c/EPA
United States
Environmental Protection
Agency
Environmental Research
Laboratory
Narragansett Rl 02882
EPA-600/3-79-061
June 1979
Research and Development
Metabolic
Responses of
Shallow Tropical
Benthic Microcosm
Communities to
Perturbation
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the ECOLOGICAL RESEARCH series. This series
describes research on the effects of pollution on humans, plant and animal spe-
cies, and materials. Problems are assessed for their long- and short-term influ-
ences. Investigations include formation, transport, and pathway studies to deter-
mine the fate of pollutants and their effects. This work provides the technical basis
for setting standards to minimize undesirable changes in living organisms in the
aquatic, terrestrial, and atmospheric environments.
n ~Qi8-av?lS>lf,!°thepublic throu9h the NationalTechnical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/3-79-061
June 1979
METABOLIC RESPONSES OF SHALLOW TROPICAL
BENTHIC MICROCOSM COMMUNITIES TO PERTURBATION
by
S. V. Smith
P. L. Jokiel
G. S. Key
E. B, Guinther
Hawaii Institute of Marine Biology
Kaneohe, Hawaii 96744
Grant No.: R800906
Project Officer
Kenneth T. Perez
Environmental Research Laboratory
South Ferry Road
Narragansett, Rhode Island 02882
ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U. S. ENVIRONMENTAL PROTECTION AGENCY
NARRAGANSETT, RHODE ISLAND 02882
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DISCLAIMER
This report has been reviewed by the Environmental Research Laboratory,
Narragansett, U. S. Environmental Protection Agency, and approved for
publication. Approval does not signify that the contents necessarily reflect
the views and policies of the U. S. Environmental Protection Agency, nor does
mention of trade names or commercial products constitute endorsement or
recommendation for use.
ii
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FOREWORD
The Environmental Research Laboratory of the U. S. Environmental
Protection Agency is located on the shore of Narragansett Bay, Rhode Island.
In order to protect marine resources, the.laboratory is charged with
providing a scientifically sound basis for Agency decisions on the environ-
mental safety of various uses of marine systems. This requires research on
the tolerance of marine organisms and their life stages, as well as eco-
systems, to many forms of pollution stress. In addition, a knowledge of
pollutant transport and fate is needed.
The report that follows describes the use of flow-through aquaria for
establishing, maintaining and monitoring shallow tropical benthic communities.
Such studies are a logical intermediate point between laboratory bioassays
and field surveys. The project is also intermediary between an earlier
analysis of coral response to thermal stress and a present analysis of the
responses of an entire ecosystem to the termination of sewage stress.
Eric D. Schneider
Director
ERL, Narragansett
iii
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ABSTRACT
Benthos communities simulating various aspects of coral reefs were
established in 600-liter microcosm tanks. These communities were then
subjected to various environmental perturbations, including altered light
regime, altered substratum type, salinity depression, elevated nutrient
level, and biological manipulation. The metabolic responses of the
community to these perturbations were monitored, primarily by analysis
of dissolved oxygen flux. Light, substratum type, and nutrient levels
are resources which limit community metabolism. From 35 to 22 °/oo,
metabolism is not sensitive to salinity. Salinities below 22 °/oo kill
most test organisms. Metabolism is sensitive to biological manipulation.
iv
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CONTENTS
Foreword
Abstract iv
Figures . vi
Tables • • • • viii
Acknowledgments ix
1. Introduction ....... 1
2. Conclusions ..... 6
3. Recommendations 8
4. Utilization ......' 9
A. Description of microcosms used in
this study 9
B. Manipulation of the microcosm environment . . 9
C. Methods of structural manipulation and
analysis in microcosms 11
D. Methods of functional analysis in
microcosms ..... ....... 11
E. Flushing characteristics of microcosms
and natural ecosystems 13
F. Gas exchange in HIMB microcosms 16
G. Relationship of A02 to ACOa 16
H. Replication and reliability of
metabolic measurements .... 17
5. Microcosm Community Metabolism ............ 19
A. Light 19
B.. Substratum 29
C. Nutrients ........ 33
D. Salinity 36
E. Biological manipulation 39
F. Conclusions ......... . . 42
References • 44
Appendix: Design, Construction, and Operation of Shallow
Tropical Benthos Microcosm Facilities ........... 47
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FIGURES
Number Page
1 Configuration of the HIMB microcosm facility 10
2 Return of altered salinity to ambient as a.function
of tank flushing 15
3 A. Curve of ambient solar radiation over 24 hours .... 20
B. Dlel response of oxygen flux with and without
fouling communities 20
4 Solar radiation versus oxygen flux for four successive
measurement periods in the same tank . , . 21
5 Comparison of oxygen fluxes among replicate treatments
under identical light regimes ".. 24
6 Solar radiation versus oxygen flux treatments 25
7 Comparison of replicate tank oxygen fluxes . % 27
8 Solar radiation versus oxygen flux of benthos
communities developed on various substrata ....... 30
9 Direct comparison of oxygen flux on rubble versus
sand and mud substrata 32
10 Solar radiation versus oxygen flux for "low nutrient"
(bay water) and "high nutrient" (bay+well water)
treatments . 34
11 Direct comparison of "low nutrient" (bay water) versus
"high nutrient" (bay-Hwell water) treatments 35
12 Solar radiation versus oxygen flux under various
salinity regimes . 38
13 Solar radiation versus oxygen flux in tanks with and
without herbivorous fishes 40
A-l Map showing locations of HIMB and NUC microcosm facilities 48
vi
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A-2 A. Arrangement of standpipes in Inlet headbox ...... 52
B. Arrangement of standpipes in outlet headbox 52
A-3 Schematic diagram depicting the HIMB water sampling
system 54
A-4 Enlargement of area of water sampling system (see
Figure A-3) which measures oxygen, salinity
and temperature ......... 55
vi±;
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TABLES
Number Pa8e
1 An example of typical community succession ^2
2 Regression equations for data presented in Figure 4 .... 22
3 Analysis of covariance for data in Table 2 and Figure 4 . . 23
4 Analysis of covariance for data in Figure 5 25
5 Analysis of covariance for data in Figure 6 26
6 Analysis of covariance for data in Figure 8 31
7 Analysis of covarianca for data in Figure 6A, B and
Figure 8A 31
8 Comparison of typical dissolved inorganic nutrient levels
in bay water drawn through microcosm facility with sea
water well 33
9 Analysis of covariance foe data in Figure 10 ........ 35
10 Organisms introduced into fouling communities
for salinity stress experiments ..... 36
11 Chronology of salinity stress experiments 37
12 Analysis of covariance for data in Figure 12 ... 39
13 Analysis of covariance for data in Figure 13 41
14 Analysis of covariance, no fish versus fish, rubble .... 41
15 Analysis of covariance, reef rubble versus
echinoids versus fish ...... ...... 42
vlii
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ACKNOWLEDGMENTS
We are grateful to our many colleagues at the Hawaii Institute of Marine
Biology, Kaneohe, Hawaii, and at the Naval Undersea Center (now the Naval
Ocean Systems Center), Kailua, Hawaii, for their considerable assistance on
various aspects of the study. Dr. John E. Bardach served as principal
investigator during the course of the study, and Dr. Sidney J. Townsley did
so during its initial year; we thank them both. We owe a particular debt of
gratitude to the many students who worked long, and largely underpaid, hours
to insure the success of the program.
ix
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SECTION I
INTRODUCTION
Biological communities in natural settings are the product of a complex
and largely unknown history of physical-chemical stimuli and organism re-
sponses and interactions. Attempts to explain the composition and function
of communities and organisms in natural settings often do not arrive at a
quantitatively satisfactory understanding of how the communities might change
in response to perturbation. Biologists have frequently turned to laboratory
or aquarium studies of single organisms or populations to avoid the complex
and uncertain history of natural communities. Attempts to build a community
analysis from such observations are ordinarily frustrated by the lack of
realism in physical, chemical, and biological characteristics within the
aquaria. The logical compromise is to maintain several species and trophic
levels of organisms as an ecologically functional unit, and expose this unit
to realistic and controllable physical-chemical conditions. The term
"microcosm" has been applied to various artificially maintained biological
assemblages that function as largely self-contained functional units. Beyers
(1963) lists the following terms as having been applied to artificial aquatic
ecosystems: microcosm, aquarium microcosm, carboy microcosm, microecosystem,
experimental ecosystem, and laboratory-scale model. Other terms have appeared
in the ecological literature since that time, including "synthetic microcosm"
(Nixon, 1969), "gnotobiotic ecosystems" (Taub, 1969), and "artificial open
systems" (Confer, 1972). The term "microecosystem," while perhaps more de-
scriptive than "microcosm," is awkward , and not entirely satisfactory. Thus,
the term "microcosm" will be used throughout this report.
Using microcosms to study effects of,environmental change in aquatic
environments represents a logical advancement in the evolution of pollution
research. Early aquatic pollution research was mainly concerned with such
public health problems as the spread of disease through contamination of
drinking water. During the 1930's and 1940's it became apparent that new
tools were needed to understand the impact of pollution on aquatic systems.
Efforts led to the development of the toxicity bioassay, which uses a single
organism, (usually a fish) to "model" the response of an ecosystem to pollu-
tion stress, ,,,During the 1950' s and I9601s the toxicity.bioassay became an
increasingly sophisticated technique.
The earliest tests were short (24-hour) static tests. Further work
showed that the toxicity bioassay model became more predictive of true bio-
logical impact as exposure time,was increased (to 48 hours, 96 hours, and even
longer) and if continuous flow was used. An extensive body of published in-
formation .on.proportional diluters andmethods of analyzing mortality data
developed. The model was refined by including considerations of synergistic
effects such as natural light rhythm, temperature, oxygen tension, and,
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reproductive state; use of the most sensitive organism as an indicator further
refined the assays. Another refinement was use of the most sensitive life
stage of the organism as the bioassay model. The model was further refined
by using measures of metabolism (e.g. fish respiration), rather than mortality,
as the index of stress. Other advances led to the inclusion of a full range
of test organisms (molluscs, crustaceans, etc.), in addition to fish, in the
14th edition of Standard Methods for the Examination of Water and Waste Water
(Anonymous, 1976).
During the last decade, it has become increasingly evident that even
more sophisticated and complex analytical techniques are needed to predict
ecological effects of pollution. The study of complex multi-compartment
living systems and their physical environments plays an increasing role in
pollution research. It was inevitable that researchers would develop more
complex simulations of complex natural systems. These simulations were
microcosms, a logical extension from classical single-organism bioassays to
a multi-component analysis. The microcosm includes all the features of the
bioassay and differs only in complexity. The methodology, philosophy, and
application of the bioassay that developed over the years led directly to
microcosms. Use of metabolic variables, natural light regimes, prolonged
sublethal stress, and continuous-flow apparatus originated with classical
bioassay technique.
The microcosm provides an interface for interaction among various
scientific disciplines. At the same time that pollution researchers were
moving from single organisms towards organism interactions, ecologists were
also in a period of transition. Classical ecology began with studies of
natural systems in the field. Difficulties with interpreting and manipulat-
ing natural communities led to simplifications in the laboratory.
The microcosm is, at once, a complicated version of the pollution
researchers' original bioassays and a simplification of the ecologists'
traditional field observations. The microcosm approach will not replace
existing techniques but will be used to study questions not amenable to
present investigative methods. In order to include the microcosm technique
in ongoing programs, one must consider potential uses and alternative
techniques.
In many instances, the microcosm is clearly the method of choice. Popu-
lation or community level trophic interactions are not predictable from data
gathered on single organisms. Size and complexity of natural ecosystems
ordinarily make in situ manipulation impractical. The microcosm represents
an experimental approach which has been used successfully to isolate and
analyze processes in aquatic ecosystems. Examples of this type of study in-
clude predator-prey interactions (Hall et al., 1971), pelagic food-chain
dynamics (Mullin and Evans, 1974), diurnal metabolic patterns (Beyers, 1963),
patterns of autotrophic succession (Cooke, 1967), and the recycling of
sewage effluent materials through marine food chains (Ryther et al.t 1972).
Microcosms may be constructed'and scaled according to differing criteria.
One criterion might be to attempt to simulate an entire ecosystem in terms of
the concentration and relative abundance of major abiotic and biotic
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components. Our criterion has been to simulate relatively restricted com-
munities, or parts thereof. Ecosystem-level simulations can be achieved "by
linking (e.g. via water flow) community-level microcosms.
Microcosms represent the logical union of laboratory and field investi-
gative technique. Hence, microcosm experiments utilize various types of
laboratory techniques and concepts developed for use on single species (e.g.
mortality measures, metabolic techniques, growth measures, etc.)> combined
with standard field sampling techniques and concepts (e.g. fouling panels,
subsampling the community for epifauna, infauna, plankton and other compo-
nents, sediment analysis, community photosynthesis and respiration, etc.).
The various techniques of microcosm analysis fall into two broad
categories: functional analysis and structural analysis. Odum (1962) de-
fines biological "structure" of an ecosystem to be the composition of the
biological community including species, numbers, biomass, life history, and
distribution in space of populations. That is, biological structure is the
nature of the biota in an ecosystem at an instant in time. Odum defines
"function" to be the rates of material, energy, and information flow through
the ecosystem.
Function is often amenable to direct total-system monitoring; such
integrative monitoring reduces the need for the laborious and inherently im-
precise summation of structural components to understand the system. For
example, many organisms contribute to the biomass of a community; carbon flux,
which is a time-differential function of biomass, can be directly measured in
the water column and can be used to assess the change in biomass with time.
The assessment is properly weighted and integrated according to the contri-
bution of each component to ecosystem changes, whereas biomass need not have
any direct and/or constant relationship to energy flow or material flux.
Moreover, non-destructive methods of measurement can be employed with
functional assessment.
Because microcosm technique invites the simultaneous use of numerous
methods and involves very complex multi-compartment systems, it is vital not
to lose sight of this unifying relationship between structure and function.
Ultimately the goal of environmental research is to predict the exact nature
of the structural/functional relationship for ecosystems influenced by human
activity.
Inclusion of microcosm facilities in a;well-planned environmental pro-
gram provides many research advantages, but the technique must.also be evalu-
ated in terms of .time and cost. Advantages and disadvantages which will
ultimately influence utilization of continuous-flow microcosms can be sum-v
marized as follows:
Advantages
1. Microcosms are the most suitable method available for studying cer-
tain community-level processes; the size and complexity of natural eco-
systems make them impractical to manipulate experimentally. Experiments
based on single organisms do not predict community responses. The microcosm
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consists of major biological components of natural communities, and there-
fore should be a better tool for predicting ecosystem responses to perturba-
tion than are single organisms.
2. Various structural and functional responses can be observed simul-
taneously. Growth, reproductive state, recruitment, mortality, individual
component metabolism, material and energy pathways can be identified and
measured. Sensitive indicator species for a given stress can be quickly
identified.
3. Microcosms are extensions of the natural world. Hormal diel varia-
tions in ambient conditions can be duplicated. Natural foods and recruit-
ment are provided. Normal seasonal variations are followed, and natural
serai development is allowed.
4. Wastes, biogenic toxins, hormones, and pheromones can be kept at
near-natural concentrations.
5. Microcosms represent a middle stage between controlled laboratory
experiments and in situ field observations.
6. Microcosms offer research flexibility. Units can be connected in
series; thus progressive de-toxification or stripping processes may be
studied. Conversely, a single unit may be simultaneously used for a number
of non-destructive studies. Microcosms may be used as a sorting technique
for the identification of potential bio-indicators.
7. Various perturbants can be introduced into replicate microcosm
communities or communities with specified differences under controlled con-
ditions. Sub-lethal stress levels may be used, because long-term experiments
are feasible; such experiments also lend themselves to chain-response
studies in complex communities.
8. Electrochemical probes and automatic recording systems can be added
to the microcosms, facilitating continuous observation. Large amounts of
data gathered in this manner can be processed automatically.
9. Because microcosms can be more precisely controlled and monitored
than the natural systems they simulate, the microcosms are amenable to the
validation of mathematical ecosystem models. Accurate mathematical descrip-
tions of natural systems are a major objective of the environmental sciences,
because only with high-speed simulation of ecological pressures can a proper
evaluation be made of the likely long-term environmental effects of manage-
ment decisions.
Disadvantages
i .,-h T?e COSt °f a comPlex microcosm facility is high, and considerable
lead time is required to build such a facility.
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2. Nearly continuous pump operation is required in flow-through micro-
cosms; there are high maintenance costs, as well as considerable experimental
risk of breakdown.
3. Biological recruitment into the system may be largely uncontrolled,
or controlled with difficulty.
4. There are constraints on the manipulation of certain variables
(e.g. salinities higher than ambient are possible but difficult) and also on
the size of the microcosm. Although size limits have not been thoroughly
investigated, not all components of a given community (large carnivores, for
example) can be effectively accommodated.
Within this context of potential and realized utility of aquatic micro-
cosms, this report describes the design and utilization of microcosms
appropriate for shallow tropical benthos communities. Because these com-
munities may be complex, heterogeneous, fragile, and metabolically active
(e.g. coral reefs), we have been forced to consider and overcome numerous
specific operational problems. Many design characteristics of the resultant
product, as well as many of the scientific findings, can be transferred to
other situations. We refer, in particular, to the report by Henderson et a1<
(1976) comparing the Hawaii Institute of Marine Biology microcosm facility
with a companion facility designed by the Naval Undersea Center.
The focus of this study has been the design and construction of an
experimental microcosm facility for the culture of integral benthic communi-
ties, under conditions which are more representative of natural situations
than simple laboratory aquaria, and at the same time, are easier to control,
manipulate, and monitor than the complex communities of real-world coral
reefs.
Design, construction, and utilization of the facility were interrupted
by funding breaks between each fiscal year of the program. These interrup-
tions complicated the maintenance of personnel, continuation of experiments,
and execution of a well-designed experimental chronology. As a result, the
specific environmental lessons learned from our efforts are less than they
might have been. Nevertheless, we have extracted a series of specific
accomplishments which demonstrate the utility of the microcosm facility and
provide insight into shallow tropical benthos ecosystems.
There have been numerous spinoffs of this program. COa has been
investigated as a metabolically useful variable, primarily in situations
other than the microcosms. We have participated with other groups in field
studies at Canton, Christmas, Enewetak, and Fanning Atolls, in the tropical
Pacific Ocean. We have worked with the Naval Undersea Center in the design
and utilization of a second microcosm facility.
5
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SECTION II
CONCLUSIONS
1. General conceptual designs are presented for a microcosm facility
appropriate for simulating shallow tropical benthos communities. These
designs present major considerations for the effective operation of such a
facility.
2. The microcosm facility proves to be a useful tool for the study of
benthic communities over periods of several months. The fouling communities
which develop in the microcosms can be complex, and organisms deliberately
introduced into the facility function normally.
3. Microcosm tanks built according to our design can be characterized
by a physical flushing model of total mixing; for these microcosms, 02 pro-
duction has proven to be a useful metabolic measure. Gas exchange can be
ignored.
4. Shallow benthos communities which have been set up in the tanks are
demonstrably light-limited. The solar conversion efficiency of these com-
munities is high, so naturally or artificially turbid water is likely to be
a significant detriment to the rapid productivity characteristic of reef
communities.
5. Substratum is a second resource which limits the metabolic activity
of microcosm communities. Substratum type is often altered by artificial
activity.
6. The microcosm communities are also limited by nutrient availability,
even though the nutrient loading at our primary microcosm site is high.
Again, nutrient loading is a variable often altered by human impingement on
reef ecosystems.
7. At least three variables (light, substratum, nutrients) are resources
which may simultaneously limit reef production. Thus, heterogeneous benthos
communities, even as simplified in the microcosm situation, do not conform to
Liebig's Law of the Minimum.
8. Salinity down to 22 /oo does not have a demonstrably deleterious
effect on reef ecosystems. The damage done to reefs by stream runoff must
therefore be attributed either to lethal effects due to extreme salinity
depression or to associated variables such as siltation or toxicants.
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9. Within broad limits, organic carbon production by benthic communi-
ties with varying community structure is similar. If grazing pressure is
altered, metabolic response is responsive to quantity (but not particularly
to quality) of altered grazing pressure.
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SECTION III
RECOMMENDATIONS
1. Microcosms should be established and used as logical extensions of
standard bioassay techniques in order to gain a more adequate understanding
of how ecosystems respond to stress.
2. The results reported here are restricted to community oxygen metab-
olism. Examination of C02 and nutrient fluxes should be undertaken, although
oxygen metabolism is by far the easiest variable to automate. Community
structure in the microcosms can also be examined, although variables related
to structure are almost as "noisy" in the microcosms as in natural situations.
3. The oxygen metabolism data are examined by analysis of covariance
with the regression analysis being a convenient method to screen out the '
primary community response to variable (and largely uncontrolled) light
levels .
4. Extended, systematic experiments should be conducted to validate and
refine the results of preliminary experiments reported in this document
Light, substratum, and nutrients are all demonstrably important to reef
metabolism and should be investigated further. Salinity effects amjear
surprisingly minor; this point should also be examined in more detail Bio-
logical manipulation is also an important control of community metabolism
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SECTION IV
UTILIZATION
A. Description of Microcosms Used in this Study
A detailed description involving the design, construction and operation
of the HIMB-NUC microcosm facilities is in the Appendix. The following
section describes briefly specific experimental aspects of the microcosm
units.
The microcosm tanks are 117 cm square by 46 cm deep fiberglass containers
(Figure 1). A continuous gravity-regulated jet (normally 10 liter min-1)
of seawater enters the microcosm through a port in the center of the floor
and leaves the system through a drain in the floor corner. This arrangement
provides mixing of the water without excessive agitation, local turbulence
or bubble formation. Violent entrapment of air alters dissolved oxygen flux
used to calculate metabolism, so such air entrapment must be avoided if
community metabolism is to be measured. Mixing characteristics of the micro-
cosms are discussed elsewhere in this section. The microcosm tank is a well-
mixed, continuous-flow, 630-liter reaction vessel with a mean water residence
time of approximately 1 hour. Inlet and outlet water composition can be
sampled automatically for some variables (dissolved oxygen, pH, temperature)
or manually for others (inorganic nutrients, particulate load, plankton,
alkalinity, etc.).
Alteration of chemical, physical, or biological characteristics of the
influent water is carried out before it enters the microcosms. The particu-
lar tanks used in this study are a manageable size suitable for simulating
the community structure of shallow tropical benthic systems.
B. Manipulation of the Microcosm Environment
The effort to design adequate microcosm facilities was directed at pro-
ducing various living multi-compartment representations of reef communities,
and the means of manipulating the environment within these communities.
During this development program, a variety of factors have been manipulated:
1. Chemical factors—The initial manipulation of water chemistry was
aimed at dissolved nutrient elevation. During the studies reported here,
nutrient elevation was accomplished by mixing relatively low-nutrient water
from Kaneohe Bay with high-nutrient water from a seawater well. Subsequent
nutrient-loading experiments have been accomplished by using a precision
peristaltic pump to add concentrated nutrient salt solutions at 1 to 100 ml
min-1 to the predominantly low-nutrient flow (10 liters min"1). Copper
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SOK7JU5
LAB
IKLCT UATIit LIKES •' 0?riCC
SAtr VttL fJHt
U.S.C.CS- TISE
&1ATION
ST/VATIS WtXINS_
K A KI F 01 Q^r*"*?
^*.*^ ^---f
«•-• -^r»e*w»ur-=!iJ'*«-DiH« TA^K_-! - _. -_ ^-> --_• -•
••~~-"*~^. -^tl«£i ' —=r"*5:. - OAAIM - __ ^-^Sv.
IMTAKC
Figure 1. Configuration of the HIMB microcosm facility.
additions at the NUC facility have similarly been effected by the addition
of concentrated salt solution. In both the reagent additions and the bay
plus well mixtures, the microcosm head boxes serve as mixing chambers.
Salinity alteration was accomplished by adding municipal fresh water
from a large (10 m3) holding tank maintained at a constant head by a vertical
standpipe and an excess of freshwater input. Water was gravity-fed at a
constant flow rate from this tank to the microcosm inlet boxes. This pro-
cedure prevented possible variation in delivery rate from variation in line
pressure.
Dissolved oxygen levels were levered by bubbling nitrogen through the
seawater headbox. The degree of 02 lowering may be adjusted by varying the
rate at which the N2 is bubbled through the inlet head box.
2. Physical factors—Light is one of the most important physical vari-
ables, because it represents the major energy source for plant communities.
The light intensity, spectral quality, and photoperiod encountered on tropi-
cal reefs cannot be easily duplicated in a laboratory. Fortunately, there is
10
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no reason to duplicate such conditions, because microcosms can usually be
located outdoors in full natural radiation. Reduction of light below ambient
levels (such as might occur with high water turbidity) can be simulated by
placing various layers of different neutral-density screening over the micro-
cosms to reduce light. By use of multiple screens of various densities, we
have worked at light levels between 2 and 70 percent of full sunlight.
Temperature is altered by heater-chiller units as described by Jokiel
et al. (manuscript). Substrata of various types are added as required. Mud,
sand, rubble,and hard substrata have been utilized in this program. Water
motion is increased by positioning motor driven agitators of various
horsepower on the microcosms.
C. Methods of Structural Manipulation and Analysis in Microcosms
The microcosm communities used in this study are complex in biological
structure. Several hundred species of organisms commonly establish them-
selves, entering the microcosms as larvae in the seawater. These communities
are rich, complex, and responsive to changes in microcosm environment (e.g.
alteration of substrata, water motion, nutrient loading, light regime,
presence of large grazing fish, etc.). As in the case of natural communities,
an orderly community succession occurs (Table 1). An initial bloom of algae
is followed by settlement of rapidly growing herbivores such as the sea hare
Stylocheilus longieauda, which crop back the algae. Other organisms settle;
in time (usually several months) carnivores and omnivores settle, and a
community which will remain relatively stable through time develops.
Transplanting intact communities from the field can shorten the period or
alter the characteristics of succession and growth. Transplanted communities
are less dependent than the fouling communities on larval recruitment, and
stabilize to ambient tank conditions rapidly. Substrata with associated
organisms are removed from the field and transported to microcosms. The
microcosm community can also be structured by adding fishes, corals, or other
fully grown organisms that otherwise would enter randomly and grow towards
adult size during the course of the experiments. Some large benthic organisms
of a coral reef have lifespans of months to years, and community succession
in reefs is both complex and slow. It is therefore impractical to wait for
larval recruitment to produce a truly mature community in the microcosms.
As experiments are conducted, routine structural subsampling can be
carried out, usually using many of the same techniques that are employed in
field programs. Various subsampling routines have been employed, including
subsampling the substrata, scraping small sections of the wall, or utilizing
fouling panels. Photography is a satisfactory record for many analyses.
Various methods of statistical analysis of community structure may be applied.
Fishes, coral, and other large biota can be removed from the tanks, weighed
individually, and then returned to the tanks.
D. Methods of Functional Analysis in Microcosms
The results presented in this report deal primarily with community
function of the microcosms. Measurement of microcosm community function
11
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TABLE 1. AN EXAMPLE OF TYPICAL COMMUNITY SUCCESSION
Chronology of first appearance of dominant
biota in microcosms at the NUC facility
(Spring 1975), starting with "sterile"
microcosms (from Henderson et a£., 1976).
Weeks of
Flow-
Through
Oiideriant Annelids Echinoderms
Algae Crustaceans Molluscs
1+
2+
3+
4+
5+
7+
8+
9+
10+
11+
12+
diatoms
cyanophytes
filaments and
tufts of algae
green tufts
calcareous algae
amphipods
brownish algae tuftj
Ectocarput
Valonia
Laurenda
Aiptasia pulchella
portunjds
Pennon planissimum
StylocheOus hngicauda
Ctrithium nesioticum
bubble shells
Cheilidonura hirundintjina
Synaptidae sp.
other nudibranchs
Aplysia parvula
Aptysia Juliana
Dotabrifera dolebrifero
DolebeUa euricularia
vermetids
ffydroides sp.
alpheids ipiiorbids
Padina
13+ Hydroclothrus
Colpomenia
14+
• f m
15+
16+
17+
18+
19+
ffippoiysmaltt kukenthalt
Gnethophyllum faciolatum
Strombus maculatus
Cerithiumtinenfis
Cypraea caputterpentis
Echinothrix sp.
Srichopus horrent
Pinna muricata
involves the measurement of net flux of various biologically active materials
(e.g. oxygen, carbon dioxide, nitrogen compounds, and phosphate) through the
system. Oxygen is used most often because it is easily monitored, can be
recorded continuously with a polaragraphic cell, and is a direct measure of
12
-------
net photosynthesis and respiration. There is ordinarily relatively little
variation in the inlet oxygen concentration, so the flux calculations are
straightforward (see discussion below). Such measurements are by no means
restricted to oxygen.
Flux of nitrogen or phosphorus is determined by measuring outlet and
inlet concentrations of the various biologically active forms of these
elements. Large variations in the inlet nutrient levels make nutrient fluxes
difficult to calculate without large numbers of analyses. Measurement of
total carbon flux can be determined using pH, alkalinity, dissolved organic
carbon and particulate organic carbon measurements. Net calcification within
the community can be determined from alkalinity changes alone. Smith and
Key (1975) summarize the use of C02 as a metabolic record in marine eco-
systems. Flux of toxicants such as introduced heavy metals, or chlorinated
hydrocarbons, as well as their effect on community metabolism, can be
measured. After a period of addition, rate of de-toxification and recovery
can be similarly determined.
If inlet concentration, outlet concentration, and flow rate are known,,
the total flux of the material for a steady state microcosm would be
calculated as (outlet concentration - inlet concentration) times .the flow
rate. Steady state conditions are not usually obtained, because most
metabolic processes follow a diurnal rhythm, and because of short-term
variation. Hence, mixing characteristics of the microcosm must also be
considered.
E. Flushing Characteristics of Microcosms and .Natural Ecosystems
In order to measure community metabolism,one must .understand the flush-
ing characteristics of the ecosystems in order to apply appropriate calcula-
tions to the conservative (advective or diffusive) and nonconservative
(-in situ uptake or release) fluxes of metabolically relevant variables. One
may imagine three end members of flushing models on a triangular diagram:
non-mixing stream flow, complete-mixing with continual exchange, and pulsed
exchange. Real world conditions are ordinarily intermediate among these end
members, but many practical situations cluster near one of these conceptual
extremes. It is often possible to take advantage of a natural or artificial
tracer which is strictly conservative in order to describe the appropriate
flushing model. Smith and Pesret (1974) and Smith and Jokiel (1976) have
applied such a technique with salinity in coral reef ecosystems (see also
Smith, 1974).
It would appear that the complete-mixing, continual-exchange model most
appropriately-describes the characteristics of the microcosms. If.this
hypothesis is correct, then any instantaneous alteration.of a totally
conservative property, of incoming waters should be characterized by an
exponential decay,curve from the pre-afteration state to the post-alteration
state. The decay constant should be the inverse residence time.of water in
the tank (i.e. the flow rate of water through the tank divided by tank
volume).
13
-------
Salinity changes during a salinity-alteration experiment demonstrate the
validity of this complete-mixing model for our tanks. The salinity of the
inlet box was abruptly dropped 10 °/oo below ambient (from about 35 °/oo to
25 °/oo) by an admixture of fresh water, and the salinity -in the tanks was
monitored for four hours. Figure 2 demonstrates that, after an initial lag
(related, perhaps, to density stratification) the salinity drop was well
approximated by a negative exponential (mixing) curve. The exponential slopes
yielded water residence times ranging from 53 to 64 minutes; these residence
times agree well with the 60 minute residence time being approximated during
that experiment by the tank flow rate.
The general validity of the complete-mixing model for the microcosms has
been established with conservative properties. We can now turn to nonconser-
vative properties and superimpose these on the model. For a known residence
time, we can now develop the appropriate equations. Let the subscripts 0 and
t denote samples at times 0 and t minutes later; T is the residence time of
water in the tank. X is the inlet concentration and Y is the outlet con-
centration; "a" is a subscript denoting the concentration change of Y attribu-
table to advective flux; "r" denotes the concentration change attributable to
internal reactions. V is the tank volume; Z is the tank depth. F is the flow
rate of water through the tank.
The residence time may be calculated:
T- V/F (1)
The advective concentration change at time t may be approximated by:
Ya = [
-------
z
_l
<
<3
10.0
0.1
• TANK 7 - INLET C
O TANKS- INLET C
O TANK 9- INLET C
T Cmin) r2
53 0.98
61 0.99
64 1.00
DAY 195 SALINITY STABILIZATION
I 2 3 4
TIME (HOURS)
Figure 2. Return of altered salinity to ambient as
a function of tank flushing.
15
-------
F, Gas Exchange in. HIMB Microcosms
Measurements of metabolic rates according to the general flux model
developed in the previous section implicitly or explicitly assume that advec-
tion of water and state changes within the water are the only two processes
of concern. That is not quite true; there can be gas exchange of materials
across the air-water interface. Oxygen is a commonly (including in our
studies) used metabolic indicator, and oxygen exchange across the air-water
interface can be a significant flux term (e.g. Kanwisher, 1963; Kinsey, 1973).
In general, gas exchange rate (R, moles m~2 hr"1) is a simple function
of the difference between partial pressure of the gas in the atmosphere
(Pg, atm) and the aqueous partial pressure (Pw):
R = K .(Pg - Pw) (4)
K is an exchange rate coefficient (moles m~2 hr"1 atm"1). In an open-water
system subject to wind stress, K is clearly a function of wind stress. The
explanation for this relation between K and wind speed (V) is, according to
the model of Kanwisher (1963), that there is a boundary of a finite thickness
which varies in response to wind speed.
We have measured 02 exchange in our microcosm tanks in the following
manner. Flow through a tank with no contained organisms was stopped. The
upwelling of water from the inlet was simulated by putting a submersible
bilge pump, outlet up, in the center of the tank and its pumping rate was
adjusted to approximate the ordinary rate of water flow. The oxygen level of
water in the tank was elevated by bubbling with compressed gas; then that
bubbling was stopped and the loss of 02 from the water was measured.
The measured oxygen exchange rate constant for the microcosms under a
variety of wind conditions averaged 43 mmoles m~2 hr"1 atm"1. This rate is
near the no-wind value given by Kanwisher (1963) and Kinsey and Domm (1974).
We conclude that the rim around the margin of the microcosm tanks and the
negligible fetch in the tanks combine to reduce gas exchange to a minimum.
The observed exchange rate constant is sufficiently small that we can ignore
this process in our calculations. It is generally accepted (e.g. Kanwisher,
1963) that C02 gas exchange is small relative to 02, at least in part because
generally less than 1 percent of the C02 in seawater is present as free C02.
The nominal exchange rate coefficient of 25 moles nT2 hr"1 atm"1 can be used
for C02; the process can, again, be ignored in the microcosms.
G. Relationship of A02 to AC02
Most older studies of coral-reef.metabolism relied on measurements of 02
changes, assumed a metabolic quotient of,-1.0, and calculated carbon flux
directly from 02 data (either with or without a gas exchange correction).
Qasim and Sankaranarayanan (1970) did not assume that 02/ C02 = 1.0, but
rather used RytherTs (1956) suggested "best value" of -1.2. Smith and Marsh
(1973) examined 02 and C02 data for Enewetak Atoll and concluded that the
16
-------
best general relationship between 02 and C02 Is Indeed very near 1. They
noted that there was apparently a more scattered data set in the night
samples, and they attributed this to problems in resolving C02 changes at
night.
We have measured 02 and COj in microcosm runs in which the dominant
organisms were a fouling diatom community. These data again yielded 02/
values very near -1.0, with greater scatter in the nighttime. For the most
part, 02 is an easier measurement to automate than is COz; therefore we report
02 here and assume that the appropriate metabolic quotient is near -1. This
is almost certainly an oversimplification. The quotient does vary, and it is
likely to be a useful environmental indicator in its own right. We will not
pursue that point further in this report.
Carbon dioxide changes in seawater can be related to another important
metabolic process associated with coral-reef systems: calcification. Al-
though we do not pursue C02 analyses in this report, considerable effort has
been devoted during this investigation to the development of appropriate
analytical procedures for measuring metabolic processes via the C02 system.
A publication derived from this study (Smith and Key, 1975), describes the
utility of the C02 system as a metabolic record in calcifying ecosystems,
while another paper (Smith and Kinsey, 1978),- describes the methodology
for C02 measurements in seawater. Under most conditions simulated in the
studies reported here, calcification has been very slow. Subsequent investiga-
tions (Jokiel, 1978) have demonstrated'that coral calcification is sensitive
to water mot-ion, a variable which ordinarily assures low values in the microsms.
H. Replication and Reliability of Metabolic Measurements
In essence, the utility of any environmental variable as a legitimate
and quantifiable measurement of environmental status can be reduced to a
single question: Can the particular variable be easily used to determine
statistically reliable differences between environments in order to provide
a practical means of environmental assessment? Some environmentally valuable
variables are sufficiently slow or difficult to measure that they fail the
second half of this question; unfortunately, many promising measurements of
biological community structure fall into this category. Other easily
measured variables (including many of the chemical parameters which have legal
status) fail to have demonstrable environmental utility within statistical
limits. In general, the problem with using -such variables lies with the lack
of experimental strategy associated with their measurement rather than with
lack of inherent utility of the variables.
Where they can be used, metabolically active chemical variables may be
relatively easy to measure. In at least some environments, these variables
also appear to have environmental significance. In the following section, we
will examine patterns .of metabolic variation within versus between sample
treatments. The data presented are aperies of 02 metabolic rates obtained
for microcosm communities^
17
-------
We extend conclusions about the utility of oxygen metabolism in the
microcosms to Oa metabolism in many real world situations. In those situa-
tions, gas exchange may override the metabolic effects of 02metabolism, so
CO* (including CaC03), inorganic nutrient, and other metabolic fluxes are
likely to prove more useful than 02. Data from the lagoon of Canton Atoll
(Smith and Jokiel, 1976) provide a case of point. In that study, we related
budgets of carbon, nitrogen, and phosphorus to physical and biological
gradients. We suggest, based on the analyses presented in this report and
on the Smith/Jokiel studies, that careful mass-balance budgets of many
metabolically active materials are probably of more use as environmental
measurements than are the absolute values of these components. Unless the
components in question are likely to be major environmental stimuli or
depressants as they deviate slightly from the norm, their rates of deviation
are likely to be more significant than their absolute deviation.
18
-------
SECTION V.
MICROCOSM COMMUNITY METABOLISM
The purpose of the studies reported in this section is to examine the
responses of microcosm community metabolism to changes in environmental
conditions. The experiments reported here use biological oxygen flux as the
primary community metabolic measure and evaluate the metabolic changes that
result from the following forcing functions: light, substratum, nutrient
levels, salinity, and direct manipulations of community structure. The
results are by no means final and are not intended to establish legal or
environmental guidelines. Rather, they are intended to develop and demon-
strate analytical technique for microcosm studies.
After examining several approaches to the data analysis, we have conclud-
ed that it is most useful to present the results in terms of one-way or first-
order effects. Some experiments were conducted in a matrix format to look at
synergistic (or cross-product, or second-order) treatment effects. Invariably
the first-order effects dominated, and higher order effects were barely (or
not at all) detectable above the error terms. We have therefore chosen to
present the results as a series of single-order experiments. It is obvious
that more detailed and exhaustive analyses of community metabolism responses
to environmental variability should be undertaken to define the higher order
effects which surely exist, and these analyses should also examine duration
and frequency of perturbations as well as quality and intensity of perturba-
tions. Those examinations proved to be beyond the practical scope of these
studies> partly due to time losses from funding interruptions.
A. Light
Shallow benthos communities in tropical environments (as represented by
our microcosms) are ordinarily dominated by plants, so a forcing function
which exerts major influence on the metabolism of these communities is light.
The absolute light level has not been controlled (other than "off" or "on")
in the outdoor microcosms during the course of the experiments reported here.
Neutral density filters have been used in other experiments to vary the rela-
tive intensity between treatments. Figure 3 is a typical curve of oxygen
metabolism and light level versus time of day. Two of the tanks (Tl and T3)
represent variously manipulated fouling communities developed in tank micro-
cosms over a period of 38 days. The third tank (T12) shows the calculated
flux associated with water flowing into a clean tank; this may be interpreted
as an evaluation of the "ambient water blank" plus the analytical error of
the method.
19
-------
1200
1800
I JUNE
1200
Figure 3. A. Curve of ambient solar radiation over
24 hours. B. Die! response of oxygen flux
in two tanks with fouling communities (Tl,
;T3) and one .tank with no significant bio tic
component (T12).
Clearly, responses to light dominate metabolism in these microcosm
communities. It is, therefore, necessary first to calculate the metabolic,
response to light and then to examine either residuals within a particular
photic response pattern or differences between responses.
Figure 4 presents four scatter diagrams of half-hour increments of solar
radiation versus oxygen metabolism. The community in question was a
20
-------
cc
2
0.04
0.02
0.00
•0.02
0.04
0.02
0.00
-0.02
0.04
0.02
0.00
-O.O
*
A
-0.008+0.0435-L
^
cP
7304 Tl, rs 0.834
PRE-STRESS CONTROL
+
B &0=-0.004+0.0435-L
2 rt Q
7304 Tl, r =0.872
STRESS I CONTROL
1
-0.003 4 0.0594 -L
7304 Tl, r= 0.862
STRESS 2 CONTROL
4 1
=-0.007 +0.0429 -L
'°
'•
7304 Tl, r = 0.957
POST-STRESS CONTROL
0.5
1.0
1.5
LANGUEYS PER MINUTE
Figure 4. Solar ra'diation versus oxygen flux for
four successive measurement periods in
the same tank.
21
-------
diatom-dominated fouling community which developed on rubble substratum and
tank walls over approximately one month previous to the first metabolism
measurements. Water began flowing in the tanks on 9 June 1973, and diagrams
A through D represent data collected between 10 July and 31 July. Several
observations can be offered.
For this series, the linear relationship between light and oxygen metab-
olism is excellent (correlation coefficient varies from 0.83 to 0.96).
Nevertheless, there are suggestions that the functional relation between
light and oxygen metabolism is non-linear. In all instances, the y-intercept
of the regression lines overestimates the calculated -0-light oxygen flux
(Table 2). In diagrams A through C, the oxygen flux values at intermediate
light levels appear to be underestimated by the regression lines while the
high-light values tend to be overestimated. Diagram C, which has only two
data points above a light value of 0.5 langleys per minute, appears to have
a slightly (although not statistically significant) steeper regression slope
than the other diagrams, with approximately half of their light values
between 0.5 and 1.5 langleys per minute. These observations are all consis-
tent with the generally accepted conceptual model that light becomes progres-
sively less limiting to community or plant metabolism at progressively higher
levels (e.g. Jassby and Platt, 1976).
TABLE 2. REGRESSION EQUATIONS (in the form A02 - a + b-Light)
FOR DATA PRESENTED IN FIGURE 4
Parameters ± 1 standard error unit. For comparison
the directly observed 0-light oxygen fluxes ± 1
s.e. are also reported
s-e- a ± s.e. 0-light 02 flux ± s.e,
A
B
C
D
0.0435 ± 0.0051
0.0435 ± 0.0036
0.0594 ± 0.0084
0.0429 ± 0.0027
-0.00813 ± 0.00384
-0.00356 ± 0.00228
-0.00338 ± 0.00292
-0.00689 ± 0.00216
-0.01775 ± 0.00189
-0.01050 ± 0.00078
-0.00860 ± 0.00160
-0.01033 ± 0.00273
We therefore subjected several data sets to two other regression models.
One mo4el used all data with non-zero light values and considered oxygen
metabolism versus the logarithm of light level. The other model used all
positive light and oxygen values and considered 1/02 versus I/light. This
latter transformation is analogous to the Burke-Lineweaver plot used in
enzyme kinetics and can be used to calculate the parameters of the familiar
Michaelis-Menton hyperbolic curve describing metabolic response to a limiting
substrate.
22
-------
With some data sets, one transformation or the other did improve the
statistical fit (as measured by the correlation coefficient for the data in
their transformed format). Ordinarily the improvement was not dramatic; in
many instances the correlations decreased. The linear fit was actually the
best in the plurality of cases examined. Some data sets showed a poor linear
relation between 0^ and light. Invariably this characteristic proved to be
the result of random scatter which was not improved by the transformations.
We conclude that the routine descriptive analysis of metabolic response to
light in the microcosms is best undertaken by linear regression. We believe
that the functional relationship is non-linear but that examination of the
data in detail for the functional, relationships would require more detailed
case-by-case consideration than would ordinarily be justified in routine
assays of metabolic responses to variables other than light. Resolution of
this question is, of course, fundamental to understanding the energy fluxes
within particular ecosystems.
According to an analysis of covariance (Table 3) the regression slopes
among the four replicate treatments of Figure 4 do not differ significantly
from one another. The regression heights do show significant differences.
Inspection of the mean oxygen fluxes adjusted for varying mean light levels
demonstrates that treatment C is displaced substantially above the other
curves. It has previously been pointed out that the functional relation
between light and oxygen flux is probably non-linear. Substantial differences
TABLE 3. ANALYSIS OF COVARIANCE FOR DATA IN TABLE 2 AND FIGURE A
Lln«
Treatment
i*2
Ixy
Deviations from regression
f Zdyx2 M.S.
A. Analysis of Cov»fiance
1 control period 1 34 6.9322 0.3015 0.01883
2 control period 2 48 8.2333 0.3583 0.020S3
3 control period 3 19 1.0356 0.0615 0.00492
4 control period 4 22 5.4767 0.2347 0.01098
5 within
6 regression coefficient
7 common 123 21.6778 0.9560 0.05526
8 adjusted Beans
9 total 126 23.4467 0.9865 0.05559
Significant difference saong regression coefficients?
*3,U9 • M.S.6/M.S.5 - 0.79 Ho difference
Significant difference among regression line heights?
F3,122 " M.S.8/M.S.7 - 3.82 Significant st P • 0.012
1. Adjusted Me«n T's
?x - b (Ij - Xtot> - 0.0191 • 0.0441 (0.626 - 0.511)
?2 - * <*2 - *tot> " °'0il* * 0-0441 (0.490 - 0.511)
f3 - b (83 - Jtot) - 0.0127 - 0.0441 (0.271 - 0.511)
?4 - b (*4 - tto,.) - 0.0183 - 0.0441 (0.587 - 0.311)
0.0435
0.0435
O.OS94
0.0429
0.0441
33
47
18
21
119
3
122
3
125
0.0140
0.0187
0.0233
0.0149
0.005719
0.004936
0.001264
0.000923
0.012842
0.000256
0.013098
0.001226
0.014324
0.000108
0.000085
0.000107
0.000409
23
-------
in the distribution of light values sampled could be expected to be reflected
in the characteristics of the regression equations. We therefore suggest that
this analysis of covariance indicates the regression slope to be less sensi-
tive to this non-linearity than the curve heights. Corroboration for this
interpretation may be found in the comparison (and obvious bias) between
directly calculated 0-light Oa fluxes and the Y-intercept values. It is
further evident that covariance comparisons among light versus 02 equations
should first consider different light treatments as a possible explanation
for observed regression differences. This possibility can be unequivocally
dismissed only in the situation of between-treatment intercomparisons under
identically varying light regimes^ some caution with the data should make
recognition of this possibility obvious.
Figure 5 and Table 4 compare the pre-stress control treatment of Figure
4a (Tl) with two similarly treated tanks
-------
TABLE 4. ANALYSIS OF COVAKIAN'CE FOR DATA IN FIGURE 5
Deviations from regression
Line Treatment
1 Tl
2 T7
3 110
4 vithln
5 regression coefficient
6 comnon
7 adjusted means
8 total
Significant difference among
F3,99 " M.S.5/M.S.4 - 0.09
t Ex2
34 6.9322
34 6.9322
34 6.9322
102 20. 7967
104 20. 7967
Ixy
0.3015
0.3002
0.2777
0.8793
0.8793
Iy2 b f
0.01883 0.0435 33
0.01949 0.0432 33
0.01709 0.0402 33
99
3
0.05541 0.0423 102
3
0.05559 105
Edy'x2
0.005719
0.006494
0.005970
0.018183
0.000052
0.018235
0.000180
0.018415
M.S.
0.000184
0.000017
0.000179
0.000060
regression coefficients?
Ho difference
Figure 6 presents another comparison of replicate treatments. Two tanks
(Tl, T2) were allowed to develop fouling communities on the bare tank floor
and walls over 38 days (24 April through 1 June 1973). Three other tanks
(T7, T8, T9) similarly developed over only 22 days. Analyses of covariance
for these data are presented in Table 5. The duplicate 38-day treatments are
cc
x
CO
UJ
_l
o
2
•»
X
cvj
O
-0.02
-0.02
0.04
0.02
o.oo
•0.02
0.0
7302 Tl
0 22-DAY, 2
0« s -0.006+0.0492 • L
r =0.980
-b-o
O 7302 T8
« -0.006* 0.0468 • L
r« 0.907
,
2
o cP
7302 T2
-0.006* 0.0498 • L
r » 0.903
..o.
7302 T9
=-0.004* 0.0348-L
r « 0.798
7302 T7
-0.005 + 0.0408 • L
r s 0,898
0.3 1.0
LANG LEYS PER MINUTE
0.5 1-0
LANGLEYS PER MINUTE
I.S
Figure 6. Solarradiation versus oxygen flux treatments discussed
in text.
25
-------
TABLE 5. ANALYSIS OF COVARIA.VCE FOR DATA IN FICVXE 6
Line
Treatment
Deviations fron regression
f Edyx2 M.S.
A.
1
2
3
4
5
6
7
Coaparlnon of 33-day replicates ' '
n
T2
vithln
regression coefficient
cocoon
»d jus ted Beans
total
38
38
76
77
6.7933
6.7933
13.5867
13.5867
0.3351
0.3373
0.6725
0.6725
o. oi?:oo
0.02056
0.03776
0.03950
0.0492
0.0493
0.0495
37
37
74
1
75
1
76
0.000666
0.003809
0.004475
0.000000
0.004475
0.001740
0.006215
O.OOC060
0.000000
0.000060
0,001740
Significant differences mtr.ong regression coefficients?
Fl,74 ' M.S.4/M.S.3 . 0.00 No difference
B. Comparison of 22-day realleates
1 " 38 6.7933
2 T8 38 6.7933
3 19 38 6.7933
4 vithin
5 regression coefficient
6 common 114 20.3800
7 -adjusted means
8 total 116 20.3800
0.2764
0.3175
0.2372
0.8311
0.8311
0.01394
0.01803
0.01061
0.04258
0.04286
0.0408
0.0468
0.0343
0.0408
37
37
37
111
2
113
2
115
Significant differences aaoeg regression coefficients?
F2,lll " M.S.5/M.S.4 • 3.22 Significant at P - 0.04
C- Intereonpartson between pooled 38-day treatments and pooled 22-day treatments
1 T1+T2
2 T7+T8+I9
3 vithln
4 regression coefficient
5 coonoa
6 adjusted means
7 total
77
116
13.5867
20.3800
193 33.9667
194 33.9667
0.6725
0.8311
1.5036
1.5036
0.03950
0.04286
0.08236
0.08259
0.0495
0.0408
0.0444
76
115
191
1
192
1
193
Significant differences among regression coefficient!?
*1,191 " K.S.4/M.S.ft - 7.84 Significant at P - 0.006
0.002692
0.003191
0.002331
0.008214
0.000475
0.008689
0.000280
0.008969
0.006215
0.008969
0.015184
0.000619
0.015803
0.000230
0.016033
0.000074
0.000238
0.000077
0.000140
0.000079
0.000619
0.000082
0.000230
ee,
£
another even better than Ly track "1 "68 "^ traCk °ne
26
-------
0.06
CM
Ul
-------
Obviously the direct intertank comparisons eliminate metabolic varia-
bility which is not explained statistically by the light versus metabolism
regression. Both the higher correlations and the ability to make comparisons
if (or when) light data are not available make such direct intertank compari-
sons very useful. A disadvantage of these direct comparisons is that data
collected on different days (or otherwise not simultaneously collected) cannot
be compared. Moreover, the statistical basis for interpreting regressions on
data arrays with rigorously defined independent and dependent variables is
more final;, established than is the basis for intercomparison of two dependent
variables (Ricker, 1973). With correlations as high as those shown in Figure
7, this latter point is trivial. However, not all such intercomparisons can
be expected to show this virtually perfect correlation. When the data sets
permit, we generally prefer covariance analysis among data sets for which
regressions of metabolism versus light have been calculated as the analysis
of primary preference, with the direct coinparisons as supplementary analyses.
Let us consider the energetic significance of these light versus metab-
olism analyses. For the communities represented, the regression slopes are
near 0.045 moles 02 m~2 hr"1 langley"1 minute. This slope term can be re-
duced to 7.5X10"5 moles Oa/kcal light. If we assume that one mole of oxygen
production equals (to a first approximation) one mole of organic carbon
production and that one mole of organic carbon has a caloric value of about*
120 kilocalories, then the light to fixed carbon energy conversion efficiency
is about 1 percent. Because of light absorption through the water column and
because the light measurement includes light outside the photosynthetically
active spectrum, this figure underestimates the efficiency with which actually
available light is converted to organic carbon. Odum (1971) cites conversion
efficiencies of 3 to 5 percent for the net production of intensively culti-
vated terrestrial crops and only 0.5 percent as an average favorable condition.
Both the relatively high conversion efficiency and the nearly linear
relationship between available light and productivity suggest that these
fouling communities (and, by extension, other shallow reef benthos communi-
ties) are strongly light-limited. Available data for shallov water reef
communities (summarized by Smith, 1974) usually yield gross production to
respiration ratios near 1.0. Unless the respiration rates of auch communities
drop concommitantly with production, reef communities at moderate water depths
may be heterotrophic. The shift in production with water depth should follow
an exponential decay curve in parallel with the vertical pattern of light
attenuation. It might be postulated that a shift in community composition
with depth could compensate for lower light levels; the high conversion
efficiencies suggest that there is little ecological margin for such a shift.
It is evident that the association between extensive development of
successful coral reef communities and clear waters is more than coincidental.
Gross community production rates near 0.5 moles m"2 day'1 (Smith, 1974) with
solar input of not more than 600 g cal cm~s day"1 (Holmes, 1957) imply aolar
conversion efficiencies similar to the ones we have measured in the micro-
cosms. Waters which are naturally or artificially turbid must significantly
depress organic carbon production of reef benthos.
28
-------
B. Substratum
The composition of reef communities is closely related to the nature of
the substratum inhabited by these communities. Organisms living both within
the interstices of the substratum and on the substratum surface are influenced
by the size of the interstices and by the stability of the substratum. Sub-
stratum irregularity alters the surface area, hence the "surface area index"
(Dahl, 1973). Substratum composition (e.g. grain size) relates to the ambient
environment, and as such is an index of environmental conditions (e.g. water
motion, water clarity) which may directly affect the composition of the biota.
Coral reef environments can be found effectively spanning the range of
possible substratum characteristics, so it is important to quantify reef
response characteristics to substratum composition. Artificial (e.g. dredging)
or natural (e.g. storms) processes may dramatically alter substratum charac-
teristics through either abrupt change or slow transition.
This section considers the oxygen metabolism of shallow benthos communi-
ties in direct response to the nature of the substratum. The experiments
explicitly eliminate secondary variables which may be correlated with sub-
stratum type but which may affect metabolism independently of substratum.
For example, the substrata discussed here (mud, sand, rubble, hard bottom)
may be associated with particular water motion regimes; and water motion may
affect metabolism directly. Mud, especially in shallow water where it is
likely to be re-suspended, is often associated with lowered water clarity or
depressed salinity—either of which might alter metabolism. The tanks
eliminate these secondary effects.
Figure 8 is a series of scatter diagrams of light versus oxygen flux for
three microcosm fouling communities. These communities developed on rubble,
sand, and mud bottoms for 33 days; community metabolism was then measured on
each of eight days over the next 21 days. Figure 8a presents the same data
as the diagram in Figure 4. Several facts emerge. First, linear regressions
provide relatively good fits for the data from all three communities. Second,
despite the good descriptive fit, the true functional relationship is
apparently non-linear. This interpretation can be made with most confidence
for Figure 8a (rubble). Third, the 0-light intercept is overestimated by the
regression lines. Analysis of covariance (Table 6) demonstrates that there
are significant differences among the regression slopes. - Further analyses
demonstrate that the lines for sand and mud (T2, T3)^o not differ from one
another. The pooled slope for those substrata is 0.0276, and the slope for
rubble is 0.0420.
Analysis of covariance allows the comparison of these data with data
collected in another experimental series. The data represented in Figure 6a
and 6b are for fouling community development over 38 days (about the same
time span as the Figure 8 daja) on the walls,and floor of the microcosms.
Because the rubble substratuifl has alretfdy been isolated as significantly
different from sand and mud, and because the hard bottom tanks have apparently
higher metabolism/light coefficients tnan the rubble tank, only the rubble and
hard bottom are compared."
29
-------
M
10
tu
_J
o
CM
O
0.04
0.02
0,00
-0.02
-0.04
0.04
0.02
0.00
-0.02
-0.04
0.04
0.02
0.00
-0.02
RUBBLE
-0.04
7304 Tl
=-0.004 + 0.0420-L
r - 0.862
7304 T2
= -O.O01+0.029I
r = 0.827
L ,
MUD
7304 T3
02=-0.004 + 0.0261 • L
r = 0. 810
0.0
O.S
1.0
1.5
LANGLEYS PER MINUTE
Figure 8. Solar radiacion versus oxygen flux of benthos
communities developed on various substrata.
30
-------
TABLE 6. ANALYSIS OF COV'AKIAKCE FOR DATA IN nCURK 8
Line
Treatment
Ex2
_Deyiatlons_froni regression
f Idy-^2" M.S."
1
2
3
4
S
6
7
8
rubble (Tl)
•and (12)
mud (T3)
within
regression coefficient
cooQion
adjusted Deans
total
126
126
126
378
360
23.4733
23.4733
23.4733
70.4200
70.4200
0.9870
0.6855
0.6118
2.2842
2.2842
0.05S83
0.02928
0.02430
0.10941
0.11328
0.0420
0.0291
0.0261
0.0324
125
125
125
375
2
377
2
379
0.014333
0.009261
0.008356
0.031950
0.003367
0.035317
0.003870
0.039187
0.000085
0.001684
0.000094
0.001935
Significant difference among regression coefficients?
P2.375 ' M.S.j/M.S.4 - 19.81 Significant at 0.001
Table 7 demonstrates that the slope of the hard-bottom metabolism curve
is steeper than the rubble metabolism curve. Because these experiments were
not conducted simultaneously, this comparison must be treated with some
caution. Nevertheless, the two experiments suggest a metabolic progression
with respect to substratum: hard > rubble > sand « mud. The data at hand
suggest that the ratios of metabolic response are 1.8:1.5:1.1. Rubble and
hard bottom are capable of supporting 50 to 80 percent higher metabolic rates
than sand or mud as a direct consequence of substratum type.
—
Line Treataent
1
J
•(
4
1
6
7
rubble
hard
within
regression coefficient
adjusted Beans
Co tat
f
126
77
203
204
Ex2
23.4733
13.3867
37.0600
37.4278
i*jr
0.9870
0.6725
1.6594
1.6714
V
0.05583
0.03950
0.09533
0.09571
Deviations from regression
b
0.0420
0.049$
0.0448
f
125
76
201
• -1
202
1
203
Idy'x2
0.014333
0.006215
0.020548
0.'000477
0.021025
0.000043
0.021068
H.S.
0.000102
0.000477
0.000104
0.000043
Stgoifleant difference between regression coefficients?
*1.301 " M.S.4/K.S.3 - 4.68 Significant «t 0.03
The Intercomparison of metabolic rates can be effected more directly
for the mud, sand, and rubble substrata. Figure 9 presents scatter diagrams
of rubble versus sand and rubble versus mud plots and the functional or
geometric mean regression coefficients (after Ricker, 1973). If those slopes
are used to establish the rubble:sand:mud metabolic ratios, the results are
1.5:1.1:1—virtually identical with the covariance approach.
The explanation for enhanced metabolism on rubble or hard-bottom sub-
strate is not entirely clear. Experimental design rules out water motion or
31
-------
'oc °'04
M
*2
to — 0.02
UJ O
0<
CM
O
<3
CM
H
0.00
-0.02
0.04
V
to- 0.02
Ul O
02
M
O
10
0.00
-0.02
7304
T2 = 0.001 + 0.724 Tl
r = 0.983
1 1 1 1 1 1 1 h
o 7304
T3 = -0.002 + 0.6 60
r =0.927
' ' •*••
* * - ••- *
-0.02 0,00 0.02 0.04 0.06
, MOLES M~2HR"~'
(RUBBLEV
Figure 9. Direct comparison of oxygen flux on rubble
versus sand and mud suoscrata.
32
-------
water clarity. Physical stability may be a partial answer, inasmuch as bio-
turbation of sand and mud could disrupt the algal communities on those sub-
strata. Increased surface area for algal growth could explain the difference
between the rubble and the sand-mud comparison; this explanation is not
consistent with the low-surface area hard bottom being the most active sub-
stratum. There may be an effect associated with reflectivity of the surfaces,
since light does appear to be a limiting resource. Bacterial respiration in
the sediments is yet another possible explanation. Without having an
entirely satisfactory explanation for this phenomenon; we report the existence
of a direct link between type of substratum and metabolic activity in these
shallow tropical benthos microcosms.
C. Nutrients
Coral reefs are ordinarily considered to be products of low-nutrient
conditions, and to cycle available nutrients effectively. Kaneohe Bay, Hawaii
(the site of our microcosm facility), is subjected to high levels of nutrient
loading, primarily from sewage discharge. We therefore wished to determine
whether reef communities in Kaneohe Bay were still limited by available
nutrients or were nutrient-saturated.
Fouling communities were allowed to develop in each of three tanks. The
experimental communities also included three grazing herbivorous fishes
(.Aoanthucus trioetegus) in each tank. After the fouling communities were
inoculated with unfiltered water from the bay, bay water flow to one tank was
cut by 30 percent (i.e. by 3 liters min'1). Total flow was brought back to
10 liters min"1 by the addition of water from a saltwater well. Salinity of
that well water is virtually identical to salinity of bay water (" 35 °/oo),
but nutrient levels of the well water are substantially higher than bay water
(Table 8). Thus, there were two replicate bay water communities compared with
one community enriched with well water.
TABLE 8 COMPARISON OF TYPICAL DISSOLVED INORGANIC NUTRIENT LEVELS IN BAY
WATER DRAWN THROUGH MICROCOSM FACILITY WITH SEAWATER WELL
PC*
NO:
NHL
Total inorganic N
ymoles/liter
Bay water
Well water
30% well + 70% bay
Well/bay ratio
0.5
1.2
0.7
2.4
0.6
5.0
1.9
8.3
1.6
5.0
2.6
3.1
2.2
10.0
4.5
4.5
(70% bay +302 well)/
bay ratio
1.4
3.2
1.6
2.1
33
-------
Figure 10 illustrates metabolic rate as a function of light in the three
tanks. The analysis of covariance is presented in Table 9. It is evident
that the 30 percent bay water addition boosted community metabolic response
to light by about 43 percent and that the two replicate treatments receiving
X
CM
1
CO
111
-J
O
2.
X*
1
_J
U.
o
0.06
O.O4
0.02
0.00
-0.02
0.06
0.04
0.02
0.00
-0.02
0.06
0.04
0.02
0.00
-0.02
0
,— 1 ; '
A r = 0.846
-------
TABLE 9. ANALYSIS OF COVARI/NCE FOR DATA IN FIGURE 10
Deviations from regression
Line
Treatment
Ex*
Zxy
Idyx*
M.S.
1
2
3
4
5
6
7
8
bay water 1
bay + well
bay water 2
within
regression coefficient
common
adjusted means
total
68
68
68
204
206
7.8533
7.8533
7.8533
23. 5600
23.5600
0.2638
0.3670
0.2490
0.8798
0.8798
0.01237
0.02359
0.01234
0.04830
0.04971
0.0336
0.0467
0.0317
0.0374
67
67
67
201
2
203
2
205
0.003509
0.006439
0.004447
0.014395
0.001051
0.015446
0.001410
0.016856
0.000072
0.000525
0.000076
0.000705
Significant difference among regre«»lon coefficients?
F2,201 ' M.S.5/M.S.4 " 7.29 Significant at 0.001
bay water tracked one another well. Figure 11 is a plot of 02 metabolism in
the bay + well tank versus 02 in the two bay tanks. This direct fit yields i
well/bay regression slope of 1.36—very close to the value of 1.43 inferred
from the covariance analysis. The metabolic enhancement by well water is
close to the proportional increase in phosphorus loading (Table 8).
0.04
X
CM
3
o
O
<3
0.02
0.00
-0.02
T5 •
Til o
7305
T7= 0.003+ 1.35715,1
r =0.980
-0.02
0.00
0.02
0.04
T5.ll A02, MOLES M"2HR"'
(BAY)
Figure 11. Direct comparison of "low nutrient" (bay
water) versus "high nutrient" (bay4well
water) treatments.
35
-------
There are several conclusions to be drawn from these analyses. The
microcosm benthos—and by Inference the shallow benthos of Kaneohe Bay—
increase their metabolic rate when nutrient levels are raised. Therefore,
increased nutrient loading in the bay would result in higher benthos produc-
tion. Conversely, lowering the nutrient loading should decrease production.
Moreover, the microcosms prove from these preliminary observations to be a
useful tool for examination of the effects of nutrient loading. At this
writing, this set of conclusions has been coupled with the fact that a major
nutrient input to Kaneohe Bay is being removed (diversion of sewage), to
expand this observation into a more detailed analysis of the effects of
nutrient loading on reef communities. Included in that analysis is an assess-
ment both of the generalized effects and a more specific analysis of the
individual roles of nitrogen and phosphorus.
D. Salinity
Reef ecosystems are ordinarily restricted to areas of near-oceanic salin-
ity (* 35 °/oo), although there are reefs which experience moderate departures
from this value. Freshwater "kills" from rains and runoff have been reported.
Reef communities are frequently suppressed in the vicinity of streams. The
tolerance of reef communities for salinities between 0 °/oo and. 35 °/oo has
not been well defined. We therefore conducted an experiment with two primary
purposes. Approximately what salinity depression begins to kill conspicuous
parts of the reef community? Does a measurable metabolic response occur at
salinities intermediate between 35 °/oo and this lethal threshold?
Fouling communities were allowed to develop on rubble, sand, and mud
substrata in the microcosms. The results within the substratum types were
qualitatively similar, but between-salinity differences were most conspicuous
on the rubble substratum. Only the results from the rubble experiments are
reported here. Organisms listed in Table 10 were added to the fouling
TABLE 10. ORGANISMS INTRODUCED INTO FOULING COMMUNITIES
FOR SALINITY STRESS EXPERIMENTS
ALGAE CRUSTACEANS
Aoanthapora spieifera Chiridota Twwaiiena-Ls
ECHINODERMS FISHES
Opheodesoma speotabatis Acanthums triost&gus
Holothiwia monocaria
CQELENTERATES
Zoanthus paeificus
Poeillopova damicornis
Pori-tes eompresea
36
-------
communities. These organisms are all typical of the fringing reef communities
of Kaneohe Bay. It was determined that the organisms added were themselves
insufficient to alter the microcosm community metabolism significantly.
Hence, observed metabolic responses—if any—would be that of the fouling
communities. These large organisms were simply added as indicators of stress.
Table 11 reports the chronology of salinity alteration. The initial
salinity reductions (to 29 and 25 °/oo) imposed no measurable metabolic
response or lethal effect on the microcosms, so the stresses were relaxed and
then applied more severely (to 22 and 16 °/oo). The experiment was performed
as described, with the assumption that the initial salinity reductions had no
effect. This experiment should be repeated in a manner which precludes the
need for such an assumption.
TABLE 11. CHRONOLOGY OF SALINITY STRESS EXPERIMENTS
Date (day of year) Day of Event
Experiment
11 June 1973 (162) 0 Start experiment
14 July 1973 (195) 33 Retain tanks 1,2,3 as controls
Lower tanks 7,8,9 to 25 °/oo
Lower tanks 10,11,12 to 29 °/oo
19 July 1973 (200) 38 Return all tanks to 35 °/oo
24 July 1973 (205) 43 Retain tanks 1,2,3 as controls
Lower tanks 7,8,9 to 22 °/oo
Lower tanks 10,11,12 to 16 °/oo
25 July 1973 (206) 44 Return all tanks to 35 °/oo
17 August 1973 (229) 67 Terminate experiment
Only the lowest salinity (16 °/oo) killed a substantial fraction of the
reef organisms. All organisms listed in Table 10 as well as some of the
infauna which had entered the microcosms as fouling organisms were affected
during the 24-hour exposure. The coelenterates and echinoderms were all
killed by the lowest salinity; the other animals recovered once the salin-
ity was returned to normal. Algal survival could not be assessed by visual
inspection, so is not reported here. Figure 12 and Table 12 show the results
of the metabolic measurements. Over the entire salinity range employed, there
was no significant variation in metabolic response.
37
-------
M
CO
UJ
O
2
m
X
_l
U.
CM
O
0.04
0.02
0.00
-0.02
0.04
0.02
0.00
-0.02
0.04
O.02
0.00
0 7304 Tl
A02 = -0.004 + 0.042O • L
r = 0.862
29%
73O4 TIO
= -O.OO5* 0.0387 L
r = 0.850
-0.02
7304 T7
(.003 + 0.0
r = O.87I
A02 = -0.003 + 0.0429- L
7304 T7
A02 = -0.004 + 0.0561 - L
r = 0.812
I 1
7304 TIO
= -0.004+0.0399-L
r = 0.758
O.S IJO
LANGLEYS PER MINUTE
1.5
0.0 0.5 1.0 I.!
LANGLEYS PER MINUTE
Figure 12. Solar radiation versus oxygen flux under various
salinity regimes.
There are two primary conclusions to be drawn from this surprising re-
sult. Although salinities below 22 °/oo (i.e. below 63 percent of ambient
salinity) did prove detrimental to the conspicuous reef organisms that were
added to the microcosms, these organisms were minor in the total metabolic
activity of the reef community. If we assume that the effects of lowered
salinity were ecologically significant—despite their relatively minor
"energetic" importance—then we conclude that there was not a community
metabolic harbinger to damage from salinity depression. Although it has been
demonstrated that community metabolism is'responsive .to other perturbations,
metabolism of reef benthos communities is not sensitive to sublethal varia-
tions in salinity.
38
-------
TABLE 12. AKAI.YSIS OF COVA&IAXCE FOR MTA Iff FIGURE 12
Line
Treatment
1*2
Zxy
Deviations from regression
f Edyx2 M.S.
1
2
3
4
s
6
7
a
9
10
35 °/oo
29 °/oo
25 °/oo
22 °/oo
16 °/oo
within
t«gre*6ion coefficient
comnon
adjusted means
total
126
48
48
19
19
260
264
23.4711
8.2333
6.2333
1.0356
1.0356
42.0089
43.8400
0.9669
0.3175
0.3521
0.0582
0.0413
1.7561
1.8197'
0.05583
0.01696
0.01984
0.00497
0.00287
0.10047
0.10316
0.0420
0.0387
0.0429
0.0561
0.0399
0.041*
125
47
47
18
18
255
4
259
4
263
0.014332
0.004715
0.004781
0.0001695
0.001223
0.026746
0.000314
0.027060
0.000566
0.027626
0.00010
0.00007!
0.00010'
o.ooou:
Significant differences among regieisiou coefficients?
F«,255 - M.S.7/M.S.6 - 0.7S No difference
E. Biological Manipulation
The analyses presented so far have taken little note of the biological
composition of the microcosm communities. The communities have been considered
only as fouling communities, with reference to some specific community
alterations common to all treatments. Such a presentation has been deliberate.
The philosophy of the analyses and of the presentation has been that com-
munity metabolism is a) easy to measure, b) sensitive to variation in (some)
external forcing functions, and c) relatively insensitive to uncontrolled
variations in community structure associated with random recruitment.
The previous sections have established the validity of these points. Is
community metabolism sensitive to direct, deliberate manipulation of biologi-
cal composition? This question is the subject of the present section.
Three tanks were set up with a sand substratum and allowed to develop a
significantly different feeding strategies,
respiration of the fishes themselves was a negligible contribution to the
total microcosm community metabolism.
Figure 13 is a plot of oxygen metabolism versus
treatments, and Table 13 is the covariance analysis.
a
is
to fish
given compar ab !*
latlon affects metabolism.
^^
39
-------
I
cc
I
CM
I
(O
UJ
U-
CM
O
0.06
-0.02
0.06
0.04
-0.02
0.06
0.04
0.02
0,00
-0.02
-------
TARLF 11 AVH.YSIS Or COVASIA^CE FOR DATA IS FIGURE 13
Treetatnt
1*2
Depletion* frota Regression
"7" Idyx*M.S.
1
0 fifth, **nd
3 Aaantrsu'ua, end
3 Soarus, «»nd
within
zecretdon coefficient
COSQOB
adjusted Bean*
total
68
68
68
204
206
T.8S33
7.8533
7.8333
23.5600
23.5600
0.3314
0.2230
0.1757
0.7301
0.7301
0.01858
0.00908
0.00610
0.03376
0.3519
0.04230
0.0285
0.0225
0.0310
67
67
67
-201
2
203
2
205
0.004593
0.002750
0.002169
0.009512
0.00162!
0.011135
0.001430
0.01256S
0.000047
0.000811
0.000055
0.000715
0.3987
0.3987
Bepeet llaec 4-8 for Aaant'airus v. Saearut
4' within
5' regret*ion coefficient
«' coran 136 15.7067
7' «djv«t«d mean*
«' t«Ml 137 15.7067
Signlflciut difference* u»ng regression coefficient*?
'2,201 • K.S.j/H.8.4 - 17.26 Significant *t P « 0.001
Bapeit. tilting 4oenthun«« v. Soarut
t P - 0.05
0.01518
0.01527
0..025S
134
1
135
1
136
0.004919
0.000142
0.005061
0.000090
0.005151
0.000037
0.000142
0.000037
0.000090
The next comparison involves a complex reef rubble community (trans-
planted from the reef flat nearly in toto and then allowed to stabilize), a
sterile rubble community to which two species of grazing echinoids (5 speci-
mens each of adult Tripneustes gratilla and Echvnom&tiea matfaei) were added,
and the duplicate rrt>bl&/Acanthia>u8 communities previously considered.
Analysis of covariance (Table 15) demonstrates no significant difference
among the regression slopes. The variety of choices of grazers, from fishes
to large invertebrates to cryptic invertebrates, has imposed similar effects
on community metabolic response to light. Apparently community metabolism
is sensitive to grazing pressure but not to the quality of grazing. Either
by chance or adaptive response, the communities have shown very al>U«
responses despite our approach to adding the herbivore level in a trophic
pyramid.
TABLE ™. AMtLTSIS OF OOVMtlAKCE. KO FISH VERSUS FISH. KTOBLj
Deviations from regression
Line
Treatment
1 0 fish, rubble 137
2 3 Aoar.thurua, rubble 137
3 within
4 tegrenion coefficient
J coinoa 274.
6 *dju«ted «ean«
7 total 275
15.7067
15.7067
31.4133
»
-------
There does appear to be a substantially lower net production in the reef
rubble community than in the two simpler communities (Table 15b). The three
communities respond similarly to varying light, so we assume that the lower
net production represents a higher community respiration rate.
TABLE 15. ANALYSIS OF COVARIAKCE. REEF RUBBLE V. ECHIKOIPS V. FISH .
Deviations from regression
Line Treatment
A.
1
2
3
4
5
6
7
8
Analysis of Covatiance
reef rubble
sterile rubble 4- echinoid
sterile rubble + fish
within
regression coefficient
coumon
adjusted means
total
f
68
68
137
273
275
£X2
7.8533
7.8533
15.7056
31.4122
31.4122
Ixy
0.3054
0.2542
0.5128
1.0724
1.0724
ryz
0.01599
0.01243
0.02477
0.05319
0.05389
b
0.4390
0.0324
0.0327
0.0342
f
67
67
136
270
2
272
2
274
Zdyx*
0.004111
0.004200
0.008029
0.016340
0.000236
0.016576
0.000700
0.017276
M.S.
0.000061
0.000118
0.000061
0.000350
Significant differences among regression coefficients?
*2,270 " M.S.5/M.S-4 - 1.94 Ho difference at P - 0.10
B. Adjusted aean T*« 1 95Z confidence interval
Yj - 0.0024 1 0.0019
?2 - 0.0069 * 0.0019
23 - 0.0052 ± 0.0013
One might anticipate, a priori, that the effects of grazing pressure on
reef metabolism would have been different from those that we observed. In
some situations, cropping seems to accelerate growth; that proves not to be
true for reef community metabolism, although it might be the case for the
metabolic rate normalized per unit biomass rather than per unit area. This
latter normalization is difficult (in fact, apparently impossible without at
least partial destruction of the community).
We conclude that community metabolism is indeed sensitive to biological
manipulations within the microcosms. We suggest that there may be relatively
broad limits of herbivore food uptake requirements over which the community
metabolism adjusts to a constant rate. A sufficiently low herbivore food
demand apparently does allow the community metabolism to Increase, and an
excessive herbivore food demand will result in eventual starvation. Although
not explicitly examined by these analyses, we would anticipate analogous
patterns among carnivores and detritivores.
F. Conclusions
In the preceding sections we have examined the metabolic responses of
shallow tropical benthos communities to five forcing functions: light, sub-
stratum, nutrient loading, salinity, and direct manipulation of the biological
community. The first three forcing functions may be treated conceptually as
limiting resources, with light being a primary limitation which has not been
controlled in these experiments. Salinity depression was Investigated as a
42
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direct stress imposed upon the community. Manipulation of community structure
and, inferentially, metabolic similarities in apparently replicate treatments
provide insight into the ability to extrapolate from the metabolic character-
istics of such simplified simulations of nature to reefs under natural
conditions.
The manipulations and replications demonstrate that the communities are
sensitive to biological alterations but that the sensitivity is only between
distinctly different communities. Treated similarly, the communities converge
towards similar metabolic rates. Moreover, complexity of the manipulated
communities does not appear to be a major factor in the metabolic response
characteristics. On this basis, we may extrapolate from the microcosms to the
real world.
Limiting resources in the microcosms are strongly reflected in their
metabolic responses. Light, substratum characteristics, and nutrient loading
all impose substantial and quantifiable metabolic responses on the microcosm
communities. We conclude that any alteration of these variables will impose
effects on reef communities. It is likely that, as low-level chronic pertur-
bations, these variables are altered more frequently in tropical nearshore
ecosystems than other variables. The data presented here only begin to
reduce our ignorance about metabolic responses to these variables; far more
work is needed to quantify these responses adequately. Information on light
response is of primary importance and accumulates most rapidly in an experi-
mental facility such as we describe, because all experiments so-conducted
will contain light as an "uncontrolled" independent variable. By such
treatment in outdoor microcosms, we are able to achieve natural levels of
intensity and natural photoperiod. We are continuing to define reef benthos
community responses to nutrient loading. Metabolic responses to substratum
alteration remain inadequately described.
The remaining variable which we have examined is salinity. This vari-
able is also frequently altered in nearshore environments. Reef communities
have an unexpected resilience to salinity depressions. Neither structural
nor metabolic responses to depressed salinity occurred in the microcosms
untifsalinity was reduced below 22 %>o. Thus, the deleterious effects to
Telfs associated with lowered salinity may be attributed to extreme salinity
depression (probably largely in the form of freshwater lenses floating on the
seawaSr) or to materials introduced with the fresh water (sediment, nutri-
enta? toxins). Salinity depression does not appear to be a m*jor chronic
sublethal stress on reef communities.
43
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Confer, J. L. 1972. Interrelations among plankton, attached algae, and the
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Cooke, G. D. 1967. The pattern of autotrophic succession in laboratory
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Dahl, A. L. 1973. Surface area in ecological analysis: quantification of
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Hall, D. J., W. E. Cooper, and E. E. Werner. 1971. An experimental approach
to the dynamics and'structure of freshwater animal communities. Limnol.
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Henderson, R. S., S. V. Smith, and E. C. Evans III. 1976. Flow-through
microcosms for simulation of marine ecosystems: development and inter-
comparison of open coast and bay facilities. Technical Report NUC
TP519. Naval Undersea Center, San Diego, California. 80 pp.
Holmes, R. W. 1957. Solar radiation, submarine daylight, and photosynthesis,
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Washington, D. C.
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Jokiel, P. L. 1978. Effects of water motion on reef corals. Jour. Exp.
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Jokiel, P. L,, S. L. Coles, E. B. Guinther, G. S. Key, S. V. Smith, and
S. J. Townsley. (manuscript) Effects of thermal loading on Hawaiian
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D. K. Phelps, National Marine Water Quality Laboratory, Narragansett,
Rhode Island, November 1974, 285 pp.
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Kanwisher, J. 1963. On the exchange of gases between the atmosphere and the
sea. Deep-sea Res., 10:195-207.
Kinsey, D. W. 1973. Small-scale experiments to determine the effects of
crude oil films on gas exchange over the coral back-reef at Heron Island.
Environ. Pollut., 4:167-182.
Kinsey, D. W., and A. Domm. 1974. Effects of fertilization on a coral reef
environment - primary production studies. Proc. 2nd Internat. Coral
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Mullin, M. M., and P. M. Evans. 1974. The use of a deep tank in plankton
ecology. II: Efficiency of a planktonic food chain. Limnol.
Oceanogr. 19:902-911.
Nixon, S. 1969. A synthetic microcosm. Limnol. Oceanogr. 14:142-145.
Northby, J. A. 1976. A comment on rate measurements in open systems.
Limnol. Oceanogr. 21:180-182.
Odum, E. P. 1962. Relationships between structure and function in the
ecosystem. Jap. Jour, of Ecol., 12:108-118.
Odum, E. P. 1971. Fundamentals of ecology, 3rd ed., W. B. Saunders Company,
Philadelphia, Pa. 574 pp.
Qasim, S. Z., and V. N. Sankaranarayanan. 1970. Production of particulate
matter by the reef on Kavaratti Atoll (Laccadives). Limnol. Oceanogr.
15:574-578.
Ricker, W. E. 1973. Linear regressions in fishery research. Jour. Fish.
Res. Bd. of Canada, 30:409-434.
Ryther, J. H. 1956. The measurement of primary production. Limnol.
Oceanogr. l(2):72-84.
Ryther, J. H., W. M. Dunstan, K. P. Tenore, and J. E. Hugunin. 1972.
Controlled eutrophication increasing food production from the sea by
recycling human wastes. BioScience, 22:144-151.
Smith, S. V. 1974. Coral reef carbon dioxide flux. Proc. 2nd Internat.
Coral Reef Symp. 1:77-85.
Smith, S. V., and G. S. Key. 1975. Carbon dioxide and metabolism in marine
environments. Limnol. Oceanogr. 20:493-495.
Smith, S. V., and D. W. Kinsey. 1978. , .Calcification and organic carbon
metabolism as indicated by carbon ^dioxide. In: Coral Reefs: Research
Methods, ed. by D. R>Stoddart arfd R. E. Johannes. UNESCO, Paris.
581 pp.
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Smith, S. V., and F. Pesret. 1974. Processes of carbon dioxide flux in the
Fanning Island lagoon. Pac. Sci., 28:225-245.
Smith, S. V., and J. A. Marsh, Jr. 1973. Organic carbon production on the
windward reef flat of Eniwetok Atoll. Limnol. Oceanogr. 18:953-961.
Smith, S. V., and P. L. Jokiel. 1976. Water composition and biogeochemical
gradients in the Canton Atoll lagoon. In: An Environmental Survey of
Canton Atoll Lagoon 1973, ed. by S. V. Smith and R. S. Henderson, Naval
Undersea Center Technical Report NUC TP 395, San Diego, Calif., pp. 5-14.
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Taub, F. B. 1969. A biological model of a freshwater community: a
gnotobiotic ecosystem. Limnol. Oceanogr. 14:136-142.
46
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APPENDIX
DESIGN, CONSTRUCTION, AND OPERATION
OF SHALLOW TROPICAL BENTHOS MICROCOSM FACILITIES
A. General
Two microcosm facilities were developed during the course of this pro-
gram. These facilities are outdoor constructions designed to simulate
environmental characteristics typical of shallow tropical benthic settings.
The prototype (Figure 1) is at the Hawaii Institute of Marine Biology (HIMB)
and draws water from protected, organic-rich Kaneohe Bay, Hawaii. This
facility evolved gradually. All experiments described in this report were
performed at the HIMB facility. The Naval Undersea Center (NUC, now the
Naval Ocean Systems Center) used the HIMB experiences to design and establish
an analogous facility on the clean-water open coast of nearby Ulupau Head.
Experiments began there near the termination of the contract period covered
by this report.
Despite the proximity of the two locations to one another (Figure A-l)
and the similarity of "operating philosophy" at the two facilities, site-
specific physical, chemical, and biological considerations provide useful
insight into the design and operation of such microcosm facilities.
Henderson et al. (1976) describe the NUC facility in some detail and provide
results from preliminary inter-calibration experiments.. This appendix
presents design, construction, and operating considerations consistent with
the two localities. Inasmuch as design detail must inevitably be site-
specific and "state-of-the-art" specific, plans and layout are not presented
in any detail here.
The primary operating constraint at HIMB is associated with biological
fouling. Large numbers of marine organisms settle throughout the seawater
system and capitalize on abundant particulate organic food to grow rapidly,
clog pipes,.and restrict water flow. The system was designed and constructed
to minimize this problem in a manner which in no way impinges upon biological
activity within the microcosms themselves. At NUC, the primary operational
hurdle was associated with inexpensively securing a seawater system which
could reliably draw ocean water from beyond a surf zone where breaking winter
waves commonly exceed 3 meters in height for days to weeks at a time.
We describe the microcosm components according to the following
divisions:
47
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Kaneohe Bay
B.
Figure A-l. Map showing locations of HIHB and NUC microcosm facilities.
a. seawater supply and distribution system;
b. microcosm aquaria and associated devices for environmental
modification;
c. automatic sampling and data acquisition system.
Seawater Supply and Distribution System
The microcosms must be supplied with an uninterrupted flow of seawater.
The water should be free of uncontrolled contaminants (e.g. fresh water or
sediment from storm runoff). Delivery of water should exceed total antici-
pated flow through the microcosms by at least 50 percent, so that there is
an adequate supply for overflow from constant head tanks, for holding tanks,
and so forth. An adequate system should meet the following criteria:
1. Inertness of material—-All surfaces coming in contact with water to
be delivered to the system must be made of non-toxic plastic, fiberglass, or
titanium. All wetted surfaces should be conditioned with running seawater
48
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for several weeks to leach out any residual solvents or other possible toxins
before experimental organisms are added. Folyvinyl chloride (PVC) pipes,
valves, and other fittings are acceptable, and PVC is particularly easy to
use and modify. A single toxic (e.g. copper) fitting among many square
meters of otherwise inert materials may prevent the survival of delicate
organisms (e.g. corals).
2. Reliability—Microcosm experiments may run for months and are
vulnerable to interruptions in seawater delivery. The entire delivery
system should be constructed in duplicate (see below, on cleaning) so that
there is adequate system redundancy in the event of system failure. The
primary pump for the facility is likely to be electrical; there should be an
auxiliary generator or a gasoline-driven pump in the event of power failure.
The auxiliary system should be periodically tested according to a routine
maintenance schedule. There should be an alarm system which operates inde-
pendently of the electrical system and which is tripped by any interruption
in water flow. The alarm itself should also be checked regularly.
3. Cleaning—The distribution system should be designed for ease of
cleaning. If the entire system (including pumps) is installed in duplicate,
then one system can be shut down for cleaning while the other system is
operational. Periodic cleaning minimizes the problem of fouling. Water
allowed to stagnate in the closed system will kill newly-settled larvae. This
system is then backflushed, to avoid discharge of anoxic water, sulfides, and
organic materials into the microcosms. To the extent possible, straight
delivery lines should be used instead of ones with many bends, (the straight
lines also improve flow characteristics). Open bends should be used rather
than tight elbows. Each straight section of pipe should be directly acces-
sible via cleaning ports.
4. Flexibility—In order to accommodate modifications towards differing
experimental purposes, facility design should be flexible. Light fiberglass
tanks and plastic plumbing are particularly amenable to modification. Suf-
ficient open working area, seawater delivery, drain systems, fresh water, and
electrical power should be provided so that facilities can be expanded and
modified. In the HIMB system, groups of three microcosms are served by a
single inlet headbox. The NUC system allows single or multiple microcosm
service by each inlet headbox. The latter arrangement is preferable.
5. Environmental modifications—Water composition can be varied by -
choice of water source (fresh water, bay water, well water), by manipulation
before the water enters the head boxes, by modification in the head boxes (or
inlet lines),land by direct manipulation within the tanks. Natural, uncon-
trolled variations in water quality should^-be minimized by choice of water
intake sites. Care should be ?fcaken to se%that the microcosms are not shaded
by buildings or other obstructions at anytime.
6. Plumbing characteristics—Pipe^diameters to serve the microcosm
system can be calculated from an estimate of. the maximum height to which the
water must be delivered,'the ,total length of.pipe in the distribution system,
the flow rates to be maintained, and the pump characteristics. Engineering
handbooks or plumbing experts should be consulted for detail, with some
49
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allowance made for fouling. Our facility delivers approximately 400 liters/
minute, to a maximum delivery height of 5 meters (an aeration tower). The
water flows through approximately 10 meters of pipe before it is delivered to
the microcosms. Minimum pipe diameters in the delivery system are 1-1/4
inches. Valves are not used to regulate water flow. Instead, standpipes
maintain constant water levels and allow excess water to spill into drains.
Flow rates are controlled by head differences between constant-head reser-
voirs and overflow pipes.
Major considerations about the pump are: 1) that it be- capable of
delivering the required flow to the maximum elevation in the system; 2) that
it be reliable under conditions of constant operation; 3) and that all wetted
surfaces be made of non-toxic materials. It is desirable to have two primary
pumps (in addition to the auxiliary). One pump can be in operation while the
other is down for routine maintenance or repair.
We have used centrifugal pumps. Most small planktonic organisms en-
trained in the flow survive passage through the pump, although recent studies
suggest that larger and more delicate holoplankton and meroplankton are
killed.
7. Water characteristics—The water used for most experiments at HIMB
is drawn from a depth of 2 meters adjacent to a reef slope in Kaneohe Bay.
The water is rich in plankton and organic detritus, so a fouling community
develops rapidly. This biological fouling necessitates the double seawater
distribution system which has been described. Inlet screens must be ex- ;
changed and cleaned fortnightly. A second water source at HIMB is a seawater
well. The salinity of that water is very similar to bay salinity. There are
other substantial chemical and biological differences between the two water
sources. Larvae and organic detritus are effectively filtered from the well
water. The only organisms associated with the well water are diatoms which
appear to be introduced as airborne contaminents. The inorganic-nutrient
level of the well water is substantially higher than that of the bay (Table ••
8). The well water is anoxic and rich in hydrogen sulfide. It is aerated by
being flowed as a "film" across rippled plastic roofing material before being
delivered to the microcosms. That treatment is sufficient to remove the H2S
and bring the 02 concentration to saturation.
At the NUC facility, water is drawn from a natural sump at the seaward
edge of the reef flat. This sump, protected from the force of the ocean waves
by the algal ridge, allows-us to draw water from beyond the reef crest. In
certain weather conditions, water draining off the reef flat flows into the
sump and delivers nitrogen-rich water to the microcosm (see Henderson et at.,
1976). On rare days during low spring tides when there is no surf action,
the water in the sump is drawn down below the intake level so that the
pumping ceases. A standpipe arrangement prevents the microcosms from drain-
ing, and the pump is re-started manually. The double pipe across the reef
flat to the sump was emplaced during a quiet-water spring low tide and then
secured with cloth bags which were filled, in place, with concrete and
further anchored with reenforcing rods. This emplacement has now survived
two seasons^of winter surf. At the NUC facility a large amount of sand is
50
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suspended in the surf zone and pumped into the facility. This problem is
alleviated by delivering the water to a 2,500-liter settling tank which
allows the sand to settle out. That sand is then cleaned out as needed.
C. Microcosm Aquaria. Associated Devices for Environmental Modification of
Aquarium Characteristics ,
The microcosm tanks used in our facilities are constructed of 3/8"
thick sprayed fiberglass. The inner dimensions are 117 cm by 117 cm by 46 cm
deep. The total volume is 630 liters. A horizontal flange approximately 5 cm
wide lends rigidity to the tanks. Tank dimensions should be kept constant
for inter-tank comparisons. There are demonstrable microcosm community
responses associated with surface to volume ratios and other "container
effects." The water depth in the tanks is usually kept near 35 to 40 cm
(480-550 liters). Water depth in the tanks and flow rate through the tanks
are established by means of inlet and outlet head boxes. The water depth in
the head boxes is fixed by means of adjustable standpipes (Figure A-2).
Coarse control on the flow rate is controlled by the length of the standpipe.
Screwing the standpipes up or down on threaded fittings provides fine control
of flow. Such gravity control of flow rate is preferable to valves, which
rapidly become fouled or clogged. With weekly cleaning of distribution lines,
flow rates can be maintained to well within 5 percent of the desired rate by
this system. The double standpipe arrangement also prevents the microcosms
from draining in the event that seawater delivery stops. Flow rate through
each microcosm is usually maintained near 10 liters/minute, so the flushing
time of each aquarium is about 50 minutes. The drain on each outlet head box
has a simple, automatic (inverted-U) siphon so that the head box fills, starts
the siphon, drains, stops the siphon, and then repeats the cycle. Flow
through the tanks is precisely measurable by timing the filling rate of the
head boxes. Such a measurement system could be automated by installing
electrodes which registered the time at two known points (hence, volumes) on
the filling cycle. We have not found a preferable inexpensive flow meter
which neither interferes with flow nor remains unaffected by fouling in the
pipes. .-.,-,
Water flows into the aquaria via a pipe (actually, one of two; one for
each of the duplicate distribution systems) near the center of the aquaria.
The water wells up, mixes through the tank, and exits through another (again,
one of two) pipe near one corner of the tank. An earlier configuration of
the inlet induced a horizontal rotary flow from a point inlet on one side of
each tank. This resulted in a conspicuous gradient in the fouling community
around the tank sides. Such a gradient induced by variable water motion
precluded convenient sampling of an homogenous community; the gradient has
been eliminated by the present design.
Water composition can be varied by initial choice of water source (fresh
water, bay water, well water), by manipulation before the water enters the
inlet head boxes, by mixing in the head boxes or the inlet lines, or by direct
additions to the tanks themselves. Descriptions of how we alter water
composition follow.
51
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AMBIENT (GRAVITY
Ft£0) INLET LINE
TEMPERATURE MIX
INLET LINE -
RESERVOIR WAIN
(SETS LEVEL IN
RESERVOIR)
INLET RESERVOIR
BOX
MANOMETER FORT-
UNES TO TANKS
W-COMWa
WATER SAMPLE
PEOCOCK
SECONDARY FEED LINE
(B)
DRAIN BOX
/"INDIVIDUAL CHAMBERS
FOR EACH TANK)
OUTLET STANOPIPE
(SETS LEVEL IM TANK}
OUT-COIHO WATER
SAMPLE PEOCOCK
Figure A-2. Arrangement of standplpes in inlet (A) and outlet (B)
head boxes.
52
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Salinity is decreased by adding fresh water to the head box at a fixed
rate. The fresh water is delivered by gravity feed from a large constant-
head reservoir, rather than being supplied directly from the freshwater line
which is subject to variable pressure and flow rate.
Dissolved inorganic materials (nutrients, toxins, etc.), are added to
the inlet boxes or inlet lines by means of a peristaltic pump drawing from a
stock solution in distilled water. By using a stock solution which is highly
concentrated relative to the desired dissolved material concentration in the
microcosm (e.g. 1,000-fold), one can avoid lowering the microcosm salinity
with the additions. Cations can often be added as chloride compounds, while
anions are often best added as sodium compounds. Because chloride and sodium
are the two most abundant ions in seawater, use of such compounds minimizes
the effects of added materials other than those of specific interest. Of
course, salts of sodium or chloride are not always available or practical.
Consideration of available salts and seawater chemistry can suggest the most,
viable choices. For nutrient additions under less precisely controlled
conditions, we have also used high-nutrient water from a seawater well (see
Table 8).
Temperature is controlled by heating or chilling the inlet stream with a
heat exchanger system (Jokiel et al.t manuscript) or by placing glass resist-
ance heaters in the head boxes* The former approach allows efficient and
sophisticated control but involves extensive construction; the latter is
simple to operate, but energy-intensive.
Dissolved oxygen concentration is lowered by bubbling nitrogen through
the inlet head box. It is possible by this method to achieve a wide variety
of oxygen levels simply by varying the nitrogen bubbling rate and monitoring
the water until the desired oxygen level is obtained. If incoming water has
low or variable oxygen level, the values can be brought to near saturation
by cascading the water across ripple panels.
D. Automatic Sampling and Data Acquisition System
1. Automatic water sampling system—The purpose of this system is to
control water flow from various sources to the measurement devices. The unit
is under the control of a data logger which advances solenoid values from one
water source to the next after each measurement sequence. Each channel is
identified by a feedback signal to a data logger input channel.
Each water source being monitored is connected via a normally closed
solenoid valve to a common manifold that directs water to, the test electrodes.
Each valve is actuated in order by the sequencer.
Various electrical, pneumatic, or hydraulic valves are available, and
different sequence control mechanisms can be used to meet specific needs.
Multiple port distribution valves operated by stepping motors can hydraul-
ically or pneumatically trigger the water sampling valves in sequence. Elec-
trically controlled valves are also available. New products are constantly
coming onto the market but the following description of the HIMB prototype
will serve as an example:
53
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Water flow from the various sources is controlled by 20 remote-
controlled normally-closed one-inch valves. The valves we have used at HIMB
are Toro Company Model 202-08-04 units; these are made of plastic and offer
no resistance to flow when open. The valves were modified by replacing the
hard rubber seating gasket with soft 1/4 inch neoprene material to improve
seating. These valves are hydraulic, operating off freshwater line
pressure; they are actuated by 24 volt current to small Automatic Switch
Company Model 8320A136 control valves. The fresh water is isolated from the
seawater stream.
The configuration of the HIMB water sampling system is shown in Figure
A-3. Only one solenoid is activated at any given time by an electrical
signal from the data acquisition system. Water flushes the system for one
minute before data from the probes are recorded. Specific flushing time
should consider maximum volume of the lines through which the water flows,
minimum flow rate of the water, and maximum response time of any in-line
probes. The manifold is designed to insure complete flushing; stagnant areas
are eliminated by use of a loop. Differences in flow over the probes that
occur due to variation in length of hose can influence readings in the oxygen
electrode. Constant flow over the probes at any water source pressure is
accomplished by using a double standpipe arrangement (Figure A-4). Excess
water spills over the first standpipe; a constant difference in height and
thus constant flow over the probes is maintained.
HOSES FROM MICROCOSM
INLETS AND OUTLETS
SEQUENCER
SENDS SIGNAL TO OPEN ONE VALVE
AT A TIME. IN SEQUENCE
FEEDBACK SIGNAL
TO IDENTIFY
SOURCE
4. LIGHT (INTEGRATED)
5 LIGHT (INSTANTANEOUS)
6. OPTIONAL
7. OPTIONAL —
8. SOURCE •
9. TIME •
DATA ACQUISITION
SYSTEM
CONTROLS SCAN RATE
SELECTS CHANNEL
ADVANCES SEOL-ENCER
CONVERTS ANALOG TO
DIGITAL SIGNAL
INSERTS CHANNEL
IDENTIFIER INTO DATA
STREAM
10. ADVANCE TO NEXT SOURCE
Figure A-3.
Schematic diagram depicting the HIMB water
sampling system.
54
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SURPLUS
OVERFLOW
WATER FROM
MICROCOSMS
OXYGEN
PROBE
pH
ELECTRODE
THERMJSTER
CONSTANT
OVERFLOW
Figure A-4.
Enlargement of area of water sampling system (see Figure
A-3) which measures oxygen, salinity and temperature.
2. Automatic data acquisition system—Electronic data-loggers and
electronic measurement probes can be used to monitor water composition and
other variables in microcosms. Many components of the systems utilized in
this program were designed and built locally by electronic technicians to
meet specific needs; since then, versatile commercial data acquisition
systems have become available. The data acquisition system is simple in
concept. The acquisition system signals the water sampling system to shunt
water from various sources past electronic sensors. Outputs from the sensors
are recorded on magnetic tape and/or on a hard-copy printer. A properly
designed system of this type is reliable and relatively easy to operate. The
major problem usually centers on designing, building, and debugging the
unit. The total system consists of measurement devices and a data logger
system.
A variety of useful measurement devices are available. The system
utilized in this program normally measures the following: light, temperature,
dissolved oxygen, and pH. Additional channels are available for input from
other instruments (turbidometer, fluorometer, specific ion electrode, con-
ductivity meter, etc.), as required. Certain electrodes can interfere with
one another through the common ground of seawater (e.g. oxygen and pH
electrodes), so care must be exercised in matching instrument types. Examples
of instruments used successfully with this, system are as follows:
Temperature: An electronic telethermometer (Yellow Springs
Instruments Model 47) with epoxy coated probe (Model 402) was utilized;
numerous other products would be equally suitable. The probe is
replaced with a 5 k-ohm variable resistor when intercalibrating the
instrument with the data acquisition system.
55
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Oxygen: Units with stable battery power sources that are
isolated from line voltage (e.g. Yellow Springs Instrument
Model 57) are unlikely to lose calibration or interfere with
other sensors.
pH: Most pH meters have circuits designed to measure
ungrounded test solutions and will not function in a grounded
salt water stream. The Orion model 801A meter has an isolated
test loop. This meter is satisfactory when used with a
combination electrode such as the Beckman Model 3900.
Light: Instantaneous values of ambient light are measured
by a standard radiometric cell and/or are accumulated value from
a light integrator. In the past few years commercially produced
quantameters with integrators and recorder outputs have become
available (Lambda Instruments) and provide a measure that is
superior to radiometric values for biological studies.
Our test instruments are obsolete, because they produce analog outputs
which must be converted to digital values in the data logger. Analog signals
are prone to transmission interference. A superior system would utilize
digital output measurement devices exclusively. Converters could be in-
stalled directly on analog output instruments that could not be replaced with
digital output units. We have been able to eliminate interference with our
analog signals by shielding the wires and removing sources of electromagnetic
noise (high voltage transformers, large motors, etc.), from the immediate
vicinity of the data acquisition system.
Up to 12 microcosms are usually monitored simultaneously in our system,
although fewer units are used for some experiments. The data acquisition
system is usually set to scan at one-minute intervals, but six different
scanning speeds are available on our logger. Eighteen "water sources"
(twelve microcosm outlets, four inlet head boxes, water from an aerated
saturation bath for Oa probe calibration, and one source in which the 02 meter
is grounded to zero as an event mark) are monitored in sequence. On each
scan, the following variables are recorded or cassette magnetic tape: water
temperature, dissolved oxygen, pH, integrated total light, "mark" (a feed-
back voltage from the water sampling system used to identify each water
source) and "time" from an internal digital clock. The data logger identifies
each of the eight data channels on the tape by inserting a channel mark. Use
of the YSI Model 57 oxygen meter has eliminated calibration drift encountered
with the older YSI Model 54, and use of the aerated calibration water source
on each cycle probably could be discontinued. That calibration bath still
serves as an excellent check and reference mark in the data stream.
Data cassettes are transcribed onto 9-track tape for use on an IBM 370
computer system. The data are formatted into rows and columns and printed
for editing before data analysis.
56
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
i. REPORT NO.
EPA-600/3-79-061
2.
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
Metabolic Responses of Shallow Tropical Benthic
Microcosm Communities to Perturbation
5. REPORT DATE
June 1979 issuing date
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
S. V. Smith,
P. L. Jokiel, G. S. Key, and E. B. Guinther
8. PERFORMING ORGANIZATION REPORT NO
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Hawaii Institute of Marine Biology
Kaneohe, Hawaii 96744
10. PROGRAM ELEMENT NO.
1BA608
11. CONTRACT/GRANT NO.
R800906
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Narragansett, Rhode Island 02882
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
EPA/600/05
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Benthos communities simulating various aspects of coral reefs were
established in 600-liter microcosm tanks. These communities were then
subjected to various environmental perturbations, including altered
light regime, altered substratum type, salinity depression, elevated
nutrient level, and biological manipulation. The metabolic responses of the
community to these perturbations were minortored, primarily by analysis of
dissolved oxygen flux. Light, substratum type, and nutrient levels are
resources which limit community metabolism. From 35 to 22 /oo. Metabolism
is not sensitive to salinty. Metabolism is sensitive to biological
manipulation.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
Marine Biology
Benthos
Metabolism
Reefs
a Ecosystems
06 F
8. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS (ThisReport)
UNCLASSIFIED
21. NO. OF PAGES
67
20. SECURITY CLASS (Thispage)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
57
OUSGPOi 1979-657-060/1675
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