Managing Troubled Waters The Role of Marine Environmental Monitoring (1990) / Chapter Skim
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4 Designing and Implementing Monitoring Programs
4 Designing and Implementing Monitoring Programs
Pages 53-89
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From page 53... ...
As emphasized in Chapter 2, when monitoring data have been converted to information in this manner, they generally provide better support for specific management actions. This chapter presents comprehensive guidance for developing the technical design of monitoring programs and describes a procedure for ensuring that the information produced meets the needs of managers and decision makers.
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From page 54... ...
Without this commitment, effort and money will be spent to collect data and produce information that may be useless. A CONCEPI UAL APPROACH TO DESIGNING MONITORING PROGRAMS Technical design can be challenging.
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From page 55... ...
To specific a methodology (i.e., one that specifies the exact models, parameters, sampling plans, and analyses) would be applicable only to a narrow range of
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From page 56... ...
The focused questions that serve as the basis of a monitoring program rely on clear management objectives
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From page 57... ...
allow program designers to review and modify monitoring objectives in light of actual monitoring information about the effectiveness of specific management actions and technological advances that occur during the study. The above, and other, feedback points at more detailed levels of the methodology permit information that results from monitoring to be used to refine the sampling design.
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From page 58... ...
growth and continued development of the coastal zone will increase the demand for monitoring information to support environmental decision making (EPA 1987; Champ, Conti, and Park 1989~. If monitoring programs are to meet these demands, their objectives must integrate public concerns and expectations with the legal and regulatory framework through the use of scientific understanding to identify the relevant questions to be addressed.
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From page 59... ...
" Stating clear monitoring objectives involves answering these questions as precisely and unambiguously as possible. The three case studies identified many instances in which the development of clear objectives helped translate monitoring data into tnformation that supported management actions.
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From page 60... ...
Even though the analysis underlying Figure 4.3 was qualitative and was based on incomplete understanding, it helped participants in the Southern California Bight case study identify potential effects not addressed by ongoing monitoring programs. Figure 4.3 was especially valuable as a tool for synthesizing the available information into a conceptual model of system interactions.
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From page 61... ...
This figure was used to summarize and investigate ways of identifying and ranking impacts in the Southern California Bight. SOURCE: Adapted from Clark 1986.
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From page 62... ...
These questions guide subsequent steps in the technical design process. Step 2 begins with the general monitoring objectives developed in step 1 and ends with explicit questions to be answered that are the basis for developing a sampling design.
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From page 63... ...
" As shown in Figure 4.4, several steps are involved in progressing from general monitoring objectives (step 1 and Figure 4.3) to specific questions to be answered (step 2 and Figure 4.4~.
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From page 64... ...
Few long-term monitoring programs have dealt with the effects of OCS development activities; several field assessments, although not continued for long periods, share a basic purpose and many design considerations with environmental monitoring. They include several studies in the Gulf of Mexico, which has experienced offshore oil and gas development since the 1940s, and monitoring studies in the Mid-Atlantic Bight, on Georges Bank, and, more recently, in central California.
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From page 65... ...
The evolution of the sampling design of the San Onofre kelp bed monitoring program (see Box 4.3) is a good example of a typical situation in which information acquired during the technical design stage modified the original understanding of the system and thus the monitoring objectives.
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From page 66... ...
" To produce precise questions, SCE and MRC integrated preliminary studies with research and monitoring information on kelp bed ecology. Arriving at specific questions to be answered required refinement of the conceptual model and several iterations of modeling, research, and prediction.
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From page 67... ...
Suitable boundaries ensure that monitoring is relevant to both natural processes and the environmental quality and human health objectives established early in the technical design. For example, a major finding of the Southern California Bight case study was that the assortment of individual monitoring programs in Southern California was not adequate to address important potential regional and cumulative environmental effects.
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From page 68... ...
Based on available technical knowledge, it was then expanded to include quantitative elements, such as analytical or numerical models. Sometimes the conceptual model includes more than one kind of numerical model (e.g., in the kelp bed example, plume dispersion and light attenuation models)
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From page 69... ...
Establishing appropriate space and time boundaries is particularly important in developing the sampling design for monitoring studies for several reasons. First, the majority of parameters that could be measured by monitoring programs vary on space and time scales.
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From page 70... ...
And third, spatial and temporal variability in the marine environment can easily confound the interpretation of monitoring results (Botkin and Sobel 1976; Livingston 1982; Pearson and Barnett 1987; Holland, Shaughnessy, and Hiegel 1986~. Establishment of appropriate boundaries ensures consideration of all events and processes that affect the questions being asked and thus the sampling design.
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From page 71... ...
Numerical models are often used to make predictions for monitoring design and management because they systemize knowledge and produce quantitative predictions. However, it is important to recognize that numerical models are not infallible.
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From page 72... ...
Such studies help refine measurement techniques, result in the development of new methods or models, estimate the magnitude of natural variability, or otherwise lay the groundwork for developing a monitoring design. Preliminary studies have supported development of the technical design of many monitoring programs.
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From page 73... ...
supported development of the long-term benthos monitoring program. An important category of preliminary studies is the measurement of important parameters under different hydrological regimes to calibrate and validate water quality models.
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From page 74... ...
The elements of step 4 include: identifying the lipids and amounts of change that are meaningful; identifying and quantizing the sources of variability that may obscure or confound responses; deciding what to measure, in light of logistical constraints and limitations on scientific knowledge; developing a sampling design that provides the logical structure for the measurement program by specifying how variability will be partitioned; specifying statistical models that are the basis for selecting the kinds and numbers of measurements that should be taken; performing optim~ation and power analyses to determine whether the monitoring design can measure meaningful levels of change; defining data quality objectives; and developing the sampling/measurement design that incorporates all the above elements. Defining Meaningful Change The goal of a monitoring sampling design should be the detection of specific kinds and amounts of change in the resources at risk, in surrogate variables related to them, or in parameters involved in model validation or increasing the understanding of important natural processes (e.g., Fredette et al.
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From page 75... ...
note that statistical, scientific, project-specific, and wider societal concerns all contribute to the definition of meaningful changes. The benefits of defining how much change is meaningful cannot be overstated.
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From page 76... ...
Virtually any change can be statistically significant, depending in part on the sampling effort. Thus a monitoring program with a small sampling effort will detect only large changes, but one with an intensive sampling effort could find even miniscule changes statistically significant.
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From page 77... ...
. Understanding variability aids development of a sampling design in several ways: it helps construct a conceptual model that includes key natural processes and linkages that affect the resources being monitored, it helps partition variability by collecting data on appropriate space and time scales (Livingston 1987; Kerr and Neal 1976)
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From page 78... ...
For example, the lack of an atmospheric source term for nutrients in water quality models of Chesapeake Bay led to erroneous predictions and incomplete management strategies (Fisher et al. 1988; Tyler 1989~.
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From page 79... ...
In addition, changes in diversity can be ambiguous, particularly when the study assemblage is exposed to more than one source of disturbance (NRC 1986~. Criteria that should be used to select surrogate variables include sensitivity to the stress of concern, reliability and specificity of responses, ease and economy of measurements, and relevance of the indicator to specific concerns (NRC 1986~.
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From page 80... ...
Such variables are not appropriate for routine monitoring programs.
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From page 81... ...
A poorly thought out sampling design usually results in testing of inappropriate questions, incomplete evaluation of questions, inability to separate change due to natural processes from change due to multiple activities, relatively low ability to detect change (low statistical power) , and poor use of resources due to oversampling (e.g., Gore, Thomas, and Watson 1979; Hurlbert 1984; Stewart-Oaten and Murdoch 1986; Green 1979; Thomas 1978; Bernstein and Zalinski 1983; Taft and Shea 1983; liautmann, McCulloch, and Oglesby 1982; Skalski and McKenzie 1982; Millard and Lettenmaier 1986~.
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From page 82... ...
Quality control includes activities to ensure that the data collected are of adequate quality given study objectives and the specific hypotheses to be tested (steps 1-4~. Quality control activities frequently undertaken within monitoring programs include standardized sample collection and processing protocols and requirements for technician training (EPA 1984b)
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From page 83... ...
For example, during the early stages of the Chesapeake Bay Monitoring Program, nutrient data were collected and analyzed by three regional laboratories, all using different protocols for processing samples. As a result, the data were not comparable and could not be used to depict nutrient distributions accurately (Martin Marietta Environmental Systems 1987~.
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From page 84... ...
.. in a monitoring program frequently do not direct~y address public concerns or the information needs of decision makers.
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From page 85... ...
Analysis programs should be developed prior to data collection. This development should include both statistical testing and modeling to ensure that the analysis approach is appropriate to the sampling design and the sampling methods.
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From page 86... ...
can be an important source of ideas for future experiments and measurements. The Southern California Bight case study found that monitoring programs had benefited greatly from their close association with ongoing research programs designed to understand the fate of discharged wastes and assess sublethal effects.
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From page 87... ...
Monitoring programs that produce only technical reports summarizing data and scientific findings are not likely to show the public or decision makers that they provide information essential to better environmental protection or management decisions. In fact, management information is produced only when it is delivered to managers and decision makers in a usable, accessible form.
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From page 88... ...
Executive Summaries Program summaries, prepared annually, are short documents prepared for each major program element. They list the data being collected; describe how, when, and where collections are made; list the name, telephone number, organization, and address of the responsible principal investigators; describe how to obtain data summaries and/or raw data; highlight major findings, conclusions, and recommendations; and describe future plans.
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From page 89... ...
Although not a necessary ingredient of every monitoring program, research on natural variability and its causes, ecosystem function, transport and fate of materials, and biological effects of contaminants and habitat alterations is critical to the evolution of knowledge that makes monitoring more effective. At the least, regional trends monitoring should be accompanied by an ongoing research program designed to contribute to the interpretation of monitoring results.
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