EPA/620/R-94/027
October 1994
Forest Health Monitoring
Field Methods Guide
Technical Director
Samuel A. Alexander
U.S. Environmental Protection Agency
Environmental Monitoring and Assessment Program Center
Research Triangle Park, NC 27709
and
Program Manager
Joseph E. Barnard
U.S.D.A. Forest Service
U.S. Forest Service Laboratory
Research Triangle Park, NC 27709
Environmental Monitoring Systems Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Las Vegas, NV 89119
Printed on Recycled Paper
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EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page ii of
xx
FOREST HEALTH MONITORING
Field Methods Guide
edited by
Nita G. Tallent-Halsell
Approved by
Barnard
'National Program Manger
Forest Health Monitoring
Samuel A. Alexander
Technical Director
Forest Health Monitoring
NOTICE
The U.S. Environmental Protection Agency (EPA), through its Office of Research and Development
(ORD), partially funded and collaborated in the research described here, it has been peer reviewed by the
Agency and approved as EPA publication.
Proper citation of this document is:
Tallent-Halsell, N.G. (ed.). 1994. Forest Health Monitoring 1994 Field Methods Guide. EPA/620/R-94/027
U.S. Environmental Protection Agency, Washington, D.C.
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EMAP Forest Monitoring, Section - F:ront, Revision 0, October, 1994, Page iii of xx
FOREWORD
In response to legislation and policy requirements, the U.S. Department of Agriculture (USDA) Forest
Service (FS) and the U.S. Environmental Protection Agency (EPA) must provide periodic reports on the
nation's forest health, status, and trends. To do this, the FS and EPA have developed a cooperative, multi-
agency monitoring activity within the framework of the EPA's Environmental Monitoring and Assessment
Program (EMAP).
The Forest Health Monitoring (FHM) program is jointly managed and largely funded by the FS and EPA
in cooperation with other program participation. FHM partners -- participating State Forestry agencies, the
U.S. Department of the Interior (USDI) Bureau of Land Management, the Tennessee Valley Authority, and
the USDA Soil Conservation Service - provide additional financial and personnel support. Other
cooperators include universities and three additional agencies: USDI's U.S. Fish and Wildlife Service, U.S.
Geological Survey, and the National Park Service. The National Association of State Forester provides
essential program support, guidance, and assistance.
The FHM program was developed in response to increasing concern for the health of the nation's
forests in light of the potential effects of atmospheric pollutants, global climate change, and a variety of
insect, disease, and other stressors. To help address these concerns, the FHM program is designed to
assist resource managers and policy makers in managing the nation's forest resources, allocating funds
for research and development, and evaluating environmental policy for forest resources.
The specific objectives of this program are to:
1. Estimate with known confidence the current status, changes, and trends in selected indicators of
forest ecosystem condition on a regional basis;
2. Identify associations between changes of trends in indicators of forest ecosystem condition and
indicators of natural and human-caused stressors, including changes in forest extent and
distribution;
3. Provide information on the health of the nation's forest ecosystems in annual statistical summaries
and periodic interpretive reports for use in policy and management decisions;
4. Identify mechanisms of ecosystem structure and function through long-term monitoring of
ecosystem processes at intensively monitoring sites representing major forest ecosystems;
5. Improve the effectiveness and efficiency of forest health monitoring through directed research; and
6. Integrate forest health monitoring with other EMAP resource groups in order to complete multi-
ecosystem assessments.
During the past three years, the agencies participating in the FHM program have worked to develop
a national sampling design to identify and develop indicators that can be used to assess forest health, and
to begin implementing data collection from a national sample of monitoring sites. The organizational
structure for planning, managing, and implementing the program has evolved gradually and is still being
developed. An overview of the current organizational structure is provided in Figure 1.
in
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EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page iv of xx
Forest Health Monitoring field work in 1994 will include detection monitoring activities in the
northeastern and northcentral, southeastern and western states, including Maine (ME), New Hampshire
(NH), Vermont (VT), Massachusetts (MA), Connecticut (CT), Rhode Island (Rl), New Jersey (NJ), Delaware
(DE), Maryland (MD), Virginia (VA), Minnesota (MN), Wisconsin (Wl), Michigan (Ml), Georgia (GA),
Alabama (AL), Colorado (CO), and California (CA). Additional FHM field activities will be occurring in
Washington (WA) and Oregon (OR) as the Pacific Northwest Pilot Study (PNW-PS).
The FHM Field Methods Guide documents all field measuring activities and collection being
implemented across the nation. Note, a number of regional variations do exist. Regional versions of this
field guide contain only those activities being implemented in that region. The FHM Field Methods Guide
are integral parts of the FHM Quality Assurance Project Plan (Cline (ed.) 1994).
The purpose of this guide is to document and encourage standardization of data collection procedures
for all 1994 FHM field activities. The following sections of this guide contain detailed instruction for locating
and establishing sample plots and for correcting and recording observational and measurement data for
individual indicators in detection monitoring. In addition, it includes a general field logistics plan and a
safety plan identifying potential field hazards, recommended precautions, and accident reporting
procedures.
IV
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EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page v of xx
National Program Manager
USDA Forest Service
Joseph E. Barnard
Technical Director
U.S. EPA, EMAP
Samuel A. Alexander
FHM Deputies
State/Federal
Technical Groups
Regional
Coordinators
Cooperating Federal
Agency Coordinators
BLM;SCS; TVA
Program Area
Coordinators
Indicator Leads
Figure 1. Forest Health Monitoring organization structure.
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EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page vi of xx
Table of Contents
Section Title
Page
Notice »
Contributors xii
Acronyms xiv
Acknowledgements xv
Glossary xvi
Section 1. Site Condition, Growth, and Regeneration 1 of 86
1.0 Quick Reference Tally PDR Screens . 2 of 86
1,1 Overview 9 of 86
1.2 Sample Collection, Preservation, and Storage 10 of 86
1.3 Equipment and Supplies 11 of 86
1.4 Calibration and Standardization 12 of 86
1.5
1.6
Quality Assurance 12 of 86
Procedures 19 of 86
1.7 References 85 of 86
Section 2. Crown Condition Classification 1 of 23
2.1 Overview 2 of 23
2.2 Sample Collections, Preservation, and Storage 6 of 23
2.3 Equipment and Supplies 7 of 23
2.4 Calibration and Standardization 7 of 23
2.5 Quality Assurance 10 of 23
2.6 Procedure 11 of 23
2.7 References 23 of 23
Section 3. Damage and Catastrophic Mortality Assessment 1 of 22
3.0 Quick Reference 2 of 22
3.1 Overview 3 of 22
3.2 Sample Collection 4 of 22
3.3 Equipment and Supplies 4 of 22
3.4 Calibration and Standardization 4 of 22
3.5 Quality Assurance 4 of 22
3.6 Procedures 5 of 22
3.7 References 19 of 22
Appendix 3.1 Catastrophic Mortality Assessment 20 of 22
Section 4. Photosynthetically Active Radiation (PAR) Indicator 1 of 18
4.1 Overview 2 of 18
4.2 Sample Collection, Preservation, and Storage 4 of 18
4.3 Equipment and Supplies 4 of 18
4.4 Calibration and Standardization 4 of 18
4.5 Quality Control 7 of 18
4.6 Procedures 8 of 18
4.7 References 18 of 18
VI
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Section 5. Vegetation Structure 1 of 12
5.1 Overview 2 of 12
5.2 Plant Sample Collection and Handling 3 of 12
5.3 Equipment and Supplies 5 of 12
5.4 Calibration and Standardization 5 of 12
5.5 Quality Assurance 5 of 12
5.6 Procedure 6 of 12
5.7 References 12 of 12
Section 6. Ozone Bioindicator Plants 1 of 21
6.1 Overview 2 of 21
6.2 Sample Collection, Preservation, and Storage 3 of 21
6.3 Equipment and Supplies 3 of 21
6.4 Calibration and Standardization 4 of 21
6.5 Quality Assurance 4 of 21
6.6 Procedure 7 of 21
6.7 References 16 of 21
Appendix 6.A Ozone Bioindicator Plants 17 of 21
Section 7. Lichen Communities 1 of 11
7.1 Overview 2 of 11
7.2 Sample Collection, Preservation, and Storage 3 of 11
7.3 Equipment and Supplies 6 of 11
7.4 Calibration and Standardization 6 of 11
7.5 Quality Assurance 6 of 11
7.6 Procedure '. 9 of 11
7.7 References 11 of 11
Section 8. Field Logistics 1 of 12
8.1 Overview 2 of 12
8.2 Training 2 of 12
8.3 Field Logistics 3 of 12
8.4 Data Transfer and Sample Handling 9 of 12
8.5 .Debriefing 12 of 12
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Appendices
Appendix A U.S. Tree Species Codes 1 of 8
Appendix B State and County FIPS Codes 1 of 9
Appendix C Forest Type Descriptions 1 of 10
Appendix D Land Use Classifications ' 1 of 3
Appendix E Safety Plan 1 of 10
Figures
1-1 National FHM plot layout is designed around four points (subplot centers) 22 of 86
1-2 Terrain position 39 of 86
1-3 Boundary delineation 42 of 86
1-4 Distinctions among trees less than 5.0 in. (12.7 cm) DBH 45 of 86
1-5 Where to measure diameter breast height in a variety of situations 52 of 86
1-6 Points of diameter measurement on woodland trees 54 of 86
1-7 Relative crown positions of dominant (D), codominant (C),
intermediate (I), and overtopped (O) trees 64 of 86
1-8 Location of four subplot offset points 79 of 86
1-9 Locating offset point #3 , 79 of 86
1-10 Locating other subplot centers 80 of 86
1-11 Locating offset points from each other on the same subplot 81 of 86
1-12 Locating the microplot center from subplot offset points 82 of 86
1-13 Referencing trees to offset points 83 of 86
1-14 Estimating boundaries from offset points 83 of 86
1-15 Subplot limiting distances from offset point #4 84 of 86
2-1 Crown density - foliage transparency card 8 of 23
2-2 Crown grid 9 of 23
2-3 Sapling live crown ratio determination examples 13 of 23
2-4 Crown rating example 15 of 23
2-5 Crown rating example, hardwood 16 of 23
2-6 Crown rating example, pine 17 of 23
2-7 Crown diameter determination 18 of 23
2-8 Live crown ratio determination examples 20 of 23
3-1 Location codes for the damage indicator 6 of 22
3-2 The damage runs from stump to crownstem 7 of 22
3-3 A canker which exceeds threshold 13 of 22
3-4 Multiple damage in "stump" and lower bole 14 of 22
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Figures Cont'd
4-1 PAR sampling scheme 3 of 18
4-2 Solar declination (D) in degrees 11 of 18
4-3 Ambient station setup 12 of 18
5-1 Plant specimen label used for vegetation structure indicator 4 of 12
5-2 Portable data recorder screen 4 of 12
5-3 Layout of quadrats on each subplot 7 of 12
5-4 Collapsible 1 m2 quadrat sampling frame and placement of telescoping pole
on quadrat 8 of 12
6-1 Example of a well drawn map locating the bioindicator site for a permanent detection
monitoring plot 9 of 21
7-1 Conceptual model of the lichen community indicator : 2 of 11
7-2 Plot packing slip for lichen communities 4 of 11
7-3 Form used for mailing lichen community specimens, one form per box 5 of 11
7-4 Lichen sampling area 10 of 11
IX
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Tables
1-1 Plot-Level Note Screen 2 of 86
1-2 Plot Identification Screen 2 of 86
1-3 Condition Classification Screen 2 of 86
1-4 Site-Tree Screen 3 of 86
1-5 Point-Level Descriptors Screen 3 of 86
1-6 Boundary Delineation Screen 4 of 86
1-7 Understory Vegetation Screen 4 of 86
1-8 Microplot Seedling Screen 4 of 86
1-9 Microplot Sapling Screen 5 of 86
1-10 Subplot Tree Screen 6 of 86
1-11 Full-Hectare Boundary Screen (CA/PNW PS Only) 7 of 86
1-12 Full-Hectare Tree Screen (CA/PNW PS Only) 7 of 86
1-13 Full-Hectare Tree Mortality Screen 8 of 86
1-14 Plot-Level Note Screen - Nonforested/Access Denied/Dangerous Plots 8 of 86
1-15 Plot Identification Screen - Nonforested/Access Denied/Dangerous Plots 8 of 86
1-16 Site Condition, Growth, and Regeneration Measurement Quality Objectives 12 of 86
1-17 English and Metric Slope Distance Correction Factors 38 of 86
1-18 Valid Micropiot Tree History Codes by Measurement Types 49 of 86
1-19 Valid Subplot Tree History Codes by Measurement Types 58 of 86
1-20 Valid Full-Hectare Tree History Codes by Measurement Types 69 of 86
1-21 Tree Sizes Sampled for Mortality by Plot Type 72 of 86
1-22 Distances and Azimuths Between Subplots 2-4 80 of 86
1-23 Distances and Azimuths Between Offset Points 81 of 86
1-24 Directions from Offset Points to Microplot Centers 82 of 86
1-25 Limiting Distances to 18 Points on the Subplot 84 of 86
2-1 PDR Prompt Codes 5 of 23
2-2 Crown Diameter Codes 6 of 23
2-3 Live Crown Ratio, Crown Density, Crown Dieback, and
Foliage Transparency Codes 6 of 23
2-4 Crown Classification Measurement Quality Objectives 10 of 23
3-1 Damage Measurement Quality Objectives 4 of 22
5-1 PDR Screens and Codes 9 of 12
6-1 Measurement Quality Objectives 5 of 21
7-1 Measurement Quality Objectives and Their Method of Assessment 7 of 11
7-2 Summary of 1993 SE and SAMAB Demonstrations
Lichen Community Data Quality 9 of 11
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Tables Cont'd
8-1 FHM Crew Types, Definitions, and Regions or States Implementation 2 of 12
8-2 FHM Key Positions per Region and Crew Type 3 of 12
8-3 Field Work Time Allocation 4 of 12
8-4 Suggested Work Flow Pattern (Forester and Botanist Crew Working Together
on 1/4 plot) 5 of 12
8-5 Suggested Work Flow Pattern (Forester Crews - Mt2 Plots) 5 of 12
8-6 Suggested Work Flow Pattern (Forester Crews - Mt1/3 Plots/No PAR, Lichens
or Vegetation Measurements Being Collected) 5 of 12
8-7 Suggested Work Flow Pattern (1/4 Crew (CO)) . 5 of 12
8-8 Suggested Work Flow Pattern (1/4 Crew (CA & PNW Pilot Study)) 6 of 12
XI
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Contributors
(listed alphabetically by organization, location, name, and contribution, lead author listed in bold)
Colorado State Forest Service, 214 Forestry Building, Colorado State University, Fort Collins, CO
80523
M. Schomaker (Damage and Mortality Assessment)
Illinois Wesleyan University, Department of Biology, Bloom, IL 61702
J. Dey (Lichen Community)
Lockheed Environmental Systems & Technologies Company, 980 Kelly Johnson Dr., Las Vegas, NV
89119
R.L. Tidwell (Logistics & Safety)
Oregon State University, Dept. of General Science, Weniger355, OSU, Corvallis OR 97331-6505
B.M. McCune (Lichen Community)
Tennessee Valley Authority, Ridgeway Road, Forestry Building, Morris, TN 37828
N.S. Nicholas (Logistics & Safety)
University of Massachusetts, Dept. of Forestry and Wildlife Manage., Amherst, MA 01003
G. Smith (Ozone Bioindicator Plants)
USDA Forest Service, Anchorage Forest Sciences Lab, 201 e. 9th, Suite 303, Anchorage, AK 99501
V.J. LaBau (Site Condition, Growth and Regeneration)
USDA Forest Service, Forest Inventory and Analysis, 200 Weaver Blvd, Southeastern Experiment
Station, Asheviile, NC 29804
W. Bechtold (Site Condition, Growth and Regeneration)
B. Brantley (Ozone Bioindicator Plants)
USDA Forest Service, Forest Pest Management, RT 3 Box 1249A, Asheviile, NC 28806
R.L. Anderson (Crown Condition Classification)
W. Hoffard (Damage and Mortality Assessment)
USDA Forest Service, U.S. Forest Service Lab, 3041 Comwallis Rd, Research Triangle Park, NC
27709
J. Barnard (Foreword)
K.W. Stolte (Crown Condition Classification)
USDA Forest Service, Northeastern Area State and Private Forestry, Concord Mast Rd., Durham, NH
03824
S. Cox (Damage and Mortality Assessment)
I. Miller (Crown Condition Classification)
M. Miller-Weeks (Damage and Mortality Assessment)
USDA Forest Service, Northeastern Area, State and Private Forestry, 5 Radnor Corporation Center,
100 Matsomford Rd., Suite 200, Radnor, PA 19087
W. Burkman (Crown Condition Classification & Damage and Mortality Assessment)
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USDA Forest Service, Northeastern Area, State and Private Forestry, 1992 Folwell Ave., St. Paul, MN
55108
M. Mielke (Damage and Mortility Assessment)
USDA Forest Service, Forest Science Lab, 507 25th St. Ogden, UT 84401
W. McLain (Site Condition, Growth, and Regeneration)
P. Rogers (Site Condition, Growth, and Regeneration & Glossary)
USDA Forest Service, Research Lab, 5985 Highway K, Rhinelander, Wl 54501
J.G. Isebrands (PAR)
S. Steele (PAR)
J. Van Cleve (PAR)
USDI Bureau of Land Management, Oregon State Office, c/o U.S. EPA, EMSL-LV, 944 E. Harmon Ave.
Las Vegas, NV 89119
S. Cline (Vegetation Structure Indicator)
N. Tallent-Halsell (Logistics)
USDI Bureau of Land Management, Oregon State Office, c/o U.S. EPA, Environmental Reseach
Laboratory, 200 S.W. 35th St. Corvallis, OR 97333
M. Stapanian (Vegetation Structure Indicator)
U.S. EPA, U.S. Forest Service Lab, 3041 Cornwallis Rd, Research Triangle Park, NC 27709
S.A. Alexander (Foreword)
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ACRONYMS
3-D - three-dimensional
MS - atomic absorption spectrometry
BLM - Bureau of Land Management
DBH - diameter at breast height
DRC - diameter at root collar
EMAP - Environmental Monitoring and Assessment Program
EMSL-LV - U.S. EPA Environmental Monitoring Systems Laboratory in Las Vegas
EPA - Environmental Protection Agency
FIA - Forest Inventory and Analysis
FS - Forest Service
FY - fiscal year
FHM - Forest Health Monitoring
GIS - Geographic Information System
GMT - Greenwich Mean Time
GPS - Global Positioning System
ICP-OES - inductively coupled plasma-optical emission spectroscopy
ID - identification
IM - information management
IRC - independent regional coordinator
MEI - maximum expression of injury
MLRA - major land resource area
MQO - measurement quality objective
MSDR - measurement system detection reference samples
MSFD - measurement system field duplicate samples
NCSS - National Cooperative Soil Survey
PAR - photosynthetically active radiation
Pb - the element lead
PC - personal computer
PDR - portable data recorder
PL - Preparation Laboratory
PVC - polyvinyl chloride
QA • - quality assurance
QC - quality control
SA - selective availability
SCS - Soil Conservation Service
SOP - standard operating procedure
Sr - the element strontium
USDA - United States Department of Agriculture
USDI - United States Department of the Interior
USGS - United States Geological Survey
TVA - Tennessee Valley Authority
XRF - X-ray fluorescence spectroscopy
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ACKNOWLEDGEMENTS
Special appreciation goes to the following persons: E. Eastman for her assistance with the Foreword;
C. Chojnacky, C. Liff, W. McLain, P. Rogers, C. Scott, S. Solano and C. Bylin for their assistance with
Site Condition, Growth, and Regeneration; J. Van Cleve for his assistance with PAR; R. O'Brien and F.
Peterson for their assistance with the Vegetation Structure indicator; J. Peck, K. Heiman, S. Will-Wolf, D.
Cassell, R. Rosentreter, A. Debolt and numerous anonymous reviewers for their suggestions on the Lichen
Community method and manuscript. K. Stolte instigated the Lichen Community method by declaring the
need for a user-friendly method for studying lichen communities and initially sponsoring its development.
The rest of the FHM staff has been helpful, and the Lichen Community staff appreciate their efforts; D.L.
Cassell and J. Hazard for their overall statistical support; B. Conkling and F. Lopez for their overall
assistance and support; S. Burns for her excellent graphics assistance; and the staff of Applied Technology
Associates, Las Vegas, NV, without their valuable and expert word processing, graphics, and editing
support this document would never have been completed.
The following individuals are acknowledged for their review and subsequent suggestions and comments
on the methods and manuscript: S. Abboud (Alberta Research Council, Alberta, CAN), S. Alexander (U.S.
EPA), B. Anderson (USDA FS), C. Bylin (USDA FS), J. Bofinger (New Hampshire Division of Forest and
Lands), G. Canterbury (University of Montana), D. Cassell (USDI BLM), S. Cline (USDI BLM), G. Collins
(U.S. EPA), B. Conkling (North Carolina State University), J. Dale (USDA FS), W. Dorsey (Maryland Dept.
of Natural Resources), S. Draggan (U.S. EPA), A. Gillespie (USDA FS), J. Hyland (Alabama Forestry
Commission), W. Kinney (U.S. EPA), L. Kirkland (U.S. EPA), W. McLain (USDA FS), A. Pitchford (U.S.
EPA), R. Rhoades (USDA FS), P. Rogers (USDA FS), S. Solano (USDA FS), R. Schonbrod (U.S. EPA),
T. Scherbatskoy (University of Vermont), M. Stapanian (USDI BLM), C. Thomas (USDA FS), H. Trial (Maine
Forest Service), J. Vissage (USDA FS), L. Williams (U.S. EPA), S. Wilmont (Vermont Dept. of Forests,
Parks and Recreation), and numerous anonymous reviewers.
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GLOSSARY
Ambient Station - The place where the quantum sensors are set up to measure incoming light in a forest
opening or unshaded area.
Annular Subplot - The area ranging from 24.0 ft (7.32 m) and 58.9 ft (17.95 m) around each subplot center,
designated for potentially destructive sampling procedures. Some destructive sampling is restricted to a
smaller area within the annular plot (45.0-58.9 ft) to avoid damaging the environment at the subplot
perimeter.
Baseline - A method employed in plot establishment to determine actual photo scale in the vicinity of the
plot by measuring the distance on the ground between two visible points on the photo. See Section 1, Plot
Establishment for a step by step procedure.
Beam Fraction - The percentage of light that is direct sunlight, not diffuse. It is a measure of cloudiness.
Bioindicators - Plant species that are sensitive to ozone and exhibit visible symptoms of injury.
Ceptometer - An instrument used to measure PAR under canopy.
Condition Boundary - A boundary established by the field crew to delineate between two distinct condition
classes encountered on a plot (see Condition Class). Multiple condition boundaries may be established
by a field crew. Boundaries should always be documented on the plot sketch map. Additionally,
boundaries which cross subplots or microplots are further documented in the PDR.
Condition Class - A spatial representation of present environmental conditions on the plot in terms of five
key land cover variables: Land Use, Forest Type, Stand Origin, Stand Size, and Past Disturbance. New
condition classes are assigned when one or more of these variables changes. Except for urban land uses,
a condition must be at least an acre in size to be recognized as a distinct condition. Condition classes are
numbered sequentially as they are encountered on the plot and referenced by that same code on
subsequent encounters.
Cover (canopy cover) - The area described by individual plant canopies within or overlapping the sampling
area. Canopies are visualized as polygons that are vertically projected to the ground surface to determine
the percent of the quadrat area (1 m2) covered by each plant species in the stratum (see also Crown
Cover).
Crown - The foliated portion of a tree or other plant.
Crown Cover - An area percentage of ground obscured by plant cover when viewed from above. When
associated with a specific area (i.e., a plot or quadrat), stems of plants do not necessarily have to fall within
that area for portions of the plant to be counted.
Crustose - A crust-like growth form of lichen that is tightly appressed to the substrate, like paint, and
generally attached by all of the lower surface.
Dead Tree - Any dead tree standing upright and being greater than 5 inches DBH. Stumps or broken trees
less than 4.5 feet in height are not recorded as dead trees.
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DBH - Diameter at Breast Height. Normally this diameter measurement is taken 4.5 ft (1.37 m) above the
forest floor on the up hill side of the tree. Adjustments are made for bole irregularities (see DBH,
Section 1).
Destructive Sample - Any sampling method which involves sampling activities that are potentially damaging
to the vegetation from which the samples were extracted.
DRC - Diameter at Root Collar. This was designed as a multi-stem equivalent of the DBH whereby all
stems of woodland species trees (marked by "ww" in the species list) are measured at their base and
aggregated into a single value using the formula shown in the DRC section of the field guide.
EMAP - Environmental Monitoring and Assessment Program. A program within the Environmental
Protection Agency set up to undertake long term monitoring and evaluation of ecosystems. EMAP-Forests
with FHM form one of multiple ecosystems that fall under the EMAP umbrella.
FHM - Forest Health Monitoring. A National program for monitoring the long term health of the nation's
forest ecosystems. This program is sponsored jointly by the Environmental Protection Agency and the U.S.
Forest Service in cooperation with the National Association of State Forester and other state, federal, and
private organizations.
FIA - Forest Inventory and Analysis. A program within U.S. Forest Service Research assigned the task
of measuring and analyzing forest resources at the State, Regional, and National levels.
Foliose - A "leaf-like" growth form of lichen that is essentially two-dimensional, and is usually made up of
repeatedly branching lobes, and has a definite upper and lower surface.
Forest - Land which is at least 10% stocked with any combination of trees found in the FHM species list
AND at least one acre in size. Adjacent nonforest inclusions less than one acre in size are considered
forest land.
Forest Type - A grouping, or association, of species which comprise plurality of stocking on a given site
at the present time. Forest type is most often selected from the species which make up the forest canopy,
not the understory. In cases of recent disturbance, forest type may be determined from the current
regeneration.
Fruticose - A three-dimensional growth form of lichen including forms that are pendulous and stringy,
upright, or shrub-like.
Hex - A 40° km2 hexagon which surrounds the sample point. The data collected on the plot, in many
cases, are expanded to represent the entire area of the hexagon. This hexagon is the fundamental unit
for the EMAP sample grid.
Hex Number - A unique seven digit code representing the sample plot and ail data collected on that plot.
Improved Road - This is a road that is graded, ditched, or otherwise maintained as a permanent travel
route. For the purpose of FHM field plots, improved roads will be considered an urban land use because
reforestation is actively being prevented.
Indicator - A characteristic of the environment that, when measured, quantifies the magnitude of stress,
habitat characteristics, degree of exposure to the stressor, or degree of ecological response to the
exposure. Indicators may be of a biotic or abiotic nature.
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Interveinal - Between veins on the leaves of plants. In terms of bioindicators, this is the area of the upper
leaf surface where symptoms of ozone injury are most often observed.
Land - This includes (1) areas of dry ground temporarily or partly covered by water, such as marshes,
swamps, and river flood plains; (2) streams, sloughs, estuaries and canals less than 120 ft in width; and
(3) lakes, reservoirs, and ponds smaller than 1 acre in size. Land/Water boundaries for larger bodies of
water (> 1 acre) should always be established at the high water mark.
Leaf Area Index (LAI) - The canopy leaf area per unit of ground area. It is an index of forest health and
productivity.
Lichen - A lichen is a symbiotic association between a fungus and a photosynthetic partner (either green
algae or cyanobacteria).
Lichen Plot - The area to be sampled for lichen communities. For standard FHM plots, the lichen plot is
a circular area with a 120-foot radius centered on subplot 1, but excluding the four subplots. The area of
the lichen plot is 0.378 hectares or 0.935 acres.
Macrolichen - Foliose and fruticose lichens.
Microplot - A circle offset 90° and 12 ft (3.66 m) from each subplot center for the purpose of measuring
understory vegetation and regeneration trees (i.e., saplings and seedlings). The microplot is 6.8 ft (2.07
m) in radius. It is .offset to minimize trampling damage on the microplot.
Monitoring - The collection of information over time to determine the effects of resource management and
to identify changes in natural systems.
Mortality Tree - A standing or downed tree (1.0 inches DBH/DRC a larger) that was sampled at the
previous inventory, but no longer has any living tissue above 4.5 ft.
Nonforest - (see also Forest Land) This is land that (1) has historically not supported forests (e.g., barren,
alpine tundra); (2) was formerly forested, but has been converted to a nonforest land use (e.g., cropland,
lawn, or improved pasture);'or (3) presently meets the stocking requirements for forest land, but human
activity on that land prevents natural succession of the site (e.g., golf courses, cemeteries, urban parks and
picnic grounds, and forested home sites with lawns). Other nonforested conditions include a land use or
corridor of any width maintained by humans as a long-term nonforested site. Examples of these conditions
include right-of-ways for improved roadways, rail lines, canals, powerlines (above and below ground), and
pipelines.
Non-Stocked Forest Land - Formerly forested land which (1) recently met the stocking and/or regeneration
requirements of forested land; (2) does not meet those requirements because trees have temporarily been
removed or destroyed; and (3) has the potential to regenerate to forest because there are no conflicting
land uses. Examples of non-stocked forests include incidents of recent clearcutting, fire, or windthrow.
Off-plot - The area outside of the sample hectare (186.2 ft radius from plot center).
Off-frame - Generally refers to FHM activities which take place off of the network of regular field plots, and
not associated with any particular hex centers. Off-frame work is usually done at experimental sites in
conjunction with indicator development and testing.
On-Plot - The area within the sample hectare (186.2 ft radius from plot center). See Off-Plot.
xviii
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EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page xix of xx
Ozone - A gaseous air pollutant that causes injury to sensitive plants, also known as bioindicators. Ozone
is taken in through the stomata of susceptible plants causing visible damage to the upper leaf surface.
PAR - Photosynthetically Active Radiation. The portion of light spectrum that plants use for photosynthesis.
FHM uses the percent transmitted PAR (ratio of PAR under the canopy to the ambient, incoming PAR at
the site) and the calculated leaf are a index.
Pathogen - An organism capable of causing disease.
PDR - Portable Data Recorder. The PDR is the primary field tool used by crews to record and download
data for future analysis.
Phenological Status - Presence and condition of flowers, fruits, and leaves.
Plot Center - The center point of the FHM field sample, also known as subplot #1, point #1, or location
center. •
Quadrat Frame - A collapsible square frame made of plastic pipe that defines the perimeter of a quadrat.
Each side of the frame is 1 m long.
Quantum Sensor - A device that measures the quantity of light reaching its surface.
Remeasurement - Any plot visit, excepting the initial plot establishment, conducted for the purpose of
gathering comparative data to previous visits. Multiple remeasurements allow analysts to assess changes
in forest conditions over time.
Reserved Forest Land (Timberland) - Land reserved from wood products utilization by statute or
administrative designation. Some examples of reserved forest land are National Parks, wilderness areas,
state, county, municipal, and other lands expressly prohibiting wood product extraction.
Reference Point (RP) - A prominent tree, or other landmark, which is easily detected on an aerial
photograph and on the ground. The reference point (also called Starting Point) is most commonly used
as the point of origin for chaining into the plot center. Remeasurement crews begin their search for the
plot center by first locating the reference point.
Sapling - A live tree at least 1.0 inch (2.54 cm) and less than 5.0 inches (12.7 cm) DBH/DRC.
Appendix A lists all FHM tree species measured for both timberland and woodland.
Seedling - A live tree less than 1.0 inches DBH/DRC and greater that 12 inches in height is a seedling.
Trees less than 12 inches in height are considered seedlings as part of understory vegetation coverage
estimate. Appendix A lists all FHM tree species measured for both timberland and woodland.
Specimen Tree - Trees systematically selected by the field crew within the annular plot expressly for the
purpose of destructive sampling.
Specimen, Vegetation - A sample of an unknown that is collected pressed and shipped to a herbarium for
identification. Vegetation specimens are collected outside of the quadrats.
Starting Point (SP) - See Reference Point.
xix
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EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page xx of xx
Stipple - Pigmented spots (up to a few millimeters in diameter) suggesting ozone damage to bioindicator
plants. Stipples are generally observed on the upper surface of leaves.
Stocking - An expression of the extent to which growing space is effectively utilized by trees.
Stratum - (plural: strata) A class of vegetation height in which vegetation structure measurements are
obtained (e.g., 0-2 ft, 2-6 ft, 6-16 ft, and > 16 ft). Vegetation measurements are obtained within each
stratum in each quadrat.
Subplot - The basic sampling unit for trees 5.0 in DBH and larger on an FHM plot. Each of four subplots
is 1/24 acre (1/60 hectare) in area, and 24.0 feet in radius (7.32 meters). Subplot 1 is located at the plot
center, while the remaining three subplots are located 120 ft (36.6 cm) and 360° (#2), 120° (#3), and 240°
(#4) from the plot center (see Figure 1.1).
Substrate (ground substrate) - Organic and inorganic material on the ground within the vegetation quadrat.
Examples include: mineral soil, rock, water, dead wood (> 10 cm), litter and branches (< 10 cm), exposed
roots, roads, dung, and trash.
Timberland Species - These are tree species commonly having a dominant single stem at the base which
are traditionally measured at breast height. Appendix A lists all FHM tree species measured for both
timberland and woodland.
Tree - Any tree at least 5.0 inches (12.7 cm) DBH/DRC. See Timberland and Woodland Species for further
clarification.
Unimproved Road - A road which is not periodically maintained as a transportation route (see Improved
Road). An unimproved road is considered the same condition as the area surrounding it. If the road acts
as a boundary between forest and non-forest conditions, it is considered a transition zone in which a forest
may reestablish itself, and is therefore part of the adjacent forested condition.
Voucher Leaf Samples - Three leaves with ozone injury that are collected from a bioindicator plant,
pressed, and mailed to the national ozone indicator lead (Gretchen Smith).
Water- As a land use classification, water is defined as streams, sloughs, estuaries, and canals more than
120 feet (36.6 m) in width; and lakes, reservoirs, and ponds more than 1 acre in size.
Witness Trees - Trees to which distances and azimuths are recorded for the purpose of relocating a
particular point on the ground. In addition to plot centers, witness trees may be used to monument starting
points and intermediate points along the course to plot center.
Woodland - Forest land with 10 percent or more crown cover in (1) woodland species, or (2) timber species
and woodland species, but less than 5 percent crown cover in timber species; or forest land with sufficient
woodland species reproduction (minimum of 40 seedlings/saplings per acre).
Woodland Species - These are tree species commonly having multiple stems near their base, or those
which have a typical morphology not conducive to measuring diameters a breast height. These species
are measured using a diameter at root collar formula (DRC), which accounts for multiple stems originating
at a single base, as a DBH equivalent. Appendix A lists all FHM tree species measured for both timberland
and woodland.
xx
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 1 of 86
Section 1. Site Condition, Growth, and Regeneration
Section/Title
1.0 Quick Reference Tally PDR Screens 2 of 86
1.1 Overview 9 of 86
1.1.1 Scope and Application 9 of 86
1.1.2 Summary of Method 9 of 86
1.1.3 Interferences 10 of 86
1.1.4 Safety 10 of 86
1.2 Sample Collection, Preservation, and Storage 10 of 86
1.3 Equipment and Supplies 11 of 86
1.4 Calibration and Standardization 12 of 86
1.5 Quality Assurance 12 of 86
1.5.1 Measurement Quality Objectives 12 of 86
1.5.2 Method Performance 19 of 86
1.5.3 Corrective Action 19 of 86
1.6 Procedures 19 of 86
1.6.1 Permanent Plot Design and Forest Plot Establishment 21 of 86
1.6.1.1 Plot Design "! 21 of 86
1.6.1.2 Forest Plot Establishment 21 of 86
1.6.2 Plot-Level Data 25 of 86
1.6.2.1 Plot-Level Notes 25 of 86
1.6.2.2 Plot Identification 25 of 86
1.6.2.3 Condition Classification 29 of 86
1.6.2.4 Site-Tree Data 34 of 86
1.6.3 Point-Level Area Descriptors 37 of 86
1.6.3.1 Point Description 37 of 86
1.6.3.2 Boundary Delineation 41 of 86
1.6.4 Microplot Understory Vegetation 44 of 86
1.6.5 Microplot Tree Data 46 of 86
1.6.5.1 Seedlings 46 of 86
1.6.5.2 Saplings 48 of 86
1.6.6 Subplot Tree Data 57 of 86
1.6.7 Full-Hectare Plots (CA/PNW PS only) 66 of 86
1.6.7.1 Full-Hectare Boundary Delineation (CA/PNW PS Only) .- 66 of 86
1.6.7.2 Full-Hectare Large-Tree Cruise (CA/PNW PS Only) 68 of 86
1.6.7.3 Full-Hectare Mortality Plot (CA/PNW PS Only) 72 of 86
1.6.8 Nonforest/Access Denied/Dangerous Plots 75 of 86
1.6.8.1 Plot-Level Notes 75 of 86
1.6.8.2 Plot Identification 75 of 86
1.6.9 Offset Procedures 78 of 86
1.7 References 85 of 86
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 2 of 86
1.0 Quick Reference Tally PDR Screens
Table 1-1. Plot-Level Note Screen (Subsection 1.6.2.1)
Measurement Variable
Notes
PDR Prompt
(Notes)
Meas. Meas. Meas. Page
Type 1 Type 2 Type 3
x x, D Sec. 1, p.25
Table 1-2. Plot Identification Screen (Subsection 1.6.2.2)
Measurement Variables
State
County
Hexagon Number
Plot Number
Project
QA status
Crew Type
Measurement Type
Old Plot Status
Current Plot Status
Month
Day
Year
Elevation
Tally! -TallyS
Interim Disturbance 1-3
Interim Disturbance Year 1-3
'Only on newly forested plots.
Table 1-3. Condition Classification
Measurement Variables
Condition Class Change
Condition Class
Land Use Class
Forest Type
Stand Origin
Stand Size
Past Disturbance 1
Disturbance Year 1
Past Disturbance 2
Disturbance Year 2
Past Disturbance 3
Disturbance Year 3
Previous Stand Age
Stand Age
PDR Prompt
(State)
(Cnty)
(Hex Num)
(Plot Num)
(Project)
(QA Stat)
(CrewTyp)
(MeasTyp)
(OldStat)
(CurStat)
(Month)
(Day)
(Year)
(Elev)
(Tally!.. .5)
(Dstrbl...3)
(DstYrL.3)
Screen (Subsection 1.6.2.3)
PDR Prompt
(CC_Chg)
(CndCIs)
(LU CIs)
(ForTyp)
(StdOrg)
(StdSize)
(Dstrbl)
(DstYrl)
(Dstrb2)
(DstYr2)
(DstrbS)
(DstYrS)
(PrAge)
(StAge)
Meas. Meas. Meas.
Type 1 Type 2 Type 3 Page
x D D 25,App.B
x D D 25,App.B
x D D 25
x D D 25
x x x 25
x x x 25
x x x 26
x x x 26
D D 26
x x x 26
x x x 27
x x x 27
x x x 27
x x1 27
x x x 27
x 28
x 28
Meas. Meas. Meas. Page
Type ! Type 2 Type 3
x 30
x x1 30
x x1 30,App.D
x x1 30,App.C
x x' 31
x x' 31
x x 3!
x x 32
x x 32
x x 32
x x 32
x x 32
D 32
x x 32
'These data are supplied on computer-generated plot maps.
-------
EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 3 of 86
Table 1-4. Site-Tree Screen (Subsection 1.6.2.4)
Measurement Variables
Tree Type
Site-Tree History
Tree Number
Point Number
Previous Condition Class
Condition Class
Species
Old DBH
DBH
DBH Check
Horizontal Distance
Azimuth
Crown Class
Tree Height
Tree Age at DBH
Notes
Description
Competing Basal Area
Crown Diameter Wide
Crown Diameter 90°
Live Crown Ratio
Crown Density
Crown Dieback
Foliage Transparency
Location 1...3
Damage 1 ...3
Severity 1...3
'Age is not recorded for downloaded
Table 1-5. Point-Level Descriptors
Measurement Variables
Previous Point History
Point History
Slope Correction
Percent Slope
Aspect
Terrain Position
Subplot Condition List
Subplot Center Condition
Microplot Center Condition
Subplot Offset
Microplot Offset
PDR Prompt
(TreeTyp)
(SitHist)
(Tree#)
(Point*)
(PrCndCI)
(CondCIs)
(Sped)
(PrDBH)
(DBH)
(DBHChk)
(HDist)
(Azi)
(Crown Cl)
(TotHt)
(DbAge)
(Notes)
(Desc)
(CmpBA)
(CrDiaW)
(CrDia9)
(CRatio)'
(CrnDen)
(CrnDbk)
(FolTrn)
(Locatnl ..3)
(Damag1..3)
(Sevrty1..3)
trees. It is computed at processing.
Screen (Subsection 1.6.3)
PDR Prompt
(PrPnHst)
(PnHst)
(SICor)
(%Slope)
(Aspct)
(TerrPos)
(SbCdList)
(SbCtrCd)
(MpCtrCd)
(SbOffst)
(MpOffst)
Meas.
Typel
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Meas.
Type 1
X
X
X
X
X
X
X
X
X
X
Meas. Meas.
Type 2 Type 3
X
X
D
x,D
D
X
x,D
D
X
X
x,D
x,D
X
X
X1
x,D
x,D
X
X
X
X
X
X
X
X
X
X
Meas. Meas.
Type 2 Type 3
D
X
D x,D
X1
X1
X1
X2
X2
X2
D x,D
D x,D
Page
34,57
34
35
35
35
35
35
35
35,57
35,57
35
35
35,57
35
35
36
36
36
Sec.2, p. 14
14
19
19
21
21
Sec. 3, p.3-5
3-8
3-12
Page
37
37
37
37
38
38
39
39
39
39,78
40,78
1 Only on newly forested points.
2 These data are supplied on computer-generated plot maps.
-------
EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 4 of 86
Table 1-6. Boundary Delineation Screen (Subsection 1.6.3.2)
Measurement Variables
Boundary Change
Plot Type
Offset Point
Contrasting Condition
Left Azimuth
Left Distance
Comer Azimuth
Comer Distance
Right Azimuth
Right Distance
PDR Prompt
(Bd Chg)
(PlotTyp)
(OffstPt)
(Contend)
(LftAz)
(LftDs)
(CnrAz)
(CnrDs)
(RgtAz)
(RgtDs)
Meas.
Typel
X
X
X
X
X
X
X
X
X
Meas. Meas.
Type 2 Type 3
X
, X1
X1
X1
X1
X1
X1
X1
X1
x'
Page
42
42
42
43
43
43
43
43
43
43
'These data are supplied on computer-generated plot maps.
Table 1-7. Understory Vegetation
Measurement Variables
Percent Moss
Percent Lichens
Percent Ferns
Percent Herbs
Percent Shrubs
Percent Seedlings
Screen (Subsection 1.6.4)
PDR Prompt
(%Moss)
(%Lichn)
(%Fems)
(%Herbs)
(%Shrubs)
(%Seeds)
Meas.
Type 1
X
X
X
X
X
X
Meas. Meas.
Type 2 Type 3
X
X
X
X
X
X
Page
44
44
44
44
44
45
Table 1-8. Mlcroplot Seedling Screen (Subsection 1.6.5.1)
Measurement Variables
Species
Condition Class
Crown Class
Seedling Count
Crown Vigor
PDR Prompt
(Speci)
(CondCIs)
(CrownCI)
(#Seeds)
(CrnVigr)
Meas.
Type 1
X
X
X
X
X
Meas. Meas.
Type 2 Type 3
X
X
X
X
X
Page
46,App.A
46
46
47
Sec.2, p. 11
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 5 of 86
Table 1-9. Microplot Sapling Screen (Subsection 1.6.5.2)
Measurement Variables
Tree Number
Previous Condition Class
Condition Class
Offset Point
Old Tree History
Last Tree History
Current Tree History
Fader (CA)
Species
Old DBH
DBH
DBH Check
Live/Dead (CA PNW PS)
Old Stem Count (W)
Stem Count
Old Diameter at Root Collar (W)
Diameter at Root Collar
Horizontal Distance
Azimuth
Estimated Mortality Year (CA/PNW)
Mortality Year
Nonforest Year
Ground Year
Cause of Death
Crown Class
Notes
Description
Crown Vigor
Crown Diameter Wide (CA/PNW PS)
Crown Diameter 90° (CA/PNW PS)
Live Crown Ratio
Crown Density (CA/PNW PS)
Crown Dieback (CA/PNW PS)
Foliage Transparency (CA/PNW PS)
Location 1...3
Damage 1...3
Severity 1..3
Live Tree (CA/PNW PS)
Cause of Death (CA/PNW PS)
PDR Prompt
(Tree#)
(PrCndCI)
(CondCIs)
(OffstPt)
(OldHst)
(LstHst)
(SapHst)
(Fader)
(Spec!)
(PrDBH)
(DBH)
(DBHChk)
(Live)
(PrtfStems)
(Stems)
(PrDRC)
(DRC)
(HDist)
(Azi)
(EMortYr)
(MortYr)
(NonFYr)
(GmdYr)
(Cause)
(CrownCI)
(Notes)
(Desc)
(CrnVigr)
(CrDiaW)
(CrDiaQ)
(CRatio)
(CrnDen)
(CrnDbk)
(FolTrn)
(Locatn1..3)
(Damag1..3)
(Sevrty1..3)
(Live)
(Caus1.2)
Meas.
Type 1
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Meas.
Type 2
D
D
D
D
X
D
D
D
D
D
D
X
X
X
X
X
x,D
x,D
X
D
X
X
X
Meas.
TypeS
D
D
X
x,D
D
D
X
X
x,D
D
X
X
D
X
D
X
x,D
x,D
X
X
X
X
X
x,D
x,D
X
X
X
X
X
X
X
X
X
X
Page
Sec.3, p.48
48
48
48,78
48
48
48
50
SO.App.A
50
51
52
52
53
53
53
53
54
55
55
55
55
55
55
56
56
56
Sec.2, p. 12
14
14
19
19
21
21
Sec.3, p.5
8
12
20
20
-------
EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 6 of 86
Table 1-10. Subplot Tree Screen (Subsection 1.6.6)
Measurement Variables
Tree Number
Previous Condition Class
Condition Class
Offset Point
Old Tree History
Last Tree History
Current Tree History
Fader (CA/PNW PS)
Species
Old DBH
D8H
DBH Check
Live/Dead (CA PNW PS)
Old Stem Count (W)
Stem Count (W)
CHd Diameter at Root Collar (W)
Diameter at Root Collar (W)
Horizontal Distance
Azimuth
Estimated Mortality Year (CA/PNW)
Mortality Year
Nonforest Year
Ground Year
Cause of Death
Crown Class
Notes
Description
Crown Diameter Wide
Crown Diameter 90"
Liva Crown Ratio
Crown Density
Crown Dieback
Foliage Transparency
Location 1...3
Damage 1 ...3
Severity 1...3
Cause of Death (CA/PNW PS)
PDR Prompt
(Tree*)
(PrCndCI)
(CondCIs)
(OffstPt)
(OldHst)
(LstHst)
(TrHist)
(Fader)
(Speci)
(PrDBH)
(DBH)
(DBHChk)
(Live)
(PrtfStems)
(#Stems)
(PrDRC)
(DRC)
(HDist)
(Azi)
(EMortYr)
(MortYr)
(NonFYr)
(GmdYr)
(Cause)
(CrownCI)
(Notes)
(Desc)
(CrDiaW)
(CrDia9)
(CRatio)
(CrnDen)
(CrnDbk)
(FolTrn)
(Locatn1..3)
(Damag1..3)
(Sevrty 1..3)
(CausL. 2)
Meas.
Typel
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Meas.
Type 2
D
D
D
D
X
D
D
D
D
D
D
X
X
X
X
X
x,D
x,D
D
D
D
X
X
X
X
X
X
Meas.
TypeS
D
D
X
x,D
D
D
X
X
x,D
D
X
X
D
X
D
X
x,D
x,D
X
X
X
X
X
x,D
x,D
X
X
X
X
X
X
X
X
X
Page
57
57
57
57
57
57
57
59
59, App.A
60
60
61
61
61
61
61
61
62
62
63
63
63
63
63
63
64
65
Sec.2, p. 14
14
19
19
21
21
5
8
12
20
-------
EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 7 of 86
Table 1-11. Full-Hectare Boundary Screen (CA/PNW PS Only) (Subsection 1.6.7)
Measurement Variables
Hectare Center Condition
Hectare Contrasting Condition
Left Azimuth
Corner Azimuth
Corner Distance
Right Azimuth
Table 1-12. Full-Hectare Tree Screen
Measurement Variables
Hectare Tree Type
Tree Number
Previous Condition Class
Condition Class
Tree Location
Old Tree History
Current Tree History
Species
Old DBH
DBH
DBH Check
Point Number
Horizontal Distance
Azimuth to nearest point
Mortality Year
Nonforest Year
Ground Year
Cause of Death
Crown Class
Notes
Description
Crown Vigor
Crown Diameter Wide (CA/PNW PS)
Crown Diameter 90° (CA/PNW PS)
Live Crown Ratio
Crown Density (CA/PNW PS)
Crown Dieback (CA/PNW PS)
Foliage Transparency (CA/PNW PS)
Location 1...3
Damage 1 ...3
Severity 1..3
PDR Prompt
(CtrCd)
(Contend)
(LftAz)
(CnrAz)
(CnrDs)
(RgtAz)
(CA/PNW PS Only) (Subsection
PDR Prompt
(HTrTyp)
(Tree*)
(PrCndCI)
(CondCIs)
(TrLoc)
(OldHst)
(SapHst)
(Sped)
(PrDBH)
(DBH)
(DBHChk)
(Point*)
(HDist)
(Azi)
(MortYr)
(NonFYr)
(GrndYr)
(Cause)
(CrownCI)
(Notes)
(Desc)
(CrnVigr)
(CrDiaW)
(CrDia9)
(CRatio)
(CrnDen)
(CrrtDbk)
(FolTrn)
(Locatn1..3)
(Damag1..3)
(Sevrty1..3)
Meas.
Typel
X
X
X
X
X
X
1.6.7.2)
Meas.
Type 1
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Meas. Meas.
Type 2 Type 3
x,D
x,D
x,D
x,D
x.D
x,D
Meas.
Type3
x,D
D
D
X
X
D
X
x,D
D
X
X
x,D
x,D
x,D
X
X
X
X
X
x,D
x,D
X
X
X
X
X
X
X
X
X
X
Page
67
67
67
67
67
67
Page
68
68
68
68
68
69
69
70,App.A
70,60
70,60
70,61
70
70
70
71,63
71,63
71,63
71,63
71,63
71,64
71,65
Sec.2, p. 12
14
14
19
19
21
21
5
8
12
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 8 of 86
Table 1-13. Full-Hectare Tree Mortality Screen (Subsection 1.6.7.3)
Measurement Variables
Hectare Tree Type
Condition Class
Tree Location
Mortality Status
Species
DBH
Point Number
Horizontal Distance
Azimuth
Mortality Year
Cause of Death (Primary)
Cause of Death (Secondary)
Notes
Description
PDR Prompt
(HTrTyp)
(CondCIs)
(TrLoc)
(MorStat)
(Speci)
(DBH)
(Point*)
(HDist)
(Azi)
(MortYr)
(Causl)
(Caus2)
(Notes)
(Desc)
Meas.
Type 1
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Table 1-14. Plot-Level Note Screen - Nonforested/Access Denied/Dangerous Plots (Subsection
Measurement Variable
Notes
1 Downloaded information is provided on
Table 1-15. Plot Identification Screen
Measurement Variables
State
County
Hexagon Number
Plot Number
Project
QA status
Crew Type
Measurement Type
CHd Plot Status
Current Plot Status
Month
Day
Year
Land Use at Point 1
Land Use at Point 2
Land Use at Point 3
Land Use at Point 4
PDR Prompt
(Notes)
hard copy.
Meas.
Typel
X
- Nonforested/Access Denied/Dangerous
PDR Prompt
(State)
(Only)
(Hex Num)
(Plot Num)
(Project)
(QA Stat)
(CrewTyp)
(MeasTyp)
(OldStat)
(CurStat)
(Month)
(Day)
(Year)
(CtrLUI)
(CtrLU2)
(CtrLUS)
(CtrLU4)
Meas.
Typel
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Meas.
Type 2
X
Meas.
TypeS
X
X
X
X
X
X
X
X
X
X
X
x,D
1.6.8.1)
Meas.
TypeS
x'
Page
~73
73,57
73
73
73,App.A
73,60
73
73
74
74
74,63
74,63
74,64
74,65
Page
75
Plots (Subsection 1 .6.8.2)
Meas.
Type 2
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Meas.
TypeS
X
X
X
X
X
X
X
X
x'
X
X
X
X
X
X
X
X
Page
76,25,App.B
76,25,App.B
76,25
76,25
76,25
76,25
76,26
76,26
76,26
76,26
76,27
76,27
76,27
76,App.D
76,App.D
76,App.D
76,App.D
'Downloaded information is provided on hard copy.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 9 of 86
1.1 Overview
1.1.1 Scope and Application
Estimation of growth (stand dynamics) and measurement of trees and stands (stand structure) are
important Forest Health Monitoring (FHM) program objectives. Stand dynamics includes three elements
that are important "indicators" of forest health: (1) rates of regeneration, (2) survivor growth, and (3)
mortality. These data are obtained by remeasuring trees on permanent plots through a series of
successive inventories (Husch et al., 1972). They are usually expressed in terms of numbers of trees,
basal area, or volume. Characterization of stand structure yields a snapshot of stand conditions at each
measurement interval. It embodies numerous parameters that describe the settings in which individual
trees or groups of trees exist. These parameters are generally area-based, either calculated directly from
the tree tally (e.g., stand density) or assigned by definition (e.g., terrain position). Data pertaining to stand
structure are valuable because they permit stratification of a forest into meaningful subgroups. An
additional objective of FHM site condition, growth, and regeneration measurements is providing a basic plot
framework upon which to conduct field activities associated with other forest health indicators not
traditionally associated with forest mensuration (i.e., vegetation structure, lichen communities, ozone
bioindicator species, and PAR). As such, these indicators can be directly correlated with stand dynamics
and stand structure.
1.1.2 Summary of Method
FHM sampling activities fall into three general categories. Measurement Type 1 (Mt1) describes
activities conducted when a portion of the national plot grid is activated the first time. At that time, all plots
are visited regardless of whether or not they are forested. In general, if any portion of a FHM plot is
forested, and access can safely be gained, that plot is a forest plot. If access is denied to an entire plot,
or it is hazardous to occupy an entire plot, or no portion of a plot is forested, that plot is a nonforest plot.
All FHM plots, both forested and nonforested, are revisited on a 4-year cycle in order to reconcile all
changes that have occurred since the previous survey. These subsequent 4-year remeasurements are
referred to as measurement type 3 (Mt3) surveys. In some regions, annual, interim, measurement type
2 (Mt2) surveys are conducted between Mt1 and Mt3 to update the tree crown and damage data for trees
tallied during the pervious years. Only plots which were determined to be forested during the Mt1/Mt3
years are visited during Mt2.
All FHM site condition, growth, and regeneration data; crown condition classification data (Section 2);
and damage and mortality assessment data (Section 3) are collected on portable data recorders (PDRs)
with the aid of a program called "Tally". The Tally program prompts crews to enter measurements as they
complete each plot. Tally incorporates numerous list, range, and logic checks to verify the accuracy of the
data. Lists of variable codes are described in this and subsequent sections and in the PDR help menu.
There are seven versions of Tally, each designed for specific regional and/or measurement type
variations.
1. New Eastern forest plots (Mt1/Mt3)
2. Mt2 (East)
3. Mt3 (East)
4. Nonforest/No access/dangerous plots (Mt1/Mt2/Mt3)
5. Mt1 Colorado (CO)
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 10 of 86
6. Mt1 California (CA)/Pacific Northwest Pilot Study (PNW PS)
7. Mt1 Minnesota (MN)
More than one version of Tally may be used for each of the three measurement types.
Mt1 Versions 1, 5, 6, and 7 are used to initially install forests plots in the eastern U.S., CO, CA,
PNW PS, and MN, respectively. Version 4 is used for all nonforested Mt1 plots regardless of
region.
Mt2 Version 2 is used for forested Mt2 plots. If a Mt2 plot that was previously forested has since
become nonforest, Version 4 is used rather than Version 2.
Mt3 Version 3 is used to remeasure previously established forested plots that are still forested. If
a previously forested plot has since become nonforest when approached for Mt3, Version 4
is used. If a plot which was previously recorded as being nonforest has since become forest,
Version 1 is used.
This section documents plot establishment and plot evaluation procedures associated with collecting
Tally data. These methods and procedures apply to the 1994 field season; they were compiled and
modified from the previous FHM Field Methods Guide (Conkling and Byers, 1993), U.S. Forest Service
Forest Inventory and Analysis (FIA) field guides (U.S. Department of Agriculture 1981; 1988; 1989a; 1989b;
1992; 1993), and from EPA-EMAP Standard Operating Procedures. The methods and procedures
described herein apply to field activities in all areas of the United States.
1.1.3 Interferences
Several uncontrollable environmental and site conditions have hindered or slowed Tally measurement,
including (1) poor weather conditions such as gusting wind, heavy rain, and dark overcast skies; (2) steep
and/or unstable slopes; (3) dense and diverse understory vegetation which constrains free movement upon
the plot; and (4) thick canopy immediately overhead that obscured clear view of plot. Suspend data
collection under severe weather conditions, such as strong winds and heavy rainfall. Review offset
procedures (Subsection 1.6.9) in applicable steep and/or unstable slopes.
1.1.4 Safety
No specialized safety precautions are necessary. Follow general safety precautions for conducting
fieldwork (See Appendix E).
1.2 Sample Collection, Preservation, and Storage
Tally protocols do not require the deliberate collection of samples, yet if a species is encountered which
is not listed in Appendix A and there is uncertainty whether it should be tallied as a tree, bring branch
samples of foliage from the plot to the State FHM Project Coordinator or Field Supervisor for identification.
Collect samples outside of the subplots from similar specimens and make a note to change the species
code later.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 11 of 86
1.3 Equipment and Supplies
The list below includes all equipment and supplies needed for two trained and certified persons to
perform all measurements described in this section. Equipment and supplies associated with PDRs are
discussed in FHM Field Methods Guide, Volume II. Regions using the metric system should use equipment
calibrated in metric units. Those using the English system will use equipment calibrated in English units.
Equipment:
1 first aid kit
2 hard hats
2 pocket-size field methods guides
2 compasses
2 clinometers (with percent scale)
2 prisms or angle gauges (10-factor English, 2.5 metric) (Mt1 and Mt3 only)
2 cruiser vests
• 1 utility belt
1 increment borer (with sheath) (Mt1 and Mt3 only)
1 hatchet and sheath
1 nail pouch
2 diameter tapes (with holder)
2 loggers tapes
1 loggers tape refill
1 clipboard
• 2 protractors
2 photo scales
Consumable Supplies:
tree tags and nails
tree paint (no lead or copper)
pins/stakes for subplot and microplot centers
blank 3.5-inch formatted disks for data transfer
disk mailers
Field Documentation:
For Plot Reconnaissance:
state maps with plot locations designated
county maps with plot locations designated
aerial photographs with plot locations designated
FHM program brochures for interested landowners
copies of completed landowner permission forms
starting-point notes from the previous visit (Mt2 and Mt3 only)
hand-sketched plot diagrams from the previous visit (Mt2 and Mt3 only)
For Data Collection:
• blank starting point notes
blank plot sketch maps
blank Tally sheets for use in the event of PDR failure
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 12 of 86
• hard copy of downloaded data (Mt2 and Mt3 only)
• computer-generated plot diagrams (Mt2 and Mt3 only)
1.4 Calibration and Standardization
Purchase tapes to required specifications. Tapes should be maintained in working order and do not
require calibration. Check the compass regularly against known directions. In the field, avoid magnetic
interference. Use the compass without correction for declination (magnetic north). Check PDR functions
prior to departing for field. Include backup battery with supplies in case of primary battery failure.
1.5 Quality Assurance
1.5.1 Measurement Quality Objectives
Table 1-16 displays the Measurement Quality Objectives (MQOs) associated with the forest site
condition, growth, and regeneration data. The table lists the bounds of accuracy that are considered
acceptable with respect to data measurement or observation. Variable names are given in the first column,
reporting units in the second column, and the Data Quality Limits (DQLs) in the third column.
Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives
Variables
Reporting Units
Data Quality Limits
PLOT IDENTIFICATION (FOREST)
State
County
Hexagon Number
Plot Number
Measurement Type
Project
QA Status
Crew Type
Old Plot Status
Current Ptot Status
Month
Day
Year
Elevation
Tally 1-5
Interim Disturbance
Disturbance Year
FIPS codes
FIPS codes
EMAP hex code
number
3 classes
2 classes
3 classes
2 classes
3 classes
6 classes
12 classes
31 classes
31 classes
100 ft (10 m)
FHM code
17 classes
years
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
95% agreement
NA, crew dependent
NA, crew dependent
99% agreement
90% @ +1 - 200 ft (100 m)
NA, crew dependent
90% agreement
90% @ + / - 2 years
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 13 of 86
Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives
Variables
Reporting Units
Data Quality Limits
CONDITION CLASSIFICATION
Condition Class Change
Condition Class
Land Use Class
Forest Type
Stand Origin
Stand Size
Past Disturbance
Disturbance Year
Previous Stand Age
Stand Age
SITE-TREE DATA
Site-tree History
Tree Type
Tree Number
Point Number
Previous Condition Class
Condition Class
Species
Old DBH
DBH
DBH Check
Horizontal Distance
Azimuth
Crown Class
Tree Height
Tree Age at DBH
Notes
Description
Competing Basal Area
2 classes
9 classes
15 classes
122 classes
3 classes
4 classes
17 classes
years
years
years
3 classes
2 classes
'number
4 classes
9 classes
9 classes
314 classes
0.1 in (0.1 cm)
0.1 in (0.1 cm)
3 classes
0.1 ft (0.1 m)
1°
5 classes
1 foot (0.5 m)
years
2 classes
alphabetic field
ff/ac (m2/ha)
90% agreement
NA, arbitrary value
90% forest vs nonforest
90% agreement to broad type
90% agreement
85% agreement
85% agreement
85% @ + / - 2 years
NA, downloaded
85% @ + / -10 years
95% agreement
90% agreement
NA, downloaded
NA, arbitrary
NA, downloaded
95% agreement
95% to genus, 90% to species
NA, downloaded
90% @ + / - 5% of True DBH
90% agreement
90% @ + / - 1 ft (0.3 m)
90% @ + / - 10°
85% agreement
90% @ + / - 3% of True Site
Tree Height
90% @ + / - 5 years
NA, discretionary
NA, discretionary
90% @ + / - 20 sq ft (5 sq m)
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 14 of 86
Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives
Variables
POINT DESCRIPTION
Previous Point History
Point History
Slope Correction
Percent Slope
Aspect
Terrain Position
Subplot Condition List
Subplot Center Condition
Microplot Center Condition
Subplot Offset
Microplot Offset
BOUNDARY DELINEATION
Boundary Change
Plot Type
Offset Point
Contrasting Condition
Left Azimuth
Left Distance
Comer Azimuth
Comer Distance
Right Azimuth
Right Distance
MICROPLOT UNDERSTORY VEGETATION
Percent Moss
Percent Lichens
Percent Ferns
Percent Herbs
Percent Shrubs
Percent Seedlings
Reporting Units
2 classes
2 classes
0.1 ft (0.1 m)
1 percent
1"
7 classes
9 classes
9 classes
9 classes
2 classes
2 classes
2 classes
2 classes
5 classes
9 classes
1°
0.1 ft (0.5 m)
1°
0.1 ft (0.5 m)
1°
0.1 ft (0.5m)
5% classes
5% classes
5% classes
5% classes
5% classes
5% classes
Data Quality Limits
NA, downloaded
90% agreement
90% @ + / - 1 ft (0.3
90%@+/-10%
90% @ + / - 30°
90% agreement
90% agreement
90% agreement
90% agreement
90% agreement
90% agreement
90% agreement
95% agreement
90% agreement
90% agreement
90% @+ 7-15°
90% @ + / - 1 ft (0.3
90% @ + /- 15°
m)
m)
90% @ + 1 - 5 ft (2 m)
90% @ + /- 15°
90% @ + / - 1 ft (0.3
90% @ + / - 20%
90% @ + / - 20%
90% @ + / - 20%
90% @ + / - 20%
90% @ + / - 20%
90% @ + / - 20%
m)
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 15 of 86
Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives
Variables
MICROPLOT SEEDLINGS
Species
Condition Class
Crown Class
Seedling Count
Crown Vigor Class
MICROPLOT SAPLINGS
Tree Number
Previous Condition Class
Condition Class
Offset Point
Old Tree History
Last Tree History
Current Tree History
Fader (CA)
Species
Old DBH
DBH
DBH Check
Old Stem Count
Stem Count
Old DRC
DRC
Horizontal Distance
Azimuth
Mortality Year
Est. Mortality Year (CA)
Nonforest Year
Ground Year
Cause of Death
Crown Class
Notes
Description
Reporting Units
314 classes
9 classes
5 classes
number
3 classes
number
9 classes
9 classes
5 classes
1 4 classes
1 4 classes
1 4 classes
2 classes
314 classes
0.1 in (0.1 cm)
0.1 in (0.1 cm)
3 classes
number
number
0.1 in
0.1 in (0.1 Cm)
1 ft (0.5 m)
1°
year
year
year
year
year
5 classes
2 classes
alphabetic field
Data Quality Limits
90% to genus, 80% to species
90% agreement
85% agreement
90% @ + / - 3
90% agreement
NA, downloaded
NA, Downloaded
90% agreement
90% agreement
NA, downloaded
NA, downloaded
95% agreement
90% agreement
95% to genus, 85% to species
NA, downloaded
90% @ + / - 5% of True DBH
85% agreement
NA, downloaded
85% agreement
NA, downloaded
85% @ + / - 0.2 in (0.5 cm)
90% @ + / - 1 ft (0.3 m)
90% @ + /- 10°
85% @ + / - 2 years
85% @ + / - 2 years
85% @ + / - 2 years
85% @ + / - 2 years
85% agreement
85% agreement
NA, discretionary
NA, discretionary
-------
EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 16 of 86
Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives
Variables
SUBPLOT TREES
Tree Number
Previous Condition Class
Condition Class
OHset Point
Old Tree History
Last Tree History
Current Tree History
Fader (CA)
Species
Old DBH
OBH
DBH Check
Old Stem Count
Stem Count
OldDRC
DRC
Horizontal Distance
Azimuth
Mortality Year
Est. Mortality Year (CA)
Nonforest Year
Ground Year
Cause of Death
Crown class
Notes
Description
Reporting Units
number
9 classes
9 classes
5 classes
14 classes
1 4 classes
1 4 classes
2 classes
314 classes
0.1 in (0.1 cm)
0.1 in (0.1 cm)
3 classes
number
number
0.1 in
0.1 in (0.1 Cm)
1 ft (0.5 m)
1°
year
year
year
year
year
5 classes
2 classes
alphabetic field
Data Quality Limits
NA, downloaded
NA, downloaded
90% agreement
90% agreement
NA, downloaded
NA, downloaded
95% agreement
90% agreement
95% to genus, 85% to species
NA, downloaded
90% @ + / - 5% of True DBH
85% agreement
NA, downloaded
85% agreement
NA, downloaded
85% @ + / - 0.2 in (0.5 cm)
90% @ + / - 1 ft (0.3 m)
90% @ +/- 10°
85% @ + / - 2 years
85% <3> + / - 2 years
85% @ + / - 2 years
85% @ + / - 2 years
85% agreement
85% agreement
NA, discretionary
NA, discretionary
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 17 of 86
Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives
Variables
FULL-HECTARE BOUNDARY DELINEATION
Hectare Condition List
Hectare Center Condition
Contrasting Condition
Lett Azimuth
Corner Azimuth
Corner Distance
Right Azimuth
FULL-HECTARE LARGE TREES
Hectare Tree Type
Tree Number
Previous Condition Class
Condition Class
Tree Location
Old Tree History
Current Tree History
Species
Old DBH
DBH
DBH Check
Point Number
Horizontal Distance
Azimuth to nearest point
Mortality Year
Nonforest Year
Ground Year
Cause of Death
Crown Class
Notes
Description
Reporting Units
9 classes
9 classes
9 classes
1°
1°
0.1 ft (0.5 m)
1°
2 classes
number
9 classes
9 classes
3 classes
1 1 classes
1 1 classes
314 classes
0.1 in (0.1 cm)
0.1 in (0.1 cm)
3 classes
4 classes
1 ft (0.5 m)
1°
year
year
year
year
5 classes
2 classes
alphabetic field
Data Quality Limits
90% agreement
90% agreement
90% agreement
90% @ + / - 15°
90% @ + /- 15°
90% @ + / - 5 ft (2 m)
90%@+/-15°
95% agreement
NA, downloaded
NA, downloaded
90% agreement
95% agreement
NA, downloaded
95% agreement
95% to genus, 85% to species
NA, downloaded
90% @ + / - 5% of True DBH
85% agreement
NA, arbitrary
90% @ + / - 1 ft (0.3 m)
90% @ +/- 10°
85% @ + / - 2 years
85% @ + / - 2 years
85% @ + / - 2 years
85% agreement
85% agreement
NA, discretionary
NA, discretionary
-------
EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 18 of 86
Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives
Variables
FULL-HECTARE MORTALITY
Hectare Tree Type
Condition Class
Tree Location
Mortality Status
Species
DBH
Point Number
Horizontal Distance
Azimuth
Mortality Year
Cause of Death (primary)
Cause of Death (secondary)
Notes
Description
PLOT IDENTIFICATION (NONFOREST)
State
County
Hexagon Number
Plot Number
Measurement Type
Project
QA Status
Crew Type
Old Plot Status
Current Plot Status
Month
Day
Year
Land Use at Point 1
Land Use at Point 2
Land Use at Point 3
Land Use at Point 4
Reporting Units
2 classes
9 Classes
3 classes
3 classes
314 classes
0.1 in (0.1 cm)
4 classes
1 ft (0.5 m)
1°
year
year
year
2 classes
alphabetic field
FIPS codes
FIPS codes
EMAP hex code
number
3 classes
2 classes
3 classes
2 classes
3 classes
6 classes
1 2 classes
31 classes
number
1 5 classes
15 classes
1 5 classes
15 classes
Data Quality Limits
95% agreement
90% agreement
95% agreement
95% agreement
90% to genus, 80% to species
90% @ + / - 5% of True DBH
NA, arbitrary
90% @ + / - 1 ft (0.3 m)
90% @ +/- 10°
85% @ + / - 2 years
85% agreement
85% agreement
NA, discretionary
NA, discretionary
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
99% agreement
90% agreement
90% agreement
90% agreement
90% agreement
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 19 of 86
1.5.2 Method Performance
Expected data measurement performance is indicated in the third column of Table 1 -16. For instance,
for the DBH data variable, these data will be measured to the nearest 0.1 inch for English and to the
nearest 0.1 cm for metric. An acceptable accuracy or performance criteria, as measured on Reference
Plots or in Field Audits, is that the crews will be within 5 percent of the true value (as measured by an audit
team) on 90 percent of their measurements.
These comparisons are based on numbers of observations for matching entities. That is, prior to
making a comparison, it must be determined that the same tree or Condition Class is involved. In some
cases, arbitrary values cannot be directly compared. For example, crews are allowed to choose site trees,
and then reference them to any point. Prior to comparisons involving site trees, it must be verified that the
same tree is referenced to the same point. Most notably, Condition Classes are identified by arbitrary
numbers assigned by crews. These numbers can change with the order in which the plot is completed and
can also change between surveys. Prior to comparison of values involving Condition Class, it must be
established that all Condition Classes have been assigned the same numbers, or otherwise matched.
Variables affected by this caveat include: Condition Class, Subplot Condition List, Subplot Center
Condition, Microplot Center Condition, and Contrasting Condition.
1.5.3 Corrective Action
Reference plot data and/or audit results will be evaluated for indications of data measurement
deviations in excess of the MQOs. Crews with unacceptable MQO deviations will be advised of problem
situations and special attention will be directed to followup training or other appropriate action. Within a
short period after retraining, followup audits will be conducted to verify that subsequent measurements are
within MQOs. See FHM Quality Assurance Plan (Cline (ed.), 1994) for a full explanation of this corrective
process.
1.6 Procedures
Tally prompts the field crew for the measurements required at each plot. This section is organized
similar to the way information is presented on the PDR screens. A Quick Reference Guide to all Tally
Screens has been provided in Subsection 1.0. The tables in the quick reference guide serve as indices
to Section 1, indicating the pages where Tally variables are defined. In cases where the same variable
appears on multiple screens (e.g., DBH), a cross reference is provided to the page where the most
comprehensive description is given. All site condition, growth, and regeneration measurement variables
are discussed in Section 1. Most crown condition classification and damage and mortality assessment
variables are introduced in Section 1, yet are discussed more fully in Sections 2 and 3, respectively.
Although the lists of variables are organized by PDR screen, the order of the variables within each figure
of the screen may not match the current ordering of variables on the PDR screen. Additionally, some of
the screens shown here are optional, to be activated only in certain regions. As an example, the
full-hectare boundary and full-hectare tree screens will be done in California and Pacific Northwest Pilot
Study only.
The tables listed in the Quick Reference Guide indicate which variables are prompted for forest plots
under each of the three measurement types. A "x" in one of these tables means that the variable is
prompted for a particular measurement type, and the crew will be prompted to complete that field. Other
variables will either be provided from previous field visits (downloaded) or, if not applicable to that field visit,
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 20 of 86
will not be presented. A "D" means that the variable has been downloaded from previous field visits. A
"x,D" will be downloaded from existing Tally data, but new data are required for new forest plots and new
sample trees. Only if a mistake was made during a previous visit will crews have an opportunity to change
some of the codes that have been downloaded. Whenever a downloaded variable is changed, an
explanation is required in the field notes.
Variables followed by "(W)" are scheduled for collection in western states only. Variables followed by
"(CA/PNW PS)" are scheduled for collection in CA and the PNW PS only.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 21 of 86
1.6.1 Permanent Plot Design and Forest Plot Establishment
1.6.1.1 Plot Design
The FHM national sampling scheme is discussed at length by Overton et al. (1990). The sampling
framework is based upon a triangular grid of 40 km2 hexagons that spans the entire U.S. The grid contains
atotal of 12,600 hexagons (about 1/16 of the U.S. land area). FHM ground plots are systematically located
within 1 kilometer of each hexagon center.
Procedure
Each FHM plot consists of a series of fixed-area, circular subplots tied to a cluster of four points that
are spaced 120 ft (36.6 m) apart (Figure 1-1). A cluster design was chosen because it has proven to be
cost-effective for extensive surveys (Scott et al., 1983; Scott, 1993). The key sampling unit for most tree
measurements is the 1/24-acre (1/60-hectare) subplot (Figure 1-1). Each subplot includes a 1/300-acre
(1/750-hectare) microplot, offset from subplot center to avoid trampling. Seedlings, saplings, and other
vegetation are measured on the microplot.
Other FHM measurements are made on the plot as well. Lichen community is sampled in a circular
area with a 120-ft radius centered in the middle of subplot 1 and excluding the four subplots. Non-timber
vegetation measurements are collected at points offset from the subplot center points at 30°, 150°, and
270° azimuths. PAR measurements are made on a grid of seven stations located on each of the subplots
as shown in Figure 4-1. Ozone bioindicator plants are sampled at the most easily accessible opening that
is within three miles +/- 300 ft (91 m) elevation of the detection monitoring plot.
The center of subplot 1, or point 1, is also the center of overall plot. The other subplot centers (or
points) are located as follows: point 2 is 360° and 120 ft (36.6 m) from point 1; point 3 is 120° and 120 ft
(36.6 m) from point 1; and point 4 is 240° and 120 ft (36.6 m) from point 1. Microplot centers are located
90° and 12 ft (3.66 m) from the center of each subplot.
All compass readings on FHM plots are taken from magnetic north, and not corrected for declination.
Field data are recorded in metric units in Forest Service (FS) Regions 5, 6, and 10 (Pacific Northwest,
California, Hawaii, and Alaska). All other FS regions use English units.
1.6.1.2 Forest Plot Establishment
A FHM plot is installed at all sample locations where any portion of a 1/24-acre (1/60-hectare) subplot
is forested (e.g., a timberland, reserved timberland, or woodland land use). A plot is not established where
all four subplots are obviously nonforest. To qualify as forest, an area must meet Forest Inventory and
Analysis (FIA) specifications for timberland, reserved timberland, or woodland. These specifications are
provided in Appendix D.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 22 of 86
Azimuth 1 -2 360°
Azimuth 1-3120°
Azimuth 1 -4 240°
Subplot
24.0' radius (7.32 m).
Annular Plot
58.9'radius (17.95m).
Distance between
points is 120" (36.6m).
Microplot
6.8" radius (2.07 m) 12' @
90° azimuth from subplot
centers (3.66 m).
0195msd94.fig-1
Figure 1-1. National FHM plot layout is designed around four points (subplot centers).
if a land owner refuses access to a forested sample plot, do not attempt to visit the plot, rather report
the refusal to the field supervisor. If the field supervisor cannot obtain permission, the plot is set aside until
the next Mt3, when access will again be requested. No substitute plot is established. A similar procedure
applies to plots where access is preempted by safety considerations. Hazardous plots are not occupied
until the situation is rectified.
Plot Establishment Procedures
Scaling a Course to Sample Plot
For initial plot establishment, and for future measurements where the previously established course is
unsuitable, a new course to the sample plot must be scaled from aerial photography. Always select a
prominent landmark or physical feature for a starting point (e.g., field corners, buildings, bridges,
intersections of roads, streams, or ditches). If necessary, reference the starting point with one or more
witness trees. Pinprick and label the images of the starting point and plot center (subplot #1) on the
photograph. Scale a new course to the sample plot as follows:
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 23 of 86
1. Establish a baseline by selecting two points that are at least 600 ft (182.9 m) apart and clearly
identifiable on the photo and on the ground.
2. Measure the distance between these two points on the ground and note the azimuth of the
direction the measurement is taken.
3. Pinprick these two points on the photo and measure the distance between them using a photo
scale.
4. To compute the Photo Scale Reciprocal (PSR), divide the horizontal ground distance by the photo
distance.
5. Measure the distance on the photo between the starting point and the plot center and multiply that
number by the PSR to get the horizontal ground distance between the two.
6. Find the azimuth from the starting point to the plot center by placing the protractor at the
intersection of the baseline and the starting point to plot center line on the back of the photo,
making sure the protractor is face down.
7. Using the azimuth of the baseline as a reference, find the course to plot center azimuth by reading
the number where the course line meets the edge of the protractor.
Establishing a ground course to the sample plot
1. Using a compass and tape, follow the azimuth and distance from the starting point to plot center.
2. Horizontal distance should be corrected for slope, but record slope distance in the field notes.
3. Reference all line segments exceeding 500 ft (150 m) with witness trees. Mark shorter segments
in areas where relocation difficulties might be expected.
4. At the end of the course, check the photograph to verify that the ground location of the plot center
is correct.
5. If the 24 ft (7.32 m) radius around subplot #1 contains no forest, establish a turning point and
proceed to the lowest-numbered subplot that does contain forest.
6. Place a permanent marker in the ground at the lowest-numbered forested subplot and reference
it with two witness trees. The witness trees should be placed outside the 24 ft (7.32 m) subplot
radius, approximately at right angles to each other with respect to the subplot center.
7. Also place permanent ground markers at the center of the other three subplots, but it is not
necessary to reference them with witness trees.
Witness Tree Marking Procedures
1. Tag or otherwise mark starting points, starting-point witness trees, line trees, and plot-center
witness trees according to the usual procedures followed by the local FIA Unit. Avoid scribing any
trees with 58.9 ft of a subplot center.
2. Avoid penetration of the cambium when scribing trees.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 24 of 86
Course Documentation
Preprinted field notes will be provided for plot relocation. A written description of the starting point will
be included in the appropriate section of the notes. The following information should be recorded on the
preprinted field notes:
1. Whenever practical, add information that will help locate the plot without the aid of a photograph.
2. Sketch a map of the course from the starting point to the center of the lowest-numbered forested
subplot.
3. Record the slope distances (to the nearest foot [0.1 meter]) and azimuths of all line segments
between the starting point, line trees, turning points, prominent physical features, and plot center.
Slope distances are counted as cumulative until the azimuth changes.
4. At the lowest-numbered forested subplot, record the species, DBHs, slope distances, and azimuths
of two witness trees. Ail distances and azimuths should be measured to the center of a tree at its
base.
5. Also sketch the positions of the two witness trees as well as any other features of the plot that
might facilitate future relocation on the preprinted plot diagram.
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1.6.2 Plot-Level Data
1.6.2.1 Plot-Level Notes
The plot-level notes screen (Table 1-1) may contain notes from previous field crews. These could be
extremely important and should be reviewed before starting the plot. Do not delete any notes downloaded
from previous visits. New notes can be typed in the PDR alphabetic fields found at the end of the
downloaded notes. Additionally, using some codes automatically prompts further explanation be added to
the notes. All notes are reviewed by the regional coordinator when the data are processed. If appropriate,
they will be downloaded to future field crews.
1.6.2.2 Plot Identification
Plot identification data provide information concerning the crew members, date, and other
circumstances associated with each plot.
Procedure
The Quick Reference Plot Identification Screen (Table 1 -2) lists the plot identification variables. Record
the appropriate codes for each variable.
STATE
Two-digit FIPS codes are listed in Appendix B.
COUNTY
Three-digit FIPS codes are listed in Appendix B.
HEXAGON NUMBER
Record the unique 7-digit EMAP code assigned to each 40-km2 hexagon. These are provided on
the field maps and/or the PDR.
PLOT NUMBER
• Plot numbers are used to identify individual plots when more than one plot occurs within the same
hexagon. Record the 1 -digit code that applies. In cases where only one plot is located in the
hexagon, assign a "1" in this field.
PROJECT
Specify whether the plot is a standard detection plot or a special demonstration plot.
Code Definition
1 Detection Monitoring
2 Demonstration Project
QA STATUS
Indicate whether or not the plot is being measured for Quality Assurance (QA) purposes. QA field
plots are plots on the regular grid that are remeasured for QA by both regular field and QA crews.
QA reference plots are special plots that have been established solely for QA purposes. They are
not part of the regular grid, usually located near regional training centers, and measured by both
regular and expert field crews.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 26 of 86
Definition
Standard field plot
QA field plot
QA reference plot
Training plot
Botched plot
CREW TYPE
Specify whether the plot is being measured by a regular field crew or QA crew or an expert crew
consisting of indicator leaders.
Code Definition
1 Regular field crew
2 QA field crew
3 Expert crew
MEASUREMENT TYPE
Indicate whether this is a new plot (Mt1), a plot being remeasured as part of the annual tree crown
and damage update (Mt2), or a plot being remeasured as part of the 4-year Mt3 remeasurement
cycle.
Definition
New plot - First time this plot has been established.
Annual measurement - Plot is being remeasured as part of the annual crown
and damage assessment.
3 Periodic measurement - Plot is being remeasured as part of the 4-year Mt3
remeasurement cycle.
OLD PLOT STATUS
This code indicates plot status the last time a Mtl or Mt3 survey was conducted at this location.
For Mt2 and Mt3 surveys, old plot status has been downloaded from the current plot status
recorded at the previous inventory.
Definition
Forest Plot - Plot had at least one forested condition class that was occupied
and measured in the normal manner.
2 Nonforest plot - Plot did not have any forested condition classes.
3 Forest plot, access denied - Plot had at least one forested condition class,
yet access had been denied to the entire plot.
4 Forest plot, dangerous access - Plot had at least one forested condition
class, yet dangerous conditions prevented access to the entire plot.
5 Lost data - Plot had at least one forested condition class, yet the data that
were or should have been collected at that time are not available.
CURRENT PLOT STATUS
Indicate the status of this plot at the current time.
Definition
Forest Plot - Plot has at least one forested condition class that can be visited
and measured in the normal manner.
Nonforest plot - Plot does not have any forested condition classes. (Note:
Also assign this code to plots that cannot be visited because of access
problems if it is obvious that the plot contains no forested condition classes.)
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 27 of 86
Code Definition
3 Forest plot, access denied - Plot has at least one forested condition class,
yet access has been denied to entire plot. Use code 1 if access is denied to
only part of the plot.
4 Forest plot, dangerous access - Plot has at least one forested condition
class, yet dangerous conditions prevent access to the entire plot. Use code 1
if access is prevented to only part of the plot.
5 Lost data - Plot has at least one forested condition class that has been or
can be visited and remeasured, yet the data may have been lost. (Note:
This code is valid only after the close of field season.)
MONTH, DAY, YEAR
Record 2-digit codes to identify the month, day, and year when the plot is measured (e.g., record
July 14, 1994 as 07 14 94).
ELEVATION
Obtain elevation data from USGS topographic maps, generally the 7 1/2 minute series quadrangle.
Locate the plot center on the map. Record elevation as a 3-digit code, rounding to the nearest 100
ft and dropping the last two digits. In metric, elevation is rounded to the nearest 10 m. For
example, 240 ft is coded 002; 5,600 is 056; 240 m is coded 024; while 1,800 m is 180. If the
elevation is unknown at the time the plot is occupied, record 999.
TALLY1 - TALLY5
All FHM field personnel have been assigned a 7-digit Cruiser I.D. code. Record the I.D. of each
crew member or visitor participating in site condition, growth and regeneration, crown classification,
or damage/mortality field measurements (up to a maximum of five). Cruiser I.D. codes are
sequenced as follows:
The first two digits identify the agency with whom the crew member is employed.
Code Definition
11 Forest Service, FHM Research
12 Forest Service, State and Private Forestry
13 Forest Service, National Forest Systems
14 Environmental Protection Agency (including contractors)
15 State
16 Bureau of Land Management
17 Tennessee Valley Authority
18 National Park Service
19 Soil Conservation Service
20 Bureau of Indian Affairs
90 Other
The second two digits specify the federal agency or state affiliation. FS agency branches,
independent contractor, and other codes are listed below. State employees should use the 2-digit
state FIPS code (Appendix B). Non-Forest Service federal employees should use the "other" code.
Code Definition
01 Region 1 (Northern Region)
02 Region 2 (Rocky Mountain Region)
03 Region 3 (Southwestern Region)
04 Region 4 (Interrnountain Region)
05 Region 5 (Pacific Southwest Region)
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 28 of 86
Code Definition
06 Region 6 (Pacific Northwest Region)
07 Northeastern Area
08 Region 8 (Southern Region)
09 Region 9 (Eastern Region)
10 Region 10 (Alaska Region)
22 Intermountain Station
23 North Central Station
24 Northeast Station
26 Pacific Northwest Station
27 Pacific Southwest Station
28 Rocky Mountain Station
29 Southeast Station
30 Southern Station
31 Independent Contractor
90 Other
The last three digits correspond to the personal identification number assigned to each crew
member at the beginning of the field season.
INTERIM DISTURBANCE 1-3
Describe up to three treatments or disturbances that have occurred since this plot was last visited
by a field crew. This information will be downloaded as plot-level notes to future crews to aid
condition classification at the next Mt3 survey. If there are more than three, describe the additional
disturbance in the plot-level notes.
Code Definition
0 None
1 harvest
2 commercial thinning
3 selective cutting and highgrading
4 other cutting
5 site preparation
6 artificial regeneration on existing forest
7 artificial regeneration on nonforest
8 prescribed burning
9 other silvicultural (i.e., injection, herbicide, fertilizer)
10 natural reversion on nonforest
11 disease
12 insects
13 weather
14 wildfire
15 grazing
16 Other
INTERIM DISTURBANCE YEAR 1-3
Record the year (2-digit) during which an interim disturbance occurred.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 29 of 86
1.6.2.3 Condition Classification
The FHM plot configuration is locked into a fixed pattern and subplots are never moved (rotated or
substituted). As a result, some plots may straddle more than one land use or forest condition. To
compensate for this and to enable stratification of the data by meaningful stand and area descriptors, all
subplots and microplots are mapped by condition class (Scott and Bechtold, 1994)..
Procedure
A condition class is defined by five variables: (1) Land Use, (2) Forest Type, (3) Stand Origin, (4)
Stand Size, and (5) Past Disturbance. New conditions are recognized each time a distinct change occurs
for one or more of these variables on the plot. As different conditions are encountered, they are defined
by recording all five variables associated with the new condition class.
To qualify as a separate condition, a change must be obvious and the contrasting condition must be
at least 1 acre (0.4 hectare) in size. The only exception to the 1-acre (0.4-hectare) rule is a maintained
nonforest inclusion in a forest environment (i.e., house site, powerline, improved road).
Examples of situations where separate condition classes will NOT be recognized include the following:
• transition zones
natural nonforest inclusions less than 1 acre (0.4 hectare) in size (i.e., rock outcrops, openings,
lakes)
streams less than 30 ft (9 m) wide
unimproved woods roads (e.g., not ditched)
fire lines
contrasting forest conditions less than 1 acre (0.4 hectare) in size.
Situations where changes in condition class WILL be recognized include the following:
contrasting land uses and forest conditions greater than 1 acre (0.4 hectare) in size
all maintained, human-caused, nonforest inclusions regardless of size or width (i.e., powerlines,
improved roads, house sites, canals)
linear strips of forest in a FOREST matrix (stream margins) regardless of width, as long as the
condition is at least 1 acre (0.4 hectare) [Note: linear strips of forest in a NONFOREST matrix
(riparian forest in a grassland environment) must be at least 120 ft (36.6 m) wide to qualify as
forest].
On new forest plots (Mt1 or newly forested Mt3), condition classes are recorded as they are
encountered at the plot. However, at Mt3 plots, crews are provided with computer-generated plot diagrams
showing how condition classes were defined during the previous Mt1/Mt3 visit. If no change has occurred,
the Mt3 crew should rerecord the condition class data provided on the plot diagram. If change has
occurred, or an error was made during the previous visit, ignore the condition class provided on the plot
diagram and enter the revised condition class data.
The quick reference condition classification screen (Table 1-3) lists the variables describing condition
classification.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 30 of 86
CONDITION CLASS CHANGE
Indicate whether or not the data for this condition class are being copied from the computer-
generated plot map. All data copied from the data diagram will be checked for transcription errors
when the data are processed.
Code Definition
0 The condition class is different from the plot map.
1 The condition class has been copied from the plot map.
CONDITION CLASS
An arbitrary number is used to identify and map different land uses and forest conditions occurring
on a plot. Once a number is assigned, that number is reused whenever the same condition class
is encountered on the plot. Most plots will have only one or two conditions, but as many as nine
can be recorded. On new plots (Mt1 and newly forested Mt3), number condition classes
consecutively as they are encountered. On Mt3 plots, use the same numbers assigned at the
previous inventory, if they still apply. (Code 1 = Condition 1 ... Code 9 = Condition 9)
LAND USE CLASS
Record the appropriate land use. For sampling purposes, Timberland (01), Reserved Timberland
(12), and Woodland (13) are all considered forest land uses. Definitions and additional information
concerning land use classification are provided in Appendix D.
Code Definition
0 Lost data / lost plot
1 Timberland
2 Cropland
3 Improved pasture
4 Rangeland
5 Idle farmland
6 Other farmland
7 Urban and other development
8 Marsh
9 Water
10 Access denied
11 Dangerous condition
12 Reserved Timberland
13 Woodland
14 Rocky, barren, excessively steep terrain (nonforest)
15 Natural alpine clearing (nonforest)
FOREST TYPE
Detailed Forest Types are arranged into major Forest-Type Groups recognized by the Society of
American Foresters (Eyre, 1980). A list of species associations that correspond to the various
Forest Types is provided in Appendix C.
Forest type is based on the stocking of all live trees in the sampled condition. Overtopped trees
are not usually considered. When assigning forest type, it may be necessary to look beyond the
trees tallied in that condition. If Tally trees alone do not accurately reflect the forest type, include
a note of explanation.
AH species associated with a forest type need not be present for that type to apply. For example,
if red maple predominates on a wet to very wet site, then the type is Black ash/American elm/Red
maple even though Black ash and American elm are absent (see Appendix C, code 710).
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 31 of 86
If a stand is at early serai stage, forest type is derived from seedling or sapling cover alone. If a
disturbance is very recent, and there is less than 10 percent stocking (Appendix D), use code 0999
to denote a nonstocked plot. Remeasurements will trace the development of this tract toward a
specific forest type as reforestation takes place.
STAND ORIGIN
Examine the plot for evidence of tree planting or seeding and assign the appropriate code.
Code Definition
1 Natural stand, no evidence of planting or direct seeding
2 Softwoods planted or seeded
3 Hardwoods planted or seeded
STAND SIZE
Record the stand size based on the average DBH of all live trees that are not overtopped.
Code Definition
1 Sawtimber - softwood or woodland > 9.0 in (22.9 cm) DBH/DRC
Sawtimber - hardwood > 11.0 in (27.9 cm) DBH/DRC
2 Poletimber - softwood or woodland > 5.0 in - 8.9 in (12.7 - 22.8 cm) DBH/DRC
Poletimber - hardwood > 5.0 in - 10.9 in (12.7 - 27.8 cm) DBH/DRC
3 Sapling/seedling < 5.0 in (12.7 cm) DBH/DRC
4 Nonstocked
PAST DISTURBANCE 1
The area affected by any human-caused or natural treatment or disturbance must be at least 1
acre (0.4 hectare). Record up to three significant treatments and/or disturbances. In most cases,
only the disturbances listed below are significant. In cases where "other" categories are used
(other cutting, other silvicultural, and other), describe the situation further in the notes. For new
plot establishment (Mt1 or newly forested Mt3 plots), the disturbance must be clearly visible and
recent enough to affect current competitive conditions or otherwise influence stand health.
For Mt3 remeasured forest plots, recognize only those disturbances that have occurred in the four
years since the previous Mt1/Mt3 survey. Review the plot-level notes to determine which
disturbances were recorded during previous visits. These should not be rerecorded because only
disturbances that have happened since then are relevant. However, if plots have been annually
revisited (Mt2), interim disturbances may be recorded in plot-level notes. Because disturbances
occurred during Mt2 visits since previous Mt1/Mt3 visits, they should be recorded during the Mt3
visit, as well. When evaluating disturbance notes from previous visits, any disturbances with a date
equal or prior to the previous Mt1/Mt3 survey should be ignored.
Code Definition
0 None
1 harvest
2 commercial thinning
3 selective cutting and highgrading
4 other cutting
5 site preparation
6 artificial regeneration on existing forest
7 artificial regeneration on nonforest
8 prescribed burning
9 other silvicultural (i.e., injection, herbicide, fertilizer)
10 natural reversion on nonforest
11 disease
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Definition
insects
weather
wildfire
grazing
Other
DISTURBANCE YEAR 1
Record the year (2-digit) in which Disturbance 1 occurred. For new plot establishment (Mt1 or
newly forested Mt3 plots), there is no time limit on recognition of past disturbances, as long as they
are still visibly impacting the stand. Remeasured Mt3 plots will not be assigned a disturbance that
happened before the previous Mt1/Mt3 survey.
PAST DISTURBANCE 2
If a stand has experienced more than one disturbance, record the second disturbance here. See
Past Disturbance 1 for coding instructions.
DISTURBANCE YEAR 2
Record the year in which Past Disturbance 2 occurred.
instructions.
See Disturbance Year 1 for coding
PAST DISTURBANCE 3
If a stand has experienced more than two disturbances, record the third disturbance here. See
Past Disturbance 1 for coding instructions.
DISTURBANCE YEAR 3
Record the year in which Past Disturbance 3 occurred.
instructions.
See Disturbance Year 1 for coding
PREVIOUS STAND AGE
Previous stand age is downloaded from "STAND AGE" recorded during the previous Mt1 or Mt3
survey. If this condition has not experienced any major treatment or disturbance, previous stand
age can be used as a guide to determine current stand age.
STAND AGE
An estimate of stand age is required for every forested condition class defined on a plot. Stand
age is usually highly correlated with stand size and should reflect the average age of all trees that
are not overtopped. Unlike the procedure for Site-tree age, estimates of stand age should range
back to the time of tree establishment (e.g., not age at DBH). Note: For planted stands, estimate
age based on the year the stand was planted (e.g., do not add in the age of the planting stock).
Stand age is different from other condition class variables in that the decision to create a separate
condition class is rarely based solely on age. If the difference between two conditions does not
involve land use, forest type, stand origin, stand size, or disturbance history, do not recognize two
separate condition classes. The only exception is when two saw timber stands are the same in
every respect, but they differ in age by more than 50 years.
Determination of stand age involves the extraction of tree cores. Cores are not usually taken from
trees within 58.9 ft (17.95 m) of any subplot center. This is required in order to protect trees on
any subplot from potential damage caused by the coring process. Trees must be cored off plot, yet
still within the same condition class to which the age data applies. CAUTION: When trees are
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 33 of 86
chosen beyond 58.9 ft of the subplot center, make sure they are not located on an adjacent
subplot.
To estimate stand age, select three or four dominant or codominant trees from the overstory. If
the overstory covers a wide range of tree sizes and species, try to select the trees accordingly, but
it is not necessary to core additional trees in such stands. The variance associated with mean
stand age increases with stand heterogeneity, and additional cores are not likely to improve the
estimate. Core each tree at DBH and count the rings from the outside edge of the core to the pith.
Add in the number of years that passed from germination until the tree reached DBH to determine
the total age of the tree. Unless more specific information is provided at training, add 5 years to
all eastern species, 5 years to western hardwoods, and 10 years to western softwoods. Assign
a weight to each core by visually estimating the percentage of total overstory trees it represents.
Make sure the weights from all cores add up to 1.0, compute the weighted average age, and
record. For example, if three trees aged 34, 62, and 59 years represent 25 percent, 60 percent,
and 15 percent of the overstory, respectively, the weighted stand age should be:
(34 x .25) + (62 x .60) + 59 x (.15) = 55 years.
In some cases, it may be possible to avoid coring trees to determine age. If a stand has not been
seriously disturbed since the previous Mt1 or Mt3 survey, simply add the number of years since
the previous survey to the previous stand age. In other situations, cores collected from site trees
(Subsection 1.6.2.4) can be used to estimate Stand Age.
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1.6.2.4 Site-Tree Data
Site-tree data provide a measure of site productivity by quantifying the height-to-age relationship of
dominant and codominant trees. Site-tree data are required for every forested condition class defined on
a plot, if suitable site trees are available. National guidelines require only one site tree per forested
condition class, yet in some FHM regions more may be selected. The preferred number of site trees will
be specified at training. On plots where suitable site trees are not available, the corresponding PDR
warning should be overridden.
Procedure
Site-trees should be selected from species common to the overstory of the condition class being
sampled. If possible, choose a species with clearly visible annual rings and a central stem. Use only trees
that have remained in a dominant or codominant crown position throughout their entire life span. Reject
trees that exhibit signs of damage, trees with ring patterns that exhibit signs of suppression, trees less than
20 years old, trees less than 5.0 inches (12.7 cm) DBH, trees with rotten cores, and woodland species.
Site-tree procedures include the extraction of tree cores. Site-tree cores are not usually taken from
trees within 58.9 ft (17.95 m) of any subplot center. These trees must be selected off plot yet within the
same condition class that they represent. CAUTION: When trees are chosen beyond 58.9 ft (17.95 m)
of the subplot center, make sure they are not located on an adjacent subplot.
In some cases, it may be possible to use previously gathered site tree data. Crews are encouraged
to reuse the downloaded tree data if the tree still qualifies. The current age of downloaded site trees will
be computed from past data files when the data are processed, so it is not necessary to re-core these
trees.
The quick reference site-tree screen (Table 1-4) lists the site-tree variables.
TREE TYPE
In past years, foliage samples, tree cores, and other specimens were collected from "specimen
trees." For convenience, site tree data and specimen tree data were combined on the same PDR
screen. In 1994, specimen trees will not be selected nor will tree related specimens be collected;
therefore, the tree type variable automatically sets to "1".
Code Definition
1 Site Tree Only
2 Specimen Tree Only
3 Site tree and specimen tree
SITE-TREE HISTORY
Indicate whether a downloaded site tree is suitable for reuse as a site tree. This field automatically
set to "1" for Mt1 plots. Note: No site trees are available for downloading to Mt3 plots in 1994,
therefore this field is automatically set to "1".
Code Definition
1 First time tree used
2 Downloaded site tree, still suitable for site tree
3 Downloaded site tree, no longer suitable for site tree
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 35 of 86
TREE NUMBER
The same procedure for subplot trees in Subsection 1.6.6 applies.
POINT NUMBER
Record the number of the point to which the site tree distance and azimuth are measured.
PREVIOUS CONDITION CLASS
Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 survey.
CONDITION CLASS
Record the Condition Class in which the site tree is currently located. (Code 1 = Condition 1 —
Code 9 = Condition 9).
SPECIES
Select the appropriate species code from Appendix A.
OLD DBH
Downloaded from "DBH" recorded during the previous Mt1/Mt3 survey.
DBH
Use the same procedures described for subplot trees in Subsection 1.6.6.
DBH CHECK
Use the same procedures described for subplot trees in Subsection 1.6.6.
HORIZONTAL DISTANCE
Measure and record the horizontal distance to the nearest 0.1 ft (0.1 m) from the subplot center
to the pith at the base of the site tree.
AZIMUTH
From subplot center, view the base of the site tree with a compass. Record the azimuth (to the
nearest degree) as a 3-digit code ranging from 001 to 360. Use 360 for north.
CROWN CLASS
Use the same procedures described for subplot trees in Subsection 1.6.6. Site trees must be
dominant or codominant.
TREE HEIGHT
With a clinometer or other approved instrument, measure the total length of the site tree from the
ground to the top of the tree. Record the 3-digit code to the nearest 1 ft (0.1 m).
TREE AGE AT DBH
Drill the site tree at DBH with an increment borer. Count the rings from the outside edge of the
core to the pith. Record the age of the tree at DBH (3-digit code). Do not attempt to add in the
time it took the tree to reach DBH.
Use the following procedure to estimate the age of the tree if the radius is greater than the length
of the increment borer.
1. Bore into the tree as far as possible, extract the core, and count the rings.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 36 of 86
2. Count the number of rings in the inner 2 inches (5 cm) of the core.
3. While the increment borer is still in the tree, measure the length of the borer that is exposed.
4. Subtract this length (step 3) from the total length of the increment borer.
5. Divide tree DBH by 2.
6. Subtract step 4 from step 5 to find the distance short of the center.
7. Divide step 6 by 2 (or 5 if metric) to determine how many 2 inch (5 cm) lengths are needed
to make up the missing distance.
8. Multiply step 7 by the number of rings counted in step 2.
9. Add step 8 to the total number of rings in the extracted core (step 1) to determine the tree
estimated age at DBH.
10. Note "extrapolated age" in notes.
NOTES
Indicate if any notes are to be recorded for this tree. A "1" downloaded to this field indicates the
presence of notes from a previous field crew.
Code Definitions
0 No notes will be recorded for this tree.
1 Written notes will be recorded for this tree.
DESCRIPTION
Record tree-level notes in the alphabetic field on the PDR. These notes will be reviewed by the
regional coordinator and passed onto future crews, if appropriate.
COMPETING BASAL AREA
Using a 10 English-factor (2.5 metric) prism, estimate the basal area of other trees competing with
the site tree. This is accomplished by centering the prism over a point 3 ft (1 m) due north of the
face of the site tree at DBH, counting the number of trees that are "in" (5.0 inches (12.7 cm) DBH
and larger), and then multiplying the tree count by the prism factor. Do not include the site tree
in the count. "Borderline" trees should be counted as a half tree. Record the estimate as a 3-digit
code in square feet per acre (square meters per hectare). For example, 12.5 trees tallied with a
10-factor prism equal 125 sq. ft of basal area is recorded as 125.
ADDITIONAL CROWN AND DAMAGE VARIABLES
Use crown classification procedures described for subplot trees in Section 2 for: Crown Diameter
Width, Crown Diameter 90°, Live Crown Ratio, Crown Density, Crown Dieback, and Foliage
Transparency.
Use damage classification procedures described for subplot trees in Section 3 for: Location 1-3,
Damage 1-3, and Severity 1-3.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 37 of 86
1.6.3 Point-Level Area Descriptors
1.6.3.1 Point Description
Each subplot is described by a series of area parameters relating to topographic features and existing
cover type. These data also relate to the microplot, since the microplot is contained within the subplot
perimeter.
Procedure
The quick reference point-level area descriptors screen (Table 1 -5) lists variables which apply to each
subplot. All condition classes occurring within the perimeter of the subplot should be recognized and
defined as soon as the subplot center is established.
PREVIOUS POINT HISTORY
Downloaded from "Point History" recorded during the previous Mt1/Mt3 survey.
POINT HISTORY
Indicate whether or not this point currently has at least one forested condition class.
Code Definitions
0 Entire subplot nonforest
1 At least one accessible forest condition on subplot (land use class 1, 12, or
13)
SLOPE CORRECTION
Distance must be added to adjust for slope if the slope between points is greater than 5 percent.
Record distance in 0.1 ft (0.1 m) added to the standard 120 ft (36.6 m) distance between subplot
1 and subplots 2-4. The English and metric distances which should be added are found in Table
1-17. As an example, 1.3 ft (0.4 m) should be added to a slope distance of 120 ft (3.6 m) if the
slope is 15 percent. The multipliers in Table 1-17 can be used to convert any horizontal distance
to slope distance and slope distance to horizontal distance.
PERCENT SLOPE
Record the angle of slope to the nearest percent. Percent slope is determined by sighting the
clinometer along a line parallel to the average incline (or decline) of the subplot. This angle is
measured along the shortest pathway downslope before the drainage direction changes. To
measure percent slope, observer #1 should stand uphill 50 ft (15 m) from subplot center and sight
observer #2, who is directly downhill 50 ft (15 m) from subplot center. Sight observer #2 at the
same height as the eye-level of observer #1. Read the slope directly from the percent scale of the
clinometer. The use of other scales requires conversion to percent.
Code Definition
000 0 to 4 percent slope
005 5 percent slope
006 6 percent slope
155 155 Percent slope
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 38 of 86
Table 1-17. English and Metric Slope Distance Correction Factors
Percent
Slope
5
10
15
20
25
30
35
40
45
50
55
60
65
70
80
90
100
110
120
130
140
150
Horizontal to Slope
Multiplier
1.001
1.005
1.011
1.020
1.031
1.044
1.059
1.077
1.097
1.118
1.141
1.166
1.193
1.221
1.281
1.345
1.414
1.487
1.562
1.640
1.720
1.803
Slope to Horizontal
Multiplier
0.999
0.995
0.989
0.980
0.970
0.958
0944
0.929
0.912
0.894
0.876
0.858
0.838
0.819
0.781
0.743
0.707
0672
0.640
0.610
0.581
0.555
Feet added per 120ft
0.1
0.6
1-3
2.4
3.7
5.3
7.1
9.2
11.6
14.2
16.9
19.9
23.2
26.5
33.7
41.4
49.7
58.4
67.4
76.8
86.4
96.4
Meters added per 36.6
m
0.0
0.2
0.4
0.7
1.1
1.6
2.2
2.8
3.6
4.3
5.2
6.1
7.1
8.1
10.3 •
12.6
15.2
17.8
20.6
23.4
26.4
29.4
ASPECT
Aspect specifies the direction of slope for land surfaces with at least 5 percent slope. Aspect is
measured with a hand compass between the same two points where slope was measured. Aspect
is measured to the nearest degree. Record 000 if percent slot is less than 5 percent.
TERRAIN POSITION
This is the position of the subplot in relation to the surrounding topography. See
Figure 1-2 for examples of different terrain positions.
Definition
Top and upper slopes - convex region on the upper part of the slope profile;
may be either xeric or mesic depending on aspect.
2 Midsiope - uniform, fairly straight region of the middle part of the slope
profile; may be either xeric or mesic depending on aspect
3 Bench - area of level terrain, with midslope above and lower slope below.
4 Lower slope - concave region on the lower part of the slope profile.
5 Flatland - level or near-level terrain not part of or related to major elevational
change; may have minimal elevational change (e.g., rolling uplands,
flatwoods, deep sands).
6 Bottomland - level terrain; normally well drained but subject to occasional
flooding (e.g., flood plains of rivers and streams.)
7 Wet bottomlands - level terrain; generally having year-round abundance or
overabundance of water (e.g., swamps, small drains, bays, and wet
pocosins.)
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 39 of 86
Top and
upper slopes
Midslope
Wet Bottomland
Bottomland
Flatland
Lower
slope
0195msd94.fig-2
Figure 1-2. Terrain position.
SUBPLOT CONDITION LIST
This is a listing of all condition classes located within the 24-ft (7.32-m) radius around the subplot
center. A maximum of four conditions is permitted at any individual subplot (a total of nine is
permitted for an entire plot). Condition classes are defined in Subsection 1.6.2.3. If a condition
class has already been defined at a previously completed subplot, use the same condition-class
number whenever that condition is encountered. Define new conditions as they are encountered.
If more than one condition class is listed here, boundary data are required. If only one condition
class is listed, this condition is automatically assigned to the subplot center and microplot center.
SUBPLOT CENTER CONDITION
This is the Condition Class of the subplot center.
corresponds to the subplot center.
MICROPLOT CENTER CONDITION
This is the condition class at the microplot center.
corresponds to the microplot center.
Record the previously defined condition that
Record the previously defined condition that
SUBPLOT OFFSET
Whenever possible, all subplot boundary and tree data should be recorded from, and referenced
to, the subplot center. If some obstruction prevents the collection of any subplot data from subplot
center, then record these data from one of the four offset points on the subplot perimeter. (See
Subsection 1.6.9.) The use of code 1 here activates the PDR to prompt for the offset position from
which data are being recorded.
Code Definition
0 All subplot data referenced to subplot center
1 Some subplot data referenced to one or more subplot offset points
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 40 of 86
MICROPLOT OFFSET
Whenever possible, all microplot boundary and tree data should be recorded from, and referenced
to, the microplot center. If some obstruction prevents the collection of any microplot data from
microplot center, then these data should be recorded from one of the four cardinal offset points on
the subplot perimeter. (See Subsection 1.6.9.) The use of code 1 here activates the PDR to
prompt for the subplot offset position from which data are being recorded.
Code Definition
0 All microplot data referenced to microplot center
1 Some microplot data referenced to one or more subplot offset points
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 41 of 86
1.6.3.2 Boundary Delineation
All subplots that straddle more than one condition class are mapped by delineating the boundaries
between contrasting conditions. Boundary data are required any time the subplot condition list indicates
more than one condition. Boundary data are used to compute the area of all subplot fragments by
condition class. In addition to the recording procedures described herein, detailed maps of condition class
boundaries should also be sketched onto preprinted plot diagrams.
Microplots that straddle more than one condition are handled in the same manner.
Procedure
Delineate the boundary of each condition class that differs from the condition at a subplot center with
a series of reference points. Boundary delineation is accomplished by recording azimuths and distances
from the subplot center to the reference points (Figure 1-3). Each boundary is marked by a maximum of
three points - two where the boundary intersects the subplot circumference and one "corner" point between
the two end points, if necessary. Unless offset points are used, only the corner points require a distance,
since the distance from the center to the circumference is always equal to the subplot radius. In rare cases
when boundary data are being referenced to offset points (Subsection 1.6.9), distances to the
circumference points are necessary.
Microplot boundaries are delineated and referenced to the microplot center in the same manner
described for subplots.
When a boundary between forest and nonforest is clearly marked (i.e., by a fence, fireline, ditch), the
boundary should follow the stems of the trees at the forest edge. When a boundary between two
contrasting forest conditions is not clearly marked, "average in" the boundary between the two conditions.
Upon remeasurement, do not move boundaries unless there has been a definite change, an obvious
mistake by the previous crew occurs, or a clear boundary is no longer detectable.
When the boundary between two different conditions is separated by a narrow linear inclusion (i.e.,
woods road, fireline, ditch), always establish the boundary to the nearest edge of the inclusion.
On new forest plots (Mt1 or newly forested Mt3), boundaries are recorded as they are encountered on
the plot. However, Mt3 crews are provided with computer-generated plot diagrams that show how
boundaries were located during the previous Mt1/Mt3 visit. If there has been no change, the current Mt3
crew should rerecord the boundary data provided on the plot diagram. If change has occurred or an error
was made during the previous visit, disregard the boundary data provided on the plot diagram and enter
the correct boundary data.
The quick reference boundary screen (Table 1-6) lists the boundary delineation variables.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 42 of 86
Right Azimuth /^
"™""^^™"™i"^
Forested
(Condition #1)
' Left Azimuth
Clearcut
(Condition #2)
Right Azimuth
Cropland
(Condition #3)
Corner Azimuth !
.. *• «•_ <
Left Azimuth
0195fnsd94.fig-3
Figure 1-3. Boundary delineation.
BOUNDARY CHANGE
Indicates whether or not the data for this boundary are being copied from the computer-generated
plot map. All data copied from the plot diagram will be checked for transcription errors when data
are being processed.
Code Definition
0 The boundary is different from the plot map.
1 The boundary has been copied from the plot map.
PLOT TYPE
Specify whether the boundary data is for a subplot or microplot.
Code Definition
1 Subplot boundary
2 Microplot boundary
OFFSET POINT _,/r> ^
Record the position from which boundary distances and azimuths are being measured (Subsection
1.6.9). This variable will not appear on the PDR and is automatically set to "0" unless Subplot
Offset = 1 or Microplot Offset = 1.
Code Definition
0 Normal position (subplot or microplot center)
1 North offset point
2 East offset point
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 43 of 86
Definition
South offset point
West offset point
CONTRASTING CONDITION
Record the condition class that contrasts with the condition class located at the subplot or microplot
center (e.g., the condition class on the other side of the boundary line). (Code 1 = Condition 1...
Code 9 = Condition 9) '
LEFT AZIMUTH
The azimuth (001-360°) to the farthest left point (facing the contrasting condition) where the
boundary intersects the subplot or microplot circumference (Figure 1-3).
LEFT DISTANCE
The horizontal distance (to nearest 1 ft [0.1 mj) from an offset point to the farthest left point (facing
the contrasting condition) where the boundary intersects the subplot or microplot circumference.
This variable is required only when the boundary data are being recorded from one of the four
subplot offset points (e.g., when Offset Point = 1, 2, 3, or 4).
CORNER AZIMUTH
The azimuth (000-360°) from the subplot or microplot center to a corner or curve in a boundary
(Figure 1-8). If a boundary is best described by a straight line between the two circumference
points, then record 000 for corner azimuth (000=none).
CORNER DISTANCE
The horizontal distance (to 1 ft [0.1 m]) from the subplot or microplot center to a boundary corner
point.
RIGHT AZIMUTH
The azimuth (001-360°) to the farthest right point (facing the contrasting condition) where the
boundary intersects the subplot or microplot circumference (Figure 1-3).
RIGHT DISTANCE
The horizontal distance (to nearest 1 ft [0.1 m]) from an offset point to the farthest right point
(facing the contrasting condition) where the boundary intersects the subplot or microplot
circumference. This variable is required only when the boundary data are being recorded from one
of the four subplot offset points (e.g., when Offset Point = 1, 2, 3, or 4).
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 44 of 86
1.6.4 Microplot Understory Vegetation
Crown canopy cover of understory vegetation (Daubenmire, 1959; Mueller-Dumbois and Ellenberg,
1974) Is assessed for six types of understory vegetation: mosses, lichens, ferns, herbs, and shrubs. Tree
seedlings less than 1 ft (0.3 m) in height are also counted as understory vegetation. These estimates are
used to describe the understory plant community and potential understory/overstory competition factors.
They are not meant to provide data for detection of species changes.
Procedure
Visually estimate the cover occupied by each vegetation type described below. This is done on the
6.8 ft (2.07 m) radius microplot, which is offset 90° and 12 ft (3.66 m) from each subplot center. Estimate
the cover of each life form independently and express it as the percentage of ground surface under live
aerial plant parts (Avery, 1975). Include all foliage inside the microplot perimeter -- not just the foliage of
plants with stems in the circle. Because of layering, the total cover of all six life forms could exceed 100
percent.
If a microplot boundary results in a microplot that is only partially forested, base the 100 percent on
the forested position of the microplot and do not discount the cover estimate for the nonforest area.
Code Definition
00 absent
01 trace
05 5% cover
10 10% cover
15 15% cover
20 20% cover
95 95% cover
99 100% cover
The quick reference microplot understory vegetation screen (Table 1-7) lists understory measurement
variables.
PERCENT MOSS
Only include moss on the ground.
PERCENT LICHENS
Only include lichens on the ground.
PERCENT FERNS
Record fern cover for all ferns present.
PERCENT HERBS
Herbs are forbs (herbaceous broad-leaved plants), vines, grasses, and grass-like plants.
PERCENT SHRUBS
Shrubs are all woody-stemmed species not measured as trees.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 45 of 86
PERCENT SEEDLINGS
Record seedling cover only for tree species less than 12 inches (0.30 m) in height. Measure height
perpendicular to the ground. Seedlings greater than 12 inches (0.30 m) in height are not measured
as part of the understory data, rather are measured as part of the tree data described in
Subsection 1.6.5.1 (Figure 1-4).
> 1.0 in. (2.54 cm) DBH
> 1 ft. (0.3 m) tall
< 1.0 in. (2.54 cm) DBH
< 1 ft. (0.3 m) tall
t^fi'tft^j'kf'y^#tff^^
Understory
Seedling
Microplot
Seedling
Microplot
Sapling
0195msd94.fig-4
Figure 1-4. Distinctions among trees less than 5.0 in. (12.7 cm) DBH.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 46 of 86
1.6.5 /If/crop/of Tree Data
Rates of regeneration constitute an important aspect of forest health and are obtained by tallying
seedlings and saplings (trees less than 5.0 inches [12.7 cm] DBH). Seedlings and saplings are too
numerous to be measured on the subplots within a reasonable time, therefore they are tallied on the
smaller microplots. Besides providing information concerning regeneration, these data are used to
supplement the subplot tree data, since a variety of understory tree species never reach the 5.0 inch
(12.7 cm) diameter threshold required for inclusion on the subplots, even when fully grown. All living trees
less than 5.0 inches (12.7 cm) DBH encountered the first time a microplot is established, and all trees that
grow into each microplot thereafter, are monitored until they either die or grow over the 5.0 inch (12.7)
diameter threshold and into the subplot. The procedures described below form the basis of an intricate
accounting system by which these trees are selected for long-term monitoring and then followed as stands
develop over time. Microplot sampling procedures incorporate two different protocols as described below
-- one for seedlings and one for saplings.
1.6.5.1 Seedlings
Procedure
Microplot seedlings are trees at least 12 inches (0.3 m) in height but less than 1.0 inch (2.54 cm) DBH
(timber species) and woodland species with no stem 1.0 inch (2.54 cm) or more DRC (Figure 1.4).
Seedlings less than 12 inches (0.3 m) are tallied with the understory vegetation (Subsection 1.6.4).
Seedlings can originate from seeds, sprouts, or layering, and are measured on the 1/300-acre (1/750
hectare) microplot (radius is 6.8 feet [2.07 m]) offset 90° and 12 feet (3.66 m) from each subplot center.
They are tallied in groups by (1) species, (2) condition class, (3) crown class, and (4) crown vigor class.
In other words, count the trees by species and then:
• Divide the species counts into condition classes.
Divide the species/tree condition counts into crown classes.
Divide the species/tree condition/crown counts into crown vigor classes.
(NOTE: Include only seedlings with stems inside the microplot perimeter.)
The quick reference microplot seedling screen (Table 1-8) lists variables to be entered in the PDR.
SPECIES
Select the appropriate species code from the list in Appendix A. If you encounter a species not
listed in Appendix A and are not sure if it should be tallied as a tree, consult your Field Supervisor.
If species cannot be determined in the field, bring branch samples of foliage from the plot to your
State FHM Project Coordinator or Field Supervisor for identification. Collect samples outside of
the subplots from similar specimens and make a note to change the species code later.
CONDITION CLASS
Record the Condition Class within which the seedlings are located. If more than one Condition
Class is present on the microplot, the seedlings should be grouped separately by condition class.
CROWN CLASS
Rate seedling crowns in relation to the sunlight received and proximity to neighboring trees. This
includes all trees, not just other seedlings.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 47 of 86
Code Definition
1 Open grown. Seedlings whose crowns have received full light from above and from all
sides during early development and most of their life. Their crown form or shape appears
to be free of influence from neighboring trees.
2 Dominant. Seedlings with crown extending above the general level of the crown cover and
receiving full light from above and partly from the sides. These trees are taller than the
average trees in the stand and their crowns are well developed, but they could be
somewhat crowded on the sides.
3 Codominant. Seedlings with crowns at the general level of the crown canopy. Crowns
receive full light from above, but little direct sunlight penetrates their sides. Usually they
have medium-sized crowns and are somewhat crowded from the sides. In stagnated
stands, codominant trees have small-sized crowns and are crowded on the sides.
4 Intermediate. These seedlings are shorter than dominant and codominant, but their
crowns extend into the canopy of codominant and dominant trees. They receive little direct
light from above and none from the sides. As a result, intermediates usually have small
crowns and are very crowded from the sides.
5 Overtopped. Suppressed seedlings with crowns entirely below the general level of the
crown canopy that receive no direct sunlight either from above or the sides.
SEEDLING COUNT
Record the number of seedlings in each (1) species, (2) condition class, (3) crown class, and (4)
crown vigor class category. If a category has 100 or more trees, record 99.
CROWN VIGOR
Use the crown classification procedure described for Crown Vigor in Section 2.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 48 of 86
1.6.5.2 Saplings
Procedure
Saplings are live trees between 1.0 inch (2.54 cm) and 4.9 inches (12.69 cm) DBH/DRC (Figure 1-4).
They are alive if they have any living parts (leaves, buds, cambium) at or above DBH. Saplings that have
been temporarily defoliated are still alive. Like seedlings, all sapling variables are measured on a single
1/300-acre microplot (6.8 feet radius) offset from each subplot center. Unlike seedlings, saplings are tallied
separately. Start at an azimuth of 001° from microplot center and continue clockwise around the microplot.
The quick reference microplot sapling screen (Table 1-9) lists the variables to be recorded.
TREE NUMBER
Tree numbers are recorded by field crews on special QA reference plots only (QAStat=3). On all
other plots, tree numbers are assigned during data processing after the field season. This field is
therefore not presented to Mt1 crews. Once assigned, tree numbers are permanent and are
downloaded to future Mt2 and Mt3 crews.
PREVIOUS CONDITION CLASS
Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 survey.
CONDITION CLASS
Record the condition class in which each sapling is presently located.
OFFSET POINT
Record the position from which the tree distances and azimuths are being measured. (See
Subsection 1.6.9.) This variable will not appear on the PDR and is automatically set to "0" unless
Subplot Offset = 1 or Microplot Offset = 1.
Code Definition
0 Normal position (subplot or microplot center)
1 North offset point
2 East offset point
3 South offset point
4 West offset point
OLD TREE HISTORY, LAST TREE HISTORY, CURRENT TREE HISTORY
Tree history codes track the status of the sample tree through each 4-year measurement cycle.
Old Tree History is the status of the tree during the previous Mt1 or Mt3 survey. Last Tree History
is the status of the tree during the previous survey. Both of these values have been downloaded
into the PDR and cannot be modified. Old Tree History and Last Tree History may or may not be
the same. In the absence of Mt2 surveys, Last Tree History will equal Old Tree History. If interim
Mt2 surveys have been conducted, Last Tree History would be the status of the tree at the
previous Mt2 survey.
Current Tree History is the present status of the tree and is depicted by the codes listed below.
The Current Tree History recorded is used to determine which additional variables will be displayed
on the PDR. A complete listing of Current Tree History codes is shown in Table 1-18. An 'x' has
been placed beside those Current Tree History codes that are valid for microplot trees.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 49 of 86
Table 1-18. Valid Microplot Tree History Codes by Measurement Types
Code
01
02
03
04
05
06
07
08
09
10
11
12
13
14
Current Tree History Mt1
Live/Survivor tree x
Ingrowth tree on microplot
Ingrowth tree on subplot
Outgrowth tree from microplot
Dead tree (qualifies as a snag)
Dead tree (does not qualify as a snag)
Cut tree
Land use change
Missed live tree
Extra tree
Access Denied
Dangerous condition
Lost Data
Missed Snag
Mt2
X
X
X
X
X
X
X
X.
X
X
Mt3
X
X
X
X
X
X
X
X
X
X
X
X
Further elaboration on microplot tree history codes is provide below.
Code 01. Live/Survivor trees on the microplot are live trees 1.0-4.9 inches (2.54-12.6 cm) DBH.
Code 01 is used in the following cases:
A live Mt1 sapling encountered for the first time.
A downloaded sapling on an Mt2 plot that is still alive regardless of current DBH.
A live Mt3 sapling encountered for the first time (newly forested plots, points, and condition
classes). These are added by scrolling past all downloaded trees on the appropriate
point(s).
• A downloaded sapling on an Mt3 plot that is still alive and still less than 5.0 inches (12.7
cm) DBH.
Code 02. Ingrowth trees on the microplot are trees on previously forested condition classes that
have grown above the 1.0 inch (2.54 cm) DBH threshold since the previous Mt1/Mt3 survey. This
code is valid only for Mt3 plots.
Code 03. Ingrowth trees on the subplot are trees on previously forested condition classes that
have grown above the 5.0 inch (12.7 cm) DBH threshold since the previous Mt1/Mt3 survey.
These trees were not previously located on the microplot, and this code is reserved for subplot
trees.
Code 04. Outgrowth trees from the microplot are downloaded microplot saplings that have grown
above the 5.0 inch (12.7 cm) DBH threshold since the previous Mt1/Mt3 survey. This code is valid
only for Mt3 plots. If such trees are encountered on Mt2 plots, they would be assigned code 01.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 50 of 86
Code 05. The only time a tree on a microplot qualifies as a snag is when a downloaded sapling
grows above 5.0 inches (12.7 cm) DBH, then dies, and is still standing on its own. This code is
valid for Mt2 and Mt3 plots.
Code 06. A downloaded sapling that has died and does not qualify as a snag.
Code 07. A downloaded sapling that has been cut.
Code 08. A downloaded sapling on land that has since been withdrawn from a forest land use,
regardless of whether the tree is alive or dead.
Code 09. A tree that should have been tallied as a microplot sapling at the previous Mt1/Mt3
survey but was missed. It is added to the PDR by scrolling past all downloaded trees on the
appropriate point.
Code 10. A downloaded tree that was tallied as a microplot sapling at the previous Mt1/Mt3 survey
but should not have been.
Code 11. A downloaded sapling on land to which access has been denied.
Code 12. A downloaded sapling on land that is too hazardous to occupy.
Code 13. A downloaded sapling on a plot that cannot be relocated. This code is valid only after
the close of the field season.
Code 14. This is a snag that should have been tallied on the subplot at the previous Mt1/Mt3
survey but was missed. This code is reserved for the subplot.
FADER (CA/PNW PS Only)
Fader trees have fading foliage and are expected to die within the next year.
Code Definition
0 Not a fader tree
1 Fader tree
SPECIES
Select the appropriate species code from the list in Appendix A. If you encounter a species not
listed in Appendix A and are not sure if it should be tallied as a tree, consult your Field Supervisor.
If species cannot be determined in the field, bring branch samples of foliage from the plot to your
State FHM Project Coordinator or Field Supervisor for identification. Collect samples outside of
the subplots from similar specimens and make a note to change the species code later.
OLD DIAMETER at BREAST HEIGHT
This is the DBH that was assigned at the previous Mt1 or Mt3 survey. It has been downloaded
from the previous inventory. Any change made to this field signifies a misclassification at the time
of the previous inventory. "DBHCheck" should be set to 1 and an explanation is required in the
notes if the old DBH is changed.
If a tree was missed during a previous survey (Current Tree History, code 09), estimate the
diameter at the time the tree was missed, and then record the estimated old DBH.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 51 of 86
DIAMETER at BREAST HEIGHT
Measure diameter at 4.5 ft (1.37 m) above the groundline, on the uphill side of the tree. If the tree
has been measured during a previous survey, remeasure DBH at the painted mark. If the paint
is starting to wear off, mark the tree again at the same spot.
If this is the first time the tree has been measured, mark the point of measurement with a thin line
of paint placed 0.1 inch (1 crn) below the point of measurement. Mark the tree before the taking
the measurement, and then use a D-tape to measure outside bark diameter. Round the diameter
down to the last 0.1 inch (1 mm) and code as 3 digits (4 digits in metric). For example, 3.68
inches is coded 036 (36.84 cm is coded as 0368).
Upon encountering any irregularities such as swellings, bumps, depressions, or branches, mark
and measure diameter immediately above the irregularity wherever the stem form appears normal.
For fenceline trees that contain wire, mark and measure the diameter at the normal 4.5 ft (1.37 m)
height. Mark and measure swell-butted trees (such as cypress, tupelo, sitka spruce, and redwood)
at 1.5 ft (0.5 m) above the pronounced swell or bottleneck if the bottleneck is more than 3.0 ft
(1 m) high (Figure 1-5).
Forked trees require special attention. In order to qualify as a fork, the stem in question must be
at. least 1/3 the diameter of the main stem and must branch out from the main stem at an angle
of 45 degrees or less.
Trees forked below 1 ft (.3 m) are considered to be two separate trees. Distances and azimuths
are measured individually to each tree, so they may differ. In the case of stump sprouts or clumps
that are forked below 1 ft (.3 m), horizontal distance (and azimuth) is measured to where the stem
enters the stump, so it is possible for some stems to be within the limiting distance of the plot and
others to be beyond the limiting distance. DBH is measured for each stem at 4.5 ft (1.37 m) above
the ground.
Trees that have no forks below 4.5 ft (1.37 m) are measured as one single tree. If a fork occurs
at or immediately above 4.5 ft (1.37 m), mark and measure diameter below the fork just beneath
any swelling that would inflate DBH.
Trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m) are handled differently. All forks are measured
individually, but only one distance and azimuth (to the central stump) is used for all. Thus, in the
case of stump sprouts or clumps that are forked above 1 ft (.3 m), the limiting distance is the same
for all forks--they are either all on, or all off the plot.
For trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m), the DBH of each fork is measured at a
point 3.5 ft (1.07 m) above the crotch where the bark separates. It is possible to have multiple
forks, but count only forks that originate from the main stem (i.e., never count a fork that originates
from another fork). If a main stern forks again within 3.5 ft of a lower fork, measure up another 3.5
ft (1.07 m) from the second fork. For example, a tree with a main stem that forks at 2.0 ft (0.61
m) and 5.0 ft (1.52 m) requires three DBH measurements. The lower fork is measured at a point
3.5 ft (1.07 m) above the crotch. Since the main stem forks again within 3.5 ft (1.07 m) of the
lower crotch, the upper two forks are measured at a point 3.5 ft (1.07 m) above the second fork.
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r
EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 52 of 86
t
• DBH
• DBH
4.5' (1.37 m)
4.5' (1.37 m)
1 .Tree on slope.
2. Tree on level ground.
4.5'(1.
Diameter
Point
j»»k*«» If— Diameter
Point 4.5'(1.37
$?^
2. Tree on level ground.
Diameter
Point
5' (1.07 m)
4.5' (1.37 m)
4. Tree forks at or
above 4.5 feet
5. Tree forks below 4.5 feet
6. Tree with branch.
Diameter
Point
3' (1 m) or more
4.5' (1.37 m)
S^J^^SMgg
7. Tree with swell at 4.5 feet.
Diameter Point
,1.5' (0.37m)
8. Bottleneck tree.
9. Windthrown/dead tree
0195msd94.fig-5
Figure 1-5. Where to measure diameter breast height in a variety of situations.
Upon remeasurement, if a previously tallied fork has died, move the point of DBH on the living
stem back to where it would have been if there had never been a fork, and record a "1" for DBH
CHECK. In addition, make a note that a fork has died and the point of DBH has been moved.
DBH CHECK
Identify any irregularities in DBH measurement positions (e.g., abnormal swellings, diseases,
damage, new measurement positions, etc.) that invalidate the use of this tree in diameter
growth/change analyses. Upon diameter remeasurement, DBH check will always equal 1 if the tree
is measured somewhere other than the paint mark left by the previous crew (e.g., a fork dies and
the point of measurement is moved back to 4.5 ft [1.37 m]). DBH check should also be set to 1
if either DBH or old DBH has been estimated for any reason (e.g., a missed tree). Whenever code
1 is used, further explanation is required in the notes.
Code Definition
0 No problem with DBH Measurement
1 Irregular DBH measurement
LIVE/DEAD TREE (CA/PNW PS Only)
Specify whether the tree is alive, standing dead, or dead and down.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 53 of 86
Code Definition
0 Tree is living.
1 Tree is standing dead.
2 Tree is dead and down.
OLD STEM COUNT (WEST ONLY)
For western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). This is the stem count recorded at the previous Mt1 or Mt3 survey.
STEM COUNT (WEST ONLY)
For western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). If there is at least one stem 1.0 inches (2.54 cm) DRC or greater, then
record the total number of stems measured for DRC (e.g., all qualifying stems). Note that all
qualifying stems must be at least 1.0 inches (2.54 cm) in diameter at the root collar and contribute
to the overall crown. For dead stems, a judgement call must be made as to whether they had
contributed to the crown at one time, or whether they were just interior branches. Dead stems
must still be at least 1.0 (2.54 cm) inches in diameter at the base.
OLD DIAMETER AT ROOT COLLAR (WEST ONLY)
For western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). This is the diameter at root collar (DRC) recorded at the previous Mt1
or Mt2 survey.
DIAMETER at ROOT COLLAR (WEST ONLY)
For Western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). All western woodland species are measured for diameter at root collar
(DRC). This procedure has been adopted as a multistem equivalent to the DBH. Tally woodland
saplings with at least one stem greater than or equal to 1.0 inches (2.54 cm) and a cumulative
DRC less than 5.0 inches (12.70 cm). Measure all qualifying stems and calculate the DRC using
the formula below.
]P (stem diameter^
Round the result to the nearest 0.1 inch (2 mm) and record. For single-stemmed woodland trees,
the DRC is equal to the diameter of that stem at its root collar. The PDR is equipped with a
program for calculating this formula in the "Pop Up" menu. This "Pop Up" program is limited to a
total of 13 stems. If more than 13 stems are encountered, DRC must be manually calculated.
Record all pertinent stem measurements on the supplemental Multistemmed Woodland Tally form
to provide for future tracking of individual stem data. Record dead stems with the small letter "d"
following the 3 digit code (4 digit metric).
Some woodland trees, particularly juniper and oak, are extremely variable in form. Measure the
DRC of stems so that the measurements are consistent with the volume above the stem(s),
especially when trees are extremely deformed at the base. For example, when a single diameter
measurement taken below several main stems originating near the root collar does not reasonably
represent the tree volume of the stems, individually measure the qualifying stems (above the single
diameter location) and compute the DRC (see Figure 1-6). When in doubt, measure individual
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 54 of 86
stems rather than one large stem. Mark the point of diameter with paint to maintain consistency
upon remeasurement.
Whenever DRC is impossible or extremely difficult to measure with a diameter tape (e.g., due to
thorns, extreme limbiness, packrat's nest), the stem(s) may be measured to the last whole inch
(centimeter) with the measurement poles. In this case, always record the stem(s) to the nearest
1-inch (1-cm) class and use these values in DRC computations.
1. Measure at ground line
when reasonable.
3. Multistemmed above
diameter.
5. Measure missing stem(s).
Compute DRC.
2. Measure above butt swell.
4. Excessive diameter below stems.
Measure stems. Compute DRC.
6. Multistemmed at or below
ground. Compute DRC.
0195msd94.fig-6
Figure 1-6. Points of diameter measurement on woodland trees. Measure just above ground level and above any swell
present.
HORIZONTAL DISTANCE
Measure the horizontal distance (to the nearest 0.1 ft [0.1 m]) from the microplot center to the
pith at the base of the sapling.
NOTE: For trees forked at or above 1 ft (.3 m), record the distance to the central stem at
ground level for all forks. For trees forked below 1 ft (.3 m), record the distance to where each
individual stem enters the stump (or clump).
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 55 of 86
For all western woodland trees, the horizontal distance should be taken from the "geographic
center" to the subplot/microplot center. The geographic center is a point of equal distance
between all stems tallied for a given woodland tree. If only one stem is tallied, the procedure is
the same as for timber trees.
NOTE: For Mt3 surveys, if a tree has grown out of the microplot (Current Tree History, 04 or
05), the must be remeasured from the subplot center.
AZIMUTH
From microplot center, sight the base of each tree with a compass (sight the geographic center for
western woodland species). Record azimuth (to the nearest degree) as a 3-digit code ranging from
001 to 360. Use 360 for due north.
NOTE: For Mt3 surveys, if a tree has grown out of the microplot (Current Tree History, 04 or 05),
the azimuth must be remeasured from the subplot center.
NOTE: For trees forked at or above 1 ft (.3 m), record the azimuth to the central stem at ground
level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each individual
stem enters the stump (or clump).
MORTALITY YEAR
In the case of tree histories 05, 06 and 07, record the year (2-digit) in which the sapling died or
was felled.
ESTIMATED MORTALITY YEAR (CA/PNW PS Only)
In the case of Mtl mortality, record the year (2-digit) in which the sapling died.
NONFOREST YEAR
In the case of tree history code 08, record the year (2-digit) in which the land use became
nonforest.
GROUND YEAR
• Record the year (2-digit) in which a snag falls to the ground or no longer stands on its own.
CAUSE OF DEATH
Assign a cause of death to all trees that have died or been cut since the previous survey. In some
cases, it will be difficult to determine cause of death, but do not guess. If uncertain, use code 800.
If a cause of death is not on the list, use code 999 and explain in the notes. Code 001 is assigned
at processing for all trees that are dead when initially encountered (e.g., MT1 snags).
Code Definition
001 Dead tree when first encountered
100 Insects
210 Blister rust (CA/PNW PS only)
200 Disease
300 Fire
400 Animal
500 Weather
600 Suppression / Competition
700 Logging and related; human damage
800 Unknown'
999 Other than described above; needs explanation in notes.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 56 of 86
CROWN CLASS
Rate the sapling's crown in terms of sunlight received and proximity to its neighbors. See
Subsection 1.6.6 for a more comprehensive description of the crown class coding system.
Code Definition
1 Open Growth
2 Dominant
3 Codominant
4 Intermediate
5 Overtopped (suppressed)
NOTES
Indicate if any written notes are to be recorded for this tree. A "1" downloaded to this field
indicates the presence of notes from a previous field.
Code Definition
0 No notes will be recorded for this tree.
1 Written notes will be recorded for this tree
DESCRIPTION
Record tree-level notes in the alphabetic field provided on the PDR. These notes will be reviewed
by the regional coordinator and passed on to future crews if appropriate.
ADDITIONAL CROWN AND DAMAGE VARIABLES
The following crown classifications are described in Section 2: Crown Vigor, Crown Diameter Wide
(CA), Crown Diameter 90° (CA), Live Crown Ratio (CA), Crown Density (CA), Crown Dieback (CA),
and Foliage Transparency (CA).
The following damage classifications are described in Section 3: Location 1-3, Damage 1-3, and
Severity 1-3.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 57 of 86
1.6.6 Subplot Tree Data
Trees 5.0 inches (12.7 cm) DBH and larger are the main focus of FHM detection monitoring. Even
after a tree completes its life cycle, it continues to influence biodiversity by providing valuable habitat for
wildlife and by contributing to the nutrient cycling process. All trees encountered the first time a plot is
established, and all trees that grow into each subplot thereafter, are monitored until they are dead and
down. The procedures described below form the basis of an intricate accounting system by which these
trees are selected for long-term monitoring and then followed as stands develop over time.
Procedure
Tally all living trees and standing dead trees (snags) 5.0 inches (12.7 cm) DBH/DRC and larger on
each 1/24 acre (1/60 hectare) subplot. Trees are alive if they have any living parts (leaves, buds cambium)
at or above DBH. Trees that have been temporarily defoliated are still alive. To qualify as a snag, a dead
tree must stand at least 4.5 ft (1.37 m) above the ground and be at least-5.0 inches (12.7 cm) in diameter
at DBH. Snags must be self supporting, so dead trees supported by other trees (or other snags) do not
qualify. Begin tallying trees at an azimuth of 001° from subplot center and continue clockwise around the
subplot. Record the measurement variables listed on the quick reference subplot tree screen (Table 1-10).
TREE NUMBER
Tree numbers are recorded by field crews on special QA reference plots only (QAStat=3). On all
other plots, tree numbers are assigned during data processing after the field season. This field is
therefore not presented to Mt1 crews. Once assigned, tree numbers are permanent and are
downloaded to future Mt2 and MT3 crews.
PREVIOUS CONDITION CLASS
Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 survey.
(Code 1 = Condition 1... Code 9 = Condition 9).
CONDITION CLASS
Record the condition class in which each tree is presently located. (Code 1 = Condition 1 ... Code
9 = Condition 9).
OFFSET POINT
Record the position from which the tree distances and azimuths are being measured. This variable
will not appear on the PDR and is automatically set to "0" unless Subplot Offset = 1 or Microplot
Off set = 1.
Code Definition
0 Normal position (subplot or microplot center)
1 North offset point
2 East offset point
3 South offset point
4 West offset point
OLD TREE HISTORY, LAST TREE HISTORY, CURRENT TREE HISTORY
Tree history codes track the status of the sample tree through each 4-year measurement cycle.
Old Tree History is the status of the tree at the previous Mt1 or Mt3 survey. Last tree History is
the status of the tree at the previous survey. Both of these values have been downloaded into the
PDR and can not be modified. Old Tree History and Last Tree History may or may not be the
same. In the absence of Mt2 surveys, Last Tree History will equal Old Tree History. If interim Mt2
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 58 of 86
surveys have been conducted, Last Tree History would be the status of the tree at the previous
Mt2 survey.
Current tree history is the present status of the tree and is depicted by the codes listed below.
The Current Tree History recorded is used to determine which additional variables will be displayed
on the PDR. A complete listing of Current Tree History codes is shown (Table 1-19). An 'x' has
been placed beside those current tree history codes that are valid for microplot trees.
Table 1-19. Valid Subplot Tree History Codes by Measurement Types
Code
01
02
03
04
05
06
07
08
09
10
11
12
13
14
Current Tree History
Live/Survivor tree
Ingrowth tree on microplot
Ingrowth tree on subplot
Outgrowth tree from microplot
Dead tree (qualifies as a snag)
Dead tree (does not qualify as a snag)
Cut tree
Land use change
Missed live tree
Extra tree
Access Denied
Dangerous condition
Lost Data
Missed Snag
Mt1 Mt2
X X
X X
X
X
X
X
X
X
X
X
X
Mt3
X
X
X
X
X
X
X
X
X
X
X
X
Further elaboration on subplot tree history codes is provided below.
Code 01. Live/Survivor trees on the subplot are live trees equal to or greater than 5.0 inches (12.7
cm) DBH. Code 01 is used in the following cases:
A live Mt1 tree encountered for the first time.
A downloaded Mt2 or Mt3 tree that is still alive.
• A live Mt3 tree encountered for the first time (newly forested plots, points, and condition
classes). These are added by scrolling past all downloaded trees on the appropriate
point(s).
Code 02. This code is for trees that grow above the 1.0 inch (2.54 cm) diameter threshold on the
microplot and is reserved for microplot trees only.
Code 03. Ingrowth trees on the subplot are trees on previously forested condition classes that
have grown above the 5.0 inch (12.7 cm) DBH threshold since the previous MT1/MT3 survey.
These trees were not previously located on the microplot; trees that grow above 5.0 inches (12.7
cm) on the microplot are assigned code 04 and are recorded on the microplot screen.
Code 04. This code is for trees that grow above the 5.0 inch (12.7 cm) DBH threshold on the
microplot and is reserved for microplot trees only.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 59 of 86
Code 05. Snags are standing dead trees equal to or greater than 5.0 (12.7 cm) inches DBH.
Code 05 is used on the subplot in the following cases:
A Mt1 snag encountered for the first time.
A downloaded Mt2 or Mt3 tree (or snag) that is currently a snag.
A Mt3 snag encountered for the first time. Most often, new Mt3 snags are associated with
newly forested plots, points, and condition classes. Occasionally, a tree will grow into the
subplot and die before ever being tallied as a live tree. All of these cases are added to
the PDR by scrolling past all downloaded trees on the appropriate point(s).
Code 06. A downloaded tree that has died and fallen, or a snag that has fallen.
Code 07. A downloaded tree or snag that has been cut.
Code 08. A tree on land that has been withdrawn from a forest land use, regardless of whether
the tree is alive, dead, standing, or down.
Code 09. A tree that should have been tallied as a live subplot tree at the previous Mt1/Mt3 survey
but was missed. It is added to the PDR by scrolling past all downloaded trees on the appropriate
point.
Code 10. A downloaded tree that was tallied as a subplot tree at the previous Mt1/Mt3 survey but
should not have been.
Code 11. A downloaded tree to which access has been denied.
Code 12. A downloaded tree on land that is too hazardous to occupy.
Code 13. A downloaded tree on a plot that cannot be relocated. This code is valid only after the
close of the field season.
Code 14. This is a snag that should have been tallied on the subplot at the previous Mt1/Mt3
survey but was missed. If a tree has grown above 5.0 inches (12.7 cm) and died since the last
Mt1/Mt3, it should be assigned code 05 instead of code 14.
FADER (CA/PNW PS Only)
Fader trees have fading foliage and are expected to die within the next year.
Code Definition
0 Not a fader tree
1 Fader tree
SPECIES
Select the appropriate species code from Appendix A. If you encounter a species not listed in
Appendix A and are not sure if it should be tallied as a tree, consult your Field Supervisor. If
species cannot be determined in the field, bring branch samples of foliage from the plot to your
State FHM Project Coordinator or Field Supervisor for identification. Collect samples outside of
the subplots from similar specimens and make a note to change the species code later.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 60 of 86
OLD DIAMETER at BREAST HEIGHT
This is the DBH that was assigned at the previous Mt1 or Mt3 survey. It has been downloaded
from the previous inventory. Any change made to this field signifies a misclassification at the time
of the previous inventory. "DBHCheck" should be set to 1 and an explanation is required in the
notes if the old DBH is changed.
If a tree was missed during a previous survey (Current Tree History, code 9), estimate the diameter
at the time the tree was missed, and then record the estimated old DBH.
DIAMETER at BREAST HEIGHT
Measure diameter at 4.5 ft (1.37 m) above the groundline, on the uphill side of the tree. If the tree
has been measured during a previous survey, remeasure DBH at the painted mark. If the paint
is starting to wear off, mark the tree again at the same spot.
If this is the first time the tree has been measured, mark the point of measurement with a thin line
of paint placed 0.1 inch (1 cm) below the point of measurement. Mark the tree before the taking
the measurement, and then use a D-tape to measure outside bark diameter. Round the diameter
down to the last 0.1 inch (1 mm) and code as 3 digits (4 digits in metric). For example, 3.68
inches is coded 036 (36.84 cm is coded as 0368).
Upon encountering any irregularities such as swellings, bumps, depressions, or branches, mark
and measure diameter immediately above the irregularity wherever the stem form appears normal.
Forfenceline trees that contain wire, mark and measure the diameter at the normal 4.5 ft (1.37 m)
height. Mark and measure swell-butted trees (such as cypress, tupelo, sitka spruce, and redwood)
at 1.5 ft (0.5 m) above the pronounced swell or bottleneck if the bottleneck is more than 3.0 ft (1
m) high (Figure 1.5).
Forked trees require special attention. In order to qualify as a fork, the stem in question must be
at least 1/3 the diameter of the main stem and must branch out from the main stem at an angle
of 45 degrees or less.
Trees forked below 1 ft (.3 m) are considered to be two separate trees. Distances and azimuths
are measured individually to each tree, so they may differ. In the case of stump sprouts or clumps
that are forked below 1 ft (.3 m), horizontal distance (and azimuth) is measured to where the stem
enters the stump, so it is possible for some stems to be within the limiting distance of the plot, and
others to be beyond the limiting distance. DBH is measured for each stem at 4.5 ft (1.37 m) above
the ground.
Trees that have no forks below 4.5 ft (1.37 m) are measured as one single tree. If a fork occurs
at or immediately above 4.5 ft (1.37 m), mark and measure diameter below the fork just beneath
any swelling that would inflate DBH.
Trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m) are handled differently. All forks are measured
individually, but only one distance and azimuth (to the central stump) is used for all. Thus, in the
case of stump sprouts or clumps that are forked above 1 ft (.3 m), the limiting distance is the same
for all forks-they are either all on, or all off the plot.
For trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m), the DBH of each fork is measured at a
point 3.5 ft (1.07 m) above the crotch where the bark separates. It is possible to have multiple
forks, but count only forks that originate from the main stem (i.e., never count a fork that originates
from another fork). If a main stem forks again within 3.5 ft of a lower fork, measure up another 3.5
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 61 of 86
ft (1.07 m) from the second fork. For example, a tree with a main stem that forks at 2.0 ft (0.61
m) and 5.0 ft (1.52 m) requires three DBH measurements. The lower fork is measured at a point
3.5 ft (1.07 m) above the crotch. Since the main stem forks again within 3.5 ft (1.07 m) of the
lower crotch, the upper two forks are measured at a point 3.5 ft (1.07 m) above the second fork.
Upon remeasurement, if a previously tallied fork has died, move the point of DBH on the living
stem back to where it would have been if there has never been a fork, and record a "1" for DBH
CHECK. In addition, make a note that a fork has died and the point of DBH has been moved.
DBH CHECK
Identify any irregularities in DBH measurement positions (e.g., abnormal swellings, diseases,
damage, new measurement positions, etc.) that invalidate the use of this tree in diameter
growth/change analyses. Upon diameter remeasurement, DBH check will always equal 1 if the tree
is measured somewhere other than the paint mark left by the previous crew (e.g., a fork dies and
the point of measurement is moved back to 4.5 ft [1.37 m]). DBH check should also be set to 1
if either DBH or old DBH has been estimated for any reason (e.g., a missed tree). Whenever code
1 is used, further explanation is required in the notes.
Code Definition
0 No problem with DBH Measurement
1 Irregular DBH measurement
LIVE/DEAD TREE (PNW PS Only)
Specify whether the tree is alive, standing dead, or dead and down.
Code Definition
0 Tree is living.
1 Tree is standing dead.
2 Tree is dead and down
OLD STEM COUNT (WEST ONLY)
For western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). This is the stem count recorded at the previous Mt1 or Mt3 survey.
STEM COUNT (WEST ONLY)
For western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). If there is at least one stem 1.0 inches (2.54 cm) DRC or greater, then
record the total number of stems measured for DRC (e.g., all qualifying stems). Note that all
qualifying stems must be at least 1.0 inches (2.54 cm) in diameter at the root collar and contribute
to the overall crown. For dead stems, a judgement call must be made as to whether they had
contributed to the crown at one time, or whether they were just interior branches. Dead stems
must still be at least 1.0 inches (2.54 cm) in diameter at the base.
OLD DIAMETER AT ROOT COLLAR (WEST ONLY)
For western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). This is the diameter at root collar (DRC) recorded at the previous Mt1
or Mt2 survey.
DIAMETER at ROOT COLLAR (WEST ONLY)
For western woodland species only. Western woodland species are denoted by a "(ww)" in the
species list (Appendix A). AH western woodland species are measured for diameter at root collar
(DRC). This procedure has been adopted as a multistem equivalent to the DBH. Tally woodland
trees with at least one stem greater than or equal to 1.0 inches (2.54 cm) and a cumulative DRC
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of 5.0 inches (12.7 cm) or greater. Measure all qualifying stems and calculate the DRC using the
formula below.
DRC =
stem diameter^1
Round the result to the nearest 0.1 inch (2 mm) and record. For single-stemmed woodland trees,
the DRC is equal to the diameter of that stem at its root collar. The PDR is equipped with a
program for calculating this formula in the "Pop Up" menu. This "Pop Up" program is limited to a
total of 13 stems. If more than 13 stems are encountered, DRC must be manually calculated.
Record all pertinent stem measurements on the supplemental Multistemmed Woodland Tally form
to provide for future tracking of individual stem data. Record dead stems with the small letter "d"
following the 3 digit code (4 digit metric).
Some woodland trees, particularly juniper and oak, are extremely variable in form. Measure the
DRC of stems so that the measurements are consistent with the volume above the stem(s),
especially when trees are extremely deformed at the base. For example, when a single diameter
measurement taken below several main stems originating near the root collar does not reasonably
represent the tree volume of the stems, individually measure the qualifying stems (above the single
diameter location) and compute the DRC (see Figure 1-6). When in doubt, measure individual
stems rather than one large stem. Mark the point of diameter with paint to maintain consistency
upon remeasurement.
Whenever DRC is impossible or extremely difficult to measure with a diameter tape (e.g., due to
thorns, extreme limbiness, packrat's nest), the stem(s) may be measured to the last whole inch
(centimeter) with the measurement poles. In this case, always record the stem(s) to the nearest
1-inch (1-cm) class and use these values in DRC computations.
HORIZONTAL DISTANCE
Measure the horizontal distance (to the nearest 0.1 foot [0.1 m]) from the subplot center to the pith
at the base of the tree.
For all western woodland trees, the horizontal distance should be taken from the "geographic
center" to the subplot/microplot center. The geographic center is a point of equal distance between
all stems tallied for a given woodland tree. If only one stem is tallied, the procedure is the same
as for timber trees.
NOTE: For trees forked at or above 1 ft (.3 m), record the distance to the central stem at ground
level for all forks. For trees forked below 1 ft (.3 m), record the distance to where each individual
stem enters the stump (or clump).
AZIMUTH
From subplot center, sight the base of each tree with a compass (sight the geographic center for
western woodland species). Record azimuth (to the nearest degree) as a 3-digit code ranging from
001 to 360. Use 360 for due north.
NOTE: For trees forked at or above 1 ft (.3 m), record the azimuth to the central stem at ground
level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each individual
stem enters the stump (or clump).
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MORTALITY YEAR
In the case of tree histories 05, 06 and 07, record the year (2-digit) in which the tree died or was
felled.
ESTIMATED MORTALITY YEAR (CA/PNW PS)
In the case of Mt1 mortality, record the year (2-digit) in which the tree died.
NONFOREST YEAR
In the case of tree history, code 08, record the year (2-digit) in which the land use become
nonforest.
GROUND YEAR
Record the year (2-digit) in which a snag falls to the ground or no longer stands on its own.
CAUSE OF DEATH
Assign a cause of death to all trees that have died or been cut since the previous survey. In some
cases, it will be difficult to determine cause of death, but do not guess. If uncertain, use code 800.
If a cause of death is not on the list, use code 999 and explain in the notes. Code 001 is assigned
at processing for all trees that are dead when initially encountered (e.g., MT1 snags).
Code Definition
001 Tree dead when first encountered
100 Insects
210 Blister rust (CA/PNW PS only)
200 Disease
300 Fire
400 Animal
500 Weather
600 Suppression/Competition
700 Logging and related; human damage
800 Unknown
000 No secondary cause
999 Other than described above; needs explanation in notes.
CROWN CLASS
Rate the tree crown in terms of sunlight received and proximity to neighboring trees (Figure 1-7).
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0195msd94.fig-7
Figure 1-7. Relative crown positions of dominant (D), codominant (C), intermediate (I), and overtopped (O) trees.
Definition
Open Grown. Trees whose crowns have received full light from above and
from all sides during early development and most of their life. Their crown
form or shape appears to be free of influence from neighboring trees.
2 Dominant. Trees with crown extending above the general level of the crown
cover and receiving full light from above and partly from the sides. These
trees are taller than the average trees in the stand and their crowns are well
developed, but they could be somewhat crowded on the sides.
3 Codominant. Trees with crowns at the general level of the crown canopy.
Crowns receive full light from above but little direct sunlight penetrates their
sides. Usually they have medium-sized crowns and are somewhat crowded
from the sides. In stagnated standards, codominant trees have small-sized
crowns and are crowded on the sides.
4 Intermediate. These trees are shorter than dominant and codominants, but
their crowns extended into the canopy of codominant and dominant trees.
As a result, intermediates usually have small crowns and are very crowded
from the sides.
5 Overtopped. Suppressed trees with crowns entirely below the general level
of the crown canopy that receive no direct sunlight either from above or the
sides.
NOTES
Indicate if any written notes are to be recorded for this tree. A "1" downloaded to this field
indicates the presence of notes from a previous field.
Code Definition
0 No notes will be recorded for this tree.
1 Written notes will be recorded for this tree
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DESCRIPTION
Record tree-level notes in the alphabetic field provided on the PDR. These notes will be reviewed
by the regional coordinator and passed onto future crews if appropriate.
ADDITIONAL CROWN AND DAMAGE VARIABLES
The following crown classifications are described in Section 2: Crown Vigor, Crown Diameter
Wide, Crown Diameter 90°, Live Crown Ratio, Crown Density, Crown Dieback, and Foliage
Transparency.
The following damage classifications are described in Section 3: Location 1-3, Damage 1-3, and
Severity 1-3.
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1.6.7 Full-Hectare Plots (CA/PNW PS only)
Full-hectare plots are available for situations where the 1/6-acre (l/l5th-hectare) area covered by the
four subplots is too small to provide an accurate estimate of tree and stand characteristics. Full-hectare
plots are done for two reasons: (1) To obtain more sample trees in stands containing extremely large
trees, such as redwoods and sequoias, and (2) to obtain better estimates of tree mortality. Full-hectare
plots are supplementary. They do not replace the standard subplots, so the regular plot network remains
consistent across the landscape.
Full-hectare plots include the circular area defined by a 186.2 ft (56.4 m) radius extending from the
center of Subplot 1. Both boundary and tree data are recorded on the full hectare. Two types of trees are
tallied: (1) Large, living trees greater than or equal to 40 inches (100 cm) DBH (Subsection 1.6.7.2), and
(2) mortality trees (Subsection 1.6.7.3). "Fader" trees are counted among the living and the dead on the
full hectare. These trees are trees with fading foliage that are expected to die within the next year.
Although they are tallied as living trees on the standard FHM subplots and microplots, and as large trees
on the full hectare (if they are at least 40 inches (100 cm) DBH), they are recorded again on the mortality
plot to provide consistency with Forest Pest Management (FPM) mortality data.
1.6.7.1 Full-Hectare Boundary Delineation (CA/PNW PS Only)
All full-hectare plots that straddle more than one condition class are mapped by delineating the
boundaries between contrasting conditions. These procedures are similar to those used for mapping
subplots (see Subsection 1.6.3.2), except there are no provisions to reference full-hectare boundaries to
offset points.
Boundary data are used to compute the area of all fragments on the hectare by condition class. In
addition to recording the boundary information described below, a map of condition boundaries should also
be sketched on pre-printed plot diagrams.
Procedure
Delineate the boundary of each condition class that differs from the condition at a full-hectare plot
center with a series of reference points. Boundary delineation is accomplished by recording azimuths and
distances from the plot center to the perimeter reference points. Each boundary is marked by a maximum
of three points-two where the boundary intersects the circumference of the hectare, and one "corner" point
between the two end points, if necessary. Only the corner points require a distance, since the distance
from the center to the perimeter is constant.
When a boundary between forest and nonforest is clearly marked (i.e., by a fence, fireline, ditch), the
boundary should follow the stems of the trees at the forest edge. When a boundary between two
contrasting forest conditions is not clearly marked, "average in" the boundary between the two conditions.
Upon remeasurement, do not move boundaries unless there has been a definite change, an obvious
mistake made during the previous visit, or a clear boundary is no longer detectable.
When the boundary between two different conditions is separated by a narrow linear inclusion (woods
road, fireline, ditch), always establish the boundary to the nearest edge of the inclusion. The quick
reference full-hectare boundary screen (Table 1-11) lists the full-hectare boundary delineation variables.
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HECTARE CENTER CONDITION
This is the Condition Class of the hectare plot center. Record the previously defined condition that
corresponds to the subplot center.
HECTARE CONTRASTING CONDITION
Record the Condition Class that contrasts with the Condition Class located at the hectare plot
center (i.e., the Condition Class on the other side of the boundary line).
LEFT AZIMUTH
The azimuth (001-360°) to the farthest left point (facing the contrasting condition) where the
boundary intersects the hectare perimeter.
CORNER AZIMUTH
The azimuth (000-360°) from the hectare plot center to a corner or curve in a boundary. If a
boundary is best described by a straight line between the two circumference points, then record
000 for corner azimuth (000=none).
CORNER DISTANCE
Using a distance range finder or other accepted method, approximate the distance from the hectare
plot center to the boundary corner point. Record hectare distances to the nearest 1 ft (0.1 m).
RIGHT AZIMUTH
The azimuth (001-360°) to the farthest right point (facing the contrasting condition) where the
boundary intersects the hectare perimeter.
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1.6.7.2 Full-Hectare Large-Tree Cruise (CA/PNW PS Only)
The purpose of the full-hectare cruise is to obtain better estimates of tree and stand characteristics
associated with extremely large trees. This screen is activated on any plot that has at least one forested
condition class on one of the regular subplots and has at least one tree 40 inches (100 cm) DBH or larger
within 186.2 ft (56.4 m) of the center of Subplot 1. Once prompted, the full-hectare module remains active
in future surveys until there are no longer any trees greater than 40 inches (too cm) on the hectare. The
full-hectare large tree screen is used in conjunction with the Full-Hectare Boundary Delineation module,
so Tally trees can be assigned to the appropriate condition classes. Western woodland species are not
tallied on the full hectare.
Tree data from the full-hectare cruise are supplemental to data gathered on the subplots and
microplots. The full-hectare cruise is therefore conducted somewhat independently of the standard subplots
and microplots, but Condition Classes defined on subplots are also used for the full hectare. Only trees
40 inches (100 cm) DBH and larger are tallied as part of the large-tree cruise. All full-hectare tree Tally
will also be mapped on hard copy.
The quick reference full-hectare tree screen (Table 1-12) lists the full-hectare large tree variables.
Procedure
HECTARE TREE TYPE
Specify whether the tree is being measured as a large tree or a mortality tree on the full-hectare
plot. The use of Code 1 will activate the prompts for full-hectare large trees, code 2 will activate
the prompts for full-hectare mortality trees. Note: Large fader trees, as well as large mortality
trees (downloaded Mt3 trees with current tree histories of 06) are measured twice on the full
hectare-once as Hectare Tree Type 1 and again as Hectare Tree Type 2.
Code Definition
1 Full-hectare large tree (including large faders)
2 Full-hectare mortality tree (including all faders)
TREE NUMBER
Tree numbers are recorded by field crews on special QA reference plots only (i.e., QA Status =
3). On all other plots, tree numbers are assigned during data processing after the field season.
This field is therefore not presented to Mt1 crews. Once assigned, tree numbers are permanent
and are downloaded to future Mt2 and Mt3 crews.
PREVIOUS CONDITION CLASS
Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 survey.
CONDITION CLASS
Using the same procedures described for subplot trees in Subsection 1.6.1, record the Condition
Class in which the tree is currently located. The tree must be in one of the conditions in the
Hectare Condition List. (Code 1 = Condition ... Code 9 = Condition 9).
TREE LOCATION
Record the appropriate code.
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Code Definition
0 Tree does not occur on subplot or microplot
1 Tree occurs on subplot
2 Tree occurs on microplot
OLD TREE HISTORY, CURRENT TREE HISTORY
Tree history codes track the status of the sample trees through each 4-year measurement cycle.
Old Tree History is the status of the tree at the previous Mt1 or Mt3 survey (there is no provision
for Mt2 full-hectare plots). Old Tree History has been downloaded and cannot be modified.
Current Tree History is the present status of the tree. Select the code below that best describes
the sample tree. The Current Tree History recorded by the field crew is utilized to determine which
additional variables will be displayed on the PDR. A complete listing of full-hectare tree history
codes is provided below (Table 1-20). An 'x' has been placed beside those Current Tree History
codes that are valid for full-hectare large trees. Not all of the tree history codes utilized for regular
subplot trees are valid for full-hectare trees. Note that snags are not distinguished from other
mortality on the hectare.
Table 1-20. Valid Full-Hectare Tree History Codes by Measurement Types
Code
01
03
06
07
08
09
10
11
12
13
Current Tree History Mt1
Live/Survivor tree x
Ingrowth tree on full hectare
Dead tree
Cut tree
Land use change
Missed live tree
Extra tree
Access Denied
Dangerous condition
Lost Data
Mt3
x
x
x
x
x
x
x
x
x
x
Further elaboration on full-hectare tree history codes is provided below:
Code 01. Live/Survivor trees on the hectare are live trees equal to or greater than 40.0 inches
(100 cm) DBH. Code 01 is used in the following cases:
A live Mt1 tree encountered for the first time.
A downloaded hectare tree that is still alive.
A live Mt3 tree encountered for the first time (newly forested plots, points, and condition
classes). These are added by scrolling past all downloaded trees on the appropriate
point(s).
A fader tree (which should be assigned damage code 26).
Code 03. Ingrowth trees on the hectare are trees on previously forested condition classes that
have grown above the 40.0 inch (100 cm) DBH threshold since the previous Mt1/Mt3 survey. This
also includes fader trees.
Code 06. A downloaded hectare tree that has died or become a fader tree. Snags are not
distinguished from other dead trees on the hectare mortality screen.
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Code 07. A downloaded hectare tree that has been cut.
Code 08. A downloaded hectare tree on land that has been withdrawn from a forest land use,
regardless of whether the tree is alive, dead, standing, or down.
Code 09. A tree that should have been tallied as a live large hectare tree at the previous Mt1/Mt3
survey but was missed. It is added to the PDR by scrolling past all downloaded trees on the
appropriate point.
Code 10. A downloaded hectare tree that was tallied at the previous Mt1/Mt3 survey but should
not have been.
Code 11. A downloaded hectare tree to which access has been denied.
Code 12. A downloaded hectare tree on land that is too hazardous to occupy.
Code 13. A downloaded hectare tree on a plot that cannot be relocated. This code is valid only
after the close of the field season.
SPECIES
Select the appropriate species code list (Appendix A). Woodland species not tallied.
OLD DBH
Use the same procedures described for subplot trees in Subsection 1.6.6.
DBH
Use the same procedures described for subplot trees in Subsection 1.6.6.
DBH CHECK
Use the same procedures described for subplot trees in Subsection 1.6.6.
POINT NUMBER
Full-hectare trees can be referenced to the center of the most convenient subplot. Record the
number of the subplot to which the tree is referenced. There is no provision for referencing trees
to offset points on the full-hectare plot. Note: Borderline trees must be checked with a tape,
measured from the center of Subplot 1.
HORIZONTAL DISTANCE
Measure the horizontal distances to sample trees from the center of the most convenient
subplot to the center of the tree at its base. Record the distance to the nearest 0.1 ft (0.1 m).
NOTE: For trees forked at or above 1 ft (.3 m) record the distance to the central stem at ground
level for all forks. For trees forked below 1 ft (.3 m), record the distance to where each individual
stem enters the stump (or clump).
AZIMUTH TO NEAREST POINT
From the center of the most convenient subplot, view the center of the tree at its base.
Record the azimuth (to the nearest degree) as a 3-digit code ranging from 001 to 360. Use 360
for north.
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NOTE: For trees forked at or above 1 ft (.3 m) record the azimuth to the central stem at ground
level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each individual
stem enters the stump (or clump).
MORTALITY YEAR
Use the same procedures described for subplot trees in Subsection 1.6.6.
NONFOREST YEAR
Use the same procedures described for subplot trees in Subsection 1.6.6.
CAUSE OF DEATH
Use the same procedures described for subplot trees in Subsection 1.6.6.
CROWN CLASS
Use the same procedures described for subplot trees in Subsection 1.6.6.
NOTES
Use the same procedures described for subplot trees in Subsection 1.6.6.
DESCRIPTION
Use the same procedures described for subplot trees in Subsection 1.6.6.
ADDITIONAL CROWN AND DAMAGE VARIABLES
Use the same crown classification procedures described for subplot trees in Section 2 for: Crown
Diameter Wide, Crown Diameter 90°, Live Crown Ratio, Crown Density, Crown Dieback, and
Foliage Transparency.
Use the same damage classification procedures described for subplot trees in Section 3 for:
Location 1-3, Damage 1-3, arid Severity 1-3.
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1.6.7.3 Full-Hectare Mortality Plot (CA/PNW PS Only)
Compared to the other components of stand dynamics (survivor growth and regeneration), mortality
is a relatively rare occurrence. The main function of the full-hectare mortality cruise is to provide an
estimate of mortality during the initial Mt1 survey rather than waiting four years for mortality data from the
Mt3 remeasurement. This screen is activated on any plot that has at least one forested condition class on
one of the regular subplots. It must be used in conjunction with the Full-Hectare Boundary Delineation
screen, so mortality trees can be assigned to the appropriate condition classes (see Subsection 1.6.7.1).
Data from the full-hectare mortality cruise are supplemental to data gathered on the subplots and
microplots. Mortality data are gathered only from forested condition classes. Ignore mortality occurring
in condition classes that are currently nonforest, even though the area may have previously been forest.
The full-hectare cruise is conducted somewhat independently of the standard subplots and microplots,
except that Condition Classes defined on the subplots are also used for the full hectare. All trees tallied
as part of the mortality plot will be mapped on the field form.
Procedure
Mortality trees have no living cambium above DBH; they can either be standing or on the ground.
"Fader trees are also tallied as mortality. Western woodland species are not counted on the Full-Hectare
Mortality Plot. Cut trees are also excluded because of difficulties in reconstructing pre-cut data. Note that
the procedures described below also apply to situations where there has been catastrophic mortality (i.e.,
fire, insect infestations).
On Mt1 plots, and other forest plots where a previous full-hectare mortality sample does not exist, mark
all qualifying mortality trees with a double blaze 1 foot (0.30 m) high on the stump (mark "faders" with red
crayon at DBH). Mark and tally all mortality trees (standing and down) meeting the following specifications:
(1) trees 11.0 inches (27.9 cm) and larger that have died during the previous 5 years on the full-hectare
circle surrounding Subplot 1; (2) trees 5.0 -10.9 inches (12.7 - 27.8 cm) that have died within the previous
5 years on the four 1/24th acre (1/60th hectare) subplots and (3) trees 1.0 - 4.9 inches (2.54 -12.6 cm)
that have died within the past five years on the four microplots (Table 1-21). Guidelines to identify 5-year
mortality trees are provided in Section 3.
Tablo 1-21. Tree Sizes Sampled for Mortality by Plot Type
Tree Size at DBH1 plot TyPe
inches centimeters Microplot Subplot Full Hectare
1,0-4.9
5.0-10.9
11.0 +
2.54-12.6
12.7-27.8
27.9 +
X
X X
X X
X
'Trees less than 5.0 inches (12.7 cm) are referenced to the microplot center. All larger trees are referenced to subplot center.
On remeasured Full-Hectare Mortality Plots (Mt3), identify all trees that have died since the previous
(Mt1 or Mt3) survey, ignoring any trees blazed or marked as having died prior to the last survey. Mark and
tally all new mortality trees as described above.
The quick reference hectare mortality screen (Table 1-13) lists the hectare mortality variables.
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HECTARE TREE TYPE
Specify whether the tree is being measured as a large tree on the full-hectare plot or a mortality
tree on the full-hectare plot. The use of Code 1 will activate the prompts for full-hectare large
trees, code 2 will activate the prompts for full-hectare mortality trees. Note: Large fader trees, as
well as large mortality trees (downloaded Mt3 trees with current tree histories of 06) are recorded
twice on the full hectare-once as Hectare Tree Type 1 and again as Hectare Tree Type 2.
Code Definition
1 Full-hectare large tree (including large faders)
2 Full-hectare mortality tree (including all faders)
CONDITION CLASS
Using the same procedures described for subplot trees in Subsection 1.6.6, record the Condition
Class in which the tree is currently located. The tree must be in one of the conditions in the
Hectare Condition List.
TREE LOCATION
Record the appropriate code. Reconstruct the location of the standing stump for mortality trees
that are down.
Code Definition
0 Tree does not occur on subplot or microplot
1 Tree occurs on subplot
2 Tree occurs on microplot
MORTALITY STATUS
Select the code below that best depicts the current status of the tree.
Code Definition
01 Mortality Tree (standing
02 Mortality Tree (down)
04 Fader Tree
SPECIES
Select the appropriate species code (Appendix A). Woodland species not tallied.
DBH
If DBH can still be measured, use the same procedures described for subplot trees in Subsection
1.6.3. If bark is missing, estimate what the diameter would be with bark. If only a stump is
present, estimate DBH according to guidelines presented at training.
POINT NUMBER
Trees 11.0 inches (27.9 cm) DBH and larger can be referenced the tree to the center of the most
convenient subplot. Smaller trees are referenced to the center of the subplot or microplot on which
they occur. There is no provision for referencing trees to offset points. Record the number of the
point to which the tree is referenced.
HORIZONTAL DISTANCE
Measure all distances to sample trees from the center of the subplot to which the tree is
referenced, to the center of the tree at its base. Reconstruct the location of the standing stump
for mortality trees that are down. Record the distance to the nearest 0.1 ft (0.1 m). Borderline
trees must be checked with a tape, measuring from the center of the hectare.
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NOTE: For microplot mortality trees less than 5.0 inches (12.7 cm) DBH, reference the tree to the
microplot center instead of the subplot center.
NOTE: For trees forked at or above 1 ft (.3 m) record the distance to the central stem at ground
level for all forks. For trees forked below 1 ft (.3 m), record the distance to where each individual
stem enters the stump (or clump).
AZIMUTH
From the center of the subplot or microplot to which the tree is referenced, view the center of the
tree at its base. Estimate the location of the standing stump for mortality trees that are down.
Record the azimuth (to the nearest degree) as a 3-digit code ranging from 001 to 360. Use 360
for north.
NOTE: For microplot mortality trees less than 5.0 inches (12.7 cm) DBH, reference the tree to the
microplot center instead of the subplot center.
NOTE: For trees forked at or above 1 ft (.3 m) record the azimuth to the central stem at ground
level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each individual
stem enters the stump (or clump).
MORTALITY YEAR
Record the 2-digit year in which the tree died.
CAUSE OF DEATH (PRIMARY)
Use the same procedures described for subplot trees in Subsection 1.6.6, assigning the cause
estimated to be the "primary" cause of death.
CAUSE OF DEATH (SECONDARY)
Use the same procedures described for subplot trees in Subsection 1.6.6, assigning the cause
estimated to be the "secondary" cause of death, if appropriate. If only a "primary" cause of death
is apparent, record 000 for this entry.
CROWN CLASS
Estimate the crown class occupied by the tree at the time it died according to procedures described
for subplot trees in Subsection 1.6.6.
NOTES
Use the same procedures described for subplot trees in Subsection 1.6.6.
DESCRIPTION
Use the same procedures described for subplot trees in Subsection 1.6.6.
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1.6.8 Nonforest/Access Denied/Dangerous Plots
This section describes field procedures for nonforest and inaccessible plots. These plots are of interest
from the standpoint that they may once have been forest, or that they may revert to forest or become
accessible in the future. Thus, they are monitored to account for lands that move into and out
of the forest land base. Only basic plot identification data are recorded on these plots.
A plot is considered nonforest if no part of it is currently located in forest (Land Use 1, 12, or 13). A
plot is inaccessible if it potentially contains forest, but access is prevented to the entire plot by the land
owner or because of some hazardous situation.
No ground plots are established at nonforest or inaccessible sample locations. If a forest plot has been
converted to nonforest or becomes inaccessible, the old plot is abandoned. If a nonforest plot becomes
forest or access is gained to a previously inaccessible plot, a new forest ground plot is
installed from scratch.
All nonforest and inaccessible plots are visited at Mt1 and Mt3 surveys in order to determine if they
have reverted to forest or become accessible. The only nonforest/inaccessible plots visited at Mt2 surveys
are those plots that were forest at the last visit.
Procedure
The "Nonforest/No Access/Dangerous Plot" version of Tally should be used if no part of a plot is
currently located in accessible forest (Land Use codes 01,12, and 13) regardless of whether or not the plot
was previously forest. Trees on previously forested plots will be reconciled at data processing.
Remember, there is a distinction between plots that have been clearcut and plots that have been
converted to another land use. A clearcut plot is considered to be forest until it is actively converted to
another land use. Additional information concerning land use classifications is contained in Appendix D.
In cases where a plot is inaccessible, but obviously contains no forest, assign the plot to the
appropriate nonforest land use. Access-denied and dangerous land uses are used only if there is a
possibility the plot contains forest.
It is not necessary to establish or maintain any starting points, witness trees, boundaries, etc., on
nonforest or inaccessible plots.
1.6.8.1 Plot-Level Notes
Type all notes into the fields provided on the PDR. Notes are reviewed by the regional coordinator
when the data are processed. If appropriate, they will be passed to future field crews in the form of hard
copy.
1.6.8.2 Plot Identification
Record the appropriate codes for each variable. The quick reference nonforest plot-level note screen
(Table 1-15) lists the variables recorded on nonforest plots.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 76 of 86
STATE
Use the same procedures described for forest plots in Subsection 1.6.2.2.
COUNTY
Use the same procedures described for forest plots in Subsection 1.6.2.2.
HEXAGON NUMBER
Use the same procedures described for forest plots in Subsection 1.6.2.2.
PLOT NUMBER
Use the same procedures described for forest plots in Subsection 1.6.2.2.
PROJECT
Use the same procedures described for forest plots in Subsection 1.6.2.2.
QA STATUS
Use the same procedures described for forest plots in Subsection 1.6.2.2.
CREW TYPE
Use the same procedures described for forest plots in Subsection 1.6.2.2.
MEASUREMENT TYPE
Use the same procedures described for forest plots in Subsection 1.6.2.2.
OLD PLOT STATUS
Use the same procedures described for forest plots in Subsection 1.6.2.2. For Mt3 plots,
information concerning Old Plot Status will be provided on hard copy.
CURRENT PLOT STATUS
Use the same procedures described for forest plots in Subsection 1.6.2.2.
MONTH, DAY, YEAR
Use the same procedures described for forest plots in Subsection 1.6.2.2.
LAND USE AT POINT 1...4
Record the appropriate land use at the center of each subplot. Timberland (01), Reserved
Timberland (12), and Woodland (13) are considered forest land uses and are invalid for nonforest
plots. All other land uses are valid for this screen. Definitions and additional information
concerning land-use classifications are provided in Appendix D.
Code Definition
0 Lost data / lost plot
1 Timberland
2 Cropland
3 Improved pasture
4 Rangeland
5 Idle farmland
6 Other farmland
7 Urban and other development
8 Marsh
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 77 of 86
Code Definition
9 Water
10 Access denied
11 Dangerous condition
12 Reserved Timberland
13 Woodland
14 Rocky, barren, excessively steep terrain (nonforest)
15 Natural alpine clearing (nonforest)
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 78 of 86
1.6.9 Offset Procedures
Because subplot locations are fixed and cannot be moved or rotated, the subplot center may fall in the
middle of a tree, stream, building, or some other obstruction. Since it is impossible to occupy the point
underthese circumstances, distances and azimuths to boundaries and trees cannot be measured. Instead,
four points can be established on the subplot perimeter, offset 24.0 ft (7.32 m) in the four cardinal directions
from the subplot center. These serve as reference points for tree selection, instead of the subplot center.
Microplot boundary and tree data also can be recorded from subplot offset points if there is an obstruction
at a microplot center.
Procedure
When a subplot or microplot center cannot be established because of an obstruction, any one of four
subplot offset points can be used to reference boundaries or trees. That is, all distances and azimuths that
would normally be taken from a subplot or microplot center are instead taken from one or more subplot
offset points. Subplot offset points are.located on the perimeter of the subplot in one of the four cardinal
directions (360, 090, 180, and 270°) from the subplot center (Figure 1-8).
Code Definition
0 Normal position (subplot or microplot center)
1 North offset point
2 East offset point
3 South offset point
4 West offset point
Obstructions that necessitate the use of offset points can also make travel to and around the plot
difficult. The following illustrations provide information that facilitate plot establishment and measurement
in such cases.
Case 1: An obstruction occurs at the center of Subplot 1.
If an obstruction prevents access to the center of Subplot 1, then stop at or before the obstruction,
offset 24.0 ft (7.32 m) in one of the cardinal directions (360, 090, 180, or 270°), and complete the course
to arrive at one of the offset points. For example, say the course to plot center is 375 ft (114.3 m) at 34°,
the obstruction extends 17 ft (5.18 m) from plot center, and the most convenient offset point is #3. Stop
at 358.0 ft (109.12 m), proceed 24.0 ft (7.32 m) at 180°, and then go 17.0 ft (5.18 m) at 34°. This is will
position you at Offset Point 3 (Figure 1-9).
If Subplot 1 cannot be occupied, Subplot centers 2, 3, and 4 must be found by starting from one of
Subplot 1's offset points. Travel 120.0 ft (36.6 m) in the prescribed direction (360, 120, or 240°) to arrive
at the same offset point at the next subplot 1. Then measure 24.0 ft (7.32 m) back to subplot center.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 79 of 86
Figure 1-8. Location of four subplot offset points.
24.0 ft at 180'
Figure 1-9. Locating offset point #3.
Case 2: An obstruction hinders travel from Subplot 1 to Subplots 2, 3, and 4.
If an obstruction occurs at the center of Subplot 1 or between Subplot 1 and Subplots 2, 3, or 4, then
Subplots 2-4 can be reached from each other (e.g., travel from Point 2 to Point 3) (Figure 1-10). The
azimuths and distances between subplots are given in Table 1-21. If the direction is reversed from what
is shown in the Table 1-22 (e.g., subplot 3 to subplot 2), then use the backsight for the azimuth.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 80 of 86
Figure 1-10. Locating other subplot centers.
Table 1-22. Distances and Azimuths Between Subplots 2-4
Subplot Numbers
From To
Azimuth Backsight
-degrees-
-Distance-
feet meters
2
2
3
3
4
4
150
210
270
330
030
090
207.8
207.8
207.8
63.4
63.4
63.4
Case 3: An obstruction occurs at the center of Subplot 2, 3, or 4.
This situation is handled the same as Case 1. Stop at or before the obstruction, proceed 24.0 ft
(7.32 m) in one of the cardinal directions, and then finish chaining to the subplot. This will position you at
the targeted offset point.
Case 4: No portion of Subplot 1 can be occupied, not even the offset points.
This situation is handled similarly to Case 1 except that instead of proceeding to an offset point on
Subplot 1, proceed directly to another subplot center. Stop at or before the obstruction, proceed 120 ft
(36.6 m) in one of the prescribed directions (360, 120, or 240°), and then finish chaining to the subplot.
This will position you at the center of the selected subplot.
Case 5: Locating offset points from each other on the same subplot.
Once one offset point is determined, the location of other offset points can be found as indicated in
Table 1-23 (Figure 1-11).
Case 6: Locating the microplot center from subplot offset points.
A microplot center can be located from subplot offset points as indicated in Table 1-24 (Figure 1-12).
Use offset point 2 whenever possible.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 81 of 86
Table 1-23. Distances and Azimuths Between Offset Points
To offset point •
North (1) East (2) South (3) West (4)
From Offset Point Azi Dist Azi Dist Azi Dist Azi Dist
North (1)
East (2)
South (3)
West (4)
deg
315
360
045
ft
13533.9
33.9
48.0
33.9
deg
180
045
090
English Units -
ft deg
48.0 225
225
33.9
48.0
135
ft
33.9
33.9
33.9
deg
270
315
— Metric Units —
m
48.0
33.9
deg
m
deg
m
deg
m
North (1)
East (2)
South (3)
West (4)
315
360
045
10.3
14.6
10.3
135
045
090
10.3
10.3
14.6
180
225
135
14.6
10.3
10.3
225
270
315
10.3
14.6
10.3
Figure 1-11. Locating offset points from each other on the same subplot.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 82 of 86
Table 1-24. Directions from Offset Points to Microplot Centers
North (1)
Azi
def
153
Distance
ft
26.8
m
8.2
East (2)
Azi
deg
270
Distance
ft
12.0
m
3.7
South
Azi
deg
027
(3)
Distance
ft
26.8,
m
8.2
West (4)
Azi
Distance
deg ft m
090 36.0 1 1
.0
01B5nlBCflM.IO-12
Figure 1-12. Locating the mlcroplot center from subplot offset points.
Case 7: Tallying trees from offset points.
Not all trees may be visible from the initial offset point. It is permissible to use more than one offset
point to Tally trees. Both subplot and microplot trees can be tallied from the subplot offset (Figure 1-13).
Thus, in the unusual case where a microplot center cannot be occupied, and there are still microplot trees
to be tallied, they should be measured from a subplot offset point (i.e., there is no provision for establishing
offset points on the microplot perimeter).
Using the horizontal distance from an offset point to a tree, the PDR will automatically check borderline
trees and issue a warning if a tree is not located within the perimeter of the subplot (or microplot). If a tree
Is out, either hit the HOME key and record the next tree's data or hit the DELETE LINE key.
Case 8: Recording boundaries from offset points.
Choose one offset point from which the left, right, and comer azimuths and distances can be measured.
If possible, select an offset point which is on the same side of the boundary as the subplot center.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 83 of 86
0195msd94.Ig.13
Figure 1-13. Referencing trees to offset points.
When referenced to an offset point, it is difficult to pinpoint where a boundary crosses the subplot
perimeter. Left and right azimuths and distances from an offset point to the edge of the subplot will often
have to be estimated and should be measured to points on the boundary that are close to the subplot
perimeter (Figure 1-14). From the recorded data, the exact points of intersection will be computed at the
time of data processing.
0195msd94.fg-l4
Figure 1-14. Estimating boundaries from offset points.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 84 of 86
Case 9: Checking limiting distances from offset points without a PDR.
Table 1-25 lists the angle and limiting distance to 18 perimeter points on the subplot (Figure 1-15).
The angle is the difference between the azimuth to subplot center (180, 270, 360, or 90°) and the azimuth
to the tree. This angle should never be more than 90°. Borderline trees should be tallied and will be
checked later during data processing.
Table 1-25. Limiting Distances to 18 Points on the Subplot
Angle
dog
0
5
10
15
20
25
30
35
40
ft
48.0
47.8
47.2
46.3
45.1
43.5
41.6
39.3
36.8
— Distan ea-
rn
14.64
14.57
14.39
14.11
13.75
13.26
12.68
11.98
11.27
deg
45
50
55
60
65
70
75
80
85
Angle
ft
sag
30.8
27.5
24.0
20.3
16.4
12.4
8.3
4.2
-Distan ea-
rn
10.33
9.39
8.38
7.32
6.16
5.00
3.78
2.53
1.28
0195msdM.lig.15
Figure 1-15. Subplot limiting distances from offset point #4.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 85 of 86
1.7 References
Avery, T.E. 1975. Natural Resources Measurements. McGraw Hill, New York.
Cline, S.P. (ed). 1994. Forest Health Monitoring Quality Assurance Plan. In Preparation. U.S.
Environmental Protection Agency, Washington, D.C.
Conkling, B.L. and G.E. Byers (eds.). 1993. Forest Health Monitoring Field Methods Guide. Internal
Report. U.S. Environmental Protection Agency, Las Vegas, NV.
Daubenmire, R. 1959. A canopy coverage method of vegetational analysis. Northwest Sci. 33:43-64.
Eyre, F.H., ed. 1980. Forest Cover Types of the United States and Canada. Society of American
Foresters, Washington, DC. 148 pp.
Husch, B., C.I. Miller, and T.W. Beers. 1972. Forest Mensuration. The Ronald Press Company New
York. 410pp.
Mueller-Dombois, D. and H. Ellenberg. 1974. Aims and Methods of Vegetation Ecology. John Wiley and
Sons, New York. 547 pp.
Overton, W.S., D. White, and D.L. Stevens. 1990. Design report for EMAP (Environmental Monitoring
and Assessment Program). EPA/600/3-91/053, U.S. Environmental Protection Agency, Office of
Research and Development, Washington, D.C.
Scott, C.T., A.R. Ek, and T.R. Zeisler. 1983. Optimal spacing of plots comprising clusters in extensive
forest inventories, p. 707-710 in Renewable Resource Inventories for Monitoring Changes and
Trends. Corvallis, OR. Soc. Amer. For. SAF 83-14.
Scott, C.T. 1993. Optimal design of a plot cluster for monitoring. K. Rennolls and G. Gertner (eds.).
In The Optimal Design of Forest Experiments and Forest Surveys, London, England, Sept. 10-14,
1991. Sch. of Math., Stat. and Computing, Univ. of Greenwich, London, p. 233-242.
Scott, C.T., and W.A. Bechtold. 1994. Procedures to handle inventory cluster plots that straddle two or
more conditions. Submitted to Forest Science.
U.S. Department of Agriculture, Forest Service. 1981. Resources evaluation field instructions for
California, 1981-84. Unpublished field guide on file at: U.S. Department of Agriculture, Forest
Service, Pacific Northwest Forest and Range Experiment Portland, OR.
U.S. Department of Agriculture, Forest Service. 1988. Field instructions for the fourth inventory of
Pennsylvania 1988 - 1989. Unpublished field guide on file at: U.S. Department of Agriculture,
Forest Service, Northeastern Forest Experiment Station, Radnor, PA.
U.S. Department of Agriculture, Forest Service. 1989a. Forest Survey Inventory Work Plan, Alabama
1989-1990. Unpublished field guide on file at: U.S. Department of Agriculture, Forest Service,
Southern Forest Experiment Station, Starkeville, MS. 61 p. plus appendices.
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EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 86 of 86
U S Department of Agriculture, Forest Service. 1989b. North central region forest inventory and
" analysis field instructions. Unpublished field guide on file at: U.S. Department of Agriculture, Forest
Service, North Central Forest Experiment Station, St. Paul, MN. 99 p.
U S. Department of Agriculture, Forest Service. 1992. Utah forest survey field procedures, 1992-1993.
Unpublished field guide on file at: U.S. Department of Agriculture, Forest Service, Intermountam
Research Station, Interior West Resource Inventory, Monitoring, and Evaluation Program, Ogden,
UT. 232 p.
U.S. Department of Agriculture, Forest Service. 1993. Field instructions for the southeast. Unpublished
field guide on file at: U.S. Department of Agriculture, Forest Service, Southeastern Forest
Experiment Station, Asheville, NC.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 1 of 23
Section 2. Crown Condition Classification
Section/Title
2.1 Overview 2 of 23
2.1.1 Scope and Application 2 of 23
2.1.2 Summary of Method ; 3 of 23
2.1.3 Interferences 3 of 23
2.1.4 Safety 4 of 23
2.1.5 Definitions and Codes 4 of 23
2.2 Sample Collections, Preservation, and Storage 6 of 23
2.3 Equipment and Supplies 7 of 23
2.4 Calibration and Standardization , ; 7 of 23
2.5 Quality Assurance 10 of 23
2.5.1 Crown Classification Measurement Quality Objectives 10 of 23
2.5.2 Data Quality Procedures 10 of 23
2.5:3 Crown Rating Precautions 10 of 23
2.6 Procedure ••,:••;-.- 11 of 23
2.6.1 Seedling Procedure ......"."".". 11 of 23
2.6.1.1 Vigor Class 11 of 23
2.6.2 Sapling Procedure 12 of 23
2.6.2.1 Vigor Class 12 of 23
2.6.2.2 Live Crown Ratio 12 of 23
2.6.3 Crown Evaluation Procedures for Trees 5..Q inches (12.7 cm) DBH and Larger .. 14 of 23
2.6.3.1 Crown Diameter Measurements ,;.'.. , 14 of 23
2.6.3.2 Live Crown Ratio 19 of 23
2.6.3.3 Crown Density 19 of 23
2.6.3.4 Crown Dieback 21 of 23
2.6.3.5 Foliage Transparency 21 of 23
2.7 References 23 of 23
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 2 of 23
2.1 Overview
A multitude of abiotic and biotic influences shape forest trees, individual tree, seedling and sapling
vigor, and growth are determined by a variety of physiological and external influences, such as
physiological age, available light, water and nutrients. This section describes protocols to rate seedling,
sapling, and tree crown conditions. Procedures will be discussed beginning with seedlings, followed by
saplings and ending with crown evaluation for trees.
2.1.1 Scope and Application
Individual tree vigor and growth are also determined by physiological age and available water,
nutrients, and light resources at a site. Both climate and site affect resource availability, but a tree's
position relative to its neighbors becomes critical when determining the amount of water, light, and nutrients
that are available for any one tree. Because of these tree-stand interactions, both stand-level data and
individual tree data must be collected.
Seedlings are trees at least 12 inches (30 cm) or greater in height but less than 1 inch (2.54 cm) in
diameter at breast height (DBH) [or diameter at root collar (DRC) in the West]. All seedling variables are
measured on each 1/300 acre (1/750 hectare) microplot (6.8 ft [2.07 m] radius) offset from each plot center
at a distance of 12 ft (3.66 m), due east (90°) from each subplot center. Seedlings can originate from
seeds, sprouts, or layering. Only one indicator is recorded for seedlings, vigor class. Vigor class is
determined for each -seedling but then aggregated by species, crown position, condition class, and vigor
class when recorded. Seedling measurements will only be done during plot establishment (Mt1) and when
plot remeasurement (Mt3) occurs to reduce damage to seedlings.
Saplings are tree species with DBH (or DRC in the West) between 1.0 inch (2.54 cm) and 4.9 inches
(12.69 cm). Like seedlings, all sapling variables are measured on each 1/300 acre (1/750 hectare)
microplot (6.8 ft [2.07 m] radius) offset a distance of 12 ft (3.66 m), due east (90 degrees) from each
subplot center. Sapling vigor class, as well as live crown ratio, is determined for each sapling. Any foliage
below the point used for live crown ratio is not considered in vigor class determination. Sapling vigor class
is evaluated during plot establishment (Mt1) and then annually (Mt2). Live crown ratio is evaluated during
plot establishment (Mt1). Live crown ratio is also recorded during annual crown measurements (Mt2) when
live crown ratio changes by more than 15% (3 classes) and completely reevaluated when plot
remeasurement (Mt3) occurs.
Crown evaluations describe tree conditions. An observed tree condition results from the preceding
year's growth processes, which are influenced by site, stand density, and external stresses. Therefore,
crown evaluations that quantitatively assess current tree conditions become an integrated measure of site,
stand density, and external stresses.
In the eastern U.S., crown diameter has been related to the size of hardwood trees (Francis, 1986;
Sprinz and Burkhart, 1987), and crown density has been related to the growth of loblolly pines (Grano,
1957; Anderson and Beianger, 1987; Anderson et al., 1992; Belanger and Anderson, 1991). In the western
U.S., live crown ratio and crown density have been related to growth and survivorship of conifers (Dolph,
1988). Other crown variables, crown dieback, foliage transparency, and crown density, can be related to
insect defoliation and subsequent growth and survivorship effects on both conifers and hardwoods
(Kuhlman, 1971). In general, trees with high scores for live crown ratio, crown density, and crown diameter,
and low scores for crown dieback and foliage transparency, have increased potential for carbon fixation,
nutrient storage, and increased potential for survival and reproduction.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 3 of 23
2.1.2 Summary of Method
Only one indicator is recorded for seedlings, vigor class. Vigor class is determined for each seedling
but then aggregated by species and vigor class when recorded. Seedling measurements will only be done
during plot establishment (Mt1) and when plot remeasurement (Mt3) occurs to reduce damage to seedlings.
Sapling vigor class, as well as live crown ratio, is determined for each sapling. Any foliage below the point
used for live crown ratio is not considered in vigor class determination. Sapling vigor class is evaluated
during plot establishment (Mt1) and then annually (Mt2). Live crown ratio is evaluated during plot
establishment (Mt1). Live crown ratio is also recorded during annual crown measurements (Mt2) when live
crown ratio changes by more than 15% (3 classes), and completely re-evaluated when plot remeasurement
(Mt3) occurs.
The FHM crown rating technique helps describe current tree condition. As part of this system, various
tree conditions and damage assessments are taken to describe attributes on all live trees 5.0 inches (12.7
cm) DBH (or DRC in the West) or larger on the four FHM subplots. The organization of various
measurements is listed below.
Crown Evaluation Measurements
(1) crown diameter wide and 90°
(2) live crown ratio,
(3) crown density,
(4) crown dieback,
(5) foliage transparency.
[Note: Measurements are listed in order of data collection on each tree].
Crown diameter and live crown ratio are done during plot establishment (Mt1) and during
remeasurement (Mt3). These variables are remeasured during annual crown measurements (Mt2) when
live crown ratio changes by more than 15% (3 classes) or individual crown diameter measurements (crown
diameter wide or crown diameter 90) changes by more than 5 ft (1.5 m). The other crown measures
(crown density, crown dieback, and foliage transparency) are measured annually (Mt1, 2, and 3).
2.1.3 Interferences
Several uncontrollable environmental and site conditions have hindered or slowed the crown condition
classification measurements, including (1) poor weather conditions such as gusting wind, heavy rain, and
dark overcast skies; (2) steep and/or unstable slopes; (3) dense understory vegetation which prohibits free
ground movement; and (4) thick canopy immediately overhead that obscures full view of the tree canopy.
Suspend data collection under severe weather conditions, such as strong winds and heavy rainfall.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 4 of 23
2.1.4 Safety
No specialized safety precautions are necessary. Follow general safety precautions for conducting
fieldwork (See Appendix E).
2.1.5 Definitions and Codes
Definitions
For the purposes of this guide, three crown areas are clearly defined: top, outer sides, and base.
Three other areas also need to be defined: crown diameter, crown form, and branch.
Top
The tree top is the highest point of a standing tree. Younger trees usually have conical shaped crowns
and the main terminal stem is the top. Older trees and many hardwoods have globose and flat-topped
crowns, where a lateral branch is the highest point. For some measurements (live crown ratio), only the
highest live branch is considered, while other measurements include dead top. Crown measurements, such
as crown density, assess how much of the expected crown is present and include all dead branches and
snag branches (old dead branches which have lost most of the small branches and twigs, less than 1 inch
[2.54 cm] diameter at the base). Crown dieback measurements concern recent branch mortality and do
not include snag branches.
Base
The crown base is defined here as the lowest live part of the crown. Include most of the crown
branches but exclude epicormic shoots and straggler branches that usually do not contribute much to the
tree's growth. Most measurements define the live crown base by drawing a horizontal line from the bottom
of the lowest foliage of the obvious crown (usually the largest branches at the crown bottom) across the
trunk Thus the base of the branch may be above or below this line. Then, if any branches greater than
1 inch (2 54 cm) in diameter are within 5 ft (1.5 m) below this line, the base is moved down to the base
of the foliage on that branch. Continue to move down the trunk until no 1 inch (2.54 cm) diameter
branches are found within 5 ft (1.5 m). The crown base then becomes the horizontal line at the bottom
of the foliage of the lowest qualifying branch where it intersects the trunk.
Occasionally all original major crown branches are dead or broken and an abundance of new branches
are developing. At first, before branches reach the 1 inch (2.54 cm) diameter size, the tree for this
measurement has no crown. When new branches reach the 1 inch (2.54 cm) diameter limit, a new crown
is forming. The previous obvious crown base here would be the dead branches, while many of the live
branches with foliage may be below this point. The recommendation is to find the line for the lowest live
branch (1 inch diameter [2.54 cm] or larger) that meet the 5 ft (1.5 m) rule. These situations are likely to
occur in areas of heavy thinning, commercial clearcuts, and severe weather damage.
Sides of the Crown
Most measurements consider the crown in a two-dimensional perspective, the way it would appear
when reflected in a mirror. The side boundaries are limited by a line drawn from branch tip to branch tip,
except when branches are widely separated. For the purpose of foliage abundance (foliage transparency),
the line would encircle each separated branch. For crown density, the perimeter is drawn from branch tip
to branch tip, and open spaces become part of the crown density measurement. Occasionally, a branch
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 5 of 23
may protrude abnormally, but the lateral crown line may be drawn across the portion of the branch that
contains most of the tips.
Crown diameter
Crown diameter is defined as the average of two diameter measurements: 1) widest distance anywhere
in the crown between two live branches (the drip line), and 2) the perpendicular distance to the first
measurement. Abnormally long branches sticking out beyond the edge of the crown are not used in
establishing the extent of a crown.
Crown shape
Crown shape is a silhouette of an average open-grown tree. Usually, silhouettes are derived from
vigorously growing trees and tend to be species specific. With age, tree crowns tend to flatten out. Crown
shapes are important when measuring crown density and will be used in the future with tree height, live
crown ratio, crown density, and crown diameter to estimate crown biomass. Crown shape is used as an
outline for the sides of the tree, and voids of branches are considered as a loss in density for this
measurement.
Branch
A live branch is defined as any woody lateral growth supporting foliage and larger than 1-inch at the
base just above the swelling where it joins the main stem. Dead branches have no minimum size to be
included for crown dieback estimates. Lower dead branches are not included in crown dieback. Dead
upper crown branches without twigs (branches less than 1-inch diameter) are considered as old dead, or
snag branches, and are not included in crown dieback estimates, but are included in crown density
estimates. Secondary growth, less than 1-inch diameter, such as water sprouts, suckers, or epicormics,
are excluded from the branch definition. After a sudden release or damage, a tree may have very dense
foliage, but by definition no crown. These situations can be coded as follows: live crown ratio - 00, crown
density -00, crown diameter (wide and 90 degrees) - 0, crown dieback - 99, and foliage transparency - 99.
Codes
General Codes
Table 2-1 lists the PDR Prompt Codes.
Table 2-1. PDR Prompt Codes
Variables
PDR Code
Seedling Measurements:
Seedling Vigor
Sapling Measurements
Sapling Vigor
Live Crown Ratio
Trees >5.0 in dbh:
Crown Diameter Wide
Crown Diameter 90 Degrees
Live Crown Ratio
Crown Density
Crown Dieback
Foliage Transparency
SeedVig
SapVig
CRatio
CrDiaW
CrDai9
CRatio
Cm Den
CrnDbk
FolTrn
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 6 of 23
The following are the codes for seedling vigor:
Code
1
2
3
Definition
100 to 80% crown area with normal foliage, 1/3 or more of seedling height in
foliage, and less than 5% dieback in the upper or outer-exposed portion of the
crown.
79 to 21% crown area with normal foliage.
20 to 1% crown area with normal foliage.
The following are the codes for sapling vigor:
Code
1
2
3
Definition
100 to 80% crown area with normal foliage, 1/3 or more of sapling height in
foliage, and less than 5% dieback in the upper or outer-exposed portion of the
crown.
79 to 21% crown area with normal foliage.
20 to 1% crown area with normal foliage.
Table 2-2 lists codes which should be used for the Crown Diameter measurements.
Tablo 2-2. Crown Diameter Codes
Code
00
01
02
03
99
Definition (national)
Epicormic branches only
< 1.5 ft
1.6 to 2.5 ft
2.6 to 3.5 ft
>99.6ft
Code
000
001
002
003
995
Definition (California)
Epicormic branches only
<0.15 m
0.16to 0.25 m
0.26 to 0.35 m
>99.6 m
Table 2-3 lists codes which should be used for Live Crown Ratio, Crown Density, Crown Dieback, and
Foliage Transparency.
Table 2-3 LIva Crown Ratio, Crown Density, Crown Dieback, and Foliage Transparency Codes
Code
00
05
10
15
20
25
30
Definition
0%
1-5%
6-10%
11-15%
16-20%
21-25%
26-30%
Code
35
40
45
50
55
60
65
Definition
36-40%
41-45%
46-50%
51-55%
56-60%
61-65%
Code
70
75
80
85
90
95
99
Definition
71-75%
76-80%
81-85%
86-90%
91-95%
96-100%
Note: Class code is the percentage of the upper limit of the class, i.e. Code 10 is 6% to 10%, etc. Also for live crown ratio the
code 00 is used for trees with epicormic branches only.
2.2 Sample Collections, Preservation, and Storage
No material samples are collected.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 7 of 23
2.3 Equipment and Supplies
The list below includes all equipment and supplies needed for two persons to perform all
measurements described in this section. All measurements are recorded on portable data recorders
(PDRs).
Binoculars - required, 1 set per field crew
Crown Density - Foliage Transparency Card - required (provided), 1 for each field crew personnel
75-ft loggers tape (or equivalent) - required, 1 per field crew
Clinometer - optional, 1 per field crew
Crown Grid - optional, 1 per field crew
2.4 Calibration and Standardization
General calibration and standardization protocols should be applied to field equipment. Purchase tapes
to required specifications. Tapes should be maintained in working order and do not require calibration upon
confirmation of accuracy. Use the crown density - foliage transparency card to calibrate the observer's
eyes at the start of every day and on those trees that do not fit into an obvious class.
The crown density - foliage transparency card (Figure 2-1) should be used as a training aid until crew
personnel are comfortable with both ratings. White areas of the card represent skylight visible through the
crown area and black areas represent some aspect of the tree. For crown density, hold the card so that
"Crown Density" is right-side up ("Foliage Transparency" should be upside down). Use the numbers that
are right-side up. Conversely, for foliage transparency, make sure that "Foliage Transparency" is right-side
up. Crews should refer to specific crown density or foliage transparency sections for a definition of aspects
that are included in the crown rating. Crews should use the card to calibrate their eyes at the start of each
day and on those trees that do not fit into an obvious class.
The back of the crown density - foliage transparency card has two uses: for crown density when a
portion of the crown is missing and a general scale for estimating live crown ratio. Crews should refer to
the crown density and live crown ratio sections to use this side of the card.
A crown grid is used in training for crown area estimation. The crown grid was developed from similar
grids used to estimate areas on maps. The area does not represent a quantitative unit since the grid is
intended to determine proportions. The central square has 100 dots, and each peripheral square has 25
dots (Figure 2-2). The grid may be copied on a transparency and mounted on thick Plexigias™ with clear
cellophane tape for field use.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 8 of 23
Crown Density Scale
65 55 45 35 25 15
& &'\ /::r*i /'*\
$& © 0
9S 9£ 5V 99 99 9Z
eieos AouejedsuejjL e5e||oj
Front
Back
Density of Tree, Present
35 45 55 65 75
85 95
g>10
"^20
§ 30
§40
£50
"o 60
§70
5£ 80
O)
0.90
5
5
5
5
5
5
5
5
5
15
15
15
10
10
10
5
5
5
25
20
20
15
15
10
10
5
5
35
30
25
25
20
15
15
10
5
45
40
35
30
25
20
15
10
5
50
45
40
35
30
25
20
15
10
60
55
50
40
35
30
20
15
10
70
60
55
45
40
30
25
15
10
80
70
60
55
45
35
30
20
10
90
80
70
60
50
40
30
20
10
o
5"
<3
0
J2-
3
I
o
o
tD
CD
CD
o
00
o
o
c
Cj
~r
to
o
T"
o
~r
Figure 2-1. Crown density - foliage transparency card (front and back).
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 9 of 23
Figure 2-2. Crown grid.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 10 of 23
2.5 Quality Assurance
2.5.1 Crown Classification Measurement Quality Objectives
Table 2-4 lists Crown Classification Measurement Quality Objectives.
Table 2-4 Crown Classification Measurement Quality Objectives
Variable
Reporting
Units
Data Quality
Limits
Vigor Class
(Seedling and Sapling)
Crown Diameter Wide1
Crown Diameter 90 Degrees'
Live Crown Ratio
Crown Density
Crown Dieback
Foliage Transparency
3 classes
1 ft (30 cm)
1 ft (30 cm)
21 classes
21 classes
21 classes
21 classes
90% agreement
90% @ ± 5 ft (1.5 m) or 10% of the-mean
(whichever is larger)
90% @ ± 5 ft (1.5 m) or 10% of the mean
(whichever is larger)
90% @ ± 10% (2 classes)
90% @ ± 10% (2 classes)
90% @ ± 10% (2 classes)
90% @ ± 10% (2 classes)
'Only evaluated as the difference between the mean of the 2 crown diameter measurements.
2.5.2 Data Quality Procedures
Sources of measurement differences include boundary estimates for the crown and the affected area,
ability to detect damage, and rater's ability to estimate crown conditions. Differences between observers
can be minimized by open and frequent communication between crew members. Consistency and quality
are also encouraged by changing observation positions and repeating estimation procedures.
In addition, remeasurements may differ because of weather conditions, particularly light, and when a
sufficient amount of time has passed to allow changes in the tree itself. Remeasurements taken
immediately after the original measurement is best to determine variability among raters. This procedure
should be used during the training and certification program. All remeasurements should be completed
less than two weeks after trees were originally rated.
Crown indicators (crown diameter measurements, live crown ratio, crown density, crown dieback, and
foliage transparency) can be easily reproduced partly because the indicators are easy to apply and
because of data quality expectations of ± 10 percent (or 2 classes), 90% of the time. To meet these
standards, proper training and follow-up are vital throughout the program. All crown rating procedures
require two individuals to rate each tree for each variable and agree on a final value to enter into the PDR
(exception: crown diameter wide and crown diameter 90).
2.5.3 Crown Rating Precautions
The following areas show where crown indicators could be difficult to evaluate and crews must be
especially careful:
Distance from the tree -
Crews must attempt to stay at least 1/2 to 1 tree length from trees. Some ratings change with proximity
to the tree. In some situations, it is impossible to satisfy this step, so the crew should try to do the best
in each case.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 11 of 23
View of the crown -
In a forest, getting a good perspective of the crown becomes difficult. Overlapping branches,
background trees, and lack of a good viewing area can cause problems. Crews need to move laterally to
search for a good view. Density of stands may prohibit a full view. Take special care when rating such
trees.
Climatic Conditions -
Cloudy or overcast skies, fog, rain, and poor sun angle may affect estimates.. Live crown ratio and
crown diameter may be affected but to a lesser degree than other crown indicators. Crown density tends
to be over- or under-estimated because light does not project well through the foliage or, in some cases,
the light may be too bright for a good estimate. Crown dieback may be under-estimated because it is
difficult to see dead twigs and/or differentiate defoliated twigs from dead twigs. Foliage transparency
estimates could be affected in either direction because it is hard to discern foliage from branches. The data
quality expectation standard helps because crews can normally be within ± 10 percent, even in poor
weather conditions. However, crews need to be especially careful during poor lighting conditions. Crews
should move around a tree to get another view, even if the view appears adequate at a specific location.
Heavy defoliation -
During heavy defoliation, crown dieback may be over-estimated and foliage transparency may be
under-estimated due to the difficulty in differentiating dead twigs from defoliated twigs. The use of
binoculars may help in separating dead twigs from defoliated twigs.
Leaning trees -
Trees that are leaning cause a major problem in estimating many crown variables. In these situations,
record crown variables as best as possible for the tree as it actually occurs rather than as it might appear
if standing upright and also record in the tree note field that it is leaning. This will allow for a better data
interpretation.
2.6 Procedure
2.6.1 Seedling Procedure
2.6.1.1 Vigor Class
Vigor class measures seedling visual crown vigor. Seedlings are classified for (1) high vigor, (2)
moderate vigor, or (3) low vigor. The middle class (2) is largest because the objective is to separate
excellent seedlings (1) from very poor ones (3) and place all others in the middle class (2). The easiest
method for vigor classification is to determine whether the seedling meets the criteria for class (1) or (3).
If it does not, the seedling belongs in class (2).
Vigor Class Definitions
Vigor Class 1 - Class (1) seedlings must have more than 1/3 of the height in foliage, have less than 5%
dieback* in the upper half of the crown or outer-exposed portion of the crown, and 80
percent or more of the foliage is normal (at least 50 percent of the individual leaf normal
and present). Greater than 5% dieback in the upper or outer-exposed portion of the crown
is considered abnormal.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 12 of 23
Vigor Class 2 - These seedlings do not meet Class 1 or 3 criteria. They may have any crown length, may
or may not have dieback, and between 21 and 79 percent of the foliage is classified as
normal.
* Dieback is defined as branch mortality which begins at the terminal portion of a branch and proceeds
toward the trunk. When whole branches are dead in the upper crown, without obvious signs of damage
such as breaks or animal injury, assume that the branches died from the terminal down.
Vigor Class 3 - Class (3) seedlings may have any live crown length and should have 1 to 20 percent
normal foliage. (Or the percent of foliage missing on branches with dieback and percent
of abnormal foliage when combined, should equal 80 percent or more of the crown.)
Branches that are dead because of normal shading are not included.
2.6.2 Sapling Procedure
2.6.2.1 Vigor Class
Vigor class measures sapling visual crown vigor. Saplings are classified for (1) high vigor, (2)
moderate vigor, or (3) low vigor. The middle class (2) is largest because the objective is to separate
excellent saplings (1) from very poor ones (3) and place all others in the middle class (2). The easiest
method for vigor classification is to determine if the sapling meets criteria for class (1) or (3). If it does not,
classify it as a (2).
Vigor Class Definitions
Vigor Class 1 - Class (1) saplings must have more than 1/3 of the sapling height in foliage, have less than
5% dieback* in the upper half of the crown or outer-exposed portion of the crown, and 80
percent or more of the foliage is normal (at least 50 percent of the individual leaf normal
and present). Greater than 5% dieback in the upper or outer-exposed portion of the crown
is considered abnormal.
Vigor Class 2 - These saplings do not meet Class 1 or 3. They may have any crown length, may or may
not have dieback, and between 21 and 79 percent of the foliage is classified as normal.
Vigor Class 3 - Class (3) saplings may have any live crown length and should have 1 to 20 percent normal
foliage. (Or the percent of foliage missing on branches with dieback and percent of
abnormal foliage when combined, should equal 80 percent or more of the crown.)
Branches that are dead because of normal shading are not included.
* Dieback is defined as branch mortality which begins at the terminal portion of a branch and proceeds
toward the trunk. When whole branches are dead in the upper crown, without obvious signs of damage
such as breaks or animal injury, assume that the branches died from the terminal down.
2.6.2.2 Live Crown Ratio
Determine sapling live crown ratio by dividing the live crown length by total tree height to last live
branch. Crown length is the distance between the tree top (dieback and dead branches are not included)
and the obvious bottom where crown foliage exists. If the crown bottom is difficult to identify, select a base
below "most" of the foliage. The definition of the live crown base for saplings is slightly different than for
trees 5.0 inches DBH (or DRC in the West) and larger, because the 5 ft/1 inch rule does not apply in this
case. Do not include occasional "leafed twigs" branches or leaves on the main stem below the main mass
of foliage (Figure 2-3).
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 13 of 23
Sapling Crown Ratio
0%
Leafed twigs
or Epicormics
only
10%
30%
Simple
30%
Leafed twigs
ignored, crown
dieback not
included
0195msd94.«g2.3
60%
Separated
branches included,
jcwer leafed twig
ignored
Figure 2-3. Sapling live crown ratio determination examples.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 14 of 23
2.6.3 Crown Evaluation Procedures for Trees 5.0 inches (12.7 cm) DBH and
Larger
The various crown indicators are designed to work together. Each indicator comprises a piece of
information that can be used individually or as a factor in combination with other indicators. Live crown
ratio is a measure of crown length and its relationship to total tree height. Trees with higher live crown
ratios are typically viewed as healthier and faster-growing.
Crown diameter is a measure of crown width. Wider crowns are often associated with faster-growing
trees and are normally indicators of stocking. Once the live crown ratio and crown diameter are
determined, the next logical step is to measure how much of a crown exists. Crown density, which includes
foliage, branches, and reproductive structures, measures the crown biomass. Crown dieback defines how
much of the crown does not have foliage but has fine twigs, indicating a loss of vigor or growth potential.
Foliage transparency estimates how dense the foliage is on branches, indicating stress due to foliar
damage or defoliation.
Some people want to know why both crown density and foliage transparency are determined when they
seem to be inverse measures. This is true on trees having a full crown, with no crown dieback, and no
open areas in the crown. However, the average tree does not have a full, uniform crown. For example,
a tree with 80 percent crown dieback could have a few living branches with a foliage transparency rating
of 5 percent, but the crown density rating would be 15 percent. (Crown density rating considers a normal,
forest-grown crown form and then makes an estimate of how much is present on the tally tree. Foliage
transparency rating considers the foliated part of the crown only.) Some examples of crown silhouettes
and various limitations on crown measures are in Figures 2-4 through 2-6.
All of these indicators have been combined into a model called the Visual Crown Rating Model. It is
clear that each indicator adds to the overall rating given each tree. It is important to realize that the model
is designed to rate trees on how they look, from thriving to almost dead.
2.6.3.1 Crown Diameter Measurements
Crown diameter at the widest point, if viewed from the air, is the diameter of a circle including all
foliage. Measure it at the crown's widest point with a tape by having one observer stand under the drip
line at the crown's edge, opposite an observer at the other side of the crown; this is the crown diameter
wide measurement. A second measurement is made at 90 degrees to the crown diameter at the widest
point (crown diameter 90) using the same procedures (Figure 2-7).
Determine drip line end points by looking up perpendicular to the tape and projecting where crown edge
branches would hit the ground if they fell. Occasionally, a branch may protrude abnormally, but the lateral
crown line may be drawn across the portion of the branch that contains most tips. It is helpful to use a
device, such as a clinometer, that allows the observer to measure a line perpendicular to the ground. The
device should be used for training and to check estimates made during the operational field season. If you
cannot see the crown edge from the drip line, both observers should move an equal distance from the tree
and project the crown for an estimate. All measurements are rounded to the nearest foot (nearest 0.1 m
in California) and both measurements are recorded in the PDR.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 15 of 23
Crown Density Outline —»^
^»».^-^^- ~~T^~' ~~*~^. •» _ Jl
f « *.^
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 16 of 23
Crown Density Outline
CiZJ
Exclusion Areas for
Foliage Transparency**
(Crown Dieback)
Crown Outline for Crown
Dieback and Foliage
Transparency
Base of Live Crown
Exclusion Areas for
Crown Dieback and
Foliage Transparency
Figure 2-5. Crown rating example, hardwood.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 17 of 23
Crown Density Outline
^f N- %X •C-
* •• v •.
,
\ ^^----\-^ --.'- -^*^.
i *—.1 -, l^^*S^!!>^ ^iM1^
; iwi ^
Crown Dieback f
and Foliage
Transparency
EBB Exclusion Areas for
Crown Dieback and
Foliage Transparency
Figure 2-6. Crown rating example, pine.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 18 of 23
Crown Diameter
Crown Diameter (wide) ->
Side view
•i^~>*
', &"{?*•?',' t
N , <* I
•«—•Crown Diameter (90°)
•\*. W J
^ •- S ^ •- •• ^ fff ts?Jfff****f"
•- *"" ^-*A ^5«.'s^, MM*' 6i95m««M.ll82.7
90° from side view
Top view of crown diameter.
Figure 2-7. Crown diameter determination.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 19 of 23
2.6.3.2 Live Crown Ratio
Live crown ratio is the percentage of total tree height which supports live green foliage that is effectively
contributing to tree growth. Live crown ratio is determined by the ratio of crown length to total tree live
height (Figure 2-8). Crown length is determined from the crown top with the last live branch (dieback on
the upper portion of the crown is not part of the live crown) to the obvious crown base. Many times there
are additional live branches below the obvious crown. These branches are only included if they have a
basal diameter greater than 1 inch (2.54 cm) and are within 5 ft (1.5 m) of the base of the obvious crown.
The crown base is that point on the main bole perpendicular to the lowest foliage on the last branch that
is included in the live crown. The crown base is determined by the foliage and not by the point where a
branch intersects with the main bole. Live crown ratio is measured by two raters.
Raters step back about 1/2 to 1 tree length from the base of the tree and move sideways at least 10
ft (3 m) to obtain a good view of the crown. An individual can use the live crown ratio scale on the back
of the crown density-foliage transparency card to help in estimating live crown ratio. To use the scale, hold
the card in one hand and move the card closer or farther from your eye until the 0 is at the live top of the
tree and the 99 is at the base of the tree (ground). Then place your finger at the base of the live crown.
The number on the scale provides the live crown ratio. Interpolate to the nearest 5% if the point is between
two values on the scale. A clinometer can also be used to verify the live crown ratio by determining the
values of both heights and determining the ratio of the two values. This is very useful during training but
is not necessary under field conditions.
When the two raters disagree in their estimates, they should discuss the reasons for their ratings.
Either a rater will change his or her estimate, or the two ratings will be averaged and the class recorded.
The estimate is placed into one of 21 five percentage classes. Codes are structured to the nearest 5
percent to be consistent throughout this guide with other procedures and to allow estimator flexibility.
2.6.3.3 Crown Density
Crown density estimates the tree crown condition in relation to a normal, healthy, forest tree and also
serves as an indicator of expected growth in the near future. Crown density is the amount of crown
branches, foliage, and reproductive structures that blocks light visibility through the crown. Each species
of tree has a normal crown that varies with the site, genetics, tree damage, etc. Higher crown density
estimates are indicative of faster growth, while lower crown density measures indicate slower growth.
Crown density rating is measured by two persons. Individuals should stand about 1/2 to 1 tree length
away from the tree and move sideways at least 10 ft (3 m) to obtain a good view of the crown. To
determine the crown outline, select the point on the stem used for live crown ratio and project a normal
crown for that tree. Foliage below the crown base is not included in the crown. Project half-sided trees
as full crowns, and include crown dieback and open areas in this outline. In many cases, portions of the
tree outline may not be complete, i.e., half-sided trees, and in these situations it may be easier to determine
the percent of the tree missing and the crown density of the tree's remaining portion. Then use the table
in Figure 2-1 (Back) to arrive at the final crown density for that tree.
After determining the outline, the two persons should hold the crown density - foliage transparency card
(Figure 2-1) along the line of sight and estimate what percentage of the outlined area is blocking sunlight.
Try to place trees in 10 percent classes; use a 5 percent class if you cannot decide which 10 percent class
to use. If you disagree on a rating, discuss and adjust it as needed. In most cases, two scores can be
averaged. Two raters may try trading places if their difference is greater than 10 percent or two classes.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 20 of 23
" •• A t
> ^
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 21 of 23
2.6.3.4 Crown Dieback
Crown dieback is defined as branch mortality which begins at the terminal portion of a branch and
proceeds toward the trunk. When whole branches are dead in the upper crown, without obvious signs of
damage such as breaks or animal injury, assume that the branches died from the terminal down. Snag
branches without smaller branches, 1 inch (2.54 cm) or less in diameter at the base, will not be considered
as part of the crown. Dead branches below the upper half of the crown are assumed to have died from
competition and shading, and are not considered as part of crown dieback.
Estimate crown dieback in 5 percent classes, based on the whole crown present at the time of
observation. The crown base should be the same position that is used for the live crown ratio estimate.
Assume that the perimeter of the crown is a two-dimensional outline from branch-tip to branch-tip.
Crown dieback rating is obtained by two raters. Raters should step back about 1/2 to 1 tree length
from the tree base and move sideways at least 10 feet (3 m) to obtain a good view of the crown.
Binoculars should be used to assist in the data collection. Observers should be conscious of lighting
conditions and how they affect the day's observations. Under limited-light conditions, observers should take
extra time because poor lighting can make the measurement more difficult.
First, the raters should mentally draw a two-dimensional crown outline. Second, block in the affected
area. Third, the proportion of the affected area should be estimated in 5 percent classes and recorded.
When two raters disagree in their estimates, they should discuss the reasons for their rating. Either a rater
will change his or her estimate or the ratings should be averaged and the class of the estimate recorded.
Differences may be due to differences in crown conditions, the estimate of the rater, or both.
2.6.3.5 Foliage Transparency
Foliage transparency is defined as the amount of skylight visible through the live, normally foliated
portion of the crown or branch. Each tree species has a normal range of foliage transparency. Changes
in foliage transparency occur as a result of current damage, frequently referred to as defoliation, or from
reduced foliage resulting from stresses during preceding years.
Estimate foliage transparency in 5 percent classes based on the live, normally foliated portion of the
crown and branches using the crown density - foliage transparency card (Figure 2-1). Dead branches,
crown dieback and missing branches or areas where foliage is expected to be missing are deleted from
the estimate.
Large uniform crowns are rated as if the whole crown should be foliated. When defoliation is severe,
branches alone will screen the light, but the raters should exclude the branches from foliage and rate the
area as if the light was penetrating. For example, an almost completely defoliated dense spruce may have
less than 20 percent light coming through the crown, but it will be rated as highly transparent because of
the missing foliage. Old trees, and some hardwood species, have crown characteristics with densely
foliated branches which are spaced far apart in the crown. These spaces between branches should not
be included in the foliage transparency rating. When foliage transparency in one part of the crown differs
from another part, the average foliage transparency is estimated and recorded.
Foliage transparency should be rated by two raters. Raters should step back about 1/2 to 1 tree length
from the tree base and move sideways at least 10 ft (3 m) to obtain a good view of the crown. First, raters
will mentally draw a two-dimensional crown outline. Second, the foliated area will be blocked into the crown
outline. Third, estimate the transparency of the foliated area in 5 percent classes and record.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 22 of 23
When two raters disagree in their estimates, they should discuss the reasons for their rating. Either
a rater will change his or her estimate or the ratings should be averaged and the class of the estimate
recorded. Differences may be due to differences in crown conditions, the estimate of the rater, or both.
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EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 23 of 23
2.7 References
Anderson, R.L. and R.P. Belanger. 1987. A crown rating methods for assessing tree vigor of loblolly
and shortleaf pines. In, D.R. Phillips, camp., Proceedings of the fourth biennial southern silvicultural
research conference. Nov. 4-6, 1986; Atlanta, GA. USDA Forest Service Gen. Tech. Rep. SE-42,
Asheville, NC. pp. 538-543.
Anderson, R.L., W.G. Burkman, I. Millers, and W.H. Hoffard. 1992. Visual crown rating model for
upper canopy trees in the eastern United States. USDA Forest Service, Region 8/Northeastern
Area. 15p.
Belanger, R.P. and R.L. Anderson. 1991. A guide for visually assessing crown densities of loblolly and
shortleaf pines. USDA Forest Service Res. Note SE-352. 10p.
Dolph, K.L. 1988. Predicting height increment of young-growth conifers in the Sierra Nevada. USDA
Forest Service Res. Paper PSW-191. 7p.
Francis, J.K. 1986. The relationship of bole diameters and crown widths of seven bottomland
hardwood species. USDA Forest Service Res. Note. SO-328. 3p.
Grano, C.X. 1957. Growth of loblolly pine seed trees in relation to crown density. J. For. 55(11):852.
Kuhlman, H.M. 1971. Effects of insect defoliation on growth and mortality of trees. Annual Rev. of
Entomology 16:289-324.
Sprinz, P.T. and H.E. Burkhart. 1987. Relationships between tree crown, stem, and stand
characteristics in unthinned loblolly pine plantations. Can. J. For. Res. 17(6):534-538.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 1 of 22
Section 3. Damage and Catastrophic Mortality Assessment
Section/Title
Page
3.0 Quick Reference 2 of 22
3.1 Overview 3 of 22
3.1.1 Scope and Application 3 of 22
3.1.2 Summary of Method 3 of 22
3.1.3 Interferences 3 of 22
3.1.4 Safety 3 of 22
3.2 Sample Collection 4 of 22
3.3 Equipment and Supplies 4 of 22
3.4 Calibration and Standardization 4 of 22
3.5 Quality Assurance 4 of 22
3.5.1 Measurement Quality Objectives 4 of 22
3.6 Procedures 5 of 22
3.6.1 Locationl 5 of 22
3.6.2 Damagel 8 of 22
3.6.3 Location and Damage Combinations 10 of 22
3.6.4 Severity! 12 of 22
3.6.5 Procedures to Record Multiple Occurrences of
the Same Damage 18 of 22
3.6.6 Procedures to Measure Circumference Affected 18 of 22
3.6.7 Location2 18 of 22
3.6.8 Damage2 18 of 22
3.6.9 Severity2 18 of 22
3.6.10 Locations 18 of 22
3.6.11 Damages 18 of 22
3.6.12 SeverityS 18 of 22
3.7 References 19 of 22
Appendix 3.1 Catastrophic Mortality Assessment 20 of 22
Procedure 20 of 22
Table 3-1 Guide for Estimating Time Since Death 21 of 22
General Guides for Postdating Mortality 22 of 22
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EMAP Forest Monitoring, Section 3, Rev. No. 0; October, 1994, Page 2 of 22
3.0 Quick Reference
Definition
No damage
Roots (exposed) and "stump" (12 in [30 cm] in height from ground level)
Roots and lower bole
Lower bole (lower half of the trunk between the "stump" and base of the live crown)
Lower and upper bole
Upper bole (upper half of the trunk between "stump" and base of the live crown)
Crownstem (main stem within the live crown area, above the base of the live crown)
Branches (woody stems other than main stem)
Buds and shoots (the most recent year's growth)
Foliage
Damage
Code Description
Severity Threshold
(in 10% classes to 99%)
01 Canker 20%
02 Conks, fruiting bodies, and other indicators of advanced decay none*
03 Open wounds 20%
04 Resinosis or gummosis 20%
11 Broken bole or roots less than 3 ft (0.91 m) from bole none
12 Brooms on roots or bole none
13 Broken or dead roots( >3 feet from bole) 20%
21 Loss of apical dominance, dead terminal 1%
22 Broken or dead branches 20%
23 Excessive branching or brooms 20%
24 Damaged foliage buds or shoots 30%
25 Discoloration of foliage 30%
31 Other none
*20% for roots >3 feet from bole or branches.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 3 of 22
3.1 Overview
3.1.1 Scope and Application
Damage caused by pathogens, insects, air pollution, and other natural and man-made activities can
affect the growth and development of trees. Damage caused by any of these agents, either singly or in
combination, can significantly affect forest health. Identifying the signs and symptoms of damage provides
valuable information concerning the forest's condition and indicates possible causes of deviation from
expected conditions. For Forest Health Monitoring (FHM), damage signs and symptoms are recorded if,
by definition, the damage could kill the tree or affect the long-term survival of the tree.
This definition of damage was developed to improve data quality and to improve the repeatability of
measurements. Only those damage categories that could kill the tree or have the potential to affect the
long-term survival of the tree are recorded. The cause of damage is not recorded due to variability among
raters The damage categories are prioritized based on location, eliminating uncertainties due to the
estimate of observers." Minimum thresholds and severity classes exist for appropriate damage categories.
Obvious signs of catastrophic events such as fire, bark beetles, wilts, beaver, wind, or logging may
cause mortality to trees when no previous significant signs of damage were present. Identification of these
major agent groups can help explain sudden, unexpected causes of mortality. Due to the complicated
interactions of biotic and abiotic agents, this level of evaluation is not generally repeatable. However when
the signs are obvious even to the casual observer, this datum, together with the damage indicator
information, can provide valuable insight to the causes of deviations from expected conditions.
3.1.2 Summary of Method
Damage signs and symptoms are recorded on all live saplings 1.0 inch (2.54 cm) to 4.9 inches (12.5
cm) DBH on the 1/300 acre (1/750 hectare) microplot and all live trees 5.0 inches (12.7 cm) DBH and
larger on the 1/24 acre (1/60 hectare) subplot. Also included in this section is Catastrophic Mortality
Assessment protocols (Appendix 3.1).
Due to the difficulty in incorporating proposed changes into the Tally program at this time, the "cause
of death" codes used in 1994 will be the same as those used in 1993. Some codes will be eliminated and
others'combined during post processing for analysis purposes. Insect/disease, fire, animal, weather,
logging/human damage, and unknown/other will be the major agent groups used for analysis.
3.1.3 Interferences
Several uncontrollable environmental and site conditions have hindered or slowed the damage and
mortality assessment measurements, including (1) poor weather conditions such as gustmg wind, heavy
rain and dark overcast skies; (2) steep and/or unstable slopes; (3) dense understory vegetation which
prohibits free ground movement; and (4) thick canopy immediately overhead that obscures full view of the
tree. Suspend data collection under severe weather conditions, such as strong winds and heavy rainfall.
3.1.4 Safety
No specialized safety precautions are necessary. Follow general safety precautions for conducting
fieldwork. (See Appendix E.)
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 4 of 22
3.2 Sample Collection
No material samples are collected.
3.3 Equipment and Supplies
Two trained and certified persons should be able to perform measurements using only a diameter tape.
Binoculars are helpful yet optional. All measurements are recorded on portable data recorders (PDRs).
In case of PDR failure, record the appropriate code for up to three damage types for each tree in the
appropriate column.
Location
(1) (2) (3)
Damage
(1) (2) (3)
Severity
(1) (2) (3)
3.4 Calibration and Standardization
General calibration and standardization protocols should be applied to field equipment. Purchase tapes
to required specifications. Tapes should be maintained in working order and do not require calibration upon
confirmation of accuracy.
3.5 Quality Assurance
3.5.1 Measurement Quality Objectives
Table 3-1 lists Damage Measurement Quality Objectives.
Table 3-1. Damage Measurement Quality Objectives
Variable
No damage
Location
Damage
Severity
All
No. of Units
1
10
13
10
258 combinations
Acceptable Range
90% agreement
90% agreement
85% agreement
80% + or - class
80% complete agreement
(+ or - 1 severity class)
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 5 of 22
3.6 Procedures
The tree is observed from all sides starting at the roots. Damage signs and symptoms are prioritized
and recorded based on location in the following order: roots, roots and lower bole, lower bole, lower and
upper bole, upper bole, crownstem, branches, buds and shoots, and foliage recorded as location code 0-9.
Within any given location, the hierarchy of damage follows the numeric order of damage types possible
for that location. The numeric order denotes decreasing significance as the code number goes up, i.e.,
damage 01 is more significant than damage 25. A maximum of three damages are recorded for each tree.
If a tree has more than three damages that meet the threshold levels, the first three that are observed
starting at the roots are recorded.
When multiple damages occur in the same place, the most damaging is recorded. For example, if a
canker, damage code 02, meets the threshold and has a conk growing in it, record only the canker.
Another example is, if an open wound meets threshold and also has resinosis, record only the open wound.
Specific causal agents are not identified through the coding system. One goal of FHM is the detection
of change. The identification of specific causal agents is one of the objectives of Evaluation Monitoring.
If the field crew can identify specific causal agents, the agents should be included in the "notes" section
for individual trees. In the future, codes for specific causal agents may be added.
3.6.1 LOCATION1
LOCATION1 is the location (LOCATN1) on the tree where DAMAGE1 is found (see Figure 3-1). If the
same damage continues into two or more locations, record the appropriate code listed below, or if the
combination of locations does not exist (damage extends from crownstem to roots), record the lowest
location (see Figure 3-2). Multiple damages may occur in the same location, but record the higher priority
damage (lower code number) first. If the damages are coincident (a conk within a canker), record only the
higher priority damage.
Definition
No damage
1 Roots (exposed) and "stump" (12 inches (.3 m) in height from ground level)
2 Roots and lower bole
3 Lower bole (lower half of the trunk between the "stump" and base of the live crown)
4 Lower and upper bole
5 Upper bole (upper half of the trunk between "stump" and base of the live crown)
6 Crownstem (main stem within the live crown area, above the base of the live crown)
7 Branches (woody stems other than main stem)
8 Buds and shoots (the most recent year's growth)
9 Foliage
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 6 of 22
12" I "STUMP-TOP
FOLIAGE
(09)
BUDS/SHOOTS
(08)
BRANCHES
(07)
CROWNSTEM
(06)
BASE OF UVE
CROWN
MIDPOINT OF BOLE
MIDWAY BETWEEN CROWN
BASE AND "STUMP"
ROOTST STUMP"
(01)
0195mad94-2Q
Figure 3-1. Location codes for the damage indicator.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 7 of 22
Exposed
Decay Column
Figure 3-2. The damage runs from stump to crownstem. Code here should be 02 (roots and "stump" and lower bole)
which represents the lowest locations of this multi-location damage.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 8 of 22
3.6.2 DAMAGE1
DAMAGE1 is the first damage observed that meets the damage threshold definition in the lowest
location. Damage categories are recorded based on the numeric order which denotes decreasing
significance from damage 01 - 31.
FHM Damage codes and definitions:
Code Description
01 Canker
Cankers may be caused by various agents but are most often caused by fungi. The bark and
cambium are killed, and this is followed by death of the underlying wood, although the causal
agent may or may not penetrate the wood. This results in areas of dead tissue that become
deeper and wider, or galling (including galls caused by rusts) on roots, bole, or branches. (For
procedures on how to measure multiple cankers see Sections 3.6.5 and 3.6.6.) A canker may
be:
Annual (enlarges only once and does so within an interval briefer than the growth cycle of the
tree, usually less than one year),
Diffuse (enlarges without characteristic shape or noticeable callus formation at margins), or
Perennial (enlarges during more than one year - often has a target appearance).
02 Conks, fruiting bodies, and other indicators of advanced decay. Fruiting bodies on the main
bole, crownstem, and at the point of the branch attachment are decay indicators. "Punky
wood" is present when openings larger than the width of a pencil occur in the main bole.
Punky wood is evidenced by soft, often moist, and degraded tissue.
Open cracks that do not qualify as open wounds because they do not meet that threshold
should be coded here even if they have no obvious signs of punky wood. A fire scar at the
base of a tree is an indicator of decay.
Cavities into the main bole from old branches are indicators of decay.
Open wound in contact with the ground is an indicator of decay.
Rotten branches or branches with conks are not indicators of decay unless the threshold is met
(>20% of branches are affected).
Rotting stumps associated with coppice regeneration (e.g., northern pin oak, red maple) are
excluded from coding.
03 Open wounds
An opening or series of openings where bark has been removed or the inner wood has been
exposed and no signs of advanced decay are present. Pruning wounds that cut into the wood
of the main stem are coded as open wounds, if they meet the threshold; those which leave the
main stemwood intact are excluded. (For procedures on how to measure open wounds see
Sections 3.6.5 and 3.6.6.)
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 9 of 22
Code Description
04 Resinosis or gummosis
Areas of resin or gum (sap) exudation on branches and trunks. (For procedures on how to
measure resinosus or gummosis, see Sections 3.6.5 and 3.6.6.)
11 Broken bole or roots less than 3 feet (.91 m) from bole
Broken roots within 3 feet (.91 m) of bole either from excavation or rootsprung for any reason.
For example, those which have been excavated in a road cut or by animals.
Stem broken in the bole area (below the base of the live crown) and tree still alive.
12 Brooms on roots or bole
Clustering of foliage about a common point on the trunk. Examples include ash yellows
witches' brooms on white and green ash and eastern and western conifers infected with dwarf
mistletoes.
13 Broken or dead roots (beyond 3 feet (.91 m))
Roots beyond 3 feet (.91 m) of bole that are broken or dead.
21 Loss of apical dominance, dead terminal
Mortality of the terminal of the crownstem caused by frost, insect, disease, or other causes.
22 Broken or dead
Branches or shoots that are broken or dead. Dead branches attached to the bole below the
base of the live crown are not coded.
23 Excessive branching or brooms
Brooms are a dense clustering of twigs or branches arising from a common point that occur
within the live crown area. Includes abnormal clustering of vegetative structures and organs.
This includes witches' brooms caused by ash yellows on green and white ash and those
caused by dwarf mistletoes.
24 Damaged foliage or shoots
Insect feeding, shredded or mechanically damaged or distorted foliage or shoots affecting at
least 30% of foliage or shoots. Also includes herbicide-damaged shoots.
25 Discoloration of foliage
At least 30% of the foliage is more than 50% affected. Affected foliage must be more of some
color other than green. If the observer is unsure if the color is green, it is considered green
and not discolored.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 10 of 22
Code Description
31 Other
Use when no other explanation is appropriate. Specify in comments section of PDR for "tree
notes."
3.6.3 LOCATION and DAMAGE Combinations
The following table depicts the possible combinations of damage by location, "Y" indicates a valid
combination, and "N" indicates an invalid combination.
Damage
Location
1
2
3
4
5
6
7
8
9
01
Y
Y
Y
Y
Y
Y
Y
N
N
02
Y
Y
Y
Y
Y
Y
Y
N
N
03
Y
Y
Y
Y
Y
Y
Y
N
N
04
Y
Y
Y
Y
Y
Y
Y
N
N
11
Y
Y
Y
Y
Y
N
N
N
N
12
Y
Y
Y
Y
Y
N
N
N
N
13
Y
N
N
N
N
N
N
N
N
21
N
N-
N
N
N
Y
N
N
N
22
N
N
N
N
N
N
Y
N
N
23
N
N
N
N
N
N
Y
N
N
24
N
N
N
N
N
N
N
Y
Y
25
N.
N
N
N
N
N
N
N
Y
31
Y
Y
Y
Y
Y
Y
Y
Y
Y
Determining Damage by Location
For each of the following location codes, possible damage codes and damage definitions are
presented.
Code Location
1 Roots, within 3 feet (.91 m) of bole to 12 inches (.3 m) in height on the bole ("stump") - (Code 13,
if appropriate, for roots beyond 3 feet (.91 m) from bole)
01 Canker - exceeds 20% of circumference of "stump".
02 Conk, fruiting body, or other indicators of advanced decay, or if open wound is in contact
with the ground - any occurrence.
03 Open wounds - exceeds 20% of circumference of "stump" and are not in direct contact with
the ground - any occurrence.
04 Resinosis or gummosis - flow width exceeds 20% of circumference of "stump".
11 Broken bole or roots less than 3 feet (.91 m) from bole - any occurrence.
12 Brooms on roots and bole - any occurrence.
13 Broken or dead - exceeds 20% of roots, beyond 3 feet (.91 m) of bole, broken or dead
31 Other.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 11 of 22
Code Location
2 Roots and lower bole
01 Canker - exceeds 20% of circumference at the point of occurrence.
02 Conk, fruiting body, or other indicators of advanced decay, or if open wound is in contact
with the ground - any occurrence.
03 Open wounds - exceeds 20% of circumference at the point of occurrence, and are not in
direct contact with the ground.
04 Resinosis or gummosis - flow width exceeds 20% of circumference at the point of
occurrence.
11 Broken bole or roots less than 3 feet (.91 m) from bole - any occurrence.
12 Brooms on roots and bole - any occurrence.
31 Other.
3 Lower bole - same as roots and lower bole.
4 Lower and upper bole - same as roots and lower bole.
5 Upper bole - same as roots and lower bole.
6 Crownstem
01 Canker - exceeds 20% of circumference of crownstem at the point of occurrence.
02 Conk, fruiting body or other indicators of advanced decay - any occurrence.
03 Open wounds - exceeds 20% of circumference of crownstem at the point of occurrence.
04 Resinosis or gummosis - flow width exceeds 20% of circumference of crownstem at the
point of occurrence.
21 Loss of apical dominance, dead terminal - any occurrence.
31 Other.
7 Branches
01 Canker - exceeds 20% of circumference on at least 20% of branches.
02 Conks, fruiting bodies and other indicators of advanced decay - more than 20% of
branches affected.
03 Open wounds - exceeds 20% of circumference on at least 20% of branches.
04 Resinosis or gummosis - flow width exceeds 20% of circumference on at least 20% of
branches.
22 Broken or dead - more than 20% of branches affected.
23 Excessive branching or brooms - more than 20% of branches affected.
31 Other.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 12 of 22
Code Location
8 Buds and shoots
24 Damaged buds, shoots or foliage - more than 30% of buds and shoots damaged more
than 50%.
31 Other.
9 Foliage
24 Damaged buds, shoots or foliage - more than 30% of foliage damaged more than 50%.
25 Discoloration of foliage - more than 30% of foliage discolored more than 50%.
31 Other.
3.6.4 SEVERITY1
SEVERITY1 is amount of affected area (above threshold) in LOCATION1 recorded for
DAMAGE1. Severity codes vary depending on the type of damage recorded. The codes and
procedures for SEVERITY1 values are:
Code 01 - Canker
Measure the affected area from the margins (outer edges) of the canker or gall within any 3 foot
(.91 m) vertical section in which at least 20% of circumference is affected at the point of occurrence.
See Figure 3-3.
Severity classes for code 01 (percent of circumference affected):
Classes Code
20-29 2
30-39 3
40-49 4
50-59 5
60-69 6
70-79 7
80-89 8
90-99 9
Code 02 - Conks, fruiting bodies, and other indicators of advanced decay
Severity classes for code 02:
None. Enter code 0 regardless of severity.
Code 03 - Open wounds
The damaged area is measured at the widest point between the margins of the exposed wood
within any 3 foot (.91 m) vertical section in which at least 20% of the circumference is affected at the
point of occurrence. See Figure 3-4.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 13 of 22
Figure 3-3. A canker which exceeds threshold. Since 40% of circumference is visible from any side, and since over half
the visible side Is taken up by the canker, it obviously exceeds the 20% minimum circumference threshold.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 14 of 22
Figure 3-4. Multiple damage in "stump" and lower bole. Approximately 40% of tree circumference; B=portion of tree
circumference affected by damage; C=vertical distance within one meter; D=midpoint of occurrence at which
circumference is measured.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 15 of 22
Severity Classes for code 03 (percent of circumference affected):
Classes
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
2
3
4
5
6
7
8
9
Code 04 - Resinosis or gummosis
Resinosis or gummosis is measured at the widest point of flow within any 3 foot (.91 m) vertical section
in which at least 20% of the circumference is affected at the point of occurrence.
Severity classes for code 04 (percent of circumference affected):
Classes
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
2
3
4
5
6
7
8
9
Code 11 - Broken bole or roots less than 3 feet (.91 m) from bole
Severity classes for code 11:
None. Enter code 0 regardless of severity.
Code 12 - Brooms on roots or bole
Severity classes for code 12:
None. Enter code 0 regardless of severity.
Code 13 - Broken or dead roots
Over 20% of roots beyond 3 feet (.91 m) of bole that are broken or dead.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 16 of 22
Severity classes for code 13 (percent of roots affected):
Classes
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
2
3
4
5
6
7
8
9
Code 21 - Loss of apical dominance, dead terminal
This damage has no threshold for recording but is recorded, if it occurs, in 10% classes as percent of
crownstem affected. Use trees of the same species and general DBH class in the area or look for
crownstem on the ground to aid in estimating percent affected.
Severity classes for code 21:
Classes
01-09
10-19
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
0
1
2
3
4
5
6
7
8
9
Code 22 - Broken or dead branches (within the live crown)
Over 20% of branches are broken or dead.
Severity classes for code 22 (percent of branches or shoots affected):
Classes
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
2
3
4
5
6
7
8
9
Code 23 - Excessive branching or brooms.
Over 20% of crownstem or branches affected with excessive branching or brooms.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 17 of 22
Severity classes for code 23 (percent of area affected):
Classes
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
2
3
4
5
6
7
8
9
Code 24 - Damaged buds, shoots or foliage
At least 30% of the buds, shoots or foliage (i.e., chewed or distorted) are more than 50% affected.
Severity classes for code 24:
Classes
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
3
4
5
6
7
8
9
Code 25 - Discoloration of Foliage
At least 30% of the foliage is more than 50% affected.
Severity classes for code 25 (percent affected):
Classes
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Code
3
4
5
6
7
8
9
Code 31 - Other
Severity classes for code 31:
None. Enter code 0 regardless of severity. Describe condition in notes.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 18 of 22
3.5.5 Procedures to Record Multiple Occurrences of the Same Damage
Damage codes 01 (canker), 03 (open wounds), and 04 (resinosis/gummosis) must meet a threshold
of 20 percent of the circumference at the point of occurrence, within any 3 foot (.91 m) section. Multiple
cankers or open wounds which are directly above one another pose no more threat to long term tree
survival than would a single damage incidence of the same width. However, should multiple damages be
located horizontally within any 3 foot (.91 m) section, the translocation of water and nutrients would be
significantly affected. The widths of each individual damage are added and compared as a percent, to the
total circumference at the midpoint of the 3 foot (.91 m) section (Figure 3-2).
3.6.6 Procedures to Measure Circumference Affected
A practical approach is to observe every face of the "stump", bole, or crownstem. About 40% of the
circumference of a face can be observed at any one time. The damage is measured horizontally between
the margins (see Figure 3-4). If the cumulative area affected within a 3 foot (.91 m) section exceeds 1/2
of any face, then the 20% minimum threshold has been met. The percent of the circumference affected
by damage is then estimated in 10% classes. If in doubt, measure the damage and circumference with
a linear tape.
3.6.7 LOCATION2
LOCATION2 is the location (LOCATN2) on the tree where the DAMAGE2 is found. See LOCATION1
for codes. If damage continues into two or more locations for which a code does not exist, use lowest
location (see Subsection 3.6.1).
3.6.8 DAMAGE2
DAMAGE2 is the second damage observed that meets the damage threshold definition in the lowest
location. Damage categories are recorded for a given location based on numeric order from 01- 31 (see
Subsection 3.6.2).
3.6.9 SEVERITY2
SEVERITY2 is the severity class for DAMAGE2. See SEVERITY1 (Subsection 3.6.4) for codes.
3.6.10 LOCATIONS
This is the location (LOCATN3) on the tree where the DAMAGES is found. See LOCATION1 for codes.
If damage continues into two or more locations for which a code does not exist, use lowest location (see
Subsection 3.6.1).
3.6.11 DAMAGES
DAMAGES is the third damage observed that meets the damage threshold definition in the lowest
location. Damage categories are recorded for a given location based on numeric order from 01 - 31 (see
Subsection 3.6.2).
3.6.12 SEVERITY3
SEVERITY3 is the severity class for DAMAGES. See SEVERITY! (Subsection 3.6.4) for codes.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 19 of 22
3.7 References
Johnson, W.T., H.H. Lyon. 1988. Insects That Feed on Trees and Shrubs. Comstock Publishing
Associates, Cornell University Press, Ithaca, NY.
Sinclair, W.A., H.H. Lyon, W.T. Johnson. 1987. Diseases of Trees and Shrubs. Comstock Publishing
Associates, Cornell University Press, Ithaca, NY.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 20 of 22
Appendix 3.1 Catastrophic Mortality Assessment
Obvious signs of catastrophic events such as fire, bark beetles, wilts, beaver, wind, or logging may
cause mortality to trees when no previous significant signs of damage were present. Identification of these
major agent groups can help explain sudden, unexpected causes of mortality. Due to the complicated
interactions of biotic and abiotic agents, this level of evaluation is not generally repeatable. However, when
the signs are obvious even to the casual observer, this datum, together with the damage indicator
information, can provide valuable insight to the causes of deviations from expected conditions.
Due to the difficulty in incorporating proposed changes into the Tally program at this time, the "cause
of death" codes used in 1994 will be the same as those used in 1993. Some codes will be eliminated and
others combined during post processing for analysis purposes. Insect/disease, fire, animal, weather,
logging/human damage, and unknown/other will be the major agent groups used for analysis.
Cause of death is recorded for all saplings 1.0 inch (2.54 cm) DBH and larger on the microplot, and
all trees 5.0 inches (12.7 cm) DBH and larger on the subplot that were recorded as live trees during the
previous inventory.
Procedure
Record the appropriate 3-digit code for each cut or dead tree tallied. From the list below, specify the final
causal agent group that most likely resulted in tree death. Code 001 is assigned at processing for all trees
that are dead when initially encountered (e.g., Mt1 snags).
CAUSE OF DEATH
Code Definition
001 Tree dead when first encountered
100 Insect
200 Disease
201 Fire
300 Blister Rust (CA)
400 Animal
500 Weather
600 Suppression/Competition
700 Logging and related human damage
800 Unknown
999 Other than described above; needs explanation in notes
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 21 of 22
Tabl» 3-1. Guide for Estimating Time Since Death (CA/PNW PS Only)
Died within past 5 years
Species
Died more than 5 years ago
Often some foliage left; 30+% twigs left; few branches falling; some Sugar Pine
bark loosening; green to deteriorated sapwood; Blue stain fungi or
Polyporus volvatus present or drying up.
Often some foliage left; 60+% twigs left; very few branches falling; Western
bark intact; sapwood green to gray, sound; Little or no fungi. Redcedar
Often some foliage left; 30+% twigs left; small branches falling;
some bark loosening; green to deteriorated sapwood; Blue stain
fungi or Polyporus volvatus present or drying up.
Ponderosa Pine
Sometimes some foliage left; 10+% twigs left; small branches Douglas-Fir
falling; some top breakage; bark sloughing on small trees; sapwood
green to deteriorating; Polyporus volvatus and/or Fome pinocola
present, the latter on small trees.
Sometimes some foliage left; 5+% twigs left; limbs intact to starting True Firs
to fall; bark intact to beginning to slough; sapwood green to having
considerable rot; Polvporus volvatus and/or Fomes pinocola
appearing.
Sometimes some foliage left; 20+% twigs left; some small tree Western hemlock
branches falling; bark intact to loosening on smaller trees; sapwood
stained to deteriorating Fungi may include Polyporus volvatus
and/or Fomes pinicola.
Some foliage teft, 75+% twigs & 30+% branches left; bark intact. White pine
Some foliage left; 30+% twigs & 50+% branches left; little bark
sloughing.
Some foliage left; 75+% twigs & branches left.
Some foliage left
HARDWOODS
50+% bark attached in some degree.
50% or more of bark still attached to the bole in some degree.
50% or more of bark still attached to the bole in some degree.
Spruce
Lodgepole pine
Pinyon
Aspen
Cotton wood
Other Hardwoods
(i.e., Oaks)
No foliage; <30% of the twigs left;
many limbs falling; bark loose &
sloughing; sapwood deterioration
almost complete; miscellaneous
species of fungi.
No foliage; <60% of the twigs left;
some limbs falling; large pieces of
bark striping off; sapwood sound;
fungi few.
No foliage; <30% of the twigs left;
many limbs falling; bark loose &
sloughing; sapwood deterioration
severe; miscellaneous species of
fungi.
No foliage; <10% of the twigs left;
limbs falling; about 50% with tops
broken; bark sloughing;
considerable sap rot; Fomes
pinicola and other corks common.
No foliage; <5% of the twigs left;
many limbs falling; bark loose and
sloughing; sapwood deterioration
complete; miscellaneous species
of fungi present.
No foliage; <20% of the twigs left;
many limbs falling; bark loose and
sloughing; sapwood deterioration
almost complete; Fomes pinicola
common.
No foliage; 75% of less twigs left;
many big limbs gone; much bark
sloughing (except small trees).
No foliage; 30% or less twigs &
50% or less branches left; bark
sloughing. Big limbs gone.
No foliage; 75% or less twigs &
branches left; bark sloughing.
No foliage left.
No foliage; bark 50% or less
attached.
No foliage; bark completely free of
bole or less than 50% attached in
any degree.
No foliage; bark completely free of
bole or less than 30% attached in
any degree.
In all cases, the presence of sporophora or sapwood rotting fungi such as Polyporus rolvalis, Fomes pinicola, etc., will be accepted
as evidence that the tree has been dead more than 5 years.
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EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 22 of 22
GENERAL GUIDES FOR POSTDATING MORTALITY
1. Large trees generally deteriorate more slowly than small trees.
2. Douglas-fir usually deteriorates more slowly than hemlock or true firs. Cedars deteriorate the slowest
of all trees.
3. Deterioration often depends on the local environment.
4. Blue stain usually appears in the sapwood during the first year.
5. Fomes pinicola (red belt fungus) usually produces conks the third year after death. It is yellowish in
color for the first 3 years, appearing in bark crevasses. As it grows older, it develops reddish margins
and grows to a large bracket shape. It is a perennial conk. Each year it lays down a new belt of
growth which can be counted to age mortality.
6. Sapwood usually completely deteriorates in 5 years in Douglas-fir; sooner in hemlock and true firs.
7. Heartwood deteriorates 2 cm to 15 cm in 8-10 years.
8. Foliage is usually absent after 3 years in conifers, sooner in deciduous.
9. Most twigs and small branches are absent after 5 years.
10. Large limbs usually begin falling in 8-10 years.
11. Tops start breaking up in most standing trees in 8-10 years, sooner in Douglas-fir.
12. Trees with > 50% of the bark detached have been dead over 5 years.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 1 of 18
Section 4. Photosynthetically Active Radiation (PAR) Indicator
Section/Title Page
4.1 Overview 2 of 18
4.1.1 Scope and Application '. . . . 2 of 18
4.1.2 Summary of Method 2 of 18
4.1.3 Interferences 2 of 18
4.1.4 Safety 3 of 18
4.2 Sample Collection, Preservation, and Storage 4 of 18
4.3 Equipment and Supplies 4 of 18
4.3.1 Equipment and Apparatus 4 of 18
4.3.2 Consumable Supplies 4 of 18
4.4 Calibration and Standardization 4 of 18
4.4.1 Ceptometer 4 of 18
4.4.2 Quantum Sensors 5 of 18
4.4.3 Reprogramming the LICOR 1000 Datalogger 5 of 18
4.5 Quality Control 7 of 18
4.5.1 Data Quality 8 of 18
4.5.2 Method Performance 8 of 18
4.6 Procedures 8 of 18
4.6.1 Sample Collection 8 of 18
4.6.1.1 Timing of Measurements 9 of 18
4.6.1.2 Weather Considerations 9 of 18
4.6.2 Ceptometer - Basic Operation 9 of 18
4.6.3 Daily Operations 10 of 18
4.6.3.1 Ambient Measurements 10 of 18
4.6.3.2 Daily Programming of the Ambient Station Datalogger 13 of 18
4.6.3.3 PAR Grid Establishment 14 of 18
4.6.3.4 Under-Canopy Measurements 15 of 18
4.6.3.5 Deactivate Ambient Station 16 of 18
4.6.3.6 Downloading Data 16 of 18
4.6.4 Preventative Maintenance 17 of 18
4.7 References 18 of 18
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 2 of 18
4.1 Overview
4.1.1 Scope and Application
Measurements of solar radiation intercepted by the canopy are fundamental for interpreting the
productivity and function of plant communities (Norman and Campbell, 1989). Photosynthetically active
radiation (PAR) is the quantity of light between the 400-700 nm wavelengths of the spectrum and is that
part of the spectrum that plants use for photosynthesis. The amount of PAR that is transmitted through
a plant canopy can be expressed as the ratio of PAR under the canopy to the total ambient (incoming) PAR
at the site. This ratio can be used to estimate Leaf Area Index (LAI), an indicator of canopy condition, and
upon remeasurement, can be combined with growth measurements to estimate growth efficiency, an
important indicator of forest health (Waring and Schlesinger, 1985). PAR can also be combined with
companion indicators of site condition, growth, regeneration, vegetation structure, crown assessment,
and/or remote sensing to assess canopy condition with a multivariate indicator approach.
In the past, reliable ground-level measurements of transmitted solar radiation were difficult to achieve
and were typically characterized by significant temporal and spatial variability. Ambient PAR measurements
vary depending upon cloud conditions, time of day, and solar angle (i.e., location and time of season). This
method uses a portable integrating radiometer called a Ceptometer (Decagon Devices, Inc., Pullman, WA)
for estimating PAR in combination with quantum sensors (LI-COR, Lincoln, NE) to estimate transmitted
PAR in various forest types and stand conditions.
4.1.2 Summary of Method
PAR is measured with specialized quantum sensors that are responsive to solar radiation in the
400-700 nm waveband. Ambient PAR is measured with two independent quantum sensors placed in a
nearby open area and connected to a datalogger. One quantum sensor is shaded, and one is left in full
sun. The shaded quantum sensor measures diffuse PAR, which allows determination of beam fraction:
an indicator of cloudiness. Under-canopy PAR is measured with the ceptometer, which has a wand with
a linear array of 80 quantum sensors coupled to an internal integrating datalogger. Under-canopy and
ambient PAR are measured in synchrony to estimate transmitted PAR and canopy leaf area index.
PAR measurements are obtained during a standard sampling window from 1200 hrs to 1400 hrs
daylight time (standard zone time, i.e., 1100 and 1300). This window is necessary to minimize the effects
of solar angle upon transmitted PAR. The measurement window is most important late in the field season.
PAR measurements are made on a grid of 28 sample points, 7 at each of the 4 subplots (Figure 4-1).
This allows remeasurement of sample points for quality control (QC). Furthermore, this system allows us
to estimate the spatial and temporal variability of PAR and to scale up from the subplot level to the plot
level. Studies have shown that measurement of 7 points per subplot is sufficient to accurately characterize
the subplot while minimizing sampling time.
4.1.3 Interferences
• Rain - on the sensors may affect the readings. On rainy days, PAR sampling must be done either
before rain begins or after the rain has ceased. There will be plots on which PAR cannot be
sampled because of rain.
• Heavy wind - could topple the ambient station. (There are no documented cases of this
happening. In winds that strong, get out of the woods for safety's sake.)
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 3 of 18
Dense underbrush requires the sampler to employ a "stab" technique when using the ceptometer,
which takes more time than when in the open.
Steep slopes require more care to be taken in keeping the ceptometer level during sampling.
Long distance to open areas may require a hike to set up the ambient sensors. However, new
shade disk positioning methods have eliminated the need to recheck the shade disk immediately
prior to ceptometer sampling.
270
Sample Subplot
PAR Sample Locations
Subpbd: 1-7
Subpb<2: 8-14
SubpbtS: 15-21
SubpbU: 22-28
Figure 4-1. PAR sampling scheme. Subplot example on left shows sampling point layout according to azimuth.
Diagram on right shows 7-point grid for each subplot of the 4 fixed-area subplot cluster. A total of 28 points will be
sampled per location.
4.1.4 Safety
Vehicle safety is important.
Ceptometers and plastic flags have sharp, pointed ends.
Poor footing could lead to falls.
Heat exhaustion can occur during summer days, therefore, plenty of water should be available, and
sun protection should be used.
Insect bites and poison ivy/oak are potential hazards.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 4 of 18
4.2 Sample Collection, Preservation, and Storage
PAR measurements are taken in the field with a portable ceptometer, under the canopy, and with
quantum sensors in the open (ambient). The under-canopy measurements are stored in memory by the
ceptometer and the measurements taken in the open areas are stored in a datalogger attached to two (2)
quantum sensors; one shaded, and one unshaded. The measurements are downloaded to a
microcomputer (PC) at the end of the day and then sent to a mainframe computer for backup and analysis.
Collection of the data follows procedures outlined in Section 4.6.
No material samples are collected or stored.
4.3 Equipment and Supplies
4.3.1 Equipment and Apparatus
• 1 ceptometer, Decagon Devices, Inc. Model SF-80 with case
• 2 quantum sensors, LI-COR LI-190, calibrated to a standard
• 1 datalogger, LI-COR 1000
• 1 platform for mounting quantum sensors with attached and adjustable black disk for shade
• 1 tripod
• 1 hand compass (shared with crew)
• 1 measuring tape - with trailer (shared)
• 1 timepiece (wristwatch)
• 1 portable microcomputer (PC) at office or motel
• 1 datalogger shelter (constructed from 2 empty bleach bottles)
• 1 backpack
• 1 protractor
• 1 six-inch rule
• 1 screwdriver
• Rite in the Rain field notebook
• Laminated HELP sheets
• Cables for downloading ceptometer and datalogger to PC
4.3.2 Consumable Supplies
• 10 "AA" batteries for ceptometer (5, plus 5 spares)
• 12 "D" batteries for datalogger (6, plus 6 spares)
• 2 soft, clean cloths
• 1 bottle 50% ethyl alcohol
• 50 plastic flags (25 one color; 25 another)
4.4 Calibration and Standardization
4.4.1 Ceptometer
A ceptometer has a wand comprised of an array of 80 quantum sensors. The end sensor is calibrated
by the manufacturer. The other 79 sensors need to be calibrated to match the end sensor whenever the
batteries are changed. Calibration is done at the beginning of the field season by the PAR coordinator and
by the PAR crew member, if the batteries are changed during the season. Recalibration should be done
on a clear day. To calibrate the ceptometer:
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 5 of 18
1. Set the ceptometer to Function 7.
2. Then hold down buttons A and B and press the Function key. When the letters "PLL" appear on
left hand side of display, the probe is calibrated (Decagon Devices, Inc., 1989).
The PAR coordinator will perform additional calibration at the beginning of the field season by collecting
simultaneous readings under uniform conditions from each ceptometer and the specific pair of quantum
sensors to be used with that ceptometer. Regressing the readings will provide a ceptometer-specific
multiplier which is applied to the data during analysis.
4.4.2 Quantum Sensors
The quantum sensors for measuring ambient PAR are factory calibrated. The specific calibration
multiplier to be used with each sensor is printed on a card attached to the quantum sensor cable. These
multipliers are programmed into the datalogger; it is extremely important that quantum sensors A and B
not be confused. Always use sensor A as the full ambient sensor on datalogger channel 1. Always use
sensor B as the black disk (shaded) sensor on channel 2. If the sensors are mixed up, the calibration
constants will not be correct.
Synchronize the wristwatch, ceptometer, and datalogger each day.
4.4.3 Reprogramming the LICOR 1000 Datalogger
The six "D" cells in the LI-COR should last the entire field season. If they do not, then you will need
to reprogram the LI-COR. Reprogramming the LI-COR informs the datalogger how and when to record
measurements.
An internal lithium cell will retain datalogger memory, including channel configurations and stored data,
for a short time while the batteries are removed. Changing batteries promptly when the "LO" low battery
warning appears may avoid the need to reprogram the LI-COR. If reprogramming becomes necessary,
here is how to do it:
1. Press "FCT ON" to turn on the LI-COR. The display will first read "LI1000.02.02" (the name of the
resident software) and then will display some numbers and letters such as "11 O.OUM". The
specific display may vary.
2. Press "CFG" to enter the configuration mode. LI-COR will prompt, "mode is ". Choices are
INSTantaneous or LOG; use LOG. Using the up or down arrow, scroll through the menu until
display reads "mode is LOG", then press "ENTER."
3. LI-COR will prompt, "ch1 is ". Choices are OFF, LIGHT, GENeral, or THERMocouple; use
LIGHT. Using the up or down arrow, scroll through the menu until display reads "ch1 is LIGHT",
then press "ENTER."
4. LI-COR will prompt, "range= ". Choices are A, 1, 2, 3, or 4; use A for automatic. Using the up
or down arrow, scroll through the menu until display reads "range= A", then press "ENTER."
5. LI-COR will prompt, "mult= ". The datalogger requires the calibration multiplier for channel
1. The calibration multiplier is determined at the factory and printed on a card attached to each
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 6 of 18
quantum sensor. Since currently programming channel 1, which is always used with Sensor A
(the full ambient sensor), enter the calibration multiplier found on the card attached to Sensor A,
use the number keys (left arrow will undo mistakes), and press "ENTER" when ready.
6. LI-COR will prompt, "label= ". Enter UM (jamoles/nf/second). Accessing letters on the Ll-
COR's keypad is a two-key operation. The letters in the upper left comer of each key are
accessed by first pressing the up arrow, then the key. Letters in the lower left comer of each key
are accessed by pressing the down arrow, then the key. Pressing T, 3, t, 2 should display UM.
Press "ENTER" when ready.
7. LI-COR will prompt, "per= ". This is the logging period, in minutes, over which readings will be
taken and averaged. Using the up or down arrow, scroll through the menu until the display reads
"per= 1", then press "ENTER."
8. LI-COR will prompt, "reset= HHMM". This is the time each day when logging is to begin.
Use numbered keys to enter 1100, and press "ENTER."
9. LI-COR will prompt, "thr= ". The datalogger requires a threshold level below which data will not
be stored in memory. To collect and log all data enter "00.00" using the numbered keys, and press
"ENTER."
10. LI-COR will prompt, "store= ". The LI-COR reads the sensors every 5 seconds. To average
these readings and log the mean each minute, use the up or down arrow to scroll through the
menu until the display reads "store= MEAN", then press "ENTER."
11. LI-COR will prompt, "min/max= ". To log the minimum and maximum readings for each sensor,
scroll through the menu until the display reads "min/max= YES", and press "ENTER."
12. LI-COR will prompt, "time stamp= ". Use the up or down arrow to scroll through the menu until
the display reads "time stamp= NO", then press "ENTER."
13. Channel 1 is now programmed. The LI-COR will now prompt, "ch2 is ". Return to step 3
above and repeat the procedure for channel 2. All entries will be the same as for channel 1 except
the multiplier. Since channel 2 is always used with Sensor B (shaded ambient, or black disk
sensor), use the calibration multiplier for that sensor when programming channel 2.
14. Upon completion of configuration of channel 2, the LI-COR will go on to channel 3, then 4, up
through 8, followed by channels A, B, and M. Turn all of these channels OFF at step 3.
15. After turning OFF channel M, the datalogger will automatically exit the configuration mode. The
display will read "1M O.OUM" or something similar. The precise display depends on whether or not
there are data points in memory.
It will be necessary to define date and hex number prompts. Press the "FCT ON" key to bring up a list
of auxiliary functions.
16. Using the up or down arrow, scroll through the menu until the display reads, "FCT:Def Prompts",
then press "ENTER."
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 7 of 18
17. LI-COR will display "PROMPT1: ". Using the up and down arrows in conjunction with the
' numbered keys as before, "1, 4, T, 7, i, 6, T, 1," to display DATE. Press "ENTER" when ready.
18. LI-COR will display "PROMPT2: ". Press "-1, 0, t, 1, I, --," to display HEX. Press "ENTER"
when ready.
19. LI-COR will display "PROMPTS: ". Third prompt is not used, therefore press "ENTER."
20. The display now reads "FCT:Def Prompts". Press the "FCT ON" key to exit the list of auxiliary
functions, returning to the "1M O.OUM" display. The second field in this display, "M", indicates the
LI-COR is in LOG mode.
The basic programming for the LI-COR LI-1000 datalogger is now complete. Daily programming and
logging may proceed; otherwise, save memory space and batteries by placing the datalogger in
INSTantaneous mode and turning it off (the LI-COR never sleeps when in LOG mode).
21. Press the "CFG" key to enter configuration mode. LI-COR will display "mode is LOG".
22. Press either the up or down arrow so the display reads "mode is INST", and press "ENTER."
23. Display should read "ch1 is LIGHT". Press the "CFG" key to exit configuration mode.
24. Display should read "11 O.OUM". The second field in this display, "I", indicates that the datalogger
is in INSTantaneous mode. Press the "OFF" key to shut the machine down.
In summary form, here are the settings to select from the configuration menus:
mode =
ch1 =
range =
mutt =
label =
per =
reset =
thr =
store =
min/max =
time stamp =
LOG
LIGHT
A
SPECIFIC NO. FOR EACH QUANTUM SENSOR
UM
1
1100
00.00
MEAN
YES
NO
4.5 Quality Control
The regional PAR trainer/auditor will visit the field crew and conduct a field audit of at least one (1) plot
per crew early in the season. The auditor will take independent measurements on all four subplots of each
site immediately after the field crew to check the crew methodology and the data quality. The PAR auditor
will then review PAR data downloading procedures and data files for the day and storage of PAR data files
to date. This duplicate procedure provides an estimate of the reproducibility of PAR measurements. The
data collected by the PAR auditor will be kept separate from the field data. The PAR auditor will also work
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 8 of 18
with the field crew on any logistical problems, such as ensuring the ambient station readings are taken for
the full measurement period.
4.5.1 Data Quality
Sources of error include incorrect calibration, incorrect instrument operation, incorrect location of
sample stations, failure to position shade disk properly, and asynchrony of time among instruments. These
errors can be minimized by training and adhering to standard procedures.
Data completeness is the most important data quality concern. The most common reason for
incomplete data is failure to store the average ceptometer readings. The operator must give careful
attention to the sequence of ceptometer buttons to push, and ensure that the desired operation has
occurred as each button is pushed. In cases where PAR points are visited out of order, it is essential to
include a note in the comment section.
The following table serves as a reference in the field to help ensure that the ceptometer data are
complete.
Ceptometer reading expected
Sample locations after storing a value.
Subplot 1 (7 sample points) 1, 2 7
Subplot 2 (7 sample points) 8, 9, .... 14
Subplot 3 (7 sample points) 15, 16, ..., 21
Subplot 4 (7 sample points) 22, 23 28
4.5.2 Method Performance
Method performance is excellent except on rainy days. Crews should be aware that they may add an
hour to sampling window, if necessary, on rainy days. Performance depends upon the crew's thoroughness
and adherence to the methods. There are very few equipment concerns and data completeness is usually
above 85%.
4.6 Procedures
4.6.1 Sample Collection
PAR measurements are taken simultaneously at the plot and at the "ambient station." The ambient
station is set up in the morning and allowed to run all day. Ceptometer measurements are made during
the sampling window (12:00 to 2:00 daylight time). It usually takes about 45 minutes to collect the
ceptometer measurements for an entire plot. Since all measurements are time stamped, ambient station
data and ceptometer data can be matched up later for analysis.
A single ambient station with two quantum sensors is needed. Locate the station in an open area that
is free from shade and as near to the FHM plot as possible. Preferably, the area is located in a large
clearing, but a roadway is allowed if it is sufficiently wide enough that shadows do not fall on the quantum
sensors. In some situations, you may need to use large gaps in the forest canopy itself. If the unshaded
area at the ambient station is less than 10 m x 10 m (30 ft x 30 ft), make a note in the comment section
on the portable computer after downloading the ceptometer data. Quantum sensor "B" will be shaded to
collect diffuse (indirect) PAR, while unshaded sensor "A" collects all incoming PAR to the site. The ambient
station should be run continuously for the entire work day.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 9 of 18
Under-canopy sampling points are the subplot locations where PAR is measured with the ceptometer.
A grid of seven PAR points will be sampled at each of the four subplots (Figure 4-1). The subplot grid will
be flagged with temporary flags during plot establishment by either the foresters or the PAR person. The
subplot grid helps all crew members by delineating the subplot boundaries. Use of temporary flags also
ensures that QA samples are taken at the same locations within the stand; QA measurements will be taken
immediately after initial sampling on audit days.
4.6.1.1 Timing of Measurements
Because measured PAR depends on sun angle, it is critical that the ceptometer procedures be
performed between 12:00 and 2:00 (daylight time). Usually this will require less than one hour. If the
starting time is delayed, PAR should be taken anyway as long as samples can be collected before 3:00
p.m. (daylight time). Note this discrepancy in the comments file when downloading. All measurements
should be taken on the same day.
4.6.1.2 Weather Considerations
1. Do not take measurements in steady rain.
2. If rain causes sampling to be delayed, go ahead and collect PAR measurements until 3:00. Skip
the PAR procedures entirely if no measurements can be taken until after 3:00 p.m. because of rain.
Take measurements early if necessary to beat an approaching storm, but never sample earlier than
11:00 a.m. (daylight time). In other words, you may stretch the sampling window by an hour in
either direction if necessary, yet be sure to record this in the comments section when downloading.
3. If rain starts after sampling has begun, keep the ceptometer dry until rain stops. Dry off the
ambient station quantum sensors, then resume sampling.
4. On rain-interrupted days, cease sampling by 3:00 p.m. at the latest, even if all samples have not
been collected.
5. Always download any data that have been collected, even on rainy days when only a partial
sample can be obtained. Clear the memory (see step 2 of 4.6.3.4) to clear ceptometer for the next
day's sample.
6. Measurements can be taken regardless of cloud conditions.
4.6.2 Ceptometer - Basic Operation
The following procedures are performed as part of ceptometer operation:
1. Clean the white surface of the probe with alcohol (see Section 4.6.4).
2. Set time of day: Select Function 6 on the ceptometer. Button A sets the hour and button B sets
the minute. Synchronize with ambient datalogger time clock and field crew timepiece (wristwatch).
3. Activate the ceptometer by pressing the function key; it deactivates automatically (without memory
loss) after a 7-minute time-out period. Select function 1, PAR.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 10 of 18
4. Hold the Ceptometer level to the ground during operation (use bubble level on display panel) with
arms outstretched, at waist height. Avoid shading the probe with the body.
Different measurements may be made with the ceptometer. By pressing the function key, one of eight
functions can be selected. The selected function is indicated by a small arrow pointing to the function
number above the display. Use function 1 for PAR sampling.
4.6.3 Daily Operations
4.6.3.1 Ambient Measurements
When the crew reaches the plot location, use the following procedure to position the black disk so that
sensor B will be shaded during the 12:00 to 2:00 sampling window. The black disk provides 2 hours and
20 minutes of shade for sensor B.
1. Locate the ambient station in an open area as near as possible to the plot (preferably within
400 m). The sensors have a 45° range of view so the ambient station should be at least one tree
height away from surrounding trees, if possible.
2. Set up the tripod. Use rubber tips or spikes as needed, lift center column to 1 meter height. If on
steep ground, shorten the uphill leg so center column is approximately vertical.
3. Attach platform to the tripod, and place quantum sensors A and B on the platform. Sensor A
measures full sun, and sensor B measures shaded light. Each sensor has a specific calibration
multiplier. Do not interchange sensors.
4. Determine the sun zenith angle at solar noon, p, which is the angle of the sun from vertical:
P= L - D
L is the latitude of the plot, and
D is the solar declination.
L, the latitude of the plot, is contained within the hex number. The first two digits of the hex
number represent the latitude of the plot in degrees.
D, the solar declination, varies with the day of year and is listed in Figure 4-2.
Example: Plot number 4709464 on July 1st.
L = 47 (the first two digits of the hex number)
D = 23 (from the Solar Declination table)
P = 47 - 23 = 24 degrees.
5. Use protractor and 6-inch ruler to set the black disk at p degrees from vertical. A 5° error is
acceptable. The disk should be 15 cm (6 inches) above the sensor. See Figure 4-3.
6. Level the platform using tripod controls. Place compass adjacent to platform and rotate platform
until the full ambient end points clue south (true south - add or subtract magnetic declination as
needed). Use caution; each degree of rotation moves the shade window by about 3 minutes.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 11 of 18
May
Jura
July
August
Ssptorriber
May
June
July
Auguit
Stpfeirtor
16
Day of Month
6789
10 11
12
13 14
17 18 19 20
Day of Month
21 22 23
24 25 26 27 28
15
15
22
23
18
9
15
22
23
18
8
15
22
23
18
8
16
22
23
18
8
16
22
23
17
7
16
23
23
17
7
17
23
23
17
6
17
23
23
16
6
17
23
22
16
6
17
23
22
16
5
18
23
22
16
5
18
23
22
15
5
18
23
22
15
4
18
23
22
15
4
19
23
22
14
3
30 31
19
23
22
14
3
19
23
21
14
3
19
23
21
13
2
20
23
21
13
2
20
23
21
13
1
20
23
21
12
1
20
23
20
12
1
20
23
20
12
0
21
23
20
11
0
21
23
20
11
0
21
23
20
11
-1
21
23
19
10
-1
21
23
19
10
-2
21
23
19
10
-2
22
23
19
9
-2
22
19
9
Figure 4-2 Solar declination (D) In degrees.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 12 of 18
True
South
Figure 4-3 Ambient station setup. Sensor A measures full sun. Sensor B is shaded by the black disk. By adjusting
angle p according to plot latitude and day of year, and aligning platform to true south (plus or minus a small longitude
correction), sensor B will be shaded during the sampling window.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 13 of 18
7. Correct for current position within time zone. Time zones are centered on 15-degree meridians
(eastern = 75, central = 90, mountain = 105, pacific = 120). The sun will be directly over the
central meridian at noon (1:00 daylight time); current position may be a few degrees east or west,
therefore, a correction must be made so that the shadow cast by the black disk will correspond with
local time.
The longitude of the plot is contained within the hex number: digits 3 through 5 represent the longitude
of the plot. Find the difference in degrees between plot longitude and central meridian. Multiply this
difference by 1.5. Rotate the platform by this amount so that the south end moves toward central meridian.
Example: Hex number 4709464.
Longitude: 094 (digits 3 - 5 of hex number)
Central meridian: 90 (Central time zone)
Difference: 94 - 90 = 4 degrees
Correction required: 4 x 1.5 = 6 degrees
Since the central meridian is east of the plot (longitudes increase from east to west), rotate the south
end of the sensor mounting platform 6 degrees to the east. This will position the shade disk so that the
shadow will run on local time.
8. Stand behind the setup and recheck the azimuth from a distance to make sure the compass was
not affected by metal. Tighten tripod controls. Make sure each sensor is level.
9. Perform daily programming of the datalogger (Section 4.6.3.2). When complete, place datalogger
inside its shelter.
The ambient station may now be left unattended for the rest of the day.
In most cases, the longitude correction will be provided ahead of time by the regional PAR coordinator.
Provided will be the "target azimuth" for each plot which incorporates both magnetic declination and the
time zone correction.
4.6.3.2 Daily Programming of the Ambient Station Datalogger
Each day you need to synchronize the datalogger with your wristwatch, enter the date and hex number
and put the datalogger in LOG mode. (You will have taken it out of LOG mode the previous afternoon in
order to power down.) Here are the steps to follow to prepare the LI-COR for the day's logging.
1. Press "FCT ON" to turn on the LI-COR. The display will first read "LI1000.02.02" and then will
display numbers like "11 O.OUM." The specific display depends on data stored in memory.
2. Press the "TIME" key. The date will be displayed, followed by "YYMMDD". If the date is correct,
press "ENTER." Otherwise, use the numbered keys to enter the correct date in year-month-day
format (the left arrow key will undo mistakes) and press "ENTER."
3. LI-COR will display the time of day, followed by "HHMM." Adjust to match your watch using the
numbered keys (hours-minutes, 24 hour clock), and press "ENTER".
4. LI-COR will display numbers and letters as in step 1, for instance, "11 O.OUM".
5. Press "FCT ON" a second time to bring up a list of auxiliary functions. Using the up or down
arrow, scroll through the menu until the display reads, "FCT:Log Remarks".
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 14 of 18
6. Press "ENTER." The LI-COR will read "LOG REMARKS," then it will prompt, "DATE :940721."
The date shown will be the last day you did PAR. Use numbered keys to enter today's date using
year-month-day format. The left arrow will erase mistakes. Press "ENTER" when ready.
7. LI-COR will prompt "HEX :3712061." The hex shown will be the last one on which PAR data was
collected. Use the numbered keys to enter today's hex number, and press "ENTER."
8. LI-COR will prompt" : " We don't use the third remark, so press "ENTER." The display will
now read "FCT:Log Remarks."
9. Press the "FCT ON" key to exit the list of auxiliary functions, returning to "11 O.OUM."
10. Press "CFG" to enter the configuration mode. LI-COR will prompt "mode is INST."
11. Use the up or down arrow to make the display read "mode is LOG", and press "ENTER."
12. Display will read "ch1 is LIGHT." Press "CFG" to exit configuration mode. Now the display shows
a data point like "1M O.OUM." (The exact numbers will vary with light levels.) When in LOG mode,
the "M" in the second field, following the "1."
The datalogger is now reading channels 1 and 2 every five seconds and averaging the readings every
minute. At the programmed time (11:00 a.m.), readings will be stored in memory. Until that time, the
datalogger will measure but not record data. NOTE: If you set up the ambient station after 11:00 a.m.,
the datalogger will measure but not record data until the following morning!
To prevent this from happening, put the datalogger into LOG mode before 11:00 a.m., even if you are
not yet on site. If you put the LI-COR into LOG mode while en route to the plot, it will begin logging at
11:00 a.m., even though the quantum sensors are not attached. When you get to the plot, attach the
quantum sensors and proceed as usual.
If you still miss the 11:00 a.m. deadline, you will need to reprogram the LI-COR to begin logging at a
later time. Follow the instructions in Section 4.4.3, except the time to enter at the "reset= HHMM"
prompt should be the present time, plus 5 or 10 minutes to allow for reprogramming.
For example, you have missed 11:00 a.m. start and realize at 11:30 that the LI-COR is still in INST
mode. If you put it in LOG mode now, it will not record data until tomorrow morning. You need to
reprogram the datalogger to begin logging at 11:40 a.m. The other menu selections will all remain the
same, therefore enter "ENTER" at each prompt. When prompted for "reset= HHMM", enter "1140". This
will need to be repeated for both channel 1 and channel 2. (Remember afterwards to change the reset
time for both channels back to 11:00 a.m. prior to the next day's plot.)
4.6.3.3 PAR Grid Establishment
It is easiest to establish the PAR grid at each subplot during initial plot layout (see Figure 4-1). Be
careful of the microplots and the vegetation structure quadrants to avoid trampling or disturbing vegetation.
In many cases, the foresters will establish the PAR plot.
1. Locate center point of subplot 1 and flag. Stake the measuring tape at subplot center.
2. With the compass located over the center point, establish point 2 (as numbered in Figure 4-1) by
heading 30° azimuth for a distance of 7.3 m (24 feet) horizontal. Mark this point with a flag the
same color as used at subplot center (e.g., yellow).
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 15 of 18
3. Establish points 3, 4, 5, 6, and 7 by heading 7.3 m (24 feet) horizontal from the subplot center at
azimuth bearings 90°, 150°, 210°, 270°, and 330°, respectively. Marking these points with flags
of contrasting color (e.g., pink) makes it easier to keep track of position.
4. Repeat these steps on subplots 2, 3, and 4.
At each subplot, the subplot center and the PAR grid point at 30° will be flagged in one color while the
remaining points will be flagged with another color.
4.6.3.4 Under-Canopy Measurements
1. Clean the ceptometer probe by rubbing the white surface with a soft cloth dipped in alcohol.
2. Clear memory on ceptometer. Select Function 8, hold down button A and press Button B. The
display will indicate "POOOO" (meaning: the number of averages that are currently stored in memory
is zero).
3. Check time of day by selecting Function 6. Adjust if necessary to match your watch. The "A" key
changes hours, the "B" key changes minutes. The ceptometer has a 24-hour clock, therefore 1:00
p.m. is 1300.
4. Prepare for sampling. Select Function 1. The display indicates PAR on the right side and sample
number of the left side of the display. The PAR number will change as the ceptometer is moved.
5. At PAR point 1, the first under-canopy sampling location, perform the following procedure:
(a) Stand over the sample point with the ceptometer at waist height. Arms should be extended
so that the body will not shade the sensors. Hold the ceptometer level. Press button A and
hold down while turning in a circle. The ceptometer will take 4 samples per second while the
A key is held down. If the turn is obstructed, release button A temporarily, move past the
obstruction (e.g., shrub), and press button A again to complete the turn. When complete,
release the A key. The ceptometer will display the number of readings taken at the left and
the last PAR reading on the right. Collect 30 or more readings at each grid point. When
"stabbing" in heavy underbrush, attempt to distribute the readings evenly around the full circle.
(b) Press button B to display average.
(c) Press button B again to store the average. The ceptometer will display "P00001" to indicate
that 1 reading has been stored in memory. Make sure that the number of readings stored in
memory corresponds with the PAR point just sampled! Proceeding to the next point and
pressing A before saving the average will erase the data.
(d) After making sure that the average has been saved, press button A once to clear
readings and reset the sample counter.
6. Move to the next under-canopy sampling point on subplot 1 in sequence.
7. Repeat steps 5 and 6 until all 7 sampling points on subplot 1 have been sampled. IMPORTANT:
After all of the 7 points on a subplot have been sampled, make sure that the record count is
correct. If the record count is not correct, make a note in the notebook. Then enter these notes
in the comment field when downloading the data in step 1 of Section 4.6.3.6. The following format
should be used (for example): "After completing subplot 2, ceptometer only had 13 records." Do
not attempt to erase data or to add missing data.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 16 of 18
8. Repeat: Steps 5-7 at subplots 2, 3, and 4 in sequence. When finished, return ceptometer to
carrying case.
4.6.3.5 Deactivate Ambient Station
At the end of the work day, return to the ambient station. End the recording session by putting the
datalogger into the INSTantaneous mode:
1. Press "FCT ON." LI-COR will display "1 Ml O.OUM."
2. Press "CFG" to enter configuration mode. LI-COR will display "mode is LOG."
3. Use up or down arrow to scroll display to "mode is INST," and press "ENTER."
4. Press "CFG" to exit configuration mode. LI-COR will display "11 O.OUM."
5. Press "OFF" to shut down the LI-COR. Data in memory is safe.
4.6.3.6 Downloading Data
1. To download the data from the ceptometer and the datalogger to a microcomputer (PC), complete
these procedures following the prompts from the PC.
(a) Press F2 to select "PAR Services" from the main menu.
(b) Press F1 to activate the ceptometer download procedure on the PC menu.
(c) Connect the interface cable between the PC and ceptometer.
(d) Follow PC prompts to enter state, hex number, plot ID, QA status, crew type, and sky
conditions. "F1" is a help key that accesses menu choices for each of these entries. Choices
for sky conditions are full sunshine, few clouds, many clouds, or overcast.
(e) Select function 8 on the ceptometer.
(f) Press button B to send the accumulated values to the PC. The display will count the records
as they are sent. When the PC requests a second transfer, press button B again.
(g) If both transfers match byte for byte, the PC will prompt you to enter comments about the plot.
Type in all comments written in the pocket notebook. Any information concerning weather, plot
conditions (e.g. brushiness or steepness), missed or out of order data points, etc., should be
included. Note the forest type. Press ESC when finished with comments.
(h) Use any key to return to the main menu.
2. Download the LI-1000 Datalogger.
(a) Press F2 to select "PAR Services" from the main menu.
(b) Press F2 again to call up the datalogger dump program.
(c) Read the message about hex numbers and press any key. A box is displayed showing
information about the software.
(d) Press any key. The top 2/3 of the screen is now blank, and the bottom 1/3 lists various
function key assignments.
(e) Securely connect the proper cables between the PC and the LI-1000 datalogger.
(f) On the PC, press the F1 key, then the I key, highlight "LI-1000, Li-1200 Datalogger".
Press Return key.
(g) On the PC, to name the file, press F6. Type in the 7-digit hex number followed by the 1-
digit plot number, and press Return.
(h) On the datalogger, press FCT/ON.
(i) On the datalogger, press OUT.
(j) On the datalogger, use up/down arrows to select the baud rate of 48 and press ENTER.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 17 of 18
(k) On the datalogger, select H for horizontal format. Display will read "form=H". Press
ENTER.
(I) On the datalogger, the next display will be "len = ". Enter the number 80. Press ENTER.
(m) On the datalogger, the next question is "dump all = yes", toggle answer and press ENTER.
The display will show "dumping". The data dump can be aborted by pressing the OUT key
again. When the data dump is complete, the display will read 11 XX.XXUM.
(n) On the PC, press Alt-X to exit the program.
(o) Check the PC or disk directory to make sure the transfer was successful. An 8-hour data
file will be approximately 24000 bytes.
(p) Follow the PC instructions to make a backup copy of the file.
To clear the memory for the next plot's data:
3. Press "FCT ON" to enter the list of auxiliary functions. LI-COR will display "FCT:Log Remarks."
4. Use the up or down arrow to scroll display until it reads "FCT:Clear Ram," and press "ENTER."
5. Display reads "OK Clear Mem NO." Scroll to YES and press "ENTER." The datalogger
memory is now cleared.
6. Press "FCT ON" to exit the auxiliary functions. Display reads "11 O.OUM."
7. Press "OFF" to shut down the LI-COR.
4.5.4 Preventative Maintenance
1. Always keep the white surface of the ceptometer probe clean to assure accurate readings. To
clean the probe, use alcohol and a soft cloth. Rub the surface until it appears clean.
2. Change batteries (see User's Manual) prior to the field season and whenever the display indicates
"LO" when the ceptometer is activated. Field calibration is required after batteries are changed.
3. Always transport the ceptometer in the protective carrying case. Shield the ceptometer from shock
damage by securing it to some part of the vehicle during travel to and from plot locations.
4. The ceptometer is a fragile and expensive electronic instrument. Never use it as a tool for anything
other than the designed purpose. Protect the probe from shock damage by avoiding impact with
trees while moving from location to location.
5. Keep the ceptometer dry and in the carrying case when not in use. It is neither water-proof nor
water-resistant. Bring the ceptometer into the hotel at night to prevent heat damage and theft.
6. Use only water to clean the quantum sensors. Keep them in a carrying case while transporting
them from location to location. Keep the datalogger in a cool place, out of the sun when it is not
in use. Also, bring the quantum sensors and the datalogger into the hotel when not in use.
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EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 18 of 18
4.7 References
Decagon Devices, Inc. 1991. Application note: canopy leaf area index from sunfleck ceptometer PAR
measurements. Decagon Devices, Inc., Pullman, Washington, 3 pp.
Decagon Devices, Inc. 1989. Sunfleck ceptometer user's manual. Decagon Devices Inc Pullman WA
28 p.
Norman, J. and G. Campbell. 1989. Canopy structure. In: Pearcy, R., J. Ehleringer, H. Mooney, and P.
Rundel, eds. 1989. Plant Physiological Ecology. Chapman and Hall, London, p. 301-325.
Waring, R.H. and W.H. Schlesinger. 1985. Forest ecosystems: concepts and management. Academic
Press, Orlando, FL.
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 1 of 12
Section 5. Vegetation Structure
Section/Title
5.1 Overview 2 of 12
5.1.1 Scope and Application 2 of 12
5.1.2 Summary of Method 2 of 12
5.1.3 Interferences 2 of 12
5.1.4 Safety 3 of 12
5.2 Plant Sample Collection and Handling 3 of 12
5.3 Equipment and Supplies 5 of 12
5.4 Calibration and Standardization 5 of 12
5.5 Quality Assurance 5 of 12
5.5.1 Training 5 of 12
5.5.2 Measurement Quality Objectives (MQOs) 6 of 12
5.5.3 Collection of Quality Control Data 6 of 12
5.5.3.1 Remeasurements and Audits 6 of 12
5.5.3.2 Calculation of Achieved Data Quality 6 of 12
5.5.4 Method Performance 6 of 12
5.6 Procedure 6 of 12
5.6.1 Overview 6 of 12
5.6.2 Quadrat Layout 6 of 12
5.6.3 Vegetation Structure Measurements 7 of 12
5.6.4 Documentation of Plot Conditions 11 of 12
5.7 References 12 of 12
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 2 of 12
5.1 Overview
5.1.1 Scope and Application
The vegetation structure indicator provides information on species composition, relative amounts of
cover, and spatial distribution of vascular plants in the forests. Further, it quantifies habitat structure, which
strongly influences wildlife diversity (DeGraaf and Rudis, 1983). Plants are one of the many taxa (e.g.,
arthropods, vertebrates, nematodes) that should be measured in order to fully assess forest biodiversity
on a regional scale. Vegetation structure complements other indicators, particularly PAR, wildlife habitat,
crown condition, growth, regeneration, mortality, and species diversity.
5.1.2 Summary of Method
Vegetation measurements are taken in small permanent 1 m* quadrats that are systematically laid out
on each subplot (3 per subplot or 12 per plot). On each quadrat, three basic types of data are recorded:
(1) plant species identification, (2) height class(es) (stratum or strata) at which each species occurs, and
(3) plant canopy cover. Collect data by stratum. There are four strata, defined below. Start at the lowest
stratum and work up, using the quadrat frame and height pole to define the sampling area. Specimens
of all plants present in the quadrats that cannot be confidently identified to the species level should be
collected off-plot, labelled, pressed, and submitted for subsequent identification. Record all data on the
appropriate screen on the portable data recorder (PDR). The PDR data file for each plot should be closed
before leaving the field and later that day downloaded to the field crew's laptop computer for transmission
to the central data base.
5.1.3 Interferences
Several uncontrollable environmental and site conditions have hindered or slowed vegetation structure
measurements, including (1) poor weather conditions such as gusting wind, heavy rain, and dark overcast
skies; (2) steep and/or unstable slopes; (3) dense and diverse understory vegetation; (4) the phenological
and/or maturity stage of plant(s); and (5) thick vegetation immediately overhead that obscured the view of
the taller vegetation. Follow these guidelines to reduce the effects of interferences on proper data
collection:
1. Suspend data collection under severe weather conditions, such as strong winds and heavy rainfall.
2. In areas with thick vegetation, each side of the collapsible quadrat frame should be slid carefully
through the vegetation separately and then attached at comers. The frame should be completely
assembled and the height pole in place before vegetation measurements begin; all vegetation should
hang freely and naturally about the frame and pole. First, record the cover of taller and/or abundant
species in each layer before searching for shorter or obscure species growing below them. See
Subsection 5.6.4 for additional details.
3. On steep and/or unstable slopes, avoid the area immediately upslope from the quadrat sampling area.
Stand below or to the side of the sampling frame to avoid falling or sliding into the sampling area and
disturbing the vegetation and ground surface. Next, level the quadrat frame, and proceed with
measurements.
4. Immature plants or plants not flowering or fruiting have affected the level and accuracy of identification.
In addition, plants either expanding or dying back have hindered both identifications and canopy cover
estimates. For either situation, collect the most complete plant specimen that is possible and
appropriate, including roots, stem and leaves, and fruit, seeds, or cones. If the plant sample is dry and
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 3 of 12
brittle, soak it in water before pressing. See Subsection 5.2 for additional details. Meanwhile, the
canopy cover of each plant species should be estimated as it exists at the time of sampling, ignoring
whether it is expanding or dying.
5. When thick vegetation is immediately overhead, the height pole should be leveled and raised through
the vegetation as necessary to provide a reference for estimating the cover of taller vegetation covering
the quadrat.
5.1.4 Safety
No specialized safety precautions are necessary. Follow general safety precautions for conducting
fieldwork (see Appendix E).
5.2 Plant Sample Collection and Handling
Plant specimens should be collected in the field for three reasons: 1) to obtain the most accurate
taxonomic identification (FHM is concerned with basic biodiversity elements, including species, varieties
and subspecies, endemics, exotics, and threatened and rare plants); 2) to obtain a quality assurance check
of field identifications (FHM is providing policy-relevant information so the level of uncertainty must be
known); and 3) to secure a permanent record of the plants sampled (FHM is a long-term program so
activities and data bases must be thoroughly documented).
Specimens of all plants present in the quadrats that cannot be confidently identified to species should
be collected off-plot, labeled, pressed, and dried for shipping and subsequent identification by the field
botanist or a cooperating herbarium. Field specimens permit field identifications to be confirmed, corrected,
or improved (e.g., from genus only to species). Subsequently, field specimens will serve as documentation
of the presence of the species on a plot and as a permanent record of the identity of the sampled plant.
Follow these guidelines when collecting plants and handling specimens for identification:
1. Each botanist should record his/her most accurate taxonomic field identification for each vascular plant
encountered. However, a specimen of each unique plant should be collected for identification and/or
verification except when the plant in question is common or abundant, widespread, and well-known
(i.e., 'its species identity is known with complete confidence). Most tree and some shrub species fit this
exception. However, many herbaceous species do not.
2. Supply as complete as specimen as possible. Do not "top" or "end snatch" plants. Underground parts
should be collected for complete identification (e.g., bulbs of Allium or rhizomes of perennial grasses).
Fruit should be collected, especially for oaks and pines.
3. Collected plant specimens should be stored temporarily in either (1) large, scalable plastic bags held
in a 3-ring binder or (2) a magazine or stack of newspapers until field work is completed. Large
specimens should be bent or broken along the stem to fit in the bags or papers. Brittle specimens
should be wetted with water to prevent or lessen breakage of leaves and fruits. Separate nuts, fruits,
or cones should be placed in the same bag if possible. Otherwise, the nuts or cones can be labeled
identically and stored separately. High heat and humidity will damage specimens stored in plastic
bags.
4. Complete a label with the appropriate number for each specimen (Figure 5-1). This provides a unique
reference code of plot number, subplot number, quadrat number and the plant identification number
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 4 of 12
entered in the PDR (i.e., field 1 in Figure 5-2). This code will be used to match the specimen with the
correct data line in the PDR. Remove the sticky back from the label. Attach the label directly to the
stem of the specimen so that the information on the label is clearly visible.
5. After the field work has been completed on the plot, plant specimens should be removed from the
plastic bags or magazines and arranged on dry, folded newsprint for pressing and drying. As the two
presses fill up with fresh specimens, the drier plants should be moved to the storage box for
subsequent mailing. More detailed instructions for pressing plants will be given at the training sessions
prior to the beginning of the field season.
6. Pressed plant specimens should be mailed regularly to the plant taxonomist for identification or
verification. Packages should be mailed weekly or after specimens from 3 plots have accumulated.
Additional written guidelines for plant sampling and handling based on Radford et al. (1974) and
Walters and Keil (1988) will be supplied at training, along with instruction.
00000
HEX NO.
DATE
HABITAT
00000
HEX NO.
DATE
HABITAT
00000
STATE
COUNTY
DATE
HABITAT
Figure 5-1. Plant specimen label used for vegetation structure indicator.
Subplot 1
Trample: _
Quadrant 1
FIA Condition:
Dominant mircohabitat
Start: Stop:
Sub/Spc
ST CC
Enter Trample Code
Figure 5-2. Portable data recorder screen.
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 5 of 12
5.3 Equipment and Supplies
The equipment needed to measure vegetation structure includes:
• Loggers tape and hand compass for quadrat layout
• Hammer; long, thick plastic tent stakes to monument quadrat locations for relocation; and quiver
to hold stakes
• One collapsible, plastic pipe, quadrat sampling frames (1 m )
• Short (5-6 m/16-20 ft), telescoping height pole (equipped with leveling device and pointed foot
attachment to securely set pole vertically) for measuring upper strata heights, the location of tall
overhanging vegetation, and the heights of tall shrubs
• 15x hand lens, binoculars, metric ruler, and regional/local plant taxonomy handbooks to aid in plant
species identification
• Portable data recorder with two extra batteries; backup supply of field sheets
• Three-ring binder and large plastic bags for holding plant specimens collected in the field, pre-
printed waterproof labels, and indelible ink pens or magazines
• Two plant press frames (ca. 12x18 inch or 30 x 50 cm), with corrugated cardboard sheets (50),
blotter paper sheets (200), newspapers (200 pages), small paper bags (50) for pressing and drying
field specimens, and four (4), 1-inch wide binder straps
• Sturdy box (ca. 12x18 inch or 30 x 50 cm) for storing, transporting, and shipping dried plant
specimens removed from the plant press
• Cruiser vest
• Internal frame backpack
• Hand trowel
• Pocket knife
• Snake leggings, gloves, insect and tick repellent
• Bee sting and snake bite antidotes
• Quadrat levelers
5.4 Calibration and Standardization
Purchase tapes to required specifications. Tapes should be maintained in working order and do not
need calibration. Check the compass regularly against known directions. In the field, avoid magnetic
interference. Use the compass without correction for declination (magnetic north).
5.5 Quality Assurance
5.5.1 Training
Indicator leads direct training of botanists. Trainers should meet during a pretraining session to
troubleshoot methods and refine the written protocols. These meetings should be in conditions similar to
field settings, (i.e., similar forest types and equipment). Follow pretraining with a training session for the
field teams.
During the training session, trainers will test the botanists for comparability after complete training of
the vegetation structure protocol. The test should consist of a series of on-plot and between-plot
remeasurements and calculations of method precision. Use estimates of method precision in the field as
quidelines for data acceptability. The botanists will also be trained and tested on plant identifications skills
using specimens collected from last year's plots. In order to be certified, botanists must perform at or
above a specified level of accuracy on test plots. Certification is discussed in greater detail in FHM Quality
Assurance Plan (Stapanian and Cline, 1994).
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 6 of 12
5.5.2 Measurement Quality Objectives (MQOs)
For the training session, the MQOs are as follows:
1. Difference in total number of species per plot: not to exceed + 10%.
2. Plant community similarity: > 75%.
3. Absolute difference in abundance of each plant species (cover):
Strata 3 & 4:+ 15%
Strata 1 &2: +10%.
These MQOs are not based on data previously collected, therefore, revisions are quite likely. Use data
from the remeasurement program of the training session to estimate measurement quality objectives for
the field work.
5.5.3 Collection of Quality Control Data
5.5.3.1 Remeasurements and Audits
The entire crew should also remeasure predetermined "quality control" plots during the field season
(preseason [training], mid-season, and post-season [debriefing]). These remeasurements can be used to
estimate variation due to measurement error and season. In addition, botanists will be audited in the field
at least once in order to minimize errors in procedure.
5.5.3.2 Calculation of Achieved Data Quality
Quality control data should be analyzed and reported as a component of the overall population
variation. Variation should be assessed from control charts of quantitative measurements and frequency
distributions of qualitative measurements.
5.5.4 Method Performance
Method performance will be determined through analyses of quality control data collected during the
field season. A series of reference plots will be visited by the crew several times during the year to
estimate bias, within-and between-crew variation, and within-year variation.
5.6 Procedure
5.6.1 Overview
For the vegetation structure measurements, the sequence of activities at each subplot is: (1) establish
sample locations for quadrats (Figure 5-3), (2) measure vegetation within each quadrat, and (3) photograph
the subplot to document conditions.
5.6.2 Quadrat Layout
The first step is to define the sample areas for the vegetation measurements. Quadrats are established
15 ft (4.57 m) from each subplot center along 30° (no. 1), 150° (no. 2), and 270° (no. 3) azimuths (Figure
5-3).
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 7 of 12
Figure 5-3. Layout of quadrats on each subplot. Quadrats are 1 m2 and subplot 168 m2 drawn to scale.
1. Site the 30° azimuth and measure and mark 15- and 18.28-ft (4.57- and 5.57-m) horizontal distances.
2. Mark the two distances permanently with long, heavy, plastic tent stakes to serve as reference corners
for remeasurement of the quadrat. o
3. Place one side of the sample frame directly on or next to these stakes, since the azimuth line defines
the left edge of the sampling area.
4. Assemble and level the other sides of the quadrat frame to define the horizontal sample area (Figure
5-4).
5. Set the telescoping height pole vertically in the ground at or near the center of the plot to aid definition
of the vertical sample areas and determination of "in or out" plant cover in higher strata (Figure 5-4).
6. Make the vegetation measurements as described in 5.6.3.
7. Repeat steps 1 -6 for quadrat layout and vegetation measurements for quadrats 2 and 3 on the subplot.
8. Repeat steps 1-7 for subplots 2-4.
5.6.3 Vegetation Structure Measurements
Measure vegetation structure immediately after you establish a quadrat. The objectives of the
procedure are 1) to identify all plant species present within each sample quadrats, and 2) to measure
the amount to their canopy cover both individually and collectively.
Record the following header information for each quadrat: subplot no., quadrat no., disturbance
("trample") code (see Table 5-1 a for codes and definitions), FIA condition code (from FIA crew leader),
dominant microhab'rtat (Table 5-1b), start time and stop time (from PDR internal clock).
(NOTE: Enter the data for each quadrat on a separate PDR screen (Figure 5-2). The PDR quadrat screen
has 40 columns and 16 rows visible at once and scrolls up and down line by line after the 16th row. This
setup allows the field botanist to see all or most of the previous entries made on the quadrat. The stop
time is the last item recorded for the quadrat; the program returns to this item after all vegetation data are
recorded and it must be filled in to exit and begin the next quadrat.)
1.
2.
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 8 of 12
a.
Inside dimensions 1 m x 1 m
Ignore overlap of
same species
Add individual
polygons to determine
total for species
Count overlap of
plant and substrate
separately
Count overlap
of two different
species separately
Count overlap of two
different substrates separately
1/2" - 3/4" Plastic pipe
(thick-walled) divided
into 10-cm segments
using black tape or paint
Removable
S~ plastic corners
b.
Figure 5-4. a) Collapsible 1 m2 quadrat sampling frame and b) placement of telescoping pole on quadrat.
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 9 of 12
Table 5-1. PDR Screens and Codes
a) Disturbance codes (Trampling)
1 none/slight 0-10% of quadrat disturbed
2 moderate >10-50% of quadrat disturbed
3 heavy >50% of quadrat disturbed
b) dominant microhabitat
1 Mineral Soil/Sediment; physically weathered soil parent material that may or may not also be chemically and biologically
altered
2 Rock: a large rock or boulder or accumulations of pebbles or cobbles
3 Standing water/Flooded: ponded or flowing water that is not contained within banks
4 Stream: body of flowing water contained within banks
5 Dead wood: log and slash (> 10 cm diameter), stump
6 Litter/duff: accumulation of organic matter over forest mineral soil, including branches and limbs
<10 cm diameter and bark
a-< 1 cm continuous
b-> 1 cm continuous
7 Live roots/bole: living roots at the base of trees or exposed at the surface of the forest floor or soil and cross-sectioned area
of live tree boles at ground-line.
8 Road
9 Cow pie
10 Trash/junk
c) vegetation strata (O'Brien and Van Hooser, 1983)
Code Definition Strata Height
1 Ground/bryophyte/low herb layer 0-2 ft (0-0.61 m)
2 High herb/low shrub layer 2-6 ft (0.61 -1.83 m)
3 High shrub/low tree layer 6-16 ft (1.84-4.88 m)
4 Middle/upper tree layer >16 ft (>4.88 m)
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 10 of 12
Table 5-1. PDR Screens and Codes (cont.)
d) identification of plant species
Species codes for vascular plants will come from a standard national list (Soil Conservation Service, 1982). Species codes
are typically a 4-letter code, formed by the first two (2) letters of genera and species. Replicates of the base 4-letter code are
differentiated by adding a sequential number, forming a 5- or 6-digit code (4 letters plus 1 or 2 numbers). Similarly, a variety or
subspecies are indicated by adding their first letter to the base 4-letter code, forming a 5-digit code. An example is shown below.
A different coding format is used if the plant cannot be confidently identified to the species level. Specimens should be collected
for such "unknown" plants (Subsection 5.2). The specimen number on the preprinted label for the specimen should be entered as
the species on the PDR. When a specimen for an unknown can not be found, the botanist should enter an "x" (representing an
unknown species for which there is no specimen) followed by a consecutive number, (representing the sequential numbering of
unknowns on the plot) and a short descriptor (e.g., herb). Numbering starts over on each new plot.
Phylogentic Determination
1. Genera / species / subsp. or var.
Astragolus adsurgens subsp. rebustion or
A. adsurgens var. tamaraicans
2. Genera species
A. adsurgens
Code
ASADR2
ASADT
ASAD
3. Make and record separately three types of vegetation structure measurements:
a) Identification of plant species,
b) Stratum (ST) of plant, and
c) Amount of plant canopy cover (CC).
The following guidelines should be observed during measurements and data recording:
1. Begin measurements and data recording in the lowest stratum (0 - 2 ft, Table 5-1 b) and work upward,
making sure to stay within the predefined horizontal and vertical boundaries of the sampling areas
(Subsection 5.6.2, Figure 5-4).
2. First identify the dominant microhabitat (Table 5-1c) and plant species (Table 5-1 d) in the vertical
stratum (Figure 5-4) and record on PDR (Figure 5-3).
a) Plants are identified with the highest level of taxonomic accuracy possible, preferably to species,
and if applicable and possible, to subspecies or variety. Use the 4- or 5-character abbreviation
(Soil Conservation Service, 1982). Similarly, unknown species are identified with the highest level
of taxonomic accuracy possible. When the botanist encounters a plant which he/she can not
confidently identify to species, a specimen should be collected off-quadrat (Subsection 5.2). The
specimen number from the preprinted label should be entered in the species field on the PDR
screen. If no specimen of the "unknown" plant can be found, then an "x" followed by a consecutive
number (1, 2, 3...) and a descriptor (e.g., herb) should be entered.
b) The species list for each stratum should be as comprehensive as possible, including species of
vascular plants (herbs, shrubs, vines, grasses, ferns, and trees), bryophytes (mosses and
liverworts), and lichens. Priority is given to terrestrial vascular plants rooted in the soil, other
ground substrates, or those overhanging the quadrat. Mosses, liverworts, and lichens should be
recorded and scientifically named if possible. If they cannot be named scientifically, then they
should be named as "moss," "liver," or "lien," followed by a consecutive number (1, 2, 3...) if more
than one species is apparent. Epiphytes (e.g., lichens and mosses on tree boles or branches) will
not be sampled on quadrat.
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 11 of 12
3. Next record the vertical stratum code (1-4) of the plant species cover (Table 5-1 b) on the PDR (ST in
Figure 5-2). Plant species growing in more than one stratum will have multiple entries, with one record
for each stratum. In these cases, record the same plant codes used in field 1 for each stratum.
4. Directly estimate the canopy cover (CC) of every plant species within a stratum to the nearest one
percent (no classes) and record (Figure 5-2).
a) Canopy cover is estimated in two steps following the rationale of Daubenrnire (1968). First, the
natural extent of individual plant canopies within or overlapping the sample area are visualized as
polygons (Figure 5-4). Conceptually, the polygons define a plant species' sphere of influence
above- and below-ground, including any natural openings of each canopy. Then, the polygon
areas are vertically projected to the ground surface to determine the percent of the quadrat area
(1 m2) covered by each plant species in the stratum. Superimposed canopies of different species
are determined separately, while the overlap of superimposed canopies of the same species is
ignored (Figure 5-4).
b) Use the guides on the sampling frame to successively delimit the quadrat area covered by the
vertically projected canopy of each plant species in the stratum (Figure 5-4). For example, there
are 100,1 dm2 (1%) and 4, 25 dm2 (25%) areas in a 1 m2 sampling frame. The larger areas can
be used initially to determine if plant species canopy cover is >75, 50-75, 25-50, or <25%, while
the smaller 1 dm segments can be used to aid subdividing the larger areas to arrive at a final
percent cover estimate for the species.
5. Repeat steps 1-4 for each stratum of the quadrat.
6. After completing measurements for all strata on the quadrat, collect (off-plot) specimens of all plants
not positively identified by species and specimens of known species encountered for the first time.
Refer to Subsection 5.2 for a complete description of plant collection and handling procedures.
7. Repeat steps 1-6 for quadrats 2 and 3.
8. Repeat steps 1-7 on quadrats of subplots 2-4.
5.5.4 Documentation of Plot Conditions
Environmental and disturbance factors encountered on the plot should be documented in the
disturbance codes. This information assists the indicator in data analysis and interpretation and provides
information on plot aesthetics.
The foresters have been instructed to provide the botanists with their general descriptions of forest,
topographic, and soil conditions for each subplot. Supplement these descriptions, as necessary, with
unique or special conditions affecting plant distribution and growth that may be encountered on particular
quadrats.
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EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 12 of 12
5.7 References
Archambault, L, B.V. Barnes, and J.A. Witter. 1989. Ecological species groups of oak ecosystems of
southeastern Michigan. For. Sci. 35: 1058-1074.
Atkeson, T. D. and A.S. Johnson. 1979. Succession of small mammals on pine plantations in the
Georgia Piedmont. Amer. Midi. Nat. 101: 385-392.
Childers, E.L., T.L. Sharik, and C.S. Adkisson. 1986. Effects of loblolly pine plantations on songbird
dynamics in the Virginia Piedmont. J. Wildl. Manage. 50: 406-413.
Cline, S.P. 1992. Vegetation Structure indicator. IN Forest Health Monitoring 1992 Activities Plan.
S.A. Alexander and J.E. Barnard. EPA/620/R-93/002. U.S. Environmental Protection Agency,
Washington, D.C.
Daubenmire, R. 1968. Plant communities: a textbook of plant synecology. Harper & Row, New York.
DeGraaf, R.M. and D.D. Rudis. 1983. New England Wildlife: Habitat, natural history, and distribution.
USDA Forest Service. NE For. Exp. Stn. Gen. Tech. Rpt. NE-108. 491 p.
Felix, A.C. Ill, T.L. Sharik, and B.S. McGinnes. 1986. Effects of pine conversion on food plants of
northern bobwhite quail, eastern wild turkey, and white-tailed deer in the Virginia piedmont. South.
J. Appl. For. 10:47-52.
Miller, P.R. and J. R. McBride. 1975. Effects of air pollution on forests. IN Mudd, J.B. and T.T.
Kozlowski (eds.) Responses of Plants to Air Pollution. Academic Press, N.Y. pp. 175-235.
O'Brien, R. and D. Van Hooser. 1983. Understory vegetation inventory: an efficient procedure. USDA
Forest Service. Intermt. Forest and Range Exp. Stn., Ogden, UT. Res. Paper INT-323. 6p.
Radford, A., W. Dickison, J. Massey, and C.R. Bell. 1974. Collection and field preparation of
specimens. Chapter 18. IN Vascular plant systematics. Harper and Row. pp 387-398.
Repenning, R.W. and R.F. Labisky. 1985. Effects of even-age timber management on bird communities
of the longleaf pine forest in northern Florida. J. Wildl. Manage. 48: 895-911.
Soil Conservation Service. 1982. National list of scientific plant names. Vol. 1. List of plant names.
USDA Soil Conservation Service. Ecological Sciences Staff. Washington D.C. SCS-TP-159. 416p.
Stapanian, M.A. and S.P. Cline. 1994. Vegetation structure indicator, jn Cline, S.P. and C. Palmer.
Forest Health Monitoring: 1994 Quality Assurance Project Plan.
Walters, D. and D. Keil. 1988. Collecting and preserving plants for study. Chapter 6 IN Vascular plant
taxonomy. Kendall and Hunt, pp 55-67.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 1 of 21
Section 6. Ozone Bioindicator Plants
Section/Title Page
6.1 Overview 2 of 21
6.1.1 Scope and Application 2 of 21
6.1.2 Summary of Method 2 of 21
6.1.3 Interferences 3 of 21
6.1.4 Safety 3 of 21
6.2 Sample Collection, Preservation, and Storage 3 of 21
6.3 Equipment and Supplies 3 of 21
6.3.1 Equipment and Apparatus 3 of 21
6.3.2 Consumable Supplies 4 of 21
6.4 Calibration and Standardization 4 of 21
6.5 Quality Assurance 4 of 21
6.5.1 Training 4 of 21
6.5.2 Field Audits/Remeasurement 5 of 21
6.5.3 Voucher Specimens (Pressed Leaves With Symptoms) 5 of 21
6.5.4 Measurement Quality Objectives 5 of 21
6.5.5 Method Performance 6 of 21
6.5.6 Communications 6 of 21
6.6 Procedure 7 of 21
6.6.1 Evaluation Window 7 of 21
6.6.2 Site Selection 7 of 21
6.6.2.1 New Plots (Mt1) 8 Of 21
6.6.2.2 Established Plots (Mt2 and Mt3) 9 of 21
6.6.3 Species Selection 10 of 21
6.6.4 Plant Selection ...: 10 of 21
6.6.5 Symptom Identification and Scoring 11 of 21
6.6.6 Collection of Leaf Samples 13 of 21
6.6.7 Crew Member Responsibilities 14 of 21
6.6.8 Reference Plot Methods 14 of 21
6.6.9 Data Sheets 15 of 21
6.7 References 16 of 21
Appendix 6.A Ozone Bioindicator Plants 17 of 21
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 2 of 21
6.1 Overview
Plant species that respond to ambient levels of air pollution with distinct visible foliar symptoms are
used as bioindicators of pollution stress (Manning and Feder, 1980). Field studies and/or fumigation
experiments have identified ozone sensitive species (Davis and Umbach, 1981; Duchelle and Skelly, 1981;
Krupa and Manning, 1988). Foliar injury symptoms include distinct patterns of coloration, often associated
with accelerated senescence. Ozone is the only regional gaseous air pollutant that is frequently measured
at known phytotoxic levels (Cleveland and Graedel, 1979; Lefohn and Pinkerton, 1988); thus, the focus of
this indicator in detection monitoring will be only on ozone. Suitable sites close to the FHM detection
monitoring plots will be selected for ozone injury evaluations. The foliage of sensitive plants will be
examined for the presence or absence of ozone injury, and the amount and severity of injury will be
recorded. Reference plots will be established in different physiographic or political regions (e.g., states or
USFS regions) to improve the regional assessment of this indicator. Reference plot evaluations are done
using the same methodology as the on-frame activities and are just as important.
6.1.1 Scope and Application
The scope of this indicator is national, but information on the occurrence of phytotoxic ozone exposures
at the regional or state level is also obtained. Procedures are amended regionally as needed, particularly
with regard to suitable sites and target species. Other variables, such as number of species, number of
plants, and methods of scoring are standardized nationally. In general, the formulation of procedures and
the reporting and assessment goals were developed with the following considerations:
1. Keeping the evaluation of ozone indicator plants close enough to the detection plots to avoid
problems with inclusion probabilities and create links between phytotoxic levels of ozone on the
sensitive species and other detection plot indicators;
2. Keeping estimated errors for the detection plot below 10%. We attempted to devise a method that
can be reproduced by an audit crew within 10% for the selection of ozone-sensitive species, symptom
identification, and quantification of injury; and
3. Addressing seasonal variability in ozone injury. We know that ozone injury must reach an undefined
threshold within a leaf before the injury becomes visible to the human eye, and then tends to be
cumulative over the growing season until Fall senescence masks the symptoms.
6.1.2 Summary of Method
Crew procedures include the selection of a suitable site for symptom evaluation, identification of one
to three known ozone-sensitive species at the site, and identification of ozone injury on the foliage of up
to 30 plants of each species. Each plant is evaluated for the percentage of injured area and severity of
injury on a five point scale. Field crews record information on the location and size of the opening used for
biomonitoring and record injury amount and severity ratings for each plant.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 3 of 21
To eliminate problems with seasonal variability in ozone response, all foliar evaluations are conducted
during a two-to-three week window towards the end of the growing season. Foliar injury data are also
collected, during the evaluation window, from off-frame reference plots established in each state by
Regional Cooperators. The reference plots are standardized for certain site characteristics that influence
ozone uptake by sensitive plants (Heck, 1968; Krupa and Manning, 1988). They are intended to provide
ozone injury information under optimal conditions of field exposure and to improve the regional
responsiveness of the ozone indicator.
Voucher specimens (pressed leaves with symptoms) are collected for each species for proper symptom
identification. Additional quality control measures include field audits and remeasurement of 10% of the
biomon'rtoring sites.
6.1.3 Interferences
Primary interferences to consider are the lack of suitable sites and/or target species at some detection
plots. These detection plots are not directly evaluated for this indicator. Establishing reference plots helps
address this issue. Ozone is a regional pollutant, understood to have regional effects on vegetation. The
data collected at reference plots within each physiographic region should, therefore, have some application
to detection plots within the same region.
The other serious consideration is discriminating ozone foliar injury symptoms from other abiotic or
biotic foliar injury symptoms. Since the target species selected for these studies were selected because
of their sensitivity and distinctness of symptom, this should be an issue that can be adequately addressed
in training.
6.1.4 Safety
No specialized safety precautions are necessary. Follow general safety precautions for conducting
fieldwork (see Appendix E).
6.2 Sample Collection, Preservation, and Storage
Leaf samples are collected by field crews. They are to be placed in a small plant press immediately
after removal from the selected plant. This is to preserve the integrity of the leaf sample and the injury
symptoms until they can be verified by the National Indicator Lead. Samples should not be exposed to
excess humidity or allowed to dry up too quickly. They should not be stored for any length of time outside
of a plant press. The sooner the pressed leaves are mailed to the National Indicator Lead, the better. A
data sheet identifying the field crew and plot location is to be filled out and mailed with each sample.
6.3 Equipment and Supplies
6.3.1 Equipment and Apparatus
- Reference photographs to aid in symptom identification.
- A small plant press with cardboard inserts to store leaves with ozone injury for quality control
purposes.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 4 of 21
6.3.2 Consumable Supplies
- Stamped, addressed envelopes to mail to the National Lead for validation of the correct ozone-
injury symptoms on each species.
Flagging: for temporary marking of sites or sample plants.
Field data sheets:
(a) for documenting the presence and amount of ozone injury on each plot in the event
of a PDR failure and for mapping the location of the suitable sites.
(b) for recording information about the pressed leaf samples for quality control purposes.
6.4 Calibration and Standardization
The field crew foresters will be trained in species and symptom identification and quantification of foliar
injury symptoms.
6.5 Quality Assurance
One individual in each region assumes quality control responsibilities for the field season. These
Regional Indicator Leads meet during a preseason session to refine methods and establish a unified
approach to training, audits, and debriefing. Their responsibilities include: (1) training and certifying the
state trainers and/or field crews as needed for their region, (2) documenting hot audits of the field crews,
(3) overseeing the field crew refresher session held just prior to the evaluation window for this indicator,
(4) validating the ozone injury symptom recorded by the field crews and cooperators on the detection and
reference plots, (5) assisting in the field with remeasurement procedures for symptom quantification, and
(6) conducting a debriefing session for the indicator.
Quality control reports are prepared by the National Indicator Lead with input from the Regional Leads
as needed. These reports will discuss all issues related to quality assurance and quality control including
results of the training sessions and field audits, debriefing comments from the field crews, and an
evaluation of remeasurement and reference plot data.
Quality control activities of direct interest to the field crews are discussed below. Additional detail is
provided in the 1994 Quality Assurance Project Plan for the ozone indicator.
6.5.1 Training
Each field crew member is trained and tested for familiarity with the site selection, species selection,
and data collection procedures, and their ability to recognize ozone injury and discriminate against
mimicking symptoms. Although field crews are certified during the regular preseason training session, they
must also participate in a refresher session held just prior to the beginning of the evaluation window for this
indicator.
The Regional Indicator Lead is available to answer questions and provide retraining as needed
throughout the field season.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 5 of 21
5.5.2 Field Audits/Remeasurement
A field audit crew remeasures a subsample of the detection plots in each region. Auditing procedures
cover species selection, symptom identification, and quantification of injury, as well as foliar sample
collection, preservation and shipment.
Field crew supervisors audit the field crews and remeasure one bioindicator site in their jurisdiction.
The Regional Indicator Leads assist with these audit and remeasurement activities as needed.
6.5.3 Voucher Specimens (Pressed Leaves With Symptoms)
Field crews and cooperators collect leaf samples on the detection plots and on the reference plots
according to procedures outlined in Subsection 6.6.6. These voucher specimens are pressed and mailed
to the National Indicator Lead for validation of the ozone symptom.
6.5.4 Measurement Quality Objectives
Table 6-1 lists measurement quality objectives. The measurement error limits for this indicator are set
at 10% for the training of the field crews. We expect that the crews will identify the species and pollutant
symptoms and be able to estimate the amount and severity of injury within one class at least 90% of the
time.
We expect that field audit crews will get the same results as the field crews at least 90% of the time
when selecting the indicator species and quantifying ozone injury. The ozone symptom will be validated
for each injured species on each plot with the use of a leaf voucher. There must be no differences between
the crew and expert identification of the ozone symptom.
Table 6-1. Measurement Quality Objectives
Plot Level Variables
Bioindicator species
For each species:
No, stems evaluated
No. stems inj/No. stems eval
Amount of injury
Severity of injury
Symptom verification (TS)*
Symptom verification (FS)
Reporting Units
species code
number
ratio
5 classes
5 classes
yes or no
yes or no
Data Quality Limits
+•/- 1 species
+/- 10%
+/- 10%
90% @ +/- 1 class
90% @ +/- 1 class
90% agreement
100% agreement
* TS - Training Session; FS » Reid Session
Results of the field audits and remeasurement activities described in Subsection 6.5.2 will be used to
determine if the measurement quality objectives are being met. Regional Leads and State
Coordinators/Field Supervisors who are certified for the ozone indicator have the authority to implement
whatever corrective action is needed in the field (e.g., retraining and retesting).
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 6 of 21
6.5.5 Method Performance
Method performance will be determined through analyses of the quality control data collected at the
training sessions and during the field season.
In 1992 and 1993, field crews trained and tested at the beginning of the field season easily met
certification standards for species and symptom identification. Field audits conducted within two weeks of
the training session confirmed that all crews were proficient in the field methods for the ozone indicator.
In 1994, because data collection occurs late in the season, a refresher training course and late season
audit have been added to the quality control procedures. In addition, remeasurement procedures (absent
in 1992 and 1993) have been added.
Results of the audit and remeasurement procedures will be used to assess the ability of the field crews
to meet measurement quality objectives with respect to identification of bioindicator species, number of
stems evaluated, number of stems injured, amount of injury, and severity of injury. Voucher leaf samples
will also be used to assess measurement quality for identification of the ozone injury symptom. If the
measurement quality objectives (discussed in detail in the 1994 Quality Assurance Project Plan) are not
met, the data will not be used.
6.5.6 Communications
Any questions arising during the field season that cannot be answered by the Field Supervisor or State
Coordinator, should be directed to the Regional Lead for the ozone indicator. If any field crew orcooperator
is uncertain about who to call for information, they should contact the National Lead at the number listed
below. All data sheets and voucher specimens are mailed to the National Lead.
National Lead and Regional Lead for the Northeast and Mid-Atlantic:
Gretchen Smith Phone:(413)545-1680
Holdsworth Hall
University of Massachusetts
Department of Forestry and Wildlife Management
Amherst, MA 01003-0130
Regional Lead for the Southeast and South:
Beth Brantley Phone: (704) 257-4857
USDA Forest Service - FPM
200 Weaver Blvd.
Ashville, NC 28804
Regional Lead for the Lake States:
Ed Hayes Phone: (507) 285-7428
Minnesota Department of Natural Resources
2300 Silver Creek Rd. NE
Rochester, MN 55906
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 7 of 21
6.6 Procedure
NOTE: In the following discussion, use of the word "plot" refers to the permanent FHM detection
monitoring plot. Use of the word "site" refers to the open area used for the ozone indicator evaluations.
The procedures for documenting the occurrence of ozone air pollution injury on sensitive bioindicator
species include the selection of a suitable site for symptom evaluation, identification of 1-3 known ozone-
sensitive species at the site, and evaluation of injury amount and severity on the foliage of 10-30 plants
of each of three species. If three species cannot be found at a site, a lesser number of species is still
evaluated. If 30 plants of each species cannot be found at the site, a lesser number (between 10 and 30)
can be evaluated. Each individual plant with ozone injury is scored for amount and severity of injury. If a
plant does not have ozone injury, it is still tallied with zeros for these measurements. A data sheet and
map, identifying key characteristics of the bioindicator site, is prepared for each plot. If a plot has no
bioindicator site, this information is recorded on the PDR.
All foliar evaluations are conducted during a two-to-three week window towards the end of the field
season. This is necessary to eliminate differences between plots that are caused by timing. During the
evaluation window, a minimum of seven plots per crew are evaluated for ozone injury. If crews have
completed the detection monitoring plots prior to the opening of the window, they must return to a minimum
of seven plots for the specific purpose of completing the bioindicator measurements.
In the following discussion, it should be noted that site selection procedures depend on whether crews
are establishing new plots (Mt1) or revisiting established plots (Mt2 and Mt3). However, procedures for
species and plant selection, symptom identification and scoring, and collection of leaf samples for
remeasurement are the same for all crews, regardless of measurement type.
6.6.1 Evaluation Window
Quantifying ozone injury on the FHM detection plots is limited to a two-to-three week period in late-July
to mid-August. The evaluation window for crews in the Northern Region (NO) begins 8 August and extends
through 19 August. In the Southeastern (SE) and Southern (SO) Regions, the window is open from 25 July
through 12 August. A PDR edit check will prompt the field crews at the start and end of the evaluation
period.
States in the NO, SE, and SO that are new to this indicator collect the ozone injury data on whatever
plots they visit during the prescribed evaluation period. States in the NO, that have established bioindicator
sites, are provided with a list of preferred plots to visit during the evaluation window. Specific procedures
are outlined in the following section.
6.6.2 Site Selection
States in the Northern (NO), Southeastern (SE), and Southern (SO) Regions, that are new to this
indicator, complete the site selection procedures described below at each detection plot visited by the crews
during the field season. However, the subsequent procedures for species and plant selection, and symptom
quantification are completed only if the evaluation window is open at the time of the plot visit. States in the
NO with established sites may choose to select and map new sites as needed throughout the field season,
but the focus of the field activities should be on symptom quantification during the two-week evaluation
period.
Crews are given maximum flexibility to select the bioindicator evaluation site that, in their judgement,
provides the best opportunity for quality data collection. A crew locates and maps the largest, most easily
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 8 of 21
accessible opening that is within three miles and +/- 300 feet (91 m) elevation of the detection monitoring
plot. The crew is not expected to measure distance or elevation, but to use the numbers given as general
guidelines in the site selection process. There are no minimum plot size or distance requirements, but a
site must contain at least ten individuals of at least one bioindicator species to be evaluated for ozone
injury.
The site is described as an open area because this is the usual case, but there may be some instances
where the appropriate number of bioindicator plants are found under the canopy. The best site may be
found along the vehicle access route to the plot or within walking distance of the course-to-plot (or whatever
alternate course may have been established to access the FHM plot). No more than 30 minutes should be
spent locating the bioindicator evaluation site.
Once an evaluation site has been located, a permanent map is made by the crew which will be used
by audit and regular crews in subsequent visits to the plot (see Figure 6-1). This map is attached to the
original plot data sheet with the sketch map of plot location, so that it is readily available to whoever needs
it.
NOTE: Examples of suitable openings include old logging sites and abandoned pasture or farmland
where you are reasonably certain that soil/site conditions are stable and free of chemical contaminants.
Avoid open areas where plants are obviously stressed by some other factor that could mimic the ozone
response. Do not select a site under a high-tension power line or on or near an active or reclaimed landfill.
6.6.2.1 New Plots (Mt1)
Site selection procedures begin wfth an in-office review of the plot photos or, in the field, if no suitable
opening is visible on the plot photos. Candidate sites must be easily accessible open areas that are within
three miles or +/- 300 feet (91 m) elevation of the detection plot and more than 100 feet (30 m) from a busy
(paved) road. There are no additional site selection criteria other than the requirement that there be at least
ten individuals of at least one bioindicator species on site.
Ideally, candidate sites are visited prior to the beginning of the field season by a reconnaissance team.
If this is not possible, site selection occurs at the time of plot establishment. A plot without a suitable site
(no opening or less than the minimum number of plants or species) is not evaluated for this indicator.
The characteristics of a preferred evaluation site are as follows: (1) opening >0.5 acre, (2) soil/site
conditions with low drought potential and adequate fertility, (3) more than ten individuals of more than one
species, and (4) easy access from car or course-to-plot. These are not meant to be used as site selection
criteria but to assist the crew in selecting the best site when more than one option is available to them.
When site selection occurs at the time of plot establishment, the following procedures are followed:
Crews screen candidate sites along the vehicle access route and course-to-plot, keeping in mind the
characteristics of a preferred site as described above. Final site selection and mapping occurs as the last
plot activity on the way back to the vehicle. This allows the crew to select the best site for evaluation after
viewing all the possibilities.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 9 of 21
Pa-lunbo
• woodsJKoad
From SS go 7.5'± to
clump of milkwead.
Ihara ara scattered black
cherry along- tha easterly
a Ida of tha open fiald.
Refer to the plot data sheet for
hex code number 4407255 for directions
to tha starting point.
Figure 6-1. Example of a well drawn map locating the bioindicator site for a permanent detection monitoring plot.
The best site is the largest, easily accessible opening, with the most ozone indicator species. However,
size should not be a determining factor unless the candidate sites are all less than 0.5 acre. If two sites
are >0 5 acre, select the site with the most plants or species. If two sites are similar in size and number
of plants and species, select the site which appears to have the most favorable soil/site conditions (e.g.,
low drought potential and adequate fertility). These statements are provided as guidelines, not as rules that
must be followed in the site selection process. The intention is to provide the field crews with maximum
flexibility to select the bioindicator site that provides the best opportunity to collect quality data.
Once a bioindicator site is selected, the field crew records the estimated size (half-acre increments)
of the site opening and other key site characteristics identified on the PDR or data sheet. On a separate
data sheet, the crew maps the location of the site relative to the detection plot or some other obvious and
permanent marker. Directions to the site, including road names and distances, are included as needed. The
map will be used by audit and regular crews in subsequent visits to the site.
6.6.2.2 Established Plots (Mt2 and Mt3)
States in the NO, SE, and SO Regions, that are new to this indicator, should follow procedures outlined
in the previous section for new plots (Mt1). Procedures for crews in the NO, that have established
bioindfcator sites, are as follows: Each crew is provided with a preferred list of plots to visit during the two-
week evaluation window. Preferred plots are those that provide the best opportunity to detect injury if
phytotoxic ozone concentrations are present on the plot. Once the evaluation window opens, crews
complete the bioindicator measurements on as many of the preferred plots as possible. If there are no
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 10 of 21
preferred plots in their area, or if they are logistically unable to visit them, bioindicator measurements are
made on whatever plots they visit during the evaluation window.
If crews have completed the FHM detection plots prior to the opening of the window, they must return
to a minimum of seven plots (preferred or otherwise) for the specific purpose of completing the bioindicator
measurements. The seven plot minimum is a recommended goal. Logistics or an absence of suitable
evaluation sites may make it impossible for some crews to meet this goal. For example, it is understood
that most of the plots in Northern Maine can not be evaluated for this indicator due to the complete
absence of bioindicator species in the area.
6.6.3 Species Selection
At the selected bioindicator site, the crew evaluates between 10 and 30 individuals of up to three
bioindicator species. If three species can not be found at the site, then a lessor number of species is still
evaluated. A prioritized list of species is provided to the field crews for each region. The top three species
in each list are the first priority for choice of species.
Field crews record the species code number for each selected species in the PDR or on the data
sheet. The target species and codes for each region are:
Northern Region (NE. mAtl. and LS sub-regions)
Code Definition
915 Blackberry
762 Black Cherry
365 Common Milkweed
621 Yellow Poplar
541 White Ash
364 Big Leaf Aster
366 Dogbane
Scientific Names
Rubus allegheniensis
Prunus serotina
Asclepias syrica
Liriodendron tulipifera
Fraxinus americana
Aster macrophylum
Apocynaceae androsaemifolium
Southeastern and Southern Regions
Code Definition
915 Blackberry
762 Black Cherry
365 Common Milkweed
621 Yellow Poplar
541 White Ash
6.6.4 Plant Selection
Scientific Names
Rubus allegheniensis
Prunus serotina
Asclepias syrica
Liriodendron tulipifera
Fraxinus americana
After site and species selection, the next task is to contiguously sample 10-30 individual plants of each
species. The following procedures help the crews to collect the bioindicator data in as systematic a way
as possible.
1. Identify a starting point at the edge of the opening. This point should be mapped on the plot data
sheet so that audit and regular crews evaluate roughly the same population of plants in subsequent
visits to the plot.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 11 of 21
2. Move away from the starting point, towards the center of the opening.
3. Begin locating individuals in a sweeping pattern, selecting plants that are growing under the same
or similar growing (microhabitat) conditions. Do not skip plants with little or no injury.
4. Select the more exposed plants (high sunlight exposure) and avoid suppressed and shaded
individuals. Plants along the edge of an opening may be used if, in your judgement, they receive
direct sunlight for three to four hours each day.
5. Evaluate the foliage that you can see and touch on 30 plants of each species in the opening (a
minimum of 10 plants must be found for a species to be evaluated).
6. Record both the amount and severity of injury for each plant evaluated (with or without symptoms)
on the PDR or data sheet.
NOTE: Milkweed and blackberry spread vegetatively. This means that neighboring plants are often
genetically identical. To avoid repeat sampling of clonal material take several steps between each plant
selected for evaluation. With blackberry, it is often difficult to distinguish individual plants or stems. In this
case, use an approximate 2-foot square area to represent a single plant.
On average, it should take no more than 45-60 minutes to locate and evaluate the bioindicator plants
at each plot.
6.6.5 Symptom Identification and Scoring
&
Symptoms of air pollution injury are taught intensively in training, with emphasis on appearance,
patterns, and discrimination from any mimicking symptoms. The bioindicator species selected for each
region are those that have been determined through field and laboratory studies to be highly sensitive to
ozone air pollution. However, within a species, differences in genetics between individuals result in
differential sensitivities to ozone. This means that you often find an individual of a species with severe air
pollution injury growing immediately adjacent to another individual of the same species with few or no
symptoms.
In addition to genetics, the age of the leaves (position on the stem, branch, or rosette) affects a plant's
susceptibility to ozone air pollution. In general, leaves at 75% full expansion are the most sensitive and tend
to show symptoms most definitively toward the center of the leaf. Older leaves show symptoms more
widespread over the leaf surface, while younger leaves show symptoms more commonly near the leaf tip.
If leaves on one branch are affected, then leaves at a similar leaf position on another branch should be
affected, especially for branches on the same side of the plant under similar environmental conditions (sun
or shade leaves).
When scoring foliar symptoms on bioindicator plants check for the following characteristics of ozone
injury:
- Symptoms are more severe on mid-aged and older leaves. New leaves will have no or very little
injury.
Symptoms are most likely confined to the upper leaf surface.
- Check leaves covering each other. Overlapped leaves will have no injury on the bottom leaf.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 12 of 21
There will be some uniformity to size and shape of the lesions on a leaf.
Almost all exposed branches on a plant will be affected to some degree.
Symptoms are more often visible as tiny purple-red to black spots (stippling) and less often as
small white to tan flecks.
Later in the growing season, stippling may be associated with leaf yellowing or premature
senescence. Check the ground for fallen leaves.
Each plant with ozone injury is evaluated for the percent of the plant that is injured and the average
severity of injury. This information will be used to calculate an injury index value for each plant and a mean
value for each species at each plot location. For each plant located, the percentage of injured area and
the severity of injury are both rated on a scale of 0 to 5 (see below).
Percentage of injured area is determined by estimating the proportion of live crown or leaf area injured
relative to the total leaf area. Severity of injury is determined by estimating the mean severity of symptoms
on injured foliage. If a plant does not have injury, it is still tallied with zeros for these measurements.
Percent Scale:
0= no injury
1= 1 to 6% [of the live crown, or leaf area, (for percent estimate) or injured leaf (for severity estimate)
with ozone symptoms]
2= 7 to 25% [..with ozone symptoms]
3= 26 to 50% [..with ozone symptoms]
4= 51 to 75% [..with ozone symptoms]
5= > 75% [of the live crown, or leaf area, (for percent estimate) or injured leaf (for severity estimate)
with ozone symptoms]
Proceed as follows:
1. Record the injury amount and the injury severity ratings for each plant on the PDR or data sheet.
2. Use the notes section on the PDR or data sheet to briefly describe what you saw and recorded as
ozone injury for each species. Use the terminology discussed in training whenever possible (e.g.,
stipple, mottle, fleck, chlorosis, etc.).
3. Collect a voucher leaf sample (one for each species evaluated at each location) and mail them to
the National Lead using the guidelines presented in Subsection 6.6.6.
NOTE: Do not take measurements in steady rain. Foliar symptoms are easiest to see under overcast
skies. Bright sun will make it difficult to see the ozone stipple. Stand so that you reduce the glare on the
leaf surface. Long periods without rain will inhibit symptom development even on the most sensitive plants.
If you are experiencing below average rainfall for your area, please note this in the PDR or on the data
sheet.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 13 of 21
6.6.5 Collection of Leaf Samples
The voucher leaf samples are a critical aspect of the data collection procedures as they provide the
necessary validation of the ozone injury symptom observed in the field by the field crews. During the
evaluation window, a voucher leaf sample must be collected for each injured species evaluated on the
bioindicator site. For example, if a field crew records ozone injury on blackberry, black cherry, and milkweed
then a minimum of one leaf voucher from each of the three species is collected and mailed to the National
Indicator Lead.
Field Collection: The voucher consists of three leaves that clearly show the ozone injury symptom.
Ideally, these are three leaves with high amounts of foliar injury symptoms. If this is not possible, send
whatever leaf sample is available even if it's only one leaf with faint symptoms. Cut the leaf at the petiole
with hand clippers or a sharp knife.
If the leaves are wet when you cut them, shake off any excess moisture and pat dry. The samples do
not have to be completely dry at this point. Place the samples into the plant press you were provided at
training. Each leaf is placed in the press so that it does not overlap another leaf. Include a small label with
each leaf sample you place into the plant press that identifies which plot the sample came from and the
date. Small labels are provided for this purpose. Record the information on the labels with indelible ink and
then wrap them around the petiole of one leaf per sample so that the back sides stick together and will not
slip off the leaf. If you forget to take the plant press with you into the field, then place the leaves and
accompanying label between pages of a notebook, or otherwise keep as flat as possible.
NOTE: Blackberry leaves consist of 3-7, mostly 5 leaflets. Select the whole leaf when preparing a
voucher sample. Injury will tend to be more pronounced on second year canes bearing fruit and flowers.
Mailing Procedure: Vouchers may be mailed in bulk at the end of the evaluation window, or earlier,
depending on your work schedule. It is very important to mail only dry, pressed leaf samples. Before
mailing, make sure you have filled out the upper half of the voucher data sheet. This sheet is filled out on
the same day the sample is collected even if the sample is not mailed on that day. Although it is not a
requirement, please take the time to include a brief description of your findings on the voucher data sheet.
This could include observations on the weather, on injury amount and severity, or on general plot
conditions. Examples: "It's been 14 days now without rain," "Every plant showed the same response and
it was very obvious," or "This was a highly disturbed site." Include anything that you think might help in
the interpretation of the results.
The lower half of the voucher data sheet is filled out by the National Lead to whom you are sending
the sample. Place the voucher data sheet and the leaf sample into a mailing envelope addressed to the
National Indicator Lead. Include as many samples as fit easily into each mailing envelope. Mail the voucher
first class.
The National Lead returns a copy of the voucher data sheet to you by return mail to let you know
whether or not you correctly diagnosed the ozone symptom. The copy of the voucher sheet that is returned
to you will include an explanation of why your diagnosis was correct or incorrect. This is for your information
only. You do not need to save the sheet unless you feel it could be helpful for future reference. Don't
hesitate to call your Regional Indicator Lead anytime you have a question on procedures or diagnosis.
NOTE: Field crews are encouraged to mail leaf samples for symptom verification at any time during
the field season even though the requirement to do so is in effect only during the evaluation window. Keep
in mind that the more voucher samples you send in for verification, the greater confidence we can have
in the plot findings for this indicator.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 14 of 21
6.6.7 Crew Member Responsibilities
1. Two crew members are trained for this indicator and are responsible for site selection, plant
selection, and ozone injury evaluations.
2. The two trained crew members should assist each other in the site selection process. Once a site
is selected, one crew member should be responsible for mapping the site on the data sheet, while
the other crew member begins to search for plants for each bioindicator species.
3. One crew member should be responsible for evaluating the plants while the other crew member
records the injury scores on the PDR or data sheet. The other crew member should counsel the
evaluating crew member when there is doubt concerning the nature or severity of injury.
4. The crew member who evaluates the plants for injury should be responsible for collecting and
mailing the voucher sample with air pollution symptoms.
6.6.8 Reference Plot Methods
In addition to the regular FHM detection plots that are evaluated by the field crews for this indicator,
a subset of reference plots is established in each region to represent the local plant populations and
environmental conditions. This is not an auxiliary effort, but an integral part of the detection-level activities
for this indicator.
Reference plots possess attributes of an ideal site for evaluating ozone injury on sensitive species.
They are larger than three acres, contain the maximum number of indicator species, and have soil/site
conditions with low drought potential and adequate fertility. These plots are evaluated for ozone injury using
the same methods as on the detection plots, and during the same timeframe (i.e., from 8 August to 19
August in the North and from 25 July to 12 August in the South and Southeast).
In New England and the Mid-Atlantic states, the reference plot system is already in place and personnel
are available to conduct the field evaluations. In the South and the Lake states, additional cooperators will
be identified for this task. All reference plot personnel are trained and tested along with the regular field
crews.
NOTE: In most states, the regular detection plot crews are not involved in the reference plot activities.
The site selection criteria for the reference plots are as follows:
- > 3 acres.
- contain the maximum number of indicator species
- have soil/site conditions that favor injury.
- have southwest aspects or be relatively flat (Eastern region).
- have low drought potential.
NOTE: The reference plot may be the same as one of the detection plot suitable sites (i.e., on-frame),
as long as the site selection criteria for reference plots are met.
Once a reference plot is selected, proceed as follows:
1. Record the estimated size of the opening (half-acre increments) and other key site characteristics
identified on the PDR or data sheet.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 15 of 21
2. On a separate data sheet, map the location of the site relative to some obvious and permanent
marker. Directions to the plot, including road names and distances, are included using standard
FHM procedures.
3. Once the reference plot has been appropriately mapped for easy relocation, begin the species and
plant selection procedures. These procedures are identical to those presented in Subsections 6.6.3
and 6.6.4 and are not repeated here.
NOTE: Ideally, a reference plot has close to 30 individual plants of at least three bioindicator
species. If not, a lessor number of plants and species may be evaluated.
4. Adhere to the guidelines presented in Subsection 6.6.5 for symptom identification and scoring.
5. Voucher leaf samples must be collected, according to guidelines presented in Subsection 6.6.6,
and mailed to the National Indicator Lead.
The reference plot system improves the regional assessment of this indicator. It is expected to minimize
uncertainty factors (e.g., the variable soil/site conditions encountered on the FHM detection plots) and
ensure the regional responsiveness of the bioindicator data.
6.6.9 Data Sheets - Detection Plot and Reference Plot Procedures
(see Appendix 6.A)
1. Ozone Bioindicator Plants -1994 Data Sheet for Site Characteristics and Symptom Quantification.
2, Ozone Bioindicator Plants -1994 Data Sheet for Mapping the Bioindicator Site Location. (All data
codes on back side.)
3. Ozone Bioindicator Plants -1994 Data Sheet for the Voucher Leaf Sample.
Field crews and cooperators, in all regions, return data sheet #1 and #3 to Gretchen Smith at the end
of the field season, or earlier, as the work schedule permits. The original of data sheet #2 remains with the
permanent plot file. A copy of data sheet #2 should be mailed to Gretchen Smith at the end of the field
season. Refer to Subsection 6.5.6 for Gretchen Smith's mailing address.
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6.7
EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 16 of 21
References
Cleveland, W.S. and T.E. Graedel. 1979. Photochemical air pollution in the Northeast United States.
Science 204: 1273-1278.
Davis, D.D., and D.M. Umbach.1981. Susceptibility of tree and shrub species and response of black
cherry foliage to ozone. Plant Disease 65:904-907.
Duchelle, S.F.and J.M. Skelly. 1981. Response of common milkweed to oxidant pollution in the
Shenandoah National Park in Virginia. Plant Disease 65: 661-663.
Horsefall, J.G. and E.B. Cowling.1978. Pathometry: the measurement of plant disease, pp. 119-136. In:
J.G. Horsefall and E.B. Cowling (eds.), Plant Disease, an Advanced Treatise, Vol II. Academic
Press, New York, 436 pp.
Krupa, S.V., and WJ. Manning. 1988. "Atmospheric ozone: formation and effects on vegetation,"
Environ. Pollut. 50:101-137.
Lefohn, A.S. and J.E. Pinkerton. 1988. High resolution characterization of ozone data for sites located
in forested areas of the United States. JAPCA 38(12) :1504-1511.
Manning, W.J., and W.A. Feder. 1980. Biomonitoring Air Pollutants with Plants, Applied Science Publ.
Ltd., London, 142pp.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 17 of 21
Appendix 6.A OZONE BIOINDICATOR PLANTS -1994
Site Characteristics
ST
CTY
HEXAGON
MO
DAY
TALLY 1
TALLY 2
' Please put a checkmark beside the correct information.
Ptot size:
> 3.0 acres
0.5 to 3.0 acres
< 0.5 acres
Approximate elevation (feet):
Slope (Aspect):
flat
10-45%
>45%
Soil depth:
bedrock not exposed
bedrock exposed
Terrain position:
lowland
hillside
ridgetop
Soil drainage:
well-drained
wet
very dry
Disturbance:
no disturbance
evidence of overuse
other
Comments:
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 18 of 21
OZONE BIOINDICATOR PLANTS - 1994
Foliar Injury Data
Record species code number from the list below (choose up to 3):
915 Blackberry 762 Black cherry 365 Common milkweed 621 Yellow poplar
541 White ash 364 Big leaf aster 366 Dogbane
Use the codes below (percent injury scale, 0-5) to:
0 = No injury; 1 = 1-6%; 2 = 7-25%; 3 = 26-50%; 4 = 51-75%; 5 = >75%
Record the percent of the leaf area injured relative to the total leaf area (amt).
Record the average severity of symptoms on the injured leaves (sev).
SPECIES CODE
Plot Type
_ Detection Mon.
_ Reference
Remeas.
Plant
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
'17
18
19
20
21
22
23
24
25
26
27
28
29
30
amt
sev
amt
sev
amt
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 19 of 21
OZONE BIOINDICATOR PLANTS 1994
ST
CTY
HEXAGON
MO
DAY
TALLY 1
TALLY 2
Map of the Bioindicator Site Location
Please include the following information on the map:
Location of site relative to detection plot; road names and distance as needed; North arrow.
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 20 of 21
OZONE BIOINDICATOR PLANTS - 1994
General Information
Preferred site characteristics:
* largest, most easily accessible opening
* within 3 miles & +/- 300 feet in elevation of
FHM detection monitoring plot
* good soil conditions
* at least 10 individuals of one bioindicator
species present
« free from chemical contaminants
Sampling the bioindicator site:
* identify starting point (put on map)
* move towards center of opening
* locate plants in a sweeping pattern
* do not skip plants with little or no injury
* avoid suppressed or shaded plants
* evaluate foliage on each plant for amount
and severity of injury
Ozone injury characteristics:
* usually present on mid-aged and older
leaves
* on the upper leaf surfaces
* overlapped leaves will have no injury on the
bottom leaf
* spots are uniform in size and shape', most
often tiny purple-red to black spots
* almost all leaves exposed to sunlight will
have injury
Amount = Percent of leaf area injured relative to the total leaf area.
Severity = Average severity of symptoms on the injured leaves.
Rating scale for amount and severity of ozone injury:
0 = 0% 3 = 26-50%
1 = 1-6% 4 = 51-75%
2 = 7-25% 5 = >75%
Leaf images are upper bounds of each rating class for the severity estimates:
0%
6%
25%
50%
75%
100 %
1 = 1-6% 2 = 7-25 % 3 = 26-50 % 4 = 51-75 %
5 = >75 %
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EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 21 of 21
OZONE BIOINDICATOR PLANTS - 1994
Voucher Leaf Samples
FIELD CREW
ST
CTY
HEXAGON
MO
DAY
TALLY 1
TALLY 2
Name, address, and phone number where you can be contacted:
Bloindicator species:.
Notes:
Mail this sheet with the leaf sample to:
QA/QC PERSON
GRETCHEN SMITH
Dept. of Forestry, Holdsworth Hall
University of Massachusetts
Amherst, MA 01003
Positive for ozone symptom
Negative for ozone symptom
Explanation:
Date received:.
Notes:
Sample condition:
Questions? Call your regional bioindicator lead:
Northeast and Mid-Atlantic: Gretchen Smith (413) 545-1680
South and Southeast: Beth Brantley (704) 257-4857
Lake States: Ed Hayes (507) 285-7428
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 1 of 11
Section 7. Lichen Communities
Section/Title
7.1 Overview 2 of 11
7.1.1 Scope and Application 2 of 11
7.1.2 Summary of Method 2 of 11
7.1.3 Interferences 3 of 11
7.1.4 Safety 3 of 11
7.2 Sample Collection, Preservation, and Storage 3 of 11
7.2.1 Sample Procurement 3 of 11
7.2.2 Sample Mailing 4 of 11
7.3 Equipment and Supplies 6 of 11
7.3.1 Equipment and Apparatus 6 of 11
7.3.2 Consumable Supplies 6 of 11
7.4 Calibration and Standardization 6 of 11
7.5 Quality Assurance 6 of 11
7.5.1 Measurement Quality Objectives 6 of 11
7.5.2 Certification 7 of 11
7.5.3 Audits 7 of 11
7.5.4 Remeasurements 8 of 11
7.5.5 Debriefing 8 of 11
7.5.6 Method Performance 9 of 11
7.6 Procedure 9 of 11
7.7 References 11 of 11
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 2 of 11
7.1 Overview
7.1.1 Scope and Application
The purpose of the lichen community indicator is to use lichen species and communities as biomonitors
of change in air quality, climate change, and/or change in the structure of the forest community. Lichen
communities are excellent indicators of air quality, particularly long-term averages of sulfur dioxide
concentrations (Hawksworth and Rose, 1976; Smith et al., 1993; van Dobben, 1993).
Lichen communities provide information relevant to several key assessment questions, including those
concerning the contamination of natural resources, biodiversity, and sustainability of timber production
(Figure 7-1). Lichens not only indicate the health of our forests, but there is a clearly established linkage
to environmental stressors, as described below.
LICHEN
COMMUNITY
INDICATES
CONDITION OF
RESOURCE
Forest productivity,
biodiversity
ENVIRONMENTAL
STRESSORS
N- and S-bascd air
pollutants: direct loxicity
and acidifying and
fcrliliang effects.
Figure 7-1. Conceptual model of the lichen community indicator.
7.1.2 Summary of Method
The objectives of this task are to determine the presence and abundance of macrolichen species on
woody plants in each plot (using the 120-foot radius core of the plot) and to collect samples to be mailed
to lichen experts.
The method has two parts which are performed at the same time:
1. Make a collection of voucher specimens for identification by a specialist, the collection
representing the species diversity of macrolichens on the plot as fully as possible. The
population being sampled consists of all macrolichens occurring on woody plants, excluding the
0.5 m basal portions of trees and shrubs. Include fallen branches in your sampling.
2. Estimate the abundance of each species. Note that the crew member responsible for this task
is not required to accurately assign species names to the lichens (that is done later by a
specialist) but must be able to make distinctions among species.
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 3 of 11
7.7.3 Interferences
This method may be used in any season or weather condition. It should not be used in poor light,
however, because the method requires careful discrimination among species in the field. Therefore, it
should not be performed within an hour of sunset or sunrise, or during dark, rainy conditions. Another
common interference is to have a tough plot with other crew members who are impatient to leave the plot.
Chances are that you will have to wait for them at some point. Remind them of this and proceed with your
task, or, if it is a recurrent problem, discuss it with your crew leader to see if you can devise a more
equable work loads.
7.1.4 Safety
Only minor hazards are associated with the method. Care should be used when removing lichens
specimens with a knife or chisel. The knife should have a locking blade or fixed blade. Trees should not
be climbed to procure specimens.
7.2 Sample Collection, Preservation, and Storage
7.2.1 Sample Procurement (note: Portable Data Recorder not used)
1. Optimally collect a palm-size (about 5-10 cm in diameter) sample of fruticose and foliose growth
forms. This includes all species that are three-dimensional or flat and lobed. Even minute
fruticose and lobate forms should be included. Squamulose species and Cladonia squamules
lacking upright stalks should not be included. In many cases a much smaller sample should be
""obtained because of the scarcity of the species.
Collecting large samples improves the likelihood that the specialist can properly name your collections.
2. Place each specimen in a separate #2 brown paper bag and label the bag with appropriate codes:
Bag (species) number (sequentially as collected).
Relative abundance. (Feel free to revise this rating as collection proceeds and you become
more familiar with the plot.)
Often there will be more than one species on a given bark sample. If there is any chance of
ambiguity about which species in the bag corresponds with the abundance rating, write a
descriptive clarifying phrase, such as "the white one" or 'the sorediate one," on the bag.
Label the bag with an indelible marker. If the bags are damp, a soft pencil (No. 2 or softer) will work
better than an alcohol marker.
3. When finished for the day, or earlier as time allows, label all of the paper bags from that day with
the plot ID code (the hexagon code number for that plot). At this time you should add sequential
bag numbers if you did not do that in the field.
4. Be sure that the "Plot Packing Slip" (Figure 7-2) is completely filled out.
5. Place all of the specimen bags from a given plot WITH the Plot Packing Slip into a larger brown
paper bag. Record plot ID code, your name, and date on outside of bag. Fold the top of the large
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 4 of 11
bag closed. The redundancy in all of this labelling may seem unnecessary, but it has proved quite
helpful in resolving problems of mislabeled material.
6. Store bags in a dry place until you mail them. Specimens must be thoroughly air dried to avoid
fungal decay. If specimens were wet when collected, the individual bags should be spread out and
dried inside or in the sun as soon as possible.
7.2.2 Sample Mailing
After the first two plots are completed, mail the specimens to the lichen specialist right away. The
purpose of this is to allow immediate feedback to the field crews concerning specimen quality and quantity.
Thereafter, mail the bags each week or every other week to the lichen specialist. You should have the
name and address of the lichen specialist. In case of doubt, contact Bruce McCune (503-737-1741 or
mccuneb@bcc.orst.edu). Bags should be packed closely, but without excessive crushing, in sturdy
cardboard boxes. Bags from several plots can be mailed in the same box. Enclose in the box a Lichen
Specimen Mailing Form (Figure 7-3) specifying the box's contents. Extra copies of the Mailing Form can
be found in the notebook of lichen training materials under "Mailings."
Lichen Communities
PLOT PACKING SLIP
FHM, 1994
Plot hex number:.
Date:
State:
County:.
Crew Member's Name:
Crew number:
A copy of this sheet will be part of the permanent record for this plot. PLEASE COMPLETE
IT FULLY.
Record the time lichen sampling began:
Record the time lichen sampling ended:
Total time spent sampling the plot:
Comments about the plot, the lichens, the vegetation, and/or the weather:
REMEMBER:
Record the abundance code on each bag!
Remember to look for the common species.
Try to put only one species in each bag.
Figure 7-2. Plot packing slip for lichen communities. Complete this form and insert it into the bag containing all of the
smaller bags for a single plot.
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 5 of 11
LICHEN SPECIMEN MAILING FORM
Please enclose a copy of this form whenever these specimens are mailed. Keep a copy for your
records.
FIELD CREW TO LICHEN SPECIALIST:
Sent by:
Sender's comments:
Received:
Comments:
Date
to:
LICHEN SPECIALIST TO STORAGE:
Sent by:
Sender's comments:
Received:
Comments:
Date
to:
CONTENTS
Hex number
State
County
Notes
Figure 7-3. Form used for mailing lichen community specimens, one form per box.
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 6 of 11
7.3 Equipment and Supplies
7.3.1 Equipment and Apparatus
Locking-blade or fixed-blade knife (ca. 4" blade) with belt sheath.
• 14X hand lens (Bausch & Lomb Hastings Triplet).
• Fanny pack.
Regional guides for lichen identification. Different guides will be needed for different areas:
Northeast, Lake States, and Southeast:
Hale, M.E. 1979. How to Know the Lichens. 2nd Ed. Wm. C. Brown, Dubuque, Iowa.
Colorado, California, and Pacific Northwest:
Hale, M.E. and M. Cole. 1988. Lichens of California. University of California Press, Berkeley. 254
pp.
Hand pruners (useful for collecting small branch segments).
• 1-inch wide chisel (Northeast and Southeast only; useful for collecting samples from tough-barked
hardwoods. You may wish to make a sheath from a piece of cardboard and strapping tape or save
the plastic cap that comes on some chisels).
7.3.2 Consumable Supplies
• #2 brown paper bags (or next size smaller), averaging 20 per plot.
• Black waterproof markers for writing plot ID'S and abundance data on paper bags.
Larger brown paper bags (16.5 x 9.5 inch or similar size), one per plot.
Soft pencils (No. 2 or softer).
6 mailing forms (supplied in Lichen Community Training Manual).
7.4 Calibration and Standardization
Calibration and Standardization is not applicable in this section.
7.5 Quality Assurance
Data quality will be measured at (1) post-training certification, (2) field audits, and (3) plot
remeasurements. Each of these is discussed briefly below, and at length in the QA Project Plan. (Cline
et at., 1994) See also Subsection 7.5.6, "Method Performance," for QA results from recent years.
7.5.7 Measurement Quality Objectives (MQOs)
Data must be collected within certain standards of quality (Table 7-1). Remeasurements and audits
will be conducted during the field season as ways of evaluating data quality. Corrective action (retraining
and retesting) will be taken if standards are not met.
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 7 of 11
Table 7-1. Measurement Quality Objectives and Their Method of Assessment
MQO
Method of Assessment
Precision
Bias
Accuracy
Completeness
12% Deviation between index scores from repeat measurements of the same plot
12% Signed deviation from "true" index scores, as determined from expert data. In
practice, obtaining 65% or more of the expert's species will yield index scores that
meet this MQO
12% Absolute deviation from "true" index scores, as determined from expert data. In
practice, obtaining 65% or more of the expert's species will yield index scores that
meet this MQO
90% Percentage of forested plots with lichen data
Accuracy can be expressed in terms of the percent deviation between index scores of two independent
samples of the same lichen plot, one of which is collected by a lichen specialist and is considered the true
species composition. "Index scores" in this case tell where a plot falls on a climatic gradient and on an air
quality gradient. This percent deviation is calculated as:
100 * (expert's score - trainee's score) / length of the gradient.
The signed deviation expresses bias. The absolute deviation expresses accuracy. These calculations
are possible only for those regions that are in the "application phase" of the lichen community indicator,
meaning that a gradient model of lichen communities has already been constructed. As of March 1994,
this model is available only for the southeastern U.S. We have found, however, that if the trainee obtains
65% or better of the specialist's species list, the index scores will mostly fall within 10% of the expert's.
Therefore, this 65% figure is used as an operational goal for training, certification, and audits. It is referred
to below as our "field MQO", and is used as a readily calculated basis for providing rapid feedback to the
crew.
Precision is estimated from remeasurements of the same crew on the same plot. For the lichen
community indicator, it is assessed with the percent deviation between index scores, calculated as
100*(trainee's 1st score - trainee's 2nd score)/length of the gradient,
where index scores are calculated by applying the regional gradient model.
Another aspect of quality control is making sure that the voucher specimens are adequate, not
decomposed, and being received by the lichen specialist. If problems are perceived either by the field crew
or the lichen specialist, they should contact each other and/or the indicator lead.
7.5.2 Certification
Only people who have successfully completed lichen training and certification should collect the lichen
community data. You are certified by performing the lichen community method on a test plot and meeting
the field MQO (65% of the expert's species list). Your trainer completes a form (see QA Plan) that records
your score and certification. You will receive supplemental training and retesting if you fail the initial test.
7.5.3 Audits
Audits serve two primary purposes: (1) check in with the field crew to see if they are having any
difficulties with the method, and (2) documenting the data quality. The first objective is achieved by talking
with the crew, observing the method in progress, and providing immediate feedback. The second objective
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 8 of 11
is met by calculating numerical scores (comparing results to those of the lichen specialist) based on the
field crew sampling a plot without interference from the auditor. One or more plots will be examined per
audit. The lichen community audit proceeds in four steps. Note that the early steps provide immediate
feedback to the crew, but the later steps quantify the data quality with increasing rigor.
1. The auditor asks the crew member if they have questions concerning the method before the
sampling begins, then discusses those problems with the crew member. (If time allows the auditor
to be present for two plots, the first plot should be done more interactively, with the specialist
helping the crew rather than as a test plot.)
2. The auditor then allows the crew member to sample on their own but observing at a distance the
manner in which the crew member covers the plot. At the end of the plot, the lichen specialist then
quickly assesses the number and quality of specimens and provides immediate feedback on the
specimens and other aspects of technique (for example, if the person camps out on one tree and
doesn't see a lot of the plot). Normally it is fairly easy for a specialist to judge how well someone
is doing, even before the final scores are in.
3. The specialist identifies the lichens, then evaluates the number of species obtained by the crew
member as a percentage of the specialist's. These values are reported by the specialist to the
Indicator lead and crew member as soon as possible. In some cases this can be reported to the
crew member in the field, but if time or weather does not allow complete field identifications by the
specialist, those figures may be delayed by a week. In the past we have found that if trainees
obtain 65% or better of the number of species obtained by the specialist, the plot index scores
(item 4 below) will mostly fall within 10% of the specialist's.
4. After the data are delivered from the specialist to the indicator lead, the species scores for both
the crews and the specialists are entered into data files. The indicator lead then calculates plot
index scores for each QA plot for both the crews and the specialists. This requires application of
the multivariate lichen gradient model for that specific region. Until those models are built for each
region, the results cannot be delivered during the field season. The crew's score is then expressed
as a deviation from the expert's. This is the most important numerical descriptor of the data
quality, because it takes into account the mix and abundance of species.
7.5.4 Remeasurements
Plot remeasurements are an important part of ensuring comparability between crews and between
years. Each region is handling this QA task in different ways. "Reference crews" resample selected plots
done by the regular field crews. Alternatively, "reference plots" are sampled by multiple crews and/or by
a single crew on multiple dates. Your crew leader will inform you about the remeasurement method used
In your area.
7.5.5 Debriefing
We schedule time at the end of the field season to leam from you. This will happen via a questionnaire
(see QA plan). In some cases a lichen specialist or their representative will solicit feedback from you in
person. Your comments during debriefing are collated and summarized by the indicator lead and become
part of the basis for improving the method for next year.
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 9 of 11
7.5.6 Method Performance
The performance of the method is assessed by evaluating measurement quality objectives (MQOs) for
precision, accuracy, and completeness. Our QA results from the 1993 Southeast and SAMAB
demonstrations are summarized below (Table 7-2). Average accuracy and bias are expressed with respect
to index scores on two lichen community gradients. Gradient 1 is a regional climatic gradient. Gradient
2 is an air quality gradient. The MQO of 90% completeness was exceeded.
Table 7-2. Summary of 1993 SE and SAMAB Demonstrations Lichen Community Data Quality
% Deviation from expert
No. of Gradient 1 Gradient 2
Species, % of Index Index
expert
QA activity Ace. Bias Ace. Bias
Certifications (N=7)
Audits (N=3)
Reference Plots* (N=16)
74%
50%
61%
2.7
10.3
4.4
+2.4
+3.7
+2.4
2.1
6.0
11.1
-2.1
+2.7
-10.5
* excluding two minimal-effort outliers
7.6 Procedure
1. The area to be sampled (henceforth the "lichen plot") is a circular area with 120-foot radius
centered on the macroplot, excluding the four subplots (see Figure 7-4). The area of the lichen
plot is 40715 ft2 = 3782 m2 = 0.378 ha = 0.935 acres.
(Note: For off-frame applications where subplots have NOT been set up, an equal area is sampled by
using a 34.7 m = 114 ft radius circular plot, sampling the whole area within that radius.)
2. Record the time sampling begins on the "Plot Packing Slip" (you will be given a supply of these
at the beginning of the field season). Sampling continues for a maximum of two hours or until 10
minutes elapse with no additional species recorded. At least 45 minutes in the East and 30
minutes in the West must be spent searching the plot, even if very few lichens are present.
3. Take a reconnaissance walk through the lichen plot, locating lichen epiphytes on woody plants and
collecting voucher samples and assigning abundances as you go. The following method is
suggested. Begin at approximately 100 ft due north from plot center, measuring with your eye to
the limiting boundary of 120 ft and continue to the right in a sinuous manner until you reach the
perimeter of subplot 3. (The perimeter of the subplot will have been flagged.) The same
procedure is followed between subplots 3 & 4 and 4 & 2. The idea behind this approach is that
you can scan the whole area but intensely scrutinize selected areas to best represent the diversity
on the plot (see item 6 for more details). If time allows, make additional circuits of the plot,
searching for substrates or spots that were not visited on the first pass.
4. Lichen species with the following growth forms will be collected: fruticose and foliose (i.e.,
macrolichens).
5. Inspect woody plants (trees and shrubs > 0.5 m tall) within the lichen plot for lichen species.
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 10 of 11
Subplot
24.0' radius
Annular plot
59.9' radius .
Distance between
points is 120°
Azimuth 1-2 360°
Azimuth 1-3 120°
Azimuth 1-4 240
Microplot
6.8' radius
12'offset
90° az. from
subplot center
Figure 7-4. Lichen sampling area. The shaded area is the "lichen plot."
6. Be careful to inspect the full range of substrates and microhabitats available: shaded and exposed,
conifers and hardwoods, fallen upper branches and lower branches, large shrubs, and trees in
particular topographic positions (for example, you would check in a draw or ravine on an otherwise
uniform slope, so long as it occurs within the lichen plot). Rotten logs or other semi-permanent
features of the forest floor should NOT be sampled. Also, stumps should not be sampled.
7. Abundance ratings. Record relative abundance within the lichen plot. Relative abundance for each
species is estimated as follows:
Code Abundance
1 Rare (< 3 individuals in area)
2 Uncommon (4-10 individuals in area)
3 Common (> 10 individuals in area but less than half of the boles and branches have that
species present)
4 Abundant (more than half of boles and branches have the subject species present)
8. Collect a sample of each putative species, place it in a small paper bag, label the bag with a hex
number (you can do this at the end of the day), bag number (sequentially as collected), and record
relative abundance. Feel free to revise the abundance rating as collection proceeds. Also record
any comments on the outside of the bag. For more details, see "Sample Procurement" above.
After completing the task, check each bag to be sure that each bag has a hex ID code number and
abundance code.
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EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 11 of 11
9. How to handle uncertainties: The field crew will frequently have uncertainties about the
classification of an organism. The following rules for the field crew are designed to put the onus
of the responsibility for classification on the specialist, not the field crew.
a. When in doubt, assume it is a lichen.
b. When the growth form is in doubt, assume it is a macrolichen.
c. When species distinctions are in doubt, assume that two different forms are different species.
The purpose of these rules is to encourage the field crew to make as many distinctions in the field as
possible. The specialist can later adjust the data by excluding specimens that are not macrolichens and
by combining forms that were considered separately by the field crew but are actually the same species.
For more information, see the material distributed at your training session.
10. Wrap-up. Complete the "Plot Packing Slip." Record the time lichen sampling ended and any other
comments about the plot, the lichens, the vegetation, weather conditions, your mood, etc. This
is important information for future evaluations of the relationship between effort and data quality.
There may also be extenuating factors that allowed you to do an especially good job on this plot
(a recent storm blew down lots of fresh branches) or an especially bad job (it was dark).
7.7 References
Brodo, I. M. 1991. Lichens of the Ottawa Region. National Museums of Canada.
Dey, J. P. 1978. Fruticose and foliose lichens of the high-mountain areas of the southern
Appalachians. Bryologist 81:1 -93.
Hale, M.E. 1979. How to Know the Lichens. 2nd Ed. Wm. C. Brown, Dubuque, Iowa.
Hale, M.E. and M. Cole. 1988. Lichens of California. University of California Press, Berkeley. 254 pp.
McCune, B. 1988. Lichen communities along O3 and SO2 gradients in Indianapolis. Bryologist 91:
223-228.
McCune, B. 1992. Field Key to the Lichens of the Northwest Forests West of the Cascade Crest. Dept.
Botany and Plant Pathology, Oregon State University, Corvallis. 19 pp.
McCune, B. and J. Peck. 1994. Lichen Communities Training Document. Oregon State University,
Department of Botany and Plant Pathology, Corvallis, Oregon.
Smith, C., L. Geiser, L. Gough, B. McCune, B. Ryan, and R. Showman. 1993. Species and
communities. Chapter 4 In Lichen as Bioindicators of Air Quality. USDA Forest Service Gen. Tech.
Rep. RM-224.
van Dobben, H. 1993. Vegetation as a monitor for deposition of nitrogen and acidity. PhD
Dissertation, Utrecht University, Netherlands. 214 pp. (privately published)
Vitt, D.H., J.E. Marsh, and R.B. Bovey. 1988. Mosses Lichens and Ferns of Northwest North America.
Lonepine Publishing. 296 pp.
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 1 of 12
Section 8. Field Logistics
Section/Title
Page
8.1 Overview 2 of 12
8.2 Training : 2 of12
8.3 Field Logistics 3 of 12
8.3.1 Sampling Responsibilities 3 of 12
8.3.2 Work Flow 4 of 12
8.3.3 Crew Responsibilities and Activities 6 of 12
8.3.3.1 Sampling Schedule 6 of 12
8.3.3.2 Assembly of Field Crew 6 of 12
8.3.3.3 Transportation 7 of 12
8.3.3.4 Sampling Site Location 7 of 12
8.3.3.5 Plot Establishment 7 of 12
8.3.3.6 Ensuring Adherence to Sampling Protocol 7 of 12
8.3.3.7 Ensuring Proper Use of Field Equipment 7 of 12
8.3.3.8 Equipment Maintenance 8 of 12
8.3.3.9 Maintaining Site Integrity 8 of 12
8.3.3.10 Daily Communication 8 of 12
8.4 Data Transfer and Sample Handling 9 of 12
8.4.1 Data Transfer 9 of 12
8.4.2 Sample and Voucher Specimens Handling 9 of 12
8.4.3 Sample Maintenance Until Shipping 9 of 12
8.4.4 Sample Transfer and Tracking 10 of 12
8.4.5 Sample Shipping 10 of 12
8.4.6 Shipping Destinations . 10 of 12
8.5 Debriefing 12 of 12
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 2 of 12
8.1 Overview
Each Forest Health Monitoring (FHM) region conducts logistics in a manner most suitable for the
requirements and constraints of that region. While crew configuration and/or coordination activities may
vary across states and regions, the measurement and collection protocols remain constant. The following
section describes field personnel responsibilities and activities and suggests a number of possible sampling
scenarios. Additionally, this section discusses training, sample maintenance, data transfer and debriefing
activities.
Ultimately, each region and crew type will develop field logistics optimal for their specific requirements
and constraints. FHM crew types, definitions, and the regions or states of implementation are provided in
Table 8-1.
8.2 Training
Field activities are preceded by training and certification. Training activities start with national
pretraining where the indicator leads train regional instructors or trainers. All regional trainers must
complete training and be certified prior to training regional or state field crews. In 1994, pretraining will be
held May 2-6, in Asheville, NC.
Regional and state training sessions are held following pretraining. After completing training, trainers
will test the field crew personnel for comparability. Upon satisfactory completion of the test, personnel will
be considered certified. The primary objective of the certification process is for field personnel to
demonstrate proficiency in established, fixed, measurement protocols, ease of adherence to established
guidelines and to be able to perform comparably between the FHM regions.
Immediately following certification, crews will visit practice/training plots before beginning formal FHM
field collection.
Table 8-1. FHM Crew Types, Definitions, and Regions or States Implementation ^^^
CREW TYPES
DEFINITION
REGION/STATE
Forester or Core4 crew
Botany Crew
Interpenetrating or 1/4 crew
Two-person crew which measures site
condition, growth, and regeneration,
crown classification, damage and
mortality assessment, and ozone
bioindicator plants. This crew, when
visiting a plot with a botanist crew, may
assist with PAR and lichen community
variables.
Two-person crew with at least one who
is qualified as a field botanist. This
crew measures vegetation structure,
PAR, and lichen community variables.
This crew may assist with ozone
bioindicator plants if time allows.
Three- or four-person crew which
measures site condition, growth, and
regeneration, crown classification,
damage and mortality assessment,
ozone bioindicator plants (eastern
crews only), vegetation structure, PAR,
and lichen community variables.
North, South (Alabama [AL])
North, South (AL)
Three person crew: Southeast (Georgia
[GA], Virginia [VA]), and Intermountain
(Colorado [CO])
Four person crew: West (California
[CA]) and Pacific Northwest Pilot Study
(PNW PS).
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 3 of 12
8.3 Field Logistics
8.3.1 Sampling Responsibilities
In all regions each crew member will be required to assume full responsibility for specific tasks. Listed
below are suggestions for the key position assignment per region and/or crew type.
Table 8-2. FHM Key Positions per Region and Crew Type
ACTIVITY
Sampling Schedule
"Srevi Assembly &
Coordination (Crew Leader)
CREW TYPE
Forester Crew
Botanist Crew
1/4 Crew
"Fb7esteF& 1/4 crews
Botanist Crew
LEAD
State Coordinator
Field Coordinator
Field Coordinator
"Forester I
Botanist I (Bot. Crew will
REGION/STATE
North, AL
North, AL
GA, VA, CO, CA, PNW PS
"North, AL, GA, VA", CO, CA,
PNW PS
North, AL
"TransplirtaTion To site"
"SltoTocatton
"WoFestabiishrnerit
"Slte~6on<5for7. Growth""
Regeneration. Crown
Condition Classification,
Damage and Mortality
Assessment (Tally)
Forester & 1/4 crews
Botanist crew
""FbresterT "Bofahlsf& 174 '
crews
~ "ForesterT "Botanist"& 177esteF&~l74 Grew"
Botanist Crew
All
~ Forester (I
Botanist II
Forester II & Botanist
Forester II & Logistician
""KiresteFl
Botanist I
"AT"
North, AL
North, AL
CO, GA, VA
CA, PNW PS
"Communications"'
PNW PS
North, AL
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 4 of 12
Field personnel will each have primary responsibility for completion of one or more tasks as shown in
Tables 8-2. While task completion may require more than one individual's effort, there will be one person
assigned to assume full accountability. Some of the crew members will be cross-trained in several other
measurement indicators other than those specifically assigned to them, yet varies per region. Cross-
training is beneficial because the time some task requires depends on plot location and condition. As the
crews become more familiar and proficient, the field personnel can redistribute workloads to increase
efficiency and productivity. However, if a crew member has not been trained and certified to carry out a
task, then they can not make the measurement. Even if a crew member, who was cross-trained/certified,
samples on a particular day, the crew member originally assigned still has primary responsibility for a
particular indicator measurement and remains accountable for quality and completion of that measurement.
8.3.2 Work Flow
Tables 8-3 approximates the amount of time estimated for task completion for all preparation, sampling,
and data/sample management activities.
Tables 8-4 through 8-8 suggests just one field work flow pattern possible per crew scenario and region.
Ultimately, each region/state will develop the work flow pattern best suited for that area.
In general, the forester I and forester II will be working together for the majority of the day. Their tasks
are plot establishment, site condition, growth and regeneration, visual crown rating, and damage and
mortality measurements. When ozone bioindicator plants are collected within the assigned two-week
window, the forester I and II will collect those samples as well. The botanist will be responsible for
vegetation structure. Other measurements, such as PAR and lichen community, can be measured and
collected by the forester I, II, botanist I, II, or logistician depending on the region.
Sample handling and shipping and data transfer will be the responsibility of the measurer as assigned
within a region. For example, in the North and Northeast, the botanist I will transfer vegetation data and
handle and ship vegetation samples, while the botanist II will transfer PAR measurements and handle and
ship the lichen samples.
A number of voucher specimens will be collected at each plot. These will be prepared and analyzed
and incur a significant cost from collection through analysis and interpretation. It is imperative that their
integrity be maintained. All samples must be dried first. The person who collects the sample is responsible
for packaging and labeling it in the field and in handling and shipping from the hotel or office.
Table 8-3. Field Work Time Allocation
Measurements
Plot establishment
Mensuration/
Crowns/Damage
Samples
Collected
no
no
Forester I
1 hour
5 hour
Forester II
1 hour
5 hour
Botanist I
.5 hour
N/A
Botanist II
.5 hour
N/A
Logistician
.5 hour
N/A
PAR (Set-up, measurements
and ambient sensor check)
no
N/A
2 hour
N/A
2 hour
2 hour
Lichen community
Vegetation Structure
Ozone Bioindicator Plants
(Two-week window only)
yes
yes
yes
N/A
N/A
1 hour
2 hour
N/A
1 hour
2 hour
6 hour
N/A
2 hour
N/A
N/A
2 hour
N/A
N/A
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 5 of 12
Table 8-4. Suggested Work Flow Pattern (Forester and Botanist Crew Working Together on 1/4 Plot)
Wow /.-Forester I, II establish plot. Botanist I establishes Vegetation Structure (VS) quadrants. Botanist II sets up PAR
ambient station and flags PAR measuring points.
Hour 2: Forester I, II begin Site Condition, Growth, and Regeneration/Crowns/Damage (Tally) sampling. Botanist I begins VS
sampling. Botanist II begins lichen community sampling.
Hour 3: Forester I, II continue Tally sampling. Botanist I continues VS sampling. Botanist II continues lichen community
sampling until complete.
How4:Forester I, II continue Tally sampling. Botanist I continues VS sampling. Botanist II carries out PAR sampling (*) until
complete.
Hour 5: Forester I, II continue Tally sampling until complete. Botanist II continues PAR sampling until complete.
Forester I, II carry out Ozone Bioindicator Plants sampling during two-week window only. Forester I, II may leave plot upon
completion of Tally and Ozone. Botanist I & II continue VS sampling until complete.
(*) PAR must be done between 1200 to 1400. Foresters assist Botanist with PAR, lichen community or vegetation structure if
time allows.
Table 8-5. Suggested Work Flow Pattern (Forester Crews - Mt2 Plots)
Full Day: Forester I, II begin Mt2 Tally sampling. Forester I, II carry Ozone Bioindicator Plants sampling during two-week
window only. .
Table 8-6. Suggested Work Flow Pattern (Forester Crews - Mt1/3 Plots/No PAR,
Lichens or Vegetation Measurements Being Collected)
Hour 1: Forester I, II establish plot.
Remaining Day: Forester I. II begin Mt1 Tally sampling. Forester I, II carry out Ozone Bioindicator Plants sampling during two-
week window only.
Table 8-7. Suggested Work Flow Pattern (1/4 Crew (CO))
Hour 1: Forester I, II establish plot. Botanist establishes VS (Vegetation Structure) quadrants. Forester II sets up PAR
ambient station and flags PAR measuring points.
Hour 2: Forester I. II begin Tally sampling. Botanist begins VS sampling.
Hour 3: Forester I, II continue Tally sampling. Botanist continues VS sampling.
Hour 4: Forester I continues Tally sampling. Botanist' begins Lichen Communities sampling. Forester II begins PAR
measurements.
Hour 5: Forester I continues Tally sampling. Botanist continues Lichen Communities sampling until complete. Forester II
begins PAR measurements until complete.
Hour 6: Forester I, II continue Tally sampling until complete. Botanist continues VS sampling until complete.
(*) PAR must be done between 1200 to 1400.
'Forester I may assist or replace Botanist when sampling Lichens, if time allows.
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 6 of 12
Table 8-8. Suggested Work Flow Pattern (1/4 Crew (CA & PNW Pilot Study))
Hour 1: Forester I, II establish plot. Botanist establishes VS (Vegetation Structure) quadrants. Logistician sets up PAR
ambient station and flags PAR measuring points.
Hour 2: Forester I, II begin Tally sampling. Botanist and Logistician begin VS sampling.
Hour 3: Forester I, II continue Tally sampling. Botanist and Logistician continue VS sampling.
Hour 4: Forester I continues Tally sampling. Forester II begins Lichen Communities sampling. Logistician begins PAR
measurements. Botanist continues VS sampling.
Hour 5: Forester I continues Tally sampling. Forester II continues Lichen Communities sampling until complete. Logistician
continues PAR measurements until complete. Botanist continues VS sampling.
Hour 6: Forester I, II continue Tally sampling until complete. Botanist and Logistician continue VS sampling until complete.
(*) PAR must be done between 1200 to 1400. Forester I & II may assist Botanist and Logistician if time allows.
8.3.3 Crew Responsibilities and Activities
The crew's daily field activities will be supervised by one member of the crew who will be designated
by the field coordinator. The crew leader will supervise all field operations and, if necessary, resolve all
discrepancies or issues at the site. The field crew leader has the responsibility of:
• Maintaining sampling schedule.
• Assembly of field crew.
• Transportation to the sampling site.
• Ensuring adherence to sampling protocol.
• Ensuring proper use of field equipment.
• Maintaining site integrity.
• Daily communication.
Any crew member can be assigned to serve as crew lead.
8.3.3.1 Sampling Schedule
The initial sampling schedule will be coordinated by the field or state coordinator. The field or state
coordinator will work with the crew leader to determine the most appropriate timeline and seasonal itinerary
to meet program goals yet maintain sample integrity and crew morale. The crew leader will be responsible
for sampling a certain number of plots within an index period and have ultimate responsibility to meet
sampling quota while maintaining the quality of the measurements and samples and following standard
protocol. The crew leader must also be attentive in assessing field crew morale while planning a productive
sampling schedule.
8.3.3.2 Assembly of Field Crew
Each crew must assemble at an appropriate, pre-determined time and place each scheduled sampling
day, generally designated by the crew leader. Each crew member should be given the opportunity to note
the location and route to the plot, and review site specific safety information. The crew leader will also
determine rendezvous points to assemble the crew after scheduled time off (i. e., after weekends, holidays).
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 7 of 12
8.3.3.3 Transportation
The crew leader should assign transportation responsibility within the crew. This individual will be
responsible for providing and maintaining overall adequate, efficient transportation to the sample site, as
well as hotel accommodations and eating establishments, if plot location and schedule require. Most of
the crew members will be assigned a field vehicle and will be responsible for the care and maintenance
of that vehicle. Crews must make efficient.use of vehicles and not use the vehicles for non-work related
activities unless otherwise approved by the field or state coordinator.
8.3.3.4 Sampling Site Location
In some states, FIA photopoints are used for the sampling plots. Other plot locations are based on
the EMAP hex grid system. Information packets pertaining to each sampling sites should be provided by
the field or state coordinator and include maps, landowner information, local emergency information, and
any existing directions to the plots. Foresters will follow standard FIA protocol in locating sampling sites.
Procedures for this activity are detailed in Section 1.
8.3.3.5 Plot Establishment
The forester I and forester II will be responsible for establishing the plot. Details of this procedure are
provided in Section 1. However, Section 1 only details establishment of the plot for tally. Vegetation
structure and PAR subplots must also be established. It is very important that the plot establishment be
accomplished in a sequence that 1) maintains plot integrity for other measurements (i.e., regeneration
measurements before vegetation structure measurements), and 2) allows field crew members to start data
collection activities as soon as possible in order to finish sampling within a reasonable timeframe. To
accomplish this, the foresters should work with the botanist (s) and/or logistician to develop a standard plot
layout procedure appropriate for their specific field crew.
8.3.3.6 Ensuring Adherence to Sampling Protocol
The crew leader is expected to have a basic knowledge of all sampling procedures and be able to
determine whether crew members are adhering to sampling protocols. It is suggested that the crew attend
all possible additional training sessions to become familiar with other crew members' sampling tasks. If
protocols appear to be inconsistent or arc- being misinterpreted, the crew leader should address the
inconsistency during communications update with field or state coordinators, who should contact regional
indicator leads. It is of primary importance that problems be rectified prior to visiting another FHM plot.
8.3.3.7 Ensuring Proper Use of Field Equipment
Some field equipment will require special care (i.e., PDRs, laptop computers, printers, ceptometers and
dataloggers) and proper use. The assigned crew member(s) must be familiar with the proper use of
equipment and if necessary assist crew members if problems occur. Crew members will inform the crew
leader of equipment that is destroyed or in need of repair. The crew leader is responsible for addressing
the equipment problems. For those crews which communicate via the EPA VAX network, equipment needs
or repairs can be communicated in the note section of the daily communication update. For those without
VAX capabilities, equipment needs or repairs can be communicated to field or state coordinators via
telephone.
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 8 of 12
8.3.3.8 Equipment Maintenance
During orientation and training, each field crew member will be provided equipment and an inventory
list of the equipment they will receive. If equipment is damaged during field activities, the item should be
identified on the inventory list and the service or repair that may be required should be specified. The crew
members must inform the crew leader, who will inform the field coordinator of the damaged equipment.
The crew leader is responsible for disclosing this information through the periodic communications update.
If available, the field crew member will use replacement equipment. If supplies run low or an item of
equipment is needed, notify the field coordinator by means of the VAX or DG computer system or
telephone.
At the end of the field season, crews will return all equipment to the field coordinator. The field
coordinator and each crew member will check off each item on the inventory list that was provided at the
beginning of the field season to each field crew member. All items must be accounted. Items will be
inspected for damage and their condition recorded.
8.3.3.9 Maintaining Site Integrity
During sampling, flagging will be placed around the site to mark various sampling points (vegetation
and PAR measurement points). All flagging must be removed after sampling has been completed. The
crew leader will be responsible for maintaining plot integrity and anonymity when sampling is completed
and will direct all of the crew members to assist in these activities.
8.3.3.10 Daily Communication
Regional field communications vary. Forester crews usually will be able to depend on the telephone
to communicate with field or state coordinators, while botanist and 1/4 crew communications most likely
will be able to communicate electronically through laptop computers using the telephone system in the hotel
the crew is staying or an available office. A communications package and modem will connect the laptop
computer to either the VAX or DG computer systems. When using the VAX, an "update" screen will appear
and request the following information:
• Field Crew ID.
• Visitor(s) (i.e., auditors, Indicator leads).
Field crew location (hotel name, address, telephone number).
• Expected location of next day.
• Hexagon sampled that day and data collected on the plot.
• Comments/Problems/Mail messages to other crews and/or non-field personnel.
The botanist or forester II may fill out the update; however, it is the crew leader's responsibility to make
sure that the update is filled out each night the field crew is collecting data, whether or not data is
transmitted that night. This update will be electronically sent to the VAX computer which will then be used
to update DG and EMAIL accounts of appropriate individuals in FHM. The crew leader is also required to
read all incoming communications to the crew and make sure all messages are relayed to appropriate
individuals. Instructions for this operation are presented in the FHM PDR Guide.
Some hotels have hardwire phone lines, prohibiting the connection of the laptop to the telephone
system. In this instance, the crew should contact their field or state coordinator via telephone. Additionally,
the data collected for that day and sample tracking information should be loaded on a floppy disk. The
floppy disk is created each time a shipment of samples is created.
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 9 of 12
If communication using the laptop computer or the telephone is impossible, then the crew leader is
responsible for calling the field or state coordinator as soon as possible. The appropriate telephone
numbers and times of contact for the field coordinator will be given during regional training.
8.4 Data Transfer and Sample Handling
All field positions are responsibility for the following activities:
• Data transfer.
• Sample maintenance.
• Sample transfer and tracking.
• Sample shipping.
8.4.1 Data Transfer
Completed data from PDRs and ceptometers must be uploaded to laptop computers daily and
transferred to the VAX computer. Instructions for these operations are presented in the FHM PDR Guide.
8.4.2 Sample and Voucher Specimens Handling
Vegetation voucher specimens lichen samples, and ozone bioindicator plant voucher specimens will
be collected from the plots. The number of samples and vouchers expected from each plot are identified
in the appropriate methods section.
8.4.3 Sample Maintenance Until Shipping
All samples and vouchers should be packaged by the field crew in a manner that will maintain integrity.
Vegetation voucher specimens are to be placed in zip-lock bags or arranged in a magazine (See Section
5) until they can be placed into a plant press later that day. Ozone bioindicator plant voucher specimens
are to be placed in a plant press in the field. More specific sample handling instructions are outlined below.
Lichens
1.' Lichen samples will be carried off the plot in the labeled #2 brown paper bags by the collector.
Bags will be appropriately marked with the words "Lichen Community."
2. If specimens were wet when collected, then the individual bags should be spread out and left with
the tops open for the evening in the hotel room in order to dry out the samples.
3. Place all voucher bags from a given plot into a larger brown paper bags. Record plot ID code and
date.
4. Staple or tape the top of the large bag closed and store in a dry place.
Vegetation Voucher Specimens
1. The vegetation voucher specimens will be carried off the plot placed between the pages of
magazines or in labeled zip-lock bags arranged in a three-ring binder notebook.
2. After every day of sampling, the botanist will place the specimens in a plant press to dry.
Ozone Bioindicator Voucher Specimens (East only)
1. The ozone bioindicator voucher specimens will be carried off the plot in a plant press, each sample
with a label with the plot number and date collected.
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 10 of 12
2. Fill out the upper half of a "Sample Voucher Sheet" the same day of collection for each ozone
bioindicator voucher specimen.
3. After samples are dried and pressed, they should be placed in a unsealed ziplock bag, each
accompanied with its corresponding "Sample Voucher Sheet."
8.4.4 Sample Transfer and Tracking
Samples and specimens must be tracked as they are transferred from field to hotel/office to herbaria,
laboratory, or indicator lead. Each big bag of lichens (which contains all lichens from one plot) is to be
treated as an individual sample and given just one sample number. Each plot's worth of vegetation
vouchers is to be treated as one sample and given just sample number. Each plot's worth of bioindicator
plant vouchers is to be treated as one sample and given just one sample number.
Procedure
1. Vegetation voucher specimens will be sent in boxes as soon as they are dry on a weekly basis.
Ozone bioindicator plant specimens will be sent by regular mail at the close of the ozone
bioindicator evaluation window (Northeast, August 19 and Southeast, August 12). Lichen samples
will be shipped by regular mail in separate boxes as soon as a box is full.
5.4.5 Sample Shipping
Administrative shipping protocols vary per region. The field crews will be either provided with a number
of Federal Express shipping labels or directed to cover the cost of shipping/mailing to be reimbursed per
regional protocol. The field coordinator will provide more specific guidance per region or crew. When using
Federal Express, the crew may call Federal Express (800-238-5355) and arrange for pickup of the
packages at the hotel/office.
8.4.6 Shipping Destinations
Once the samples are packed, they should be shipped according to sample. Ozone bioindicator plant
voucher specimens must be pressed and dried prior to shipping to:
Gretchen Smith
Department Forestry, Holdsworth Hall
University of Massachusetts
Amherst, MA 01003
(413)545-1680
Vegetation voucher specimens, having been pressed and dried, should be sent as soon as possible to the
respective regional herbium at:
California:
Attention: FHM
Herbium, Department of Botany
CordieyHall 2082
Corvallis, OR 97331-2902
(503) 737-4106
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 11 of 12
Colorado:
Renee O'Brien
USDA Forest Service
507 25th St.
Ogden. UT 84401
(801) 625-5371
PNW Pilot Study:
Attention: FHM
Herbium, Department of Botany
CordleyHall 2082
Corvallis, OR 97331-2902
(503) 737-4106
Southeast/Southern:
Dr. B. E. Woffard
University of Tennessee
Department of Botany
437 Hesler Biology Building
Knoxville, TN 37996
(615)974-6212
New England and Lake States:
Dr. Garrett Crow
Department of Plant Biology
Neismith Hall
University of New Hampshire
Durham, NH 03824
(603) 862-3865
Maryland and New Jersey:
Herbarium Curator
Department of Biology
West Virginia University
Morgantown, WV 26506-6057
(304) 293-5201
Lichen samples should be thoroughly air-dried and sent when the box is full to the appropriate regional
lead:
California, PNW Pilot Study & Colorado:
Bruce Ryan
Department of Botany & Microbiology
Arizona State University
Tempe, AZ 85287
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EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 12 of 12
Southeast/ June 13 - July 21:
Jonathan Dey
Biology Department
Illinois Wesleyan University
Bloomington, Illinois 61702
(309) 556-3057
Southeast/July 22 - end of season:
Karin Heiman
50 Rector Branch Road
Marshall, NC 28753
(704) 649-3804
Northeast
Susan Will-Wolf
Department of Botany, Birge Hall
University of Wisconsin
430 Lincoln Dr.
Madison, Wl 53705-1381
(608) 262-2179
8.5 Debriefing
Upon completion of field activities, crews will be given an opportunity to evaluate the field activities,
measurement protocols, the Field Guide, and logistics. Initially, crews will be given a "Debriefing
Questionnaire" to complete prior to any formal debriefing meeting. In some areas, the questionnaires are
tallied and the results are presented at the debriefing meeting. The debriefing lends crews an opportunity
to further present and discuss issues. These meetings are held soon after field collection is finished in late
August or September.
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EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 1 of 8
Appendix A
U.S. Tree Species Codes
Most species encountered in the continental United States and considered to be trees by FHM are
listed below. When in doubt about whether a species not listed is a tree, consult your Field Supervisor.
Western woodland species are prefaced with "(ww)".
Code
Common Name
Genus
Species
010 firsp.
011 Pacific silver fir
012 balsam fir
014 bristlecone fir
015 white fir
016 Fraserfir
017 grand fir
018 corkbark fir
019 subalpinefir
020 California red fir
021 Shasta red fir
022 noble fir
041 Port-Orford-cedar
042 Alaska-Yeilow-cedar
043 Atlantic white-cedar
050 Cypress
051 Arizona cypress
052 Baker cypress
058 (ww) Pinchot juniper
059 (ww) Red berry juniper
060 Redcedar/Juniper
061 Ashe juniper
062 (ww) California juniper
063 (ww) Alligator juniper
064 (ww) Western juniper
065 (ww) Utah juniper
066 (ww) Rocky Mountain juniper
067 southern redcedar
-Softwoods-
Abies
Abies
Abies
Abies
Abies
Abies
Abies
Abies
Abies
Abies
Abies
Abies
Chamaecyparis
Chamaecyparis
Chamaecyparis
Cupressus
Cupressus
Cupressus
Juniperis
Juniperis
Juniperis
Juniperis
Juniperis
Juniperis
Juniperis
Juniperis
Juniperus
Juniperus
sp.
amabilis
balsamea
bracteata
concolor
fraseri
grandis
lasiocarpa var. arizonica
lasiocarpa
rnagnifica var. magnifica
magnifica var. shastensis
procera
lawsoniana
nootkatensis
thyoides
sp.
arizonica
bakeri
pinchotii
erythrocarpa
sp.
ashei
Californica
deppeana
occidentalis
osteosperma
scopulorum
sillcicola
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EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 2 of 8
Code Common Name Genus Species
Softwoods
068
069 (ww)
-070
071
072
073
081
090
091
092
093
094
095
096
097
098
101
102
103
104
105
1 06 (ww)
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
eastern redcedar
one-seed juniper
larch (introduced)
tamarack (native)
subalpine larch
western larch
incense-cedar
spruce
Norway spruce
Brewer spruce
Engelmann spruce
white spruce
black spruce
blue spruce
red spruce
Sitka spruce
whitebark pine
bristlecone pine
knobcone pine
foxtail pine
jack pine
common pinyon
sand pine
lodgepole pine
coulter pine
shortleaf pine
slash pine
Apache pine
limber pine
Mexican white pine
spruce pine
Jeffrey pine
Sugar pine
Chihuahua pine
Western white pine
bishop pine
longleaf pine
ponderosa pine
table mountain pine
monterey pine
red pine
Juniperus
Juniperis
Larix
Larix
Larix
Larix
Libocedrus
Picea
Picea
Picea
Picea
Picea
Picea
Picea
Picea
Picea
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
virginiana
monosperma
sp.
laricina
lyallii
occidentallis
decurrens
sp.
abies
breweriana
engelmannii
glauca
mariana
pungens
rubens
sitchensis
albicaulis
aristata
attenuate
balfouriana
banksiana
edulis
clausa
contorta
coulteri
echinata
elliottii
engelmannii
flexilis var. reflexa
flexilis var. reflexa
glabra
jeffreyi
lambertiana
leiophylla
monticola
muricata
palustris
ponderosa
pungens
radiata
resinosa
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Code
EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 3 of 8
Common Name Genus Species
126 pitch pine
127 Grey pine
128 pond pine
129 eastern white pine
130 Scotch pine
131 loblolly pine
132 Virginia pine
133 (ww) Singleleaf pinyon
134 (ww) Border pinyon
135 Arizona pine
136 southwestern white pine
137 washoe pine
138 four-leaf pine
139 Austrian pine
140 (ww) Mexican pinyon pine
201 bigcone Douglas-fir
202 Douglas-fir
211 redwood
212 giant sequoia
221 baldcypress
222 pondcypress
231 Pacific yew
241 northern white-cedar
242 western redcedar
251 California torreya
260 hemlock
261 eastern hemlock
262 Carolina hemlock
263 western hemlock
264 mountain hemlock
300 (ww) acacia
310 maple
311 Florida maple
312 bigleaf maple
313 boxelder
314 black maple
315 striped maple
316 red maple
317 silver maple
318 sugar maple
319 mountain maple
321 (ww) Rocky Mountain maple
-Softwoods
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pinus
Pseudotsuga
Pseudotsuga
Sequioa
Sequoiadendron
Taxodium
Taxodium
Taxus
Thuja
Thuja
Torreya
Tsuga
Tsuga
Tsuga
Tsuga
Tsuga
Acacia
Acer
Acer
Acer
Acer
Acer
Acer
Acer
Acer
Acer
Acer
Acer
rigida
sabiniana
serotina
strobus
sylvestris
taeda
virginiana
monophylla
discolor
ponderosa var. arizonica
strobiformis
washoensis
quadrifolia
nigra
cembroides
macrocarpa
menziesii
sempervirens
giganteum
distichum
distichum var. nutans
brevifolia
occidentalis
plicata
Californica
sp.
canadensis
caroliniana
heterophylla
mertensiana
sp.
sp.
barbatum
macrophyllum
negundo
nigrum
pennsylvanicum
rubrum
saccharinum
saccharum
spicatum
glabrum
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Code
EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 4 of 8
Common Name Genus Species
-Hardwoods
322 (ww) Bigtooth Maple
330 buckeye, horsechestnut
331 Ohio buckeye
332 yellow buckeye
333 California buckeye
341 ailanthus
350 alder
351 red alder
352 white alder
353 Sitka alder
354 thinleaf alder
355 European alder
356 serviceberry
361 Pacific madrone
367 pawpaw
370 birch sp.
371 yellow birch
372 sweet birch
373 river birch
374 water birch
375 paper birch
376 western paper birch
377 Alaska paper birch
378 northwestern paper birch
379 gray birch
381 chittamwood, gum bumelia
391 American hornbeam,
musclewood
400 hickory sp.
401 water hickory
402 bitternut hickory
403 pignut hickory
404 pecan
405 shellbark hickory
407 shagbark hickory
408 black hickory
409 mockernut hickory
421 American chestnut
422 Allegheny chinkapin
423 Ozark chinkapin
430 chinkapin
431 golden chinkapin
Acer
Aesculus
Aesculus
Aesculus
Aesculus
Ailanthus
Alnus
Alnus
Alnus
Alnus
Alnus
Alnus
Amelanchier
Arbutus
Asimina
Betula
Betula
Betula
Betula
Betula
Betula
Betula
Betula
Betula
Betula
Bumelia
Carpinus
Carya
Carya
Carya
Carya
Carya
Carya
Carya
Carya
Carya
Castanea
Castanea
Castanea
Castanopsis
Castanopsis
grandidentatum
sp.
glabra
octandra
californica
altissima
sp.
rubra
rhombifolia
sinuata
tenuifolia
glutinosa
sp.
menziesii
triloba
sp.
alleghaniensis
lenta
nigra
occidentalis
papyrifera
papyrifera var. commutata
papyrifera var. neoalaskana
papyrifera var. subcordata
populifolia
lanuginosa
caroliniana
sp.
aquatica
cordiformis
glabra
illinoensis
laciniosa
ovata
texana
tomentosa
dentata
pumila
ozarkensis
sp.
chrysophylla
-------
EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 5 of 8
Common Name Genus Species
^r w w
450
451
452
460
461
462
463
471
475 (ww)
476 (ww)
477 (ww)
478
479
481
491
492
500
510
521
531
540
541
542
543
544
545
546
547
551
552
555
571
580
581
591
600
601
602
603
604
605
606
\-4zttT\\nif\r\ri'
cataipa
southern cataipa
northern cataipa
hackberry sp.
sugarberry
hackberry
netleaf hackberry
eastern redbud
curileaf mountain-mahogany
alder-leaf mountain-mahogany
hairy mountain-mahogany
birchleaf mountain-mahogany
dwarf mountain-mahogany
yellowwood cladrastis
flowering dogwood
Pacific dogwood
hawthorn
eucalyptus
common persimmon
American beech
ash
white ash
Oregon ash
black ash
green ash
pumpkin ash
blue ash
velvet ash
waterlocust
honeylocust
loblolly-bay
Kentucky coffeetree
Mountain silverbell
Carolina silverbell
American holly
walnut
butternut
black walnut
California black walnut
southern California black
walnut
palo verde
palo verde
Cataipa
Cataipa
Cataipa
Celtis
Celtis
Celtis
Ceitis
Cercis
Cercocarpus
Cercocarpus
Cercocarpus
Cercocarpus
Cercocarpus
Cladrastis
Cornus
Cornus
Crataegus
Eucalyptus
Diospyros
Fagus
Fraxinus
Fraxinus
Fraxinus
Fraxinus
Fraxinus
Fraxinus
Fraxinus
Fraxinus
Gleditsia
Gleditsia
Gordonia
Gymnocladus
Halesia
Halesia
Ilex
Juglans
Juglans
Juglans
Juglans
Juglans
Leguminosae
Leguminosae
sp.
bignonioides
speciosa
sp.
laevigata
occidentalis
reticulata
canadensis
ledifolius
montanus
breviflorus
betuloides
intricatus
kentukea
florida
nuttallii
sp.
sp.
virginiana
grandifolia
sp.
americana
latifolia
nigra
pennsylvanica
profunda
quadrangulata
velutina
aquatica
triacanthos
lasianthus
dioicus
sp.
Carolina
opaca
sp.
cinerea
nigra
hindsii
californica
parkinsonia
cercidium
-------
Code
EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 6 of 8
Common Name Genus Species
611 sweetgum
621 yellow-poplar
631 tanoak
641 Osage-orange
650 magnolia sp.
651 cucumbertree
652 southern magnolia
653 sweetbay
654 bigleaf magnolia
660 apple sp.
661 Oregon crab apple
680 mulberry sp.
681 white mulberry
682 red mulberry
691 water tupelo
692 ogeechee tupelo
693 blackgum
694 swamp tupelo
701 eastern hophornbeam,
ironwood
711 sourwood
712 paulownia, empress tree
721 redbay
722 water elm, planer tree
730 sycamore California
731 sycamore
740 cottonwood
741 balsam poplar
742 eastern cottonwood
743 bigtooth aspen
744 swamp cottonwood
745 plains cottonwood
746 quaking aspen
747 black cottonwood
748 fremont poplar
749 narrowleaf cottonwood
752 silver poplar
755 (ww) mesquite
760 cherry, plum spp.
761 pin cherry
762 black cherry
763 chokecherry
764 plums, cherries,
except 762
-Hardwoods
Liquidambar
Liriodendron
Lithocarpus
Maclura
Magnolia
Magnolia
Magnolia
Magnolia
Magnolia
Malus
Malus
Morus
Morus
Morus
Nyssa
Nyssa
Nyssa
Nyssa
Ostrya
Oxydendrum
Paulownia
Persea
Planera
Platanus
Platanus
Populus
Populus
Populus
Populus
Populus
Populus
Populus
Populus
Populus
Populus
Populus
Prosopis
Prunus
Prunus
Prunus
Prunus
Prunus
styraciflua
tulipifera
densiflorus
pomifera
sp.
acuminata
grandiflora
virginiana
macrophylla
sp.
fusca
sp.
alba
rubra
aquatica
ogeche
sylvatica
sylvatica var. biflora
virginiana
arboreum
tomentosa
borbonia
aquatica
californica
occidentalis
spp.
balsamifera
deltoides
grandidentata
heterophylla
sargentii
tremuloides
trichocarpa
fremontii
angustifolia
alba
sp.
sp.
pensylvanica
serotina
virginiana
sp.
-------
Code
EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 7 of 8
Common Name Genus Species
765
766
800
801
802
803 (ww)
804
805
806
807
808
809
810(ww)
811
812
813
814 (ww)
815
816
817
818
819
820
821
822
823
824 .
825
826 (ww)
827
828
829 (ww)
830
831
832
833
834
835
836
837
Canada plum Prunus
wild plum
oak
coastal live oak,
California live oak
white oak
Arizona white oak, Gray oak
swamp white oak
canyon live oak
scarlet oak
blue oak
durand oak
northern pin oak
emery oak
engelmann oak
southern red oak
cherrybark oak,
swamp red oak
gambel oak
Oregon white oak
bear oak, scrub oak
shingle oak
California black oak
turkey oak
laurel oak
valley oak,
California white oak
overcup oak
bur oak
blackjack oak
swamp chestnut oak
chinkapin oak
water oak
nuttall oak
Mexican blue oak
pin oak
willow oak
chestnut oak
northern red oak
shumard oak
post oak
delta post oak
black oak
Prunus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
nigra
.americana
spp.
agrifolia
alba
arizonica, grisea
bicolor
chrysolepsis
coccinea
douglassi
durandii
ellipsoidalis
emoryi
engelmannii
falcata var. falcata
falcata var. pagodaefolia
gambelii
garryana
ilicifolia
imbricaria
kelloggii
laevis
laurifolia
lobata
lyrata
macrocarpa
marilandica
michauxii
muehlenbergii
nigra
nuttalii
oblongifolia
palustris
phellos
prinus
.rubra
shumardii
stellata
stellata var. Mississippiensis
velutina
-------
EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 8 of 8
Code Common Name Genus Species
Hardwoods-
838 live oak
839 interior live oak
840 dwarf post oak
841 dwarf live oak
842 bluejack oak
843 (ww) silverleaf oak
848 western Oak (Deciduous)
849 western Oak (Evergreen)
899 scrub oak
901 black locust
902 (ww) New Mexico locus
920 willow
921 peachleaf willow
922 black willow
928 diamond willow
931 sassafras
935 American mountain-ash
936 European mountain-ash
950 basswood
951 American basswood
952 white basswood
970 elm
971 winged elm
972 American elm
973 cedar elm
974 Siberian elm
975 slippery elm
976 September elm
977 rock elm
981 California laurel
990 (ww) Arizona ironwood
991 salt cedar
992 sparkleberry
993 chinaberry
994 Chinese tallowtree
995 tung-oil tree
996 smoketree
998 not listed
999 unknown
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Quercus
Robinia
Robinia
Salix
Salix
Salix
Salix
Sassafras
Sorbus
Sorbus
Tilia
Tilia
Tilia
Ulmus
Ulmus
Ulmus
Ulmus
Ulmus
Ulmus
Ulmus
Ulmus
Umellularia
Olneya
Tamarisk
Vaccinium
Melia
Sapium
Aleu rites
Cotinus
virginiana
wislizenii
stellata var stellata
sp.
incana
hypoleucoides
spp.
spp.
sp.
pseudoacacia
neomexicana
sp.
amygdaloides
nigra
eriocephala
albidum
americana
aucuparia
sp.
americana
heterophylla
sp.
alata
americana
crassifolia
pumila
rubra
serotina
thomasii
californica
tesota
sp.
arboreum
azedarach
sebiferum
fordii
obovatus
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 1 of 9
Appendix B
State and County FIPS Codes
(01)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
(039)
(041)
(043)
(045)
(047)
(049)
(051)
(053)
(055)
(057)
(059)
(061)
(063)
(065)
(067)
(069)
(071)
(073)
(075)
(077)
(079)
(081)
(083)
(085)
(087)
(089)
Alabama
Autauga
Baldwin
Barbour
Bibb
Blount
Bullock
Butler
Calhoun
Chambers
Cherokee
Chilton
Choctaw
Clarke
Clay
Cleburne
Coffee
Colbert
Conecuh
Coosa
Covington
Crenshaw
Cullman
Dale
Dallas
De Kalb
Elmore
Escambia
Etowah
Fayette
Franklin
Geneva
Greene
Hale
Henry
Houston
Jackson
Jefferson
Lamar
Lauderdale
Lawrence
Lee
Limestone
Lowndes
Macon
Madison
(091)
(093)
(095)
(097)
(099)
(101)
(103)
(105)
(107)
(109)
(111)
(113)
(115)
(117)
(119)
(121)
(123)
(125)
(127)
(129)
(131)
(133)
(06)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
(039)
(041)
Marengo
Marion
Marshall
Mobile
Monroe
Montgomery
Morgan
Perry
Pickens
Pike
Randolph
Russell
St Clair
Shelby
Sumter
Talladega
Tallapoosa
Tuscaloosa
Walker
Washington
Wilcox
Winston
California
Alameda
Alpine
Amador
Butte
Calaveras
Colusa
Contra Costa
Del Norte
El Dorado
Fresno
Glenn
Humboidt
Imperial
Inyo
Kern
Kings
Lake
Lassen
Los Angeles
Madera
Marin
(043)
(045)
(047)
(049)
(051)
(053)
(055)
(057)
(059)
(061)
(063)
(065)
(067)
(069)
(071)
(073)
(075)
(077)
(079)
(081)
(083)
(085)
(087)
(089)
(091)
(093)
(095)
(097)
(099)
(101)
(103)
(105)
(107)
(109)
(111)
(113)
(115)
Mariposa
Mendocino
Merced
Modoc
Mono
Monterey
Napa
Nevada
Orange
Placer
Plumas
Riverside
Sacramento
San Benito
San Bernardino
San Diego
San Francisco
San Joaquin
San Luis Obispo
San Mateo
Santa Barbara
Santa Clara
Santa Cruz
Shasta
Sierra
Siskiyou
Solano
Sonoma
Stanislaus
Sutler
Tehama
Trinity
Tulare
Tuolumne
Ventura
Yolo
Yuba
(08) Colorado
(001) Adams
(003) Alamosa
(005) Arapahoe
(007) Archuleta
(009) Baca
(011) Bent
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 2 of 9
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
(039)
(041)
(043)
(045)
(047)
(049)
(051)
(053)
(055)
(057)
(059)
(061)
(063)
(065)
(067)
(069)
(071)
(073)
(075)
(077)
(079)
(081)
(083)
(085)
. (087)
(089)
(091)
(093)
(095)
(097)
(099)
(101)
(103)
(105)
(107)
(109)
(111)
(113)
Boulder
Chaff ee
Cheyenne
Clear Creek
Conejos
Costilla
Crowley
Custer
Delta
Denver
Dolores
Douglas
Eagle
Elbert
El Paso
Fremont
Garfield
Gilpin
Grand
Gunnison
Hinsdale
Huerfano
Jackson
Jefferson
Kiowa
Kit Carson
Lake
La Plata
Larimer
Las Animas
Lincoln
Logan
Mesa
Mineral
Moffat
Montezuma
Montrose
Morgan
Otero
Ouray
Park
Phillips
Pitkin
Prowers
Pueblo
Rio Blanco
Rio Grande
Routt
Saguache
San Juan
San Miguel
(115) Sedgewick
(117) Summit
(119) Teller
(121) Washington
(123) Weld
(125) Yuma
(09)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
Connecticut
Fairfield
Hartford
Litchfield
Middlesex
New Haven
New London
Tolland
Windham
(10) Delaware
(001) Kent
(003) New Castle
(005) Sussex
(13)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
(039)
(043)
(045)
(047)
(049)
(051)
Georgia
Appling
Atkinston
Bacon
Baker
Baldwin
Banks
Barrow
Bartow
Ben Hill
Berrien
Bibb
Bleckley
Brantley
Brooks
Bryan
Bulloch
Burke
Butts
Calhoun
Camden
Candler
Carroll
Catoosa
Charlton
Chatham
(053) Chattahoochee
(055) Chattooga
(057) Cherokee
(059) Clarke
(061) Clay
(063) Clayton
(065) Clinch
(067) Cobb
(069) Coffee
(071) Colquitt
(073) Columbia
(075) Cook
(077) Coweta
(079) Crawford
(081) Crisp
(083) Dade
(085) Dawson
(087) Decatur
(089) De Kalb
(091) Dodge
(093) Dooly
(095) Dougherty
(097) Douglas
(099) Early
(101) Echols
(103). Effingham
(105) Elbert
(107) Emanuel
(109) Evans
(111) Fannin
(113) Fayette
(115) Floyd
(117) Forsyth
(119) Franklin
(121) Fulton
(123) Gilmer
(125) Glascock
(127) Glynn
(129) Gordon
(131) Grady
(133) Greene
(135) Gwinnett
(137) Habersham
(139) Hall
(141) Hancock
(143) Haralson
(145) Harris
(147) Hart
(149) Heard
(151) Henry
(153) Houston
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 3 of 9
(155)
(157)
(159)
(161)
(163)
(165)
(167)
(169)
(171)
(173)
(175)
(177)
(179)
(181)
(183)
(185)
(187)
(189)
(191)
(193)
(195)
(197)
(199)
(201)
(205)
(207)
(209)
(211)
(213)
(215)
(217)
(219)
(221)
(223)
(225)
(227)
(229)
(231)
(233)
(235)
(237)
(239)
(241)
(243)
(245)
(247)
(249)
(251)
(253)
(255)
(257)
Irwin
Jackson
Jasper
Jeff Davis
Jefferson
Jenkins
Johnson
Jones
Lamar
Lanier
Laurens
Lee
Liberty
Lincoln
Long
Lowndes
Lumpkin
Me Duffie
Me Intosh
Macon
Madison
Marion
Meriwether
Miller
Mitchell
Monroe
Montgomery
Morgan
Murray
Muscogee
Newton
Oconee
Oglethorpe
Paulding
Peach
Pickens
Pierce
Pike
Polk
Pulaski
Putnam
Quitman
Rabun
Randolph
Richmond
Rockdale
Schley
Screven
Seminole
Spalding
Stephens
(259)
(261)
(263)
(265)
(267)
(269)
(271)
(273)
(275)
(277)
(279)
(281)
(283)
(285)
(287)
(289)
(291)
(293)
(295)
(297)
(299)
(301)
(303)
(305)
(307)
(309)
(311)
(313)
(315)
(317)
(319)
(321)
(23)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
Stewart
Sumter
Talbot
Taliaferro
Tattnall
Taylor
Telfair
Terrell
Thomas
Tift
Toombs
Towns
Treutlen
Troup
Turner
Twiggs
Union
Upson
Walker
Walton
Ware
Warren
Washington
Wayne
Webster
Wheeler
White
Whitfield
Wilcox
Wilkes
Wilkinson
Worth
Maine
Androscoggin
Aroostook
Cumberland
Franklin
Hancock
Kennebec
Knox
Lincoln
Lincoln
Oxford
Penobscot
Piscataquis
Sagadahoc
Somerset
Wald
Washington
(031) York
(24) Maryland
(100) Allegany
(003) Anne Arundel
(005) Baltimore
(009) Calvert
(011) Caroline
(013) Carroll
(015) Cecil
(017) Charles
(019) Dorchester
(021) Frederick
(023) Garrett
(025) Harford
(027) Howard
(029) Kent
(031) Montgomery
(033) Prince Georges
(035) Queen Annes
(037) St. Marys
(039) Somerset
(041) Talbot
(043) Washington
(045) Wicomico
(047) Worcester
(510) Baltimore City
(25) Massachusetts
(001) Barnstable
(003) Berkshire
(005) Bristol
(007) Dukes
(009) Essex
(011) Franklin
(013) Hampden
(015) Hampshire
(017) Middlesex
(019) Nantucket
(021) Norfolk
(023) Plymouth
(025) Suffolk
(027) Worcester
(029) Washington
(031) York
(26) Michigan
(001) Alcona
(003) Alger
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 4 of 9
(005) Allegan
(007) Alpena
(009) Antrim
(011) Arenac
(013) Baraga
(015) Barry
(017) Bay
(019) Benzie
(021) Berrien
(023) Branch
(025) Calhoun
(027) Cass
(029) Charlevoix
(031) Cheboygan
(033) Chippewa
(035) Clare
(037) Clinton
(039) Crawford
(041) Delta
(043) Dickinson
(045) Eaton
(047) Emmet
(049) Genesee
(051) Gladwin
(053) Gogebic
(055) Grand Traverse
(057) Gratiot
(059) Hillsdale
(061) Houghton
(063) Huron
(065) Ingham
(067) Ionia
(069) losco
(071) Iron
(073) Isabella
(075) Jackson
(077) Kalamazoo
(079) Kalkaska
(081) Kent
(083) Keweenaw
(085) Lake
(087) Lapeer
(089) Leelanau
(091) Lenawee
(093) Livingston
(095) Luce
(097) Mackinac
(099) Macomb
(101) Manistee
(103) Marquette
(105) Mason
(107)
(109)
(111)
(113)
(115)
(117)
(119)
(121)
(123)
(125)
(127)
(129)
(131)
(133)
(135)
(137)
(139)
(141)
(143)
(145)
(147)
(149)
(151)
(153)
(155)
(157)
(159)
(161)
(163)
(165)
(27)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
Mecosta
Menominee
Midland
Missaukee
Monroe
Montcalm
Montmorency
Muskegon
Newaygo
Oakland
Oceana
Ogemaw
Ontonagon
Osceola
Oscoda
Otsego
Ottawa
Presque Isle
Roscommon
Saginaw
St. Clair
St. Joseph
Sanilac
Schoolcraft
Shiawassee
Tuscola
Van Buren
Washtenaw
Wayne
Wexford
Minnesota
Aitkin
Anoka
Becker
Beltrami
Benton
Big Stone
Blue Earth
Brown
Carlton
Carver
Cass
Chippewa
Chirago
Clay
Clearwater
Cook
Cottonwood
Crow Wing
(037) Dakota
(039) Dodge
(041) Douglas
(043) Faribault
(045) Fillmore
(047) Freeborn
(049) Goodhue
(051) Grant
(053) Hennepin
(055) Houston
(057) Hubbard
(059) Isanti
(061) Itasca
(063) Jackson
(065) Kanabec
(067) Kandiyohi
(069) Kittson
(071) Koochiching
(073) Lac qui Parle
(075) Lake
(077) Lake of the Woods
(079) Le Sueur
(081) Lincoln
(083) Lyon
(085) McLeod
(087) Mahnomen
(089) Marshall
(091) Martin
(093) Meeker
(095) Mille Lacs
(097) Morrison
(099) Mower
(101) Murray
(103) Nicollet
(105) Nobles
(107) Norman
(109) Olmsted
(111) Otter Tail
(113) Pennington
(115) Pine
(117) Pipestone
(119) Polk
(121) Pope
(123) Ramsey
(125) Red Lake
(127) Redwood
(129) Renville
(131) Rice
(133) Rock
(135) Roseau
(137) St. Louis
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 5 of 9
(139) Scott
(141) Sherbume
(143) Sibley
(145) Stearns
(147) Steele
(149) Stevens
(151) Swift
(153) Todd
(155) Traverse
(157) Wabasha
(159) Wadena
(161) Waseca
(163) Washington
(165) Watonwan
(167) Wilkin
(169) Winona
(171) Wright
(173) Yellow Medicine
(33) New Hampshire
(001) Belknap
(005) Cheshire
(009) Grafton
(011) Hillsborough
(013) Merrimack
(015) Rockingham
(017) Strafford
(019) Sullivan
(34)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
New Jersey
Atlantic
Bergen
Burlington
Camden
Cape May
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
Morris
Ocean
Passaic
Salem
Somerset
Sussex
(039) Union
(041) Warren
(37) North Carolina
(181) Vance
(183) Wake
(185) Warren
(187) Washington
(189) Watauga
(191) Wayne
(193) Wilkes
(195) Wilson
(197) Yadkin
(199) Yancey
(023) Burke
(025) Cabarrus
(027) Caldwell
(029) Camden
(031) Carteret
(033) Caswell
(035) Catawba
(037) Chatham
(039) Cherokee
(041) Chowan
(043) Clay
(045) Cleveland
(047) Columbus
(049) Craven
(051) Cumberland
(053) Currituck
(055) Dare
(057) Davidson
(059) Davie
(061) Dupli
(063) Durham
(065) Edgecombe
(067) Forsyth
(069) Franklin
(071) Gaston
(073) Gates
(075) Graham
(077) Granville
(079) Greene
(081) Guilford
(083) Halifax
(085) Harnett
(087) Haywood
(089) Henderson
(091) Hertford
(093) Hoke
(095)
(097)
(099)
(101)
(103
(105)
(107)
(109)
(111)
(001)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(113)
(115)
(117)
(119)
(121)
(123)
(125)
(127)
(129)
(131)
(133)
(135)
(137)
(139)
(141)
(143)
(145)
(147)
(149)
(151)
(153)
(155)
(157)
(159)
(161)
(163)
(165)
(167)
(169)
(171)
(173)
Hyde
Iredell
Jackson
Johnston
Jones
Lee
Lenoir
Lincoln
McDowell
Alamance
Alexander
Allegheny
Anson
Ashe
Avery
Beaufort
Bertie
Bladen
Brunswick
Buncombe
Macon
Madison
Martin
Mecklenburg
Mitchell
Montgomery
Moore
Nash
New Hanover
Northhampton
Onslow
Orange
Pamlico
Pasquotank
Pender
perquimans
Person
Pitt
Polk
Randolph
Richmond
Robeson
Rockingham
Rowan
Rutherford
Sampson
Scotland
Stanly
Stokes
Surrey
Swain
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 6 of 9
(175) Transylvania
(177) Tyrrell
(179) Union
(41)
(01)
(03)
(05)
(07)
(09)
(11)
(13)
(15)
(17)
(19)
(21)
(23)
(25)
(27)
(29)
(31)
(33)
(35)
(37)
(39)
(41)
(43)
(45)
(47)
(49)
(51)
(53)
(55)
(57)
(59)
(61)
(63)
(65)
(67)
(69)
(71)
Oregon
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Klamath
Lake
Lane
Lincoln
Linn
Malheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
(44) Rhode Island
(001) Bristol
(003) Kent
(005) Newport
(007) Providence
(009) Washington
(45) South Carolina
(001) Abbeville
(003) Aiken
(005) Allendale
(007) Anderson
(009) Bamberg
(011) Barnwell
(013) Beaufort
(015) Berkeley
(017) Calhoun
(019) Charleston
(021) Cherokee
(023) Chester
(025) Chesterfield
(027) Clarendon
(029) Colleton
(031) Darlington
(033) Dillon
(035) Dorchester
(037) Edgefield
(039) Fairfield
(041) Florence
(043) Georgetown
(045) Greenville
(047) Greenwood
(049) Hampton
(051) Horry
(053) Jasper
(055) Kershaw
(057) Lancaster
(059) Laurens
(061) Lee
(063) Lexington
(065) Me Cormick
(067) Marion
(069) Marlboro
(071) Newberry
(073) Oconee
(075) Orangeburg .
(077) Pickens
(079) Richland
(081) Saluda
(083) Spartanburg
(085) Sumter
(087) Union
(089) Williamsburg
(091) York
(47) Tennessee
(001) Anderson
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
(039)
(041)
(043)
(045)
(047)
(049)
(051)
(053)
(055)
(057)
(059)
(061)
(063)
(065)
(067)
(069)
(071)
(073)
(075)
(077)
(079)
(081)
(083)
(085)
(087)
(089)
(091)
(093)
(095)
(097)
(099)
(101)
(103)
Bedford
Benton
Bledsoe
Blount
Bradley
Campbell
Cannon
Carroll
Carter
Cheatham
Chester
Claiborne
Clay
Cocke
Coffee
Crockett
Cumberland
Davidson
Decatur
De Kalb
Dickson
Dyer
Fayette
Fentres
Franklin
Gibson
Giles
Grainger
Greene
Grundy
Hamblen
Hamilton
Hancock
Hardeman
Hardin
Hawkins
Haywood
Henderson
Henry
Hickman
Houston
Humphreys
Jackson
Jefferson
Johnson
Knox
Lake
Lauderdale
Lawrence
Lewis
Lincoln
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 7 of 9
(105)
(107)
(109)
(111)
(113)
(115)
(117)
(119)
(121)
(123)
(125)
(127)
(129)
(131)
(133)
(135)
(137)
(139)
(141)
(143)
(145)
(147)
(149)
(151)
(153)
(155)
(157)
(159)
(161)
(163)
(165)
(167)
(169)
(171)
(173)
(175)
(177)
(179)
(181)
(183)
(185)
(187)
(189)
Loudon
Me Minn
Me Nairy
Macon
Madison
Marion
Marshall
Maury
Meigs
Monroe
Montgomery
Moore
Morgan
Obion
Overton
Perry
Pickett
Polk
Putnam
Rhea
Roane
Robertson
Rutherford
Scott
Sequatchie
Sevier
Shelby
Smith
Stewart
Sullivan
Sumner
Tipton
Trousdale
Unicoi
Union
Van Buren
Warren
Washington
Wayne
Weakley
White
Williamson
Wilson
(50) Vermont
(001) Addison
(003) Bennington
(005) Caledonia
(007) Chittenden
(009) Essex
(011) Franklin (775)
(013) Grand Isle (780)
(015) Lamoille (790)
(017) Orange (800)
(019) Orleans (810)
(021) Rutland (820)
(023) Washington (830)
(025) Windham (093)
(027) Windsor (003)
(005)
(007)
(51) Virginia (009)
(001) Accomack (011)
(840) Winchester City (013)
(193) Westmoreland (015)
(195) Wise (017)
(197) Wythe (019)
(199) York (021)
(510) Alexandria City (023)
(515) Bedford City (025)
(520) Bristol City (027)
(530) Buena Vista City (029)
(540) Charlottesville City (031)
(550) Chesapeake City (033)
(560) Clifton Gorge City (035)
(570) Colonial Heights City (036)
(580) Covington City (037)
(590) Danville City (041)
(595) Emporia City (043)
(600) Fairfax City (045)
(610) Falls Church City (047)
(620) Franklin City (049)
(630) Fredericksburg City (051)
(640) Galax City (053)
(650) Hampton City (057)
(660) Harrisonburg City (059)
(670) HopewellCity (061)
(678) Lexington City (063)
(680) Lynchburg City (065)
(683) Manassas (067)
(685) Manassas Park (069)
(690) Martinsville City (071)
(700) Newport News City (073)
(710) Norfolk City (075)
(720) Norton City (077)
(730) Petersburg City (079)
(735) Poquoson (081)
(740) Portsmouth City (083)
(750) Radford City (085)
(760) Richmond City (087)
(770) Roanoke City (089)
Salem City
South Boston City
Staunton City
Suffolk City
Virginia Beach City
Waynesboro City
Williamsburg City
Isle of Wight
Albe marie
Allegheny
Amelia
Amherst
Appomattox
Arlington
Augusta
Bath
Bedford
Bland
Botetourt
Brunswick
Buchanan
Buckingham
Campbell
Caroline
Carroll
Charles City
Charlotte
Chesterfield
Clarke
Craig
Culpeper
Cumberland
Dickenson
Dinwiddie
Essex
Fairfax
Fauquier
Floyd
Fluvanna
Franklin
Frederick
Giles
Gloucester
Goochland
Gray son
Greene
Greensville
Halifax
Hanover
Henrico
Henry
-------
EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 8 of 9
(191) Washington
(095) James City
(097) King and Que
(099) King George
(101) King William
(103) Lancaster
(105) Lee
(107) Loudoun
(109) Louisa
(111) Lunenberg
(113) Madison
(115) Mathews
(117) Mecklenburg
(119) Middlesex
(121) Montgomery
(125) Nelson
(127) New Kent
(131) Northampton
(133) Northumberla
(135) Nottoway
(137) Orange
(139) Page
(141) Patrick
(143) Pittsylvania
(145) Powhatan
(147) Prince Edward
(149) Prince George
(153) Prince Willia
(155) Pulaski
(157) Rappahannock
(159) Richmond
(161) Roanoke
(163) Rockbridge
(165) Rockingham
(167) Russell
(169) Scott
(171) Sehenandoah
(173) Smyth
(175) Southampton
(177) Spotsylvania
(179) Stafford
(181) Surry
(183) Sussex
(185) Tazewell
(187) Warren
(35) Washington
(001) Adams
(003) Asotin
(005) Benton
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
(039)
(041)
(043)
(045)
(047)
(049)
(051)
(053)
(055)
(057)
(059)
(061)
(063)
(065)
(067)
(069)
(071)
(073)
(075)
(077)
(54)
(001)
(091)
(003)
(005)
(007)
(009)
(011)
(013)
(015)
(017)
(019)
(021)
Chelan
Clallam
Clark
Columbia
Cowlitz
Douglas
Ferry
Franklin
Garfield
Grant
Grays Harbor
Island
Jefferson
King
Kitsap
Kittitas
Klickitat
Lewis
Lincoln
Mason
Okanogan
Pacific
Pend Oreilie
Pierce
San Juan
Skagit
Skamania
Snohomish
Spokane
Stevens
Thurston
Wahkiakum
Walla Walla
Whatcom
Whitman
Yakima
West Virginia
Barbour
Highland
Berkeley
Boone
Braxton
Brooke
Cabell
Calhoun
Clay
Doddridge
Fayette
Gilmer
(023)
(025)
(027)
(029)
(031)
(033)
(035)
(037)
(039)
(041)
(043)
(045)
(049)
(051)
(053)
(047)
(055)
(057)
(059)
(065)
(061)
(063)
(069)
(071)
(073)
(075)
(077)
(079)
(081)
(083)
(085)
(087)
(089)
(091)
(093)
(095)
(097)
(099)
(101)
(103)
(105)
(107)
(109)
Grant
Greenbriar
Hampshire
Hancock
Hardy
Harrison
Jackson
Jefferson
Kanawha
Lewis
Lincoln
Logan
Marion
Marshall
Mason
McDowell
Mercer
Mineral
Mingo
Moegan
Monogalia
Monroe
Ohio
Pendleton
Pleasant
Pocahontas
Preston
Putnam
Raleigh
Randolph
Ritchie
Roane
Summers
Taylor
Tucker
Tyler
Upshup
Wayne
Webster
Wwetzel
Wirt
Wood
Wyoming
(55) Wisconsin
(001) Adams
(003) Ashland
(005) Barren
(007) Bayfield
(009) Brown
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EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 9 of 9
(011)
(013)
(015)
(017)
(019)
(021)
(023)
(025)
(027)
Buffalo
Burnett
Calumet
Chippewa
Clark
Columbia
Crawford
Dane
Dodge
(029)
(031)
(033)
(035)
(037)
(039)
(041)
(043)
(045)
(047)
(049)
(051)
(053)
(055)
(057)
(059)
(061)
(063)
(065)
(067)
(069)
(071)
(073)
(075)
(077)
(078)
(079)
(081)
(083)
(085)
Door
Douglas
Dunn
Eau Claire
Florence
Fond du Lac
Forest
Grant
Green
Green Lake
Iowa
Iron
Jackson
Jefferson
Juneau
Kenosha
Kewaunee
La Crosse
Lafayette
Langlade
Lincoln
Manitowoc
Marathon
Marinette
Marquette
Menominee
Milwaukee
Monroe
Oconto
Oneida
(087)
(089)
(091)
(093)
(095)
(097)
(099)
(101)
(103)
(105)
(107)
(109)
(111)
(113)
(115)
(117)
(119)
(121)
(123)
(125)
(127)
(129)
(131)
(133)
(135)
(137)
(139)
(141)
Outagamie
Ozaukee
Pepin
Pierce
Polk
Portage
Price
Racine
Rich land
Rock
Rusk
St. Croix
Sauk
Sawyer
Shawano
Sheboygan
Taylor
Trempealeau
Vernon
Vilas
Walworth
Washburn
Washington
Waukesha
Waupaca
Waushara
Winnebago
Wood
-------
EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 1 of 10
Appendix C
Forest Type Descriptions
Eastern Forest Type Descriptions
0000 WHITE/RED/JACK PINE GROUP
0010 Jack pine: Associates-red pine, northern pin oak, quaking and bigtooth aspen, paper birch, black
spruce, and white spruce. Sites-generally driest, most porous sands but also on more moist, sandy
soils near swamps and on rocky hills and lodges.
0020 Red pine: Associates-white, jack, or pitch pine; northern pineoak; white oak; red maple; paper
birch; quaking and bigtooth aspen, chestnut oak, northern red oak, and hemlock. Sites-spotty
distribution in Northeast and sandy and gravelly locations or dry sandy loam soils; often in plantations.
0030 White pine: Associates-pitch pine, gray birch, aspen, red maple, pin cherry, white oak, paper
birch, sweet birch, yellow birch, black cherry, white ash, northern red oak, sugar maple, basswood,
hemlock, northern white-cedar, yellow-poplar, white oak, chestnut oak, scarlet oak, and shortleaf pine.
Sites-wide variety, but best development on well drained sands and sandy loams.
0040 White pine/hemlock: Associates-beech, sugar maple, basswood, red maple, yellow birch, black
cherry, white ash, paper birch, sweet birch, northern red oak, white oak, chestnut oak, yellow-poplar,
and cucumbertree. Sites-wide variety but favors cool locations, moist ravines, and north slopes.
0050 Hemlock: Associates-beech, sugar maple, yellow birch, basswood, red maple, black cherry,
white ash, white pine, paper birch, sweet birch, northern red oak, and white oak. Sites-cool locations,
moist ravines, and north slopes.
0060 Scotch pine: plantation type, not naturally occurring.
0070 Ponderosa pine:
0100 SPRUCE/FIR GROUP
0110 Balsam fir: Associates-black, white, or red spruce; paper or yellow birch; quaking or bigtooth
aspen, beech; red maple; hemlock; tamarack; black ash; or northern white-cedar. Sites-upland sites
on low lying moist flats and in swamps.
0120 Black spruce: Associates-white spruce, balsam fir, jackpine, quaking aspen, paper birch,
tamarack, northern white-cedar, black ash, or red maple. Sites-acid peat swamps but also on moist
flats and uplands.
0130 Red spruce/balsam fir: Associates-red maple, paper birch, whitepine, hemlock, white spruce,
and northern white-cedar. Sites-moderately drained to poorly drained flats or on thin-soiled upper
slopes.
0140 Northern white-cedar: Associates-tamarack, yellow birch, paperbirch, black ash, red maple,
white pine, and hemlock. Sites-slow drainage (not stagnant bogs) areas that are not strongly acid.
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 2 of 10
0150 Tamarack (eastern larch): Associates-northern white cedar, red maple, black ash, and quaking
aspen. Sites-wet swamps.
0160 White spruce: Associates-black spruce, balsam fir, quaking aspen, paper birch, jack pine, red
spruce, sugar maple, beech, and yellow birch. Sites-moist, sandy loam or alluvial soils-found on
many different sites but especially typical of stream banks, lake shores, and adjacent slopes.
0170 Norway spruce: plantation type, not naturally occurring.
0180 Larch (introduced): plantation type, usually Japanese larch, European larch, or a hybrid of the
two (Dunkeld larch) - not naturally occurring. Sites-well-drained uplands; heavy plantation in New
York.
0190 Red Spruce: Associates-vary widely and may include red maple, yellow birch, eastern hemlock,
eastern white pine, white spruce, northern white-cedar, paper birch, pin cherry, gray birch, mountain
ash, beech, striped maple, sugar maple, northern red oak, red pine, and aspen. Sites-include
moderately well drained to poorly drained flats and thin-slopes and on varying acidic soils in abandoned
fields and pastures. This code should be used where red spruce comprises a plurality or majority of
the stand's stocking but where balsam fir is either nonexistent or has very little stocking. Otherwise
the plot would be coded 130, red spruce/balsam fir.
0200 LONGLEAF/SLASH PINE GROUP
0210 Longleaf pine: Longleaf pine occurs as a pure type or comprises a majority of the trees in the
overstory. Associates-slash, loblolly and shortleaf pine, southern red oak, blackjack oak, water oak,
persimmon, and sweetgum. Sites-those areas that can and do burn on a periodic basis-usuaily
occurs on middle and upper slopes with a low severity of hardwood and brush competition. Regional
distribution-coastal plain and piedmont units.
0220 Slash pine: Slash pine is pure or provides a majority of the stocking. Associates-on moist sites;
a wide variety of moist-site hardwoods, pond pine, and pondcypress. On dry sites; a wide variety of
dry-site hardwoods, longieaf, loblolly, and sand pine. Sites-both moist and well-drained flatwoods, and
bays. Regional distribution-coastal plain and piedmont units from North Carolina to Florida.
0300 LOBLOLLY/SHORTLEAF PINE GROUP
0310 Loblolly pine: Associates-sweetgum, southern red oak, post oak, blackjack oak, blackgum,
yellow-poplar, and pond pine. Sites-in Delaware and Maryland both on upland soils with abundant
moisture but good drainage and on poorly drained depressions.
0320 Shortleaf pine: Associates-white oak, southern red oak, scarlet oak, black oak, hickory, post oak,
blackjack oak, blackgum, red maple, pitch pine, and Virginia pine. Sites-low, well drained ridges to
rocky, dry, south slopes and the better drained spur ridges on north slopes and also on old fields.
0330 Virginia pine: Associates-shortleaf pine, white oak, chestnut oak, southern red oak, black oak,
sweetgum, red maple, blackgum, and pitch pine. Sites-dry sites, often abandoned fields.
0340 Sand pine: Sand pine occurs in pure stands or provides a majority of the stocking.
Associates-dwarf live oak, dwarf post oak, turkey oak, persimmon, and longieaf pine. Sites-dry,
acidic, infertile sands. Regional distribution-found chiefly in the central peninsula and panhandle of
Florida, although planted stands extend into the sandhills of Georgia and South Carolina.
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 3 of 10
0350 Eastern redcedar: Associates-gray birch, red maple, sweetbirch, Virginia Pine, shortleaf pine,
oak. Sites-usually dry uplands and abandoned fields on limestone outcrops and other shallow soils
but can grow well on good sites.
0360 Pond pine: Associates-loblolly pine, sweetgum, baldcypress, and Atlantic white-cedar. Sites-
rare, but found in southern New Jersey, Delaware, and Maryland in low, poorly drained acres, swamps,
and marshes.
0370 Spruce pine: Spruce pine comprises a majority of the stocking. Associat"es--any of the moist site
softwood or hardwood species. Sites-moist or poorly drained areas. Regional distribution-this type
is rarely encountered and is found almost exclusively in the coastal plain.
0380 Pitch pine: Associates-chestnut oak, scarlet oak, table-mountain pine, black oak, and blackgum.
Sites-relatively infertile ridges, dry flats, and slopes.
0390 Table-mountain pine: Associates-chestnut oak, scarlet oak, pitch pine, pine, and black oak.
Sites-poor, dry, often rocky slopes.
0400 OAK/PINE GROUP
0410 White pine/northern red oak/white ash: Associates-red maple, basswood, yellow birch, bigtooth
aspen, sugar maple, beech, paper birch, black cherry, hemlock, and sweet birch. Sites-deep, fertile,
well-drained soil.
0420 Eastern redcedar/hardwood: Associates-oak, hickory, walnut, ash, locust, dogwood, blackgum,
hackberry, winged elm, shortleaf pine, and Virginia pine. Sites-usually dry uplands and abandoned
fields.
0430 Longleaf pine/scrub oak: Longleaf pine and scrub oaks-primarily turkey, bluejack, blackjack, and
dwarf post oak-comprise the type. Associates-southern scrub oaks in the understory. Sites-common
on sandhills where soils are dry, infertile, and coarse textured. Regional distribution-coastal plain and
piedmont units.
0440 Shortleaf pine/oak: Associates-(oaks generally include white, scarlet, blackjack, black, post, and
southern red) hickory, blackgum, sweetgum, Virginia pine, and pitch pine. Sites-generally in dry, low
ridges, flats, and south slopes.
0450 Virginia pine/southern red oak: Associates-black oak, scarlet oak, white oak, post oak, blackjack
oak, shortleaf pine, blackgum, hickory, pitch pine, table-mountain pine, chestnut oak. Sites-dry slopes
and ridges.
0460 Loblolly pine/hardwood: Associates-wide variety of moist and wet site hardwoods including
blackgum, sweetgum, yellow-poplar, red maple, white and green ash, and American elm; on drier sites
associates include southern and northern red oak, white oak, post oak, scarlet oak, persimmon, and
hickory. Sites-usually moist to very moist though not wet all year but also on drier sites.
0470 Slash pine/hardwood: Slash pine and a variable mixture of hardwoods comprise the type.
Associates-codominant with the slash pine component are sweetbay, blackgum, loblolly-bay,
pondcypress, pond pine, Atlantic white-cedar, red maple, ash, and water oak. Sites-undrained or
poorly drained depressions such as bays or pocosins and along pond margins. Regional
distribution-primarily coastal plain units.
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 4 of 10
0480 Scarlet oak: Associates-black oak, southern red oak, chestnut oak, white oak, post oak, hickory,
pitch pine, blackgum, sweetgum, black locust, sourwood, dogwood, shortleaf pine, and Virginia pine.
Sites-dry ridges, south- or west-facing slopes and flats but often moister situations probably as a result
of logging or fire.
0490 Other oak/pine:
0500 OAK/HICKORY GROUP
0510 Post, black, or bear oak: Associates-blackjack oak, hickory, southern red oak, white oak, scarlet
oak, shingle oak, live oak, shortleaf pine, Virginia pine, blackgum, sourwood, red maple, winged elm,
hackberry, chinkapin oak, shumard oak, dogwood, and eastern redcedar. Sites-dry uplands and
ridges.
0520 Chestnut oak: Associates-scarlet oak, white oak, black oak, post oak, pitch pine, blackgum,
sweetgum, red maple, red oak, shortleaf pine, Virginia pine. Sites-rocky outcrops with thin soil, ridge
tops.
0530 White oak/red oak/hickory: Associates-scarlet oak, bur oak, pinoak, white ash, sugar maple, red
maple, walnut, basswood, locust, beech, sweetgum, blackgum, yellow-poplar, and dogwood. Sites-
wide variety of well drained upland soils.
0540 White oak: Associates-black oak, northern red oak, bur oak, hickory, white ash, yellow-poplar.
Sites-scattered patches on upland, loamy soils but on drier sites than type 530.
0550 Northern red oak: Associates-black oak, scarlet oak, chestnut oak, and yellow-poplar. Sites-
spotty distribution on ridge crests and north slopes in mountains but also found on rolling land, slopes,
and benches on loamy soil.
0560 Yellow-poplar/white oak/northern red oak: Associates-blackoak, hemlock, blackgum, and hickory.
Sites-northern slopes, coves, and moist flats.
0562 Sweetgum/yellow-poplar: Associates-red maple, white ash, green ash, and other moist site
hardwoods. Sites-generally occupies moist, lower slopes.
0564 Yellow-poplar: Associates-black locust, red maple, sweet birch, cucumbertree, and other
moist-site hardwoods (except sweetgum, see type 562) and white oak and northern red oak (see type
560). Sites-lower slopes, northerly slopes, moist coves, flats, and old fields.
0570 Southern scrub oak: This forest cover type consists of a mixture of scrub oaks that may include
several of the following species: turkey oak, bluejack oak, blackjack oak, dwarf post oak, and dwarf
live oak. Sites-dry sandy ridges-the type frequently develops on areas formerly occupied by longleaf
pine. Regional distribution-common throughout all coastal plain units and into the lower piedmont.
0580 Black locust: Associates-many species of hardwoods and hardpines may occur with it in mixture,
either having been planted or from natural seeding. Sites-may occur on any well-drained soil but best
on dry sites, often in old fields.
0590 Mixed central hardwoods: Associates~Any mixture of hardwoods of species typical of the upland
central hardwood region, should include at least some oak. Sites-wide variety of upland sites.
0592 Sassafras/persimmon: Associates-elm, eastern redcedar, hickory, ash, sugar maple,
yellow-poplar, and oaks. Sites-abandoned farmlands and old fields.
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 5 of 10
0594 Central hardwood reverting field: Associates--any commercial or noncommercial pioneer species
commonly found in the oak/hickory region except black locust (see type 0580), yellow-poplar (see type
564), sassafras or persimmon (see type 0592), or eastern redcedar (see type 0350). Sites-abandoned
farmlands and old fields.
0600 OAK/GUM/CYPRESS GROUP
0610 Swamp chestnut oak/cherrybark oak: Associates-white ash, hickory, white oak, shumard oak,
blackgum, sweetgum, southern red oak, post oak, American elm, winged elm, yellow-poplar, and
beech. Sites-within alluvial flood plains of major rivers on all ridges in the terraces and on the best
fine sandy loam soils on the highest first bottom ridges.
0620 Sweetgum/Nuttall oak/willow oak: Associates-green ash, American elm, pecan, cottonwood, red
maple, honeylocust, and persimmon. Sites-very wet.
0630 Sugarberry/American elm/green ash: Associates-pecan, blackgum, persimmon, honeylocust, red
maple, hackberry, and boxelder. Sites-low ridges and flats in flood plains.
0650 Overcup oak/water hickory: Associates-willow oak, American elm, green ash, hackberry,
persimmon, and red maple. Sites--in South within alluvial flood plains in low, poorly drained flats with
clay soils; also in sloughs and lowest backwater basins and low ridges with heavy soils that are subject
to late spring inundation.
0660 Atlantic white-cedar: Associates-North includes gray birch, pitch pine, hemlock, biackgum, and
red maple. South includes pond pine, baldcypress, and red maple. Sites-usually confined to
sandy-bottomed, peaty, interior, and river swamps, wet depressions, and stream banks.
0670 Baldcypress/water tupelo: Associates-willow, red maple, American elm, persimmon, overcup
oak, and sweetgum. Sites-very low, poorly drained flats, deep sloughs, and swamps wet most all the
year.
0680 Sweetbay/swamp tupelo/red maple: Associates-blackgum, loblolly and pond pines, American
elm, and other moist-site hardwoods. Sites-very moist but seldom wet all year-shallow ponds, muck
swamps, along smaller creeks in Coastal Plain (rare in Northeast).
0690 Palm/mangrove/other tropical:
0692 Mangrove: Forests in which mangrove comprises a majority of the stocking.
Associates-cabbage palm on some of the higher sites in the area. Sites-predominantly salt marshes;
mangrove frequently develops its own island or shoreline made up of a dense mat of root structures.
Regional distribution-restricted to South Florida and the Keys.
0694 Palm: Cabbage palm comprises a plurality of the stocking. This type can occur as a pure stand.
Associates-slash pine, dwarf live oak, live oak, laurel oak, water oak, baldcypress, pondcypress, red
maple, redcedar, redbay, and loblolly pine. Sites-coastal dunes and floodplains of major rivers north
of Florida; in Florida the type occurs on moist sites such as marsh islands, marshy shorelines, and
floodplains. Regional distribution-coastal plain units from North Carolina to the southern tip of Florida.
0696 Other tropical: Forests in which other tropical species, singly or in combination, comprise a
majority of the stocking. The species may include melaleuca, Australian pine, sable palm, and any of
the miscellaneous citrus species encountered in the southernmost region of Florida. Associates-wide
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 6 of 10
variety of species indigenous to south Florida. Sites-wide variety. Regional distribution-restricted
exclusively to south Florida.
0700 ELM/ASH/RED MAPLE GROUP
0710 Black ash/American elm/red maple: Associates-silver maple, swampwhite oak, sycamore, pin
oak, blackgum, white ash, and cottonwood. Sites-moist to wet areas, swamps, gullies, and poorly
drained flats.
0720 River birch/sycamore: Associates-red maple, black willow, and other moist-site hardwoods.
Sites-moist soils at edges of creeks and rivers.
0730 Cottonwood: Associates-willow, white ash, green ash, and sycamore. Sites-streambanks where
bare, moist soil is available.
0740 Willow: Associates-cottonwood, green ash, sycamore, pecan,. American elm, red maple, and
boxelder. Sites-streambanks where bare, moist soil is available.
0750 Sycamore/pecan/American elm: Associates-boxelder, green ash, hackberry, silver maple,
cottonwood, willow, sweetgum, and river birch. Sites-bottomlands, alluvial flood plains of major rivers.
0800 MAPLE/BEECH/BIRCH GROUP
0810 Sugar maple/beech/yellow birch: Associates-basswood, red maple, hemlock, northern red oak,
white ash, white pine, black cherry, sweet birch, American elm, rock elm, and eastern hophornbeam.
Sites-fertile, moist, well-drained sites.
0820 Black cherry: Associates-sugar maple, northern red oak, red maple, white ash, basswood, sweet
birch, butternut, American elm, and hemlock. Sites-fertile, moist, well-drained sites.
0830 Black walnut: Associates-yeilow-poplar, white ash, black cherry, basswood, beech, sugar maple,
oaks, and hickory. Sites-coves and well-drained bottoms.
0840 Red maple/northern hardwoods: Associates-the type is dominated by red maple and some of
the wide variety of northern hardwood associates include sugar maple, beech, birch, aspen, as well
as some northern softwoods like white pine, red pine, and hemlock; this type is often man-made and
may be the result of repeated cuttings. Sites-uplands.
0850 Red maple/central hardwoods: Associates-the type is dominated by red maple and some of the
wide variety of central hardwood associates include upland oak, hickory, yellow-poplar, black locust,
sassafras as well as some central softwoods like Virginia and shortleaf pines. Sites-uplands (see type
0840).
0880 Northern hardwood reverting field: Associates-any commercial or noncommercial pioneer
species commonly found in the northern hardwood region except aspen (see type 0910) and gray birch
(see type 0930). Sites-abandoned farmlands and old fields.
0890 Mixed northern hardwoods: Associates-wide variety of upland hardwoods typical of northern
hardwood or cover hardwood types where the sugar maple-beech-yellow-birch combination or
blackcherry alone do not comprise a plurality of stocking. Sites-upland, well drained, fertile.
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 7 of 10
0900 ASPEN/BIRCH GROUP
0910 Aspen: Associates-paper birch, pin cherry, bur oak, green ash, American elm, balsam poplar,
and boxelder. Sites-all kinds of soils except very driest sands and wettest swamps; found on burns,
clearcuts, and abandoned land.
0920 Paper birch: Associates-aspen, white pine, yellow birch, hemlock, red maple, northern red oak,
and basswood. Sites-wide range of upland site, common on burns or clearcuts.
0930 Gray birch: Associates-oaks, red maple, white pine, and others. Sites-poor soils of abandoned
farms and burns.
0998 INDETERMINATE-to be used only when a plot cannot be classified into one of the types listed
above. A detailed note describing the situation must appear in the general notes.
0999 NONSTOCKED-the site qualifies as forest but is presently stocked with too few trees to assign
a forest type.
Western Forest Type Descriptions
All Western Forest Type Groups, for the purpose of Condition Classification, are based on the
predominance of stocking, except for codes 9001 and 3097 below. The stocking will be based on some
field procedure application (a tree count by species) using a predetermined, regionally appropriate prism.
See the instructions for determining Forest Type calls in the two special mixed stand conditions (codes
9001 and 3097) below.
1200 DOUGLAS-FIR TYPE GROUP
1201 Bigcone Douglas-fir
1202 Douglas fir
2100 MAJOR PINE TYPE GROUP
2108 Lodgepole pine
2116 Jeffrey pine
2117 Sugar pine
2119 Western white pine
2122 Ponderosa pine
3000 WESTERN FIR-SPRUCE TYPE GROUP
3010 Fir
3011 Pacific silver fir
3014 Bristlecone fir
3015 White fir
3016 Fraser Fir
3017 Grand fir
3019 S.ubalpinefir
3020 California red fir
3021 Shasta red fir
3022 Noble fir
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 8 of 10
3090 Spruce
3092 Brewer spruce
3093 Engelmann spruce
4000 HEMLOCK-SPRUCE TYPE GROUP
4098 Sttka spruce
4242 Western redcedar
4263 Western hemlock
4264 Mountain hemlock
5200 REDWOOD/SEQUIOA TYPE GROUP
5211 Redwood
5212 Giant sequoia
6300 WESTERN HARDWOODS
6300 Acacia
6310 Maple
6312 Bigleaf maple
6321 Rocky Mountain maple
6350 Alder
6351 Red alder
6360 Madrone
6361 Pacific madrone
6370 Birch
6374 Water birch
6375 Paper birch
6430 Chinkapin
6431 Golden chinkapin
6475 Curl leaf mountain mahogany
6478 Birch-leaf mountain mahogany
6492 Pacific dogwood
6510 Eucalyptus
6540 Ash
6542 Oregon ash
6600 Walnut
6631 Tanoak
6660 Apple
6661 Oregon crab apple
6730 Sycamore
6740 Cottonwood
6746 Quaking aspen
6747 Black cottonwood
6748 Fremont cottonwood
6749 Narrowleaf cottonwood
6755 Mesquite
6800 Oak
6801 California Live oak
6805 Canyon live oak
6807 Blue oak
6811 Engelmann oak
6815 Oregon white oak
6818 California black oak
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 9 of 10
6821 California white oak
6826 Chinkapin oak
6839 Interior live oak
6848 Western oak-deciduous
6849 Western oak-evergreen
6920 Willow
6981 California-laurel
7000 MISCELLANEOUS WESTERN SOFTWOODS
7041 Port-orford-cedar
7042 Alaska-cedar
7051 Arizona cypress
7060 Juniper
7062 California juniper
7064 Western juniper
7065 Utah juniper
7073 Western larch
7081 Incense-cedar
7101 Whitebark pine
7102 Bristlecone pine
7103 Knobcone pine
7104 Foxtail pine
7106 Common pinyon
7109 Coulter pine
7113 Limber pine
7114 Mexican white pine
7120 Bishop pine
7124 Monterey pine
7127 Grey pine
7133 Singleleaf pinyon
7137 Washoe pine
7138 Four-leaved pine
7140 Mexican pinyon
7141 Pinyon-Juniper
7231 Pacific yew ,
7251 California Torreya
7990 Arizona ironwood
7991 Salt cedar
Forest Type codes required for FIA reports will be computed at each FIA regional office using existing
computer algorithms.
9000 MIXED CONIFERS
9001 Mixed conifers, California. Algorithm for determining this type: This pertains only to conifer
stands with a mix of Douglas-fir, white fir, red fir, ponderosa pine, Jeffery pine, sugar pine, and incense
cedar:
1) If Douglas-fir occurs as the plurality stocking species in any of the following counties (see county
code list section 2.11): Codes 15, 23,41,45,55, 81,85,87, 97, then the Forest Type is Dougl~Mir (1202).
For other counties, if the predominant species is Douglas-fir in a mix with other species, th?> •. -est Type
is Mixed Conifer (9001). If these conditions do not exist, then go to 2.
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EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 10 of 10
2) Anytime sugar pine or incense cedar occur as a plurality in a mix of the above Mixed Conifers
species, we have a Mixed Conifer Type (9001). If these conditions do not exist, then go to 3.
3) Anytime there is a combined stocking of over 50% in Jeffery and Ponderosa pine, the Forest Type
call goes to the predominant pine (either 2116 or 2122). Otherwise, go to 4.
4) Anytime there is a combined stocking of over 50% in white fir, California red fir, and/or shasta red
fir, the Forest Type call goes to the predominating fir (either 3015, 3020, or 3021). Otherwise, go to 5.
5) If there is over 80% stocking in any of the other species (1 above), the type call is given to the
individual species with the stocking over 80%; see codes in Major Pine Group (2108-2122), above.
Otherwise, go to 6.
6) All other combinations of the above Mixed Conifers species will be classed as Mixed Conifers
(9001).
3097 Mixed Engelmann spruce/subalpine fir. Algorithm for determining this type:
1) If the combined stocking of Engelmann spruce and subalpine fir does not carry the plurality of
stocking, it is not a mixed type. The type is called on which other species carries the plurality (see above).
If the combined plurality is there, go to 2.
2) If Engelmann spruce is greater or equal to 20% and subalpine fir is 0-19, the type is given to
Engelmann spruce (see code 3093 above). Otherwise, go to 3.
3) If Engelmann spruce stocking is less than 20% and subalpine fir stocking is greater than 0%, the
type is mixed Engelmann spruce/subalpine fir (3097). And, if Engelmann spruce and subalpine fir are both
greater or equal to 20%, the type is Mixed Engelmann spruce/subalpine fir (3097).
4) There is one more condition: If subalpine fir has stocking greater than 0% and there is no
Engelmann spruce present, the type is Mixed Engelmann spruce/subalpine fir (3097). This is to
accommodate the fact that Intermountain FIA never sets up a category to take all subalpine fir stands in
the subalpine fir type (no pure subalpine fir type exists).
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EMAP Forest Monitoring, Appendix D, Rev. No. 0, October, 1994, Page 1 of 3
Appendix D
Land Use Classifications
Overview
The primary objective of land use classifications is to separate forest land from inaccessible and
nonforest land uses. The land use classes recognized by FHM have largely been adopted from FIA in
order to retain consistency between FHM and FIA data sets.
Forest Land
Forest is land that is at least 10 percent stocked with tree or woodland species, or currently nonstocked
but formerly having such stocking; and not developed for use other than growing trees. Thus, stands that
have recently been clearcut, but not developed to another land use still qualify as forest. Commercial tree
plantations (except orchards and Christmas trees) are classified as forest. Table 1 provides approximate
guidelines as to how many trees are necessary to meet the 10 percent stocking requirement.
Table 1. Number of Trees Required for 10% Stocking, by DBH Class
DBH Class'
Size of Area
Inches
Seedlings
2
4
6
8
10
12
14
16
18
20
Centimeters
-
5
10
15
20
25
30
35
40
45
50
1 Acre
100
94
77
57
40
26
19
15
12
10
9
1/24 Acre
4
4
3
3
2
1
1
1
1
1
1
1 Hectare
250
234
192
142
100
65
48
38
30
25
22
1/60 Hectare
4
4
3
3
2
1
1
1
1
1
1
'Seedlings, 2 inch (5 cm), and 4 inch (10 cm) trees occurring in clumps are counted as 1.
To qualify as forest, the site in question must be attached to forest land that is at least 1 acre (0.4
hectare) in area and at least 120 ft (36.6 m) wide. Note that wooded areas less than 120 ft (36.6 m) wide
are considered forest if attached to forest land that meets the minimum size requirements. Strips of trees
in a nonforest matrix that do not meet these minimum qualifications are not recognized as forest and should
be assigned the same land use as the surrounding nonforest area.
Within forested areas, include as forest such associated features as unimproved woods roads, firelines,
rock outcrops and natural openings less than 1 acre (0.4 ha), and streams less than 30 ft (9 m) wide). •
Exclude all other land uses developed by man, regardless of size (i.e., improved roads, utility rights-of-way,
house sites, canals).
Forest land is subdivided into three different categories-timberland, reserved timberland, and woodland
(Land Use codes 01, 12 and 13, respectively). If any part of a plot is assigned one of these three land
uses, that entire plot is classified as a forest plot. Timberland is capable of producing 20 cu ft of wood per
acre (1.4 m3/ha) per year, whereas woodland is not. Reserved timberland meets the minimum productivity
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EMAP Forest Monitoring, Appendix D, Rev. No. 0, October, 1994, Page 2 of 3
requirements but has been withdrawn from commercial timber production by law. Examples of reserved
timberiand include national parks, wilderness areas, and some state parks.
In some cases, the separation between timberiand and woodland is difficult. Follow regional FIA
procedures to separate timberiand from woodland in borderline cases. Since FHM sampling procedures
conducted on all three types of forest are identical, distinctions between timberiand and woodland are not
critical in such situations and can be verified with growth data obtained from the plot.
Inaccessible Forest
Whole plots or portions of plots can be inaccessible because permission is denied by the landowner
(Land Use code 10), or because some hazardous condition prevents occupation of the site (Land Use code
11). Land Use codes 10 and 11 should not be utilized if the inaccessible area would otherwise be
classified nonforest. In such cases, use the appropriate nonforest land use code. However, if there is any
chance the site in question might be forest, classify it as inaccessible forest.
If a potential forest plot is entirely inaccessible, it should be assigned a Current Plot Status of "3" if
permission has been denied, or "4" if it is a dangerous plot (Section 1). Procedures for recording plots that
are entirely inaccessible are outlined in Section 1.
Nonforest Land
Nonforest is land currently developed for use other than growing trees; land that has never attained
the minimal stocking to qualify as forest; or land that does not meet the minimum area to qualify as forest.
Procedures for recording plots that are entirely nonforest are outlined in Section 1. Various nonforest land
uses recognized by FHM are defined as follows:
Cropland (Land Use code 02). Land that has been actively cultivated within the past 2 years, including
orchards and Christmas tree plantations but excluding improved pasture.
Improved Pasture (Land Use code 03). Land currently improved for grazing by fencing, cultivation,
seeding, irrigation, or clearing of trees and brush.
Rangeland (Land Use code 04). Land on which the natural plant cover is composed of vegetation
valuable for forage (native grasses, forbs, and shrubs) and less than 10 percent stocked with tree or
woodland species.
Idle Farmland (Land Use code 05). Former croplands, orchards, or improved pastures that have not
been tended within the past 2 years and are less than 10 percent stocked with tree or woodland
species.
Other Farmland (Land Use code 06). This includes area such as farmsteads, bams, and other
buildings.
Urban and other development (Land Use code 07). These include suburban areas developed for
residential, industrial, or recreational purposes; schools; cemeteries; improved roads; railroads; airports;
beaches; powerlines and other rights-of-way; canals; or other nonforest land not included in any other
specified land use.
Marsh (Land Use code 08). Land characteristically supporting low, herbaceous, or shrubby vegetation;
intermittently covered with water; and jess than 10 percent stocked with trees or woodland species.
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EMAP Forest Monitoring, Appendix D, Rev. No. 0, October, 1994, Page 3 of 3
Water (Land Use code 09). Streams, sloughs, and estuaries more than 30 ft (9 m) in width. Lakes,
reservoirs, and ponds more than 1 acre (0.4 ha) in size.
Rocky, barren, excessively steep terrain (Land Use code 14). Naturally occurring areas of rock talus,
outcrops, cliffs, or steep terrain that do not support 10 percent tree stocking.
Natural alpine clearings (Land Use code 15). Nonforested alpine openings that are not specifically
used as rangeland for domestic livestock. These areas are characterized as having native grasses,
forbs, and shrubs as the predominant cover.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 1 of 10
Appendix E
Safety Plan
Section/Title
Page
1 Overview 2 of 10
2 Potential Field Hazards 2 of 10
3 Travel 2 of 10
3.1 Defensive Driving 3 of 10
3.2 Accident Reporting 3 of 10
3.2.1 Operator's Responsibilities 3 of 10
3.2.2 Supervisor's Responsibilities 3 of 10
3.3 Travel itinerary 3 of 10
3.4 Animal Travel 4 of 10
3.4.1 Assigning and Handling Stock 4 of 10
3.4.2 Horse Riding 5 of 10
3.4.3 Packing x. . 6 of 10
4 Weather Extremes 6 of 10
5 Terrain 6 of10
6 Insect Pests, Poisonous Organisms, Large Mammals 7 of 10
7 Sampling and Sampling Equipment 7 of 10
8 Tree Hazards 8 of 10
9 Training 8 of 10
10 Documentation 8 of 10
11 Personal Protection 10 of 10
12 Accident Reporting 10 of 10
13 Safety Equipment 10 of 10
14 Visitor Safety Precautions 10 of 10
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 2 of 10
1 Overview
Safety is a critical component of any field operation. Field personnel must be aware of potential safety
hazards, follow all project safety protocol and equipment guidelines, and be prepared for emergency
situations. This plan addresses potential safety hazards of field sampling and identifies required safety
protocols. Individual federal, state, and private participants .must also follow their individual agency safety
guidelines that supplement requirements outlined in this plan.
Regional coordinators are responsible for the appropriate safety training being completed during field
crew training prior to the field season.
(NOTE: Operations, field crew, and supervisory personnel involved in FHM studies must read and fully
understand all safety procedures contained in this plan.)
2 Potential Field Hazards
Field samplers will encounter hazardous field operations about which they must be aware and informed
concerning proper precautions. Some potential hazards discussed in this section are:
• Travel.
• Weather extremes.
• Terrain.
• Insect pests, poisonous organisms, large mammals.
• Sampling equipment (firearms).
• Tree hazards.
• Sampling.
3 Travel
Vehicles used for traveling on backroads should be well maintained to ensure safe travel. Clean
windows and headlights frequently to reduce dirt and grime buildup from off-road travel. Four-wheel drive
vehicles and vehicles with high clearance are preferred. Table 1 lists items required for field vehicles.
Table 1. Required Vehicle Items
1. Spare tire, jack, lug wrench
2. Fire extinguisher
3. Shovel
4. Winch/come-along *
5. Flashlight
6. Spare fuses
7. Tow strap*
8. Gas can
9. Cleaning fluid, wipes
10. Jump cables
11. Flares
12. Short wave radio *
13. Toolkit
14. Spare belts & hoses
15. Accident reporting kit
16. Water container
Suggested in at least one vehicle as determined by the regional coordinator.
Wear seat belts at all times while the vehicle is in motion. Drivers must follow all rules and regulations
of the state in which they are traveling. Never use a vehicle which is unsafe. Make necessary repairs as
soon as any unsafe condition develops. If long trips to remote sites occur, acquire extra gasoline and store
it in an approved carrying container. Store extra potable water in vehicles.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 3 of 10
3.1 Defensive Driving
Defensive driving training and certification is strongly suggested and may be required at the discretion
of the regional coordinator.
1. Make sure driver is well-rested and alert.
2. Ensure any medication taken does not cause drowsiness.
3. Limit daily travel to 400 miles per person. If possible, rotate driving responsibilities.
4. Make all drivers aware of the travel itinerary and planned routes. Vehicles should attempt to travel
within view of each other.
5. If possible, drivers should not ride alone.
6. All passengers must wear seat belts.
7. No smoking is allowed in vehicles.
8. No drinking and driving. Use the designated driver system.
3.2 Accident Reporting
3.2.1 Operator's Responsibilities
Drivers should follow accident-reporting protocols of their agency. They must know and understand
these protocols. Follow these procedures after an accident:
1. Stop immediately and determine whether anyone is injured. Help any injured secure prompt
medical care.
2. Take all precautions to prevent additional accidents by placing flares and stationing persons to
direct traffic. . .
3. Notify all proper authorities as required by law and your supervisor and regional logistics
lead/coordinator.
4. Do not sign any papers or make any statements concerning liability except as instructed by your
agency's guidelines.
5 If practicable, fill out a motor vehicle accident report according to your applicable federal or state
guidelines. Specific guidelines will be in the vehicle. You can fill out the report later, but it must
be submitted to the supervisor before the close of business the following day.
6. If you receive a citation, subpoena, summons, tag, or ticket as a result of driving a project vehicle,
you should notify your supervisor immediately.
3.2.2 Supervisor's Responsibilities
Whenever a vehicle operator is injured and cannot comply with the above requirements, the field
supervisor should report the accident to the state, county, or municipal authorities as required by law, and
complete and process applicable federal or state forms. Supervisors should immediately notify the regional
coordinator or his/her representative of the accident so that an investigating officer can be appointed.
3.3 Travel Itinerary
Use the crew update system (see Section 8) to communicate travel itineraries to management.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 4 of 10
3.4 Animal Travel (from the USDA Health and Safety Code Handbook on Stock,
Pack, and Riding Safety)
Accept only animals known to have or at least display no dangerous habits. Make an effort to discover
dangerous habits of strange animals without endangering yourself. If dangerous habits are discovered and
cannot be corrected easily, remove the animals from service. Assign only thoroughly experienced persons
the job of breaking and training saddle and pack stock. Stock used by employees must be gentle and
properly broken.
3.4.1 Assigning and Handling Stock
Use care in assigning stock to employees; all stock can be potentially dangerous.
Speak to animals when approaching them; avoid approaching them from the rear.
Handle animals carefully after prolonged layoffs.
Always lead an animal around after being saddled and before being mounted or packed. Keep a firm
hold on reins or lead rope. Never wrap them around the hand. The lead rope should be approximately
10 feet in length and should be smoothly braided at the free end with no knots or loops. Avoid excess lead
rope that may become entangled with hands or feet.
Never carry equipment on a saddle horse. Do not carry tools and equipment in your hands while
riding.
Before saddling, and at the end of each day's use, brush stock. Rub down lathered horses with a cloth
and walk them until dry.
When tying a horse:
1. Avoid slack that might entangle horse or person. Tie with no more than 4 feet of slack and make
the tie at least 4 feet above the ground.
2. Avoid tying to a wire fence.
3. Never position yourself directly in front of a solidly tied animal.
4. Tie horse to an object he cannot walk completely around, whenever possible.
5. Use a halter if the horse is to be tied for long periods. Use a rolling slipknot around the object to
which the horse is to be tied. Never use the bridle reins to tie an animal.
6. Use cotton ropes at least Va-inch diameter for picket and lead ropes.
7. Unless picketing, never tie a horse to a small log or any other object the horse can move. Slight
movement of an object can frighten the animal.
8. Stand or kneel to the side when hobbling animals.
Keep stock away from loose wire. Clear away loose wire and other hardware.
Never feed or water a sweaty horse until it has cooled off, except when on the trail, and use is to
continue after watering.
Be specifically careful when feeding several horses together in a pasture or corral. Some of the most
gentle saddle animals are fighters at feeding time.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 5 of 10
3.4.2 Horse Hiding
When saddling, always make sure rigging, latigos, and cinches are in condition.
Wear riding boots, field boots, or workshoes that will not hang up in stirrups. See that only experienced
riders wear spurs.
Wear snug-fitting clothing. Wear chaps in brushy country. Do not wear a hardhat.
When off the horse, check position of blanket and saddle and tightness of cinch. Look for worn or
broken straps, cinches, reins, and in brushy country, for trash under blanket.
When dismounting, move left foot back so ball of foot is in stirrup before swinging off.
Mounting -
Before mounting:
1. Lead a horse a short distance after cinching.
2. Check cinch again.
3. Take up slack in reins.
4. Bridle stock before mounting.
5. Check stirrups for correct positions.
a. Rider should stand close to left shoulder, facing animal's rear.
b. Take mane or saddle horn in left hand, gripping reins firmly, near rein tight, off rein slack, so
twist of wrist can pull horse to you if it becomes unruly.
c. Turn back side of near stirrup toward rider.
d. Place left foot in stirrup.
e. Grasp saddle horn with right hand and swing into saddle quickly but lightly.
f. Avoid scratching horse with spurs or heels when mounting.
6. Insert only toe of boot into stirrup. Do not shove feet clear into stirrups. If wearing field shoes, ride
on balls of feet.
Riding --
1. Be alert to animal's movements and guide it firmly but gently. Test animal's reining habits. Do not
hold a tight rein unless necessary to restrain forward movements.
2. Sit straight in the saddle and keep reins gathered in so horse knows you are in command. For
comfort, carry about half of your weight in the stirrup and the other half on your buttocks.
3. Be alert for insects and animals that may spook your stock.
4. Never wrap or tie reins around the saddle horn.
5. Never ride a horse when lightening storm is nearby.
6. Always keep lead ropes free when leading stock while riding a saddle horse. Never tie the lead
rope around the lead horse's saddle horn or wrap rope around hand.
7. Watch the slack in the lead rope to avoid animal's straddling or stepping over it, and to keep it from
getting under the lead horse's tail.
8. Get off and lead a horse across excessively rocky or steep terrain and corduroy, or pole bridges.
9. Never run a horse on hard pavement, frozen ground, uphill, downhill, or in deep snow.
10. Never shoot firearms while on horseback.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 6 of 10
11. When riding, it is good practice to carry a sharp knife to cut rope, cinches, or pack straps in
emergencies.
12. If riding alone, carry a radio. If no radio is available, travel in pairs.
13. Never ride stock bareback without a bridle. Have inexperienced riders always ride with a saddle.
3.4.3 Packing
Always treat pack animals as dangerous.
Have only trained people load or unload stock.
Keep animal's back clean; keep saddle pad straight, saddle blanket smooth, saddle properly fitted and
tight, and side packs of nearly equal weight.
Tie pack animals short to a solid post or hitching rack, with heads pulled slightly up.
Coil lash and sling ropes. Hang on pack saddles until actual packing begins, and immediately after
unloading.
Tie pack string together with rope so animals can free themselves in case of accident. A 1/4-inch loop
tied to the rigging reins or pack saddles makes a good place to tie the lead ropes of an animal being led.
Make the rigging rope on a pack saddle about 1/4-inch size. If an animal in the string falls off a precipitous
trail, the rope can break, reducing the chances of injury to other stock in the pack string.
4 Weather Extremes
The field crew leader should follow daily and weekly weather forecasts.
Field crews should prepare for the summer weather conditions of heat and rain with appropriate gear.
Each person should carry a day's supply of water. Bring extra water in transport vehicles. Apportion
field equipment and samples properly to all field crew members for transport in and out of the field. Each
field crew member should have a set of rain gear. Avoid working in thunderstorms. If caught in a
thunderstorm, set down all equipment made of metal and proceed to vehicles. If in a remote location, seek
low ground. Do not lean against or seek shelter in tall or exposed trees.
5 Terrain
Field crews will be exposed to dangerous terrain conditions such as:
• Steep slopes.
• Thick underbrush (thorns, roots, etc.).
• Loose rock conditions.
• Wet, slippery ground.
• Stream/marsh lands.
• Fence crossing.
• Deep water.
Field wear should include weather-proof field boots with ankle support and slip-resistant (Vibramtm or
similar material) soles. Long pants and shirts are required to reduce cuts and scrapes. Safety glasses are
suggested to protect against eye injury. All field crew members should wear a hard hat.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 7 of 10
6 insect Pests, Poisonous Organisms, Large Mammals
Field personnel may be exposed to insect pests and poisonous organisms such as:
• Mosquitoes • Bees/Hornets
• Biackflies • Ticks (for example, Lyme disease and Rocky Mountain
• Ants Spotted Fever)
• Poison ivy • Snakes
• Poison sumac • Poison oak
The regional coordinator or logistics lead should complete a personal and medical information form for
all field crew personnel (Figure 1) before field sampling begins. Other people visiting the plot, such as audit
staff or managers, should also complete a medical information form before travelling to the field. Keep a
copy on hand at the sampling site and distribute it to proper management personnel. This form lists crew
members and their allergies to insect pests and medicines. Proper medicine should be available for any
field crews with known allergic reactions to insects. Clothes covering the legs and arms can help protect
against insect pests. Insect repellant should be available to field crew members. Snake bite kits should
be available in regions known for poisonous snakes. Approach dogs with care. Consider dog repellant
as standard gear. Poison oak areas should be handled by applying TecNu"" or a similar product before
going into the field.
7 Sampling and Sampling Equipment
Sampling can be hazardous if a person places undue strain upon himself or herself. During training,
proper use of equipment and the limitations of field crew personnel should be addressed.
PERSONAL AND MEDICAL INFORMATION FORM
NAME:
LOCAL ADDRESS: PERMANENT ADDRESS:
LOCAL PHONE NUMBER: PERMANENT PHONE NUMBER:
NEXT-OF-KIN NAME:
ADDRESS:
PHONE NUMBER:
RELATIONSHIP TO YOU:
HEALTH CONCERNS TO BE AWARE OF (please include allergies, etc.):
DO YOU WEAR CONTACT LENSES? GLASSES?
DO YOU WEAR CORRECTIVE LENSES FOR READING? DRIVING? BOTH?
• B you need to wear corrective lenses to do your job, please keep an extra pair with you at all times or else keep a copy of your
proscription on hand.
Figure 1. Personal and Medical Information Form.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 8 of 10
If not used properly and with care, some sampling equipment can be hazardous. Keep cutting
instruments (hand pruners, knives) sharp and closed when not in use. Maintain sheaths for cutting
instruments in good condition. Alert stock packers of sharp or awkward equipment before packing so that
appropriate adjustments can be made. Take care in packing and transporting equipment in and out of the
field. Use equipment according to instructions and routinely examine it for damage.
Wear gloves when possible when working with sampling equipment. Wear eye protection when digging
soil pits and pole pruning. Field crew personnel must wear hard hats when working near branch collection
activities or during local windy conditions.
Each field crew should carry a first aid kit with the contents listed in Table 2. It is strongly suggested
that all field personnel be certified in CPR and first aid; this may be mandatory at the discretion of the
regional coordinator.
Table 2. Contents of a First Aid Kit Carried by Field Crews
1. Small gauze pads (4)
2. Large gauze pad (1)
3. Large muslin bandages (2)
4. Adhesive bandages (16)
5. Eye dressing unit (1)
6. Antiseptic unit of povidone iodine (1)
7. Roll of 2-inch wide elastic bandage (1)
8. Roll of adhesive tape (1)
9. Ophthalmic irrigation solution
10. Aspirin tablets
11. Forceps
12. Scissors
13. Medihaler-Epi (asthma)
14. Chlor-Amine tablets
15. Instructions for using above items
8 Tree Hazards
Trees can present hazards including dead trees that remain upright or lean against other trees and
dead limbs which remain in branches. Upon disturbance during travel to, from, or at a site, and during
branch sampling, limbs and trees can fall. When traveling through the forest, be aware of hazards in the
overstory. Wear a hard hat at all times in the forest. Branch samplers should know the location of each
field crew member and warn personnel when dropping or lowering branches.
9 Training
During field training, review all aspects of the safety plan. Crew leaders should conduct a 5-minute
"refresher" safety training before beginning a new week's work. Field crew personal and medical
information forms (Figure 1) should be completed prior to training.
10 Documentation
The Field Crew Personal and Medical Information Form (Figure 1) and Emergency Reference Form
(Figure 2) should be completed before entering the field.
The Field Crew Medical Information Form contains basic information on each field crew member. This
form should be completed after hiring and before sampling begins. Completed forms should be available
to each crew leader and kept with plot packets carried in field vehicles.
The Emergency Reference Form identifies emergency information within the state and county in which
the field crew is working. This information should be available to each field crew member before sampling
begins in a county. Completed forms should be kept with plot packets carried in field vehicles. The
regional coordinator or logistics lead is responsible for completing these forms and informing crew leaders
of their responsibilities to carry the forms in field vehicles.
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 9 of 10
FOREST HEALTH MONITORING
EMERGENCY REFERENCE SHEET
HEXAGON ID NUMBER
STATE:
COUNTY:
HOME OFFICE: (specific for each logistics/regional coordinator)
POLICE:
LOCAL:
STATE:
FIRE DEPARTMENT:
USDA-FOREST SERVICE RANGER STATION:
STATE FORESTRY COMMISSION:
LOGISTICS/REGIONAL COORDINATOR:
NE Detection Monitoring: Andy Gillespie, USDA-FS, Radnor, PA.
SE Detection Monitoring: Bill Bechtold, USDA-FS, Asheville, NC.
AL Detection Monitoring: John Vissage, USDA-FS, Starkville, MS.
CO Detection Monitoring: Bill McLain, USDA-FS, Ogden, UT.
CA Detection Monitoring: Leon Liegel, USDA-FS PNW, Corvallis, OR. 503-750-7299 (office)
503-750-7348 (after hrs)
Regional/ State/ Field Coordinator
215-975-4035 (office)
704-257-4357 (office)
601-323-8162 (office)
801-625-5381 (office)
(Please add the name and number of key point-of-contact in your region or state.)
HOSPITAL/CLINIC:
DIRECTIONS TO HOSPITAL/CLINIC:
Figure 2. Emergency Reference Sheet
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EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 10 of 10
11 Personal Protection
The following items of personal gear are required for field sampling:
• Hard hats.
• Safety glasses.
• Work boots with Vibramtm soles or similar traction.
• Work gloves.
• Rain gear.
• Foil fire survival kit for fire areas.
In addition, each crew member should have a day's supply of water available. Adequate amounts will
vary depending on local terrain and weather conditions.
12 Accident Reporting
If a field crew person is injured, notify the crew leader immediately. The injured person, unless
incapacitated, provides first aid treatment to himself or herself, and, if necessary, should be assisted to the
nearest medical facility. The person must immediately notify the regional coordinator or logistics lead so
that the accident can be properly documented.
13 Safety Equipment
Vehicles should maintain the equipment listed in Table 1.
• Maintain a field crew first-aid kit as listed in Table 2.
A snake bite kit should be available in regions where poisonous snakes exist.
The emergency telephone numbers and radios should be available for med-evac if a hospital is
not < 1 hour driving time from a field plot.
14 Visitor Safety Precautions
All visitors to FHM field activities (auditors, indicator representatives, managers, etc.) must inform the
Regional Logistics Lead/Field/State Coordinator before joining a field team on a plot. The Regional
Logistics Lead/Field/State Coordinator will coordinate the visit so that visitors bring appropriate attire, food,
and water and are aware of unique safety concerns for particular areas (e.g., elevational gradient, steep
slopes, poisonous plants).
OU.S. GOVERNMENT PRINTING OFFICE: 1995-650-006-22021
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