An approach to integrated ecological assessment of ... - Science Direct

Journal of Environmental Management (2002) 66, 411±427 doi:10.1006/jema.2002.0598, available online at http://www.idealibrary.com on

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An approach to integrated ecological assessment of resource condition: the Mid-Atlantic estuaries as a case study Barbara S. Brown*, Wayne R. Munns Jr and John F. Paul US Environmental Protection Agency, Of®ce of Research and Development, National Health and Environmental Effects Laboratory, Atlantic Ecology Division, 27 Tarzwell Dr, Narragansett, RI 02882, USA Received 9 March 2000; accepted 31 May 2002

The complex and interconnected nature of ecological systems often makes it dif®cult to understand and prevent multiresource, multistressor problems. This article describes a process to assess ecological condition at regional scales. The article also describes how the approach was applied to the Mid-Atlantic estuaries, where it focused on characterizing the current state of the environment rather than on predicting future effects from humans. The necessity for iteration during the exercise showed how important it was to identify the purpose of the assessment and its users, that appropriate, consistent data are lacking for large-scale assessments, and that it remains a challenge to communicate succinctly the results of such an assessment. Published by Elsevier Science Ltd

Keywords: integrated assessment, ecological condition, EMAP, MAIA.

Introduction As society succeeds in managing the impacts of single pollutants from single sources on ecological systems, it increasingly has to contend with the more-complex problems of multiple pollutants from multiple sources (NRC 1995, 1997). The risks from these multiple inputs are often experienced simultaneously and may be additive, synergistic, or antagonistic. Therefore, efforts to manage one risk may have impacts, positive or negative, on other risks. In addition, bene®t/cost evaluations of risk management options may be affected by how the scope of the problem is originally de®ned (USEPA, 2000).

* Corresponding author. Email: [email protected] 0301±4797/02/$ ± see front matter

To anticipate and contend with these concerns, environmental management in the United States is increasingly attempting to evaluate condition at larger geographic scales to integrate multiple types of management actions as well as to evaluate fully the geographic extent of effects. However, there are no generally accepted procedures for assessing ecological conditions on these scales. Regional environmental assessments in the United States are not new. In 1927, for example, Congress mandated that speci®c environmental aspects, such as hydrology, of the Nation's major drainage basins were to be assessed to evaluate the basins for particular waterrelated human use (P.L. 70-560, 1927). More recently, the National Environmental Policy Act of 1970 (NEPA) focused attention on assessing the environmental effects of human activities. NEPA required that the short-term, long-term, direct, indirect, cumulative, irreversible, and irretrievable Published by Elsevier Science Ltd

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consequences of these activities be evaluated for the purpose of avoiding to the fullest practical extent the undesirable consequences to the environment, although ùndesirable' remained ill-de®ned (P.L. 91-190, 1970). However, quanti®cation and consistency in interpreting ecological condition in these early assessments was limited due to lack of understanding of the ecological mechanisms at work (i.e., what to measure), criteria against which to compare the current state (i.e., when to declare it degraded), and information representative of or encompassing the entire geographic area of the assessment (i.e., how extensively to measure it). Interpretation of multiple pieces of information was primarily subjective in nature. Over the last 20 years, there have been increasing efforts to overcome these limitations. This article evaluates characteristics of a number of ecological assessments in the United States which attempted to characterize large regions in quantitative terms and interpret that information for management purposes. Some of the features of those assessments were used to develop a generalized process for evaluating ecological condition. Considerations speci®c to application of the process at large geographic scales as well as application of the process in the Mid Atlantic region of the US is described.

Analysis of ecological assessments In order to develop a generalized process which could be applied to assessment of large geographic regions, a number of previous and on-going assessments were analyzed. Assessments were selected for analysis if they met a majority of the following criteria: The assessment covered a multi-state geographic area. The assessment included a component characterizing the ecology of the region using data on multiple physical, chemical and biological measures. The assessment assigned a value to the measure (good, fair, poor). The assessment synthesized the data from multiple measures into a small number of synoptic indicators to portray the ecological condition of the entire region. These criteria were selected to address the limitations of early assessments identi®ed in the previous

section. No attempt was made to identify all assessments in the literature which met those criteria. Rather, a subset was chosen and compared to see if consistent approaches or limitations could be identi®ed and generalized. Six national or regional assessments are reviewed below and a comparison of key aspects of each is summarized in Table 1. The ®rst four were performed prior to the Mid Atlantic case study, and insights gained from analysis of these were used to develop the generalized framework. The last two were performed concurrently with the case study and their outcomes will be compared to the case study in the discussion section below. The US National Acid Precipitation Assessment Program of 1980 (NAPAP) was mandated by Congress to study the scienti®c, technological, and economic aspects of fossil-fuel combustion, acids and other pollutants formed from these emissions, and the effects of these pollutants on the environment, the economy, and human health (NAPAP, 1991). Stressor information was collated from a number of sources, including an inventory of existing point source emission data, a number of regional-scale wet deposition monitoring networks, and some limited dry deposition monitoring. Regional results were extrapolated using comprehensive atmospheric process models. Biological effects data were also collated in a number of ways. Water chemistry data was collected in a statistical sample of lakes and streams in areas of the United States sensitive to acidic deposition. Detailed analyses of regional patterns of ®sh distribution and trends through time were conducted for 409 lakes in a subregion (the Adirondack lakes) and used to develop an acidic stress index to extrapolate the effect of acidic deposition on ®sh regionally. A combination of routinely collected agricultural and forest health data were used to evaluate terrestrial effects, including crop production, forest soil acidi®cation, radial growth rates, and tree crown dieback. The 1990 Integrated Assessment Report of the US National Acid Precipitation Assessment Program (NAPAP, 1991) reported these data, evaluated sensitivity of the effect indicators by simulation models based on mechanistic studies, and provided information for managerial consideration in decision making by using predictive models to simulate a variety of scenarios which might occur under different management alternatives. A summary of the assessment was provided through approximately 30 narrative `®ndings' statements. The Chesapeake Bay Program (CBP), formed in 1983 by the ®rst Chesapeake Bay Agreement, is a regional partnership of states and US federal

Table 1.

Comparison of characteristics of selected regional ecological assessments

Assessment

Purpose

Geographic extent

Evaluate effects of fossil fuel combustion pollutants

Eastern United States

State of the Chesapeake Bay

Chesapeake Bay, MD and VA

Waquoit Bay ecological risk assessment Environmental monitoring and assessment program Virginian Province estuaries

Assess progress toward restoring Chesapeake Bay's natural system Determine ecological risk of excess nutrient load to biota Develop integrated monitoring & assessment protocols for ecological condition

National eutrophication survey

Evaluate status of nutrient enrichment & eutrophication

NationalÐmajor US estuaries

Mid Atlantic regional assessment

Evaluate current & future effects of climate variability & change

Mid Atlantic region

Waquoit Bay, MA US estuaries from Cape Cod to Cape Henry

Trends/changes under different management scenarios Trends Explicit selection of endpoint thresholds Thresholds

Expert opinion of high/medium/low (based on consistent thresholds) Likely trends

Synopsis method Narrative ®ndings statements Maps showing trends in key parameters N/A Cumulative distribution function graphs of % of estuaries exceeding thresholds Index from scoring of primary & secondary impacts Graphs of arrows for each issue where direction & size conveyed positive or negative trend & size of impact

Approach to integrated ecological assessment

National acid precipitation assessment program

Valuation method

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agencies dedicated to the restoration of the Chesapeake Bay. The Chesapeake Bay Monitoring Program, begun in 1984, is comprised of over 165 stations, measuring nineteen physical, chemical and biological characteristics in the Chesapeake mainstem and many of the bay's tributaries. The State of the Chesapeake Bay: A Report to the Citizens of the Bay Region (CBP, 1999) describes the progress to date in restoring the natural system of the Chesapeake using the data from the monitoring program to show trends in those measures against management goals set by the regional partnership. The US Environmental Protection Agency's (USEPA) Risk Assessment Forum began work on developing the principles for performing ecological risk assessments (ERA) in 1988. The Framework for Ecological Risk Assessment (USEPA, 1992) elucidated principles such as identi®cation and preliminary characterization of stressors, ecosystem components and ecological effects and focusing of the assessment through the use of assessment endpoints (environmental values to be protected), and measurement endpoints (ecological characteristics that can be related to the assessment endpoint). The Risk Assessment Forum sponsored several case studies to demonstrate application of the framework, including one for Waquoit Bay, Massachusetts. Problem formulation in Waquoit Bay identi®ed excess nutrient loading and its effect on eelgrass beds as the primary issue of concern for environmental managers and stakeholders. Models were developed relating eelgrass coverage to nutrient loading with the intent of predicting future loadings under different development scenarios to help decision-makers determine needed load reductions. The USEPA Environmental Monitoring and Assessment Program (EMAP) was initiated in 1988 in response to demand for information about the degree to which existing pollution control programs and policies protect the United States' ecological resources. EMAP developed integrated monitoring and assessment protocols employing a probability-based sampling design and a suite of ecological indicators to assess physical, chemical and biological condition. The selection process for ecological indicators employed the concepts of assessment endpoints and measurement endpoints from the ERA framework, but chose to communicate these in terms of assessment questions, rather than simply endpoints. The EMAPVirginian Province Four-Year Assessment Report (1990±93) (Paul et al., 1999) presents an assessment of whether there is an environmental problem in

northeastern US estuaries based on estimates of the percentage of estuaries exceeding certain thresholds (indicating degradation) using data collected as part of the initial development and demonstration of EMAP methods. The US National Oceanic and Atmospheric Administration (NOAA) began the National Estuarine Eutrophication Survey in 1992 to assess the scale and scope of nutrient enrichment and eutrophication in the major US estuaries. NOAA elected to acquire a consistent and detailed set of qualitative data on 16 parameters from the existing expert knowledge of over 300 coastal and estuarine scientists through a series of surveys. The surveys established ranges for characterizing each parameter as high, medium or low, and asked each respondent to give their opinion of the value of applying those parameters in particular estuaries. Respondents were also asked to characterize the certainty of their answers. The National Estuarine Eutrophication Assessment (Bricker et al., 1999) reported an index based on a score assigned to six key symptoms, or responses, which incorporated the spatial coverage and frequency of occurrence of those symptoms in each estuary. The United States initiated the National Assessment of the Potential Consequences of Climate Variability and Change in 1997. The national assessment contains regional components, including the Mid-Atlantic Regional Assessment (MARA). The purpose of the assessment is to provide scienti®c information to identify how people and their surroundings are affected now by climate variability and how they will be affected by climate change, as well as to identify how individuals and communities can take advantage of opportunities to reduce vulnerabilities resulting from climate variability and change (Fisher et al., 2000a). The MARA assessment identi®ed four assessment questions, one of which focused on de®ning the region's current environmental stresses and issues. The program then used existing large data sets collected by Federal agencies to describe overall regional characteristics (e.g., census population, land cover, stream¯ows), supplemented by use of quantitative models to analyze speci®c resource effects at the regional scale. Preparing for a Changing Climate: Mid Atlantic Overview (Fisher et al., 2000b) reports the overall effect on major resources (such as coastal zones) or qualities (such as biodiversity or health status), using arrows to indicate positive or negative impact as well as the strength of impact. The summary analysis is given in three categories of certainty of conclusion (most certain, moderately certain, uncertain).


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The assessments described above all follow a general process of problem formulation and analysis common to many problem-solving endeavors. These include de®ning the problem to be addressed, collecting information about the issue, analyzing and synthesizing the information to reach a conclusion about the issue, and communicating the conclusion. In the above assessments, these general steps can be described in more detail: the problems to be addressed focused on characterizing the state of environmental stressors and ecosystems of interest; the characterization was bounded by de®ning what information would be acquired based on expert knowledge of system function and process; the assessments used both place-speci®c measurements and modeled data to extrapolate local measurements to response across a large, heterogeneous landscape; expert knowledge based on the state of science was used to assess whether there was cause for concern based on the data; and extensive information was collapsed into a minimal number of `messages' (either narratively or graphically conveyed).

A generalized framework Based on the similarities identi®ed above, a generalized process for assessment of ecological condition was developed (Fig. 1). The framework was intended to provide an orderly process for de®ning context and boundaries, developing an analytical approach, acquiring the necessary data and analyzing them, and interpreting the results. The process was also structured to make intuitive sense in a management context. The process contains ®ve steps. This section describes each step, including its purpose, the factors that were considered part of it, and its contribution to the overall assessment. Step 1: Identifying the questions The ®rst step is to de®ne the issue needing resolution, usually stated by a decision-maker or concerned citizen as a question. Hence the ®rst step is couched as ìdentifying the questions'. Usually, the ®rst-order question is `What is the condition of the environmental resource as a whole?' Step 1 is intended to identify a series of narrower issues within that broad question to focus the concerns of those who will use the assessment (hereafter `the user'). The product of this step is a list of more detailed issues, in the form of questions. The focus provided by this step is critical to the process

Figure 1. Proposed process for integrated assessment of ecological condition.

because it prioritizes the kinds of information that the user needs. As assessment questions are identi®ed, they increasingly de®ne, or circumscribe, the context and boundaries of the full assessment. Formulating the broad level concerns into a series of questions that can be answered also highlights the need to identify appropriate, scienti®cally valid surrogates of condition which will also have meaning to the user. Step 2: Choosing the appropriate metrics, methods, and scales The questions identi®ed in step 1 de®ne issues such as how susceptible the Pocomoke River is to outbreaks of P®steria or whether the population of striped bass in the Chesapeake Bay has dropped below sustainable limits. They do not deal with types of measurements or analysis. The purpose of step 2 is to determine how the questions will be answered by identifying the indicators and their metrics (standards of measurement) that are needed and the methods for analyzing the data and synthesizing the results.

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Quantities that can serve as indicators for evaluating a resource must be identi®ed and justi®ed so that at the end of an assessment, all parties agree the issue of concern has been addressed appropriately. The indicators and their metrics must have both a direct scienti®c relationship to the issue and a meaning for the user. The determination of which indicators and metrics to use must balance such factors as the economics of collecting data, the limitations of existing ecological databases, the ability to synthesize large amounts of data into useful information, and the relevance of various metrics to the issues at hand. The solution may be to use a combination of simple metrics such as temperature, salinity, and concentrations of nutrients in the water to determine how susceptible the river is to P®steria blooms. Alternatively, the answer might be derived from a numerical model, such as one that predicts (calculates) population dynamics from measured size-age class structure of striped bass. Additional issues that must be addressed include the appropriate scale at which to address the question, and the methods for relating different measurements to each other. The product of step 2 is a suite of measurements or modeled outputs that can address the assessment questions on the appropriate scales, and an approach for analyzing and interpreting the resulting data. Step 3: Identifying needs and availability of data Steps 2 and 3 often form an iterative sequence. After step 2 has identi®ed appropriate indicators and metrics, step 3 checks to see whether the available data for those metrics are of quality and spatial and temporal extent appropriate to answer the question. For example, when addressing the condition of submerged aquatic vegetation (SAV) in the Chesapeake Bay and evaluating whether it is improving or declining, it is necessary to have data on SAV for the entire Bay and over an extended period. Extrapolating from a single measure of SAV, say acreage at one time in one embayment, cannot properly represent the entire bay or its trends. If the data available for a metric do not meet the requirements, one might return to step 2 and select a different metric, or allow additional time to collect enough data to satisfy step 3. In returning to step 2, one might try secchi depth and concentration of total suspended solids (TSS) as surrogate measures for the condition of SAV, provided that a scienti®c relationship had been established between the

clarity of the water, as represented by secchi depth and TSS, and the vegetation, and that data for those metrics were available for multiple locations and multiple years. If no other scienti®cally-defensible surrogate could be found for SAV, a program to collect the necessary data might have to be established before the assessment question could be addressed satisfactorily. The number of iterations between steps 2 and 3 depends on the degree of uncertainty of assessment that the user is willing to accept. Usually, this is dependent on the economic and societal implications of the decision being made. It is at this stage, therefore, that the con®dence with which a question can be answered must be speci®ed. Users may accept the best available assessment for screening purposes, but wait until more de®nitive data have been collected when large economic or societal implications are involved. In either event, the product of step 3 is a set of data for the metrics and the indicators of condition that are suf®cient to answer the questions identi®ed in step 1. Step 4: Conduct assessment Step 4 performs the tasks identi®ed in steps 2 and 3. Thresholds to discriminate within gradients of condition are selected. The required data are collected or organized, analyzed, and the results synthesized to answer the questions. At this `nuts and bolts' stage, hidden issues of incompatibility or discrepancies among data sets, such as differing methods of collecting or processing data, or differences in threshold limits, often appear. For example, if one state uses information from satellites to categorize land cover and another uses aerial photographs, the results may differ. One jurisdiction may close shell®sh beds based on counts of fecal coliform at the site, another on rainfall in the general area. Differences in data must be considered relative to the uncertainties acceptable for the assessment and by using protocols and decision criteria that are consistent with the use of the assessment. Based on this evaluation, iteration may again be required when incompatibilities emerge. The end product of step 4 is the actual assessment of regional environmental condition. Step 5: Communicating the results Finally, the results must be communicated in a way that will allow the user to agree that the issues have been addressed well enough that their answers can be used for their intended purposes. Rather than


simply listing or summarizing all information collected, the assessment must synthesize the answers to the questions being asked in such a way that the user will easily grasp its `take-home' message. The results must also clearly present the uncertainties of the assessment. The product of step 5 is, hopefully, the user's understanding of the answers to the questions and the validity and usefulness of the assessment.

Application of the framework The Mid-Atlantic Integrated Assessment (MAIA) began in 1995 as a partnership between USEPA's Region III and Of®ce of Research and Development (ORD). MAIA was envisioned as a way to provide regional managers with sound scienti®c estimates of ecological condition that would inform their environmental management decisions. MAIA was also intended to be a test bed to re®ne the monitoring designs and assessment methods of the Environmental Monitoring and Assessment Program (Holland and DeMoss, 1996). One of objectives of the MAIA program was to complete a series of `state of the resource' reports that describe the conditions of important natural resources within the region (shown in Fig. 2). The general framework described above was used to complete the ®rst condition report. The Condition of the Mid Atlantic Estuaries (USEPA, 1998a) reported on 18 endpoints using information from existing summaries and large datasets to characterize the ecological condition of the region's estuaries. The summary analysis assigned colors to the value of each indicator (as determined by comparing the regional value to a prede®ned criteria or threshold) to convey the overall sense of the condition of each resource in the region (Paul et al., 2000). Narrative statements were also included qualitatively linking stressors and effects. Speci®cs of applying each step in the framework in the MAIA case study are described below. Step 1: Identifying the assessment questions A list of assessment questions to evaluate how effectively the MAIA estuaries were being managed and for setting priorities for further research and action was identi®ed through a series of workshops with representatives from state and Federal agencies in the MAIA region. The full list of questions is shown in the Appendix. Participants in the workshop

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recommended that, in order to meet the purposes of the MAIA program, a report answering those questions should target environmental managers and the educated lay public and summarize indicators of ecological and biological condition in a simple, straightforward way rather than in detailed scienti®c report. It should be noted, however, that the workshops did not include participants from either environmental managers at the local scale, or representatives of the public, and did not, therefore, give emphasis to more site-speci®c questions. Step 2: Identifying appropriate metrics, methods, and scales The original list of assessment questions identi®ed various indicators and metrics for exposure and effect thus combining step 2 with step 1. However, no criteria were de®ned for level of certainty or appropriate scale at which to gather information on those indicators for the intended purpose. The consequent ambiguities in implementing this step would later cause confusion. However, it was not until attempts were made to complete subsequent steps that the need to reiterate steps 1 and 2 was identi®ed. Step 3: Identifying data needed and its availability As a test assessment of regional condition, the MAIA estuaries assessment was based on existing data and analyses, neither collecting new data nor reanalyzing old. Scientists collected reports and inventoried information to see which assessment questions could be answered with this boundary condition. For example, `What fraction of estuarine water is in large estuaries, in small estuaries, and in tidal rivers?' could be answered from existing EMAP reports. But `How much area contains physical habitat that is suitable for shell®sh beds or ®sh (by species of interest and a variety of physical indicators)?' would require much new data and analysis. `How is biotic integrity associated with different types of estuaries?' also could not be addressed because there is currently no generally accepted or widely collected measure of estuarine biotic integrity. Because of the limitations on type and extent of data, scientists and managers agreed to address the overaching management issues identi®ed in the original assessment questions with 18 ìndicators of condition' shown in Table 2. The ®nal suite of metrics is listed in the last column of Table 2. However, answers to many of the questions,

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Figure 2.

Region of study for the Mid-Atlantic integrated assessment.

particularly those on conditions of living resources, eventually had to be supplemented with narrative descriptions due to gaps in available data. It should also be noted that at this stage steps 1 and 2 (identifying the issues and appropriate indicators) were being iterated and re®ned. Step 4: Assessing the estuaries Information for each metric was summarized based on existing reports and data. To assess the condition the estuaries, the determination was made to select

thresholds to discriminate between `good' and `bad' values. These thresholds, where possible, were based on regulatory criteria or on peer-reviewed measures of effect. In some cases, management goals had been determined absent these criteria (e.g., SAV restoration goals in the Chesapeake Bay); where appropriate these values were used. With this constraint, it was necessary to revisit the methods for aggregating and analyzing the indicators and their metrics, especially those that did not have comprehensive spatial coverage or consistent criteria in a single data set. For example, contaminants in ®sh and shell®sh were proposed as indicators of


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Table 2. Listing of the management issues, indicators, and metrics selected for the Mid-Atlantic Condition of the estuaries assessment Management issue

Indicator

Metric

Description of estuaries

Watershed land cover Vertical strati®cation Salinity Water clarity

% area in 4 land cover categories Sigma-t Distribution of salinity Attenuation coef®cient

Water quality

Nutrients Phytoplankton Dissolved oxygen

Concentration of dissolved inorganic phosphate and dissolved inorganic nitrogen Concentration of chlorophyll a Concentration of dissolved oxygen

Sediment contamination

Toxic contaminants

ER-L/TELs; ER-M/PELs (Long et al., 1995)

Habitat change

Wetlands Submerged aquatic vegetation

Number of acres of wetlands Number of acres of SAV

Condition of living resources

Benthic condition

CB benthic restoration goal index, EMAP benthic index Annual numbers of oysters harvested and of crabs harvested Shell®sh closures as percent of productive acreage; shell®sh closure areas in 1997 Striped bass: juvenile population index American shad: #s landed White perch: juvenile index Drum: trawl catch Summer ¯ounder: trawl catch Fish consumption advisories Shell®sh tissue residues Number of ®sh pathologies

Shell®sh harvest Shell®sh closures Fish stocks

Contaminants in ®sh & shell®sh Incidence of disease in ®sh &shell®sh Waterfowl

Threatened & endangered species

the condition of living resources. Because no single data set for contaminants in ®sh or shell®sh covered the entire MAIA area, the scientists opted to use selected state advisories on consumption of ®sh and shell®sh as indicators of levels of contamination in ®sh that were high enough to impair the resource. Although the states calculated their advisory levels in different ways, each level was based on concentrations of pollutants in the ®sh or shell®sh meant to protect human health. The scientists therefore used the advisories to highlight areas of concern rather than to compare levels of contaminants quantitatively, as had been originally hoped. This

Mid-winter survey counts: Mallards & black ducks Canada geese Overall waterfowl Trends from database of endangered species: Bald eagle Peregrine falcon Piping plover Kemp's ridley turtle Shortnose sturgeon

is also an example of how using the same indicators from different sources of data may require the uncertainties of each to be explained carefully if the data are to be used properly. Step 5: Communicating the results of the assessment The analyses and conclusions were communicated in the ®nal report, Condition of the Mid-Atlantic Estuaries (USEPA, 1998a). During preparation and review of the report, a number of decisions were

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Figure 3. Sediment contamination distribution across Mid-Atlantic estuaries expressed as risks to aquatic organisms. Map depicts spatial distribution derived from multiple sources of information. Bar graph shows percent area derived from EPA EMAP 1990±93 data (USEPA, 1998a).

made to improve the effectiveness of communication: Data summaries would be conveyed primarily as maps and graphs (Fig. 3 is one example). The scienti®c basis for the thresholds would be provided in a brief technical appendix to the report. As much information as possible would be conveyed for the entire region and the major estuaries. Results for individual indicators would be summarized in a single table so as to convey the overall condition of MAIA's estuaries (Fig. 4). The report used a consistent format for presenting the indicators (which included context in the report explaining why the indicators were important), evaluated the values of the indicators relative to thresholds (by using terms such as `potential risk', `minimal risk', or `no risk' on the main maps), and extrapolated information based on best professional judgement, rather than simple displays of collected data (provided by showing continuous color on the maps, as opposed to point data). Review and revisions by the managers as well as by outside scienti®c peer reviewers led to the desired productÐa synthesis of available environmental information that provided an overall `scoping' assessment of the condition of MAIA's estuaries.

Discussion The Condition of the Mid-Atlantic Estuaries report emphasized the importance of a structured process for conducting integrated regional assessments, which typically try to synthesize large amounts of diverse information to help evaluate priorities and target appropriate actions by management. The complexity of ecological systems and the large amounts of data to be synthesized make it easy to lose sight of an assessment's purpose, extent, and desired product. The process that MAIA used ultimately provided a means to ensure that its assessment remained focused. However, the iterations served to highlight a number of areas that need special attention when exercising the framework: The importance of a detailed understanding of the assessment's purpose and how it should affect the formulation of the questions became very apparent. It was clear from the beginning that MAIA's assessment was intended to be used by management to help protect the environment. It was also clear that the assessment would focus on the regional scale, as opposed to the local or national scale. However, it was not clear speci®cally how management would use this information. The detail of the


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Figure 4. Summary of ecological conditions across the Mid-Atlantic estuaries. Shades represent best estimate of problems based upon information presented in USEPA (1998); clear for minimal or no problem, grey for moderate problem, and dark for problem. Cross-hatching indicates inadequate information available. Where multiple shades are shown, best estimate is that condition ranges between the two categories (USEPA, 1998a).

original assessment questions implied that management intended to use the results of the assessment to take speci®c actions aimed at managing speci®c problems. But the aggregation (and resulting loss of detail) necessary to supply regional answers prevented the information from being used to develop speci®c remediation actions. It was rather used in the end by regional managers to con®rm, scope or prioritize broad-scale environmental problems. Local entities have used the information to set a context for the scale of problem which they are trying to address (i.e., whether the actions they take will be effective, or whether the problem must be addressed at a scale larger than their jurisdiction). Previous assessments focused on providing information about the condition of the environment at scales not previously addressed, without trying to provide information which would allow design of speci®c actions at the local scale. In some cases, this was an explicit decision. For example, MARA's goal was to provide information about how the climate might change within a speci®c region (Fisher et al., 2000b). Little information had previously been available at the regional scale, as most climate

change models focused on predicting global scale effects. EMAP was designed to improve the de®nition of the extent and magnitude of pollution problems at regional and national scales (Paul et al., 1999). Prior to implementation of the EMAP program, monitoring over large geographic regions had been performed by multiple entities using different indicators, methods and sampling designs, limiting aggregation and interpretation of the data collected. It was unclear which groups would use the assessment. As MAIA is a partnership between USEPA ORD and Region III, Region III was originally expected to be the primary user. However, neither entity had the authority to implement many of the management actions needed to protect or restore the environment, largely because what was necessary would be the sum of local actions not within the USEPA's jurisdiction. A continuing question while the Condition of the Mid-Atlantic Estuaries report was being developed was which decisions MAIA was trying to in¯uence. Although MAIA had decided to

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focus on providing state and USEPA managers with highly aggregated data that would help them consider higher-level management issues, discussions during the MAIA Working Conference (Bradley et al., 2000) reemphasized the local needs. Many participants stated that the regional information was too broad to help them in their practical decision-making. This illustrates the complicating effect of the multiplicity of scales operating concurrently in the complex, interconnected systems that are to be assessed regionally. Although the problems identi®ed in the Condition of the Mid Atlantic Estuaries must be solved regionally, the current US governmental framework gives emphasis to local decision making. Thus, regional problem-solving requires local governments, which have their own priorities and constraints, to work together. The reconciliation of these competing priorities to address regional scale problems effectively must be accomplished through negotiation and collaboration. Some of the previous assessments, such as NAPAP, were speci®cally designed to provide information to national policy makers, and did not address multiple levels of decision making. The Chesapeake Bay Program effectively addresses the issue by consciously serving as a facilitator for decision-making among the multiple entities with responsibility for the Chesapeake Bay ecosystem. The CBP uses the monitoring data on trends, communicated through such methods as the State of the Chesapeake Bay (CBP, 1999), to identify problems and evaluate the effectiveness of previous management decisions, thus helping to focus the discussion on restoration of the Bay. MARA utilized an extensive stakeholder identi®cation and involvement program to identify the issues of concern. At this early stage, it remains unclear how those stakeholders will use the information which has been provided, or what further role MARA will play in facilitating interactions among the stakeholders. Appropriate data were lacking. Although monitoring by Federal, state and private organizations has generated much data, the methods and measures used by different programs are different enough to greatly complicate the assessment process (Messer et al., 1991). The lack of a framework for combining data across monitoring networks only worsens the situation. One fortuitous result of MAIA's partnership was that it found many more data sets than had been anticipated. Although issues of comparability remained, part of the information could often be usefully synthesized, as described above in step 4 on ®sh consumption advisories. This allowed a better

understanding of the condition of the biota in MAIA than had been anticipated. The scarcity of biological data still limits the number of biological indicators that can be used in regional assessments, however. Distant surrogates for actual issues were often required in MAIA, such as ®sh-consumption advisories rather than actual data on effects of eating contaminated ®sh. In addition, because many of these data are for lower levels of biological organization (e.g., populations of single resources like striped bass), it becomes necessary to extrapolate effects on communities and ecosystems from effects on single species even though there is still no generally accepted method for doing so. Because actions by management can be no better than the surrogates and extrapolations on which they are based, there remains large uncertainty that the actions taken will improve resource condition. The CBP, EMAP, and the National Eutrophication Survey chose to collect their own data for their purposes to circumvent the problem of inconsistent, incompatible data. However, MARA and the Waquoit Bay problem formulation effort, in using existing data sets, acknowledged the uncertainties introduced into the conclusions by this issue. All assessments struggled with the lack of data on higher levels of biological organization. It remains a challenge to synthesize large amounts of data into information that is easily communicated. Managers of complex ecosystems need multiple levels of information, provided in ways which will allow nonspecialists to understand the overall condition of the environment and to make informed decisions to improve it (Karr and Chu, 1997). The assessment process identi®es relevant indicators, measures them, evaluates them against expectations, and interprets the results. One issue is the large number of parameters for which regional assessments need data and interpretation. It may be possible to identify concentrations of stressors that are known to cause effects to individual organisms. However, these `threshold' levels are not well understood at community and ecosystem levels, nor is the importance of different effects to the overall condition of the system clearly de®ned. Thus, it remains dif®cult to evaluate measures of effect on communities against expectations. Additionally, information about multiple measures must be aggregated or synthesized to allow users to separate signals from noise. Various methods could be used for this. The Condition of the Mid-Atlantic Estuaries conveyed the overall condition of the resource by using a color-coded


matrix of only a few parameters, which made it easier for users to determine their own sense of the overall condition by weighting the issues of concern in their own ways. Karr and Chu (1997) advocated using multimetric indices to interpret monitoring data in biological assessments, which was the method used in the National Eutrophication Study. NAPAP (1991) characterized current and future emissions and environmental responses, but did not assign values of good or bad to particular measures. Instead, it de®ned the environmental responses and economic costs of various scenarios that were based on particular technological management actions. It is unclear whether any one of these methods was more effective in conveying the `bottom-line' message. However, it was noted several times during the MAIA Working Conference (Bradley et al., 2000) that in order to understand what to do about a problem, it was necessary to disaggregate and analyze the data further. It may therefore be inferred that the level of synthesis and method of communicating the results should be a function of the question being asked and that providing several levels of detail would aid in meeting the multiple needs in a regional context.

Management implications The assessment framework proved useful in structuring the process of synthesizing large amounts of diverse information to help evaluate priorities and target appropriate actions by management in the Mid Atlantic estuaries. However, the issues highlighted above have implications for management of the environment which can not be solved simply by an effective assessment process. The confusion on the use of the assessment directs attention to the institutional impediments contained in the US's current environmental management structure. On a regional scale, there are a myriad of entities which have responsibility for individual actions which affect the environment. All the information in the world will not suf®ce to stimulate collaboration among those entities; emphasis must be paid to facilitating that interaction and the negotiations necessary for effective solutions. The critical need for this kind of facilitation has been recognized in a number of issuespeci®c areas, most notably in the use of Compact Commissions of major river basins to distribute water quantity equitably between states (e.g., the Rio Grande Compact Commission) and in the use of

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special agreements for remediation of water quality problems (e.g., agreements to limit nutrient loads in the Chesapeake Bay and the Mississippi River). Recent initiatives in the Federal government have emphasized the need to seek solutions that address the various causes of problems and understand the interrelationships between human behavior and pollution. The USEPA's Community-Based Environmental Protection initiative places problem solving responsibility with stakeholders and local governments, trying to facilitate holistic, placebased solutions in such venues as the Great Lakes. As another example, the President's multi-agency Committee on the Environment and Natural Resources (CENR) provides a formal mechanism for interagency coordination on environmental and natural resources issues. The institutional problem of integrating the many environmental monitoring networks to provide data which can be aggregated and compared has been well-recognized (National Science and Technology Council, 1997). The CENR proposed a framework for integrating monitoring networks. There have been various efforts to integrate disparate monitoring programs, in both guidance, such as EPA's Consolidated Assessment and Listing Methodology for the environmental monitoring required of US states (Margarete Heber, personal communication), and in demonstration projects, such as the MAIA Estuaries Integrated Monitoring project (USEPA, 1998b). The need for more such efforts continues. The effectiveness of the synthesis and communication of condition to the many interested individuals in a large region is multi-faceted, and depends on the intent of the communication, whether it be education, scoping or design of solutions. An understanding of the magnitude and importance of a problem may require a high degree of aggregation and conceptualization to communicate, while a detailed design of a particular management action in a particular place may require a high degree of detailed information and quantitative analysis. However, it is extremely hard to gage whether an assessment has `correctly' evaluated environmental condition for the purpose at hand, whether the assessment provided information that resulted in `better' environmental management, or whether it re¯ected the issues of concern of àll' stakeholders. Continued research is needed on measures which can be used to evaluate whether an assessment has been effective in these areas. In summary, the generalized framework for large scale assessments proved useful in organizing data and focusing the assessment in the MAIA estuaries.

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However, many challenges, both technical and institutional, remain to be addressed.

Acknowledgements The authors extend their thanks to the MAIA Team in Ft. Meade, Maryland, the authors of the Condition of the Mid-Atlantic Estuaries, and the partners and collaborators who helped develop the report. We thank D. Campbell, W. Nelson, C. Strobel and three anonymous individuals for reviewing and improving the manuscript. Although the research described in this paper has been funded wholly by the US Environmental Protection Agency, it has not been subjected to Agency-level review. Therefore, it does not necessarily re¯ect the views of the Agency. This paper is Contribution No. AED-99-2084 of the US EPA's National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division.

References Bradley, M. P., Brown, B. S., Hale, S. S., Kutz, R. W., Landy, R. B., Shedlock, R., Mangold, R., Morris, A., Galloway, W., Rosen, J. S., Pepino, R. and Wiersma, B. (2000). Summary of the MAIA Working Conference. Environmental Monitoring and Assessment 63, 15±29. Bricker, S. B., Clement, C. G., Pirhalla, D. E., Orlando, S. P. and Farrow, D. R. G. (1999). National Estuarine Eutrophication Assessment: A Summary of Conditions, Historical Trends, and Future Outlook. National Oceanic and Atmospheric Administration, Silver Spring, MD. Chesapeake Bay Program (1999). The State of the Chesapeake Bay. CBP/TRS 222/108, Annapolis, MD. Fisher, A., Neff, R. and Barron, E. J. (2000a). The Mid Atlantic Regional Assessment: motivation and approach. Climate Research 14, 153±159. Fisher, A., Abler, D., Barron, E., Bord, R., Crane, R., DeWalle, D., Knight, C. G., Najjar, R., Nizeyimana, E., O'Connor, R., Rose, A., Shortle, J. and Yarnal, B. (2000b). Preparing for a Changing Climate: The Potential Consequences of Climate Variability and ChangeÐMid Atlantic Overview. Pennsylvania State University, University Park, PA. Holland, M. M. and DeMoss, T. B. (1996). The MidAtlantic Integrated Assessment: focus on process. In North American Workshop on Monitoring for Ecological Assessment of Terrestrial and Aquatic Ecosystems, (C.A. Bravo ed.), pp. 194±211, General Technical Report RM-GTR-284, US Department of Agriculture,

Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, Colorado 80526. Karr, J. R. and Chu, E. W. (1997). Biological Monitoring and Assessment: Using Multimetric Indexes Effectively. EPA/235/R-97/001, University of Washington, Seattle. Long, E. R., MacDonald, D. D., Smith, S. L. and Calder, F. D. (1995). Incidence of adverse biological effects within ranges of chemical concentration in marine and estuarine sediments. Environmental Management 19, 81±97. Messer, J. J., Linthurst, R. A. and Overton, W. S. (1991). An EPA program for monitoring ecological status and trends. Environmental Monitoring and Assessment 17, 67±78. National Acid Precipitation Assessment Program (NAPAP). (1991). 1990 Integrated Assessment Report. Of®ce of the Director, NAPAP, Washington, DC. National Research Council. (1995). Science, Policy, and the Coast: Improving Decisionmaking. National Academy Press, Washington, DC. National Research Council. (1997). Building a Foundation for Sound Environmental Decisions. National Academy Press, Washington, DC. National Science and Technology Council. (1997). Integrating the Nation's Environmental Monitoring and Research Networks and ProgramsÐA Proposed Framework. Of®ce of Science and Technology Policy, Washington, DC. Paul, J. F., Gentile, J. H., Scott, K. J., Schimmel, S. C., Campbell, D. E. and Latimer, R. W. (1999). EMAPVirginian Province Four-Year Assessment Report (1990±93). EPA 600/R-99/004. US Environmental Protection Agency, Of®ce of Research and Development, Washington, DC. Paul, J. F., Kiddon, J. A., Strobel, C. J., Melzian, B. D., Latimer, J. S., Cobb, D. J., Campbell, D. E. and Brown, B. S. (2000). Condition of the Mid-Atlantic Estuaries: production of a state of the environment report. Environmental Monitoring and Asssessment 63, 115±129. Public Law 70-560, section 308. (1927). River and Harbor Act of 1928. Public Law 91-190, section 102. (1970). National Environmental Policy Act of 1969. US Environmental Protection Agency. (1992). Framework for Ecological Risk Assessment. EPA/630/R-92/ 001. Risk Assessment Forum, Washington, DC. US Environmental Protection Agency. (1998a). Condition of the Mid-Atlantic Estuaries. EPA/600/R-98/147, Washington, DC. US Environmental Protection Agency. (1998b). National Water Quality Inventory: 1996 Report to Congress. EPA/841/R-97/008, Washington, DC. US Environmental Protection Agency. (2000). Toward Integrated Environmental Decision-Making. EPA-SABEC-00-011, Science Advisory Board, Washington, DC.


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Appendix MAIA assessment questions Category-physical characteristics What is the estimated area of estuarine waters in MAIA? What is the estimated area of estuarine waters in MAIA by State? What percent of estuarine waters are in large estuaries? small estuaries? tidal rivers? How much acreage do we have in estuaries? How much acreage do we have in individual systems and total in region? How much acreage do we have in types of systems (barrier island, drowned river valleys)? How much acreage do we have in types of habitats (oyster bed, etc)? How much acreage of shell®sh beds are there in the region?

Category-chemical attributes What are the distributions TP, NO3 and NH3 concentrations in estuaries in MAIA, states?

Category-biological attributes: ®sh What % of estuarine area had ®sh with observed abnormalities? Are the shell®sh abundant and safe to eat? What is the temporal trend for the acreage of shell®sh beds? How much non-inhabitated acreage has suitable physical habitat for shell®sh beds? Suitable physical habitat to be de®ned for each species of interest using salinity, temperature, substrate, depth and similar parameters? Of the acreage that is currently non-inhabitated, what % has low dissolved oxygen concentrations? Of the acreage that is currently non-inhabitated, what % has contaminants above some threshold? Of the acreage that is currently non-inhabitated, what % represent former ®shing grounds? Of the acreage that is currently non-inhabitated, what % overlap with known disease distributions? What is the condition of shell®sh beds? What proportion of shell®sh beds (acreage) is closed due to management actions? What condition prompted that management action? ÐWhat ÐWhat ÐWhat ÐWhat

proportion proportion proportion proportion

of of of of

shell®sh shell®sh shell®sh shell®sh

beds beds beds beds

is is is is

closed closed closed closed

due due due due

to to to to

fecal coliform contamination? proximity to known point source discharges? proximity to marinas? chemical contamination?

What is the acreage of shell®sh with chemical concentrations above critical levels, above FDA limits for human consumption, or some ecologically relevant concentrations, such as Long et al. (1995) ER-L, ER-M? What is the acreage of shell®sh with coliform above some critical level? What is the acreage of shell®sh with diseases such as DERMO, MSX? What percent of acres have healthy shell®sh beds, as measured by growth? What percent of acres have healthy shell®sh beds, as measured by age distribution? What percent of acres have healthy shell®sh beds, as measured by density (abundance and biomass)? What percent of the shell®sh beds occurs within 1 km of a National Pollutant Discharge Elimination System pipe: and what % are healthy?

Category-biological attributes: ®shability What % of estuarine area have detectable ®sh tissue contaminant residue levels? What is the size distribution of game®sh species (number of ®sh in each size class) in MAIA?

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Category-biological attributes: benthos What is the distribution of the total number of benthic species/site in estuaries? What is the distribution of species richness?

Category-landscape characteristics What % of estuaries have point sources in the watershed? What % of watersheds have had pesticide or nutrient applications in the watershed? What % of estuaries receive direct storm water discharge? Is the shoreline being overdeveloped? How much coastline is there in MAIA? How much coastline is of habitat types of interest (beach, wetland, bulkhead, etc.)? What other habitat types are of interest? How much coastline is privately owned for each habitat type of interest? What % of ocean coastline is developed? (How to de®ne developed?) What % of estuaries receive measurable amounts of wet and dry air deposition? (NOX, SO2, Ozone)

Category-non-consumptive use Are the waters safe to swim in? What proportion of shoreline miles is swimmable? What number of shoreline miles are closed to swimming? Are areas closed to swimming for reasons other than fecal coliform contamination? Water quality standards are being exceeded in what proportion of total habitat area?ÐExisting water quality standards address dissolved oxygen concentrations, turbidity, toxics, bacterial concentrations, and biodiversity.

Category-productivity for consumptive use Is the abundance of target species decreasing? Is the mean ®sh size of target species decreasing? What % of estuarine area serves as an effective reproductive and/or development habitat for target species? What proportion of estuarine area has ®sh with pathology X at frequency Y? What proportion of ®sh/shell®sh has edible tissue with contaminant X exceeding criterion Y? What proportion of ®sh/shell®sh stocks has an unacceptable condition?

Category-biotic integrity What proportion of the estuarine area has unacceptable biotic integrity? What proportion of estuarine area has unacceptable benthic community structure? Is there a declining number of benthic species or benthic biodiversity as evidenced by evaluation trends? What proportion of estuarine area has unacceptable ®sh assemblage structure? Is there a declining number of ®n®sh species or a decline in total ®sh abundance as evidenced by evaluating trends? What proportion of ®sh display external pathological conditions? What proportion of estuarine area has ®sh/shell®sh with levels of biomarker X concentration Y? What proportion of estuarine area has ®sh with body burdens of contaminant X at concentrations greater than Y? Does the coastline support indigenous biological populations?Ðturtles, for example What are the trends for ®sheries landings for the estuaries in MAIA?


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Category-habitat integrity What proportion of estuarine area is eutrophic? What proportion of estuarine area is hypoxic/anoxic? What proportion of estuarine area has unacceptable levels of total organic carbon in sediments? What is the total acreage of estuarine wetlands and SAV? Is the total acreage of unique wetland and SAV habitats decreasing? What proportion of each unique habitat type has unacceptable condition? Utilizing the Chesapeake Bay program's indicator criteria for SAV health and abundance, what % of estuarine areas are robust?

Category-system function What % of estuarine area in MAIA has degraded system functioning based on measures of hydrology, nutrient cycling and energy transfer?

Category-biological resource stressor What % of estuarine area with degraded biotic integrity are associated with acidic deposition? What % of estuarine area with degraded biotic integrity are associated with eutrophication? What % of estuarine area with degraded biotic integrity are associated with habitat degradation? What % of estuarine area with degraded biotic integrity are associated with exotics? What % of estuarine area with degraded biotic integrity are associated with toxics? What % of estuarine area with degraded biotic integrity are associated with trash? What % of estuarine area with degraded biotic integrity are associated with speci®c chemical stressors such as metals (Zn, Cr. Cd), organics (TCDD, PCB's, etc.)? What is the association of biotic integrity with different estuary types? What are potential recovery times for degraded systems following improvement? What is the relationship between habitat quality/quantity and abundance of ®sh species? What is the relationship between DO and biological integrity (or number of each species) in degraded estuarine areas? Which anthropogenic stressors can be linked to observed impacts? Where toxic contamination is absent, is physical habitat the most important factor affecting abundance and richness of benthos and ®sh?

Category-biological resource-landscape What % of estuarine area with degraded biotic integrity are associated with % agricultural till/no-till? What % of estuarine area with degraded biotic integrity are associated with % ForestÐForest mgt. practices (clear-cutting/selective)? What % of estuarine area with degraded biotic integrity are associated with erosion potential? What % of estuarine area with degraded biotic integrity are associated with % urban? What % of estuarine area with degraded biotic integrity are associated with interaction among stressorland use-biotic responses? What % of estuarine area in MAIA, states with degraded biotic integrity are associated with landscape indices such as connectivity, shape-complexity, dominance? What changes have occurred in the % estuarine area with degraded biotic integrity that are associated with changes in landscape indices? 1970±1980±1990. What % of estuarine area in MAIA have degraded biotic integrity that is associated with indicators of condition from other EMAP/REMAP resources (e.g., forest canopy index, agricultural lands erosion potential indices)? Which speci®c waters have unexplained impacts? Is there some critical level of watershed land use (e.g., forest 5 0%) after which poor benthos is expected?