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Appendix E Monitoring and Assessment Plan
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MARCH 29, 2001 MONITORING AND ASSESSMENT PLAN COMPREHENSIVE EVERGLADES RESTORATION PLAN COMPREHENSIVE EVERGLADE RESTORATION PLAN U.S. Army Corps of Engineers Jacksonville District South Florida Water Management District
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Comprehensive Everglades Restoration Plan Monitoring and Assessment Plan Table of Contents Section I. Introduction and Background 1. Purpose of the Monitoring and Assessment Plan 2. What are Monitoring and Assessment? 3. What should be Monitored? In General AET/Restudy Conceptual Ecological Models Water Quality Selection of Performance Measures for this Plan 4. Monitoring and Assessment Plan Design Strategy 5. How are Monitoring Data Managed and Analyzed? 6. How are Monitoring Data used to assess CERP Performance? 7. Implementation of the Plan 8. Uncertainties in System Responses 9. Perspectives on Successful Restoration 10. Adaptive Assessment Team Editorial Team Members Section II.Conceptual Ecological Models Section III. Monitoring Parameters and Performance Measure Documentation Sheets Section IV. Research Needs in Support of the CERP Monitoring and Assessment Plan Section V. Annual Spread Sheets for Tracking Monitoring Appendix A. Indicator Region Maps
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I. Introduction and Background The Comprehensive Everglades Restoration Plan (CERP) monitoring and assessment plan is a product of an interagency, interdisciplinary team known as Restoration Coordination and Verification (RECOVER). The Adaptive Assessment Team (AAT) of RECOVER has the lead responsibility for creating the monitoring and assessment plan, and for conducting an on-going review of how well it is working. In addition, the AAT has the responsibility to use the information that is provided by the monitoring program to assess system responses, as a basis for recommending improvements in the restoration plan where needed. Overall, the RECOVER Leadership Group holds accountability for the CERP monitoring and assessment program within RECOVER. (1) Purpose of the Monitoring and Assessment Plan The primary purpose of this monitoring and assessment plan is to identify and describe the performance measures and parameters of the natural and human systems in south Florida that should be measured in order to determine the success of the CERP. The goal is to create a single, integrated, system-wide monitoring and assessment program that will be used and supported by all participating agencies as the means for tracking and measuring the success of the Comprehensive Plan. This document identifies the specific set of physical and biological performance measures that should be monitored, the geographic regions where these measures should be monitored, and the improvements in these measures that should occur during and following the implementation of the Comprehensive Plan. Collectively these measures will serve as indicators of the overall health of natural and human systems in south Florida, relative to the objectives of CERP. This monitoring and assessment program is required as a basis for determining whether CERP achieves these objectives (i.e., the recovery of healthy and sustainable ecosystems throughout south Florida and an improved environment for people), and to support an adaptive assessment process for refining and improving the design and operation of CERP throughout its implementation. This is a system-wide monitoring and assessment program, designed solely for assessing how well CERP meets the system-wide objectives of ecosystem restoration and water supply. Each CERP project will develop a separate, local monitoring plan to assess the success of the individual project. To ensure that measures and targets selected by the project teams are consistent with system-wide measures, each project team should review this system-wide plan. As a prerequisite to the implementation of the CERP monitoring and assessment plan, RECOVER is preparing four additional planning documents that will substantially expand upon the summaries provided below. These are: an integrated and standardized system-wide sampling design and data management protocol for the monitoring plan (subsection 4); an adaptive assessment strategy explaining how the AAT will use the monitoring data to conduct annual assessments of system-wide responses (subsection 6);
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a detailed monitoring plan implementation strategy (subsection 7); and a research needs document in support of the monitoring and assessment plan (Section IV). In addition to these four planning documents, RECOVER prepares (and revises annually) a Program Management Plan. This management plan describes the tasks and responsibilities for all South Florida Water Management District and U.S. Army Corps of Engineers activities pertaining to RECOVER for a three-year planning period. The RECOVER management plan includes a budget for all monitoring and assessment tasks. The CERP monitoring and assessment plan is organized into five sections. Section I, the Introduction and Background, provides a broad overview of the purpose of the monitoring plan, how it was created, and how it should be applied. Section II contains the narrative descriptions and flow diagrams for the set of nine conceptual ecological models that provide the technical foundation for most of the natural system performance measures that have been incorporated into the monitoring plan. Section III contains the technical documentation sheets for each of the CERP performance measures that make up the monitoring plan. This section includes a description of the process used to develop and screen the biologic, hydrologic, and water quality performance measures comprising the CERP monitoring and assessment plan. These documentation sheets identify the specific parameters of the natural and human systems that are to be monitored, the geographic region where each is to be monitored, and the restoration targets for each. Section IV is a summary of the uncertainties associated with the hypotheses in the ecological conceptual models and a recommendation for research needs in support of CERP. The research listing identifies studies needed to reduce uncertainties in the model hypotheses in order to improve the ability of RECOVER teams to predict and interpret system responses. Section V is a set of spreadsheets, to be revised annually, for purposes of tracking the status of each element in the monitoring plan.1 Additional information on the content of each section is provided in the introductory paragraphs for each of the subsequent sections. Specific monitoring protocols, i.e., how the elements should be monitored individually and collectively, will be determined through consultation with the agency(s) or organizations responsible for implementing the data management program and the elements of the monitoring plan as well as outside consultants. The content and adequacy of the CERP monitoring and assessment plan will be regularly reviewed by the AAT and the full RECOVER team, by all participating agencies, and by independent reviewers. Changes in the monitoring and assessment plan will be approved by the AAT. During the initial reviews of the monitoring plan the number and focus of the performance measures may be revised, due to on-going efforts to maximize the efficiency and coverage of the monitoring effort, while at the same time attempting to settle on the smallest number of measures necessary to track system-wide responses to CERP. As part of this initial review, the AAT will continue to examine the biological performance measures that are contained in this draft. The objective of this continuing review is to insure that the biological measures have been carefully selected and designed to effectively track responses by the components of the key restoration hypotheses 1 Note that this section is not included in this review draft of the monitoring and assessment plan.
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contained in the conceptual ecological models. However, once the initial monitoring and assessment plan is reviewed and approved, it is not expected that large-scale changes will occur or would be desirable. (2) What are Monitoring and Assessment? Monitoring and assessment are critical components in the CERP adaptive assessment protocol and as such, merit clear definitions. Monitoring is the systematic process of collecting and storing data related to particular natural and human systems at some specified locations and times. Assessment is the process whereby monitoring data are interpreted in the context of particular questions and issues, such as tracking progress towards certain restoration objectives. Assessment also includes the development of statistical relationships from the monitoring data, other model development and application, and cause-effect research linked directly to the objectives of the restoration program. Monitoring can be used to document the status and trends of elements within the ecosystem over a range of temporal and spatial scales, and provide feedback that can be used to assess whether the predicted results are being achieved. It also provides information that can be used to help refine or modify actions to ensure that the targets for the project are being met. When applied to natural ecosystems where maintenance in their current condition is desired, monitoring can be used to evaluate whether there are aspects of the ecosystem that are varying beyond what would be expected under the influence of natural processes. When monitoring is applied to disturbed ecosystems that are being restored, monitoring can be used to evaluate whether the ecosystem is moving in the desired direction. Monitoring can also determine when the ecosystem has moved within the bounds of what is defined as the restored condition. It is important to be aware that rates of change, and thus the time required to document them, are often very different depending on the element being measured. Site history, landscape setting, the kind, degree, and direction of change, the potential rates of change for each parameter, and the level of applied effort in restoration projects can all affect rates of change. Restoration of some disturbed ecosystems can only be considered in geologic time frames because of the degree of disturbance that has occurred on these sites. In addition, other aspects of the South Florida ecosystem, including both restoration and development activities, will inevitably be changing at the same time, further complicating the ability to assess the success of the individual restoration components. It is essential that these differences in rates of change be factored into the assessments of environmental responses. In the context of RECOVER, monitoring has been defined in an adaptive assessment strategy (An Adaptive Assessment Strategy for the Comprehensive Everglades Restoration Plan; AAT, 2000) as having four objectives: Establish base-line variability for each of the performance measures; Determine the status and trends among the performance measures;
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Detect unexpected responses for components or measures of the ecosystem that have not been specifically identified as CERP performance measures; and Cause-and-effect scientific investigations designed to increase ecosystem understanding, particularly if restoration implementation yields unanticipated results. Addressing these objectives will allow the determination of how CERP is affecting the physical, biological, and chemical components of the system, and to increase scientific understanding of how the system works. Knowledge of how the system is changing in response to CERP restoration actions combined with investigations of cause-and-effect relationships will contribute to the refinement of CERP projects to ensure that targets are being met. It is recognized that this monitoring plan does not include all of the measures necessary to document the long-term “restoration” of all systems in south Florida (e.g., some upland systems in undeveloped and developed landscapes), but it will provide a minimal set of measures for those systems directly affected by CERP. (3) What Should Be Monitored? In General The main point of environmental monitoring is to detect change or lack of change over time, and to provide information sufficient to understand the causes of these patterns so that appropriate actions can be taken to manage the ecosystem for a desired condition. Part of the challenge in designing and sustaining a successful monitoring program is to select a limited set of parameters that adequately convey whether the ecosystem is or is not changing, in what direction it is changing, whether these changes are natural or a result of human actions, and if the latter, whether the changes improve or adversely affect the ecosystem in some significant way. Prior to determining whether a change in condition or state has occurred, it is necessary to establish the initial or baseline conditions. Baseline information provides the benchmark against which the progress of the restoration plan can be measured, and to understand the ranges of natural variability necessary to confirm when change has actually occurred. While some regions of the Everglades ecosystem have well established monitoring programs, other areas have little or no baseline data. Plugging the gaps in baseline conditions is one of the critical components of the monitoring and assessment plan. There are different approaches that can be used for selecting the best suite of monitoring parameters. One can select parameters that are considered to be the major stressors or processes that control the context within which an ecosystem operates. With this approach it is assumed that as long as the major processes are operating appropriately, the ecosystem is functioning appropriately.
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Alternately, parameters such as individual species or groups of species that are considered to be indicators of the processes operating within the ecosystem can be selected. This approach assumes that unless all of the significant processes are operating appropriately, these indicators could not exist in this ecosystem at normal population levels. This mix of constraints on the ability to detect either desirable change resulting from restoration or undesirable change in an ecosystem argues for monitoring a mix of both basic processes and integrators. This and the ever-present possibility of unanticipated ecosystem changes also argue for the use of as many monitoring parameters as are “feasible” from as broad a spectrum of ecosystem parameters as possible. In practical terms, “feasible” means that there are good assurances that the parameters can be measured and understood over sufficient time periods to determine the long-term affects of management or a restoration program. The performance measures in this monitoring plan are planning and assessment tools that were approved (and in most cases also developed) by the CERP planning teams to identify the objectives for the restoration plan. Each performance measure identifies one or more components of the natural and human systems in south Florida that CERP has been designed to improve. The performance measures may be used in evaluation of proposed changes (primarily where simulation models exist) and as field indicators that the appropriate change has occurred. These performance measures have, for the most part, been selected through two CERP planning processes; 1) the C&SF Project Comprehensive Review Study’s (Restudy) Alternative Evaluation Team (AET) and 2) the RECOVER Regional Evaluation, Adaptive Assessment, and Water Quality teams. Restudy/AET process Between 1996 – 1999, during the Restudy feasibility phase of CERP, an interdisciplinary, interagency team of biologists, ecologists, and other resource specialists (AET) developed a set of performance measures as the basis for designing and evaluating alternative restoration plans. Each performance measure was implicitly linked to one or more planning objectives, and consisted of a measurable indicator and target. Because a key tenet of south Florida ecosystem restoration is that hydrologic restoration is a necessary starting point for ecological restoration, the performance measures created by the AET were largely indicators of hydrologic characteristics, consistent with what is known or hypothesized about the optimum hydrologic patterns for a number of characteristic plant and animal communities in the historic Everglades. These performance measures described hydrological parameters, data format and hydrological targets originally used by the AET to evaluate hydrologic simulation of alternative plans. Refined versions of these hydrologic performance measures are included in this monitoring plan for their value in setting hydrological targets for CERP,
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and for evaluating how well CERP implementation corrects the hydrological problems in the natural and human systems. Conceptual Model process The Restudy included an Applied Science Strategy that will now be used to link science and management during all phases of CERP. An essential step in this strategy has been the creation and refinement of a set of nine conceptual ecological models, each for a different physiographic region of south Florida. The models link stressors on the ecosystem to ecological attributes that are considered to be indicators of ecosystem health. Each of these linkages represents a working hypothesis based upon current knowledge of the ecosystem. The overall Restudy strategy was to use the conceptual models as a basis for reducing the total number of performance measures from an almost infinite number of potential measures in the natural and human systems of south Florida to a manageable number of major key indicators of environmental conditions. The models allowed for the selection of a parsimonious set of performance measures directly based on the stressors and attributes in each model. These measures collectively describe the physical and biological conditions that will be used to define a successfully restored natural system. The rationale for having performance measures and targets for each stressor is that the stressors are known or hypothesized to be the immediate sources of the ecological problems in each landscape. A successful restoration program must eliminate the unnatural stresssors acting on the natural systems. A performance measure describes the stressor and how that stressor should be measured, and how that stressor must change in order to neutralize its adverse effects. The hydrological performance measures for the natural system that were developed by the AET were for the most part derived from the hydrological stressors in these models. Performance measures have also been developed for each attribute in the conceptual models. The attributes have been identified as the biological or ecological elements that are the best indicators of responses in the natural systems to the adverse effects of the stressors. The hypotheses used to construct the conceptual models link each attribute to the stressor(s) that are most responsible for change in that attribute. If the hypotheses are correct, neutralizing the adverse affects of the stressor will result in a predictable positive response by the attribute. The performance measure developed for each attribute identifies the element(s) of that attribute that should respond, how the element(s) should be measured, and how the element(s) should change once the effects of the stressor are removed. The conceptual models also were used to identify uncertainties in knowledge in the linkages among the stressors and attributes. These uncertainties identify where additional research is needed to ensure the success of CERP and is discussed in Section IV.
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Development of Water Quality Performance Measures A number of the performance measures developed during the Restudy/AET process specifically focused on water quality. Water quality is identified as a stressor in several of the conceptual models. The linkages between water quality, hydrology and biology are complex and led to the decision to create a team that focuses on water quality as part of the RECOVER process. Refinement of water quality performance measures for RECOVER were conducted through the application of water quality and landscape models, empirical analyses, and results of on-going research. Selection of performance measures for this plan Over 900 performance measures and indicators resulted from the above processes. The monitoring and assessment plan must be sustainable for perhaps five decades or longer if it is to be successful in guiding CERP throughout its implementation and subsequent operation. The high cost of monitoring a large number of parameters over a large area and a long period of time is a major reason that many monitoring plans in support of adaptive assessment and management have failed to be sustainable. Therefore, it is crucial to identify a minimum set of performance measures that will indicate whether CERP is achieving ecological recovery of the greater Everglades ecosystem and is meeting its water supply and flood protection objectives. Determining this minimum set of parameters from the many performance measures that were proposed was one of the tasks of the AAT’s Editorial Team. This task was accomplished by organizing the submitted performance measures into broad categories, and reviewing the performance measures in each category to determine where overlapping measures could be combined. Measures were combined when two or more had similar locations, parameters or targets (see Section III for details). The result is a list of ~150 performance measures (~60 biological and soils, ~20 hydrological and ~70 water quality) with identification of the information they provide to assess system-wide CERP performance. The refinement of the performance measures is an on-going process. It is essential that the monitoring and assessment plan address the key restoration hypotheses, and that it focus on a sustainable number of performance measures. Long-term monitoring and assessment efforts fail if they are too large, too complicated, too expensive, or if the results can not be interpreted within the context of the key hypotheses. The next steps in the evolution of this monitoring and assessment plan is for the Adaptive Assessment team to re-exam the current set of recommended measures in the context of their linkages as outlined in the conceptual models. As part of this review, the measures will be grouped into logical, hypothesis-based packages as a basis for designing a more efficient system-wide monitoring protocol. The selection of these key hypotheses provides the focus for the monitoring and assessment program and for setting hypothesis-driven priorities in on-going and future natural systems research. The ultimate success of the CERP adaptive assessment program will depend on the acquisition of new information from an integrated program of modeling, monitoring and hypothesis-driven research. The general
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framework for this approach is further outlined in Section III of this monitoring and assessment plan. (4) Monitoring Plan Design Strategy: Monitoring design considerations Along with the identification of essential parameters to monitor, a monitoring network must be logistically economical, provide quantitative data, apply a standardized monitoring and data management protocol, and ensure that data analysis is done in ways insure that trends can be correctly recognized and tracked over time with confidence. There are a number of different approaches that can be taken in the design of a monitoring network that meets these design objectives. Although decisions regarding the details of the design protocol have yet to be determined, certain guiding considerations are provided here. Field monitoring and laboratory methods must be standardized. All participating investigators in the monitoring and assessment program must use agreed-upon methods for collecting and managing monitoring data. Any changes in methods during the implementation of the monitoring and assessment plan will be documented. A spatial framework for the monitoring network and its component performance measures needs to be defined. Selection of performance measures can best be done within this framework because: 1) the spatial scale of sampling will financially constrain the number of parameters that can be measured; 2) consideration of spatial domains that are consistent with the conceptual models will promote consideration of the interactions of performance measures and the need for grouping measures, rather than assessing measures independently; and 3) consideration of gradients will add realism to the conceptual model approach – the habitats included in the conceptual models are not isolated entities, but rather exist as part of a continuum across the landscape. Common performance measures of several habitats and how they change temporally across habitat ecotones needs to be assessed. RECOVER should consider documenting changes across three important gradients that will be changed during the restoration: hydrologic, nutrient, and salinity gradients. Hydrologic gradients – restoration will change the spatial distribution of hydropatterns and associated plant and animal communities. Gradients from uplands through deeply inundated wetlands may shift over substantial distances. Nutrient gradients – must be able to detect effectiveness of water quality improvements in and near impacted zones, which generally are gradients oriented by discharge sources. Indirect hydrological effects on natural nutrient gradients must also be assessed (e.g. within mangrove zone). Salinity gradients – changing water quantity, distribution, and timing will cause changes in the location of salinity gradients and the salinity patterns along those gradients. This will yield biological responses that can best be assessed by sampling along these gradients.
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detect important changes but not so sensitive that signals are masked by natural variability?” A new performance measure that is needed to track an ecological response, but that has yet to be fully developed and tested, may be identified as a research priority in support of the monitoring plan. Feasibility of Implementation Cost-effectiveness. The above criteria determine the value of the information yielded by a performance measure, without regard to cost-effectiveness. If that information is found to be essential, can it be obtained for less cost in another way? Evaluations to date have focused primarily on the assessment of Conceptual Relevance and Interpretation and Utility. Each performance measure was subjected to a screening process using the following criteria: Is the performance measure expected to change DIRECTLY in relation to CERP (is there a clear linkage between the performance measure and the predicted changes from implementing CERP). Is the performance measure in a conceptual model (applicable to biological and soil performance measures only) Does the performance measure have a clearly defined target? Any performance measure not meeting all of the above criteria was not considered for inclusion in the monitoring plan. The remaining biological and soils performance measures were then evaluated for their ability to provide information on the following: Is it an indicator of an important ecological process? (Processes were considered things such as food webs, energy transfer, etc.). Is it an indicator of important ecological structure? (Including being an indicator for things such as fragmentation, compartmentalization, succession, disturbance) Is it a clear indicator of major environmental change? (Hydrology, Fire, Water Quality, Exotics). Animal performance measures were further reviewed using: Is the indicator a State or Federally listed Threatened or Endangered Species? Does it have high aesthetic value, high public appreciation/ symbol of the Everglades?
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Does it have important recreational value (fishing, boating, bird-watching, etc.)? Does it have important commercial value (fisheries)? The result of this process are presented in TableIII-1
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Table III-1 - Biological Performance Measures Category Unique ID Performance Measure Conceptual Models that contain the Attribute Ecological Process Ecological Structure Environmental Change Temporal Scale Threatened, Endangered, or SSC High Aesthetic value Important recreational Value Important Commercial Value Soil S01 accretion - negative shoreline organic berm LOK Lake Okeechobee X X Soil S02 shoreline habitat - Indian River Lagoon St Lucie Estuary X X X X X X Soil S03 Wetland soil accretion in greater Everglades Ridge/Slough, Mangrove Estuarine Transition, Marl Prairie, Big Cypress X X Soil S04 St Lucie Estuary Muck Removal St Lucie Estuary X X X X Soil S05 MTZ Soil Nutrient Dynamics Mangrove Transition Zone X X Animal A01 Snail Kite Nesting Lake Okeechobee M X Animal A02 Wading Bird Nesting Florida Bay, Lake Okeechobee, Mangrove Estuarine Transition, Big Cypress, Ridge & Slough X X X M X X X Animal A03 Wintering Waterfowl population estimates Mangrove Estuarine Transition X X M X Animal A04 Juvenile crocodile growth, survival, and condition Biscayne Bay, Mangrove Estuarine Transition X X M X Animal A05 Deer numbers and distribution Big Cypress X X M X X Animal A06 Crocodile distribution and relative abundance Biscayne Bay, Mangrove Estuarine Transition X X M X X Animal A08 Manatee Number and distribution Caloosahatchee and Biscayne Bay X X L X X X Animal A09 Manatee Mortality Caloosahatchee and Biscayne Bay L X Animal A10 Alligator Abundance, distribution, and size classes Marl Prairie, Big Cypress, Lake Okeechobee, Mangrove Estuarine Transition, Ridge & Slough X X X M X X X Animal A11 Alligator nesting effort and success Marl Prairie, Big Cypress, Lake Okeechobee, Mangrove Estuarine Transition, Ridge & Slough X X X L X Animal A12 Alligator condition Marl Prairie, Big Cypress, Lake Okeechobee, Mangrove Estuarine Transition, Ridge & Slough X X M Animal A13 Alligator hole distribution and occupancy Marl Prairie, Ridge & Slough X X X M Animal A14 Wading bird feeding aggregations Lake Okeechobee, Marl Prairie X X M X Animal A15 Dolphin Health Profile ??? Biscayne Bay X L X X Animal A16 Juvenile Pink Shrimp Density Florida Bay, Biscayne Bay X M Animal A17 Pink Shrimp Catch Rates Florida Bay, Biscayne Bay X M X X Animal A18 Abnormal Fish Prevalence Biscayne Bay, Florida Bay?? Animal A19 Estuarine Aquatic Fauna; Macroinvertibrates Florida Bay, Biscayne Bay, Caloosahatchee Estuary, St. Lucie Estuary X X X M Animal A20 Estuarine Fish Community Florida Bay, Mangrove Estuarine Transition, Biscayne Bay, Caloosahatchee Estuary, St. Lucie Estuary X X X M X Animal A21 Wetland Aquatic Fauna Ridge & Sough, Marl Prairie, Mangrove Estuarine Transition, Big Cypress, Lake Okeechobee X X X S X X Animal A22 Lake Okeechobee Fisheries Monitoring Lake Okeechobee X X X M X X Animal A24 Cape Sable Seaside Sparrow Marl Prairie X X M X Animal A25 Oyster Distribution, Abundance and Condition St Lucie Estuary, Caloosahatchee X X M X X NOT APPLICABLE for PLANTS Plants P01 Cattail extent Ridge and Slough X X L Plants P02 Coastal Lakes and Basins Submerged Aquatic Vegetation Mangrove Estuary Model M Plants P03 Community composition of cypress forests Big Cypress X X X M Plants P04 Community composition of hammocks Big Cypress X X X M Plants P05 Community composition of herbaceous wetlands Big Cypress X X X M Plants P06 Community composition of mesic pineland Big Cypress X X X M Plants P07 Diverse littoral zone native plant community Lake Okeechobee X X L Plants P08 Forested Wetland Plant Communities Big Cypress X X X M Plants P09 Manatee Habitat Caloosahatchee Estuary and Biscayne Bay X X M Plants P10 Mangrove presence, distribution, health, relative abundance Caloosahatchee Estuary X X X M Plants P11 Marl Prairie Vegetation Mosaic Marl Prairie X X X M Plants P12 Panther habitat Big Cypress X X M
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Plants P13 Periphyton Ridge & Slough X X X M Plants P14 Periphyton mat cover, organic-inorganic production, and marl accretion Marl Prairie X X X M Plants P15 Phytoplankton primary productivity in Lake Okeechobee Lake Okeechobee X X X L Plants P16 Plant community gradients Big Cypress X X X M Plants P17 Plant community mosaic Big Cypress X X X M Plants P18 Plant vegetation dynamics Mangrove Estuarine Transition X X X L Plants P19 Sawgrass and slough spatial coverage and orientation Ridge and Slough X X X L Plants P20 Sea Grasses Abundance - Caloosahatchee Caloosahatchee Estuary X X X M Plants P21 Seagrasses Biscayne Bay Biscayne Bay M Plants P22 Seagrasses Florida Bay Florida Bay X X X M Plants P23 Spatial extent of continuous bulrush stands Lake Okeechobee X X L Plants P24 Spatial extent of invasive exotic plants in Lake Okeechobee Lake Okeechobee X L Plants P25 Submerged aquatic vegetation St Lucie Estuary St. Lucie Estuary X X X M Plants P26 Submerged Aquatic Vegetation Coastal Lake Mangrove Estuarine Transition X X M Plants P27 Submerged Aquatic Vegetation Lake Okeechobee Lake Okeechobee X X X M Plants P28 Tree island structure and function Ridge and Slough X X X M Plants P29 Upland/Wetland Mosaic for Indian River Lagoon St Lucie Estuary X X X M Plants P30 Wetland community composition Big Cypress X X X M Plants P31 Oyster Habitat St Lucie Estuary X X M
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(3) Evaluation of Hydrologic Performance Measures The second broad category of performance measures are specific to the hydrology of the natural and human systems in south Florida. For the natural system two categories of hydrological performance measures have been created by the RET. One set is based on pre-drainage hydrological patterns predicted by the Natural System Model. This set uses these pre-drainage hydropatterns as targets for restoration. A key tenet of south Florida ecosystem restoration is that hydrologic restoration is a necessary starting point for ecological restoration. The second category of hydrological performance measures are those that define desirable characteristics of wetland systems, which differ from pre-drainage conditions. The measures in this second category are influenced by regional management constraints (e.g., Lake Okeechobee lake levels) or reflect more modern views of desirable ecosystem conditions (e.g., estuarine salinty patterns that may differ from pre-drainage conditions). COMMENT: I thought non-NSM targets were always a result of management constraints (e.g., Biscayne Bay, Caloosahatchee River, WCAs and Lake Okeechobee). Both categories of natural system hydrological measures are derived from the hydrological stressors contained in the conceptual ecological models. Originally these stressor-based performance measures were developed by the AET to set a number of hydrologic targets for restoration that could be simulated by computer models as a basis for evaluating alternative plans during the Restudy. A highly modified set of hydrological performance measures is finding application in the CERP monitoring plan. The hydrologic performance measures are included in this monitoring plan for their value in setting hydrological restoration and water supply targets for CERP, which when compared to actual field measurements will allow us to assess how well CERP corrects the hydrologic problems in the natural and human systems. The hydrologic performance measures listed in Table III-2 represent the current set of performance measures necessary to assess changes in the stressors resulting from CERP actions. They define hydropatterns for the different Everglades ecosystems, e.g., ridge and slough, marl prairie, the range of water flows to sustain estuaries and bays, and the ability to meet the water supply and flood protection needs of the human systems. Because all of the proposed hydrological performance measures have their origin either as stressors in the conceptual ecological models or are based on water supply policy or law, no screening or ranking of these measures by the RET was necessary. All are included in the monitoring plan because CERP is designed to correct the problems caused by all of the hydrological stressors
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Table III-2 Hydrologic Performance Measures Category Unique ID Performance Measure Hydrologic H1 Lake Okeechobee Extremes in Low Lake Stages Hydrologic H2 Lake Okeechobee Extremes in High Lake Stages Hydrologic H3 Spring Recession for Lake Okeechobee Hydrologic H4 St. Lucie Estuary Salinity Envelope Hydrologic H5 Lake Worth Salinity Envelope Hydrologic H6 Salinity Envelope for Caloosahatchee Estuary Hydrologic H7 Average Inundation Duration for Greater Everglades Hydrologic H8 Number of Dry Events in Greater Everglades Hydrologic H9 Duration of Water Level Deviation from NSM in Greater Everglades Hydrologic H10 Extreme Low Water Levels in Ridge and Slough Ecosystems Hydrologic H11 Extreme High Water Levels in Ridge and Slough Ecosystems Hydrologic H12 Seasonal Amplitude and Interannual Variability of Water Levels in Greater Everglades Hydrologic H13 Seasonal and Annual Overland Flow Volume in Greater Everglades Hydrologic H14 Tree Island Hydrologic Impacts Hydrologic H15 Model Lands/C-111 Hydrologic Performance Measure Suite Hydrologic H16 Surface Water Discharges to Biscayne Bay Hydrologic H17 Florida Bay - Surface Water Flows Hydrologic H18 Lake Okeechobee Service Area - Frequency of Water Restrictions Hydrologic H19 Frequency of Water Restrictions for the Lower East Coast Service Area Hydrologic H20 Potential for High Water Levels in South Miami-Dade Agricultural Area Hydrologic H21 Prevent Salt Water Intrusion of the Biscayne Aquifer: Meet Minimum Flow and Level criteria for Biscayne Aquifer Hydrologic H22 Prevent Salt Water Intrusion of Biscayne Aquifer in South Miami-Dade County Hydrologic H23 Continuity: Water Surface Elevations across Barriers Hydrologic H24 Sheetflow: Volume of Water Across Transects in the WCAs and Everglades National Park
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(4) Evaluation of Water Quality Performance Measure Documentation Sheets For the water quality component of the monitoring and assessment plan, the list of AET performance measures was expanded to over 70 performance measures by members of the RECOVER WQT. Measures were developed on a region-by-region basis to capture the unique conditions of each of the main physiographic regions in South Florida. As a consequence, there are multiple performance measures for what appears to be the same water quality parameter; however, each one has a restoration target unique to a specific region. The WQT discussed, agreed upon and went through an evaluation process to assess and better understand the informational quality/applicability of each of the water quality performance measures. However, this process was somewhat different from that conducted for the biological performance measures, in that the evaluations were made based upon a unique set of criteria that the WQT felt was more applicable to water quality. Each measure was initially screened as to whether it: Would likely change in response to the implementation of CERP components. Would be a regional indicator of CERP performance (vs. a project-level measure). Had a clearly defined restoration target. If the performance measure did not meet all three criteria, it was not considered for inclusion in the monitoring plan. The set of water quality performance measures remaining for each of the geographical regions from this initial screening underwent further evaluation by the team using the following criteria: Is the proposed performance measure a strong indicator of the health of the ecosystem or a major stress? Does the performance measure have a strong regulatory basis? Is the performance measure easy to use or implement? Does the performance measure provide information not provided by other performance measures being recommended for the geographical region? Does the performance measure have a relatively strong degree of predictability (i.e. can you easily distinguish changes resulting from CERP from those contributed by other factors, and is there a mechanism available to predict future performance of the performance measure?) Does the performance measure have a relatively low measurement uncertainty? The results of this evaluation are displayed in Table III-3.
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Table III-3 Water Quality Performance Measures EVALUATION CRITERIA Category Unique ID Performance Measures by Region (North to South) Conceptual Model Stong Indicator of Ecosystem Health or a Major Stress Strong Regulatory Basis Easy to use or implement Not duplicative of other performance measures Relatively strong degree of predictability Relatively low measurement uncertainty Lower Kissimmee River Basin Water Quality WQ1 TP Load Reduction at and downstream from S-65D X X X X X X Water Quality WQ2 Trace Metals (Mercury) at Highway 78 bridge X X X X Lake Okeechobee Water Quality WQ3 Phosphorus Loads Lake Okeechobee X X X X X Water Quality WQ4 Pelagic zone total phosphorus Lake Okeechobee X X X X X X Water Quality WQ5 Net P assimilative capacity Lake Okeechobee X X X X X Water Quality WQ6 Water Clarity Lake Okeechobee X X X X X X Water Quality WQ7 Pelagic zone algal bloom frequency based on chlorophyll a concentrations Lake Okeechobee X X X X X X Water Quality WQ8 Pelagic zone TN to TP ratio Lake Okeechobee X X X X X Water Quality WQ9 Sediment Porewater Phosphorus (P) X X X X Water Quality WQ10 Pelagic Zone Diatom; Cyanobacteria ratio X X X X Water Quality WQ11 Pelagic zone nutrient limitation status X Lake Okeechobee ASR Water Quality WQ12 Increase in Methly Mercury in surface waters in response to ASR activity related to increase in Sulfur X X X X Water Quality WQ13 Increase in Cl and salinity in L.O. in response to ASR Activity X X X X X Everglades Agric. Area/STAs Water Quality WQ14 WCA Inflow Phosphorus Concentrations X X X X X X Water Quality WQ15 WCA Inflow Phosphorus Loads X X X X X X Water Quality WQ16 STA Bypass Loads X X X X X Water Quality WQ17 Total Load Reductions in STAs & Reservoirs X X X X X X Water Quality WQ2 Trace Metals (Mercury) X X X X X Caloosahatchee River and Estuary Water Quality WQ18 Biochemical Oxygen Demand Caloosahatchee Estuary X X X X X X Water Quality WQ19 Total Phosphorus Caloosahatchee Estuary X X X X X X Water Quality WQ20 Dissolved Oxygen Caloosahatchee Estuary X X X X X X Water Quality WQ21 Chlorophyl a Caloosahatchee Estuary X X X X X Water Quality WQ22 Total Nitrogen Caloosahatchee Estuary X X X X Water Quality WQ23 Toxicity-Heavy Metals Caloosahatchee Estuary X Water Quality WQ24 Total and fecal coliforms Caloosahatchee Estuary X X X Water Quality WQ25 Organics (Pesticides) Caloosahatchee Estuary X X X X X X Caloosahatchee Basin/ASR Water Quality WQ12 Increase in Methlyl Mercury in in surface waters in response to ASR activity related to increase in Sulfate X X X X Water Quality WQ13 Increase in Cl and salinity in river in response to ASR activity X X X X X St. Lucie Estuary and Indian River Lagoon Water Quality WQ25 Organcis (Pesticides) SLE&IRL X X X X X X Water Quality WQ26 (TN Loads) - Reduce N Loads to estuary SLE&IRL X X X X X Water Quality WQ27 (TP Loads) -Reduce P Loads to estuary SLE&IRL X X X X X Water Quality WQ28 P Load to the IRL from C-25 and C-1 canals SLE&IRL X X X X Water Quality WQ29 N Load to the IRL from C-25 and C-1 canals SLE&IRL X X X X X Water Quality WQ30 Phytoplankton/Chlorophyll a SLE&IRL X X X Water Quality WQ31 Flow and TP loads to Lake Okeechobee X X X X X
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Lake Worth Lagoon Water Quality WQ32 TSS Loads X X X X Water Quality WQ33 P Loads X X X X Water Quality WQ34 N Loads X X X X Lower East Coast (North of Biscayne Bay) Water Quality WQ35 N Loads and Concentrations in waters delivered to tide through G56 (Hillsboro Basin) X X X X X X Water Quality WQ36 P Loads and Concentrations in waters delivered to tide through G56 (Hillsboro Basin) X X X X X X Water Quality WQ37 P Loads and Concentrations in waters delivered to Loxahatchee Refuge (WCA-1) X X X X X X Water Quality WQ38 P Loads and Concentrations in waters delivered to WCA3 from C11 Basin X X X X X X Lower East Coast ASR Water Quality WQ12 Increase in Methlyl Mercury in in surface waters in response to ASR activity related to increase in Sulfate X X X X Water Quality WQ13 Increase in Cl and salinity in river in response to ASR activity X X X X X Greater Everglades - WCAs, ENP, eastern Big Cypress, Holey Land, Rotenberger, Model Lands/C-111 Basin Water Quality WQ25 Organics (Pesticides) ER&S X X X X X Water Quality WQ2 Trace Metals (Mercury) ER&S X X X X X Water Quality WQ39 Wetland Soil Phosphorus concentration ER&S X X X X X X Water Quality WQ40 Wetland Surface Water Phosphorus Mass/Area Loading ER&S X X X X X X Water Quality WQ41 Wetland Surface Water Phosphorus Concentration (includes WCA 3) ER&S X X X X X X Water Quality WQ42 Wetland Surface Water Phosphorus Mass Loading (includes WCA 3) ER&S X X X X X X Water Quality WQ43 Sulfate - surface water; sulfide/sulfate-porewater X X X X X Water Quality WQ44 Conductivity X X X X X X Water Quality WQ45 Total Organic Carbaon X X X X Miccosukee Reservation Water Quality WQ46 Total Phosphorus Concentration X X X X X X Water Quality WQ47 Total Phosphorus Load X X X X X X Big Cypress Seminole Reservation Water Quality WQ48 Quality of surface water entering reservation X X X X X X Water Quality WQ49 Quality of surface water leaving reservation X X X X X X Lower West Coast-Lake Trafford Water Quality WQ50 Dissolved Oxygen X X X X X X Water Quality WQ51 Trophic State Index X X X X Lower West Coast-Southern Golden Gates Estates Water Quality WQ52 Hardness Concentration X X X X X Water Quality WQ53 Phosphorus Concentrations X X X X X X Big Cypress Basin Water Quality WQ54 Mean wet season phosphorus concentration in SE and NE Big Cypress relative to 10 year POR Big Cypress Regional X X X X X Water Quality WQ2 Trace Metals (Mercury) Big Cypress Regional X X X X Water Quality WQ25 Organics (Pesticides) Big Cypress Regional X X X X Everglades National Park Water Quality WQ55 Flow-weighted mean TP concentrations entering Shark River Slough X X X X X X Water Quality WQ56 Frequency of Shark River TP inflow samples exceeding 10 ppb within a given 12-month period. X X X X X X Water Quality WQ57 Mean TP concentration at Shark River Slough marsh stations X X X X X Water Quality WQ58 Flow-weighted mean TP concentrations entering Taylor Slough/Coastal Basins X X X X X X Water Quality WQ59 Frequency of Taylor Slough TP inflow samples exceeding 10 ppb within a given 12-month period. X X X X X X
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Water Quality WQ60 Mean TP concentration at Taylor Slough/Coastal Basin marsh stations X X X X X Biscayne Bay Water Quality WQ61 Sediment Chemistry and Toxicity Biscayne Bay X X X X X Water Quality WQ62 Water Transparency Biscayne Bay X X X X X Water Quality WQ63 Total Coliform Biscayne Bay X X X X X Water Quality WQ64 Ammonia Biscayne Bay X X X X X X Water Quality WQ65 Total Nitrogen Biscayne Bay X X X X X X Water Quality WQ66 Total Phosphorus Biscayne Bay X X X X X X Water Quality WQ67 Nox Biscayne Bay X X X X X X Model Lands/C-111 Basin Water Quality WQ68 Mean TP concentration of inflow points to the South Dade Wetlands X X X X X X Florida Bay Water Quality WQ69 Toxics Florida Bay X X X X X Water Quality WQ70 Algal Blooms Florida Bay X X X X Water Quality WQ71 Nutrients Florida Bay X X X X Water Quality WQ72 Nutrient Loads Florida Bay X X X X X Water Quality WQ73 Light Florida Bay X X X X Note: WQ1 Summary Sheet for Lower Kiss. River TP Load Reduction WQ2 Summary Sheet for Trace Metals WQ12 Summary Sheet for ASR Methyl Mercury WQ13 Summary Sheet for ASR - Cl and Salinity WQ25 Summary Sheet for (Organics) Pesticides WQ54 Summary Sheet for Big Cypress Mean Wet Season TP Concentration
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(5) Documentation Sheets The documentation sheets presented here are for the set of 156 performance measures listed in Tables III-1 to 3. Each documentation sheet describes the performance measure, in what geographic regions it is to be measured, the restoration target, and a general description of the monitoring protocol. If the original sheets were combined or edited it is noted in the editing comments. (6) Further Refinements of What to Monitor The 156 performance measures listed here linked with the key hypotheses in the conceptual models provide the basis for the monitoring and assessment plan. One of the next steps is to review the performance measures in the context of the ir linkages and uncertainties within the conceptual models and refine the monitoring and assessment plan to ensure that it addresses the key restoration hypotheses and focuses on a sustainable number of performance measures. The approach that will be used will examine the performance measures in an integrated hierarchical framework to ensure that the resulting plan will be holistic and include indicators at a range of temporal and spatial scales. The conceptual models will be further refined to focus on the most critical over-riding restoration hypotheses for each physiographic region. The models will be examined for logical groupings of performance measures, linkages, and key questions that will provide the essential information for the adaptive assessment process. The groupings within each model will be evaluated for their importance related to the success of CERP and the resulting groupings from each model will be reviewed together to ensure a system-wide perspective. It is anticipated that this process will be completed in the next 3-4 months.
Representative terms from entire chapter: