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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:
performance measure
