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10
A Scientific Framework For
Environmental Problem-Solving
To manage the effects of environmental manipulations, we must be
able to predict them. However, knowledge is seldom sufficient to allow
accurate prediction, so studies are necessary to provide the information
needed to make decisions. Such studies must be carefully planned, because
they are expensive in time, money, and effort. This chapter presents a
general framework for identifying, scoping, and planning studies of en-
vironmental problems. The framework is, in essence, an admonition to
think before acting and to use established scientific principles. Table 1
makes it clear that deficiencies in environmental impact assessment are
due not only to scientific difficulties the ones with which this chapter
is primarily concerned but also to political, administrative, and eco-
nomic difficulties.
Despite their bewildering variety, environmental problems share some
basic features, including actions that result in environmental changes,
public and scientific concern about those changes, a need for methods for
predicting environmental responses to human actions, and limited re-
sources for the acquisition and analysis of relevant ecological information.
We draw heavily on a number of recent efforts to make environmental
assessment and management scientifically more credible (Andrews et al.
1977; Anonymous, 1980; Council on Environmental Quality, 1978; Fritz
et al., 1980; Holling, 1978; Larkin, 1984; Rosenberg et al., 1981; Sanders
et al., 1980; Sharma et al., 1976; States et al., 1978; Walters, in press;
Ward, 1978) and in particular on a recent Canadian review (Beanlands
and Duinker, 19831.
104
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A SClE=IFIC FRAMEWORK FOR E^IRONME=^ PROBLEM-SOLVING 105
TABLE 1 Some Recent Criticisms of Ecological Impact Assessment,
Based Primarily on Beanlands and Duinker (1983), Carpenter (1976),
Rosenberg et al. (1981), and Skutch and Flowerdeu (1976)
Guidelines too elaborate and requirements too diverse
Time and money constraints not recognized
Unreasonable expectations of decision-makers
Tendency to start gathering baseline data immediately, at the expense of careful planning
Failure to formulate objectives clearly and to develop a study strategy
Unwarranted belief that ecological principles used in managed systems are as appropriate to
unmanaged systems
Failure to recognize the value of early input from those who might later be involved in re
view, leading to an adversarial process
Failure to define project boundaries
Failure to consider cumulative effects
Failure to state the bases of value judgments
Lack of scientific standards for impact assessment
Lack of respect in academe for impact assessment
Vague and unverifiable predictions
Lack of a rigorous, quantitative approach, especially in monitoring
Lack of continuity in studies conducted during planning, developmental, and operational
phases of a project
Failure to follow actions with adequate monitoring studies
Use of impact assessment for disclosure, rather than for learning
Failure to recognize the scientific value of experimentation and monitoring
Failure to consider the recovery potential of species and ecosystems
Poorly written reports in which major points are buried in enormous amounts of information
Inordinate expenditure of effort on descriptive studies with little potential for predictive value
Inaccessibility of reports and results of studies, making them difficult to evaluate and learn
from
DEFINING ENVIRONMENTAL GOALS AND
SCIENTIFIC QUESTIONS
In spite of the difficulties and controversies associated with identifying
environmental goals, a clear statement of goals early on can help to focus
research and can increase the chance of protecting components of the
environment likely to be identified as valuable to society. The first step
in defining such goals is to identify the components of the environment
perceived as valuable, such as salmon in rivers of the northwestern and
northeastern United States, a "natural-looking" community of plants on
reclaimed land (Chapter 18), clean water (Chapter 20), clean air, forest
productivity (Chapter 19), and fishery productivity (Chapter 12~.
The second step is to determine the desired degree of protection, ex-
ploitation, or control. This decision usually involves choosing a state in
which to maintain the ecological system in question and a length of time
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106 KINDS OF ECOLOGICAL KNOWLEDGE AND THEIR APPLICATIONS
for which to maintain it. For example, we might wish to reduce the
population of a pest or the amount of damage it causes, increase the yield
of a harvested species, or maintain the species composition of a valued
habitat. The period of management might be months, decades, or cen-
turies.
The third step is to learn the environmental and financial costs of
managing the system. Maintaining an ecological system in other than
the "natural" condition usually requires some expenditure and might
produce unwanted side effects. Harvesting a population for maximal
yield can increase the variability of the yield and the likelihood of
overharvesting (Chapter 11. Increasing production of an agricultural
crop or forest often involves the use of hazardous pesticides (Chapter
24), which can have several deleterious cumulative side effects (Chap-
ters 1, 3, and 41.
Identifying environmental goals is complex and requires input from
the public and from scientists. The public is concerned primarily with
the choice of environmental goals. Scientists can help to identify non-
obvious goals and can indicate the environmental and economic costs
involved. Scientists are also needed to translate environmental goals
into scientific objectives, which show what information is needed to
answer the major questions and hence help in the planning of studies.
As in any research plan, scientific objectives are based not only on the
need for particular information, but also on how easily that information
can be obtained.
The issues on which environmental goals are based are specified in part
by law and in part by public concern (see Table 24. The National Envi-
ronmental Policy Act requires early public and professional input in iden-
tifying those issues (Council on Environmental Quality, 1978~. The goal
of protecting the Southern Indian Lake whitefish fishery was economically
motivated (Chapter 211. Provincial wildlife biologists recognized caribou
migration as a major public concern in the Newfoundland hydroelectric
development case (Chapter 161. In the case of Lake Washington (Chapter
20), interested scientists and the public cooperated to define goals and
develop an appropriate response; the DDT case (Chapter 24) shows how
such interactions can lead to new understanding and to legislation.
Attempts to achieve a goal sometimes have unexpected results. The
New Brunswick forest case study shows how attempting to maximize
forest timber production on the basis of individual stands might not only
fail to maximize yield over the whole forest, but fail to provide consistency
in yields over a long period. In fisheries, managing for maximal sustainable
yield often produces large variations in both yields and stock abundance
(May 1980), making overexploitation and population collapse more likely
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A SCIENTIFIC FRAMEWORK FOR ENVIRONMENTAL PROBLEM-SOLVING 107
TABLE 2 Some Common Cntena for Identifying
Important Issues and Valued Ecosystem Components in
Impact Assessment
Legal requirements
Air and water quality standards
Public health
Rare, threatened, and endangered species
Protected areas or habitats
Aesthetic values
Landscape appeal
Attractive communities
Appealing species (e,g., large ungulates, colorful birds, cacti)
Species at higher trophic levels (e.g., eagles and tigers)
Clear air and water
.
Economic concerns
Species or habitats of recreational or commercial interest
Ecosystem components
Environmental values and concerns
Ecosystem rarity or uniqueness
Sensitivity of species or ecosystems to stress
Ecosystem " naturalness "
Genetic resources
Ecosystem services
Recovery potential of ecosystems
"Keystone" species
than more conservative management would (e.g., Murphy, 19771. Har-
vesting or managing populations over long periods can also produce un-
desired cumulative genetic changes (Chapter 11.
SCOPING THE PROBLEM
Scoping involves bringing together all interested parties public, busi-
ness, government, and scientific so that they can interact and express
their views before major actions or studies are initiated (Council on En-
vironmental Quality, 19781. Early scoping can help to identify the im-
portant issues and potential environmental effects associated with planned
actions. It can help to define scientific objectives and guide the design of
ecological studies. Scoping can also be useful during a program or project
to ensure that the most important issues are being addressed, that studies
are producing useful results, and that important new issues are noted (Fritz
et al., 1980; Sanders et al., 19801.
Once the valued ecosystem components, significant issues, and major
potential effects have been identified, ecologists can establish scientific
objectives. When prediction of environmental effects is a major purpose
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108 KINDS OF ECOLOGICAL KNOWLEDGE AND THEIR APPLICATIONS
of studies, four questions are usefully posed (Beanlands and Duinker,
19831:
· Are valued ecosystem components expected to be affected either
directly or indirectly by the project or action?
· Can the valued ecosystem components be studied directly? (In the
absence of adequate guidance from experience or the literature, pilot
investigations might be needed to indicate the feasibility of particular
studies.)
· Is it possible to study valued ecosystem components indirectly? For
example, because large carnivores are often difficult to study directly, the
effects of an action on their prey base or their habitat could be studied
instead. Studies of indirect effects are most appropriate when they are
reliably associated with effects on the valued ecosystem components.
· Would the use of indicators of impact be helpful? (See Chapter 7.)
Formulating a conceptual model of the relationships between the pro-
posed action and the receiving environment can help to identify pertinent
questions and potential environmental effects. The purpose of such models
is to identify the physical and biological pathways by which an action can
produce ecological effects. By focusing on relationships important to the
manifestation of effects, they help to develop specific, testable hypotheses
to explain why particular effects should or should not occur. Conceptual
models can also help to identify logical errors, to highlight factors that
require special study, to synthesize ideas and knowledge, and to com-
municate information (Beanlands and Duinker, 19831; guidance for de-
veloping conceptual models can be found in Holling (1978), Ward (1978),
Fritz et al. (1980), and Beanlands and Duinker (19831. Multidisciplinary
workshops can be used to articulate a problem and plan studies (Holling,
1978) and have been used to advantage in this way (ESSA, 19821.
Given adequate time and resources, sophisticated modeling should be
considered (Munn, 1979~. Basic guidance in development and use of such
models can be found in Frenkiel and Goodall (1978), Holling (1978), and
Ward (1978~. Quantitative modeling can help by forcing assumptions to
be made explicit, by making their consequences clear, and by revealing
the sensitivity of outcomes to details of various assumptions. Simulation
models are necessarily based on numerous unverified assumptions and
cannot predict quantitative changes very accurately (Hilborn, 1979; Wal-
ters, 19751. But they can be useful in identifying potential qualitative
effects and exploring the consequences of alternative management plans.
Sensitivity analysis allows an exploration of the consequences of altering
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A SCIE=IFIC REWORK FOR EWIRONMEV~ PROBLEM-SOLVING 109
the assumptions of a model. Simulation models are often used in con-
nection with freshwater systems (Chapter 21), in which the driving phys-
ical and chemical processes are fairly well understood; fishery and wildlife
management (Chapter 121; epidemiology (Chapter 151; and forest man-
agement (Chapter 191.
ESTABLISHING STUDY BOUNDARIES
One of the first and most important tasks in the design of research on
environmental effects is to establish a set of boundaries-temporal, spa-
tial, and ecological. When might effects appear, and how long might they
last? How long must studies last to allow reasonable predictions and
reliable diagnosis of effects? Over what area will effects occur? Are there
any natural barriers to the transmission of effects? Are any physical or
biological processes likely to spread effects to other areas? What ecosystem
components will be affected? At what levels of biological organization
will effects appear? What species or ecosystem processes need to be
studied and over what area? Boundaries in open systems, such as the
ocean or atmosphere, are the most difficult to define. Variations in eco-
system components of interest can strongly influence the time required
for biological effects to appear (Holling, 1973~.
Making judgments about boundaries is difficult, and many surprises
have occurred. For example, large water impoundments can influence
local climate or induce earthquakes (Baxter and Glaude, 19801. When
DDT was first used as a pesticide, no one expected it to appear in animals
in the ocean (Chapter 241. The DDT story and similar cases (e.g., that
of acid rain) have shown that environmental effects can spread by subtle
pathways. Assumptions implicit in management decisions might result in
setting boundaries that omit critical processes. Attempts to increase stocks
of anadromous fish by increasing reproduction in rivers might fail if
survival in the ocean is already limited by food supply (Peterman, 19844.
The cumulative effects of multiple actions have taught us that specific
projects and actions must be viewed in the context of related actions
(Odum, 1982~. Recent efforts to protect and conserve species have shown
how management of a population requires consideration of its relationship
with other populations (Franker and Soule, 1981; Schonewald-Cox, 1983;
Soule and Wilcox, 19801. And only recently has it been recognized that
systematic management procedures e.g., sex-biased or size-biased har-
vesting-can lead to undesirable genetic changes over remarkably short
periods (Chapter 11.
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110 KINDS OF ECOLOGICAL KNOWLEDGE AND THEIR APPLICATIONS
The establishment of boundaries is constrained by administrative, proj-
ect-related, technical, and ecological factors (Beanlands and Duinker,
19831. Administrative constraints include jurisdictional limits, insufficient
time or funding, and political factors. Spatial boundaries are often obvious,
unless long-range transport phenomena are involved. Temporal boundaries
might be less well defined, because of political and other uncertainties;
as we go from short-term, local effects at the population level to long-
term, regional effects at the ecosystem level, we are less able to predict
them (Christensen et al., 19761. Other technical constraints are imposed
by environmental variability, project location, and logistical problems.
Setting appropriate temporal and spatial boundaries is important in the
management of species populations, whether for protection, control, or
harvest. When populations become small, patterns and rates of interchange
of individuals and genes between populations become critical. The sizes
of populations needed for the long-term maintenance of the spotted owl
in the Pacific Northwest depend on whether the Columbia River is a
dispersal barrier (Chapter 171. When timber is managed on a forest-wide
basis, rather than by stands, yields are higher and more consistent (Chapter
191. Physical and chemical processes can be critical in defining boundaries
in aquatic systems, particularly when the spread and accumulation of
pollutants are involved. The control of eutrophication in Lake Washington
depended on knowledge of flow rates through the lake and the low turnover
of phosphate in lake sediments (Chapter 201.
DEVELOPING AND TESTING HYPOTHESES
Statements about relationships between proposed actions and ecosystem
components or processes are, in effect, hypotheses that can be tested.
Studies designed to test them can increase our ability to predict environ-
mental effects. In addition, the explicit statement of hypotheses helps us
to identify important assumptions and formulate specific objectives for
ecological studies. However, despite the acknowledged value of testing
hypotheses in solving environmental problems, many studies are not de-
signed and conducted to do so. Many studies in wildlife management, for
example, involve elaborate collection of field data with only after-the-fact
attempts at explanation (Romesburg, 19811. What happened as a result
of a project is rarely studied (Beanlands and Duinker, 1983; Larkin, 1984~.
In practice, most general hypotheses are evaluated by testing specific
predictions that arose from them. In environmental impact assessment,
the predictions themselves are a major product of preproject research. It
is often helpful to develop several hypotheses about possible effects and
their causes, so that studies can be designed to distinguish among them.
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A SCIENTIFIC FRAMEWORK FOR ENVIRONMENTAL PROBLEM-SOLVING 111
A hypothesis can be tested by studies before a project and by treating
the project itself as a test. Methods for testing ecological hypotheses in
preproject studies include the use of microcosms (Crow and Taub, 1979;
Heath, 1979), field and laboratory experiments (Giddings, 1980; Suter,
1982; Ward, 1978), and computer simulations (Frenkiel and Goodall,
1978~. Despite the difficulty of assigning causality in field experiments
(Sharp et al., 1979) and of extrapolating from small studies to large
problems (Hilborn and Walters, 1981), pilot-scale perturbation studies
could be the most productive research tool for impact assessment, although
underused (Beanlands and Duinker, 1983; Ward, 19781.
If projects are to be treated as large-scale experiments, baseline data
must be collected before the project begins (Beanlands and Duinker, 1983;
Hilborn and Walters, 1981; Larkin, 1984~. The baseline can best be viewed
as a description of the mean values and natural variability in the system
(Hirsch, 19801. Judgments of how much information is needed are often
difficult, because of periodic cycles, random events, and spatial hetero-
geneity and because many variables can change systematically during the
baseline study period (e.g., owing to succession).
Statistical guidance is available for designing baseline and monitoring
programs once the variables of interest have been identified (Cowell, 1978;
Eberhardt, 1976, 1978; Green, 1979; Kumar, 1980; Lucas, 1976; Sharp
et al., 1979; Ward, 1978; Zar, 1976~. Two common problems that make
it difficult to design projects as experiments properly are the lack of
adequate controls (Cowell, 1978) and the lack of true replicates (Eberhardt,
19761. Eberhardt (1976) suggested a "pseudodesign" with baseline data
on a control area and the project site. They can be compared with data
collected when the project is complete, with replicates in time substituting
for spatial replicates.
Baseline and monitoring studies are most effective if they are statistically
designed to detect changes of the magnitude expected (Zar, 19761. This
expectation in turn determines the extent of sampling required (Hartzbank
and McCusker, 19791. In highly variable systems, adequate sampling
might be too expensive, and resources might be better used in carrying
out less direct studies. Baseline information can sometimes be derived
after impacts have already occurred (e.g., Cowell and Syratt, 19791.
The Lake Washington case (Chapter 20) is an excellent example of
testing hypotheses concerning the effect of lake fertilization changes on
the makeup of plankton communities. A great deal was learned from this
case, because monitoring continued throughout the development and treat-
ment of the problem. Similarly, scientists at Southern Indian Lake (Chapter
21) were able to test hypotheses derived from the results of other lake
studies and current limnological models. Carefully designed studies before
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112 KINDS OF ECOLOGICAL KNOWLEDGE AND THEIR APPLICATIONS
and after project development showed that some of the predictions were
wrong because the models used were not based on knowledge of lakes in
a permafrost zone.
Field and laboratory experiments can be used to test hypotheses. The
Garki malaria project (Chapter 15) was itself a large-scale experiment to
investigate a model for controlling malaria through a combination of drugs
and mosquito control. Careful monitoring studies before, during, and
after applications allowed the model to be tested, and an important
phenomenon exophily was discovered.
SPECIFYING PREDICTIONS AND DETERMINING
THE SIGNIFICANCE OF EFFECTS
A major purpose of developing general ecological hypotheses is to
generate a set of specific predictions of ecological change that can be used
in decision-making. The predictions should be as clearly and precisely
stated as possible. The period over which a change is expected to occur,
the bases of the prediction, and the degree of uncertainty should be spec-
ified.
Determining the significance of predicted or observed ecological changes
is often very difficult, because ecological systems are not fully understood.
A clear distinction, if it can be made, between the magnitude of a change
and its biological importance is useful. The rates of change and recovery
are often important components of ecological effects (e.g., Cairns and
Dickson, 19801.
The overall significance of an effect is tied closely to the definition of
environmental goals. The best course for scientists is to predict or describe
changes precisely. Whether or not a change is " significant" is a judgment
that transcends science and is best made by all interested parties.
Several of the cases studied were organized around tests of specific
predictions. In the derelict lands restoration case (Chapter 18), predictions
were derived from empirical results of other restoration efforts and basic
plant ecological theory. The bases of these predictions were clearly stated,
and tests of them produced results of value to other restoration projects.
Predictions in the Atomic Energy Commission radiation studies were de-
rived from knowledge of food-chain dynamics and laboratory studies, and
hypotheses were continually revised as predictions were tested experi-
mentally (Chapter 221.
In the Lake Washington case, scientists predicted not only specific
changes in water quality, but also the periods over which deterioration
and recovery would occur (Chapter 201. In the Southern Indian Lake
studies (Chapter 21), predictions were based on analogs and limnological
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A SCIENTIFIC FRAMEWORK FOR ENVIRONMENTAL PROBLEM-SOLVING 1 13
principles, but were mostly qualitative. In both cases, careful monitoring
was incorporated into comprehensive postproject analyses to improve un-
derstanding.
MONITORING
Biological monitoring is used in ecological studies in two basic ways.
Studies conducted during or after an action or project are designed to learn
what ecological changes resulted. Anticipatory monitoring is designed to
track the effects of activities that might be cumulative or pose hazards to
human health (Baker, 19761. Properly done, monitoring provides contin-
uous indexes of environmental quality that can signal environmental deg-
radation or improvement (Chapter 7~.
In the event of unexpected environmental changes, monitoring can
facilitate adaptive changes in management and in the design of ecological
studies (Hilborn et al., 1980; Holling, 1978; Walters and Hilborn, 19761.
From a broader perspective, followup monitoring and retrospective anal-
ysis are ways to learn from experience and improve the prediction of
ecological effects. Monitoring is most effective when it is designed to test
ecological hypotheses and when preproject studies have provided baseline
information (see Beanlands and Duinker, 19831. Postproject studies of
the accuracy of predictions are useful, but are not as useful as followup
monitoring that coordinates preproject and postproject sampling and that
tests relevant hypotheses.
Periodic analysis of results can help to detect unexpected changes and
evaluate sampling programs, allowing them to be changed in a timely
way. Thus, an iterative approach to monitoring with results fed into
study design is often effective, particularly when methods have not been
well tested and when effects are uncertain. Any changes in sampling,
however, must be made carefully, to ensure that new data are statistically
comparable with those already collected.
Baseline monitoring of characteristics with substantial variation has a
low probability of helping to detect changes due to a project. Measure-
ments of baseline variability can help to identify the characteristics that
it will be useful to measure in followup studies (Green, 1979) and can be
used, with estimates of the duration of effects, to determine how long
followup should continue.
Even if all the above criteria are met, followup studies of ecological
effects can help in planning only if they are made available in an easily
digestible form, ideally as published summaries and as complete postproj-
ect analyses (Hilborn and Walters, 19811.
In several case studies, followup monitoring was shown to be part of
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114 KINDS OF ECOLOGICAL KNOWLEDGE AND THEIR APPLICATIONS
an overall study design to test hypotheses (Chapters 15, 22, and 23~. The
hydroelectric development in Southern Indian Lake (Chapter 21) was
treated as a large-scale experiment, and monitoring provided increased
understanding of artificial lakes. Because the results were analyzed and
published, they can be applied to other cases.
In the caribou case (Chapter 16), monitoring of caribou movements and
herd productivity began before development and continued during con-
struction. Daily information on caribou movement was incorporated into
constraints on construction activities. Annual monitoring of catch and
fishing effort is used by the International Pacific Halibut Commission to
set fishing quotas. Monitoring of conditions in Lake Washington allowed
scientists to detect changes, predict trends in eutrophication, and predict
and document recovery of the lake after action was taken; because the
work was published, its lessons are readily available to managers of similar
projects. Monitoring for DDT in the environment first identified the spread
of another important group of toxic chemicals, PCBs (Chapter 241.
SUMMARY: DEVELOPING A STUDY STRATEGY
A study strategy is a plan for conducting ecological studies to help to
predict and manage ecological effects. It is motivated by the environmental
goals identified in scoping and is organized around the scientific objectives
defined on the basis of the goals. Scoping identifies what information is
required, and the study strategy specifies how to acquire it. A problem
must be carefully thought through before studies aimed at solving it begin
(Beanlands and Duinker, 19831.
Potential study objectives should be evaluated, so that efforts can be
devoted to studies with some chance of producing useful results. What
information is needed? Why is it needed? Is it possible to acquire adequate
information? How will the information be used to satisfy the ecological
goals? How will it be used in decision-making? Highly accurate charac-
terization of a variable is of little use if decisions are made on the basis
of other considerations. Decision analysis helps to ensure that modeling
and research remain focused on the objectives.
A basic first step in designing studies is a review of what is already
known about the problem. Larkin (1984) believes that literature review
can provide more than 50% of the information needed in most initial
impact assessments, and as much as 75% when coupled with brief re-
connaissance surveys.
To summarize, a broad ecological study strategy:
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A SCIENTIFIC FRAMEWORK FOR ENVIRONMENTAL PROBLEM-SOLVING 1 15
· Is based on thought-out environmental goals.
· Is organized around clearly defined scientific objectives designed to
satisfy the environmental goals.
· Includes a description of the boundaries established for the problem,
with demonstration of their appropriateness.
· Is designed to evaluate hypotheses about how the ecological system
functions and will be affected by perturbations.
· Specifies predictions that will be tested, with the basis of the pre-
dictions and a statement of confidence in their accuracy.
· Defines the basis for choosing environmental goals and evaluating
their significance.
· Explains clearly how each part of the study fits into the overall design.
· Provides for baseline and followup monitoring to determine the ef-
fects of the project or perturbation.
· Allows the results of the study to be used to evaluate the plan and
to modify it if necessary.
Representative terms from entire chapter:
ecosystem components
