               70
                                               24
                                               43
                                               37
 198

-------
       Comparative Estimates ot the Effects of Ozone, Sulphur Dioxide and Nitrogen Dioxide on Plant Productivity
where
              i    m,
- optimum weight coefficients.  Computation
results are given in Table 1; the measurement
units for £  and  ^  are in 10/3ppnr1 hour1

     To specify the error distribution, empiric
distribution of
                          w
normalized with respect to their standard devia-
tions has been derived (Fig. 1). Verification of
the difference of these distributions from stan-
dard normal  by statistical  criterion has pro-
duced a negative result.

     The defined parameters can be  used to
make assessments (averaged for the globe or
regions) for controlling plant production during
the growing season:
                        -2.5   -1.5   -0.5        0.5   1.5   2.5

                       Figure 1.  Empiric distributions of random fluctuations 9, for
                               the effects on total biomass of agricultural crops:
                               O3 (   ),  NO2 ( =}, SO4 ( —i ) and standard
                               normal distribution
                           So, to characterize higher plant sensitivity
                       to pollutant impact, we have applied parameter
                       £ which implies a relative change in plant bio-
                       mass (productivity) per unit increase in pollution
    dose. The effect of SO
                                              NO2 and O3 on all the
                       considered indices of the state of a plant through
             P = P0 exp
-C     AD
   (SO*)   (S02)
•C      AD       -C    AD
 >02)   (N02)   S(03)   (03
                                                                                (1)
Here, P() and P-the initial and altered values of
the productivity  index,  respectively, AD -
change in the pollutant dose, C(, - the parame-
ter  which is  characteristic of the respective
group of  plants, the acting pollutant,  and pro-
duction index (Table 1). Formula (1) is based on
the assumption of an independent effect of the
pollutants under consideration since our analy-
sis of the published data on the effect of SO2,
NO2 and O3 in combination with the considered
indicator  has revealed no reliable difference
between  the  combined effect (averaged with
respect to relevant plant groups) and  the addi-
tive effect (Izrael, 1988).
                       photosynthesizing organs is confidently adverse
                       (here and further on the confidence level being
                       over 90%), i.e. £ < 0 , except NO2 effect on the
                       total tree biomass  (neutral). In terms of the
                       impact on the total plant biomass (both for trees
                       and agricultural crops) O3 >SO2, NO2, and for
                       trees, SO2 > NO2 (> implies "more phytotoxic").
                       On the average, trees are less sensitive to each
                       of the  considered pollutants than  agricultural
                       crops; ozone effect on the crop yield is lower
                      • than on the total biomass. Sulphur dioxide ef-
                       fect on roots biomass of agricultural crops  is
                       higher than on the total biomass (the  confi-
                       dence level is over 85 %).
                                                                                        199

-------
 Yu. A. Izrael, I. M. Kunina and S. M. Semjenov
     Estimates of parameters rk (Table 1) can
be  used for assessing changes in the annual
production of higher plants exposed to back-
ground regional and global levels of SO2, NO2
andO3 (Formula(1)).

     In view of a high priority of ozone as of a
phytotoxic pollutant, it is necessary to develop
quantitative methods for ozone flux studies, to
develop the ozonometer station network, to de-
velop actions for reducing man-induced levels
of ozone in the troposphere.

               Literature Cited
Effects of SO2 on Plants.  Moscow, Gidrometeoizdat.
    1984.
Guderian, Ft., (ed.). 1985. Air Pollution by Photochemi-
    cal Oxidants. Springer-Verlag, Berlin, Heidelberg,
    New-York, Tokyo.

Izrael Yu. A., and S.M. Semjenov   1986.  Ecological
    horizon. In Acidification and its Policy Implications.
    Elsevier, Amsterdam.

Izrael Yu. A., S.M. Semjenov, and I.M. Kunina.  1988.
    Integrated approach to ecological Standard setting
    for air pollution. In Problems of Ecological Monitor-
    ing and Ecosystem Modelling.  L, Gidrometeoizdat,
    v.11.
Izrael Yu. A. 1984.  Ecology and Control of the State of
    the Natural Environment. L., Gidrometeoizdat, 1984.

Kullinal. M. 1987. Assessment of ozone effect on plant
    phytomass and yield.  In Problems of Ecological
    Monitoring and Ecosystem Modelling. L, Gidrome-
    teoizdat, v. 10.

Kunina I.M. 1986. Ozone effect of plants. In  Problems
    of Ecological Monitoring and Ecosystem Modelling.
    L, Gidrometeoizdat, v.9, p.44-87.

Kunina I. M. 1988.  The effect of O3, NO3, NO2, SO2on
    higher plant biomass. Obninsk, VNIIGMI-WDC.

Nikolayevky, V.S.  1980.  Gas-resistance of plants.
    Novosibirsk, Nauka.

Ostromoguilsky, A.M., and I.M. Kunina.  1988.  .Quanti-
    tative patterns of the effect of 03, S02,  and N02 on
    higher plants. In  Problems of Ecological Monitoring
    and Ecosystem Modelling. L, Gidrometeoizdat, v.11.

Rachkovskaya M.M.  1986. The  principles of ecological
    standard setting by functional criteria. In Problems of
    Ecological Monitoring and Ecosystem Modelling. L,
    Gidrometeoizdat, v.9,.

Treshow,  M. (ed.). 1985. Air Pollution and Plant Life,
    John Wiley &  Sons.
200

-------
   Indigenous and Cultivated Plants as Bioindicators of Air
                                Pollution Injury
                           L.H. Weinstein and J.A. Laurence
                         Boyce Thompson Institute for Plant Research at
                                    Cornell University
                                 Ithaca, N.Y. 14853, U.S.A.
    Many species of plants  are  extremely
sensitive to some of  the  most important air
pollutants.  For example, in some cases, such
as with  airborne gaseous fluorides, certain
species of  plants may be more sensitive than
man by more than three orders of magnitude
(less than 1 ug m3  for injury to  gladiolus,
goatweed  [Hypericum  perforatum],  redbud
[Cercis canadensis], and other species, as com-
pared with the OSHA standard of 3.5 mg m3 for
an 8-hr working day over a lifetime).

    Because of the characteristic sensitivity of
plants, and their  ubiquity in forest, aquatic, and
agroecosystems, selected indigenous and cul-
tivated plants have been used for many years
(e.g., Ruston, 1921) to study air pollution prob-
lems (Benedict and Breen, 1955; Berge, 1973;
Brandt and Heck, 1968; Cole, 1958; Darley,
1960; Feder, 1978; Heck, 1966; Heck et al.,
1966, Heck and Heagle, 1970; Heggestad and
Menser, 1962; Hepting, 1966; Jacobson, 1977;
Jacobson and Hill, 1970; Kromroy et al., 1988;
Leone et al., 1964; Mellanby, 1978; Nakamura
and Matsunaka,  1974; Nouchi and Aoki, 1979;
Oshima, 1974; Posthumus, 1976; Scholl, 1971;
Thomas, 1951; Thomas, 1961; Treshow, 1965;
van Raay,  1969; Weinstein, 1977;  Weinstein
and Laurence, 1988;  Zimmerman and Hitch-
cock, 1956). There are many potential uses of
plants as pollutant indicators or monitors: (a)
establishing the presence of a pollutant, (b) pro-
viding an early warning system for certain air
pollutants, (c) relating dose to response (in  a
general  way only), (d) delineating the spatial
and temporal distribution of a pollutant, (e) aid-
ing in identification of pollutants, and (f) meas-
uring pollutant accumulation to conform to  a
standard that protects plants and/or animals.

     To  be useful, these bioindicators must be
(a) genetically uniform to minimize natural vari-
ability (Feder, 1978; Feder and Manning, 1979),
(b) sensitive to a specific  pollutant so that
characteristic and  recognizable symptoms are
produced, (c) abundant and widely distributed
(Darley,  1960), (d) able to maintain growth over
the entire growing season (Heck, 1966), and (e)
capable  of absorbing a pollutant in a predictable
manner  if it is to  be used as a measure of
accumulation (Feder, 1978; Feder and Man-
ning, 1979;  Guderian, 1977).

     Plants may respond  to air pollutants by
displaying (a)  characteristic chlorotic or ne-
crotic lesions, generally on foliage or fruits; (b)
changes in pigmentation, such as destruction of
existing  or  inhibition of de novo chlorophyll
                                                                                   201

-------
L.H. Weinstein and J.A. Laurence
synthesis, or excessive anthocyanin produc-
tion; (c) alteration of form; each of these are due
to (d)  alteration in metabolism. Many of these
responses  are more easily  and less expen-
sively measured  than  the usual  physical or
chemical detection of pollutants. Furthermore,
the plant, unlike instruments, integrate the ef-
fects of toxicants over a wide range of environ-
ments (Heck  et  al.,  1966;  Thomas,  1961;
Treshow, 1965). Thus, in this context, they are
biointegrators, expressing the biological effect
of a pollutant  dose, and integrating climatic,
cultural, and other biological factors into their
response by being "tuned" to the ecosystem.
Disadvantages of plants as  bioindicators are
that susceptible species may not be distributed
over the area of concern, and that they provide
information  after-the-fact (as compared  with
instruments that operate by chemical or physi-
cal principles.

     Not all plants are sensitive to air pollutants.
Often, there is a significant range in sensitivities
among cultivars of the same species. Extremely
tolerant species or  cultivars are valuable for
planting on  farms and in cities  near pollution
sources. Tolerant species may also be good
accumulators  of  pollutants,  and  can play a
special role in programs to  monitor pollution
over a geographical area.   For example, in
Ontario, the accumulation of fluoride in leaves
of silver maple,  a  common  indigenous  tree
species of only moderate sensitivity,  is used to
judge the degree of pollution  in a specific area.
Concentrations of fluoride above a certain value
indicate a polluted condition.  Similarly concen-
trations of fluoride in forage may be used as an
indicator of potential health problems with  sus-
pect to grazing animals.

     In areas where sensitive species of indige-
nous  or  cultivated plants are not present or
widely distributed, a number of field monitoring
systems  have  been devised  and are in use in
various countries. Several are briefly described
below.
               Indicator gardens

     These gardens consist of plants that are
selected for their sensitivity to pollutants known
or suspected to occur (Anonymous, 1984; Arndt
et al., 1987; Feder, 1978; Feder and Manning,
1979; Kromroy et al., 1988; Posthumus, 1976;
van Raay, 1969).  The State of Minnesota has
used indicator gardens to monitor the presence
of sulfur dioxide and ozone in phytotoxic con-
centrations (Anonymous, 1984; Kromroy et al.,
1988). Plants in indicator gardens are grown in
a standardized soil  or artificial soil mix, using
proscribed cultural methods.

          Portable exposure benches

     This technique is used extensively in Eu-
rope for the culture of sensitive trees and crops
(Arndt et al.,  1985; Arndt et al., 1987).  The
exposure bench provides a means of automatic
care for plants grown in isolated areas where
frequent visits are difficult or become too expen-
sive. The exposure bench not only supports in-
dicator plants above the ground for protection
from animals, but also provides an automatic
watering system.

              Grass culture

     Standard methods for the use of ryegrass
cultures have been devised for detecting the
presence  of certain pollutants and measuring
their rates of deposition (Arndt et al., 1987;
Scholl, 1971). Grass cultures have been used
to measure fluoride, sulfur, chloride, lead, cad-
mium, zinc, copper,  nickel, vanadium, etc.  The
typical grass culture consists of a container with
a defined medium  to  support the growth  of
ryegrass plants, an automatic water  supply,
and a post that supports the unit at a  specific
distance above the  ground.  The grass is har-
vested and analyzed periodically to determine
the presence and concentration of toxic ele-
ments, the rate of uptake, and total accumula-
tion.
202

-------
                                        Indigenous and Cultivated Plants as Bioindicators of Air Pollution Injury
     Many variations of these basic methods
have been devised,  including the use of lichen
transplants (which will not be discussed here).
The use of higher and lower plants for biomoni-
toring offers several advantages over instru-
ments  based  upon  physical-chemical  tech-
niques.   Not the least  of these  are low cost,
potential to determine pollutant dispersion over
wide geographical areas, and an approximation
of source strength.

                Literature Cited

Anonymous.  1984. Development of a Biological Air
    Quality Indexing System. A Report to the Minnesota
    Air Quality Board. 380pp. St. Paul, MN 55101.

Arndt, U.,  W. Erhardt, A. Keitel, K. Michenfelder, W.
    Nobel, and C.Schluter. 1985. Standardisierte Expo-
    sition von pflanzlichen Reaktionsindikatoren.  Staub-
    Reinh. Luft 45:481-483.

Arndt, U., W.Nobel, and B. Schweizer. 1987. Bioindika-
    toren.    Moglichtkeiten,  Grenzen  und  neue Erk-
    enntnisse.  388 pp.  Eugen Ulmer GmbH  & Co.,
    Stuttgart, FRG.

Benedict, H.M., and W.H. Breen.  1955.  The  use of
    weeds as a means of evaluating vegetation damage
    caused by air pollution.  Proc. Natl.  Air Pollution
    Symp.,3rd, pp. 177-190.

Berge, H.   1973.  Plants as indicators of air pollution.
    Toxicology 1:79-89.

Brandt, C.S., and W.W.  Heck.  1968. Use of plants for
    pollutant identification and field monitoring, pp. 428-
    443. /nA.C. Stern (ed.)  Air Pollution, Vol. 1, 2nded.
    Academic Press, New York.

Cole, G.A.  1958.  Air pollution with relation to agronomic
    crops.  III. Vegetation survey methods in air pollution
    studies.  Agron J. 50:553-555.

Darley, E.F. 1960. Use of plants for air pollution monitor-
    ing. J. AirPollut. Control Assoc. 10:198-199.

Feder, W.A.  1978. Plants as  bioassay systems for
    monitoring atmospheric pollutants.  Environ.  Health
    Perspect. 27:139-147.
Feder, W.A., and W.J. Manning. 1979. Living plants as
    indicators and monitors. In W.W. Heck, S.V. Krupa,
    and S.N. Linzon, (eds).  Handbook of Methodology
    for the Assessment of Air Pollution Effects on Vege-
    tation.  TE-2 Agricultural Committee, Air Pollution
    Control Association, Pittsburgh,  PA.

Guderian, R. 1977. Air pollution: Phytotoxicity of acidic
    gases and its significance in air pollution control.
    Chapter 4 In Ecological Studies, Vol. 22, Springer-
    Verlag, Berlin.

Heck, W.W. 1966. The use of plants as indicators of air
    pollution.  Air Water Pollut. 10:99-111.

Heck, W.W., J.A. Dunning, and  I.J. Hindawi.   1966.
    Ozone: Nonlinear relation of dose and injury in plants.
    Science 151:577- 578.

Heck, W.W., and A.S. Heagle.  1970.  Measurement of
    photochemical air pollution with a sensitive monitor-
    ing plant.  J. AirPollut. Control Assoc. 20:97-99.

Heggestad, H.E., and H.A. Menser.  1962.  Leaf spot-
    sensitive tobacco strain Bel-W3,  a biological indica-
    tor of the air pollutant ozone. Phytopathol. 52:735.

Hepting,  G.H.   1966.  Air pollution impacts to  some
    important species  of pine.   J. Air Pollut. Control
    Assoc. 16:63-65.

Jacobson, J.S.  1977.  Plants as indicators of photo-
    chemical oxidants  in the U.S.A.  VDI-Berichte Nr.
    270:191-196.

Jacobson, J.S., and A.C. Hill, (eds.)  1970. Recognition
    of air pollution injury to vegetation:  A pictorial atlas.
    Air Pollution Control Association, Pittsburgh, PA. 102
    PP-

Kromroy, K. W., P. S. Teng, M. Olson, D. French, and D.
    S.Lang. 1988. A biological system for indexing air
    quality and assessing vegetation effects (Minnesota
    Biomdicalor Study). Environ. Pollut. (In press).

Leone, I.A., E. Brennan, and R.H. Daines. 1964. Plant
    life as air pollution indicators. Proc. Northeast. Weed
    Control Conf. 18:451-457.

Lihnell, D. 1969.  Sulphate contents of tree leaves as an
    indicator of SO2 air pollution in industrial  areas,  pp.
    341-352.   In  Air Pollution, Proc.  First European
    Congr. on Influence of Air Pollution on  Plants  and
    Animals. Wageningen, 1968.
                                                                                                    203

-------
L.H. Weinstein and J.A. Laurence
Mellanby, K. 1978. Biological methods of environmental
    monitoring,  pp. 1-13.   In J. Lenihan and W.W.
    Fletcher, (eds). Environment and Man, Vol. 7: Meas-
    uring and Monitoring the  Environment.  Academic
    Press, New York.

Nakamura, H.,andS. Matsunaka.  1974.  Indicator plants
    for air pollutants. Susceptibility of morning glory to
    photochemical oxidants:   Varietal  difference  and
    effect of environmental factors. Proc. Crop Sci. Soc.
    Jpn. 43:522.

Nouchi,  I., and K. Aoki.  1979.   Morning glory  as a
    photochemical oxidant  indicator.   Environ. Pollut.
    18:289-303.

Oshima, R.J.   1974.   A viable  system of biological
    indicators for monitoring air pollutants. J. Air Pollut.
    Control Assoc. 24: 576-578.

Posthumus, A.C.   1976.  The use of higher plants as
    indicators for air pollution in the Netherlands. Proc.
    Kuopio Meeting on Plant  Damages Caused by Air
    Pollution, Sci. Pap.  Symp., 1976, pp. 115-120.

Ruston, A.G.  1921.  The plant as an index of smoke
    pollution. Ann. Appl. Bid. 7:390-403.

Scholl, G.  1971.  Die Immissionsrate von Fluor in
    PflanzenalsMasstabfureinelmmissionsbegrenzung.
    VDI Berichte Nr. 164. pp. 39-45.
Thomas, M.D. 1951. Gas damage to plants. Annu. Rev.
    Plant Physiology 2:293-322.

Thomas, M.D. 1961. Effects of air pollution on plants, pp.
    233-278. In Air Pollution. World Health Organization
    Monograph Series #46. Columbia University Press,
    New York.

Treshow, M. 1965. Evaluation of vegetation injury as an
    air pollution criterion.  J. Air Pollut. Control Assoc.
    15:266-269.

van Raay,  A.   1969.   The use of indicator  plants to
    estimate air pollution by SO2 and HF.  pp.  319-335.
    In Air Pollution. Proc. First European Congr. on the
    Influence of  Air Pollution on Plants and  Animals,
    Wageningen, 1968.

Weinstein, L.H. 1977.  Fluoride and plant life. J.Occup.
    Med. 19:49-78.

Weinstein, L.H., and J.A. Laurence. 1988.  Indigenous
    and cultivated plants as biomonitors. NRCSymp.on
    Biomonitoring. In press.

Zimmerman, P.W., and A.E. Hitchcock. 1956. Suscep-
    tibility of plants to hydrofluoric acid and sulfur dioxide
    gases.  Contrib. Boyce Thompson Inst. 18:263-279.
204

-------
      Element Accumulation in  Lichens, Mosses and Soils

                Connected with Mud Volcano Activity

                            J. Martin,  L. Martin, K. Tamm
                                 Tallinn Botanical Garden
                            Estonian S.S.R. Academy of Sciences
                                  Kloostrimetsa Road 44
                                     Tallinn 200019

                A. Kazachevsky, V. Atnashev, V. Alexeyev, N. Alexeyeva
                                Institute of Nuclear Energy
                               U.S.S.R. Academy of Sciences
                                    Leningrad 197022
     It is well known that lichens are widely
used as indicators of air pollution, and as tools
for biogeochemical  monitoring in impact and
background areas (Martin, 1987).

     As a pollution  point source analog, the
mud volcanos form dispersion zones around
active gas release areas. However, principal
differences of these pollution sources are con-
nected with the time scale (thousands of years),
number and concentration of elements emitted.

     Natural and anthropogenic anomalous
matter flow situations, both sharing similar sci-
entific goals, led us to use lichens and mosses
to estimate elements carried out and dispersed
around the mud volcanos.

     Mud volcanos are intensive background
forming sources in the recent biosphere. As
magmatic volcanos, they are situated in tectoni-
cally active areas of the East and West Pacific
and Alpine-Himalaya stress zones. There are
about 730 mud volcanos worldwide, and ap-
proximately half of them are situated on the ter-
ritory of the U.S.S.R. (Kropotkin, Valyaev, 1981),

     The main contributing factor of the mud
volcanic activity is gas release. On the base of
measurements made on the Azerbaidjan S.S.R.
(Caucasus region) volcanos, it was estimated
that the world carrying-out during mud gryphon
activity and eruptions is 106 -10' tons of gas and
10'  10s tons of  breccia annually  (Alexeyev,
Alexeyeva, 1985).

     Four active mud volcanos, Voskhod, Bul-
ganakhsky, Shugo and  Jau-Tepe, belonging
morphologically to various types, were investi-
gated in the Black Sea region, Kerch peninsula
of Crimea and Tamansky peninsula.

     Metal content in fine particles in snow
cover was estimated by using x-ray fluorescent
analysis, where soil and plant material samples
were analysed using  the neutron activation
technique. The sample size used for radiation in
block-containers was 100 mg per sample.
                                                                                 205

-------
J. Martin, V. Alexeyev, N. Alexeyeva, L. Martin, K.Tamm, A. Kazachevsky, and V. Atnashev
     Botanical field materials were collected in
April, 1987. On the slopes of the cone-shaped
mud volcano,  Voskhod,  approximately 30 m
from the top,  sample plots were  established
radially. Collected plant samples included the
lichens,  Cladonia convoluta (Lam.) P. Coul,
Cladonia rangiformis Hoffm., C. furcata (Huds.)
Shard., mosses, Tortula ruralis (Hedw.) Gard.
and Homalothecium lutescens (Hedw.) B.S.G.
Corresponding soil  samples were taken from
the 2cm surface layer.

     The Shugo volcano has a depression about
100 m in diameter which is surrounded by 30-40
m high swell.  Mixed samples  of epiphytic li-
chens  (Parmelia acetabulum,  P  quernica,
Physconia pulverulenta and Xanthoria parieti-
ina)  growing on the trunks of the oak Quercus
roburwere collected from two opposite sides of
the swell. The tree bark and living leaves as well
as the soil-like material under the epiphytes
were also collected.

     The  Bulganakhsky mud volcano has a
large flat  hollow surrounded by a 30  m high
swell. The epigeic lichens, Cladonia convoluta,
C.rangiformis, C. furcata and corresponding
soil samples were collected from flat mud sur-
face and from the swell slopes on various dis-
tances from the center of mud field.

          Results and Discussion

     One of the ways to establish the role of the
particles in the carrying out process is the com-
parison of metal content of the snow cover in the
cracks and the snow outside of the cracks zone.

     The average content of the fine fraction
(size of  particles: 0.2-4.0  microns) in snow
samples from the cracks zone was 1 g per liter
of snow  water.  Outside  of this zone, the fine
particles content in  the snow was 0.01 g per
liter. The contribution of fine fraction particles in
the snow of the cracks zone was 73.3% on
Voskhod volcano. Consequently, the fine frac-
tion  plays an essential role in the transport of
metals such as Zn, Cu, As, Br, Pb, Fe.

     On the basis of the actual concentrations
of elements in samples and their average con-
tent  in the earth's crust, the enrichment factors
Table 1. Element concentrations in the snow aerosols, enrichment factors and calculated outflow on the Bulganakhsky
        volcano, Kerch peninsula, Crimea.
Elements
K
Ca
Ti
Fe
Cu
Zn
Ye
As
Br
Pb
Rb
Sr
Y
Zr
Nb
Concentrations,
Large
Fraction
>4.0
414
491
139
956
11.4
14.8
1.2
1.3
7.3
7.9
4.4
12.4
1.7
8
1.7
ugl'1
Fine
Fraction
4.0-0.2
349
262
149
1773
60.5
95.3
6.9
23.3
17.5
59
9.5
18.7
5
8.5
2.3
Enrichment
L. tract.
0.8
0.8
1.5

12
9
41
38
170
24
1.4
1.8
2.9
2.3
4.1
factors
F. fract.
0.4
0.2
0.9

34
30
1300
360
220
96
1.7
1.5
4.5
1.3
32
kg/day
70
70
26
250
6.6
10.2
0.7
2.2
2.3
6.1
1.1
2.8
0.7
1.5
0.4
Outflow
kg/year
25500
25500
9500
91400
2420
3700
260
800
840
2200
400
1000
260
550
150
 206

-------
                    Element Accumulation in Lichens, Mosses and Soils Connected with Mud Volcano Activity
(KE) were calculated as the ratio of the element
concentration in the sample to the iron concen-
tration in the same sample using the following
formula :
where C,, CFe are actual concentrations of the
elements in the samples, and K , KFe, the aver-
age contents of those elements in the earth's
crust.

     The calculated enrichment factors may be
divided into two groups according to the factors
value :
1. The first group includes K, Ca, Ti, Sr,  Zr;
   these elements' behaviors are similar to iron
   whose enrichment factors are close to 1.
2. The second group includes Zn, Cu, Ye, As,
   Br, Pb;  enrichment factors  for these are
   within the range 101 -103, which means that
   noticeable enrichment has taken place.

     It is important to point out that the enrich-
ment factors for the fine fraction are higher by an
order of magnitude than that for the large frac-
tions (particle's size over 4.0 microns).

     The basic data on aerosols for the Bulga-
nakhsky volcano and the calculated outflow are
given in table 1.

     Actual concentrations of elements in analy-
sed plant samples are given in table 2.

              Literature Cited

Alexeyev V.A., Alexeyeva N.G. 1985. On outcome of
   heavy metals in autgassing of Earth - Nuclear-Physi-
   cal methods of analysis in monitoring of the environ-
   ment. Proc. of the 2-nd All-Union meeting. Riga,
   1982. Leningrad, p.243-250. (In russian).

KropotkinP.N.,ValyaevB.M. 1981. Geodynamicsofthe
   mudvolcanic activityes ( in connection with oil and
   natural gas). In: Geologicalandgeochemical funda-
   mentals of oil and gas search. Kiev. p.148-178. (In
   russian).

Martin J. 1987.  Dynamics of lichen synusiae and their
   biogeochemical role in extremal environmental con-
   ditions. Sverdlovsk. 26 p. (In russian).
                                                                                          207

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J. Martin, V. Alexeyev, N. Alexeyeva, L Martin, K. Tamm, A. Kazachevsky, and V. Atnashev
Table 2. Element concentration (ppm) in soils, lichens, mosses, tree bark and leaves on the mud field of Shugo volcano,
        Kerch peninsula, Crimea
Ele.
Na
K
Ca
Sc
Cr
Fe
Co
Zn
As
Se
Br
Ni
Rb
Mo
Ag
Cd
Te
Sb
Cs
Ba
La
Ce
Sm
Eu
Tb
Yb
Lu
Hf
Ta
Au
Hg
Th
U
Coef.
102
103
104
1
101
104
101
102
1
10-1
1
101
101
10-1
10-1
1
1
10-1
10-1
101
1
1
10-1
10-1
10-1
10-1
10-1
1
10-1
10-3
10-1
1
1
Soils
7.35-12.17
2.03-4.11
13.1-16.4
8.93-16.1
5.95-9.4
2.64-5.04
1.09-1.86
1 .79-4.97
3.65-6.99
7.22-18.9
3.45-7.06

6.89-14.60


1.25-10.1
6.05-12.2
32.1-81.3
21.6-55.5
31.0-65.0
14.0-21.6
32.0-71.7
14.4-21.3
9.45-21 .0
4.57-10.9
11.8-27.1
2.51-17.6
2.29-4.51
4.19-6.05
2.40-12.0
1.92-2.91
4.13-10.1
1.71-2.29
Lichens
2.21-13.7
1.52-7.07
1.14-2.65
0.49-1.28




1.62-7.26
2.59-7.67
1.43-12.2


9.02-27.4
1.12-4.01
2.91-10.1

3.33-7.90
1 .25-5.30
1.15-8.32
2.54-4.96
4.65-9.66
2.33-5.51
0.98-2.39
0.66-1 .66
1.01-2.21

0.16-0.48

4.13-9.44
1.12-2.25
0.44-1.01

Mosses
0.71-1.95
3.94-6.21
1 .33-1 .94
1.39-7.64
1.29-5.57
4.11-24.4
1.36-9.09
4.25-18.7
1.14-6.22
0.85-23.7
1 .96-8.25
2.83-9.37
1 .00-6.64
11.4-39.1
1.15-24.9
0.25-47.2

0.99-3.77
0.66-0.25
6.14-17.3
3.68-16.8
7.5-43.4
3.94-16.9
2.01-11.1
1.51-8.05
1 .55-9.42

0.44-2.06

3.2-19.4
0.46-5.18
1.18-5.0

Tree bark
1 .09-4.99
1.31-2.46
2.09-3.8
0.24-0.79




0.87-2.61
0.27-4.05
2.95-5.38


14.8-27.1
0.93-1.44
2.54-7.09

2.17-4.22
0.82-3.21
389-1500
1 .39-3.45
2.08-6.85
1 .35-4.21
0.04-1.51
0.39-1.04
0.41-2.47

0.09-0.43

1 .40-6.73
1 .35-8.40
0.23-0.72

Leaves
0.67-1.12
12.0-16.9
0.44-0.72
0.22-0.03




0.05-0.37
0.80-2.10
0.52-1 .24


4.4-8.92
0.34-1 .09
0.77-2.25

0.31-0.49
0.02-0.23
40.06-49.9
0.07-0.14
0.21-0.95
0.09-0.14
0.008-0.03
0.01-0.11
0.14-0.39

0.002-0.0

5.70-45.9
1 .27-3.07
0.02-0.03

    These data were used for the calculation of enrich-
ment factors which can better show the real role of plants
in matter accumulation compared to actual concentra-
tions since the latter lacks comparable data.

    Enrichment factors for soils, mosses, lichens, tree
bark and living leaves are compared in table 2.

    In table 2, figures in each column indicate upper and
lower levels of the enrichment factors in this order hori-
zontally : soils, lichens, mosses, tree bark and leaves for
each element.

    In most cases, the enrichment factors for plant mate-
rial are more than 1.0. The highest factors were found for
Cd, Hg,  Se, Au.

    The soils  having the highest estimated actual con-

 208
centrations for most of investigated elements do not have
the higest enrichment factors.

   Comparing the enrichment factors for soils and li-
chens, it is seen that.on average, lichens have higher K
E than soils and even mosses. For the iron-group ele-
ments, KE in lichens are several times higher than those
for soils; for  Ni, Zn, As, Se, Br, Cd, Cd, Sb, Au, and Hg,
these factors are higher by one or more levels of magni-
tude.
   The actual concentration of elements in epiphytic
lichens and mosses are, as a rule, lower than in soil-like
material under the lichens and mosses on tree trunks.
Meanwhile, enrichment factors for the plants are higher
from several times to several levels of magnitude. Higher
concentrations of elements in the material under the

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                       Element Accumulation in Lichens, Mosses and Soils Connected with Mud Volcano Activity
epiphytes is probably connected with trunk downflow and
with the filtering effect of the epiphytic cover. Only for the
Se, Cd, Hf.Yb, are the enrichment factors higher for soil
than for mosses, and for Mo and Cs higher than for
lichens. For some of the elements, the enrichment factors
are close - Na, Cs, La, Eu, Ce, Sm for mosses and soils,
and Na, Eu, Yb, Hf for lichens and soils under the epi-
phytic cover.

    It is interesting thatthe accumulation of elements by
mosses near the mud volcanos is very similar to that in
industrially polluted areas; elemental concentrations and
enrichment factors for Cd, Hg, Mo, Ag are considerably
high.
    In most samples analysed, tree bark has lower en-
richment factors than other plant material. The living
leaves of Quercus robur had highest factors for K and Au,
and considerably high factors for Hg, Cd, Ag, Mo, Br, Se,
Cu, and Ca.
    Different accumulation in lichens, mosses, soils, tree
bark and living leaves show that this process is not only
physical. Selectivity of accumulation of different ele-
ments is well known for lichens and mosses and  often
used in background and historical monitoring.

    In the situation where pollution source is "natural,"
we dealt with geochemical anomaly, and it is shown for
first time, that most of the elements transported from mud
volcano and accumulation by plants is connected with
aerosols fine fraction.

    This positive experience of element transport esti-
mation using plants confirms the possibility of using li-
chens and mosses as indicators of natural element flow
and background forming monitors.
                                                                                                    209

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                A National  Program  for  Environmental
                       Monitoring and Assessment
                 Jay J. Messer, Rick A. Linthurst, and Courtney Riordan
                         United States Environmental Protection Agency
                                   200 S.W. 35th Street
                               Corvallis, Oregon 97333, U.S.A.
                 Background

     Increasingly, reports appear on symptoms
of current or potential ecosystem problems: de-
clining fish and shellfish harvests and toxic algal
blooms in near-coastal waters, dying high-ele-
vation forests, diseased and cancerous fish in
lakes and rivers, and declining biodiversity.
Because we presently lack an integrated ap-
proach to monitoring quantitative indicators of
ecological conditions and exposure to pollut-
ants in these ecosystems, we cannot determine
whether the frequency, severity, and extent of
the problems are increasing on a regional scale,
whether such patterns are warning indicators of
significant long-term  changes in ecosystem
structure or function, or whether they are asso-
ciated with changes in ambient pollutant levels.
Lacking a framework for efficiently using data
collected by EPA and other organizations or a
monitoring scheme to fill  the critical gaps in
existing  data, an assessment of the  current
status of most environmental problems can be
expected to take 4 to 5 years to produce useful
results.

    EPA, the U.S. Congress, and private or-
ganizations with environmental and natural re-
source interests have long recognized a pro-
found need to fill this important monitoring data
gap. The need to establish baseline conditions
against which future changes can  be  docu-
mented with confidence has grown more acute
with the increasing complexity, scale, and so-
cial importance of environmental issues such
as acid deposition, global atmospheric change,
declining biodiversity, and the potential impacts
of genetically engineered organisms.

     The need for better environmental moni-
toring systems is not  restricted  to  emerging
problems. EPA's Office of Research and  De-
velopment provides the scientific underpinnings
for regulatory programs estimated to cost $70
billion annually, primarily using laboratory toxi-
cological tests and computer models to predict
pollutant transport, fate, and exposure in the en-
vironment and their corresponding effects on
biota. Years of peer review and litigation have
left little doubt that this approach is the only
rational way to form the scientific basis for the
regulation of the large number of conventional
and potentially toxic pollutants that can enter
the environment. The potential for differential
toxicity to sensitive species, different life stages
of the same species, ecological compensation
                                                                                   211

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Jay J. Messer, Rick A. Linthurst, and Courtney Riordan
and magnification, and cascading effects on
ecosystem trophic structure, however, all point
to the need for validation of the effectiveness of
the scientific models through ongoing surveil-
lance of indicators  of  continuing ecosystem
"health."

     The problem is not that we have no moni-
toring data on the environment. Approximately
$350 million is spent  each year by EPA on
environmental monitoring, about half of which is
associated with ambient (as opposed to "source"
or compliance) monitoring.  This amount is
probably at  least equaled by other Federal,
state, and private organizations.  There  also
have been programs to summarize these data.
The EPA Office of Water publishes a biannual
status  report summarizing  the  water  quality
data collected by the states to satisfy section
305(b)  of the Clean Water Act; the EPA Office
of AirQuality Planning and Standards publishes
annual reports on its air quality monitoring pro-
gram in nonattainment areas; and the Presi-
dent's  Council on Environmental Quality and
the private Conservation Foundation have sum-
marized  monitoring  statistics ranging from
population levels  to the  number of Environ-
mental Impact Statements reviewed each year
by EPA.

     These environmental monitoring programs
and interpretive summaries are an important
contribution to our knowledge of environmental
trends.  Lack of comparability of many of the
data between programs, together with the ab-
sence  of a concerted  effort to integrate data
across networks, however, have thus far pre-
vented these efforts from meeting some of the
Agency's  critical environmental risk  assess-
ment needs.   What is currently lacking  is a
systematic program for assimilating and  criti-
cally assessing the data with respect to its
quality, relevance, comparability, completeness,
and above all, for filling critical data gaps.

     If  such a program were easy or inexpen-
sive to  implement, it would certainly already be
in place, and more than one previous effort to
design and implement an integrated environ-
mental trends monitoring  program within EPA
has failed.  Many of the  obstacles that have
frustrated  the achievement of this goal  in the
past, however, may be gone. Successful inte-
grated monitoring and research programs in the
Acid Deposition Effects Program, increasing
capabilities and opportunities for cooperating
with state and other Federal agencies resulting
from National Acid Precipitation Assessment
Program, the Global Climate Program, the In-
ternational Geosphere and Biosphere Program
of the International Council of Scientific Unions,
and a resolve on the part of the Administrator of
EPA to increase the emphasis in the Agency on
protection of natural ecosystems  as well as
human health, all pave the road toward poten-
tial success.

         An Integrated Environmental
               Research Strategy

     In  September, 1987, at the  initiative of
EPA Administrator Lee Thomas, the U.S. Envi-
ronmental Protection Agency's Office of Re-
search and  Development (ORD) directed its
scientists to  develop an integrated strategy to
improve the Agency's ability to assess the risks
to natural  ecological systems at the regional
scale from current and emerging environmental
pollutants. Three primary elements were needed
to develop this strategy:

    An ecological status and trends program
    that serves to characterize, classify, and
    quantify trends in  the status of ecological
    resources and pollutant exposure;

    A core ecological research program  to de-
    velop tools to predict ecosystem-level re-
    sponses to incremental changes in anthro-
    pogenic activities

    An ecological risk assessment program
    that allows monitoring  and research out-
    puts to be integrated into quantitative esti-
 212

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                                     A National Program for Environmental Monitoring and Assessment
      mates of ecosystem-level risks from regu-
      latory policy alternatives.

     The Office of Research and Development
developed  a  coordinated  strategy for these
three elements that utilizes a tiered approach
similar to that used in risk  assessments for
single pollutants.   This approach recognizes
that, because EPA has insufficient monitoring
and research resources to address all ecologi-
cal problems, it must have an objective basis for
identifying the highest priority issues of concern
and  their current or potential severity on  a
regional basis.  The strategy also recognizes
the need to utilize, as fully as possible, current
monitoring  programs conducted  by  EPA and
other Federal and non-Federal agencies and
organizations, working cooperatively to fill any
critical data gaps.

     In the proposed tiered approach, available
biological and chemical monitoring data will be
used wherever possible to identify  problems
and corresponding geographic areas that ap-
pear to be  at the highest  risk.  High priority
systems  will serve as the  focus  for intensive
evaluation  of baseline conditions and trend
monitoring in the higher tiers, and for research
leading to the development of predictive mod-
els. Lower priority systems will be subjected to
less  intensive,  surveillance-level  monitoring.
Monitoring programs will be developed or sup-
plemented to fill data gaps which prevent mini-
mally acceptable surveillance.

           An Ecological Status and
               Trends Program

     The first proposed step in the develop-
ment of the integrated ecological research strat-
egy is creation of the Environmental Monitoring
and Assessment Program  (EMAP).  This pro-
gram has been proposed by the EPA to begin in
FY 1990 to complement its  Acid Deposition,
Global  Climate  Effects,   and Stratospheric
Modification Research Programs. The goal of
the Environmental Monitoring and Assessment
Program (EMAP) is to:

     Identify, collect,  organize, and analyze
environmental monitoring data and report peri-
odically to the Administrator on the  current
status and trends in indicators of the condition
of the nation's ecosystems.

     Combined with the expertise of the appro-
priate laboratory, program, and policy office
staffs,  these  data  reports  and  interpretive
summaries will enhance the Agency's ability to
identify and evaluate emerging environmental
issues, to focus scientific assessment programs
for high-priority issues on the regions and eco-
systems  of highest potential concern, and to
periodically evaluate the validity of the scientific
models upon which risk  management strate-
gies are based.

     In order to accomplish the program goals,
EMAP will be designed to meet the following
objectives:

1.  Make maximum use of existing monitoring
    programs to meet EPA's  ecological as-
    sessment needs and design a program to
    efficiently fill the critical data gaps

2.  Establish baseline conditions and monitor
    trends in pollutant exposure levels and vital
    indicators of ecosystem condition for for-
    est, wetland, near-coastal, inland surface
    water, and agricultural ecosystems  on a
    regional scale

3.  Seek and identify relationships between in-
    dicators of ecological condition and pollu-
    tant exposure  that should  be  considered
    for in-depth risk assessments by EPA pro-
    gram offices, or that could serve as the
    basis for important testable research hy-
    potheses or empirical management mod-
    els

4.  Provide a flexible and cost-effective mecha-
    nism for responding in a timely way to the
                                                                                     213

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Jay J. Messer, Rick A. Linthurst, and Courtney Riordan
    need to assess status and extent of rapidly
    emerging issues of public concern.

      Pollutant "exposure," as used here, may
include ambient levels of toxicants, nutrients,
microorganisms, or  geophysically active sub-
stances present in air, wet and dry deposition,
surface  and groundwater, soil, or biological
tissues as a result of human activities, that can
result in unanticipated effects on ecosystems.
Ecological indicators may include direct or sur-
rogate measures of current or future levels of
socially valued ecosystem products, structural
or functional ecosystem characteristics, includ-
ing sustainability, or impacts  on adjacent eco-
systems.

                   Approach

     The  Environmental Monitoring and As-
sessment Program  is  planned  to be imple-
mented  in three phases:

     Phase I (present-July 1989): Preparation
and Review of Phase II Research Plan

     Phase II  (August  1989-August  1991):
Assessment and Design

     Phase III  (September 1989-continuing):
Phased implementation, beginning with Pilot
testing in 1992

     The primary outputs of EMAP would be
annual environmental statistical  reports that
describe the regional status of the various indi-
cators and indices chosen for inclusion, and
statistical analyses  of regional changes and
trends. Such results are expected to come from
a  combination  of  periodic regional  surveys
(remeasurements) and more intensivedatatime-
series from selected regionally representative
research sites.  More  extensive  interpretive
assessments are expected to be produced at 3-
4 year intervals.

     A number of the tasks that are currently
planned for development in the Phase II Re-
search Plan  are  summarized briefly  below.
Although the tasks are listed in approximately
sequential order,  many can  be developed in
parallel.

I.   Develop a data management system that
    catalogs appropriate monitoring programs
    and their associated data bases and in-
    sures efficient access to quality-assured
    data in a convenient and compatible format

II.  Classify ecosystems into categories that
    could be monitored using similar measure-
    ment techniques and that would respond
    similarly to pollutant-related stresses

III.  Conduct a screening-level evaluation us-
    ing available  data and studies to identify
    high-risk  or already damaged ecosystem
    categories and to identify critical data gaps

IV.  Develop, evaluate, and standardize meas-
    urement protocols for indicators that best
    quantify the vital structural and functional
    aspects of ecosystem condition

V.  Evaluate the applicability of current moni-
    toring  network  designs, measurement
    methods, and quality-assurance programs
    to emerging environmental issues

VI.  Design and assist in the implementation of
    cost-effective monitoring programs that fill
    critical data gaps

VII. Design the annual data reports and sum-
    mary statistics

          Summary and Conclusions

     The U.S. Environment Protection Agency
is developing research plans for a program to
monitor the status and trends in extent, pollu-
tant exposure, and indicators of the condition of
ecosystems in the United States. The Phase II
Research Plan, which  is being readied for peer
 214

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                                     A National Program for Environmental Monitoring and Assessment
review in mid-1989, will describe the research    and, if so, to propose a cost-effective design. If
needed to determine whether a program meet-    implemented, the program will begin producing
ing the design objectives of EMAP can begin    annual environmental statistics on an annual
phased implementation on a pilot basis in 1992,    basis by 1994.
                                                                                     215

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           Biological Diversity and Global Change: Habit
                       Fragmentation  and Extinction

                               Christine Schonewald-Cox
                                  Thomas J. Stohlgren
                     Cooperative Parks Resources Studies Unit, Institute of Ecology,
                                     University of California,
                                    Davis, California, U.S.A.
                Abstract

     Loss of habitat through fragmentation, air
pollution, and rapid global climate change forces
an international view of the protection of biologi-
cal diversity. Anthropogenic stresses such as
acid  deposition, natural resource exploitation,
urban sprawl and global warming will undoubt-
edly cause increased extinction rates. Develop-
ing both a common terminology and a concep-
tual framework for addressing these issues is
an important first step to problem solving. We
present definitions of key terms and  propose
the use of habitat fragmentation theory as a
"common concern" approach to discuss  and
understand potential changes in regional  and
global biological diversity. We urge increased
cooperation between the U.S. and U.S.S.R. for
additional exchange of cooperative develop-
ment of inventory and monitoring technologies,
joint training of scientists of other nations,  and
increased environmental education for our citi-
zens and those of other countries.

              Introduction

    The threat of rapid deterioration of envi-
ronmental quality and  global climate change
are crises we face together as common mem-
bers of the biosphere. Tied together by this, we
need to accelerate our pace of technological
discovery for conservation.

    As research on  global  impacts, such as
that of air pollution has shown, the more we
threaten our biosphere, the more we ourselves
are threatened. We may be among the first,
rather than the last,  to disappear. Thus, the
status  of global biological diversity indirectly
represents  our own capability to endure  and
survive change.

    The subject of maintaining the self-sus-
taining systems collectively  called "biological
diversity" (or Biodiversity) is both  challenging
and complex, and stretches beyond air quality
and air pollution. The discovery, observation
and protection of biological diversity covers as
many different facets as there are disciplines in
science and professions in culture and politics.
Also included is the broad study of anthropo-
genic  extinction (damage by humans)  repre-
sented by overconsumption of natural resources,
overproduction of waste, overpopulation  and
fragmented disappearance of natural habitat.

    Our research group's specialty is the study
of how fragmentation of ecological systems ac-
                                                                                    217

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Christine Schonewald-Cox and Thomas J. Stohlgren
centuates problems such as pollution and erodes
the capability of ecosystems to rebound from
progressive catastrophic  deterioration. The
study of how fragmentation, lack of protection
(or ineffective protection) and loss of diversity
affect our natural habitats is of common inter-
est to the U.S. and U.S.S.R.  How air pollution
aggravates fragmentation is something we can
monitor and need to  cooperate to develop
mutually beneficial technologies. To progress
in this field, we depend  upon common vocabu-
laries in conservation biology that can assist us
in communicating what we observe and con-
ceptualize about habitat fragmentation and di-
rect or indirect losses of biodiversity.

       Biological Diversity: A Bridge
            For Communication

     Biological  diversity, as we conceptualize
it, is used to signify the  sum of diversity includ-
ing genetic diversity  within and between spe-
cies, between communities and between higher
taxonomic  levels (family,  ....,  class, phylum,
kingdom). Biological diversity is not necessarily
equal to species diversity,  and some groups
may house more biological (including genetic)
diversity than others. Biological diversity is what
generates and results from the ecological and
evolutionary processes we observe. The ge-
netic  diversity included in biological diversity
signifies diversity within the individual among
genes that produces phenotypes (or outward
manifestations  of the individual), diversity be-
tween individuals of a gene pool, and diversity
between gene pools. Thus, we use genetic di-
versity to signify the inherited (structural) diver-
sity at, or below, the species level.

     Also important are phenotypic diversities,
such as behavioral, physiological, etc. We use
the term "gene pool" to signify a group or aggre-
gation of interbreeding individuals (not usually a
reflection of total diversity within a species), and
within each gene pool, there is a certain amount
of genetic diversity. For  each gene pool, the na-
ture and amount of genetic diversity character-
izes the pool. The gene pool (a genetic term) is
also used frequently in ex situ conservation in
the zoo and botanical garden community when
referring to the captive groups of a species. In
ex situ conservation, scientists and managers
more  frequently use  the  demographic term,
population, to denote a group of interbreeding
individuals. So this demographic term, "popula-
tion" refers to the organisms, collectively, inhab-
iting an area or region, as the frog population of
a pond. For our purposes, the terms "gene pool"
and "population" (of a given species) are syn-
onymous. Once we have described the genetic
and demographic components of genetic diver-
sity, we know how  it  is composed  and what
constitutes its stability (or instability), both evo-
lutionarily and demographically.

     It is the  species  and population that are
generally the focus of environmental research
because these comprise the  environmental in-
dicators and failing economic resources upon
which research focuses.  However, communi-
ties comprise the group of populations that are
ecologically and geographically interconnected,
representing a few to several species. Such a
group constitutes an assemblage of plants and
animals living in a common home, under similar
environmental conditions, or  with some appar-
ent association  of needs. Therefore, the term
"community" is meant to suggest more than an
environmental indicator or forest resource. It
includes the soil microorganisms and all that the
landscape can contain within it.

     In our inventory and monitoring, we tend to
overlook this fact and concentrate too narrowly
on  a few  indicator species we presently con-
sider important. If we take on the  responsibility
to conserve biological diversity, we are made to
view the  value of both total protection  and
multiple resources use, thinking  less on  the
single species as we do the diversity and stabil-
ity of assemblages of populations. Fortunately,
a first measure of their survival is indicated or
gauged very effectively by looking at fragmen-
tation of landscapes.  Simultaneously identify-
 218

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                              Biological Diversity and Global Change: Habit Fragmentation and Extinction
ing and monitoring the conditions of such frag-
ments,  we attempt to manage the habitat to
reduce  unwanted human effects.

    Management, whether for parks or other
lands, is in danger of being  arbitrary and de-
pends upon a policy to guide it. Having a proper
guidance policy,  management  becomes the
supportive human involvement in the protection
of biological diversity. Management can either
be passive (non-interfacing) or active (manipu-
lative or interventionist). The distinction is vague.
Management implies the manner of treating a
resource for a purpose. This can range from
aesthetic purposes to the desire to control a re-
source. It is the management of fragments in its
most simple  form that equals park manage-
ment. Park management includes a full range
of characteristics in management. However,
opportunities for obtaining large parks (as op-
posed to fragments) are becoming less com-
mon and organizations  such as the U.S. Na-
tional Park Service and our state park systems
must increasingly settle for some form of com-
promise protection, management of damaged
systems, and increasingly small reclusive frag-
ments that lack inter-connections. Aside from
pollen or seeds that drift with the wind, and a few
lucky migratory animals, species diversity de-
clines in stability and quality with the disintegra-
tion of landscapes.

     Why Does Habitat Fragmentation
      Threaten Biological Diversity?

     In most  cases,  biological conservation
involves protecting fragmented habitats (Wilcove
et al., 1986; Noss, 1987). Complete protection
of ecosystems or a full spectrum of habitats  is
rarely achieved. Most reserves are  internally
fragmented by roads and inappropriate bounda-
ries, a  lack of buffer zones and/or  a lack of
corridors (Wilcove et al.,  1986; Noss, 1987;
Simberloff  and Cox, 1987;  Schonewald-Cox
and Buechner, in press).

     Recently,  attention has focused on the
complex nature of size, juxtaposition and prop-
erties of administrative  boundaries in reserve
design and preservation  (Schonewald-Cox,
1988; Goodman, 1987a, 1987b; Diamond et al.,
1987). Habitat fragmentation can reduce bio-
logical diversity in many ways, the most obvious
of which is reduced area. Reduction in area may
cause a decrease in overall habitat heterogene-
ity and reduce the role of natural  disturbance,
and even though on a small scale,  increased
edge  may temporarily increase species diver-
sity.  "Generated edges" (SCS, 1987) created
by fragmentation  adjacent  to and  within re-
serves benefit alien/pest species at the  ex-
pense of endemic species (see also Vitousek et
al., 1987). Urban sprawl and resource exploita-
tion adjacent to many nature reserves through-
out the world provide a common concern. Like-
wise,  within nature preserves, accommodating
visitors and providing for their safety has re-
stricted the role of many natural processes (e.g.
lightning-caused fires have been  suppressed,
insect outbreaks have been controlled, etc.).
Once combined, these actions can reduce the
biological diversity inside and outside nature, re-
serves.

     Wilcove et al. (1986) suggest that habitat
fragmentation  has two components, both of
which cause extinctions: (I) reduction in total
habitat area (which primarily affects population
sizes  and thus extinction rates); and (2) redistri-
bution of the remaining area into disjunct frag-
ments (which  primarily affects dispersal and
thus immigration rates). We would also add a
third component to habitat fragmentation that
causes extinction:  the  process itself is self-
driven. Fragments are increasingly likely to be
fragmented further as they increase in number
or decrease in size.

       Potential Impacts of  Habitat
              Fragmentation

     The impacts of anthropogenic stresses on
natural ecosystems largely depend on the abili-
ties of natural communities to adapt, the rate/in-
                                                                                     219

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Christine Schonewald-Cox and Thomas J. Stohlgren
tensity/magnitude of the stress, the size  of
species ranges, the dispersal rates of the indi-
vidual species, and whether or not barriers to
species migration are present (EPA, 1988).

     One example is the spotted owl in the U.S.
pacific northwest. Because of its dependence
on old-growth Douglas-fir forest which is being
harvested,  the  spotted  owl population  has
declined as edge and open habitat have in-
creased (Harris, 1986).

     Most breeding  pairs of  spotted owls re-
quire a fixed amount of old-growth forest. Long-
term population survival  will probably depend
on maximum limits for immigration distances of
the owls. If the species is to survive, remnant
patches will need to be separated by distances
(between "islands") of old-growth forests that do
not exceed natural  juvenile  dispersal  move-
ment. Harris stresses the importance of plan-
ning and understanding the spatial patterns of
forest fragments. In light of world-wide increases
of anthropogenic stress on natural ecosystems,
Harris' conceptual  model can and  must be
applied on a global scale.

     Superimposed  on  fragmentation are ef-
fects of air pollution on forests, soils and water
which  have long been  documented with the
most powerful example of large scale die-offs
we have seen previously from Germany (Pro-
ceedingsof this Symposium, Smith, 1981; Reuss
and Johnson, 1986; Blank, 1985). But, in many
cases, including  our own most protected Na-
tional Parks, subtle ecosystem changes may be
taking place because of changes in wet deposi-
tion chemistry (Stohlgren and Parsons, 1987)
or ozone concentrations  (Bennett, 1985).  Indi-
vidual species response (e.g. pine species may
be  pre-disposed to insect diseases) or inter-
specific dynamics (i.e. favoring air pollution-
tolerant species) are difficult to monitor and
assess.

     Climatic change, also of interest to these
proceedings,  will alter competitive outcomes
and destabilize natural systems in unpredict-
able ways (EPA, 1988). It is unknown to what
extent climate change will cause  changes in
species composition, food availability, preda-
tor/prey relationships or many other ecosystem
components.  It is known that species  ranges
will change (EPA, 1988; Peters and Darling,
1985), and fragments will not move with them.

    Peters and Darling (1985) provide a dia-
grammatic model of how  climate change or
shifting pollution (acid rain) might influence the
species composition of a  biological reserve.
Similarly, in our studies of National Parks we are
faced  with planning probable scenarios.  For
example, imagine a reserve in which Species A
is  pushed northward by global warming into
habitat of mixed suitability (Figure 1). Species A
may survive in pockets of this habitat as envi-
ronment pushes its dispersers further north.
Perhaps a new reserve can  be established in its
new habitat  while the old reserve becomes
home to new species assemblages. Unfortu-
nately, such a late establishment  of the new
reserve is likely to be accompanied by severe
compromises and keep species A and cohorts
in less than optimal conditions. In a worst case
scenario, development and extensive  habitat
fragmentation have removed even the opportu-
nities  for the establishment  of species A in
"mixed-suitability" sites. Species  A becomes
locally extinct as its southern limit moves north
and meets the progressive development.

    Boundaries of the park are fixed. Species
A and its associates will be eventually replaced
in the reserve. If the new species dispersing and
filling  the reserve are  non-desirable, such  as
alien plants or animals, ecosystem processes
will also be transformed. Should a replacement
species be a woody species, more flammable
than Species A, for example,  it would promote
increased intensity and frequency of wildfires.
In our current times in which the spread of alien
species has threatened representative ecosys-
tems,  such changes could exacerbate initial
impacts (Vitousek et al., 1987a and b). Such
 220

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                                Biological Diversity and Global Change: Habit Fragmentation and Extinction
           LIMITED DEVELOPMENT
EXTENSIVE DEVELOPMENT
Figure 1. Extinction, environmental change and development. In the figure on the left, a reserve (R) exists in the
        deteriorating range of species A (hatched area). Fatal sinks exist (solid black) beyond the tolerance limits
        of species A ( m : to the north; and i i i: to the south). As environmental changes move north, species A
        dispersers find refuges of mixed suitability (ms). Soon these are the only remaining sites where A can be
        found. In another scenario (figures on the right), extensive human development is expanding to the north.
        As environmental changes move northwardly, they overlay human  development (grid), and dispersers of
        species A have no "ms" habitat available. Extinction follows for lack of habitat.
                                                                                            221

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 Christine Schonewald-Cox and Thomas J. Stohlgren
changes are bound to decrease the local variety
of native  species, perhaps increase  overall
species diversity, but decrease biological diver-
sity at the continental level.

     Given paleo-ecological migration rates of
some forest species (e.g. 10-20 km per century
for chestnut, maple and  balsam fir, and be-
tween 30-40 km per century for some oak and
pine species; EPA, 1988), small reserves may
be affected more quickly than large reserves in
the same area. As was suggested by Wilcove et
al. (1986) and ourselves in the previous section,
small fragments are more likely to be depleted
than large landscape fragments.

   Uncertainties Associated With Change

     Strategies for slowing deleterious effects
of habitat fragmentation, and associated losses
in biological diversity will be difficult to come by.
Conservation Biology and Landscape Ecology
(including study of fragmentation) are still very
young disciplines. We currently possess only a
crude understanding of the  links between our
respective societies and the environment and
climate  (EPA, 1988). Taken in reverse order,
the uncertainties of climate change (it's actual
rate and potential effects) are enormous. Mod-
els used to predict climate change are in their
infancy  and are propelled by poor and incom-
plete data. Often, competing models give con-
flicting results (EPA, 1988). Little is known about
sensitivity, direction and magnitude,  and link-
ages  of climatic variables. Given our current
knowledge, it is difficult or impossible to predict
regional changes.

     Our current understanding  of  environ-
mental variables is only slightly ahead of the
case above. The widely-accepted paradigm is
that local climate is the primary factor defining
the environmental setting and determines the
species composition  and spatial patterns of
communities  in terrestrial zones (Bolin et al.,
1986).  We would add  the complex  contribu-
tions of inter- and  intra-specific competition,
predation, insects and disease and local distur-
bance frequency and intensity, and the interac-
tions of these with species population dynam-
ics. Still, this model may be replaced by an
infinitely  more complex model incorporating
climate change,  depletion  of stratospheric
ozone, the presence of tropospheric ozone and
acid deposition,  and changes to the distur-
bance regimes brought about by climate change
(EPA, 1988).

     At the present time, we are also unable to
predict the details of how fragmentation  and
anthropogenic stresses will affect species ex-
tinctions. We have few, if any cases, where the
autecological information base on a species is
complete enough to predict extinction under
different  environmental  scenarios.  Likewise,
extinction models (MacArthur and Wilson, 1967;
Quinn and Hastings, 1987; or see Burgman et
al., 1988 for a review) have not been designed
to address species-specific changes to envi-
ronmental conditions.

     The linkage between our societies to the
environment and climate is also poorly under-
stood.  How  quickly can world economies  and
resource use patterns be altered to reduce the
impacts of anthropogenic stresses on biological
diversity? Are we willingto make those changes?

     Perhaps it is this most damaging issue that
we need to address further together. How will
air pollution, global climate change and habitat
loss affect the ability of  species  to disperse?
Also, where can  they disperse to now and 20
years from now given the current rate of frag-
mentation? And,  which of these will be among
the projected percentage of extinctions? This
dispersal is fundamental to the maintenance of
species and the  generation of new ones.  Be-
cause environmental change is certain, changes
in natural selection are also certain. Few, if any,
species will remain tomorrow as they are today.
The few that are unresponsive to selection will
disappear. We need to cooperate on the study
of these broader topics  in conservation.  We
 222

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                               Biological Diversity and Global Change: Habit Fragmentation and Extinction
certainly can find commonality in the descrip-
tions of biodiversity (and methods of fragmenta-
tion), fragmentation of landscapes and effects
of environmental change on those habitats still
available in nature.

     Maintaining Biological Diversity

     Given the above  uncertainties, perhaps
our efforts to conserve species would best be
focused on  maintaining the current biological
diversity, increasing our understanding of frag-
mented landscapes and anthropogenic stresses,
and increasing cooperation between the U.S.
and U.S.S.R. as leaders in the efforts for long-
term global habitability. The U.S. and U.S.S.R.
have the greatest opportunity to provide world
leadership in the protection of biological diver-
sity in fragmented landscapes. Active  leader-
ship in the United Nations Environment Pro-
gram (UNEP), the  World  Meteorological Or-
ganization (WMO) and the International Panel
on Climate Change (IPCC) is an important first
step. We must build on the success of the Man
and the Biosphere (MAB) program and the
Montreal Protocol to protect the  Ozone Layer.
The U.S. National Park Service  stated what it
viewed as specific needs with respect to coop-
eration  in managing for viable populations in
changing  landscapes.     Emphasizing  mul-
tiagency and multinational cooperation, these
needs are probably similar in both the U.S. and
the U.S.S.R. They are:

1. The management of viable populations of
target species.
2. The preservation of variation within species
in communities extending beyond National Park
boundaries and regional landscapes.
3. Attention to external breaks in distributions
and resultant losses of migratory species to the
effects of tropical  deforestation, pollution, or
climate change.
4. Cooperation in the development and trans-
lation of technologies and exchanges of infor-
mation on inventory, monitoring, long- and short-
term research, interpretation,  education,  and
funding of protection for biological diversity.

     These needs are not limited to parks and
reserves but are required on large geographic
scales that incorporate the full diversity of exist-
ing habitats, both small and large, from hedge
rows, ponds, to riparian  and oceanic habitats.

  Increased Cooperation in U.S.-U.S.S.R.
                  Efforts

     Bilaterally, the U.S. and U.S.S.R. can serve
as the international model  in the protection of
biological diversity through more frequent inter-
actions between scientists and increased ex-
changes of data, scientific publications, tech-
niques and dialogue. We can jointly  develop
baseline inventory and monitoring techniques
and associated research, education and train-
ing activities with less-developed  countries.
Perhaps and most importantly, we can  educate
our citizens with regional and global perspec-
tives in ecology and environmental awareness.
We can actively disseminate information on bio-
logical diversity through international interpre-
tive programs. We should  stress the  interde-
pendence of our protected  areas and the nec-
essary  linkages between  socio-political sys-
tems required to protect these areas.

              Literature Cited

Bennett, J.P. 1985. Known air pollution effects on vege-
    tation in National Parks. Testimony presented to the
    House Subcommittee on National Parks  and Rec-
    reation, Committee on Interior and Insular Affairs,
    U.S. Congress, May 1985.

Blank, L.W. 1985. A new type of forest decline in Ger-
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Bolin, B., B. Doos, J. Jager, and R. Warrick (eds.). 1986.
    The Greenhouse  Effect, Climate Change and Eco-
   systems (Scope 29). John Wiley and Sons, Chick-
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Burgman, M.A., H.R. Akcakaya, and S.S. Loew. 1988.
   The use of extinction models for species conservation.
    Biological Conservation 43:9-25.
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Diamond, J.M., K.D. Bishop, and S. vanBalen. 1987. Bird
    survival in an isolated Javan woodland: island or
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Environmental Protection Agency. 1988. The potential
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Goodman, D. 1987a. Considerations of stochastic de-
    mography in the design and management of bioogi-
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Goodman, D. 1987b. How do any species persist? Les-
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Harris, L.D. 1986. The fragmented forest: Island biogeo-
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    diversity.  University of Chicago Press, Chicago, IL.

MacArthur,  R.H., and E.O. Wilson. 1967. The theory of
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Myers, N. 1987. Not Far Afield: U.S. Interests and the
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Noss, R.F. 1987. Protecting natural areas in fragmented
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Quinn, J.F., and A.  Hastings. 1987. Extinction in subdi-
    vided habitats. Conservation Biology 1(3) :198-208.

Peters, R., and J. Darling. 1985. The greenhouse effect
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Reuss, J.O., and D.W. Johnson. 1986. Acid Deposition
    and the Acidification of Soils and Waters. Springer-
    Verlag,  New York,  N.Y.

Salwasser,  H., C.M. Schonewald-Cox, and R.J. Baker.
    1987. The role of interagency cooperation in manag-
    ing for viable populations. In: M.E. Soule (ed.) Viable
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    U.K.
Schonewald-Cox, C.M. 1988. Boundaries in the protec-
    tion of nature reserves; translating multi-disciplinary
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    (in press).

Schonewald-Cox, C. M. and M. Buechner. 1989. Frag-
    mentation of ecosystems and America's crown jew-
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    and Hall, NY. (in press)

Schonewald-Cox, C.M., S.M. Chambers, B. MacBryde
    and L. Thomas (eds.). 1983. Genetics and conserva-
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Simberloff, D.S., and J. Cox. 1987. Consequences and
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Smith, W.H. 1981. Air Pollution and Forests. Springer
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Stohlgren, T.J., and D.J. Parsons. 1987. Variation of wet
    deposition chemistry in Sequoia National Park,
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Vitousek, P.M., L.L. Loope, and C.P. Stone. 1987. Intro-
    duced species in  Hawaii: biological effects and op-
    portunities for ecological research. Trends in Ecol-
    ogy and Evolution 2(7):23-37.

Vitousek, P.M., L.R. Walker, L.D. Whiteaker, D. Mueller-
    Dombois, and P.A. Matson. 1987. Biological inva-
    sion by Myrica faya alters ecosystem development in
    Hawaii. Science 238:802804.

Wilcove, D.S., C.H. McLellan, and A.P. Dobson. 1986.
    Habitat fragmentation in the temperate zone. P. 237-
    256. In: M.E. Soule (ed.) Conservation Biology, Sin-
    auer, Sunderland, MA.
 224

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   Relations Between Forest Conditions and Atmospheric
   Deposition Along the Northwestern  Minnesota-to-South-
                eastern Michigan Deposition Gradient

                       Lewis F. Ohmann and Stephen R. Shifley
                       United States Department of Agriculture, Forest Service,
                             North Central Forest Experiment Station
                     Grand Rapids, MN 557W and St. Paul, MN 55104, respectively.
                Abstract

    A distinct gradient of emission-related sul-
fate deposition increases from near background
levels in northwestern Minnesota to moderately
high levels in southeastern Michigan. Wet sul-
fate deposition patterns along this gradient are
shown to be reflected in soils of forest ecosys-
tems, and a terrestrial sulfurgradientfrom north-
eastern Minnesota to southeastern Michigan is
correlated  with the sulfate deposition gradient
in precipitation. The strongest relations between
diameter growth and estimated sulfate deposi-
tion on the 171 study plots were for jack pine,
red pine (negative relation between sulfate
deposition  and  growth),  and  sugar maple
(positive relation). Although statistically signifi-
cant, relations are weak and obscured by large
natural variation in diameter growth rates. The
effects of deposition are confounded with ef-
fects of climate due to high correlations  be-
tween the deposition levels along the gradient
and certain climatic variables. The data exam-
ined thus far make it impossible to conclude that
sulfate is a  major factor affecting tree growth in
the Lake States. With the techniques used in
this study, up to one-half of the total variation in
tree diameter growth could be explained. Of the
part that could be explained, one-fifth to one-
third was  associated with climatic variation,
sulfate deposition, other unknown factors highly
correlated with sulfate deposition or climate, or
some combination of the above.

              Introduction

    Atmospheric pollutants may  be affecting
the health of the nation's forests. Scientists
have  observed foliar damage,  unexplained
decline, and abnormal death of trees of various
species in the eastern United States (Barnard,
1986). The possibility that atmospheric pollut-
ants  are involved is frequently suggested by
members of  the scientific community and re-
ported by the media. The total geographic ex-
tent and magnitude of possible effects of air pol-
lution on  forest trees are unknown (Barnard,
1986). One way to determine the existence or
extent of forest damage is through broad sur-
veys of forest conditions that search for patterns
in relations between forest conditions and at-
mospheric deposition or  other environmental
factors (Barnard,  1986).

    We evaluated  forest conditions along a
gradient of wet sulfate (SO4) deposition ranging

                                      225

-------
 Lewis F. Ohmann and Stephen R. Shifley
 from near natural background levels in north-
 western Minnesota to moderately high pollu-
 tion-derived levels in southeastern Michigan.
 Our general hypothesis is that the wet sulfate
 deposition gradient across the  Lake States is
 reflected in the amount of accumulated sulfur in
 the forest floor-soil system and tree tissue, and
 is related to differences in tree radial increment,
 and that these effects can be separated from
 those of climate and site conditions. The follow-
 ing subsidiary hypotheses are addressed in this
 paper: (I) sulfur concentrations in the forest floor
 and mineral soil do not correlate positively with
 the sulfate deposition gradient in wet precipita-
 tion (National Atmospheric Deposition Program)
 from northwestern Minnesota to southeastern
 Michigan, and (2) when adjusted for species,
 site quality, competition and climate, observed
tree growth is independent of estimated sulfur
deposition and concentration of sulfur in the
tree woody tissue.

                 Methods

    Due to restrictions on manuscript length,
explanation of methodology is abbreviated; full
details can be found in Ohmann et a/(1988).

    This study was designed to elucidate rela-
tionships, rather than to determine cause and
effect. To facilitate sampling selection and test-
ing of the hypotheses, the gradient was divided
into 5 zones  (Figure 1). The zone boundaries
roughly correspond  to the 1, 2,  4, and  8 kg
ha' yr' isolines of the acid sulfate deposition
gradient (Nichols and Verry,  1985; Verry and
              Jack Pine    •
              Red Pine    •
              Balsam Fir   *
              Sugar Maple D
              Aspen      o
                     Michigan
    Figure 1. Sample plot distribution by forest type and zone across the sulfate deposition gradient.
226

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                                      Relations Between Forest Conditions and Atmospheric Deposition
Harris, 1988), which is equivalent to the 10,11,
13, and 17 kg ha'1 yr1 isolines of the total sulfate
deposition gradient.

    We focused on two hardwood and three
softwood  species that occur across the gradi-
ent. Three of the species are shade-intolerant:
aspen (Populus tremuloides), jack pine (Pinus
banksiana), and red pine (Pinus resinosa). The
other two are shade-tolerant: sugar maple (Acer
saccharum) and balsam fir (Abies balsamea).

    The field locations  sampled in 1985 were
selected from more than 20,000 Forest Inven-
tory and  Analysis  (FIA) plots that had been
permanently established between  1976 and
1982.  FIA forest  survey  plots for the Lake
States were screened to identify 171 plots of the
five forest types of interest, evenly spread across
the five zones and having a limited range of
initial densities, ages, and site indices (Figure
1). Numerous  measurements were made at
each study site, including current tree diameter,
crown class, measures of stand density, site
index, aspect, and  slope.

    Samples of the forest floor and mineral soil
were collected around  five selected trees  on
169 plots and returned to the laboratory  for
chemical  analysis. The chemical content  of
woody tissue samples  from those  trees was
also analyzed.

    Plot-specific sulfate levels were estimated
from atmospheric  monitoring  stations,  from
chemical  analyses  of the soil, and from chemi-
cal analyses of woody tree tissue. Atmospheric
sulfate deposition  for each sample plot was
estimated as the product of annual precipitation
and the concentrations of sulfate per unit of
precipitation. Plot-specific precipitation values
were estimated from 30-year  normal  values
(1951-1980) for 395 weather stations through-
out the Lake States. Mean annual precipitation
for each  plot was  computed as the distance
weighted average for the four weather stations
nearest to each plot.  The concentration of sul-
fate in rainfall for each plot was found to be
adequately estimated using a model relating
latitude and longitude to the mean annual vol-
ume-weighted sulfate concentrations  in  pre-
cipitation collected at monitoring sites operated
by the National Atmospheric Deposition  Pro-
gram  and  the Minnesota Pollution Control
Agency. Plot-specific deposition was estimated
as the product of the precipitation and concen-
tration estimates.

    We recognized that sulfate deposition is
only one of many factors that can affect tree
growth. Thus, we tested whether or not signifi-
cant relations between diameter increment and
sulfate level exist after accounting for variation
in tree species, tree size, site quality, tree den-
sity, and climate. Individual tree diameter growth
rates were predicted using the STEMS (Brand
et a/.,1988) tree growth projection system, ad-
justed for climatic patterns, and using an empiri-
cal linear model.

                 Results

    Forest Floor-Estimated sulfate deposition
for the plots ranged from 156 to 380 eq ha' yr'
in  zones 1 through 5 and was significantly
different among zones (P0.05) (David et a/., in press).

    Total sulfur (S) and N concentrations were
highly correlated  (R-square of 0.96, n=1765,
P
-------
 Lewis F. Ohmann and Stephen R. Shifley
 tion factors. To eliminate variation in S related to
 those factors, total S concentrations were ad-
 justed for total  N by analysis of covariance
 among zones. For both forest floor and mineral
 soils, the adjusted total S concentration stayed
 relatively constant in zones 1  through 3, and
 increased significantly (P<0.05) in zones 4 and
 5. The increase in zone 5 suggests a 15 percent
 higher S concentration; atmospheric deposition
 of S is a potential source for this increase (David
 era/., in press).

    The increase in total S concentrations ad-
 justed for total N in forest floors  and mineral
 soils across the gradient suggests rejecting the
 the null hypothesis related to  forest  floor and
 mineral soil sulfur concentrations. The results
 suggest that sulfate deposition patterns are re-
 flected in forest soil systems, and that there is a
 terrestrial sulfurgradient across the Lake States
 related to the previously demonstrated sulfate
 deposition gradients in precipitation and clear-
 water lakes (Verry and  Harris, 1988; Nichols
 and McRoberts,1986).
     Diameter Growth — All analyses testing
relationships between tree radial growth and
sulfate deposition were based on data from the
171 remeasured forest inventory plots (Figure I)
and  have focused on individual tree diameter
growth rates. To further simplify interpretation
of results, only trees that were between 13 and
23 cm dbh at the first measurement were in-
cluded in these tests. Also, analyses were lim-
ited to a single species within each  of the five
forest types of interest (e.g., only jack pine trees
growing on jack pine  plots were analyzed to-
gether, only red pine trees growing on red pine
plots, etc.). Only trees that were alive at both
measurements have been included, resulting in
between  142 and  337 observations per spe-
cies. For purposes of comparison, all periodic
diameter growth observations were  converted
to annual rates.

    The null hypothesis, that periodic tree di-
 ameter growth is  independent of the level of
 sulfate deposition at the site where those trees
 are growing, was tested by comparing observed
 diameter growth rates with two different predic-
 tions of diameter growth rate for each tree. In
 the  absence of effects of sulfate deposition,
 differences between observed and  predicted
 tree diameter growth rates were expected to be
 uncorrelated with the level of sulfate deposition.
 The following statistical tests do not make an a
 priori  assumption that the relation  between
 sulfate deposition  and tree growth is strictly a
 negative one. However, in  the analyses, the
 sign of the estimated regression coefficients for
 sulfate deposition indicates whether the level of
 sulfate deposition appears to be detrimental or
 beneficial to tree growth.

     The general model  used to test the hy-
 pothesis is:

 AD: = f(species,  size, competition, crown size,
       site quality..) + g(climate) + ei
                                      [1a]
                    vs                l  '

 AD: = f(species,  size, competition, crown size,
       site quality...) + g(climate) + h(SO4) + e
where:

 D: = observed periodic annual dbh growth of
     the ith tree
 f(species, size...) = any model  predicting dbh
     growth as a function of biological oredaphic
     factors other than climate and SO4
g(climate) = a function of climatic variables ex-
     pected to affect periodic tree dbh growth
h(SO4) =  a function of the  estimated  sulfate
     deposition or sulfate impact at each plot
ei  =  the error term,  assumed normally  distrib-
     uted with constant variance and mean zero
SO4  = estimated SO4 (kg ha  ' yr ') at each site
e. = error term
228

-------
                                      Relations Between Forest Conditions and Atmospheric Deposition
    Two  different tree growth models were
used to represent the term ((species, size,
competition, crown size, site quality...) in equa-
tions [1a] and [1b]. The first was the STEMS/
TWIGS tree growth projection model for the
Lake States (Brand etal., 1988). The STEMS/
TWIGS models are a system of individual-tree,
distance-independent  models  calibrated for
species  in  the North  Central United States.
STEMS/TWIGS was used to predict diameter
growth of the sampled trees, taking into account
tree size, crown size, size relative to competi-
tors, density, and site  quality. Differences be-
tween the  predicted  and observed periodic
diameter growth  rates for each species were
examined. If SO4 was  having a detrimental ef-
fect on tree growth, then the differences be-
tween the observed and predicted growth rates
should become large and negative as SO4 depo-
sition increases.

    The second  model used to represent the
term f(species, size, competition, crown size,
site quality...) in equations [1a] and [1b] was a
linear model of a number of variables observed
at the initial measurement  of the 171  study
plots. These variables included diameter, crown
class, crown ratio, stand density, relative tree
size, and site characteristics.
    The term g(climate) was represented by a
linear combination of the variables in Table 1,
for conifers and hardwoods,  respectively. In a
separate analysis, Holdaway (1988 and per-
sonal communication 12/87)  found these vari-
ables to be most strongly related to diameter
growth for the three conifer and two hardwood
species examined in this study. Weather vari-
ables for each plot were averaged over the re-
measurement  interval  from  observations re-
corded at the weather station nearest each plot.
    The effect of sulfate deposition was repre-
sented by the linear term, (3 0 + Bn SO4. An F-test
(McRoberts, 1988) was used to evaluate the
significance of coefficient Bn, which indicated
the importance of SO4 in explaining variation in
diameter growth. The corresponding pairs of
models are:

ADi - f(STEMS) = IB0 + g(climate) + e    [2a]
                     vs
 Di - f(STEMS) = 13 0 + g(climate) + I3n SO4
                                     [2b]
                   and
D
                                               D
    = I30 + f(species, size, competition, crown
    size, site quality...) + g(climate) + ei [3a]
                    VS
    = I30 + f (species, size, competition, crown
    size, site quality...) + g(climate) +(3 SO4 + e
                                     [3b]
Table I. Monthly and seasonal climatic variables found by Holdaway3 to have high correlations with patterns of
        tree diameter growth in the Lake States.
            Conifers
          Hardwoods
Mean November temperature
Total July precipitation
Total March precipitation
Proportion of annual ppt. in Dec. & Jan
No. days with ppt. > 0.5" in Sep., Oct., & Nov.
Temp, x ppt. for Dec. & Jan.
Temp./ppt. for July and Aug.
Ppt./temp. for Oct & Nov.
 Mean December temperature
 Total June Precipitation
 Proportion of annual ppt. in Sep., Oct. & Nov.
 Proportion of annual ppt. in Dec.
 No. days with ppt. > 0.5" in Jun., Jul. & Aug.
 Temp, x ppt. for Nov. & Dec.
a From Holdaway (1988) as amended by personal communication, Margaret Holdaway (12/87) to emphasize the
species of interest in this study.
                                                                                      229

-------
 Lewis F. Ohmann and Stephen R. Shifley
 Table 2. Summary of regression results for models [2a] and [2b] with an F-test for the significance of the
         sulfate deposition term in describing patterns of tree dbh growth. •
Model [2a]
Species
Jack pine
Red pine
Balsam fir
Sugar maple
Quaking aspen
n
305
313
142
198
205
R2
.11
.21
.21
.20
.07
without
SSEa
.793
1.543
.246
.511
.771
so.
d.f.
26
304
133
191
198
Model [2b1
R2
.13
.23
.21
.24
.09
SSEa
.781
1.508
.246
.485
.752
with SO4
d.f.
295
303
132
190
197
A Bn
-.006
-.009
.001
.011
.011
Fb
4,
7.
0
10.
5.
.5*
.0**

.2"
0*
 a Total error sum of squares
 b F-test comparing models [2a] and [2b]. This F-value indicates the importance of the SO4term after all other terms
 have been included in the model.

 Table 3. Summary of regression results for models [3a] and [3b] with an F-test for the significance of the
         sulfate deposition term in model [3b] in describing patterns of tree dbh growth.
Model T3al
Species
Jack pine
Red pine
Balsam fir
Sugar maple
Quaking aspen
n
305
313
142
198
205
R2
.35
.48
.44
.47
.33
without
SSEa
.645
1.154
.176
.402
.567
SO
d.f.
283
291
120
178
185
Model [3b]
R2 SSEa
.36
.49
.44
.51
.33
.641
1.138
.176
.377
.563
with SO4
d.f. Bn
282
290
119
177
184
-.004
-.009
-.001
.014
.006
Fb
1.8
4.1*
0
1 1 .7**
1.3
a Total error sum of squares
b F-test comparing models [3a] and [3b]. This F-value indicates the importance of the SO4 term after all other terms
have been included in the model.
where f(STEMS) is the known estimate of dbh
growth  from  the  STEMS/TWIGS  model;
f (species, size.competition, crown size,site qual-
ity...) is  the  linear combination of terms de-
scribed  above; and  g(climate) is the linear
combination  of terms (for conifers and hard-
woods, respectively) identified in Table 1.

     The left side of equations [2a] and [2b] are
simply the differences between the observed
periodic  diameter  growth and the  STEMS/
TWIGS prediction of that growth. The null hy-
pothesis of no sulfate deposition effect is re-
jected for ~3n significantly different from zero.
Weather variables  were averaged  for the
weather  station nearest each plot.
230
    Shifley (1988) used a series of additional
models to examine relations between tree ra-
dial growth and estimated SO4 deposition ex-
clusive of adjustments for differences in com-
petition, stand conditions, and weather.
    Results  (Table  2)  indicate that with the
STEMS/TWIGS model  as an indicator of ex-
pected stand change (equations [2a] and [2b]),
periodic tree diameter growth for jack pine, red
pine, sugar maple, and aspen was significantly
related to estimated sulfatedeposition(P<0.05).
However, for sugar maple and aspen trees, di-
ameter growth increased with increases in the
estimated sulfate deposition.

    When effects of sulfate deposition on tree

-------
                                         Relations Between Forest Conditions and Atmospheric Deposition
growth were evaluated in a general linear model
of tree dbh growth (with models [3a] and [3b]),
the results changed somewhat (Table 3).  The
only  significant  relations  (P<0.05)  between
diameter growth and estimated sulfate deposi-
tion  were  observed for red  pine and  sugar
maple.  As  before,  dbh growth  for  red  pine
decreased and dbh growth for  sugar maple
increased with increasing sulfate deposition.

     In the best case, these models accounted
for only about half of the total variation in  tree
diameter growth for this data set. Although sta-
tistically significant in several cases, the sulfate
deposition term accounted for no more than an
additional four percent of this variation after all
other terms were  in  the model.

     The sulfate  deposition gradient is con-
founded with climatic  gradients.  Correlations
among estimated deposition and climatic vari-
ables were  generally  between 0.5  and  0.9,
making it impossible to conclusively distinguish
effects due to the SO4 gradient from effects due
to the climatic gradients.  In combination the
climatic variables and  the estimated  sulfate
deposition accounted  for  between  6 and 15
percent of the total variation  in tree diameter
growth, or about one-fifth to one-third of all the
variability in diameter growth that was explained
by these  models. Overall, the strongest rela-
tions between diameter  growth  and  sulfate
deposition were for jack  pine,  red  pine,  and
sugar maple.

               Literature Cited

Barnard, J. E. 1986. National Vegetation Survey Pro-
   gram Plan. Forest Response Program, U.S. Dept. of
   Agric., Forest Service, Washington, D.C. 41 pp + ap-
   pendices.
Brand, G.J..M. R. Holdaway, andS. R.Shifley. 1988. A
   description of the TWIGS and STEMS individual
   tree-based growth simulation models and their appli-
   cations, pp950-959 In: A. R. Ek, S. R. Shifley, andT.
   E. Burk (eds.) Forest growth modelling and predic-
   tion: proceedings of the IUFRO conference. August
   23-27,1987, Minneapolis, MN. General Technical
   Report NC-120, U.S. Dept. of Agric., Forest Service,
   North Central Forest Experiment Station, St. Paul,
   MN, 1150pp.

David, M. B., D. F  Grigal, L. F.  Ohmann, and G. Z.
   Gertner. In press. S, C, and N relationships in forest
   soils across the  northern Great Lake States as af-
   fected by atmospheric deposition and vegetation.
   Canadian Journal of Forest Research.

Holdaway, M.  R. 1988. The relationship  between tree
   diameter growth and climate in the Lake States, pp
   490-497 In: A. R. Ek, S. R. Shifley, and T. E. Burk
   (eds.) Forest growth modelling and prediction: pro-
   ceedings of the IUFRO conference. August  23-
   27,1987, Minneapolis, MN. General Technical  Re-
   port NC-120, U.S. Dept. Agric., Forest Service, North
   Central Forest Experiment Station, St. Paul, MN,
   1150pp.

McRoberts, R. E. 1988. Comparing regression curves.
   pp 762-769 In: A. R. Ek, S. R. Shifley, andT. E. Burk
   (eds.) Forest growth modelling and prediction: pro-
   ceedings of the IUFRO conference. August 23-27,
   1987, Minneapolis, MN. General Technical Report
   NC-120, U.S.  Dept. Agric., Forest Service, North
   Central Forest Experiment Station, St. Paul, MN,
   1150p.

Nichols, D. S.  and  R. E. McRoberts. 1986. Relations
   between lake acidification and sulfate deposition in
   northern Minnesota, Wisconsin, and Michigan.  Wa-
   ter, Air, and Soil Pollution 31:197-206.

Nichols, D. S. and E. S. Verry. 1985. Evidence for the
   cultural acidification of lakes  in the northern Lake
   States, pp 253-265 In: Air pollutants effects on forest
   ecosystems. May 8-9,1985. The Acid  Rain Founda-
   tion, St. Paul, MN.

Ohmann, L. F., S. R. Shifley, and M. R. Holdaway. 1988.
   The relationship between various aspects of forest
   conditions and atmospheric deposition across the
   northwestern Minnesota-to-southeastem Michigan
   deposition gradient. Unpublished final report submit-
   ted to Program Manager, National Vegetation Sur-
   vey, Forest Response Program, National Atmos-
   pheric Precipitation Assessment Program. Available
   from authors, U.S. Dept.of Agric., Forest Service,
   North Central Forest Experiment Station, St. Paul,
   Minnesota.
                                            231

-------
  Lewis F. Ohmann and Stephen R. Shifley
  Shifley, S. R. 1988. Analysis and modelling of forest     Verry, E. S., and A. R. Harris. 1988. A description of low-
     growth trends along a sulfate deposition gradient in        and  high-acid  precipitation.  Water Resources
     the North Central United States, pp 506-513 In: A. R.        Research24(4): 481 -492.
     Ek, S. R. Shifley, and T. E. Burk (eds.) Forest growth
     mode/ling and prediction: proceedings of the IUFRO
     conference. August 23-27,1987, Minneapolis, MN.
     General Technical Report NC-120, U.S. Dept. Agric.,
     Forest Service, North Central Forest  Experiment
     Station, St. Paul, MN,  1150pp.
232

-------
     CO-Induced Climate Change and Forest Resources1
                               Robin Lambert Graham
                                Monica Goigel Turner
                                         and
                                   Virginia H. Dale
                              Environmental Sciences Division
                               Oak Ridge National Laboratory
                                     P.O. Box 2008
                          Oak Ridge, Tennessee 37831-6038, U.S.A.
    Forests both affect and respond to changes
in atmospheric CO2 and climate. Forests di-
rectly affect climate at the global scale by alter-
ing the earth's albedo, hydrological regimes,
and atmospheric CO,,.  At a local scale they can
alter air temperature, humidity, and solar radia-
tion.  In turn, forests are affected by CO2 and
climate at  many spatial and temporal scales.
The objective of this paper is to examine poten-
tial forest  responses  to increases in atmos-
pheric CO2 and to CO2-induced climate change.

    Forest responses to CO2 and climate may
be examined  by using five biotic paradigms
(Table 1).  Each paradigm has its own  spatial
and temporal scale and its own  set of unique
phenomena responsive  to CO2 and  climate
change. We will first  use these  paradigms to
review forest responses to CO2 and climate.
We will then describe the linkages between
these paradigms and the implications of these
linkages for future research on the impact of
elevated atmospheric CO, and climate change
on forest resources.
                Biosphere

     The biosphere paradigm is concerned with
global fluxes of carbon, energy, and water. It is
within this paradigm that feedbacks between
climate, atmospheric CO2, and forest resources
are most apparent.

     Biosphere carbon fluxes are, in part, regu-
lated by global vegetation because carbon, the
major constituent of plants, is absorbed  from
the atmosphere as CO2 through photosynthesis
and is returned to the atmosphere when plants
respire or die and decompose. Thus, the accu-
mulation of biomass is a major regulator of at-
mospheric CO2.  Because current atmospheric
CO2 partial pressures are generally considered
suboptimal for photosynthesis, an increase in
atmospheric CO2 should increase net photo-
synthesis in the absence of any other consid-
erations (Kramer and Sionit, 1987).

     Biosphere energy fluxes  are both directly
and indirectly influenced by global vegetation.
1 Research sponsored by the Carbon Dioxide Research Division, Office of Basic Energy Sciences, U.S. Department of
Energy, under Contract No. DE-AC05-840R21400 with Martin Marietta Energy Systems, Inc.

                                                                                   233

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Robin L Graham, Monica G. Turner, and Virginia H. Dale
Table 1. The spatial scale, temporal scale, and key phenomena within biotic paradigms in which forests respond to
        climate and CO,
Paradigm
Spatial
Scale
Temporal
Scale
                                                                   Phenomena of relevance
Biosphere

Biome


Ecosystem

Stand


Tree
Globe

Subcontinental


10'-10"ha

101-103ha


102-10'3m2
Years-millennia

Centuries-millennia


Years-centuries

Years-decades


Minutes-centuries
Energy, carbon, water fluxes

Evolution/extinction,
 migration

Disturbance, nutrient cycling

Competition, succession,
 production, water use

Phenology, reproduction,
 physiological processes,
 death
Vegetation modifies energy fluxes directly by
altering the earth's  albedo and indirectly by
regulating greenhouse gases, especially CO2,
which absorb infrared radiation from the earth
and thus create a warmer atmosphere (Mooney
et al., 1987).  A warmer atmosphere, in turn,
should increase the rate of most biochemical
processes including photosynthesis and respi-
ration.

     Biosphere water fluxes are also directly
and indirectly affected  by global  vegetation.
Evapotranspiration from vegetation directly al-
ters the global hydrologic regime (Shuckla and
Mintz, 1982).  Global vegetation can indirectly
affect biosphere water fluxes,  in that a  CO2-
controlled warmer atmosphere will cause a
change in global precipitation  patterns.   Soil
moisture availability will increase in some parts
of the  globe and  decrease  in others with a
warmer climate. Global vegetation responses
can be expected from these shifts in precipita-
tion.

     Recent human activities  have affected
these feedbacks between CO2 concentrations,
global  climate, and global vegetation.   The
largest net global fluxes of carbon from 1800 to
the present are the net releases of carbon due
to land-use changes, particularly in the tropics
                           (Houghton et al., 1983; Mellilo et al., 1988), and
                           from fossil fuel burning (Rotty, 1987). Extensive
                           planting of forests has been proposed as one
                           method for recapturing this "excess" CO2 and
                           thus slowing down climate change (Marland,
                           1988).

                                             Biome

                                The major phenomena of interest within
                           the biome paradigm are evolution/extinction
                           and species migration.   Changes in  atmos-
                           pheric CO2 and climate are likely to affect the
                           evolution and survival of tree species; however,
                           these changes are  difficult to predict.  The
                           genetic variability of CGysensitivity is not known
                           for any woody species,  although differences
                           among species have been documented (e.g.,
                           Tolley and  Strain,  1984a,1984b).  The high
                           variability of other characteristics in  natural
                           populations and the fact that the early evolution
                           of angiosperms took place in the Cretaceous
                           era when atmospheric CO2 concentrations were
                           3-10 times higher than today (Gammon et al.,
                           1985) suggest that within-species variability in
                           the response to CO2 could be significant. Under
                           rapidly  changing  environmental conditions,
                           genetic shifts could occur within a few genera-
                           tions  (Strickberger, 1985). The genetic resil-
                           ience of most tree species to climate  change
 234

-------
                                                CO2-lnduced Climate Change and Forest Resources
must be inferred from current climatic condi-
tions within their natural ranges (Johnson and
Sharpe, 1982). However, the boundaries of a
species' range  may  reflect factors such  as
competitive ability rather than climaticconstraints
(Farr and Hard, 1987; Woodward, 1987, but see
Michaels and Hayden, 1987 for an opposing
view). Tree species with broad ranges, includ-
ing most commercial species, are most likely to
survive climate change. The many tree species
that are rare or restricted in occurrence will  be
at greater risk of extinction.

     Although rates of tree species migration in
Europe and North America during the Ice Ages
were -300 m per year (Woodward, 1987),  fu-
ture migration rates are difficult to predict be-
cause the rate of a CO2-induced climate change
may be an order of magnitude faster than pre-
vious climate changes.

     Furthermore, there will be new barriers to
migration (cities, agriculture, roads) and new
modes of migration (trains, cars, or transplants
for horticulture or forest products). The current
spatial distribution and abundance of a species
will influence that species' ability to successfully
migrate to regions of suitable climate and soils
(Peters and Darling, 1985).

     Human activities will greatly influence many
biome forest responses. Breeding programs, a
viable option for many commercial species,
may permit certain species to  maintain  their
current ranges (Kellison and Weir, 1987). Land-
use and ownership will affect not only the migra-
tion rate of species but also their ultimate range
and abundance.  For example, the theoretical
range of loblolly pine under a warmer climate
would extend well into Indiana and Ohio (Solo-
mon, 1986).  However, the actual range would
not extend that far north because the northern
land would still be used for agriculture (Miller et
al., 1987).  Furthermore, the displacement of
forest types in space  will be likely to alter their
ownership and thus their commercial productiv-
ity (Wallace and Newman, 1986).  Human use
of forests for fuelwood could also change with a
warmer climate, thereby altering rates of defor-
estation in some areas.  The effectiveness of
parks and wilderness areas in preserving rare
species may change if the spatial distribution of
a biome shifts. Humans may need to assist the
migration of some species if these species are
to survive (Peters and Darling, 1985).  Active
conservation is most likely to be necessary if the
range of a species occurs at  the  edge of  a
biome, if the species has limited dispersal abil-
ity, or if the habitat of the species is disjointly
distributed within the biome.

                Ecosystem

     Phenomena of special interest within the
ecosystem paradigm are disturbance regimes
and nutrient cycling. The frequency, duration,
and severity of both abiotic and biotic distur-
bance regimes are likely to be altered by climate
change and elevated CO2. Abiotic disturbances
such as fires and floods may  change in  fre-
quency and intensity as  a consequence of cli-
mate  change. Forest fire frequencies should
increase where the climate becomes warmer
and drier (Sandenburgh et al., 1987; USDA
Forest Service, 1987).  The intensity and fre-
quency of forest fires may also be altered by
changes in species composition  induced  by
elevated CO2 and climate  change. Flooding
frequencies are also likely to change, although
not unidirectionally  (Tombaugh et al.,  1982;
USDA Forest Service,  1987).   Many  forest
ecosystems are maintained by specific abiotic
disturbances; a climate-induced shift in abiotic
disturbances  could by itself induce  major eco-
system shifts (Johnson and Sharpe, 1982; Strain
and Armentano,  1982).

     Biotic disturbances such as forest pests
and pathogens may also shift in response to
elevated CO2 and climate change.  The ranges
of pathogens are often limited by climatic fac-
tors (e.g., Rutherford and Webster,  1987), and
their distribution may change.  Insect herbivory
may also increase because  of CO2-induced
                                                                                      235

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Robin L. Graham, Monica G. Turner, and Virginia H. Dale
changes in plant tissue quality  (Butler et al.,
1986; Lincoln et al., 1984). Of importance to
managed forests and nature reserves are pos-
sible shifts in the range and relative competi-
tiveness of weedy plants (Haynes, 1982; Peters
and Darling, 1985).

     Climate change and elevated CO2 will also
alter forest  nutrient  cycles by  altering  litter
decomposition rates  and tree nutrient uptake
and internal cycling. Decomposition rates could
change in response to climate and CO2-induced
alterations in the physical environment, litter
quality, or decomposer organisms.  A warmer
climate might increase the rate of decomposi-
tion by enhancing fungal and bacterial growth
(Meentemeyer, 1978), but a drier climate would
tend to retard decomposition.  Forest arthro-
pods, a key component of the decomposition
process, could have their range altered and
their activity level affected by changing plant
tissue  or litter quality (Cooper, 1982; Kimball,
1985).  If the  higher C:N ratio found in plant
tissues grown under elevated CO2 corresponds
with a higher litter C :N ratio, then decomposition
may be slowed because decomposition rates
are negatively correlated with high  litter C:N
ratios (Mooney et al.,  1987). However, there is
experimental evidence that litter lignin:N ratios,
which are also negatively correlated with de-
composition rates and generally a better indicator
of decay rates (Mellilo et al., 1982), remain the
same or decrease under elevated CO2 (Norby
et al.,  1986a).   The interaction of  all  these
positive and negative effects and the difficulties
in extrapolating results across ecosystems limit
our current ability to predict the overall impact of
climate change and elevated CO2 on decompo-
sition processes.  The impact of elevated CO2
on many aspects of internal nutrient cycling is
largely unknown. No studies have followed the
effect of elevated CO2 on woody plant nutrition
for longer than one growing season. Limited
data suggest that the return of nitrogen through
litterfall may remain constant or decrease due
to an observed increase in nutrient-use effi-
ciency  (Norby et al.,  1986a).  Species  shifts
associated with elevated  CO2 and climate
change may also change nutrient cycling pat-
terns  and rates  at specific sites (Pastor and
Post,  1988).

     Human activities can modify ecosystem
responses to climate change and elevated CO2.
The impact of humans is most readily observed
in human-induced disturbances such as pollu-
tion and introduced pests and in human modifi-
cations of natural disturbances through activi-
ties like  fire suppression  and flood control.
Regional land-use changes could  also influ-
ence forest ecosystem responses as an eco-
system's response to disturbance  may be a
function of its setting in the larger landscape.

                  Stand

     Phenomena of  interest within the forest
stand paradigm  are  competition, succession,
production, and water use.  Competitive abili-
ties of species  may shift as a result of species-
specific physiological responses to elevated
CO2 and climate change.  Consequently, spe-
cies compositions may change (Zangerl and
Bazzaz,  1984).  New species may  invade, or
species may be eliminated (Peters and Darling,
1985). Succession may proceed faster with a
warmer climate or be slowed by drought condi-
tions.  Site-specific  stand  productivity could
change because of changes in species compo-
sition, altered climate conditions for growth, or
CO2  fertilization  effects (Leverenz and Lev,
1987). Stand water use, a critical factor in the
hydrologic budgets of many regions, may  de-
crease because  individual tree water-use effi-
ciency may increase with  greater concentra-
tions of atmospheric CO2 (Leverenz and Lev,
1987; Miller etal., 1987). However, an increase
in stand  leaf area, because of CO2-enhanced
growth and tolerance to shade, might counter-
act the decrease in stand water use expected
from the  improved water-use-efficiency.

     Few studies empirically examine the rela-
tionship between stand properties and climate
 236

-------
                                               CO,-lnduced Climate Change and Forest Resources
across a wide sample of communities (Johnson
and Sharp, 1982; but see Denton and Barnes,
1987), although site-specific empirical relation-
ships between community parameters and cli-
mate have been developed using tree ring and
pollen records (Cook et al., 1987; Josza and
Powell, 1987; Webb, 1982; Woodward, 1987).
Thus, it is difficult to predict in any quantitative
sense how climate alone affects stand phenom-
ena.

     Experimental data on the impact of ele-
vated CO2 and climate change on stand phe-
nomena are also sparse. A microcosm study of
bottomland  and upland tree communities, in
which seedlings of different species were grown
together for 90 days under elevated CO2 and
two levels of light, showed that elevated CO2
had no effect on the overall growth of either
community, although there were differential
species responses to CO2 within the communi-
ties (Williams et al., 1986). In another growth
chamber  study, a fast-growing  pioneer tree
species showed a 70 percent increase in bio-
mass under an enriched CO2 atmosphere, while
a slower-growing climax species showed only a
30X increase (Oberbauer et al., 1985).  Such
studies suggest that successional paths may
change and new community types may evolve
under conditions of elevated atmospheric CO2
just as they have in areas subjected to chronic
ozone air pollution (Taylor, 1984).

     Humans influence forest stands primarily
through forest management activities, although
local air  and  water pollution and  poor soil
management (erosion or compaction) can also
be important.  Silvicultural tools such as plant-
ing stock, density of planting, mulch, fertiliza-
tion, and thinning regimes may be used in
managed stands to counter negative effects of
climate change or augment positive effects
(Phares,  1980;  Sandenburgh  et  al.,  1987;
Tombaugh et  al., 1982).  Forest response to
elevated CO2 and climate change may be eas-
ier to manage in mixed-species stands under
uneven-aged management than in monospeci-
fic  stands  under  even-aged  management.
Individual trees will respond to climate change
on a gradual basis and at uneven rates.  Un-
even-aged management allows harvesting  in
accordance with the differential timing of those
responses.  In stands under even-aged man-
agement, species composition and genotype
can be switched  only at planting time.  Thus,
even-aged stands  will require more decisive
management with perhaps  more risk. Already
there is concern within the U.S. forest industry
about the fate of loblolly pine stands planted  to
the south and west of their  natural range if the
climate in that region  becomes even drier and
hotter (Graham et al., 1986).

                  Trees

     Phenomena of interest within the individ-
ual tree paradigm are phenology,  life cycle
events (e.g., reproduction,  death) and physio-
logical processes (e.g., photosynthesis, tran-
spiration, respiration,  carbon allocation, nutri-
ent uptake, nutrient allocation). The key issue
regarding each of these phenomena is to iden-
tify the effects of  climate factors and/or atmos-
pheric CO2 with or without other stresses (e.g.
drought, flooding, cold, shade, poor soil, pollu-
tion).

     Our understanding of the effect of climate
on trees is based  largely on qualitative observa-
tions of mature trees and short-term (minutes to
days) experiments on tree seedlings.   In par-
ticular, there is very  little information on  how
frequency of extreme climatic events  affects
tree phenomena  (USDA Forest Service, 1987;
World Meteorological Organization, 1985). This
is especially important as climate change may
frequently expose  trees to climatic extremes
that the trees are known to  survive if subjected
to  only infrequently. The lack of experimental
and quantitative data on mature trees hinders
precision and accuracy in  predictions on tree
response to climate change.

     Our understanding of the effect of CO2 on

                                       237

-------
Robin L. Graham, Monica G. Turner, and Virginia H. Dale
tree phenomena is limited to agricultural stud-
ies and short-term (< 2 growing seasons) stud-
ies on less than 20 tree species.  Under well-
watered and fertilized conditions,  nearly all C3
plants, including trees species, show signifi-
cantly greater growth with the addition of ele-
vated CO2 (Kimball, 1986; Sionit and  Kramer,
1986).  The usefulness of this information is
limited, however, as trees generally grow under
less than ideal conditions and for many years.
Thus, data on the long-term response to CO2
under conditions of nutrient stress, water stress,
and light deprivation are needed to predict the
impact of elevated CO2 on tree phenomena.
     Existing short-term seedling studies sug-
gest that elevated CO2 will  enhance seedling
growth under conditions of nutrient, soil mois-
ture, and light deprivation (Norby, 1987; Norby
et al., 1986b; O'Neill et al., 1987; Tolley and
Strain, 1984a, 1984b). The effects of tempera-
ture, humidity, or  air pollution  on the impact of
elevated  CO2 on tree phenomena have not
been studied,  although  agricultural  studies
                                 suggest that elevated CO2 will mitigate negative
                                 responses to these factors (Kramer and Sionit,
                                 1987). The lack of long-term studies precludes
                                 any data on tree life cycle events or phenology.

                                      Humans can  exert influence within this
                                 paradigm by  modifying  either the immediate
                                 environment of the tree (e.g..watering, fertiliza-
                                 tion, weed control, or pollution abatement) or
                                 the genetic makeup of the tree (e.g., breeding or
                                 genetic engineering). Of all the paradigms, this
                                 one is the most amenable to experimental study.
                                 Long-term data and data on phenological re-
                                 sponses are especially needed at this time.

                                        Linkages Between  Paradigms

                                      Linkages between  these five paradigms
                                 are illustrated in Figure 1. The biome, commu-
                                 nity, and individual tree paradigms all consider
                                 species characteristics but at progressively finer
                                 spatial and temporal resolutions.  In the same
                                 manner, biosphere, ecosystem, and individual
      Energy .water,  nutrients
                 fluxes
 Biosphere



Ecosystem—



    Tree
                                     Species  and  population
                                           characteristics






Biome
t
i- Community
I
Tree
                                       Stand
                                        Tree
                                       Forest
                                  Management
 Figure 1.  Interrelationships between biotic paradigms. The community paradigm, which was not expanded upon in
         his paper, is primarily at the same spatial and temporal scale as the stand and ecosystem paradigms. It en-
         compasses the phenomena of succession and competition but in a more general sense in that the community
         paradigm is focused on all species, not just tree species.
  238

-------
                                                   CO2-lnduced Climate Change and Forest Resources
tree paradigms all consider energy,  nutrient,
and water fluxes.  The stand  paradigm com-
bines both the  community and the ecosystem
paradigm with  a focus on management.  It is
important to recognize that these linkages are
bidirectional across spatial and temporal scales.
For example, succession, which takes decades
or centuries and is part of the  community and
stand paradigm, is a function of (I) species-
specific responses to environmental variables
(measured at the individual scale), (2) competi-
tive interactions among species for light, nutri-
ents and water (measured at the community
scale) and (3)  seed source availability, which
may be dependent on species migration rates
(measured at the biome scale).  Prediction of
many forest phenomena will require both infor-
mation  collected  across several spatial and
temporal scales and the  ability to  link these
scales.

     Implications for Future  Research

     In developing future research, it is impor-
tant to recognize and exploit the linkages be-
tween the  five paradigms so that data and
studies can  be  used most effectively.  For
example, data on litter quality, useful in making
ecosystem predictions, can and  has been col-
lected in the course of individual tree studies
(Norby etal., 1986a). Furthermore, the bidirec-
tionality  of the linkages  between paradigms
argues for forest response studies conducted
within  all paradigms.   We cannot  expect  to
predict the fate of forest resources if we focus on
only one paradigm.  The  interconnectedness
and the enormous spatial and temporal range of
forest responses also stress the  need for con-
tinued research on scaling problems, long-term
field studies, and innovative models.   Finally,
the impact of human activity on forest responses
must not be neglected, especially when study-
ing forest responses within the stand and biome
paradigms.
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                                              241

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            Direct Responses of Forest Trees to Rising
                      Atmospheric  Carbon Dioxide1

                                   Richard J. Norby
                               Environmental Sciences Division
                                Oak Ridge National Laboratory
                          Oak Ridge, Tennessee 37831-6034, U.S.A.
    The steadily increasing concentration of
C02 in the atmosphere is one of the best docu-
mented changes occurring in the global envi-
ronment. Forest resources can be expected to
respond both to the direct effects of increased
C02 and to the indirect effects of climate change
arising from the "greenhouse effect" of CO2 and
other radiatively-active trace gases.  Predic-
tions about the indirect effects necessarily
depend on  a  series of critical  uncertainties
about the relationships between fossil energy
use and atmospheric  CO2,  CO2 and climate,
climate and forests. Reliable speculation about
the direct interaction between  increasing at-
mospheric C02 and forest ecosystems will help
resolve some of these uncertainties and im-
prove our ability to evaluate the issue of global
climate change.

    The biosphere is both an important sink for
atmospheric C02 and a source of CO2.  On a
global basis, the fluxes of carbon between the
biosphere and the atmosphere are to a signifi-
cant degree determined by forest ecosystems,
which account for about two-thirds of  global
photosynthesis (Kramer,  1981).  CO2 is a pri-
mary substrate tor photosynthesis and plant
growth, and it has been well known for decades
that photosynthesis is stimulated and plants
grow larger or faster in CO2-enriched environ-
ments. Such responses in trees could increase
the flux of CO2 from the atmosphere and subse-
quent sequestering of  carbon in the biosphere,
thereby slowing the rise in atmospheric concen-
tration, even  if forest clearing and burning si-
multaneously increases the countervailing flux
of CO2 to the  atmosphere (Allen et al., 1987).

     In addition to their role in the global carbon
cycle, trees are an important commodity,  and
increased tree growth would be an economic
benefit offsetting to some degree the various
deleterious effects of climate change.  Unlike
annual crop plants, individual  trees that  are
planted today will experience substantially higher
concentrations  of  CO2 during  their lifetimes
without the opportunity for genetic adaptation,
whereas  crop plants  are constantly bred to
perform best  in the current CO2 environment.
Reliable information on the capacity for different
 1 Research sponsored by the Carbon Dioxide Research Division, Office of Energy Research, U.S. Department of
 Energy, under Contract No. DE-AC05-84OR21400 with Martin Marietta Energy Systems, Inc. Publication No. 3211,
 Environmental Sciences Division, Oak Ridge National Laboratory.
                                                                                    243

-------
Richard J. Norby
tree species to respond to rising CO2 and on the
effect of  elevated CO2 on tree responses to
climatic change could influence the decisions of
forest companies on what species to plant in dif-
ferent regions in order to maximize productivity
in an atmosphere different from the atmosphere
of today.

     Plant Responses to Elevated CO2

     Basic plant physiological processes (e.g.,
photosynthesis, transpiration, carbon metabo-
lism, nitrogen metabolism) are similar in herba-
ceous  plants and trees.  The  large body of
literature on the responses of nonwoody plants
to  elevated CO2 is,  therefore, an appropriate
starting point for considering the responses of
woody plants. There are a number of compre-
hensive reviews on the responses of crop plants
and grasses to elevated levels of atmospheric
CO2 (articles in Lemon, 1983; Strain and Cure,
1985; Enoch and Kimball, 1986) from which the
following discussion is drawn. Surveys of the
results of many experiments indicate that the
growth of C3 plants increases about 30% or
more with a doubling of CO2 concentration.  A
typical response to  CO2 enrichment  is an in-
crease in mass of all plant organs, with roots
gaining proportionately more mass than stems,
and stems more than leaves. The additional dry
matter increases root length and produces both
longer and thicker stems.  Increases in leaf
mass are associated with increases both in leaf
area and thickness.

     Physiological studies at the biochemical,
organ, and whole-plant levels help to explain
the plant  growth responses to CO2 enrichment.
Photosynthesis increases in all plants on the
initial exposure to elevated CO2. Starch often
accumulates in leaves, which leads to an inhibi-
tion  of photosynthesis in  many species  with
longer-term exposures. Leaf transpiration rate
decreases because of partial stomatal closure.
Photorespiration is decreased, but dark respi-
ration generally is not directly affected.
       Symbiotic nitrogen fixation is
          enhanced in legumes

     Despite the fundamental similarities among
all green plants,  trees have special attributes
that are likely to influence how they respond to
elevated CO2:  large size, long life, and a pre-
dominance in unmanaged habitats with resource
limitations. These attributes of trees also pre-
clude many of the same kind of CO2 enrichment
experiments as have been accomplished with
annuals.  Inferential  evidence,  such  as  very
short-term responses, responses of seedlings,
or historical records must be used instead.

     In several investigations, seedlings, trees,
or parts of trees that have been growing in the
ambient atmosphere have been subjected to
sudden increases in  CO2 concentration.   For
example, Green  and Wright (1977) enclosed
shoots of  Pinus ponderosa trees in cuvettes
and exposed them to elevated CO2 for 1  day.
Photosynthesis was significantly  enhanced.
Wong and Dunin  (1987) exposed a small group
of trees in a 12-year-old Eucalyptus forest to
680 u.l/1 CO2 for 1  day  in a 12-m high enclosure.
Photosynthesis was 50% higher  and transpira-
tion was 30% lower, relative to a day 3 weeks
prior at 340 uJ/l CO2. Such experiments may be
quite useful  for exploring fundamental ques-
tions concerning  the  mechanism of photosyn-
thesis, and they have established thattrees, like
other green  plants, do have the capacity for
increased photosynthetic rates in elevated CO2
levels.   However, these  instantaneous re-
sponses are not directly pertinent  to the re-
sponses of trees experiencing a gradual enrich-
ment of the atmosphere with CO2.  The photo-
synthetic capacity of a particular leaf is influ-
enced  by carbon demand  (sink strength) in
other parts of the organism and by feedback
inhibition from accumulation of metabolites in
the leaf.  The diurnal  and seasonal patterns of
photosynthesis may  be  more important  than
photosynthetic capacity.  Canopy photosynthe-
sis is also a function of leaf area development.
Leaf area and tree growth are highly dependent
 244

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                                 Direct Responses of Forest Trees to Rising Atmospheric Carbon Dioxide
on past environmental conditions that alter the
storage of metabolites and the number of leaf
primordia.

     Based  in part on the limited predictive
value of instantaneous responses to CO2 en-
richment, most studies on the effects of ele-
vated CO2 on trees  have used  seedlings or
small saplings grown for all or most of their life
in regulated CO2 atmospheres in growth cham-
bers orgreenhouses. Generally, the responses
are similar to those reported with herbaceous
plants (Allen et al., 1987).  Increased photosyn-
thesis, decreased transpiration, increased dry
matter accumulation, and other physiological,
morphological,  and  phenological  alterations
have been documented in conifers, hardwood
forest trees, fruit trees, and tropical trees (Enoch
and Kimball, 1986; Kramer and Sionit, 1987).

     Species vary in the magnitude or nature of
their responses, but there is not yet a strong
basis for classification by taxonornic relation-
ships, growth  form,  or other characteristics.
One obvious classification scheme would be
deciduous versus evergreen (or broadleaf ver-
sus conifer), but results of such  comparisons
(e.g., between Liquidambarstyracifluaand Pinus
taeda) have been inconsistent (Tolley and Strain,
1984; Sionit etal., 1985). A species with a fixed
growth habit (Quercus alba) might be expected
to exhibit a smaller response to CO2 enrichment
than a free-growing species  (Liriodendron tu-
lipifera), at least during a single growing sea-
son, but this hypothesis has not been supported
experimentally (Norby and O'Neill, 1988).

          Resource Interactions

     A major limitation on the use of most short-
term studies as predictive tools for the responses
of  forest trees is  that the plants were grown
under constant, stress-free  conditions,  fully
supplied with water and mineral nutrients. Forest
trees grow in environments with multiple, inter-
acting and  fluctuating  resources,  and  they
commonly are subjected to water stress or a
limited nutrient supply.  Competition between
individuals in a stand further reduces resource
availability.  The CO2 response of a tree seed-
ling well supplied with water and nutrients may
be a poor indication of the responses of forest
trees to gradually rising atmospheric  CO2.
Indeed, some physiologists and ecologists have
suggested that  resource  limitations will pre-
clude a growth response to elevated CO2 and,
therefore, discount the  possibility of a direct
effect of  rising CO2 on forests (Kramer, 1981;
Strain and Cure, 1985).  This invocation of the
"law of the minimum" is overly simplistic in that
it ignores the possible  interactions between
resources (Norby  et al., 1986a; Kramer and
Sionit, 1987).

     Nutrients.  Experiments at the Oak Ridge
National Laboratory have explored the question
of whether the growth of a tree in an infertile
habitat will increase as  the atmospheric CO2
concentration rises. This research started with
the general  hypothesis that the stimulation of
below-ground processes of plants grown in high
CO2 will  increase nutrient  availability, thereby
circumventing current  nutrient  limitations to
growth (Luxmoore, 1981). The various mecha-
nisms proposed for CO2  x nutrient interactions
begin with high CO, stimulating photosynthesis.
From what is  known about carbon allocation
patterns  in  plants,  increased photosynthesis
should lead to an increase in the relative amount
of carbon translocated to root systems.  This
could give two kinds of response: a stimulation
of activity per  unit  root, or an  increase in root
growth and  exploration  of the soil.  In either
case, nutrient uptake by  the root system could
be enhanced. Nutrient availability could also
increase because of an increase in the exuda-
tion of carbon compounds from the root to the
rhizosphere.   This,  in turn, could  stimulate
microbial activity involved in nutrient turnover.
Symbiotic activity,  such  as mycorrhization or
nitrogen fixation, might also increase.  On the
other hand,  there are mechanisms that could
lower the physiological demand for  certain
nutrients in high CO2, that is, increase the plant's
                                                                                      245

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Richard J. Norby
nutrient-use efficiency.

     Experiments in which tree seedlings were
grown  in pots containing nutrient-poor forest
soil in  controlled environment chambers with
regulated CO2 atmospheres have shown that
nutrient deficiency does not preclude a growth
response to elevated CO2.  For example, the
growth of one-year-old Ouercusalba seedlings
that were severely N deficient was 85% greater
in 690 nl/l CO2 than in 362 |il/l CO2 (Norby et al.,
1986a), and N-deficient Liriodendron tulipifera
in  elevated CO2 had  73%  greater dry weight
than plants in ambient CO2 (O'Neill et al., 1987a).
In  both of these experiments plant growth in-
creased without a concomitant increase  in N
uptake, suggesting an increase in N-use effi-
ciency. Increased N-use  efficiency  in CO2-
enriched plants  could result from a reduced
activity of the enzyme ribulose bisphosphate
carboxylase/oxygenase,  which accounts for a
substantial  portion of  leaf N.

     These and other experiments have also
provided support for some of the proposed
mechanisms  whereby CO2 enrichment might
increase nutrient availability and uptake. In the
aforementioned experiment with Q. alba seed-
lings, P uptake increased with CO2 concentra-
tion, thereby maintaining an adequate concen-
tration  of P in the leaves,  which is especially
important since Conroyetal. (1988) have shown
that if foliar  P  becomes deficient, a CO2 growth
response is inhibited (unlike the situation with N
discussed above). The increased uptake of P in
the Q. alba seedlings was attributed to acceler-
ated P  mineralization in the soil, which resulted
from a  greater proliferation of fine roots and as-
sociated mycorrhizae and rhizosphere bacteria
(Norby et al.,  1986a). A specific stimulatory
effect of CO2 on mycorrhization has been shown
in  several  studies with  the ectomycorrhizal
species, Q. alba and Pinus echinata (O'Neill et
al., 1987b;  Norby et al.,  1987).  Symbiotic N2
fixation was also shown to be stimulated by CO2
enrichment in the leguminous species, Robinia
pseudoacacia and the  actinorhizal species,
Alnus glutinosa (Norby, 1987).

     Water.  The physiological responses of
increased carbon assimilation and decreased
transpiration in plants growing in elevated C02
lead to increased water-use efficiency, which
should result in increased growth of plants with
limited water supply (Morison 1985). There are
many reports of elevated CO2 increasing instan-
taneous transpiration efficiency in woody plants
(Kramer  and Sionit, 1987;  Hollinger,  1987;
Conroy et al., 1988), resulting from enhanced
photosynthetic uptake, decreased transpiration
(stomatal closure), or both.  There are fewer
reports  documenting   increased  wholeplant
water-use efficiency (Norby etal., 1986a; Conroy
et al., 1988). I n an experiment with Liriodendron
tulipifera seedlings (Norby and O'Neill, 1988),
CO2 enrichment stimulated the rate of photo-
synthesis per unit leaf area, but this effect was
compensated for by a decrease in the relative
amount of leaf area. Although this reduction in
relative leaf area  limited  the overall  growth
increase, it had favorable consequences for
plant water use:  the water-use efficiency of
plants in elevated CO2 was significantly higher
than that in ambient CO2.

         Long-term Responses of
          Trees to Elevated CO2

     Another limitation  of short-term C02 en-
richment  experiments is that  they do not ad-
dress the important attributes of the perennial
habit and the problems of water transport and
carbon balance in tall, massive trees.  An ex-
periment with an annual plant lasting several
weeks or months might be considered a long-
term experiment, but considering the impor-
tance in  trees  of the  physiological functions
associated with winter dormancy,  carbon and
nutrient storage and remobilization,  and re-
growth, CO2 enrichment experiments with tree
species should be called "long term" only if their
duration exceeds one growing season. The
long-term responses of woody plants to ele-
vated CO2 are just beginning to be addressed in
 246

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                                Direct Responses of Forest Trees to Rising Atmospheric Carbon Dioxide
experimental studies. In a preliminary experi-
ment in Livermore, California, seedlings and
saplings of Pinus ponderosa were exposed to
elevated CO2 in open-top field chambers con-
tinuously for over 2 years (Surano et al., 1986).
The treatments were unreplicated and there
was only one sapling per treatment, but  the
results suggested that the beneficial effects of
elevated CO2 begin to decrease  at concentra-
tions greater than 500 uJ/l. A long-term CO2 en-
richment study with Liquidambarstyraciflua and
Pinus taeda seedlings was initiated at the Duke
University Phytotron (Kramer and Sionit, 1987),
but only preliminary results have been reported.
A long-term, replicated CO2 enrichment study
using  Quercus alba and Liriodendron tulipifera
seedlings in open-top field chambers  will be
initiated at the Oak Ridge National Laboratory in
1989.

    Because of the difficulty and expense of
long-term CO2  enrichment  experiments, other
indirect approaches  have been taken to ana-
lyze the responses  of trees.  Responses to
historical increases in atmospheric CO2 may be
recorded in tree-ring chronologies. After statis-
tically removing the influences of climate vari-
ables,  LaMarche et al. (1984) attributed  the
anomalous increase in tree ring  width of sub-
alpine conifers to a direct response to  the in-
creasing concentrations  of atmospheric CO2.
Another  indirect  approach  was taken  by
Woodward  (1987),  who attributed the 40%
decrease in stomatal density in  the leaves of
herbarium specimens of tree species collected
over the last 200 years to the increase in atmos-
pheric CO2, although these results have been
disputed by Korner (1988).

      Forest Ecosystem  Responses

    Neither these historical records of past
responses to CO2 enrichment in mature trees
nor direct experimentation with young trees
over a few  years  enables us to predict with
confidence the  growth  of  trees in the CO2-
enriched atmosphere of the future.  Beyond
direct observation of tree growth overthe coming
decades, a necessary approach will be to simu-
late tree growth with computer models. Physio-
logically-based  simulation models  are  being
constructed to address the responses of plants,
including trees,  to elevated CO2 (Reynolds et
al., 1988; Luxmoore et al., 1989). The use of a
model based on the integration of physiological
processes allows the prediction of plant growth
responses under conditions beyond those used
to calibrate the model, thus representing an
approach to predicting the long-term response
of a tree to elevated CO2 from the short-term
responses of seedlings.   For this modeling
approach to work, reliable data on the relevant
physiological responses to CO2 are required for
model parameterization.  The percentage dry
weight increase of a seedling in a short-term
experiment cannot be extrapolated to predict
the dry weight increase in a mature tree under
different conditions, but  the physiological  re-
sponses of a current-year leaf of a seedling can
(with caution) be used to predict the response of
a current-year leaf on a large tree. Many other
measurements of short-term responses, such
as the mass of dormant buds or nutrient storage
in perennial tissue, may provide insights into the
longer-term responses (Norby et al., 1986b).

     The responses of forest ecosystems  to
elevated CO2 will depend not  only on the pri-
mary growth responses of individual trees,  but
also on diverse biotic and abiotic interactions
(Strain,  1985). The dynamics of a forest stand
over time have been simulated with computer
models using generalized information aboutthe
birth, growth,  and death  of the individual spe-
cies in the stand. This approach has been used
to address the question of forest changes under
different scenarios of  CO2-induced climate
change (Solomon, 1986; Pastor and Post, 1988),
but because of a lack of appropriate input data
regarding the primary growth responses of dif-
ferent species or groups  of species to CO.,
enrichment, the ecosystem modeling approach
has been used  only to a limited extent to  ad-
dress the direct effects of elevated CO2 (Botkin,
                                                                                     247

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Richard J. Norby
1977; Solomon and West, 1987). As more infor-
mation  becomes available,  either from long-
term experiments or as output from physiologi-
cal growth simulations, ecosystem models will
be better able to incorporate CO2 effects.

     Ecosystem models incorporate response
functions of trees to environmental resources
as well as some feedbacks and interactions
between tree growth and resource availability.
Unless  specific CO2-response functions are
included, however, the implicit assumption is
that  the interactions do  not  change with CO2
concentration, despite the evidence from physio-
logical studies that CO2 concentration can influ-
ence resource availability and  utilization. The
model of Pastor and Post (1988), which simu-
lates the responses of northern forest ecosys-
tems to CO.,-induced climate change, empha-
sizes the importance of indirect effects on water
availability, but it does not alter the relationship
between tree growth and water as a function of
CO2 concentration.  An increase in water-use
efficiency is a well documented response  to
CO2 enrichment, as discussed above.  If longer-
term experiments  support  the  premise that
increased water-use efficiency improves a tree's
drought resistance, then this response should
be incorporated into ecosystem models. Simi-
larly, N availability, as controlled by litter de-
composition,  is an important component  of
ecosystem models (Pastor and Post, 1988). It
has been suggested that CO2 enrichment could
alter the chemistry of leaf litter such that nutrient
turnover will be slower (Strain, 1985).  The
available data  (Norby et al.,  1986b) do not
support  this premise, but more work can  be
done in relatively  short-term  experiments  to
provide the necessary input for modeling the
long-term ecological response.

     Given the  potential importance of the di-
rect responses of forest trees to increasing CO2
and  the difficulty  in  projecting the long-term
responses from existing data, it is important that
CO2 enrichment experiments  be designed  to
provide data that  are relevant to longer-term
and ecological responses.

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    Models for Analysis of Vegetation  Responses to Global

                           Environmental Change

                                   William R. Emanuel
          Environmental Sciences Division, Oak Ridge National Laboratory, P.O. Box 2008, MS-6038
                           Oak Ridge, Tennessee 37831-6038, U.S.A.

                                    I. Colin Prentice
                          Institute of Ecological Botany, Uppsala University
                                  S-751 22 Uppsala, Sweden

                      Thomas M. Smith and Herman H. Shugart, Jr.
                     Department of Environmental Sciences, University of Virginia
                              Charlottesville, Virginia 22903,  U.S.A.

                                   Allen M. Solomon
                         International Institute for Applied Systems Analysis
                                  A-2361 Laxenburg, Austria
                Abstract

     The physiology of plants depends on tem-
perature and moisture, thus large-scale climatic
change can alter earth's vegetation. In turn,
vegetation responses  influence atmospheric
composition and climate.

     Maps of  classical relationships between
natural vegetation and climatic indices  under
alternate  climates suggest the sensitivity of
equilibrium vegetation  distribution to climatic
change. For example, 34 percent of the earth's
0.5* land cells are assigned different Holdridge
Life-Zone designations under temperature in-
creases simulated  for a doubling  of atmos-
pheric CO2 concentration. Although such exer-
cises clarify the relative sensitivity of different
types and regions and the scale of changes, the
approach cannot be used to analyze transients.
     Numerous variants of forest models that
track the birth, growth, and mortality of each
tree  on relatively small stands  simulate the
dynamics of a range of forest types in terms of
variables such as total biomass, species com-
position, and  leaf area reasonably well.  But
individual plants are usually not important in
larger scale applications. Models that describe
population changes according to plant types
without maintaining the state of each individual
can simulate most of the large-scale features of
vegetation dynamics.

     Stand level models can be applied to large-
scale problems  by generating  Monte Carlo
solutions in which the distributions of parameter
values reflect variability in environmental fac-
tors such as topography and soil characteris-
tics.  Random  disturbances, such as fire and
wind, can be incorporated as well. The solution

                                       251

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William R. Emanuel, I. Colin Prentice, Thomas M. Smith, Herman H. Shugart, Jr. and Allen M. Solomon
set reflects the combined influences of spatial
variability  in parameter  values, disturbance,
and variance induced by stochastic aspects of
the models.

               Introduction

     Terrestrial  vegetation  is  an  important
component of the global carbon cycle. There
are approximately 560 x 1015 g of carbon in land
plants; about 60 x 1015 g exchanged between
the atmosphere and terrestrial ecosystems each
year (Olson et al., 1983).  These exchanges
depend on temperature and moisture so that
climatic change from increasing greenhouse
gases - due in part to changes in terrestrial
pools - can alter  terrestrial storages  and ex-
changes to  feed  back on the global  biogeo-
chemical cycles.

     Environmental changes alter vegetation
by affecting cell-level processes that depend on
light, temperature, moisture, and nutrients; with
time, the effects extend to variations in commu-
nity characteristics, including species composi-
tion,  biomass, and  leaf profiles, and to  the
continental distributions of  biomes.   Atmos-
pheric general circulation models describe the
fast dynamics of  the climate system, the re-
sponse  of  circulation patterns to the boundary
conditions imposed by solar radiation, atmos-
pheric composition, and the instantaneous state
of the land and water surfaces. But we also
need to model slower components, including
the response of the vegetation cover and sur-
face  hydrology  to their boundary conditions:
soil characteristics and longer-term values of
atmospheric properties, such as mean air tem-
perature, precipitation, and net radiation.

     In this paper, we describe models for ana-
lyzing the equilibrium relationships  between
vegetation  and climate and  vegetation  re-
sponses to  environmental changes on  time
scales  from 10-1000 years.  We emphasize
climate, but most of the concepts  and  ap-
proaches  we present are pertinent to  other
global changes as well.

 Natural Processes of Vegetation Change

     As  plants  respond  to  environmental
change, competition for light and resources
influence reproduction, growth, and mortality to
different degrees, depending on each species'
characteristics. As a result, variations in spe-
cies composition, biomass, leaf area, and simi-
lar community variables are more complex than
the collected responses of individuals that do
not interact. There may be immediate effects
on annual production, but these are modified
later by changes in composition and community
structure. This adjustment process is similar to
secondary succession after disturbances such
as fire or harvest.

     Natural areas are mosaics of patches that
were disturbed at different times by fire, wind,
flood, disease, or similar events  (Noble and
Slatyer, 1978; White, 1979). Natural distur-
bance can quicken the response of vegetated
areas to climatic change (Davis and Botkin,
1985),  and  presumably, harvest  of wood  or
crops can have the same effect. Climaticchange
can alter disturbance regimes, e.g., warmer or
drier conditions can increase  fire frequency
causing forest to be replaced by prairie (Grimm,
1984).

     The availability of propagules for  local
recruitment  depends on  abundances in the
surrounding area,  and at  this  level, climatic
change can alter regional distributions of taxa.
Such changes are well documented for the past
20,000 years (Davis, 1981; Huntley and Birks,
1983; Webb, 1986; Webb,  1987).  Trees mi-
grated  with  remarkable speed in response to
Quaternary changes, but the time needed for
large-scale  spread and regional population
changes may be 1,000 years or more and can
presumably limit the rate of vegetation response
to rapid,  large climatic changes (Davis  et al.,
1986; Bennett, 1986; Davis, 1987).
 252

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                            Models for Analysis of Vegetation Responses to Global Environmental Change
    Vegetation and soil are tightly coupled
systems. Soil water holding capacity and nutri-
ent availability  in the soil-water solution influ-
ence primary production. Although some as-
pects of soil formation are slow enough to be
considered constant through plant community
changes, nutrient turnover  depends on  litter
characteristics  so that variations in species
composition can affect plant growth and further
alter composition (Pastor and Post, 1986). The
effects  of climatic change may be amplified
through this indirect circuit of influence (Pastor
and Post, 1988).

    Thus, in the face of climatic change, vege-
tation has a certain inertia (Smith, 1965), com-
prised  of several  components:   (1) the  time
needed for individual patches of vegetation to
adjust to climatic change when the available
flora is held constant, (2) time for the  spatial
mosaic of vegetation to adjust to climatically
induced changes  in frequencies of fire and
other natural hazards, and (3) the time required
for ecdysis.

        Equilibrium Relationships

    The natural, equilibrium distribution of
vegetation is similar to climate, and plant geog-
raphers use this correlation to relate vegetation
classes to climate (Holdridge, 1947; Box, 1981;
Lashof,  1987;  Woodward, 1987).  Sensitivity
tests of such models suggest bounds  on the
impacts of climatic change.

    Emanuel  et al.  (1985a,b) compared two
world maps of  Holdridge life zones: the first
derived from climate recorded by 7000 mete-
orological stations, the second with simulated
temperature increases for  atmospheric  CO2
concentration twice the model reference  con-
centration.  Lashof (1987) did similar exercises
with a vegetation-climate relationship derived
from Olson's world  map of ecosystem com-
plexes (Olson et al.,  1983) and meteorological
records. Although the transient responses would
be complex (Shugart  et al., 1986; Solomon,
1986), such tests indicate the sensitivity of the
asymptotic distributions toward which transients
eventually converge in the absence of distur-
bances not included in these equilibrium rela-
tionships.

     In this sensitivity test, the life-zone desig-
nations of 35 percent of the 0.5° mapping cells
change. The largest changes were at high
latitudes where simulated temperature increases
are largest and where narrow temperature  in-
tervals define Holdridge life zones. The extents
of boreal forests and tundra decrease 37% and
32% respectively.  Changes are along  major
vegetation boundaries and are more extensive
than  the uncertainty  in determining  these
boundaries within the Holdridge scheme.

     Such speculations indicate some of the
challenges agriculture and forestry may face
and bound the broad vegetation changes that
influence the global carbon cycle, climate, and
other earth systems. But environmental changes
due to human activities may be rapid compared
to the vegetation  dynamics responsible for
replacement of  forest  types.  Although the
sensitivity of the Holdridge scheme suggests
conversion of much of today's boreal forest to
temperate deciduous forest, this result does not
mean that there is likely to be a gradual, straight-
forward transition between the two forest types.

     Higher summer temperatures may stimu-
late the growth of  boreal conifers at first, but
higher wintertemperatures may be unfavorable
for the natural regeneration of  some of  these
taxa at their oceanic limits.   Beyond a certain
point, increased summer temperature will re-
duce growth rates again; such a warm climate
would probably be suitable for temperate trees,
but their recruitment will take time, so produc-
tion could fall before rising again toward the
high level characteristic of temperate forests.

           Community Models

     Various models describe vegetation tran-

                                        253

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William R. Emanuel, I. Colin Prentice, Thomas M. Smith, Herman H. Shugart, Jr. and Allen M. Solomon
sient responses from different viewpoints. For-
est stand growth and succession models (Botkin
et al., 1 972; Ek and Monserud,  1 981 ; Shugart,
1984) simulate changes based on species at-
tributes and tree interaction assumptions that
emphasize competition for light.  These rela-
tively new models borrow many  ideas from
forestry models (Munro, 1974).   Nonwoody
vegetation dynamics  can probably be treated
with similar descriptions, and although  these
models describe small landscape patches, they
simulate community phenomena with consider-
able generality and  use factors  to describe
environmental influences that can be evaluated
along gradients or to sample variability within
larger landscape units.

     Shugart (1984)  describes forest  stand
models and their application  in detail.  These
models simulate the birth, growth, and death of
every tree on a small  stand (800 m2). The size
of each tree is characterized by its diameter -
other dimensions are allometrically related to
diameter, and variables such as biomass can
be derived from diameter using empirical func-
tions.

     To advance a simulation through one-year
steps,  a diameter increment is calculated for
each tree:
                       D2-b D3))
      DmHm(274.0D + 3b2D  -4b3D

D is diameter at 1 37 cm high. Leaf area la  is a
function of diameter
                  l=adb
(2)
The constants a and b are derived from relation-
ships developed by Sollins et al. (1973):

                a= 1.6069x10"
                b = 2.129.

r is a growth rate, and Dm and Hm are maximum

 254
         diameter and height.  These three parameters
         are specific to each tree species. The species
         specific  functions  g^)   and g2(GD), de-
         scribed below, express dependence  on light
         and a heat sum GD respectively.  Additional
         response functions may be included  to treat
         moisture, nutrient availability, and other envi-
         ronmental conditions.
             Height is related to diameter by the func-
         tion:
                        b,D-b,D2
                                     (3)
         where again the parameters b2 and b3 are spe-
         cies specific. If maximum height is assumed to
         occur at maximum diameter,
               b, = 2(Hm - 137)/Dm
         and
                                     (4)
                                              (5)
             Light intensity decreases below the top of
         the  plant canopy  because of shading.  This
         affects growth through the light response func-
         tion  g^)   in the diameter-increment equa-
         tion, Eq. (1), and may affect other processes,
         such as recruitment. Shading is the most impor-
         tant interaction between trees in stand models.
         Light extinction is described  by Beer's Law
         (e.g., Miller, 1981): at height  H, intensity § is
                                                                   -k f l(h)*
                                                                                   (6)
where   0 is the intensity at the top of the
canopy, and k is a  constant light extinction
coefficient. I,(H) is the leaf-area index (leaf area/
patch size) at height H.

     Leaf area is directly related to stem diame-
ter and considered to be concentrated at the top
of the stem, thus the total leaf area of each tree
shades all tree below. Stand models treat a plot
of definite size that is constrained by the as-
sumption that light availability is independent of

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                            Models for Analysis of Vegetation Responses to Global Environmental Change
horizontal position (Shugart and West, 1979).
Shugart and West (1977)  simulated gap  dy-
namics in an east Tennessee temperate forest
on a 833 m2 plot.  But in boreal forests, tree
crowns are narrow, sun angles are low, and the
gap created by the death of a single tree is insig-
nificant. Leemans and Prentice (1987) found
that to simulate gap processes, models of these
forests must be able to treat 1 000 m2 gaps for
establishment of  light-demanding  species
(Whitmore,  1982).

     The dependence of diameter increment
on light intensity is expressed by the response
function g((). A typical light response function

                                     (7)
The parameters c,, c2,and c3 reflect the shade
tolerance of each species.

     Temperature during the growing season is
summarized by a growing degree-days index:
             365
        GD=I((T.-TB).T>TB),    (8)
              1=1
where T  is daily temperature.  TB is a base
temperature (e.g., 14.4°C or 40T). This index
affects diameter increment through the response
function g2(GD):
                     mm   max
            4(GD-GD)(GD  -GD
                    max    m,n
                                   -  (9)
        max       mm
where GD and  GD  are maximum and mini-
mum values of the growing degree-days index
associated with each species' range.

    Additional environmental effects can be
described by  similar response functions g;(.)
multiplying growth increment, Eq. (1), to reflect
deviations from best conditions. Winter cold is
indexed by the mean temperature of the coldest
month; growth is suppressed if it is  too cold.
Drought  is described by an estimate  of the
proportion of the growing season with subcriti-
cal soil moisture.  Growth is reduced to zero if
drought index is less than or equal to the arid
range limit for each species, determined from
distribution maps.  Bonan's (1988) boreal forest
model considers the response of each species
to permafrost.   Pastor and Post (1986) con-
strain growth by nitrogen availability.

     The  environmental  response functions
depend on indices (e.g., drought index) that in
turn  are functions of environmental variables
such as temperature or soil moisture. Some of
these, such  as temperature, are specified di-
rectly or treated as random variables with speci-
fied distributions. Others, such as soil moisture,
are functions of additional variables including
perhaps the status of model  vegetation, and
these relationships are described by environ-
mental submodels whose state variables may
depend on vegetation variables.

     Randomly selected trees are eliminated
from the model stand on each time step. The
probability that a tree dies is much higher if it is
suppressed  than  if it is growing  well.   The
probability of mortality for all trees is such that
fewer than 2 percent of the recruits  of each
species reach  maximum  age.  If the annual
diameter increment is below a critical value for
three years running, a tree is considered slow
growing and is assigned 1 percent probability of
surviving the next  ten years.

     Disturbances such as fire and wind also
affect mortality (Mielke et al., 1978; Shugart and
Noble,  1981; Doyle, 1981).  Their occurrence
and intensity are usually random variables and
may depend on environmental conditions such
as temperature or moisture.  These relation-
ships are described by additional modules when
a model is assembled for a  region where they
are important. Mortality associated with distur-
bance can be immediate - trees are removed
from the model stand in the year disturbance
occurs.  In other cases, the probability of death
may be increased according to species' toler-
ance.  Disturbance can affect growth by de-
                                                                                     255

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William R. Emanuel, I. Colin Prentice, Thomas M. Smith, Herman H. Shugart, Jr. and Allen M. Solomon
creasing diameter increment.

     Random numbers of new trees are re-
cruited annually as saplings for each species
whose regeneration requirements - including
light at the forest floor, mineral soil exposure,
and leaf-litter depth - are met by environmental
and  vegetation status.   The persistence of
species is assured  by an assumed constant
propagule bath (Whittaker and Levin, 1977).

     Forest models based on the Botkin formu-
lation are uniquely  successful  in  describing
stand dynamics on  time  scales ranging from
decades to  centuries.  But a model that de-
scribes population changes for each species or
even plant types, as opposed to treating indi-
viduals, may be satisfactory for most continen-
tal- to global-scale applications. The computa-
tional requirements of population based models
can be substantially less than those of models
that track individuals.

     One possibility is to describe the state of
plant communities by the number of individuals
of each species or plant type in each of a set of
arbitrary width layers dividing space above the
landscape unit supporting the vegetation. Again,
the patch is sufficiently small so that light extinc-
tion can be assumed to be horizontally homoge-
neous.

     Advancement through height layers is a
stochastic process.  The probability of transfer
to higher layers is derived from a mean  height
increment of the population  of each plant type,
assumed to be uniformly distributed through
each layer. The increment depends on current
leaf size as  well as environmental conditions
including available light, air temperature, and
soil moisture. The structural emphasis on height
and the assumption of homogeneity within height
layers for each plant type or species are condu-
cive  to  incorporating  plant types other than
trees for which a growth description based on
individuals is unnatural.
           Large-Scale Analysis

     Continental-scale simulations of vegeta-
tion dynamics can be generated from large sets
of patch model solutions. The region of interest
is subdivided.  A uniform grid in spherical coor-
dinates is convenient, but arbitrary polygons
can be used.   Resolutions of about 0.5° are
reasonable (Olson et al., 1983; Emanuel et al.,
1985); such cells are approximately 50 km on a
side at the equator.

     A set of patch  model solutions is gener-
ated for each of these smaller units with appro-
priately distributed random environmental vari-
ables.  Disturbance frequency and intensity are
also specified-they  may depend on environ-
mental characteristics such as temperature or
soil moisture as well as the status of vegetation
(Kercher and Axelrod, 1984).  The solution set
reflects specified  variances  in environmental
variables, including disturbance frequency and
intensity, but is complicated  by the stochastic
processes simulated by the patch model.

     For land  units  small  enough  to support
reasonable resolution, the distributions of basic
environmental variables, such as temperature,
rainfall, soil type,  and soil texture, cannot be
derived from currently available observations.
Rather, the distribution of these variables must
be based on morphologic features with topog-
raphy as the most important.

     There are models for  calculating solar
intensity at a specified location, elevation, slope,
aspect, and time  (Swift, 1976;  Bonan, 1988;
Kutzbach and Gallimore, 1988). Although basic
principles are understood for other relations, for
example temperature change as a function of
elevation, these have not yet been expressed
systematically in schemes suitable for incorpo-
ration in global vegetation models.  It is impor-
tant to note that absolute relationships are not
required; rather we need to derive the distribu-
tions of environmental variables from underly-
ing variability in topography and other structural
 256

-------
                              Models for Analysis of Vegetation Responses to Global Environmental Change
characteristics.
                Conclusion
     Those wishing to  study interactions be-
tween climate and ecosystems must reconcile
the different  spatial and temporal scales of
atmospheric  and ecological processes.  The
design of atmospheric general circulation models
reflects the fast horizontal transport and short
memory of the atmosphere   integrations are
performed at  intervals of less than an hour and
at grid points  200 km, or more, apart.  Vegeta-
tion models are solved on yearly intervals but on
patches about 30 m across.  These differences
reflect the  inertia of vegetation  and  the fine
spatial scales at  which vegetation processes
act compared to those determining weather.

     There are general  circulation models that
allow a prescribed vegetation, in terms of height,
structure,  phenology,  rooting  depth,  etc., to
interact dynamically with the atmosphere (Dick-
inson, 1984;  Sellers et al.,  1986).  Physical
vegetation characteristics, such as albedo, leaf-
area index, and stomatal aperture, vary  diur-
nally and  seasonally in response to atmos-
pheric variables and, in turn, affect exchanges
of energy, water, and momentum.  The task of
a global vegetation  model  is to  simulate the
slower processes by which primary vegetation
characteristics - taken  as constant in climate
models  - are transformed  through  time  by
changes in climate.

     We've described  the  components  of a
scheme for simulating global transient responses
of natural vegetation to climatic change.  The
approach is based on a core description that in
our experience simulates the important proc-
esses reasonably well.  Substantial data are
required to estimate model parameters for world-
scale studies, but these needs  are realistic.
Simulations  of vegetation  responses within
hypothetical environments can make substan-
tial  contributions  toward  understanding the
implications and  impacts of climatic  change.
Adequate  data are available  now to  support
realistic continental-scale simulations for most
of the world's land areas, but data limitations
always restrict the interpretation of such large-
scale efforts to some degree.  Our ability to
interpret realistic model studies can be  ex-
tended substantially by hypothetical  simula-
tions.

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   simulated forest stands. Forest Science25:120-122.

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                                                                                                    259

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Brief Reports

-------
            Geographic Information Systems as a Tool in Regional Mapping
                           and Environmental Assessment

                  Gary D. Bishop, William G. Campbell, Barry P. Rochelle
                                  Northrop Services, Inc.

                                  M. Bobbins Church
                            U.S. Environmental Protection Agency

                         Environmental Research Laboratory - Corvallis
                            U.S. Environmental Protection Agency
                                    Corvallis, Oregon
    The  U.S.  Environmental  Protection
Agency's (USEPA)  Direct/Delayed Response
Project (DDRP) is  examining  the  following
question: "What is the future long term chemical
response of selected surface waters in the U.S.
to acidic deposition?" To answer this question,
the USEPA, in cooperation with other Federal
agencies and extramural  investigators, com-
piled and/or collected a variety of environmental
data encompassing selected  regions of con-
cern within the eastern U.S. We chose an ARC/
INFO* Geographic Information System (GIS)
as an appropriate tool for compilation, manipu-
lation, and displaying of data and results ob-
tained in the DDRP.  GIS-based graphic output
includes locational maps, contour maps, circle
andthiessen maps, and choropleth maps. This
output aids researchers in many aspects of the
DDRP including locational and logistical sup-
port, analyses, and communication of results.
In particular, the interactive environment of GIS
graphics allows researchers to examine numer-
ous 'what if scenarios. These GIS-generated
datasets and maps are being used in a variety
of procedures and predictive  models to charac-
terize the chemical response of surface waters
in the regions of concern.

     'Mention of brand names or commercial
products does not constitute endorsement or
recommendation for use.
                                                                                   263

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Air Pollution Effects on Vegetation
                          Fluoride Emission and Tree Growth

                           H. Bunce, Reid Collins & Associates
                                        L. Jozsa
                                   Forintek Canada Corp.
     Fluoride emissions from the aluminum    growth near the smelter, but satisfactory natural
smelter at Kitimat, B.C., Canada, have been    regeneration has taken place throughout the
affecting the adjacent forests  since 1954.    same area.  The level of fluoride emission has
Continuing studies of this effect have been    dropped as emission control technology has
conducted since 1973. Fluoride emission of the    improved markedly over the last decade and
aluminum smelter at Kitimat has reduced forest    trees have responded with increased growth.
 264

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                                                                             Brief Reports
     Geographic Information Systems as a Tool in Watershed Characterization for
                         Regional Environmental Assessment

                W.G. Campbell, C.G. Kaffke, D.C. Mortenson, G.D. Bishop,
                            M.R. Church and D.A. Lammers
                                  Northrop Services, Inc.
                             US Environmental Protection Agency
                                    US Forest Service
    The Direct/Delayed  Response  Project
examines the following question: "What is the
future long term chemical response of surface
waters to continued acidic deposition?" The
USEPA contracted  soil scientists to map soils,
vegetation, geology, and depth-to-bedrock on
145 watersheds in the northeast and 35 water-
sheds in the Southern Blue Ridge  Province.
These maps were digitized into an ARC/INFO
Geographic Information System (GIS) and are
currently being used to characterize watersheds
on both a per-watershed and regional basis.
Characterization involves a  variety  of tasks
including:  characterization of individual layers,
aggregation of mapping units within and be-
tween layers, and identification of mapping units
in certain proximities of the study lake or stream
reach.  GIS-generated datasets and/or maps,
based  on  these characterizations, are being
used in a variety of procedures and predictive
models to assess the influence of key water-
shed variables on surface water chemistry.
                                                                                    265

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Air Pollution Effects on Vegetation
        Quality Assurance Guidelines for Dendrochronological Research Projects

                                     Steven P  Cline
                                 NSI Technology Services, Inc.
                               EPA Environmental Research Lab
                                      Corvallis, Oregon
     A properly designed Quality  Assurance
(QA)  program should perform two functions.
First it should provide benefits to each research
project, for example, a system of activities by
which a set of standard operating procedures is
selected, a knowledge of errors due to sample
processing is accumulated, and  an error-free
data set is produced for analysis. Second, a QA
program  should provide the data  users  with
specialized information for evaluating the level
of certainty of scientific results that may be used
to formulate environmental policy. This second
function can be accomplished only if each proj-
ect conducts proper QA activities and docu-
ments them thoroughly.

     This poster presents guidelines for con-
ducting and documenting QA activities in den-
drochronological research projects. Good use
of these  guidelines is illustrated with selected
examples from projects funded by the Western
Conifers  Research Cooperative of the Forest
Response Program.  The work of L. Brubaker,
D. Graybill, and D. Peterson and their staffs is
acknowledged.
 266

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                                                                             Brief Reports
               Mapping of Soils on Watersheds Selected to Represent a
                           Region of Environmental Concern

                        J. A. Ferwerda, M. R. Church and J. J. Lee,
                            D. L. Stevens and D. A. Lammers
                             US Environmental Protection Agency
                          East Oregon State College, US Forest Service
    Watersheds were selected to statistically
represent a region of concern in which to predict
how many surface water systems will become
acidic due to acidic deposition, and on what time
scale. Regional soil surveys were conducted to
provide information on the occurrence of soils
and other characteristics on these watersheds.
Soils were mapped at second order intensity
and a scale of 1:24,000. Soils across several
states were  mapped and  correlated to  one
unified legend so that soil classes  could  be
characterized for the region.  The  mapping
design provided a database that described the
spatial distribution of soils and other watershed
characteristics within a watershed, correlated
map unit composition and soils within the  re-
gion, and allowed for extrapolation of results
across the region of concern.  All  mapped
information was entered on a geographic infor-
mation system for retrieval and analyses.
                                                                                     267

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Air Pollution Effects on Vegetation
                Free Radical Adducts of Chloroplast and Nuclear DNA in
                           Ozone and UV-B Exposed Plants1

                         R.A. Floyd, M.S. West and G.A. Llewellyn
                            Oklahoma Medical Research Foundation
                                 Oklahoma City, Oklahoma
                                          and
                 R.A. Floyd, G.A. Llewellyn, W.E. Hogsett, and D.T. Tingey
                          Corvallis Environmental Research Laboratory
                             US Environmental Protection Agency
                                     Corvallis, Oregon
     Hydroxyl free radicals react with DNA to
form several products, one of which is 8-hydrox-
yguanine.  Enzymatic digests of DNA contain
the altered nucleoside, 8-hydroxy-2-deoxygua-
nosine  (8-OHdG),  which can  be  precisely
measured by HPLC electrochemical detection.
Using this method, we found that the 8-OHdG
content of chloroplast DNA is greater in bush
beans and peas grown under a variety of ozone
exposures known to induce plant injury. Expo-
sure of illuminated isolated chloroplasts to ozone
caused nearly a 7-fold increase in 8-OHdG in
the chloroplast DNA over the non-ozone ex-
posed controls.  Isolated  DNA  solubilized in
buffer and exposed to ozone did not yield higher
levels of 8-OHdG, though the ozone reacted
with DNA perse as assessed by absorbance at
260nm.  Currently, we are investigating ozone-
and UV-B-related elevation of 8-OHdG in coni-
fer, aspen and rice chloroplast DNA and deter-
mining if there is nucleotide specificity in ozone-
or UV-B-induced damage to chloroplast DNA.
'Research supported in part by EPA grants CR-812710 and R814198.

 268

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                                                                             Brief Reports
                   An Analysis of the Reliability of DBH Measurement

                        T. Gregoire, N.S. Nichols and S.M. Zedaker
                        Department of Forestry, Virginia Polytechnic Institute
                                    Blacksburg, Virginia
    Defensible assessment of air pollution
impacts on forests depend upon precise and
accurate measures of tree growth  and yield.
Diameter breast height (DBH) is a fundamental
measure of tree size and, almost universally,
DBH measurements are taken with either di-
ameter (actually girth) tapes or with mechanical
calipers. Unfortunately, little is known about the
absolute and differential errors of measurement
associated with these techniques. Much of the
difficulty derives from the ill-defined nature of
the diameter of a noncircular cross-section such
asatreestem. Therefore, it is extremely difficult
to gauge the quality and comparability of DBH
data between investigations and between tech-
niques,  especially when  the  likely and con-
founding influence of operator error is recog-
nized.

    The size of these errors may be critical in
differentiating between changes due to meas-
urement error and possibly subtle forest growth
changes due to  pollution exposures.  In this
study, variance component models are pro-
posed to quantify the  variability in basal area
measurements in order to determine the most
reliable  means of taking repeated DBH meas-
urements.
                                                                                     269

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Air Pollution Effects on Vegetation
  Relationships Among Mapped Watershed Physical Characteristics and Surface Water
                  Chemistry: A Regional Environmental Assessment

                             M. G. Johnson and D. L. Cassell
                                   Northrop Services, Inc.

                                     D. A. Lammers
                                     US Forest Service

                                     M. R. Church
                             US Environmental Protection Agency

                                      R. S. Turner
                                Oak Ridge National Laboratory
     Bivariate and multivariate statistical analy-
ses were  used to evaluate the relationships
among mapped watershed physical character-
istics and surface water chemistry of 122 drain-
age lake systems in the Northeastern U.S. and
35 drainage stream systems in the Southern
Blue Ridge Province.  Soils, vegetation, bed-
rock geology, depth-to-bedrock, wetlands, and
land use were mapped on these watersheds at
a scale of 1:24,000 with a six acre minimum
delineation. The areal extent of these attributes
on the watersheds and within close proximity of
the subtending surface waters were determined
using GIS ARC/INFO. The proportion of these
attributes on the respective drainages were
used as regressors in multivariate regression
models.  Using various model selection tech-
niques, models were developed that describe
surface water ANC, sum of base cations, pH,
sulfate, DOC, and silica. Watershed attributes
explain a considerable amount of variation in
the surface water variables. However, in the
Northeast, deposition is the greatest source of
sulfate and consequently explains most of the
varieties in sulfate across that region.
 270

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                                                                             Brief Reports
                          Direct Reading X-ray Densitometer

                             L. A. Jozsa and R. S. Myronuk
                                   Forintek Canada Corp.
    X-ray densitometry methods were  pio-
neered in France by Polge in the early 1960's.
By 1980, there were about 30 laboratories in 18
countries engaged in densitometry work.  At
Forintek, a computerized X-ray film densitom-
etry system has been in operation since 1971.
Recently, a Direct Reading X-ray Densitometer
(DRXRD) was developed to  make  tree-ring
measurements more cost efficient. Streamlin-
ing sample preparation was the first priority to
make X-ray densitometry more efficient. To be
cost-effective and to ensure reliability the de-
sign incorporated off-the-shelf  items wherever
possible. A twin-blade sample preparation saw
was built. It is capable of cutting unmounted
5mm diameter increment cores to  a uniform
1.5mm thickness. DRXRD offers rapid meas-
urement  of ring width and ring density.  The
detail in which annual rings can be  evaluated
permits assessment of heterogeneity in wood
density within individual annual rings. Such in-
formation can be correlated with environmental
conditions, silvicultural practices, air pollution,
strength properties, tree growth and  other vari-
ables to  a greater degree  than gross wood
density measurements.
                                                                                     271

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Air Pollution Effects on Vegetation
        Basis for Using "C/12C Ratios in Tree Rings for Retrospective Monitoring of
                               Local/Regional Air Pollution

                                     Steven W. Leavitt
                       Department of Biology, University of Wisconsin-Parkside
                                     Kenosha, Wisconsin
     Stable-carbon isotope fractionation mod-
els provide a  guide to  how pollutants  may
influence 13C/12C ratios (513C) in plants. Gener-
ally, if a pollutant reduces the rate of carbon
fixation and/or increases stomatal conductance,
lower 13/C12C ratios may be expected, and vice
versa.  On the basis of reported effects of
pollutants on various plants, the following may
be expected: for sulfur dioxide, increased fixa-
tion if nutritive but decreased otherwise and
increased stomatal conductance at high humid-
ity; for carbon dioxide, increased fixation if nutri-
tive and decreased conductance; for ozone, de-
creased fixation  with chlorosis and  reduced
conductance; for nitrogen dioxide, reduced fixa-
tion and uncertain effects on conductance. In
principle, the fixation conductance effects of
CO2 are reinforcing to produce elevated 13C/12C
ratios, and the effects of SO2 are reinforcing to
induce reduced 13C/12C ratios.  Previously re-
ported growth chamber results with SO2, how-
ever,  suggest enzyme injury  may inhibit the
normal selectivity for 12C over  13C.  A field test
study to prove the value of tree rings for retro-
spective monitoring should (1) preferably be at
a site which has experienced fumigation primar-
ily from only one of these pollutants, (2) pool
tree rings from several radii of each tree cored
at the affected site and control site to ensure a
representative  sample, and (3) analyze the
cellulose component of dendrochronologically-
dated tree rings.
 272

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                                                                            Brief Reports
         Grouping Soils Mapped Across a Region into Classes for Sampling for
                         Regional Environmental Assessment

                  J. Lee, K. Thornton, D. Lammers, D. Stevens, S. Buol
                             US Environmental Protection Agency
                                  FTN, US Forest Service
                                 East Oregon State College
                               North Carolina State University
    A primary objective of the Direct/Delayed
Response  Project is to estimate how many
lakes and streams within the Northeast (NE)
and the Southern Blue Ridge Province (SBRP)
will become acidic due to current or  altered
levels of acidic deposition, and  on what time
scales.  Because many more soils than were
practical to sample were identified during  the
mapping phase of the soil survey implemented
in support of this objective (about 350  named
soil components on 145 watersheds in the NE,
and about 300 on 35 SBRP  watersheds),  the
soils  were  grouped into sampling  classes of
soils that are thought to be similar with respect
to those characteristics  that might be more
important for predicting the response of lakes
and  streams to continued acidic deposition.
The process of grouping soils was based on the
accumulated knowledge and experience of the
soil scientists and the insights of the watershed
modelers. The result was an acidic deposition
hierarchical soil classification system for each
region.  The 38 NE sampling classes followed
soil taxonomy fairly closely; this was not true for
the 12 SBRP classes.
                                                                                   273

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Air Pollution Effects on Vegetation
             Estimates of Tree Crown Areal Histories by Tree Ring Analysis:
                               Use in Throughfall Studies

                                     T. D. Leininger
                              Forest Fire Lab, Riverside, California

                                      W. E. Winner
                            Oregon State  University, Corvallis, Oregon
     Northern red oak crown areas were esti-
mated for two forested sites by  a two step
procedure using  annual growth ring chronolo-
gies and published regression equations. The
usefulness of crown area estimates in through-
fall studies was demonstrated by applying nutri-
ent ion exchange data collected beneath north-
ern red oak crowns in 1984 to 1982, and 1930
crown area  estimates.  Smaller nutrient ion
estimates  in 1930 were due to smaller crown
area estimates. Application of these techniques
for estimating historical ion exchange chemistry
in forest canopies would require modifications
to increase accuracy.  Competition and stand
dynamics need to be considered, and regres-
sion equations should be validated.  Accurate
estimates of past ion exchanges  in crowns
require knowledge of past trends in atmos-
pheric chemistry. A better understanding of the
relationship between throughfall chemistry and
chemical and physical variables in canopies is
also needed.
 274

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                                                                              Brief Reports
                   Regional Predictions of Surface Water Acidification

                                     Leon H. Leigel'
                      USDA Forest Service, Pacific Northwest Research Station
                                     Corvallis, Oregon

                                   M. Robbins Church
                             U.S. Environmental Protection Agency
                                     Corvallis, Oregon
     Recognition of acidic  deposition as  an
environmental issue led to the formulation of an
important policy question: What is the regional
prognosis for acidification of surface waters?
The Direct/Delayed Response Project (DDRP)
was developed to provide a scientific basis for
answering this question. A statistically repre-
sentative set of 260  lake and stream water-
sheds was selected and studied in three broad
geographic regions covering 14 states. Within
the statistical framework, the watershed-spe-
cific results are extrapolated to each region and
relationships  are evaluated between surface
water chemistry and watershed characteristics.

     To achieve its objectives, the DDRP  re-
quired  a multi-regional terrestrial data base.
Soil mapping and soil sampling on each water-
shed provide information about existing soils,
forest vegetation and land use, bedrock geol-
ogy, and depth-to-bedrock. Geographic Infor-
mation System (GIS) and laboratory chemical
analyses are used  to evaluate which soil or
other watershed characteristics determine the
long-term response  of surface waters to acidic
deposition. Procedures of the USDA National
Cooperative Soil Survey were incorporated to
promote regional consistency and representa-
tiveness.  A rigorous Quality Assurance and
Quality Control program was followed to pro-
mote and document product quality.  Protocols
and  procedures used in the  broad DDRP soil
survey have important implications for develop-
ing future programs concerning global  climate
change  and wetland preservation.

'Detailed to the U.S. Environmental Protection
Agency, Corvallis, Oregon.
                                                                                      275

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Air Pollution Effects on Vegetation
      Biochemical Responses of Pinus sylvestris and Picea abies to Dust Pollution

                                       M. Mandra
                           Tallinn Botanical Gardens, Estonian, S.S.R.
                                    Academy of Sciences
     Cement dust (CD) can contain a complex
of substances not especially toxic for plants, but
that have pH higher than 12.7. Dust fallout at a
distance of about 1 km from the CD emission
centre, where our field experiments were car-
ried out, ranged from 460 to 830 g/m2 annually.
High Ca and K concentrations in the CD causes
alkalinization of the soil (pH 8.1) and precipita-
tion (rain from 7.6 to 9.1; snow, 10.4 to 11.4).
CD also causes changes in the cation and anion
content of soil and precipitation as well.

     Moisture interacting with CD forms crusts
on vegetative organs, thus, creating different
light,  temperature  and water regimes  in the
tissues.  This causes metabolic deviations in
dusted plants. In dusted needles of P. sylvestris,
the content of chlorophylls and Caroline is de-
creased and winter maximum of Caroline ar-
rives earlier and more rapidly than in controls.
In dusted P. abies needles, Caroline needles
are low throughout the year.

     Bolh CD and fuel  combuslion  products
from cement plants contain sulphur subslances.
This is Ihe direcl cause of Ihe increase of free
SH-groups, SO4* and total  S in plant tissues.
The variations  of the ratio of SO42/SH1  may
provide a basis for interpretation of alterations
in S metabolism.  The greatest deviations are
indicated in mineral composition of plants under
CD pollution.

     In  most cases,  visible injuries on the
needles were not observed; however, inhibition
of radial growth and decrease in  thickness of
needles was observed in P. sylvestris.
 276

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                                                                           Brief Reports
   A Comparative Study of X-ray Densitometry and Image Analysis for Measuring the
                         Characteristics of Narrow Tree Rings

                        W.K. Park, F.W. Telewski and J.M. Burns
                      Laboratory of Tree-Ring Research, University of Arizona
                                    Tucson, Arizona
    A study was conducted to determine the
relationship between annual variations in maxi-
mum latewood  density,  ring width and  the
maximum percent cell wall area present in the
latewood of narrow and wide growth rings. The
material analyzed represents a tree-ring series
across the sapwood-heart wood boundary from
Pinus ponderosa var.  arizonica from New
Mexico.  Variations in measurements obtained
by the different analytical procedures within and
between specimen indicate image analysis is
the most precise  method for narrow growth
rings.  However, the sample  analyzed in this
study, which was obtained from a dry site, does
not have high sensitivity (0.067) compared to
ring width (0.469) or even maximum latewood
density (0.124). The maximum latewood den-
sity is highly correlated with the maximum per-
cent cell wall area present in the latewood with
a R2 = 0.78.
                                                                                   277

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Air Pollution Effects on Vegetation
               Modifications of SO2 Injury by Biological Active Substances

                                     L.A. Popovicheva
                     Central Republic Botanic Garden UKSSR Academy of Science
                            UL Timiryazevskaya 1, Kiev 252014, USSR

                             M.V. Kurek and Y.B. Shevchenko
                           Institute Physics UKSSR Academy of Science
                            Prospect Science 46, Kiev 252028, USSR
     Sulfur dioxide (SO2) is one  of the most
widespread air pollutants affecting plants.  A
plant's response to this gas, however, depends
on gas concentration and duration  of exposure.
Modification of the dose dependence response
of pea plants to gas stability modifiers-ascorbic
acid, MgCI2, CaCI2 and DMSO-were observed
and characterized by S-form curves.

     The  results of these investigations con-
firmed our assumptions that lipids are one of the
possible targets. Presence of liquid crystallized
lipids and intensification of lipids peroxide oxi-
dation related directly to  increased pollutant
concentration. Chemical stability modificators
were  observed to reduce formation of liquid
crystallized lipids as well as the level of lipid
peroxide oxidation.  These data indicate that
antioxidation effects play a definite role in the
protection mechanism provided by ascorbic
acid, MgCI2 and CaCI2; however, DMSO action
is  more complex and is evidently  related  to
changes in the membrane matrix. Many things
are not yet clear and this problem requires new
investigations.
  278

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                                                                              Brief Reports
            Chemical Analysis of Field-moist vs Air-dried Forest Soil Samples
                                      W.P. Robarge
                                 Department of Soil Sciences
                                North Carolina State University
    The purpose of this study was to quantify
the differences, if any, between field-moist and
air-dried  soil  samples, as a function of soil
horizon, using standard analytical procedures.
Soil samples were  collected from six major
research sites  in  the Spruce-Fir Research
Cooperative.  Samples  were split into those
maintained at field-moisture content and those
air-dried prior to analysis. Fifty-five soil hori-
zons were represented in the study.
     A preliminary summary of pH (water) and
exchangeable calcium are presented.  Within
sample variance for soil pH was very small; av-
erage standard deviation (wet and dry samples)
for five replicates was 0.03 pH units.  This
suggests that the soils were mixed.  Differences
between soil samples kept field-moist and those
air-dried are apparent, although all 55 horizons
have not been analyzed and data has not been
fully  validated.  For this reason, no statistical
analyses are presented.
                                                                                      279

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Air Pollution Effects on Vegetation
           Sulfate Adsorption Characteristics of Soils in the Northeastern U.S.

                               P.W. Shaffer and  D.L. Cassell
                                    Northrop Services, Inc.

                                     D.L. Stevens, Jr.
                                  East Oregon State College

                                       M.R. Church
                               US Environmental Protection Agency
     Sulfate is the dominant anion  in acidic
deposition  and the principal mobile anion in
many surface waters; thus, sulfate  retention
can be an important process in delaying or pre-
venting acidification of surface waters. As part
of an EPA project to predict future surface water
acidification, soils were mapped and sampled in
145 lake watersheds in the  Northeastern U.S.;
water and phosphate extractabie sulfate pools
and additional sulfate retention capacity (based
on nonlinear adsorption isotherms) were meas-
ured in ca 1800 soils sampled in these water-
sheds.  Data from  individual soils were ana-
lyzed to define relationships between soil and
surface water sulfur parameters.  Data will  be
presented summarizing statistical relationships
between soil sulfate data  (sulfate pools and
derived isotherm parameters) and lake sulfate
variables (concentration and input-output budget
status).  Predictions of future changes in soil
and surface water sulfate (concentration, time
to steady state sulfur budget) will also be pre-
sented, based on  use of adsorption isotherm
and deposition data with a deterministic sulfate
adsorption model.
 280

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                                                                             Brief Reports
    Aggregation of Soil Chemical and Physical Data for Regional Assessment of the
               Relationship Between Soils and Surface Water Chemistry

                      D. L Stevens, M. G. Johnson, and R. S. Turner
                          East Oregon State College, Northrop Services,
                              and Oak Ridge National Laboratory
    The Direct/Delayed Response Project was
initiated by the USEPA to study the relationship
between watershed soil properties and surface
water chemistry and to make regional predic-
tions about the future surface water chemistry.
The data for the project was obtained from 145
lake watersheds in the Northeast U.S. and 39
stream watersheds in the Southern Blue Ridge
Province. The soils on these watersheds were
mapped and  related soil components  were
grouped into classes for sampling.  The soil
samples were aggregated to a watershed level
quantity in a manner such the characteristics of
each watershed were preserved. The aggrega-
tion used differential weighting of the soil classes
occurring  on  a watershed, with the weights
based on horizon thickness, soil bulk density,
soil hydrologic group, soil depth, position on the
landscape, or proximity to surface  water.  A
variety of aggregation  models were  investi-
gated; the selected method optimized the linear
relationship between watershed soil and physi-
cal properties and surface water chemistry.
                                                                                    281

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Air Pollution Effects on Vegetation
                 Sampling Design for a Region Based on Soils Mapped

                K. Thornton, D. Stevens, J. Lee, D. Coffey, and D. Lammers
                               FTN, East Oregon Slate College,
                    US Environmental Protection Agency, NSi, US Forest Service
     A primary objective of the Direct/Delayed
Response Project (DDRP) is to estimate how
many lakes within the Northeast (NE) and the
Southern  Blue  Ridge Province (SBRP) will
become acidic due to current or altered levels of
acidic deposition, and on what time scales. The
objective of soil sampling within DDRP was to
determine the mean and variability of soil prop-
erties within sampling classes (38 in the NE, 12
in the SBRP) that had been designed to repre-
sent all soils found on the DDRP watersheds
(145 watersheds in the NE, 35 in the SBRP).
When the effects of the terrestrial component of
a watershed on a lake or stream are estimated,
it will be assumed that each soil has the proper-
ties of the sampling class in which it falls; this will
be done regardless of whether that specific soil
was sampled.  To obtain samples that collec-
tively represented regions and not  specific
watersheds, sampling sites for each class were
randomly selected on watersheds  that were
themselves randomly selected from those on
which the class  occurred.  Consistency of
sampling across regions  was maintained by
developing uniform protocols, by training crews
at regional workshops, and by a rigorous Qual-
ity Assurance/Quality Control program.
 282

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                                                                               Brief Reports
                Correlation and Control of Soil Mapping Across a Region

             J.W. Warner, H.J. Byrd, D.A. Lammers, J.J. Lee, and J.A. Ferwerda
                                       Naples, Florida
                            Raleigh, North Carolina, US Forest Service
                       US Environmental Protection Agency, Corvallis, Oregon
                             Ferwerda and Associates, Veazie, Maine
    Soils and other watershed characteristics
were mapped in a few months, across a multi-
state region, and by several soil scientists. One
uniform legend for the region was controlled by
a Regional Coordinator/Correlator (RCC).  A
preliminary regional soils legend was devel-
oped before field mapping began.  Mapping
quality was controlled through special training,
written mapping protocols, state  level field re-
view, and field review by the  RCC. Mapping
protocols specified mapping end  products and
responsibilities. Weekly telephone conference
calls were used to discuss problems, coordi-
nate work and track progress. The field review
process allowed for soil correlation on individual
watersheds and on watersheds within a state.
Soils and soil map units were correlated during
a regional workshop.  The mapping design and
correlation process provided a quality regional
soils database  for analyses of the  effects  of
acidic deposition on surface waters in the re-
gion.
                                                                                       283

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Air Pollution Effects on Vegetation
                      Dynamic Standardization of Tree-ring Species

                                    William G. Warren
                               Department of Forest Management
                                   Oregon State University
                                           and
                                Environmental Protection Agency
                                     Corvallis, Oregon
     A cumulative sum procedure, commonly
used in  industrial quality control, has  been
adapted to aid the fitting of a simplified version
of the compound growth function along the lines
suggested by Warren (Tree Ring Bulletin 40
(1980)35:44).

     The parameters of the function aF>exp (-ct)
are estimated from the first few ring widths of a
series.  The  fit is projected to the next ring.
Consistency with the established trend is analo-
gous to an industrial process being "in control,"
departure from the  established trend, analo-
gous to the process being "out of control." If the
cumulative sum indicates an "out of control"
situation, the  projection is extended to the next
few rings to see if the condition persists or if the
cumulative sum quickly returns to its "in control"
level.  The  latter suggests that  the "out of
control" indication is simply a chance event
such as must, from time to time,  be expected. In
this case or when the projection is "in control,"
the parameters of the increment function are re-
estimated with the latest point included, and the
procedure  repeated.   If the "out of  control"
indication persists,  it is assumed that a real
change in the growth trend has occurred. The
fitting of the original function is terminated and
afresh function, of the same general form, fitted
from the estimated point of departure.  Several
goodness-of-fit checks are made on all fitted
segments. The same procedure can be applied
to any assumed form for the increment function.

     The procedure is modular and  can be
applied interactively with the  user overriding
"decisions" that he or she judges to be biologi-
cally unreasonable.  Its objective is to reveal
times at which the natural growth trend is af-
fected by endogenous or  exogenous distur-
bances. Also, it may reveal whether the reduc-
tions in growth rate experienced in recent times
are more rapid than those that occurred in the
past.
 284

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                                                                              Brief Reports
                 Biological Markers of Environmental Contamination as
                   Predictors of Human Health and Ecological Effects

               J. F McCarthy, S. M. Adams, B. D. Jiminez, and L. R. Shugart
                               Environmental Sciences Division
                                Oak Ridge National Laboratory
                                   Oak Ridge, Tennessee
    The effect of environmental contamination
on human health and ecological integrity is a
topic of increasing concern.  Unfortunately, a
large gap exists in capabilities to either quantify
exposure to chemical and physical agents in the
environment, or to assess the biological signifi-
cance of such exposure. Exposure cannot be
readily quantified by measuring body burden of
contaminants because many deleterious agents
do not bioaccumulate, but are rapidly metabo-
lized.  Furthermore, the relation between body
burden and toxic response is complex and not
fully understood.  Assessing the significance of
exposure to complex mixtures of chemicals, the
most realistic environmental scenario, is even
more problematic.

    Our approach to quantifying exposure and
its potential  impact is  to  monitor biological
endpoints in feral animals as indicators of ad-
verse effects. The organisms function as inte-
grators of exposure, accounting for abiotic and
physiological factors that modulate the dose of
toxicant taken up from the environment.

     Three elements are critical to our approach:
(1)  markers selection based on toxicological
mechanisms; (2) field studies to establish corre-
lations between environmental contamination
and markers; and (3) laboratory confirmation of
causal relationships  between exposure, bio-
logical markers, and adverse effects. Labora-
tory studies establish dose-dependent relation-
ships between exposure, quantitative changes
in a suite of biological markers, and long-term
adverse effects.

     Although our work has  concentrated on
aquatic ecosystems, the techniques and ration-
ale  are applicable to a wide range of environ-
mental contamination problems.
                                                                                     285

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Air Pollution Effects on Vegetation
           Site and Stand Characteristics of Southern Appalachian Spruce-Fir

                             Black Mountains, North Carolina

                             N. S. Nicholas and S. M. Zedaker
                                   Department of Forestry
                          Virginia Polytechnic Institute & State University
                                     Blacksburg, Virginia
     Evidence for the decline of southern Appa-
lachian spruce-fir forests as a result of atmos-
pheric deposition of pollutants has recently been
reported by many authors. Although it is gener-
ally accepted that the growth of southern Appa-
lachian spruce-fir forests has  decreased over
the past two decades, the connection of this
decline to pollution may be circumstantial.  Key
issues in the debate over the involvement of air
pollution center  around the expected normal
behavior of spruce-fir stands, and their behavior
relative to  gradients  of pollution deposition.
Extreme variation in the characteristics of the
present stands,  ranging from second growth
plantations on  logged and burned areas to
virgin forests, necessitates a detailed assess-
ment of stand characteristics before reason-
able expectations of normal behavior can be
developed.

     A current assessment at three sites  indi-
cates that species composition changes  dra-
matically with elevation from dominance by red
spruce at low elevation to dominance by Fraser
fir at higher elevations (>6000 feet). Total stand
basal area decreases with increasing elevation
and the pattern is consistent with site quality.
The percent of dead basal area increases with
increasing elevation for both  spruce  and fir.
Red spruce crown  vigor has  decreased be-
tween 1985 and 1987 in the Black Mountains
(NC) and the Great Smoky Mountains (TN, NC)
but not on the Mt. Rogers National Recreation
Area (VA). The decreases in crown vigor are
more pronounced at low elevation and in stands
heavily dominated by fir.  Fir mortality is highly
correlated with the occurrence of the balsam
woolly adelgid.  The current total basal area in
even-aged stands is consistent with basa! area
projections for stands of similar age and site
quality.
 286

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                                                                            Brief Reports
        Response of Seedlings and Mature Trees of the Same Genotype to Ozone

                                  Dr. Susan V. Kossuth
                        USDA Forest Service, SE Forest Experiment Station
                                    University of Florida
                                    Gainesville, Florida
                                          and
                                   Dr. R. Hilton Biggs
                                  Fruit Crops Department
                                    University of Florida
                                    Gainesville, Florida
     Growth:   Both  juvenile  seedlings  and
mature tree ramets of the same genotype were
negatively affected by ozone. The magnitude
and direction of change may be useful for pre-
dicting stand response based on seedling re-
sponse. Seedling height was more sensitive to
ozone than ramet height, with a reduction of 17
percent compared to 11 percent for  ramets.
Ramet diameter increment was more sensitive
to ozone, being reduced by 12 percent com-
pared to 7 percent for seedlings.  The relation-
ship between juvenile and mature tree responses
was consistent for each parameter measured,
i.e., 6 percent greater height reduction and 5
percent less diameter reduction  for seedlings
vs. mature trees.  Half-sib slash pine seedlings
were  grown for 16 weeks after sowing, and
mature grafted trees, for 56 weeks in open-top
chambers that were charcoal filtered  (CF) or
fumigated 5 days per week at 150 ppb ozone.
The seed and scions were from the same parent
tree. Seedlings had only one main stem growth
flush.

     SEM:  Needles were taken from the first
1987 and first 1988 flush on a CF and an  O3
treated ramet from each of the 3 clones. The
1987 needles were fully expanded before fumi-
gation began and the 1988 needles expanded
under fumigation treatment were 22 cm long.
Results to date indicate:  1) Stomatal openings
to  stomatal chambers of 1988  needles were
about 80 percent larger  in O3 treated needles.
2)  O3 treated needles had closed or only partly
opened stomata. 3) The  O3treated needles had
a fine net-like wax layer over the guard cells. 4)
The CF treated needles had large globular wax
plugs or large rod-like wax plugs over the guard
cells. 5) 1987 needles expanded under ambi-
ent conditions did not lose their large wax plugs
even after a year in ozone fumigation.
                                                                                    287

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Air Pollution Effects on Vegetation
                  Effects of Ozone on Water Relations in Bean Leaves

                                        A. Sober
                         Institute of Astrophysics and Atmospheric Physics
                                    Academy of Science
                                     Estonian S.S.R.,
                                       Tartu, USSR
     Elevated concentrations of ozone cause,
first  of  all, changes in  cell walls  and plas-
malemma. Some characteristics of cell walls
and plasmalemma can be estimated from rela-
tionships between leaf water content and xylem
water potential.  We have measured relative
changes in leaf water content following corre-
sponding changes  in xylem water potential of
bean leaves in  ozone-treated plants.  Two
fumigation regimes were used: 1) exposure of
shoots for 3-4 hours under high (0.6 ppm) ozone
concentration, and 2) exposure for 24-48 hours
under lower (0.2 ppm) ozone concentration.

     After ozonization, the plant shoot was cut
near the stem base and let to transpire until its
tu rgor was lost. Then the stem base was closed
into a pressure bomb containing water. A leaflet
of the first trifoliate leaf was closed  into a leaf
chamber equipped with a p-gauge for monitor-
ing the leaf water content.

     The pressure in the bomb was increased
stepwise by 50 kPa until the leaf water content
stopped increasing (infiltration was avoided).
     Treated leaves absorbed water at signifi-
cantly lower rates and to a smaller extent than
the leaves of control plants. In the case of the
first ozonization regime, the increase in water
content was the smallest and sometimes only
temporary. The absolute water content of ozone
treated leaves was also lower. It was found that
the limits of the water content corresponding to
the turgor region of leaves was smaller in ozone-
treated plants. It means that an ozone treated
leaf may lose less water before the turgor loss.
It was established that the parameter  (1-a)
E*(xm-xo)/xm was a constant in our experiments,
and did not depend on ozonation. Here xm is the
maximum water content, xo is the water content
before raising  xylem water potential, E is the
elastic modulus of the leaf, and a = AWPn/AWPa
is the coefficient determining the way the os-
motic potential WP^ changes after a change in
apoplast water potential WPa. It was concluded
that the amount of osmotically active substances
and the stretching capacity of cell walls of bean
leaves decreases simultaneously after fumigat-
ing the plant.
 288

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                                                                              Brief Reports
        Response of Loblolly Pine to Acidic Precipitation and Ozone in Alabama

           A. H. Chapelka, B. G. Lockaby, R. S. Meldah, J. S. Kush and E. Robins
                                     School of Forestry
                                     Auburn University
                                     Auburn, Alabama
     Concern about damage to forest vegeta-
tion due to air pollutants has increased dramati-
cally in the past several decades.  Several or-
ganizations,  including  the  U.S.D.A.  Forest
Service and U.S. EPA, have initiated major
research programs to assess the impact of air
pollutants on forest ecosystems.  As a member
of the Southern Commercial Forest Research
Cooperative  (SCFRC), the School of Forestry,
Auburn University is part of this assessment. As
part of this long-term project (1987-1992), an
intensive site has been developed at Auburn,
Alabama to study the effects of acidic precipita-
tion and  O3  on growth, biomass  production,
nutrient status and physiological responses of
loblolly pine  (Pinus taeda L.) growing in the
coastal plain of Alabama.  Two 6-month-old
half-sib families differing in sensitivity to atmos-
pheric  deposition,  were planted  in January,
1988 in modified open-top chambers (15' x 16').
Twelve treatments are replicated twice in  a
randomized complete block design. The treat-
ments are a factorial arrangement of 3 levels of
acidic precipitation (pH's 5.3,4.3,3.3) and 4 O3
concentrations (carbon-filtered, non-filtered, 1.7
X ambient and 2.5 X ambient).  Trees will be
grown in the chambers for 3 years, with periodic
harvests  to remove competitive effects of the
trees. During the course of each growing sea-
son, intensive measurements will be taken on
tree height, diameter, cumulative growth/flush,
visible injury, photosynthesis, water relations,
nutrient status, biomass production and carbo-
hydrate status. In addition, root biomass pro-
duction and rhizosphere chemistry will be deter-
mined after the 1988 growing season. Results
from this study will provide valuable information
on the response of loblolly pine to acidic precipi-
tation and O3, and will provide a better under-
standing  of the manner in which  these pollut-
ants might affect tree seedlings and saplings.
                                                                                      289

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Air Pollution Effects on Vegetation
                 Ozone Fumigation of Two Ortets of Eastern White Pine
                        from Acadia National Park, Maine, USA

                         J. M. Skelly, K. R. Snyder, and W. Merrill
                                Department of Plant Pathology
                              The Pennsylvania State University
                                University Park, Pennsylvania
     A needleblight of eastern white pine (Pinus
strobus, L) has been observed in Acadia Na-
tional Park,  Maine,  since  1984.   Symptoms
appear very similar to the previously described
semi-mature tissue  needle blight (SNB) and
include chlorotic and necrotic spots, and chlo-
rotic bands which later advance to pink, orange,
and  brown necrotic bands with  subsequent
needle tip necrosis.  As with SNB, the cause of
this most recent blight remains unknown but
both ozone and needle invading fungi are being
investigated as etiological agents. Two ramets
derived from "SNB symptomatic" ortets in Ac-
adia National Park were exposed to four ozone
treatments.  Clones C-6,  C-13 and wild-type
seedlings in  Continuously Stirred Tank Reac-
tors were exposed 7 hours a day from May 31
to August 11 to ozone levels at:  1 )15-30 ppb;
2) 40-70 ppb; 3) 40-70 ppb with an early season
(June 9) 90 ppb Ih spike; and 4) 40-70 ppb with
a 90 ppb early season spike and an additional
(June 30) 160 ppbjh spike. SNB-like symptoms
developed only on clone C-13. Banding and tip
necrosis were first noticed in treatments 3 and
4 following the first spike exposure. SNB symp-
toms became more intense involving additional
tissues following the second spike.  Exposures
to low doses in treatment 2 induced SNB-like
symptoms late in the exposure period. Treat-
ment 1 trees  remained asymptomatic as did the
wild-type and C-6 ramet.
 290

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                                                                             Brief Reports
          Monitoring of Red Spruce and Balsam Fir Decline in the Northeastern
                United States: Symptomatology and Mortality Mapping

         Margaret Miller-Weeks, Joseph Spruce, Barbara Levesque, Dean Smoronk,
                       Robert Cooke, Susan Cox, and Imants Millers
                       Forest Pest Management, State and Private Forestry
                                   USDA Forest Service
                                  Durham, New Hampshire
     A regional multiyear red spruce and bal-
sam fir decline survey,  initiated  in  1984,  is
underway in the  northeastern United States.
This survey encompasses several overall ob-
jectives which include assessing and monitor-
ing the amount and distribution of mortality, tree
condition and rate of change, stocking  and
condition of regeneration, and role of histori-
cally important damage agents.  To address
these major objectives, several projects have
been designed  including a  symptomatology
project and a mortality mapping project.

     The specific objectives of the symptoma-
tology project are to determine the frequency,
geographic variability, and progression of crown
symptoms, and also to  determine which  of
those symptoms  were caused by identifiable
damage agents.   This project is being con-
ducted in New York, Vermont,  New Hampshire,
Massachusetts, and West Virginia. Permanent
plots are in place and are visited annually.
Various crown symptoms and several biotic and
weather related causal agents have been ob-
served.

    The specific objectives  of the mortality
mapping project are to map the locations of red
spruce and balsam fir mortality in New York,
Vermont, New Hampshire, and western Maine,
and to determine  the acres of mortality by
various cover types and elevational zones.  The
areas are being  mapped from color infrared
aerial photographs acquired in 1985 and 1986,
and the Maine Geographic Information System
is being used to  analyze the information  and
produce the acreage tables and mortality maps.
This will provide a baseline to assess the trend
of red  spruce and  balsam fir mortality in the
northeastern United States.
                                                                                    291

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Air Pollution Effects on Vegetation
          Towards Proxy Weather Data: The Association between Tree-Rings
               and Climate as Revealed by Temporal and Spatial Mapping

                                      M.L. Parker
                                 M.L. Parker Company, Inc.
                                 Vancouver, B.C., Canada
     A computerized  mapping system was
developed at the Canadian Climate Centre for
comparing tree-ring data with weather records.
It is designed to give quick visual impressions of
distributional patterns and comparisons of tree-
ring  growth and climate (in color)  over large
geographic areas and long periods  of time.

     Maximum tree-ring density was compared
with  August temperatures for six "regions" in
central Canada. Both types of data were grouped
into three category levels: "high," "medium" and
 low." The period of analysis was from 1800 to
 1984, but the weather data extend back only to
, 1903. Maximum ring density is a good measure
 of August temperature.  Of the 347 instances
 where both tree-ring and  weather  data are
 available, only 18 (5.2%) gave "opposite" re-
 sults (one parameter "high" and the other "low").

      The system can be expanded geographi-
 cally and temporally and other tree-ring and
 weather variables can be used.
 292

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Appendix

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Air Pollution Effects on Vegetation
                             Symposium Program
        SESSION I       DENDROECOLOGY—TREE RINGS AND ENVIRONMENT
                                       Papers
              1.  The US-USSR Cooperative Project—A Brief History, Juri Martin
              2.  U.S. Forests and Atmospheric Deposition, Jack Winjum
              3.  Logfren Comparative Analysis of the Standardization Methods of Tree-Ring
                    Chronologies, Stepan Shiyatov
              4.  Dendrochronology and Environmental Factors, Edward Cook
              5.  Three-Ring Reconstruction of Mean June-July Temperature Using Siberian
                    Larch Tree-Ring Series, Donald Graybill
              6.  Simulative Model on Tree-Ring Tracheidogram on the Base of Climatic
                    Variables, Evgeny Vaganov
              7.  Dendrochronology and Spatial Analyses, Gregory Reams
              8.  Dendrochronology and Forest Ecology, Linda Brubaker
              9.  Selecting Analysis Procedures for Tree-Ring Data when Estimating the
                    Effect of Exogenous Disturbances, Michael Arbaugh
                                Jeff Brandt, Moderator
                                     Workshop
         Detecting Effects of Cumulative Exogenous Disturbances in Tree-Ring Series
             Harold C. Fritts, William  G. Warren, Michael J. Arbaugh, Moderators
                                  Working Sessions
                                Jeff Brandt, Moderator
                           Beverly Law, Program Coordinator

           SESSION II      MECHANISMS AND ALTERNATIVE HYPOTHESES
                                       Papers
              1.  Air Pollution, Plants and Mechanisms: A Historical Perspective, Ellis
                    Cowling
              2.  Diagnostic Physiology and Biochemistry Studies on  Loblolly Pine
                    (Pinus taeda L.), Thomas Sasek
              3.  Impacts of SO2 Fumigation on the Ultra-Structural and Photosynthesis of
                    Pine Needles. Part I. Mesophyll Cells, Irina M. Kravkina
              4.  Impacts of SO2 Fumigation on the Ultra-Structural and Photosynthesis of
                    Pine Needles. Part II.  Resin Duct Cells, Andrey E. Vasilyev
              5.  Impacts of SO2 Fumigation on the Ultra-Structural and Photosynthesis of
                    Pine Needles. Part III. Transition Zone, Richard  Crang
              6.  Ozone Concentration in Leaf Intracellulars is Close to Zero, Agu Laisk
              7.  Forest Decline and the Winter Injury Hypothesis, Ruth Alscher
              8.  Mechanisms by which Regional Air Pollutants Affect Forest Soils and
                    Rhizospheres, Daniel Richter and Michele Schoenberger
              9.  Mechanisms of Genetic Control of Air Pollution Tolerances in Forest Trees,
                    David Karnosky

294

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                                                             Symposium Program
      10. Air Pollution Impact on Structure and State of Northern European Forest
             Ecosystems, Vladislav Alexeyev
      11. Simulating Tree Level Processes,  Cheryl Gay
      12. Tree to Ecosystem Extrapolation, Jack Waide
                        Ann Bartuska, Moderator

                             Workshops
 Physiological and Morphological Comparisons Between Seedlings and Trees
                       Robert Teskey, Moderator
                     Linkages: Trees vs. Ecosystem
                     James N. Woodman,  Moderator

SESSION III      BIOINDICATION AND PROTECTED AREA MONITORING
                               Papers
      1.   Monitoring the Environment in the  21st Century, Stanley I. Auerbach
      2.   The Great Smoky Mountains Biosphere Reserve, John Peine
      3.   (Soviet) Lichens as Bioindicators of Metal Deposition, Oleg Blum
      4.   Biomarkers of Environmental Contamination, John McCarthy
      5.   Comparative Estimates of the Effects of Ozone, Sulphur Dioxide and Nitro-
            gen Dioxide on Plant Productivity, Sergei M. Semjenov
      6.   Bioindication of Air Pollution Effects, Leonard Weinstein
      7.   Element Accumulation in Lichens,  Mosses and  Soils Connected with Mud
            Volcanos Activity, Juri Martin
      8.   A National Program for Environmental Monitoring and Assessment, Jay
            Messer
      9.   Managing for Biological Diversity, Christine Schonewald-Cox
      10. Monitoring for Exotic Species, Peter White
      11. A National Vegetation Survey, Lewis Ohman
      12. Monitoring and Detecting Climate Change, Frank Quintan
      13. Climate Change and Forest Resources, Robin Graham
      14. Direct Effects of CO2 on Trees, Richard Norby
      15. Modeling Effects of Climate Change, William Emanuel
                       David Shriner, Moderator

                             Workshop
                        Global Climate Change
                    Robert M. Cushman,  Moderator

                          Planning Session
                     Future Research Cooperation
           David Shriner, Reginald Noble, Juri Martin, Moderators
                                                                        295

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Air Pollution Effects on Vegetation
                                Session I Participants
                                   Corvallis, Oregon
                               September13- 14, 1988
James Akerson
BIA
BOFRP
Code 232
P. O. Box 3705
Portland, OR 97208

Dr. Sc. Vladislav Alexeyev
Institute  of Forest and Timber Research
Siberian Division of the USSR
Academy of Sciences
660036 Krasnojarsk
Phone:28021

Anastasia B. Allen
290 SW  Tunison
Corvallis, OR 97333

Michael  J. Arbaugh
USDA, Forest Service
Forest Fire Laboratory
4955 Canyon Crest Drive
Riverside, CA 92507-6099

Larry Bednar
USDA, Forest Service
Forest Fire Laboratory
4955 Canyon Crest Drive
Riverside, CA 92507-6099

Dr. Oleg Blum
Central Republic Botanical Garden
Ukrainan Academy of Sciences
Timiryasefskaya Street
252014 Kiev, Ukrainan SSR
Phone: 296 97 72
Margi Bohm
Western Conifers Research Coop
EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97331

Jeffrey G. Borchers
Department of Forest Science
Oregon State University
Corvallis, OR 97331

Linda Brubaker
College of Forest Resources
University of Washington
Seattle, WA 98195

Donald Charles
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Steve Cline
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Edward  R. Cook
Tree-Ring Lab
Lamont-Doherty Geol. Obs.
Palisades, NY 10964

Jennifer M. Donaldson
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333
 296

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                                                                     Session I Participants
Jim Entry
Forest Science
Oregon State University
Corvallis, OR 97333

Michael Fosberg
FFASR
USDA Forest SErvice
P.O. Box 90690
Washington, D.C. 20090

Harold C. Fritts
Laboratory of Tree-Ring Research
University of Arizona
Tucson, AZ 85721

Duane Gardiner
Soil Science Department
Oregon State University
Corvallis, OR 97333

Gail Glick
Foss NW Mtn. View
Corvallis, OR 97330

Donald A. Graybill
Laboratory of Tree-Ring Research
University of Arizona
Bldg. 58
West Stadium,  Rm. 105
Tucson, AZ 85721

Carol S.  Greitner
355 Weniger Hall
General Science Dept.
Oregon State University
Corvallis, OR 97331-6505

Sandra Henderson
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333
Jesus Vargas-Hernandez
Department of Forest Science
Oregon State University
Corvallis, OR 97331

Michael Hoag
Oregon State University
Forest Products
Corvallis, OR 97331

George Gary Ice
NCASI
P.O. Box 458
Corvallis, OR 97339

Bill Hogsett
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Alan Kanaskie
Forest Pathologist
Oregon State Dept. of Forestry
2600 State Street
Salem, OR 97310

Robert L. Krahmer
Forest Products Dept.
College of Forestry
Oregon State University
Corvallis, OR 97330

Lew Ladd
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Dr. Sc. Agu Laisk
Institute of Astrophysics and Atmospheric
Physics
Estonian SSR Academy of Sciences
Estonian SSR
202444 Toravere
Estonia, USSR
Phone:28021
                                                                                  297

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Air Pollution Effects on Vegetation
Steven W. Leavitt
Dept. of Geology
University of Wisconsin-Parkside
Kenosha,Wl 53141-2000

Ted Leininger
4955 Canyon Crest Drive
Forest Fire Lab
Riverside, CA 92507

Gwen Llewellyn
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Eini C. Lowell
Oregon State University
Peavy Hall 023
Dept. of Forest Products
Corvallis, OR 97331

Douglas A. Maguire
College of Forest Resources
AR-10
University of Washington
Seattle, WA 98195

Dr. Sc. Juri Martin
Tallinn Botanical Garden
Estonian  SSR Academy of Sciences
Kloostrimetsa Road 44
Tallinn 200019
Estonia, USSR
Phone:(142)239-001

Jim McClenahen
Environmental Studies Lab
OARDC
Wooster, OH 44691

Bruce McCune
Dept. of General Science
Oregon State University
Corvallis, OR 97331-6505
Joe Means
Forestry Sciences Lab.
3200 Jefferson Way
Corvallis, OR 97331

Margaret Miller-Weeks
USDA, Forest Service
FPM
P.O. Box 640
Durham, NH 03824

Dorothy Mortenson
1600 Western Blvd.
Corvallis, OR 97333

Richard Olson
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Wonkyu Park
Laboratory of Tree-Ring Research
University of Arizona
Tuscon, AZ 85721

M. L. Parker
1757 Johnson Road
Point Roberts, WA 98281

David R. Peart
Dartmouth College
Dept. of Biological Sciences
Hanover, NH 03755

Brian Pedersen
Crocker Lab.
University of California
Davis, CA 95616

Charles E. Peterson
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333
  298

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                                                                    Session I Participants
Milt Plocher
NSI
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Gregory A. Reams
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Cathy Rose
Dept. of Forest Science
Oregon State University
Corvallis, OR 97331

Don Sachs
Forest Science Dept.
Oregon State University
Corvallis, OR 97331

Wieger Schaap
University of Washington
Center for Urban Horticulture
GF-15
Seattle, WA 98195

Paul Schroeder
U.S. EPA
Environmental Research Lab
200 SW 35th St.
Corvallis, OR 97333

Dr. Sc. Sergei Semjenov
LAM
Glebovskaya Str. 20-B
Moscow 107258, USSR
Phone: 1692061
Dr. Sc. Stepan Shiyatov
Institute of Plant and Animal Ecology of the Ural
Division of the USSR Academy of Sciences
8 Marta Street 202
Sverdlovsk
620008 USSR
Phone: 22-05-70

W. Rick Smith
USDA, Forest Service
Institute for Quantitative Studies
RMT-90210, U.S.P.S.B.
701 Loyola Ave.
New Orleans, LA 70113

Elaine Kennedy Sutherland
Native Plants, Inc.
417 Wakana Way
Salt Lake City, UT 84108

Dr. Tounu Terasmaa
Estonian Forest Research Institute
2 Roomu Road
202400 Tartu
Estonia, USSR
Nan Vance
Forest Science Dept.
Oregon State University
Corvallis, OR 97331

Eugene A. Vaganov
Laboratory of Wood Science and
Dendrochronology
Institute of Forest and Timber Research
Siberian Division USSR Academy of
Sciences
660036, Krasnoyarsk, USSR
Phone: 259-695

Nan Vance
Forest Science Dept.
Oregon State University
Corvallis, OR 97331
                                                                                 299

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Air Pollution Effects on Vegetation
Silvia C. Vega-Gonzalez                        Richard H. Waring
Center for Quantitative Science                  College of Forestry
University of Washington, HR-20                 Oregon State University
Seattle, WA 98103                             Corvallis,  OR 97331

John E. Wade                                 Bill Winner
Mechanical Engineering                         Dept. of General Science
Oregon State University                         Oregon State University
Corvallis, OR 97333                            Corvallis,  97331

Deane Wang                                  Don Zobel
Center for Urban Horticulture                    Botany
University of Washington                        Oregon State University
Seattle, WA 98195                             Corvallis,  OR 97331

Jody Wangh
Battelle Northwest Laboratory
P.O. Box 999
Richland, WA 99352
300

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                                 Session II Participants
                                 Raleigh, North Carolina
                                 September 18-20, 1988
Tim Albaugh
N.C. State University
P.O.Box 12254
Research Triangle Park, NC 27709
919/541-2890

Dr. Sc. Vladislav Alexeyev
Institute  of Forest and Timber Research
Siberian Division of the USSR
Academy of Sciences
660036 Krasnojarsk
Phone: 259-454
Ralph Baumgardner
US EPA
MD-44
Research Triangle Park, NC 27711
919/541-4625

Dr. Oleg Blum
Central Republic Botanical Garden
Ukrainan Academy of Sciences
Timilyasefskaya Street
252014 Kiev, Ukrainan SSR
Phone: 296 97 72
H. Lee Allen
Box 8002
Dept. of Forestry
N.C. State University
Raleigh, NC 27695-8002
919/737-3500

Ruth Alscher
Plant Pathology, Physiology and Weed
Science
Virginia Polytechnic Institute and State Univ.
Blacksburg, VA 24061
703/961-6761

Thangam Arumugham
Dept. of Statistics
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3925

Ann M. Bartuska
SCFRC-Forest Service
1509 Varsity Drive
Raleigh, NC 27606
919/737-7040
Robert I. Bruck
Dept of Plant Pathology
Box7616
N.C. State University
Raleigh, NC 27695
919/737-2086

Art Chappelka
School of Forestry
White Smith Hall
Auburn University, AL 36849-5418
205/826-4050

Ellis Cowling
Atmospheric Impacts Research Program
1509 Varsity Drive
Raleigh, NC 27606
919/737-2883

Richard Crang
Center for Electron Microscopy
University of Illinois
74 Bevier Hall
905 South Goodwin Hall
Urbana, IL61801
217/333-2108
                                                                                   301

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Air Pollution Effects on Vegetation
Patti Faulkner
U.S. Forest Service
3041 Cornwallis Road
Research Triangle Park, NC 27709
919/549-4045

Edward A. Fendick
School of Forestry and Environmental Studies
Duke University
Durham, NC 27706
919/684-2421

Cheryl  Aeschbach Gay
Western Conifers Research Cooperative
Environmental Research Lab.
200 SW 35th St.
Corvallis, OR 97330
503/757-4791

Chris Geron
USDA Forest Service
P.O. Box 12254
Research Triangle Park, NC 27709
919/549-4014

Richard Gould
Dept. of Botany
N.C. State University
Air Quality Program
1509 Varsity Drive
Raleigh, NC 27606
919/737-3575

Marcia Gumpertz
Dept. of Statistics
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3925

Kerrick Hartman
Dept. Plant Pathology
N.C. State University
Box 7616
Raleigh, NC 27695
919/737-2721
Allen S. Heagle
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3728

W.E. Hogsett
EPA/ERL-C
200 SW 35th
Corvallis, OR 97333
503/757-4632

James LJ.  Houpis
Lawrence Livermore National Lab.
P.O. Box 5507, L-524
Livermore, CA 94550
415/422-0606

Kimberly C. Joyner
Atmospheric Impacts Research Program
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3520

David Karnosky
School of Forestry
Michigan Technological University
Houghton, Ml 49931
906/487-2898

J.R. Kercher
Plant Sciences
Lawrence Livermore National Lab.
P.O. Box 808, L-451
Livermore, CA 94550
415/422-1416

Tara J. Kidd
N.C. State University
810KnoxSt
Durham, NC 27701
919/383-8646
 302

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                                                                   Session II Panic/pants
Sue V. Kossuth
1143Fifield Hall
University of Florida
Gainesville, FL 32611
904/392-8065

Lance Kress
U.S. Forest Service
P.O. Box 12254
Research Triangle Park, NC 27709
919/541-2890

Bob Kucera
NSI Technologies, Inc.
2 Triangle Dr.
Research Triangle Park, NC 27709
919/541-7589

John Kush
School of Foresty
108 M.White Smith
Auburn University, AL 36849-5418
205/826-4050

Lew Ladd
U.S. EPA
200 SW 35th St.
Corvallis, OR 97333
503/757-4657

Dr. Sc. Agu Laisk
Institute  of Astrophysics and Atmospheric
Physics
Estonian SSR Academy of Sciences
Estonian SSR
202444 Toravere
Estonia, USSR
Phone: 28021

Kim Ludovici
US Forest Service
3041  E. Cornwallis Road
Research Triangle Park, NC 27709
919/541-4045
Elizabeth Lusk
School of Forestry
Duke University
1315 Morreene Road, Apt25-K
Durham, NC 27705
919/383-5327

Barry E. Martin
Atmospheric Exposure Cooperative
US EPA
MD-76
Research Triangle Park, NC 27713
919/541-4386

Dr. Sc. Juri Martin
Tallinn Botanical Garden
Estonian SSR Academy of Sciences
Kloostrimetsa  Road 44
Tallinn 200019
Estonia, USSR
Phone:(142)239-001

Susan  Medlarz
SCFRC - U.S. Forest Service
1509 Varsity Drive
Raleigh, NC 27606
919/737-3520

Bob Mickler
U.S.  Forest Service - SCFRC
P.O.  Box 12254
Research Triangle Park, NC 27709
919/541-4022

Len Milich
School of Forestry
Duke University
Durham, NC 27706
919/684-2421

Margaret Miller-Weeks
USDA Forest Service
P.O.  Box 640
Durham, NH 03824
603/868-5719
FTS-834-5765
                                                                                 303

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Air Pollution Effects on Vegetation
Bob Mills
Computer Graphics Center
Box7106
N.C. State University
Raleigh, NC 27695-7106
919/737-3433

Fred L. Mowry
School of Forestry and Environmental Studies
Duke University
Durham, NC 27706
919/541-2890

Reg Noble
Dept. of Biological Sciences
Bowling Green  State University
Bowling Green, OH 43403
419/372-2332

Ram Oren
School of Forestry & Environmental Studies
Duke University
Durham, NC 27706
919/684-2421

Valerie A. Paynter
Department of Forestry
Clemson University
Clemson, SC 29634-1003
803/656-4400 or 4062

Mary Peet
Box 7609
Dept. Horticulture Science
N.C. State University
Raleigh, NC 27695-7609
919/737-3167

Charles E. Peterson
Environmental Research Laboratory
200 S.W. 35th St.
Corvallis, OR 97333
503/757-4310
Mark J. Pistrang
School of Forestry and Environmental Studies
Duke University
Durham, NC 27706
919/684-2421

Bill Poole
Atmospheric Impacts Research Program
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3520

John Pye
USDA Forest Service
P.O. Box12254
Research Triangle Park, NC 27709
919/549-4013

John C. Reardon
Dept. of Forestry
Clemson University
Clemson, SC 29634-1003
803/656-4843 or 2251 (Site)

Richard A. Reinert
Dept. of Plant Pathology
N.C. State University
Box 7616
Gardner Hall
Raleigh, NC 27695
919/737-3962

Dan Richter
Duke University
School of Forestry and Environmental Studies
Durham, NC 27707
919/684-2619

Bruce Ripley
School of Forestry and Environmental Studies
Duke University
Durham, NC 27707
919/383-8059
 304

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                                                                   Session II Participants
Wayne P Robarge
Dept. of Soil Science
Box7619
N.C. State University
Raleigh, NC 27695-7619
919/737-2600

Mr. Ray Roten
Computer Graphics Center
Box 7106
N.C. State University
Raleigh, NC 27695
919/737-3433

Thomas W. Sasek
School of Forestry and Environmental Studies
Duke University
Durham, NC 27709
919/684-2619

Cari L. Sasser
Atmospheric Impacts Research Program
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3520

Vin Saxena
Dept. of Marine, Earth, and Atmospheric
Sciences
N.C. State University
Box 8208
Raleigh, NC 27695-8208
919/737-7290

Amy Scherzer
Forest Ecology - Dept. of Botany
Ohio State University
1735 Neil Avenue
Columbus, Ohio 43210

Michele M. Schoeneberger
P.O.Box 12254
Forestry Sciences Lab
Research Triangle Park, NC 27709
919/549-4043
Paul Schroeder
Forest Response Program
200 S.W. 35th
Corvallis, OR 97333
503/757-4658

John Seiler
228 Cheatham Hall
Dept. of Forestry
Virginia Polytechnic Institute and State Univ.
Blacksburg, VA 24060
703/961-5461

Dr. Sc. Sergei Semjenov
LAM
Glebovskaya Str. 20-B
Moscow 107258, USSR
Phone:1692061

Steven R. Shafer
N.C. State University
USDA-NCSU Air Quality Research Program
1509 Varsity Drive
Raleigh, NC 27606
919/737-2142

Dr. Sc. Stepan Shiyatov
Institute of Plant and Animal Ecology of the
Ural Division of the USSR Academy of Sci-
ences
8 Marta Street 202
Sverdlovsk
620008 USSR
Phone: 22-05-70

Kevin T. Smith
USDA-FS-NE
Box 640
Durham, NH 08324
603/868-5710

David Shriner
Oak Ridge National Laboratory
P.O. Box X
Bldg. 1505
Oak Ridge, TN 37830
615/547-7356
                                                                                  305

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Air Pollution Effects on Vegetation
Luther Smith
Northrup Environmental Services, Inc.
2 Triangle Drive
Research Triangle Park, NC 27709
919/541-0049

W. Rick Smith
USDA-USFS, Institute for Quantitative Studies
RmT-10210, USPSB
701 Loyola Ave.
New Orleans, LA 70113
504/589-4549

Paul C.  Smithson
Box 7619
Soil Science
N.C. State University
Raleigh, NC 27695-7619
919/737-2600

Dale S.  Solomon
U.S. Forest Service
P.O. Box 640
Durham, NH 03824
603/868-5719

Harriett  Stubbs
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3520

Dr. Tounu Terasmaa
Estonian Forest Research Institute
2 Roomu Road
202400 Tartu
Estonia, USSR

Robert Teskey
Univ. of  Georgia
School of Forest Resources
Athens, GA 30602
404/542-5055
Piotrek Tyszko
228 Cheatham Hall
Dept. of Forestry
Virginia Polytechnic Institute and State Univ.
Blacksburg, VA 24060
703/961-5461

Eugene A. Vaganov
Laboratory of Wood Science and Dendro-
chronology
Institute of Forest and Timber Research
Siberian Division USSR Academy of Sci-
ences
660036, Krasnoyarsk, USSR,
Phone: 259-695

Dr. Sc. Andrey Vasilyev
Komarov Botanical Institute
USSR Academy of Science
Leningrad 197022
Prof. Popov 2
Lab Anatomy a. Morph.
Phone: 2348446

David L. Vermillion
N.C. State University
Rt. 4, Box 1197
Palmer's Grove Church Rd.
Hillsborough, NC 27278
919/383-8646

Jack Waide
Coweeta Hydrologic Laboratory
SE Forest Experiment Station
999 Coweeta Lab. Road
Otto, NC 28763
704/524-2128

Charles D. Webb
Southern Air Quality/Forest Health Program
NCASI
Box12254
Research Triangle Park, NC 27709
919/541-9217
 306

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                                                                    Session II Participants
Carol G. Wells
Forestry Sciences Laboratory
P.O.Box 12254
Research Triangle Park, NC 27709
919/549-4041
James N. Woodman
Atmospheric Impacts Research Program
N.C. State University
1509 Varsity Drive
Raleigh, NC 27606
919/737-3520
                                                                                   307

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Air Pollution Effects of Vegetation
                                Session III Participants
                                Gatlinburg, Tennessee
                                September 21 - 25, 1988
Joe Abrell
Great Smoky Mountains National Park
Route 2, Box 260
Gatlinburg, TN 37738
(615)436-1245

Dr. Sc. Vladislav Alexeyev
Institute of Forest and Timber Research
Siberian Division of the USSR
Academy of Sciences
660036 Krasnojarsk
Phone:259454

Bob Anderson
US Forest Service
Route 3, Box 279
Arden, N C
(704) 667-5089

Stanley Auerbach
Oak Ridge National Laboratory
P  0 . Box 2008
Oak Ridge, TN 37831-6036
(615)574-7302

Ann M. Bartuska
US Forest Service
1509 Varsity Drive
Raleigh, NC 27606
(919)737-7040

Dr. Oleg Blum
Central Republic Botanical Garden
Ukrainan Academy of Sciences
Timilyasefskaya Street
252014 Kiev, Ukrainan SSR
Phone: 296 97 72
Kevin A. Cavender
University of Florida
2909-39 SW 13th Street
Gainesville, FL 32608
(904) 392-0845

Richard Crang
2903 Deske Court
Champaign, IL61821
(217)359-7184

Robert M. Cushman
Oak Ridge National Laboratory
P . 0 . Box 2008
Oak Ridge, TN 37831-6335
(615)574-0390

Don Davis
Penn State University
211 Buckhout Laboratory
University Park, PA 16802
(814)237-5443

William R.  Emanuel
Oak Ridge National Laboratory
P. 0 . Box 2008
Oak Ridge, TN 37831-6038
(615)574-7821

Marie Frias
Route 7, Box 69
Valley View Road
Sevierville, TN 37862

Richard Gould
Air Quality Program
1509 Varsity Drive
Raleigh, NC 27606
(919)737-3311
  308

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                                                                   Session III Participants
Robin Graham
Oak Ridge National Laboratory
P.O. Box 2008
Oak Ridge, TN 37831-6038
(615)576-7756

Albert G  Greene, Jr
Office of the Senior Scientist
National Park Service
Washington,  DC 20013-7127
(202)343-2917

Betsy Groton
Tennessee Valley Authority
Forestry Building
Norris, TN 37828
(615)632-1509

Cindy Huber
US Forest Service
P.O. Box 2750
Asheville, NC 28802
(704) 257-4329

Margaret Keener
Oak Ridge National Laboratory
P . 0 . Box 2008
Oak Ridge, TN 37831-6038
(615)574-4632

M . A . Khan
Virginia Polytechnic Institute and State Uni-
versity
Blacksburg, VA 24061

Dr. Irina Kravkina
Komorov Botanical Institute
USSR Academy of Sciences
Prof. Popov.  2
Leningrad, 197022, USSR
Phone: 2-34-84-46
Dr. Sc. Agu Laisk
Institute of Astrophysics and Atmospheric
Physics
Estonian SSR Academy of Sciences
Estonian SSR
202444 Toravere
Estonia, USSR
Phone:2802 1

Keith Langdoll
Great Smoky Mountains National Park
Route 2, Box 260
Gatlinburg, TN 37738
(615)576-6606

Dr. Sc. Juri Martin
Tallinn Botanical Garden
Estonian SSR Academy of Sciences
Kloostrimetsa Road 44
Tallinn 200019
Estonia, USSR
Phone:(142)239-001

John McCarthy
Oak Ridge National Laboratory
P  0 . Box 2008
Oak Ridge, TN 37831-6036
(615)576-6606

John McCrone
Clemson University
263 Lehotsky Hall
Clemson, SC 29634
(803)656-2182

Jay Messer
US Environmental Protection Agency
MD-39
Research Triangle Park, NC 27711
(919)541-0150

Niki S. Nicholas
Department of Forestry
Virginia Polytechnic Institute and State Uni-
versity
Blacksburg, VA 24061
(703)961-6378
                                                                                  309

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Air Pollution Effects of Vegetation
Reginald Noble
Department of Biological Sciences
Corner of E. Mary and North College
Life Sciences Building
Bowling Green State University
Bowling Green, OH 43403
(419)372-2332

Stephen C. Nodvin
Cooperative Park Studies Unit
Department of Forestry, Wildlife & Fisheries
University of Tennessee
Knoxville, TN 37901 -1071
(615)974-0739

Richard Norby
Oak Ridge National Laboratory
P.O. Box 2008
Oak Ridge, TN 37831-6034
(615)576-5261

James O'Brien
US Forest Service
Box 640
Durham, NH
(603)868-5719

Lewis Ohman
1831 E. Highway 169
Grand  Rapids, MN 55744
(218)326-8571

Jay Parrish
Department of Geology
Bowling Green State University
Bowling Green, OH 43402

John Peine
Route 2, Box 260
Gatlinburg, TN 37738
(615)436-7120

Seth Pilsk
Uplands Research Laboratory
Route 2, Box 260
Gatlinburg, TN 37738
(615)436-7120

 310
Bill Poole
North Carolina State University
1509 Varsity Drive
Raleigh, NC 27606
(919)737-3520

Randolph Pope
Great Smoky Mountains
National Park
Route 2, Box 260
Gatlinburg, TN 37738

Frank T. Quinlan
National Climatic Data Center
Federal Building
Asheville, NC 28801
(714)259-0245

David Reichle
Oak Ridge National Laboratory
P.O.  Box 2008
Oak Ridge, TN 37831-6037
(615)574-7301

Lonna Richmond
911 Loghaven
Knoxville, T N
(615)579-3079

Kurt Riitters
RD682
US Environmental Protection Agency
401 M Street SW
Washington, DC 20460
(202) 382-5609

Christine Schonewald-Cox
NPS/CPSU Institute of Ecology
University of California
Wickson Hall
Davis, C A 95616
(916) 752-2088

Dr. Sc. Sergei Semjenov
LAM
Glebovskaya Str. 20-B
Moscow 107258, USSR
Phone: 1692061

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                                                                   Session III Participants
Stephen R. Shifley
North Central Experiment Station
1992 Folwell Avenue
St. Paul, MN55108
(612)649-5172

Dr. Sc. Stepan Shiyatov
Institute of Plant and Animal Ecology of the Ural
Division of the USSR Academy of Sciences
8 Marta Street 202
Sverdlovsk
620008 USSR
Phone: 22-05-70

David S. Shriner
Oak Ridge National Laboratory
P. 0. Box 2008
Oak Ridge, TN 37831-6038
(615)574-7356

John M. Skelly
Department of Plant Pathology
Penn State University
University Park, PA 46802
(814)234-3485

Margie Steigerwald
Great Smoky Mountains National Park
Route 2, Box 260
Gatlinburg, TN 37738
(615)436-1208
 Robert L. Sutton
 Environmental Engineering Sciences Dept.
 University of Florida
 412 Black Hall
 Gainesville, FL 32611
 (904) 392-0845

 Dr. Tounu Terasmaa
 Estonian Forest Research Institute
 2 Roomu Road 202400 Tartu
 Estonia, USSR

 Dr. Sc. Andrey Vasilyev
 Komarov Botanical Institute
 USSR Academy of Science Leningrad
 197022
 Prof. Popov 2
 Lab Anatomy a. Morph.
 Phone:2348446

Leonard H. Weinstein
Boyce Thompson Institute
Tower Road
Ithaca, NY 14853
(607)254-1234

 Peter White
 Biology Department
 University of North Carolina
 Chapel Hill, NC 27599-3280
 (919)962-6939
 „ US OOVERNMENTPRINTINOWFICE ,*» - 651-158
                                      311

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Noble, Reginald D.; Martin, Juri L; Jensen, Keith F., eds. 1989. Air
  pollution effects on vegetation including forest ecosystems. Proceed-
  ings of the second US-USSR symposium; 1988  September 13-25; Cor-
  vallis,  OR; Raleigh, NC; Gatlinburg, TN. Broomall, PA: U.S. Depart-
  ment of Agriculture, Forest Service, Northeastern Forest Experiment
  Station. 311 p.
To commemorate the 10th year of cooperation between the US-USSR in
the field of environmental protection, a symposium was organized, the
major objectives of which were to acquaint US-USSR scientists with
project accomplishments; to promote understanding of the nature of
environmental problems that relate to air pollution effect on vegetation
on a more global scale; to share research priorities, interests, and
methodologies; and to plan future research cooperation.

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