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### October 17, 2007



## Development and Application of Comprehensive Everglades Restoration Plan System-wide Performance Measures

RESTORATION COORDINATION AND VERIFICATION

COMPREHENSIVE EVERGLADES
RESTORATION PLAN

CENTRAL AND SOUTHERN FLORIDA PROJECTTable of Contents October 17, 2007

i 

### Table of Contents

Executive Summary .............................................................................................................. .....ES-1

1.0 Introduction ............................................................................................................... ...... 1-1

2.0 Performance Measures as Evaluation and Assessment Tools......................................... 2-1

3.0 Relationship to CERP Adaptiv e Management Framework............................................. 3-1

4.0 CERP Success Points of Reference................................................................................. 4-1

5.0 Relationship of Performance Measures to Interim Goals and Interim Targets ............... 5-1

6.0 History of Performance Measure Development .............................................................. 6-1

7.0 Criteria and Guidelines for Performance Measure Development ................................... 7-1

8.0 Conceptual Ecological Models........................................................................................ 8-1

9.0 Lake Okeechobee CERP-Specific Conceptual Ecological Models and Performance
Measures...................................................................................................................... .... 9-1

10.0 Northern Estuaries CERP-Specific Concep tual Models and Performance Measures ... 10-1

11.0 Greater Everglades CERP-Specific Con ceptual Ecological Models and Performance
Measures...................................................................................................................... .. 11-1

12.0 Southern Estuaries CERP-Specific Conceptual Ecological Models and Performance
Measures...................................................................................................................... .. 12-1

13.0 Water Supply and Flood Prot ection Performance Measures......................................... 13-1

14.0 Total System CERP-Specific Conceptual Ecological Models and
Performance Measures .................................................................................................. 14-1

15.0 Review Process............................................................................................................ .. 15-1

16.0 Uncertainty Associated with Pe rformance Measure Application.................................. 16-1

17.0 Next Steps ................................................................................................................ ..... 17-1

Appendix A. Models Used with Performance Meas ures to Evaluate Alternative Plans............. A-1

Appendix B. Crosswalk of Performance Measures......................................................................B-1

Appendix C. Legal Justification for Performance Measures........................................................C-1

Appendix D. History of Rest udy Performance Measures ........................................................... D-1

Appendix E. Indicator Region Documentation ............................................................................E-1Executive Summary October 17, 2007

ES-1 

### Executive Summary

Performance measures are tools based on a set of indicators us ed in project planning to evaluate the degree to which proposed altern ative plans are likely to meet restoration objectives and to assess the success of im plemented plans in meeting restoration objectives. Performance measures and their asso ciated targets are integral components of the Comprehensive Everglades Restoration Pl an (CERP) Adaptive Management Strategy.

Most performance measures were developed through conceptual ecological models that identified key stressors and at tributes of the natural system . Attributes ar e biological and ecological indicators in the natural system , which respond to effects of stressors.
Performance measures for other water-related needs of the system, such as water supply
and flood control to meet urban and agricultural needs, are de rived from state and federal laws. CERP performance measures must fulfill the following:

 The performance measure must address indi cators that represent attributes or stressors of natural or human systems that CERP is expected to affect.

 Targets must reflect the desired rest oration condition, which is the maximum level of restoration possibl e given human inhabitation of South Florida. (The concept of desired restoration condi tion is currently being reexamined.)

 The performance measure must provide an understanding of system-wide responses relative to how CERP implem entation is meeting its complex, systemwide goals, while not being so unwieldy and costly that system-wide modeling and monitoring programs cannot be sustained over many years.

This report documents the development and application of system-wide performance measures developed by Restoration Coordina tion and Verification (RECOVER) technical
teams to date. Performance measures were de veloped with the best available science and tools. Development and application of performance measures is a dynamic process that incorporates new scientific understandings and technological improvements. As our understanding of the ecosystem grows, perfor mance measures and this document will be refined. Refinement of performance measures is part of CERP’s Adaptive Management Strategy. Therefore, this is a ‘living document’, as ar e the performance measure documentation sheets, and they will be updated to reflect best available science and tools.

This document provides background on how RECOVER performance measures are developed, revised, reviewed and applied. To fully understand the performance measures and how they are to be properly used, this document needs to be read. It discusses the following:

• Scope and purpose of performance measures

• History of performance measure development

• Criteria for choosing performance measures

• Detailed review process for new and revised performance measuresExecutive Summary October 17, 2007

ES-2 • Performance measures place in the CERP Adaptive Management Strategy

• Connection between performance measures and other aspects of the CERP Adaptive Management St rategy (i.e., monitoring and assessment, interim goals and targets)

• Relationship of performance meas ures to conceptual ecological
models

• Application of performance measures in evaluating alternative plans and assessing system response to CERP implementation

• Uncertainty associated with using performance measures

• Next steps in performance measure development

Performance measures themselves are docum ented separately. A documentation sheet is
maintained for each measure.1.0 Introduction October 17, 2007

1-1 

### 1.0

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### Introduction

Restoration Coordination and Verificati on (RECOVER) has developed performance measures for evaluating modeled system-wid e performance and assessing actual systemwide performance of CERP in meeting its goals and object ives. Performance measures are planning tools used to determine the de gree to which proposed alternative plans are likely to meet restoration objectives, or implemented plans have met restoration objectives. Performance measures presented in this document identify system-wide hydrological, ecological and water quality in dicators expected to respond to CERP implementation.

This document provides background on how system-wide performance measures are developed, revised and reviewe d. It also describes performa nce measure application in CERP planning and some of the uncertainty a ssociated with that application. The next steps that will be taken regarding performance measures are also discussed. Performance measures themselves are documented separa tely. A documentation sheet is maintained for each measure at the following RECOVER web site: www.evergladesplan.org/pm/recover/eval_team_perf_measures.aspx

.
The CERP system-wide performance measures are developed with the best available science and tools; however, development and application of perfor mance measures is a dynamic process that incorporates new sc ientific understand ings and technical improvements. As our understanding of th e ecosystem and the hypotheses that define ecologic relationships grows and new eval uation tools are deve loped, performance measures and this document will be refined, additional performance measures will likely be proposed, and some may be dropped. Refineme nt of performance measures is part of CERP’s Adaptive Management Strategy (REC OVER 2006). Therefore, this is a living document that will be continually updated as other RECOVER docum ents and processes are updated. The approved set of CERP system-wide performance measures as of September 2007 is as follows:

Lake Okeechobee

• Lake Okeechobee Lake Stage

• Lake Okeechobee Water Quality

• Lake Okeechobee Diatom:Cyanobacteria Ratio

• Lake Okeechobee Vegetation Mosaic

• Lake Okeechobee Fish Population De nsity, Age Structure and Condition

• Lake Okeechobee Macroinvertebrates

Northern Estuaries

• Northern Estuaries Salinity

• Northern Estuaries Water Quality

• Northern Estuaries Oyster Habitat

• Northern Estuaries Benthic Macroinvertebrates

• Northern Estuaries Submerged Aquatic Vegetation

• Northern Estuaries Fish Communities1.0 Introduction October 17, 2007

1-2 Greater Everglades Wetlands

• Number and Duration of Dry Events for Shark River Slough

• Inundation Pattern in Greater Everglades Wetlands

• Extreme High and Low Water Levels in Greater Everglades Wetlands

• Greater Everglades Wetlands Total Phosphorus Concentrations in Surface
Water

• Greater Everglades Wetlands Basinwid e Total Phosphorus Loading and FlowWeighted Mean Concentration in Inflows.

• Greater Everglades Wetlands Nutrient Total Nitrogen Concentrations in
Surface Water

• Total Nitrogen Loads/Flow-Weighted M ean Concentration in Inflows to the Greater Everglades Wetlands

• Total Phosphorus Concentrations in Soil

• Greater Everglades Tracer of Stor mwater Treatment Area Bypass Flows

• Greater Everglades Wetlands Sulfate Concentrations in Surface Water

• Greater Everglades Wetlands Conductivity in Surface Water

• Greater Everglades Wetlands Coastal Salinity Gradients

• Wetland Landscape Patterns - Freshwater and Estuarine Vegetation Mosaics

• Wetland Landscape Patterns - Marl Prai rie Cape Sable Sparrow Habitat

• Wetland Landscape Patterns - Ridge a nd Slough Community Sustainability

• Wetland Landscape Patterns - Tidal Creek Sustainability

• Wetland Trophic Rela tionships–Periphyton

• Wetland Trophic Relationships - Mangrove Forest Production/Soil Accretion

• Wetland Trophic Relationships - Regional Populations of Fishes, Crayfish, Grass Shrimp and Amphibians

• Wetland Trophic Relationships - Wadi ng Bird Foraging Patterns on
Overdrained Wetlands

• Wetland Trophic Relationships - Wading Bird Nesting Patterns

• Roseate Spoonbill Nesting Patterns

• Wetland Trophic Relationships - Ameri can Alligator Distribution, Size, Nesting and Condition

• American Crocodile - Juvenile Growth and Survival

Southern Estuaries

• Southern Estuaries Salinity

• Water Level at Regionally Significant Gauge Stations in Everglades National
Park

• Southern Estuaries Submerged Aquatic Vegetation

• Southern Estuaries Juvenile Pink Shrimp and Associated Epifauna

• Southern Estuaries Fish Community

• Southern Estuaries Water Quality

Water Supply and Flood Protection

• Frequency of Water Restrictions for Lake Okeechobee Service Area

• Frequency of Water Restrictions for the Lower East Coast Service Area1.0 Introduction October 17, 2007

1-3 • Potential for High Water Levels in South Miami-Dade Agricultural Area

• Prevent Saltwater Intrusion of the Bi scayne Aquifer - Meet Minimum Flows and Level Criteria for Biscayne Aquifer

• Prevent Saltwater Intrusion of the Bi scayne Aquifer in South Miami-Dade County

• Comparison of Stage Differences of Water Levels in South Miami-Dade Agricultural Area

Total System

• Snail Kite Foraging Conditions

• White Tail Deer Breeding Potential

• Mercury Bioaccumulation

Two Greater Everglades performance measur es have recently been developed and are
under review. The indicators used within the me asures are sheet flow in Everglades ridge and slough landscape and hydrologic patterns in wet prairies.

1.1 References

RECOVER. 2006. Comprehensive Everglades Restoration Plan Adaptive Management Strategy. Restoration Coordination and Ve rification Program, c/o United States Army Corps of Engineers, Jacksonville Di strict, Jacksonville, Florida, and South Florida Water Management District , West Palm Beach, FL. April 2006. www.evergladesplan.org/pm/recover/r ecover_docs/am/rec_am_stategy_brochure. pdf2.0 Performance Measure as Evaluation and Assessment Tools October 17, 2007

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### Performance Measures as Eval uation and Assessment Tools

Performance measures will be used during two components of the adaptive management process: evaluation of expected plan pe rformance and assessment of actual plan performance (see Section 3 Relationship to CERP Adaptive Management Framework for more details). For adaptive management to be successful, assessments (see Section 2.2) must be compared to planni ng expectations. This requires that indicators used for planning be assessed during implementation. Indi cators used for evaluations of plans are limited by available tools. Many more indicators can and will be monitored and assessed as CERP progresses. Additi onally, metrics and targets of indicators used for both evaluation and assessment may differ because it may not be practicable to use the same metric and target for planning purposes as it is for assessment purposes. This may make comparing expected responses to actual res ponses difficult. Methods that will reconcile the different metrics and targets to en able the comparison must be developed.

The specific application of performance measures to evaluation (planning) and assessment processes is discussed in the follo wing sections. In many cases, we are not yet able to apply performance meas ures to either process, but the indicator is considered important enough in assessing CERP success to be included. Also, in some instances, neither evaluation nor assessment targets ar e specific. As additional research and monitoring are conducted, and ecological mode ls are either developed or refined, RECOVER will refine and improve both evaluation and assessment restoration application and targets.

2.1 Evaluation Applications

During CERP project plan development a nd CERP updates, effects of different combinations of water management operations and features such as canal, levees and pump stations need to be estimated. Different alternatives need to be compared to select the plan that will best meet CERP goals a nd objectives. Several simulation methods can be used to evaluate the system’s respons e to a possible altern ative. These methods include computer simulation, post-processing of computer modeling results, and use of regression models. All simulati on models are basically mathem atical models that attempt to integrate and show interactions betw een multiple environmental and man-made components.

Most, if not all, simulation met hods require input of climatic variables. Since we can not predict weather, a historic period of record (currently 36 years or less) is used instead.
Results of these simulations can not be inte rpreted as predictions of actual c onditions expected to occur at a given time in the future. We can only approximate how certain features of the natural system would have re sponded to the rainfall conditions present in the period of record in combination with a fi xed set of land use char acteristics and water management practices. While output from these models are not predictions, these models are intended to provide some estimates of how average values of certain natural system features can be expected to respond over the long term. Hence, we ‘evaluate’ performance during the planning process, not ‘predict’ it. These estimations are2.0 Performance Measure as Evaluation and Assessment Tools October 17, 2007

2-2 especially useful in comparing alternate plans and adaptively managing a project or

program.

Computer simulation models are simplified representations of existing conditions (e.g., topography, vegetation) and processes (e.g., ra infall, levee seepage). These models are designed to operate at very specific spatia l and temporal scales. Usually, they are optimized to accurately represent only a few features of the system. They can not be expected to accurately simulate all of the co mplex interactions occurring between climate and hydrologic cycles, trophic we bs and vegetative communities. Therefore, not all of the CERP system-wide performance measures needed to assess the system will be applied to
evaluations.

The South Florida Water Management Model (SFWMM) is currently used for systemwide evaluations and for trying to determine system-wide effects of project alternatives. Due to the large spatial scale of this model (grids are 2 miles by 2 miles), very little, if any, differences can be seen fo r different alternatives of sp ecific projects. Project teams usually develop or modify smaller scale models to compare alternatives. Currently, the Regional Simulation Model (RSM) is being devel oped. It can operate at smaller, variable
scales.

Habitat suitability and water quality can be derived from SFWMM or other computer model hydrologic output even if they were not modeled explicitly. These post-processing methodologies may allow estimations of ecological attributes to assi st in selection of plans and may even provide some insight into interactions between stressors and
attributes.

The ability to evaluate performance measures is constrained by availability of simulation or computer modeling tools, their spatial and temporal scales, and their associated uncertainty. Uncertainty is discussed further in Section 16 of this repo rt. In the absence of adequate models, best available science and best professional judgment are used when conducting an evaluation. Assessmen ts of the system can aid in refining this professional judgment.

2.2 Assessment Applications

Progress towards restoration will be assessed at regular intervals as CERP is implemented. The assessment will not simply be a status of indi vidual performance measures with respect to individual targets. Instead, it uses a hypot hesis-based approach, which is more robust, flexible and more cons istent with an adaptive management process (see Section 3). The hypotheses are expected res ponses and relationships captured in a set of CERP-specific conceptual ecological models (see Sections 9 to 12, and14). The hypothesis-based approach recognizes complexities of ecological responses by assessing their status and trends using multiple performa nce measures or clusters of physical, water quality and ecological attributes. This more holistic approach attempts to capture
mechanistic interactions of multiple stressor-response pathways rather than relying on one metric to characterize ecological complexity. This approach is more scientifically
robust and increases the likelihood of detecting unexpected responses.2.0 Performance Measure as Evaluation and Assessment Tools October 17, 2007

2-3 The final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006), referred to as the Assessment Strategy, provides guidance for the following:

1. Estimate direction and magnitude of ch ange in performance measures from reference state both annually and cumulatively over multiple years.

2. Compare current performance measure stat us with its desired trend and target.

3. Evaluate consistency of monito ring results with MAP hypotheses.

4. Determine if unanticipated events are indicated.

5. Describe how these events ar e affecting desired outcome.

Physical, chemical and ecological data (i.e., multiple performance measures) are integrated and interpreted to assess cau sal inferences compri sing each hypothesis. Integration and interpretation of multiple physical and chemical stressor impacts on a specific ecological attribute, as described in a CERP hypothe sis, will require application of quantitative statistical and modeling methods as well as integration methods such as multiple lines-of-evidence and weight-of-evidence approaches. No single model can address complex temporal and spatial scale issues that characte rize CERP. The draft Assessment Strategy (RECOVER 2006) presents a very brief overview of statistical, modeling and weight-of-evidence approaches that have been used to analyze, integrate and interpret monitoring data to infer re lationships between stressors and effects described in MAP hypotheses.

Information will be integrated across modules (Lake Okeechobee, Northern Estuaries, Greater Everglades, Southern Estuaries and Water Supply and Flood Protection) to provide a system-wide synthesis of the inform ation and an evaluation of CERP progress. This requires identifying those physical, chem ical and ecological a ttributes that are critical to measuring restoration success at a system-level and that will be reported to the public and Congress as the keys to assess ing restoration success. One approach for addressing this requirement within our current analytical limitations is to use “defining characteristics” identified in the Total System Conceptual Ecological Model (Ogden et al. 2005). Using this point of departure, all line s of evidence needed to evaluate defining characteristics or interim goals (see Section 5) are identified. Weighing relative importance of lines of evidence wi ll make synthesis more robust.

If monitoring trends and rese arch results are inconsiste nt with or do not support hypotheses or the interim goals and targets, the following adaptive management options may be initiated: 1) modify the hypotheses, conceptual ecological models, and/or the associated performance measures, 2) modify tools (e.g., hydrologic models), 3) identify system-wide hydrological and/or ecological needs to improve CERP performance.2.0 Performance Measure as Evaluation and Assessment Tools October 17, 2007

2-4 The following assessment reports will be developed:

1. Principle investigator reports will cumula te data on an annual basis to provide a cumulative assessment of hypotheses and performance measures at the MAP component and module level.

2. Annual module group reports will provide module-level assessment of hypotheses and performance measures, review progr ess towards achieving interim goals, and identify unexpected events. These reports integrate multiple performance measures to provide an assessment of module-level hypotheses.

3. The biennial System Status Report will provide a synthesis and interpretation
across modules. It will evaluate CERP’s progress in achieving interim goals.

4. The Five-Year Technical Report will integrate trends and findings from System Status Reports and identify problems in system performance that require
corrective action.

2.3 References

Ogden, J.C., S.M. Davis, T.K. Barnes, K.J. Jacobs and J.H. Gentile. 2005b. Total system conceptual ecological model. Wetlands 25(4):955-979. www.evergladesplan.org/pm/recover/r ecover_docs/cems/cem_use_of_cems.pdf

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. www.evergladesplan.org/pm/recover/recover_map.aspx3.0 Relationship to CERP Adaptive Man agement Framework October 17, 2007

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### Relationship to CERP Ada ptive Management Framework

Adaptive management provides resource manage rs with an active strategy for dealing
with considerable uncertainties that ch aracterize management of large natural ecosystems. Natural systems are remarkably complex and it is difficult to predict how the system will respond to restoration and manageme nt efforts. Adaptive management is used to develop opportunities to incr ease knowledge by applying me thods of scien tific inquiry to planning, implementation and assessment of ecosystem management projects. The CERP Adaptive Management Strategy (REC OVER 2006a) provides a formal process for CERP refinement and addressing uncertainti es inherent in implementing and managing large-scale ecosystem restoration programs. This approach suppor ts improved decision making and plan performance over time. Pe rformance measures are an integral component of CERP adaptive management, a llowing program and project managers to gain knowledge to improve restoration success.

The CERP Adaptive Management Framework ( Figure 3-1 ) is a graphical overview of the CERP adaptive management process. This fr amework identifies four major components of the CERP Adaptive Management Stra tegy and shows how these components link together (RECOVER 2006a). The four strate gy components are Box 1: CERP Planning, Box 2: Performance Assessment, Box 3: Ma nagement and Science Integration, and Box 4: CERP Update Process. CERP system-w ide performance measures are integral to CERP planning (Box 1) and performance asse ssment (Box 2) processes. The role of performance measures in these processes is discussed below. Even though information from performance measures may contribute to integrating management and science (Box 3) and to decisions made to update CERP (Box 4), performance measures themselves are not an explicit co mponent of these processes.

Figure 3-1. CERP Adaptive Management Framework3.0 Relationship to CERP Adaptive Man agement Framework October 17, 2007

3-2 3.1

U Box 1: CERP Planning

The goal of Box 1: CERP Planning is to a pply adaptive management principles during system-wide and project planning by a ddressing performance uncertainties and incorporating performance-based versatilit y and recommended CERP improvements into project designs. Figure 3-2 illustrates adaptive management principals that play a role in the planning process.

PM = performance measure, TSP = tentatively selected plan, FSM = feasibility scoping meeting, AFB = alternatives formulation briefing, PIR = project implementation report
Figure 3-2. Box 1: CERP Planning

Performance measures play a vital role in both system-wide and project planning activities. CERP is composed of 68 ma jor components broken down into over 40 projects. Each project has or will have a projec t team that develops and uses project-level performance measures during the planni ng phase. RECOVER is responsible for providing technical and scientif ic support to CERP on a system-wide scale. To this end, RECOVER develops and uses syst em-wide performance measures.

Within project planning (i.e ., alternative plan developmen t and formulation), RECOVER is responsible for evaluating performance of project alternative plans using CERP system-wide performance measures, project pe rformance measures, a nd best professional judgment. RECOVER will also describe the ab ility of each altern ative plan to meet New Information/ Model Updates

Plan Improvement

Needs/Options Project-level Planning System-wide

Planning

To Box 3: Management/Science
Interaction To Box 2:
Performance
Assessment Comprehensive Plan

High Uncertainty Low Uncertainty

P

I R
P

r o c e s s Actions to Reduce Project
Uncertainties Alternative Development &

Formulation

Preliminary Design of TSP Base Condition

and Models

Detailed Design

Project Implementation A F B F S M

PM

PM3.0 Relationship to CERP Adaptive Man agement Framework October 17, 2007

3-3 targets established for each performance m easure and describe expected effects on the natural system. Similarly, when investiga ting system responses to large planning scenarios (e.g., sensitivity an alysis of sea-level rise, updated modeling assumptions), RECOVER evaluates CERP’s ability to m eet targets established for system-wide performance measures.

3.2

U Box 2: Performance Assessment

Monitoring and assessment of the South Fl orida ecosystem must be undertaken to determine success of CERP implementation and to provide a feedback mechanism to improve future planning deci sions. RECOVER is using a h ypothesis-based approach for assessment of system performance, which will provide a more robust and flexible approach than addressing individual perfor mance measures. This approach takes intoconsideration complexities of ecological responses being measured by CERP systemwide and project-level monitoring by assessin g their status and trends using multiple measures (clusters of physical, water quality and ecological attribut es). This approach attempts to capture mechanisti c interactions of mu ltiple stressor-respons e pathways rather than relying on one metric to characteri ze ecological complexity (RECOVER 2006b).

Figure 3-3 shows the framework for integrating adaptive management into the performance assessment process. System responses to CERP implementation will be monitored and assessed through the CERP Monitoring and Assessment Program (MAP). This program is described in two documents: CERP Monitoring and Assessment Plan: Part 1, Monitoring and Supporting Research (RECOVER 2004) and draft Monitoring and Assessment Plan (MAP), Part 2 2006 Assessment Strate gy for the MAP (RECOVER 2006b).

RECOVER will produce technical reports (referre d to as system status reports) every two years describing and interpreting ecosystem responses. During this process, hypotheses clusters will be tested, refined and updated. Updated hypotheses clusters will serve as the basis for revisions and improvements to c onceptual ecological models that depict ecosystem relationships and system-wide pe rformance measures developed from these models. Interim goals and targets are also pa rt of the performance assessment process.
These are described in Section 5.

It is necessary that a feedback loop exist between evaluation performance measures used for CERP planning (Box 1; Figure 3-2 ) and collection and assessm ent of monitoring data (Box 2; Figure 3-3 ) and. Because performance measures play an integral role in describing project performance at the system-w ide scale, it is important that evaluation tools used to evaluate system-wide perfor mance measures are developed, refined and revised as understanding of the ecosystem grow s. It is through continual collection of monitoring data, calibration an d verification of evaluation to ols, and development of new tools to evaluate ecosystem responses to CE RP implementation that the ability to plan projects to meet system-wide performance targets is improv ed. This feedback mechanism from monitoring and assessment data to eval uation tools for projec t planning is a key adaptive management principle incorporat ed into the CERP Adaptive Management Strategy.3.0 Relationship to CERP Adaptive Man agement Framework October 17, 2007

3-4 IG/IT = interim goals and targets

Figure 3-3. Box 2: Performance Assessment

3.3 References

RECOVER. 2004. CERP Monitoring and Asse ssment Plan: Part 1 Monitoring and Supporting Research. Restoration Coordina tion and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2006a. Comprehensiv e Everglades Restoration Plan Adaptive Management Strategy. Restoration Coordination and Ve rification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, Florida. April 2006. www.evergladesplan.org/pm/recover/r ecover_docs/am/rec_am_stategy_brochure. pdf

RECOVER. 2006b. Monitoring and Assessment Plan (MAP), Part 2 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, System-wide Monitoring Program (MAP)

Technical Report Conceptual Ecological

Models Hypotheses &
Performance

Measures

Assessment of Monitoring Data

To Box 3: Management and Science Integration From BOX 1: CERP Planning Project Monitoring Plans

IG/IT Assessment

Research & Modeling New Information

Triggering Events

External Peer Review Feedback

PM

PM3.0 Relationship to CERP Adaptive Man agement Framework October 17, 2007

3-5 Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. www.evergladesplan.org/pm/r ecover/recover_map_part2.aspx

USACE and SFWMD. 2007. Comprehensive Ever glades Restoration Plan Programmatic Regulations Six Program-wide Guidance Memoranda. United States Army Corps of Engineers, Jacksonville District, J acksonville, FL, and South Florida Water Management District, West Palm Beac h, FL. Revised Final Draft July 2007.4.0 Relationship of Perf ormance Measures to CERP Success October 17, 2007

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### CERP Success Points of Reference

To determine CERP’s success in restoring th e quality, quantity, timing and distribution of water to the natural system and associated ecological characteristics, RECOVER considers six “points of reference”. Each of these points is tied to a specific planning purpose and represents a different as pect of measuring CERP progress. Figure 4-1 depicts each of these points, which ar e discussed in more detail below.

Figure 4-1. Six points of reference for CERP planning activities

U 1. Pre-CERP Condition (condition prior to CERP implementation)

The first point of reference, pre-CERP conditi on, can be viewed as the starting point for
each indicator and describes the indicator’s condition prior to CERP implementation. Some state and federal monitoring programs in place prior to CERP’s inception have already supplied this information for some performance measures. For other performance measures, this information is being obtai ned through implementa tion of a monitoring program developed specifically for the CE RP. This program is laid out in the CERP Monitoring and Assessment Plan: Part 1, Monitoring and Supporting Research (RECOVER 2004). Information about an indi cator’s “pre-CERP c ondition” is provided under the Justification section on each pe rformance measure documentation sheet.

U 2. Expected CERP Performance (eval uation of performance measures)

The second point of reference anticipates the system’s pe rformance following full CERP implementation. This point of reference is currently determined during the planning process through use of hydrologi c models, other evaluation tool s, best available science, and best professional judgment. Performa nce measure indicators and targets are evaluated by comparing expected performa nce following full CERP implementation to the future without project scenario. This eval uation of performance is used in the federal planning process to outline ecological benefits expected from implementation of an individual project or a suite of projects. When applied to the CERP as a whole, evaluation of CERP alternatives provi des valuable information regarding CERP’s expected performance in meeting restoration goals. It should be emphasized that expected CERP performance, even at full proj ect implementation, is, in most cases, not equivalent to the Pre-CERP
Condition

Predicted
CERP
Performance Interim CERP
Performance (IG/IT)

CERP
Performance Full Restoration (Pre-drainage Condition)

Desired Restoration
Condition

2 5

4 3 1 64.0 Relationship of Perf ormance Measures to CERP Success October 17, 2007

4-2 desired restoration condition (fifth point of reference). It is widely recognized that CERP
alone will not achieve desired restoration condition. CERP is not the sole restoration effort taking place in South Florida. The CERP evaluation target for each measure is provided under the Predictive Metric and Target heading on the performance measure
documentation sheets.

U 3. Interim CERP Performance (assessment of interim goals and interim targets)

The third point of reference is actual measur ed condition of indicators in the field during CERP implementation to determine CERP’s incremental success toward reaching restoration goals. Currently, interim goals and interim targets (referred to as IG/IT in Figure 4-1 ), a subset of CERP performance measur es, reflect expected performance of the plan through its implementation. Monito ring of interim goal and interim target indicators throughout CERP implementation will determine status and trends in hydrological and ecological characteristics of natural areas that are being restored. Interim goals and targets are described in more detail in Section 5 of this document and in The RECOVER Team’s Recommendations for In terim Goals and Interim Targets for the Comprehensive Everglades Restoration Plan (RECOVER 2005). If a performance measure is part of this subs et it will be indicated under the Monitoring and Assessment Approach heading on performan ce measure documentation sheets.

The subset of performance measures that are being used as interim goals and targets are not the only measures being monitored during implementation; the full set of performance measures are being monitored. All will be assessed and reported on every two years in a Systems Status Report to pr ovide a broad overview of CERP progress. Interim goals and targets differ from the full set of performance measures in that most performance measures have only an end (restor ation completed) goal, not an interim goal or target.

U 4. CERP Performance (assessment of performance measures)

The fourth point of refere nce is actual CERP performance measured in the field following during and following full CERP implementation to determine success of the overall restoration effort. While similar to assessment of interim goals and interim targets, this point of referenc e refers to CERP performance as they relate to the causeand-effect hypotheses presente d in the final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006). While assessment of all performance measures will be reported every tw o years in a System Status Report, this point of reference corres ponds to assessment of indicators following full implementation. Also, assessment of inte rim goals and targets involves comparing performance measured in the field to CERP ’s expected performance, while assessment following full implementation will compare CERP 's performance measured in the field to the desired restoration condition (fifth point of reference). Another difference between the two types of assessments is that the full set of performance measures will be used for this assessment, while interim goals and targ ets were developed for only a subset of performance measure indicators. The CERP assessment target for each measure is4.0 Relationship of Perf ormance Measures to CERP Success October 17, 2007

4-3 provided under the Assessment Parameter a nd Target heading on performance measure
documentation sheets.

U 5. Desired Restoration Condition

Desired restoration condition represents the condition necessary to provide a healthy and sustainable South Florida ecosy stem. In many cases, desired restoration condition for an indicator is the same as pre- drainage, historical condition (o r full restoration, sixth point of reference); however, it is no t always possible to achieve restoration to pre-drainage conditions for some indicators because our human civilization is now a permanent part of the South Florida ecosystem. In these cases, desired restoration c ondition is something
different than historical condi tion. For example, 50 percent of the historic pre-drainage Everglades have been lost to urban and agricultural development, so increasing the Everglades’ spatial extent back to 100 percent of its historic size is not possible. The desired restoration condition for overall spatia l extent is, therefore, substantially lower than the historic condition, yet it is belie ved to be large enough to provide for a sustainable ecosystem.

Desired restoration condition for each pe rformance measure is outlined under the Restoration Expectation heading on pe rformance measure documentation sheets. Setting performance measure targets based on desired restoration condition as opposed to expected performance (second point of refere nce) is intended to provide incentive for improving upon the plan through adaptive management. For some performance measures,
desired restoration condition has not yet been clearly defined. Therefore, targets for these performance measures indicate a desired direct ion of change (increase or decrease) as opposed to a quantitative target. Desired restoration conditions will be revised as more
information becomes available.

The concept of desired restoration condition is currently being reexamined by the RECOVER Leadership Group (RLG). This s ection will be updated if necessary upon
instruction from the RLG.

U 6. Full Restoration

The sixth point of reference is full restorat ion. A fully restored South Florida ecosystem would be one that had returned to the pre- drainage condition. As di scussed above, it is not always possible to achieve restoration to pre-drainage conditions for some indicators. Given that few or no pristine pre-drainage areas exist, historical condition is often described using historical acc ounts or computer models of the ecosystem without water management structures in pl ace (e.g., Natural System Model [NSM] simulations). This point of reference is not usually required on documentation sheets, but sometimes it is provided within Justification, Relationship to Conceptual Ec ological Models, or Adaptive Assessment Hypothesis Clusters sections.4.0 Relationship of Perf ormance Measures to CERP Success October 17, 2007

4-4 4.1 References

RECOVER. 2004. CERP Monitoring and Asse ssment Plan: Part 1 Monitoring and Supporting Research. Restoration Coordina tion and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2005. The RECOVER Team’s Reco mmendations for Interim Goals and Interim Targets for the Comprehensive Ev erglades Restorati on Plan. Restoration Coordination and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonv ille, Florida, and South Florida Water Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/igit_subteam.aspx

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. www.evergladesplan.org/pm/recover/recover_map.aspx5.0 Relationship of Performance Measures to Interim Goals October 17, 2007 and Interim Targets

5-1 

### 5.0 Relationship of Performance Me asures to Interim Goals and Interim Targets

CERP system-wide performance measures prov ide targets for restoration success in 2050; interim goals and interim targets have been established to document CERP’s expected performance at five-year increm ents throughout implementation. Interim goals provide a means by which restoration succe ss may be evaluated at specific points throughout the overall planning and implementa tion process. They are established to facilitate planning, monitoring and assessment. Interim targets provide a means by which CERP’s progress towards providing for wate r-related needs of the region may be evaluated. Interim goals and targets are described in The Recover Team’s Recommendations for Interim Goals and In terim Targets for the Comprehensive Everglades Restoration Plan (RECOVER 2005). Interim goals and targets are currently being revised.

A subset of CERP system-wide performance measures was selected as indicators for interim goals and targets to document CERP performance. Additional interim goal indicators were developed for water volume and sheet flow, but ar e not currently CERP system-wide performance measures. A sheet flow performance measure has recently being developed and is under review. If an i ndicator has been used for both an interim goal or interim target and a performance measure, this information will be provided on the performance measure documentation sheet.

5.1 References

RECOVER. 2005 The RECOVER Team’s R ecommendations for Interim Goals and Interim Targets for the Comprehensive Ev erglades Restorati on Plan. Restoration Coordination and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonv ille, Florida, and South Florida Water Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/igit_subteam.aspx6.0 History of Performance Measure Development October 17, 2007

6-1 

### 6.0 History of Performan ce Measure Development

6.1 Development of Evaluation Measures

CERP was developed during the Central and Southern Florida (C&SF Project) Comprehensive Review Study, referred to as the Restudy. During the Restudy, an interagency team was created to evaluate pe rformance of plan alternatives and make performance-based recommendations. To evaluate alternatives, the interagency team was divided into subteams focusing on specific su bregions, issues, or planning objectives and constraints. Each subteam developed their ow n set of performance measures, which were then used for alternative evaluation purposes. Restudy performance measures and evaluation results are documented in Appe ndix D – Environmental Evaluation Analyses ( www.evergladesplan.org/docs/comp_plan_apr99/app_d.pdf ) of the final feasibility report for the Restudy (USACE and SFWMD 1 999). Some of the performance measures used to evaluate alternatives during the Rest udy are still being used and some have been refined as appropriate. Detailed inform ation regarding refinement of Restudy performance measures for use in current eval uations can be found in Appendix D of this
document. Additional evaluation measures have been developed based on the same processes used to develop assessment measured, which are discussed below.

6.2 Development of Assessment Measures

Progress towards restoration must be asse ssed at regular intervals during CERP implementation. CERP-specific conceptual eco logical models provide d scientific basis for development of a system-wide monitori ng design and adaptive assessment process, including performance measures for the natural system.

An initial monitoring design was developed based on CERP-specific conceptual ecological models, and associated ecological premises and hypothesis. These conceptual ecological models include only those stressors and attributes that are expected to be affected by CERP. The monitoring program is summarized in the CERP Monitoring and Assessment Plan: Part 1, M onitoring and Supporting Research (RECOVER 2004). This document referred to performance measures, but did not indicate how they would be applied to the assessment process as it was still being developed.

A draft assessment strategy has been developed and published in the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessm ent Strategy for the MAP, Final Draft (RECOVER 2006). During development of this strategy, CERP-specific conceptual ecological models were revisi ted and revised. Hypothesis cl usters representing causal linkages existing between ecosystem stressors an d biological attributes depicted in these conceptual ecological models were developed. These clusters integrate several indicators for which performance measures have been developed or can be developed. Assessments are based not upon providing a status report of individual performance measure targets, but upon testing hypothesis cl usters (RECOVER 2007).6.0 History of Performance Measure Development October 17, 2007

6-2 6.3 Development of Water Supply and Flood Protection Measures

Maintaining and enhancing the human system of South Florida is one of CERP's goals. Therefore, performance measures were de veloped to address water supply and flood protection needs of the human populace of S outh Florida. These measures are based on Florida Statutes, not concep tual ecological models.

6.4 References

RECOVER. 2004. CERP Monitoring and Assessm ent Plan: Part 1, Monitoring and Supporting Research. Restoration Coordina tion and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2007. Draft 2007 System Status Re port. Restoration Coordination and Verification Team (RECOVER) , U.S. Army Corps of E ngineers, Jacksonville, FL, and South Florida Water Management District, West Palm Beach, FL. July
2007.

USACE and SFWMD. 1999. Central and Southe rn Florida Comprehensive Review Study Final Integrated Feasibility Report a nd Programmatic Environmental Impact Statement. United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. www.evergladesplan.org/pub/re study_eis.aspx#mainreport7.0 Criteria and Guidelines for Performanc e Measure Development October 17, 2007

7-1 

### 7.0 Criteria and Guidelines for P erformance Measur e Development

A set of criteria and guidelines has been es tablished to ensure that as new performance measures are developed, or as refinements are made to existing performance measures, a single standard exists to document scientific justification of perfor mance measures and to ensure a consistent level of detail among documentation sheets.

7.1 Performance Measure Criteria

Performance measures for the natural system are derived from stressors and attributes contained in conceptual ecological models. Performance measures for the human system are presently based on water supply or flood protection policy or law.

Performance measures are chosen for their conceptual relevance and interpretation and utility. Specific criteria for performance measur es are listed below and must be followed when developing, revising and re viewing performance measures:

• A performance measure indicator is expected to change directly in relation to CERP implementation; a clear linkage must exist between the indicator and expected changes.

• A performance measure indicator should appear in a conceptual ecological model or have a strong regulatory basis.

• A performance measure should char acterize a strong indicator of ecosystem health or cause major stress on the system.

• A performance measure must contain an indicator of 1) an important ecological process (e.g., food webs, en ergy transfer), 2) an important ecological structure (e.g., fragment ation, compartment-alization, succession, disturbance, biodiversity), or 3) major environmental change (e.g., hydrology, fi re, water quality).

• A performance measure indicator sh ould be a regional or system-wide indicator of CERP performance.

• A performance measure should prov ide information not provided by other performance measures being recommended for the physiographic region.

• A performance measure indicator shoul d be measurable or indirectly measured using surrogate indicators.

• A performance measure should have a relatively strong degree of predictability. Changes in indicator performance resulting from CERP implementation should be easily dist inguished from those contributed by other factors and, ideally, a mechanism should be available to evaluate future performance for project planning purposes.

• A performance measure should have a relatively low measurement uncertainty.7.0 Criteria and Guidelines for Performanc e Measure Development October 17, 2007

7-2 When developing species performance measures , consideration should also be given to the following criteria:

 Is the species a state or federally-liste d threatened or endangered species?

 Is the species a keystone species?

 Does the species have high aesthetic valu e or high public appreciation or is it a symbol of the Everglades?

 Does it have an important recreational va lue (e.g., value to fishermen, boaters or bird watchers)?

 Does it have important commer cial value (e.g., fisheries)?

7.2 Guidelines to Complete Performa nce Measure Documentation Sheets

This section provides guidelines for comp leting performance measure documentation. Criteria specified above are overarching requirements for a performance measure to be viable for use in evaluating and assessing CERP’s progress. These guidelines indicate what information needs to be provided within each section of a documentation sheet.

While it is ideal that a performance meas ure documentation sheet measure be complete, all information necessary to achieve this may not be currently available. This is especially
true for measures for which an assessment component has been developed, but for which evaluation tools are not yet available. Also, uncertainty has not been calculated for many
of the measures. These sections will be deve loped as additional tools are developed and information becomes available. Though incomp lete, these measures can still be used when performing alternative evaluations and assessments as long th ey have been through the review process described below.

Information that should be included in the documentation sheet sections are as follows:

Performance Measure Title. The title should include a de scription of the region it is associated with (e.g., Greater Everglad es, Total System, Water Supply and Flood Protection). The performance measure title shoul d provide an adequate description of the performance measure without exceeding two line s of text. The title should be centered and in bold at the top of the page.

Document Revision Date. This must be updated following any revisions. This will help ensure that those working with documentati on sheets, both those revising and applying them, are using the latest version.

Acceptance Status. The dates when the performance measure documentation reaches milestones within the approval process are also noted on the documentation sheet. The review process is outlined in mo re detail in the following section.7.0 Criteria and Guidelines for Performanc e Measure Development October 17, 2007

7-3 1.0 Desired Restoration Condition. For each indicator, this section outlines conditions and ecological characteristics e xpected to represent desired restoration of a physiographic region or a specific attribute. The desire d restoration condition does not necessarily reflect CERP expected performance; rather, it represents the leve l of restoration to achieve a healthy and sustainable ecosyst em as defined by our best scientific understanding of the system. This condition may represent a historical pre-drainage condition or some other desired condition, and is not typically quantitative in nature.
Desired restoration condition is discussed in more detail in Section 4. Predictive and assessment targets are developed based on th e desired restoration condition. The desired restoration concept is curre ntly being reexamined by the RECOVER Leadership Group (RLG).

1.1 Predictive Metric and Target. These metrics and targets represent the desired restoration conditions as represented th rough simulation modeling or other methods. They are used to compare alternative pr oject or program plan performance as determined through simulation modeling or ot her methods. Each evaluation target can be used to measure how well a component or combination of components will meet CERP’s goals compared to other components or combination of components. In order to be used for project planning activities, it is necessary for the evaluation metric and target to be quantitative in na ture and to be scientifically documented. If possible, it is important to identify if the performance m easure target is inconsistent with other performance measures in the region.

1.2 Assessment Parameter and Target. Assessment parameter and target for each performance measure serve as the basis to a ssess responses monitored in the field in natural and human systems during and following CERP implementation. Each assessment target identifies one or more el ements to be monitored and is designed to assist in determining whethe r program objectives have be en or are being attained. Assessment targets may be a quantitative restoration target, a minimum level of performance expected, or a direction of cha nge (trend) toward an expected endpoint.

2.0 Justification. The justification provides performa nce measure users with a brief, referenced history of the attribute or stresso r being used as an i ndicator and how CERP implementation is expected to affect it. This section, at a minimum, details three subjects: 1) a pre-drainage description of the indicator, 2) a description of the current state of the indicator, and 3) a descripti on of how CERP implementation is expected to affect the
indicator.

3.0 Scientific Basis or Regulatory Basis. Scientific basis for performance measures includes conceptual ecological models and assessment hypotheses. This information is provided in the following subsections. The re lationship of the performance measure to conceptual ecological models and adap tive assessment hypotheses is provided to demonstrate the performance measure indicato r’s relevance in determining restoration success with particular emphasis on how the indicator is expected to reflect CERP restoration. For those performance m easures developed based on regulatory requirements, subsections will be removed and replaced by a citation for the statute or law that requires and authori zes the performance measure.7.0 Criteria and Guidelines for Performanc e Measure Development October 17, 2007

7-4 3.1 Relationship to Conceptual Ecological Models . This section references relevant overarching regional conceptual ecological models that are discussed in Section 8 of
this document. These models can be found on the Conceptual Ecological Models web

page: www.evergladesplan.org/ pm/recover/cems.aspx . Also, the indicator is
identified as an attribute or stressor under this heading.

3.2 Relationship to Adaptive A ssessment Hypothesis Clusters. Hypothesis clusters
from the final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006), referred to as the Assessment Strategy, related to the indicator are either 1) placed verbatim in this section along with CERP-specific conceptual ecological model diagrams describing hypotheses or 2) a link is included directing the read er to hypothesis cluste rs and conceptual ecological models provided as supplement al information on the CERP System-wide Performance Measure Report web page or within the Assessment Strategy.

The CERP System-wide Performance Measure Report web page ( www.evergladesplan.org/pm/recover/perf_systemwide.aspx ) contains a link for hypothesis clusters and diagrams for each region under Supplemental Information:

• Lake Okeechobee: www.evergladesplan.org/pm/recove r/recover_docs/et/060507_pm_rep ort/hypothesis_clusters_low.pdf

• Northern Estuaries: www.evergladesplan.org/pm/recove r/recover_docs/et/060507_pm_rep ort/hypothesis_clusters_ne.pdf

• Greater Everglades: www.evergladesplan.org/pm/recove r/recover_docs/et/060507_pm_rep ort/hypothesis_clusters_ge.pdf

• Southern Estuaries: www.evergladesplan.org/pm/recove r/recover_docs/et/060507_pm_rep ort/hypothesis_clusters_se.pdf

Note that files for which the above links are provided are taken directly from the Assessment Strategy document, but contain only hypothesis clusters and conceptual ecological diagrams. Links to complete Assessment Strategy sections containing hypothesis clusters and diagrams are as follows:

• Lake Okeechobee Module: www.evergladesplan.org/pm/recove r/recover_docs/map_part2/section _9_app_of_guidance_low.pdf

• Northern Estuaries: www.evergladesplan.org/pm/recove r/recover_docs/map_part2/section _9_app_of_guidance_ne.pdf7.0 Criteria and Guidelines for Performanc e Measure Development October 17, 2007

7-5 • Greater Everglades Module: www.evergladesplan.org/pm/recove r/recover_docs/map_part2/section _9_app_of_guidance_ge.pdf

• Southern Estuaries: www.evergladesplan.org/pm/recove r/recover_docs/map_part2/section _9_app_of_guidance_se.pdf

4.0 Evaluation Application. Performance measures will be applied during evaluation of project and program alternatives. Four categor ies of information are necessary to perform an alternative evaluation: evaluation pr otocol, normalized performance output, model output, and uncertainty.

4.1 Evaluation Protocol. The evaluation protocol provide s details related to 1) the tool used to evaluate the pe rformance measure, 2) features or components of the tool that are used to obtain necessary data , 3) any post-processing information or equations, and 4) procedure used to conduct the evaluati on (e.g., specific comparisons to be made, different post-processing me thods for individual locations, required statistical analysis of data).

4.2 Normalized Performance Output. Numeric performance measure results are
normalized and related to desired restora tion condition. That is, if a performance measure does not meet its required eval uation target, what is the ecological significance of the difference between the ev aluation result and the target? Typically, performance measure results are normali zed on a scale from 0 to 1.0, with 0 corresponding to fully degraded and 1.0 co rresponding to fully restored. Each 0.1-0.2 segment between the two endpoints represents a different level of restoration success. Normalizing performance measure output is useful when making comparisons among alternative plans.

4.3 Model Output. Models or other tools provi de output for each performance measure for the purposes of conducting an ev aluation of alternatives. An example of output is provided to show evaluators how information will be presented during an evaluation and to aid in general und erstanding of concepts presented.

4.4 Uncertainty. Performance measures all have related uncertainty that needs to be taken into account when performing an evaluation. The ability an evaluation method
to simulate observed conditions can be determined using a number of error statistics. Uncertainty should be continua lly reevaluated by comparison with assessment data in the adaptive management feedback loop between evaluation and assessment processes (see Section 3 of th is document). Types of unc ertainty associated with performance measure application are desc ribed in Section 16 of this document. Currently, this documentation sheet sec tion is not fully developed for most performance measures.

5.0 Monitoring and Assessment Approach. Monitoring and assessment approach specifies monitoring and assessment methods related to the performance measure7.0 Criteria and Guidelines for Performanc e Measure Development October 17, 2007

7-6 indicator. These methods are found in othe r RECOVER documents, which are referenced
on the documentation sheet.

5.1 MAP Module and Sections. This section references the appropriate module and monitoring components in the CERP Monitoring and Assessment Plan: Part 1, Monitoring and Supporting Research (RECOVER 2004).

5.2 Interim Goals and Interim Targets. If applicable, this section references the interim goal and interim target indicator presented in The RECOVER Team’s Recommendation for Interim Goals and Interim Targets for the Comprehensive Everglades Restoration Plan (RECOVER 2005) that is related to the performance
measure indicator.

5.3 Assessment Approach. This section references the appropriate assessment procedure in the final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006).

6.0 Future Tool Development Needed to Support Performance Measure. Many performance measures need a dditional tools or information to be used effectively and
these needs are indicated on the documentati on sheet. This indicates limitations of the measures as well as provides justification to procure necessary resources to develop and
refine these tools. If all tools and info rmation necessary to apply the performance measure are available, then this section of the documen tation sheet is left blank.

6.1 Evaluation Tools Needed. Specific tools needed to improve prediction of indicator performance when evaluating pl ans are discussed in this section.

6.2Assessment Tools Needed. Specific tools needed to improve assessment of CERP implementation effects on the system are discussed in this section.

7.0 Notes. Any additional relevant information regarding the performance measure not
covered elsewhere in the docum entation sheet is noted in th is section. If no additional information is required, this section of the documentation sheet is left blank.

8.0 Working Group Members. The members of the working group who are responsible for developing, editing and shepherding the performance measure through its approval process are provided on the documentation sheet.

9.0 References. References used to develop the documentation sheet are cited and provided at the end of the documentation sheet. These need to be updated with each
revision to the documentation sheet.

7.3 References

RECOVER. 2004. CERP Monitoring and Assessm ent Plan: Part 1, Monitoring and Supporting Research. Restoration Coordina tion and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL,7.0 Criteria and Guidelines for Performanc e Measure Development October 17, 2007

7-7 and South Florida Water Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2005. The RECOVER Team’s Reco mmendations for Interim Goals and Interim Targets for the Comprehensive Ev erglades Restorati on Plan. Restoration Coordination and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonv ille, Florida, and South Florida Water Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/igit_subteam.aspx

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. www.evergladesplan.org/pm/recover/recover_map.aspx8.0 Conceptual Ecological Models October 17, 2007

8-1 

### 8.0 Conceptual Ecological Models

A set of physiographic regional conceptual ecological models are the driving mechanisms and scientific underpinnings that define CE RP’s ecological restoration success. These models were used to develop most of CERP’s system-wide performance measures. Hypotheses presented in the c onceptual ecological models ha ve been refined during the development of the CERP Monitoring and Assessment Plan: Part 1, Monitoring and Supporting Research (RECOVER 2004) and the final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006). These hypotheses are used as a basis for performance measure development. Exceptions are water supply and flood protectio n performance measures, which are based on legislative requirements. Models were deve loped using best availa ble science and will be updated periodically to incorporate new information.

8.1 Physiographic Conceptual Ecological Models

Physiographic conceptual ecological models were developed for South Florida to illustrate links among societal actions, enviro nmental stressors and ecological responses, and provide a basis for developi ng and testing a se t of causal hypotheses that best explain why natural systems in South Florida have been altered (Gentile et al. 2001). These models highlight attribut es of natural systems that can se rve as indicators of restoration program effectiveness. In general, concep tual ecological models developed for South Florida were designed to m eet the following purposes:

• Illustrate ecological lin ks between physical, ch emical and biological elements in specific physiograp hic regions of South Florida

• Develop a suite of ca usal hypotheses linking the most important hydrological, physical and chemical stressors with major ecological
effects and attributes as a basis fo r evaluating responses to restoration projects

• Create a set of measurable indica tors of success as a basis for evaluating and assessing how well projects meet broad, policy-level goals that have been establishe d for regional restoration program

These conceptual ecological models include all major external drivers, stressors, ecological effects, and attributes within the South Florid a ecosystem, regardless of their connection to CERP. In general, stressors are physical elements and/or chemical processes (e.g., hydropattern, phosphorus inputs, lake stages) and attributes represent biological and ecological components (e.g., wetland landscape patterns, alligators, wading birds). Changes in stressors result in effects on attributes.

Eleven regional conceptual ecological models have been developed for South Florida. Each region is delineated in Figure 8-1

.8.0 Conceptual Ecological Models October 17, 2007

8-2 Figure 8-1. Physiographic regions on South Florida8.0 Conceptual Ecological Models October 17, 2007

8-3 The regions are as follows:

• Everglades Ridge and Slough (Ogden 2005)

• Southern Marl Prairies (Davis et al. 2005a)

• Everglades Mangrove Estuar ies (Davis et al. 2005b)

• Big Cypress Regional Ecosystem (Duever 2005)

• Florida Bay (Rudnick et al. 2005)

• Biscayne Bay (Browder et al. 2005)

• Caloosahatchee Estuary (Barnes 2005)

• St. Lucie Estuary and Indian River Lagoon (Sime 2005)

• Loxahatchee Watershed (VanArman et al. 2005)

• Lake Worth Lagoon (Crigger et al. 2005)

• Lake Okeechobee (Havens 2005)

In addition to the eleven regional models, a Total System Conceptual Ecological Model has been developed (Ogden et al. 2005a). Th e purpose of this m odel is to identify primary ecosystem stressors and appropriate bi ological attributes of those stressors that are operating at the scale of the total South Florida natural system. The eleven regional models and the total system model have been compiled in a special edition of Wetlands published in December 2005. The publication al so includes an introduc tory chapter that explains the process of developing the models , discusses the history of the system, and provides an overview of the system (Ogden et al. 2005b). The documents are available
online at http://www.evergladesplan.org/pm/recover/cems.aspx

.

8.2 CERP-specific Conceptual Ecological Models

The models discussed above are intended to identify all major stressors and ecological effects for each physiogeographic region, but CE RP is only designed to address some of these stressors and effects. Also, CERP is expected to affect only portions of physiogeographic regions covered by th e conceptual ecological models ( Figure 8-2 ).

CERP-specific conceptual ecological models we re developed for use in the final draft of
the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the
MAP (RECOVER 2006), referred to as the Assessment Strategy. These models only include stressors and attributes that will be influenced by CERP implementation. They were developed from a set of hypotheses that comprise the essence of CERP restoration
and are clustered to reflect inte rdependency of some hypotheses.

CERP-specific conceptual ecological models depict stressors, attributes, and pathways CERP is expected to affect and how performance measures re late to them. CERP-specific conceptual ecological models from the Asse ssment Strategy with performance measures added are presented in the following regional sections.8.0 Conceptual Ecological Models October 17, 2007

8-4 Figure 8-2. Boundaries of CERP regional modules

Conceptual models have been developed for those total system components affected by CERP but they were not developed as part of the same effort as the other CERP-specific models. Future versions of the Assessment Strategy will contain total system hypotheses and CERP-specific conceptual models presented in this document will be revisited as part of that process.8.0 Conceptual Ecological Models October 17, 2007

8-5 8.3

U Scientific Understanding and Additional Information

While conceptual ecological models outline re lationships that define the South Florida ecosystem, hypotheses and interactions that fu rther define these re lationships require further investigation. Linkages between attri butes and stressors and specific hypotheses that govern ecosystem behavior are still be ing studied and discussed among scientists.
Because a clear answer to thes e scientific differences is no t yet available, testing and monitoring of these hypotheses is needed to refine scien tific understandings. Monitoring activities based on CERP system-wide perfor mance measures are expected to provide necessary data to answer some of theses scientific uncerta inties and to clarify hypotheses that further define ecosystem relationships.

8.4 References

Barnes, T. 2005. Caloosahatchee Estuary conceptual ecological model. Wetlands 25(4):884-897. www.evergladesplan.org/pm/recover/r ecover_docs/cems/cem_ caloosahatchee_est .pdf

Browder, J.A., R. Alleman, S. Markley, P. Ortner, P.A. Pitts. 2005. Biscayne Bay Conceptual Ecological M odel. Wetlands 25(4):854-869. www.evergladesplan.org/pm/recover/ recover_docs/cems/cem_biscayne_bay.pdf

Crigger, D.K., G.A. Graves, D.L. Fike. 2005. Lake Worth Lagoon Conceptual Ecological Model. Wetlands 25(4):943-954. www.evergladesplan.org/pm/recover/r ecover_docs/cems/cem_lake_worth_lagoon .pdf

Davis, S.M., W.F. Loftus, E.E. Gaiser, and A.E. Huffman. 2005a. Southern marl prairies conceptual ecological model. Wetlands 25(4):821-831. www.evergladesplan.org/pm/recover/r ecover_docs/cems/cem_southern_marl.pdf

Davis, S.M., D.L. Childers, J.J. Lorenz, and T.E. Hopkins. 2005b. A conceptual model of ecological interactions in the mangrove estuaries of the Florida Everglades. Wetlands 25(4):832-842. www.evergladesplan.org/pm/recover/ recover_docs/cems/cem_eg_mangrove.pdf

Duever, M.J. 2005. Big Cypress regional ec osystem conceptual ecological model. Wetlands 25(4):843-853. www.evergladesplan.org/pm/recover/ recover_docs/cems/cem_big_cypress.pdf

Gentile, J.H., M.A. Harwell, W. Cropper Jr., C.C. Harwell, D. DeAngelis, S.M. Davis, J.C. Ogden, and D. Lirman. 2001. Ecologi cal conceptual models: a framework and case study on ecosystem management for South Florida sustainability. The
Science of the Total Environment 274:213-253.8.0 Conceptual Ecological Models October 17, 2007

8-6 Havens, K.E. 2005. Lake Okeechobee conceptual ecological model. Wetlands 25(4):908-
925. www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_low.pdf

Ogden, J.C. 2005. Everglades ridge and slough conceptual ecological model. Wetlands 25(4):810-831. www.evergladesplan.org/pm/recover/ recover_docs/cems/cem_eg_ridge_slough.p
df

Ogden, J.C., S.M. Davis, T.K. Barnes, K.J. Jacobs and J.H. Gentile. 2005a. Total system conceptual ecological model. Wetlands 25(4):955-979. www.evergladesplan.org/pm/recover/r ecover_docs/cems/cem_total_system.pdf

Ogden J.C., S.M. Davis, K.J. Jacobs, T. Barnes, and H.E. Fling. 2005b. The use of conceptual ecological models to guide eco system restoration in South Florida. Wetlands 25(4):795-809. www.evergladesplan.org/pm/recover/r ecover_docs/cems/cem_use_of_cems.pdf

RECOVER. 2004. CERP Monitoring and Assessm ent Plan: Part 1, Monitoring and Supporting Research. Restoration Coor dination and Verification Program, c/o United States Army Corps of Engineer s, Jacksonville Dist rict, Jacksonville, FL, and South Florida Water Manageme nt District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. www.evergladesplan.org/pm/recover/recover_map.aspx

Rudnick, D.T., P.B. Ortner, J.A. Browder, and S.M. Davis. 2005. Florida Bay conceptual ecological model. We tlands 25(4):870-883. www.evergladesplan.org/pm/recover/ recover_docs/cems/cem_florida_bay.pdf

Sime, P. 2005. St. Lucie Estuary and Indian River Lagoon conceptual ecological model. Wetlands 25(4):898-907. www.evergladesplan.org/pm/recover/r ecover_docs/cems/cem_st_lucie_irl.pdf

VanArman, J., G.A. Graves, and D. Fike . 2005. Loxahatchee Watershed conceptual ecological model. We tlands 25(4):926-942. www.evergladesplan.org/pm/recover/ recover_docs/cems/cem_loxahatchee.pdf9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-1 Pelagic Zone

Littoral Zone

Near-shore Zone Moonshine Bay

Figure 9

- 1. Lake Okeechobee U 

### 9.0 Lake Okeechobee CERP-Specific Co nceptual Ecological Models and
Performance Measures

The final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006), referred to as the Assessment Strategy, presents six CERP-specific conceptual ecological models for Lake Okeechobee ( Figure
9-1 ). These models provide a visual description of causal pathways described in hypotheses clusters.
Each cluster and associated model focus on a key indicator for the lake: submerged aquatic vegetation (SAV), macroinvertebrates, phyto-plankton, native fish species, littoral emergent vegetation mosaic, and exotic vegetation.

The following sections briefly summarize descriptive text for hypotheses clusters and present conceptual ecological model diagrams along with how performance meas ures relate to th em. Application of performance measures during evaluation (plann ing) and assessment processes, including the hypothesis-based approach, are discussed in more detail in Section 2. Full discussions of hypotheses clusters from the draft Assessment Strategy can be accessed from the CERP System-wide Performance Measures web page: http://www.evergladesplan.org/pm/recover/perf_low.aspx

.

9.1 Submerged Aquatic Vegetation

Lake stage, major wind and wave events, nut rient concentrations, and extent of mud sediments all influence SAV in Lake Okeechobee ( Figure 9-2 ). At higher lake stages, light penetration to the bottom is reduced and area capable of supporting dense SAV is smaller. Also, at higher lake stages , pelagic and littoral fringe zones ( Figure 9-1) become hydrologically connected resulting in increas ed turbidity. Major wind and wave events can also increase turbidity and can result in large-scale destruc tion of SAV by direct physical tearing and uprooting. Elevated nutrient concentrations stimulate dense phytoplankton blooms, which in turn reduce light available for SAV growth. Under physical conditions that result in low light levels, the exotic SAV species hydrilla may have a competitive advantage over more de sirable native SAV species. Changes in the extent of mud sediments in the littoral-pela gic fringe zone resulting from changes in nutrient loading and runoff influence potenti al area available for SAV colonization.9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-2 Figure 9-2. SAV Conceptual Ecological Model with associated performance

measures

Several system-wide performance measures ha ve been developed to assess and evaluate effects of CERP implementation on Lake Ok eechobee SAV and pathways leading to it from water management and nutrient load management ( Figure 9-2 ). A vegetation mosaic measure has been developed that includes SAV. A lake stage performance measure includes a target for high lake stag e. The water quality performance measure
includes nutrient concen trations, algal blooms and light conditions, all of which affect
SAV in the lake.9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-3 9.2 Macroinvertebrates

Macroinvertebrate diversity will increase and presence of pollutant-tolerant species will
decrease in Lake Okeechobee as water ma nagement and nutrient load management changes are made as CERP is implemente d and macroinvertebra te habitat improves ( Figure 9-3 ). As the lake is management for low and moderate stages and nutrient loads are reduced, density of SAV and emergent ve getation increases. Reduced nutrient loads are expected to reduce and/or cap mud sedi ments, and increase areas underlain by sand and peat sediments. Presence of dense S AV and emergent vegetation, sand and peat sediments, and low nutrient loads will provide habitat that will sustain a more diverse population of macroinvertebrate species w ith less pollutant-t olerant species.

A CERP system-wide performance measure ha s been developed for macroinvertebrates in Lake Okeechobee ( Figure 9-3 ). Performance measures have also been developed for lake stage, water quality and vegetation mosaic , all of which affect macroinvertebrates in
the lake.

Figure 9-3. Macroinvertebrates Conceptual Ecological Model with associated performance measures9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-4 9.3 Phytoplankton

Phytoplankton in Lake Okeechobee is affected by lake water levels, nutrient concentrations, light level and SAV ( Figure 9-4 ). At high lake stage, both sediment resuspension and horizontal mixing occur, resulting in increased turbidity and phosphorus levels. Under these conditions, phy toplankton growth rates and occurrence and intensity of algal blooms increase.

Figure 9-4. Phytoplankton Conceptual Ecological Model with associated performance measures9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-5 Nitrogen to phosphorus ratio (N:P) has be en altered, shifting conditions from a phosphorus-limited to an nitrogen-limited syst em whenever the system is not light limited. Frequency of severe cyanobacteria l blooms increase under phosphorus-limited
conditions.

In deeper, more turbid pelagic region, light is the limiting factor, and favors proliferation of low-light adapted non-bloom forming sp ecies. SAV and associated epiphytes can reduce water column phosphorus concentrati ons and stabilize sediment preventing resuspension of phosphorus back into th e water column. Thes e conditions inhibit phytoplankton growth and algal bloom fr equency and intens ity when nutrient concentrations are high.

A diatom-cyanobacteria ratio system-wide pe rformance measure has been developed to assess biovolume ratio of the two types of phytoplankton as CERP is implemented ( Figure 9-4 ). The water quality performance measure includes targets for algal blooms (chlorophyll a ), along with targets for nitrogen-phos phorus ratios and light conditions, which both affect phytoplankton biovolume a nd taxonomic composition. High lake stage, which also affects this attribute, is trac ked by the lake stage performance measure.

9.4 Native Fish Species

Native fish species are affected by SAV, nut rient loads, sediment composition, exotic animal species and lake levels ( Figure 9-5 ). Increases in SAV dens ity, biomass and aerial coverage improve fish habitat and fish foraging opportunities a nd improve desirable native fish abundance and diversity. Reduced nutrient loads and improved water quality will result in increased fish diversity and a shift from less desirable rough fish to more desirable game fish. Competition from introduced exotic fauna exerts negative pressure
on desirable native fish. Reduction in m ud sediment as a consequence of water management will improve macroinvertebrate species diversity resulting in a positive impact on the food web and in an increase in desirable fish species. Prolonged low lake stage, especially during breeding season, re moves large areas of fish foraging and spawning habitat from use and negatively impacts recruitment and fish abundance.
Elevated nutrient loads and high lake levels favor develo pment of dense algal blooms. These algal blooms can result in fish kills and negative imp acts on other wildlife either through the development of anoxic condition s when blooms senesce and decay or through direct effects of cyanotoxin production.

A CERP system-wide performance measure has been developed for fish population density, age structure and c ondition in Lake Okeechobee ( Figure 9-5 ). Performance measures have also been developed for lake stage, water qualit y, diatom-cyanobacteria ration, vegetation mosaic and macroinvertebrate s, which all affect fish in the lake.9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-6 Figure 9-5. Native Fish Species Conceptu al Ecological Model with associated performance measures

9.5 Littoral Zone Emergent Vegetation Mosaic

Lake stage and exotic vegetation management affects the littoral zone emergent vegetation mosaic ( Figure 9-6 ). High lake stage can 1) cause uprooting of desirable native shoreline vegetation by wind-driven wave s, 2) transport pelagic water with high phosphorus concentrations into interior re gions of the marsh, 3) cause physiological stress in rooted emergent macrophytes re sulting in plant death, 4) prevent seed germination of some desirable species, and 5) enhance wind-driven transport of floating exotics, which form mats and can cause ex tensive physical damage through uprooting or breaking emergent plant stems. Operating La ke Okeechobee at lower overall lake stages and providing periodic recession events wi ll reverse these trends and encourage expansion of desirable native emergent vege tation. On the other hand, low water events can accelerate spread of exot ic and nuisance invasive vege tation such as torpedograss, melaleuca and cattail. However, low water even ts will stimulate germination of desirable native vegetation and encourage occurrence of fire, which may help control undesirable exotic and invasive species. Exotic vegeta tion management activities can kill desirable native plants in addition to the target plant.9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-7 The Lake Okeechobee vegetation mosaic system-wide performance measure includes targets for assessing native littoral em ergent vegetation response to CERP implementation ( Figure 9-6 ). This measure includes reduction in exotic vegetation in its restoration expectation. Th e water quality performance m easure has targets for light conditions and nutrient concentrations, whic h both affect littoral vegetation. The lake stage performance measure has targets for both low and high stage events and recession.

Figure 9-6. Littoral Zone Emergent Vegeta tion Mosaic Conceptual Ecological Model with associated performance measures9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-8 9.6 Exotic Vegetation

The littoral zone emergent vegetation mosaic is affected by expansion of exotic and undesirable species and vegetation management activity ( Figure 9-7 ). Vegetation management activities, while effectively contro lling exotic and invasive plants, have also killed desirable, native species. During high lake stages, pelagic water with high phosphorus concentrations is transported into the interior marsh resulting in loss of desirable species and an expansion of cattail and other undesirable species.

The Lake Okeechobee vegetation mosaic system-wide performance measure includes
reduction of exotics in its restoration expectation ( Figure 9-7 ). Targets for nutrient load to the lake are included in the water qua lity performance measure. The lake stage performance measure includes ta rgets for high lake stage.

Figure 9-7. Exotic Vegetation Conceptu al Ecological Model with associated performance measures9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

9-9 9.7 Lake Okeechobee Performance Measures

CERP System-wide performance measures th at relate to Lake Okeechobee are as
follows:

• Lake Okeechobee Stage

• Lake Okeechobee Water Quality

• Lake Okeechobee Diatom-Cyanobacteria Ratio

• Lake Okeechobee Vegetation Mosaic

• Lake Okeechobee Fish Population

• Lake Okeechobee Macroinvertebrates

Documentation sheets can be accessed from the Lake Okeechobee Performance Measures web page: http://www.evergladesplan.or g/pm/recover/perf_low.aspx

.

9.8 References

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. http://www.evergladesplan.org/pm/recover/recover_map.aspx10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-1 

### 10.0 Northern Estuaries CERP-Speci fic Conceptual Models and
Performance Measures

The Northern Estuaries region includes Ca loosahatchee, St. Lucie and Loxahatchee Estuaries, and Lake Worth and Indian Rive r Lagoons. Caloosahatchee Estuary is located on the Gulf Coast ( Figure 10-1) , while the other estuaries are located on the Atlantic Coast ( Figure 10-2 ). The final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006), referred to as the Assessment Strategy, presents four CERP-sp ecific conceptual ecological models for Northern Estuaries. These models provide a visual description of causal pathways described in hypotheses clusters . Clusters reflect major attr ibutes of estuarine systems expected to be affected by CERP: oyster, fish, submerged aquatic vegetation (SAV) and benthic infaunal community.

The following sections briefly summarize desc riptive text for hypot heses clusters and present conceptual ecological model diagra ms along with how performance measures relate to them. Application of performance measures duri ng evaluation (planning) and assessment processes, including the hypothesis- based approach, are discussed in more detail in Section 2. Full discussions of hypot heses clusters from the draft Assessment Strategy can be accessed from the CERP Syst em-wide Performance Measures web page: http://www.evergladesplan.org/pm/recove r/recover_docs/et/060507_pm_report/hypothesi s_clusters_ne.pdf

.

Figure 10-1. Northern Estuaries Module boundary along the Gulf Coast10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-2 Figure 10-2. Northern Estuaries Module boundar ies along the Atlantic Coast10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-3 10.2 Oyster

Reduction in oyster coverage within Northe rn Estuaries is largely due to altered freshwater inflow and changes in hydrodyna mics resulting from water management practices ( Figure 10-3 ). These changes have altered sa linity and led to sedimentation. Water management practices release signifi cant volumes of fresh water over a short period of time into estuarie s resulting in a sudden drop in salinity. This sudden drop can lead to significant oyster mortality, decreased growth, reproduction and spat recruitment. Also, undesirable shifts in the estuarine sa linity envelope can result in increased susceptibility to disease.

Figure 10-3. Oyster Conceptual Ecological Mo del with associated performance

measures

In addition to altering salinity, freshwater in flow carries sediments with silt, clay and high organic content and result in increased transport of floating aquatics, which then degrade and contribute to muck accumulati on rate. Muck accumulation makes substrate unsuitable for oyster larval recruitment and growth. Deposition of sediment on oyster shells also makes them unsuitable for spat settlement. In addition, muck accumulation muck may also impact dissolved oxygen c ontent making the area unsuitable for larval10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-4 settlement and growth. Suspended solids may clog adult oyster gill s and interfere with filtering and respiration resulting in decreased growth and health.

The Northern Estuaries Water Quality performance measure addresses water quality, including sedimentation and dissolved oxygen. A performance measure has been developed to track oyster habitat du ring and following CERP implementation

10.3 Fish

Fish communities within Northern Estuaries are negatively affected by changes in natural salinity regimes and sedimentation composition a nd rate as a result of water management practices ( Figure 10-4 ). Timing and severity of salinity fluctuations affects reproduction and growth of fish and availa bility of habitat. Natural healthy soft sediments support
diverse estuarine fish communities because benthic animal communities that thrive in soft sediments are a food source and provide ha bitat for estuarine fish. Healthy oyster bed habitat is essential for survival of oyster dw elling fish and, as discussed in the previous section, muck does not support oysters. SAV co mmunities that serve as fish habitat are also affected by salinity regime.

Figure 10-4. Fish Conceptual Ecological Model with associated performance

measures10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-5 Hydrodynamics and oceanography also affect fish habitat. Sediment deposition and distribution is directly asso ciated with stream confi guration and topography, flow dynamics, water depth, and stream bank location and proximity, thus directly influencing fish species associated with sha llow marginal sediment deposits.

CERP implementation should re sult in more natural freshw ater flows to Northern Estuaries, resulting in fewer fluctuations in salinity and less muck accumulation, which is expected to benefit fish communities. Performance measures have been developed to measure response of salinity and water quality (including sedimentati on) stressors and the fish community attribute to CERP implementation.

10.4 Submerged Aquatic Vegetation

Water management practices have altered na tural flow of fresh water into Northern Estuaries ( Figure 10-5 ) resulting in changes to salinity regimes, sediment composition, and water quality, which negatively affect SAV. Extreme fluctuations in estuarine salinity have resulted in larg e decreases in spatial extent and changes in SAV species composition. Large deposits of muck have di splaced normal sandy substrate and altered
sediment characteristics c ontributing to decreased exte nt of SAV beds. Increased nutrients, dissolved organic ma tter, and turbidity increase phytoplankton levels and water color, which decreases the amount of light th at penetrates the water column, decreasing photosynthetically-activ e radiation (PAR) at SAV blad es. PAR is further reduced by increased epiphyte growth cau sed by increased nutrient avai lability and/or decreased grazing pressure.

CERP implementation is expected to provide more natural freshwater flows to Northern Estuaries, reducing stresses caused by change s to salinity regime, water quality and water clarity that are negatively affecting SAV. Pe rformance measures have been developed for salinity and water quality stressors. Water quality indicators include water clarity and
nutrient loads and concentrations. A S AV performance measure has also been developed. These performance measures will track response of these stressors and attribute to CERP implementation.10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-6 Figure 10-5. SAV Conceptual Ecological Mode l with associated performance

measures

10.5 Benthic Infaunal Community

Benthic animals are directly or indirectly involved in most physical and chemical processes that occur in estuaries and are a very important food source for many fish and bird species. Northern Estuaries benthic co mmunities have been negatively affected by alterations in salinity regimes, sedimentation type and rate, and dissolved oxygen levels caused by water management practices ( Figure 10-6 ). Regulatory releases from Lake Okeechobee lead to sudden and dramatic drops in salinity, preventing establishment of a diverse and healthy estuarine benthic infaunal community. These releases result in widescale deposition of muck, which inhibits infaunal species establishment. Also, widespread muck deposition has depressed dissolved oxygen concentrations and increased sulfide concentrations. Such hypoxic, anoxic and/or toxic conditions result in mortality of benthic communities an d prevent larval recruitment.

CERP implementation is expected to provide more natural freshwater flows to Northern Estuaries, reducing stresses caused by change s to salinity regime, sedimentation and dissolved oxygen levels that are negatively affecting benthic communities. Performance measures have been developed for salinity, water quality (including sedimentation and dissolved oxygen levels) and benthic macroinvertebrates.10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-7 Figure 10-6. Benthic Infaunal Community Conceptual Ecological Model with associated performance measures

10.6 Northern Estuaries Performance Measures

CERP System-wide performance measures that relate to Northern Estuaries are as
follows:

• Northern Estuaries Salinity

• Northern Estuaries Water Quality

• Northern Estuaries Oyster Habitat

• Northern Estuaries Benthic Macroinvertebrates10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

10-8 • Northern Estuaries Submerged Aquatic Vegetation

• Northern Estuaries Fish Communities

Documentation sheets can be accessed from th e Northern Estuaries Performance Measure web page: http://www.evergladesplan.or g/pm/recover/perf_ne.aspx

.

10.7 References

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. http://www.evergladesplan.org/pm/recover/recover_map.aspx11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-1 

### 11.0 Greater Everglades CERP-Specific Conceptual Ecological Models
and Performance Measures

The Greater Everglades region includes J.W. Corbett Water Management Area/Pal Mar, the water conservation areas (WCAs), Ever glades National Park, mangrove estuaries along the southern coast, pa rt of Big Cypress National Preserve, and Lake Okeechobee littoral zones ( Figure 11-1 ). Lake Okeechobee littoral zones are included because wading birds and alligators utilize these areas.

Figure 11-1. Boundary of Greater Everglades within CERP influence CERP11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-2 The final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006), referred to as the Assessment Strategy, includes
the clusters of interrelat ed hypotheses for the Greate r Everglades. CERP-specific conceptual ecological models were developed to depict pathways described in hypotheses
clusters:

• Integrated Hydrology and Water Quality

• Coastal Transgression

• Tidal Channel Characteristics

• Coastal Salinity Gradients

• Mangrove Forest Production, Organic Soil Accumulation and Resilience

• Ridge and Slough Landscape Dynamics

• Plant Communities/Elevation Gradients

• Predator-Prey Interactions of Wading Birds and Aqua tic Fauna Forage Base

• Linkage of Periphyton to Higher Trophic Levels

• Everglades Crocodilian Populations

The following sections summarize descriptive text for hypothes es and present conceptual ecological models along with how performance measures rela te to them. Application of performance measures during evaluation (pla nning) and assessment process, including the hypothesis-based approach, ar e discussed in more detail in Section 2. Full discussion of hypotheses clusters from the draft Assessment Strategy can be accessed from the CERP System-wide Performance Measures web page: http://www.evergladesplan.org/pm/recove r/recover_docs/et/060507_pm_report/hypothesi s_clusters_ge.pdf

.

11.1 Integrated Hydrology and Water Quality

Direct rainfall onto a vast wetland landscape of low topographic relief resulted in sheet flow and low levels of phosphorus and other chemical constituents in the predrainage Everglades. Restoration of the Everglades ecosystem depends on restoration of volume, timing and distribution of sheet flow and on restriction of in puts of phosphorus and other chemical constituents to levels approximating those in direct rainfall.

Sheet flow, in combination with direct rainfall, produced funda mental hydrologic and landscape characteristics of th e predrainage Everglades ( Figure 11-2 ). Compartmentalization has altered or eliminat ed sheet flow and related natural system hydrologic and landscape characteristic s throughout the Ever glades. Decompartmentalization combined with resumption of natural volume, distri bution, and timing of freshwater delivery is expect ed to restore sheet flow and predrainage hydrologic and landscape characteristics to an undivided ecosystem encompassing much of WCA 3A and 3B, eastern Big Cypress and Everglades National Park. A sheet flow performance measure has recently been developed and is under review.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-3 Figure 11-2. Integrated Hydrology and Water Qu ality Conceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-4 Performance measures have been developed to measure hydrologic responses of Greater Everglades freshwater wetlands to CERP impl ementation: 1) Wet Prairie, 2) Number and Duration of Dry Events for Shark River Slough, 3) Inundation Pattern in Greater Everglades Wetlands, and 4) Extreme High and Low Water Levels in Greater Everglades Wetlands. The Wet Prairie performance measur e has recently been developed and is
under review. Performance measures have al so been developed to measure hydrologic response of mangrove estuaries to altered freshwater flows re sulting from CERP implementation: 1) Coastal Salinity Gradient s and 2) Southern Estuaries Salinity. The second measure is a Southern Estuaries perfor mance measure, but it also pertains to Everglades mangrove estuaries within the Greater Evergl ades module boundary.

Increased phosphorus concentrations and loads in agricultural runoff water, and replacement of sheet flow with canal flow s and point-source disc harges, have produced phosphorus concentration gradients downstream of canal discharge structures, shifting wetlands from oligotrophic to eutrophic stat es. Nitrogen dynamics are dominated by local cycling and processing under na tural conditions in the Everglades. Performance measures have been developed to address the state of phosphorus and nitrogen in the Greater Everglades Wetlands.

Pathways in this conceptual ecological model represent major stressors on the system, while the remaining models represent attributes. Pathways presented in this model affect attributes of all other Greater Everglades models.

11.2 Coastal Transgression

Southern Everglades’ shorel ine and coastal wetland stabil ity is determined by dynamic interaction of freshwater outflows, sea level rise, saline wate r inflow, sediment import/export rate, and response of sediment ary environment to water level changes ( Figure 11-3 ). Sustained substrate buildup in coas tal marl and mangrove environments are not capable of keeping up with sea level rise, resulting in encr oachment of marine conditions inland. Also, organic peat subs trates beneath living red mangroves and sawgrass tend to collapse and rapidly subside in response to community stress initiated by hurricanes, freeze, fire or salinity change.

Performance measures have been developed for hydrologic stressors: 1) Sheet Flow in the Everglades Ridge and Slough Landscape, 2) Water Levels at Regionally Significant Gauge Stations in Everglades National Pa rk, and 3) Southern Estuaries Salinity ( Figure
11-3 ). The sheet flow performance measure has recently been developed and is under review. Salinity gradients resulting from in teractions between fres hwater flow and sea level rise are tracked using Coastal Salinit y Gradients and Southern Estuaries Salinity performance measures. Coastal substrate acc retion is tracked by the Mangrove Forest Production/Soil Accretion performance measur e. Freshwater and Estuarine Vegetation Mosaics, and Southern Estuaries Submerge d Aquatic Vegetation performance measures
relate to conversion of coastal wetlands to sub-aqueous environments. Some of these performance measures mentioned are Southern Estuaries performance measures, but they also pertain to Everglades mangrove estuaries.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-5 Figure 11-3. Coastal Transgression Conceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-6 11.3 Tidal Channel Characteristics

Dendritic pattern, channel width and depth, flow volume, and material transport of tidal watercourses through coastal mangrove estuar ies are controlled by sea level interacting with volume, timing and distri bution of sheet flow and cha nnel flow from the southern Everglades ( Figure 11-4) . Many tidal creeks have disappeared entirely during the past century because they have been filled in with sediments and vege tation of surrounding landscapes. Reduced freshwater flow volum e and rising sea level are probable contributing factors. Restored freshwater inflow from the Everglades is expected to help sustain open watercourses thr ough the estuary that will more closely resemble historic patterns, yet sea level rise is expected to modify patterns of conn ectivity through coastal
wetlands and create increased sediment loads. With rising sea le vel, offshore marine
waters become connected to interior lakes a nd freshwater marshes, increasing tidal water area and volume. This process is expected to result in stronger tidal currents through channels resulting in increased erosion and widening of those channels. Such conditions are expected to result in an increased import and/or export of partic ulates, nutrients and dissolved organics.

A performance measure, Tidal Creek Sustaina bility, has been developed to track effects
of restoration and sea level rise on tidal creeks. Severa l hydrologic performance measures that pertain to Tidal Channel Characteristics Conceptual Ecological Model stressors are 1) Sheet Flow in the Everglades Ridge and Slough Landscape, 2) Water Levels at Regionally Significant Gauge Stations in Ev erglades National Park, and 3) Southern Estuaries Salinity. These measures will track e ffects of altered flow, which will, in turn,
have an effect on tidal creeks. The sheet flow performance measure has recently been developed and is under review.

11.4 Coastal Salinity Gradients

Sheet flow in southern Ever glades prior to drainage pr oduced prolonged pooling of fresh water upstream and prolonged patterns of fr eshwater flow into mangrove estuaries. Freshwater pooling and inflow supported a wide salinity gradient, including a broad oligohaline zone, in mangrove estuaries. Reduce d freshwater flow and increased sea level rise have resulted in higher salinities in formally estuarine mangrove zones and significant saline intrusion into former fres hwater marshes of the lower Everglades. Figure 11-5 depicts these pathways.

CERP is expected to increase seasonal freshwater sheet flow to the lower Everglades. This is expected to provide a broader zone of salinity gradients in the lower Everglades and coastal wetlands and should, in the short term, reestablish an oligohaline zone in coastal wetlands. A sheet flow performance me asure has recently been developed and is currently under review. The Wa ter Levels at Regionally Significant Gauge Stations in Everglades National Park is a Southern Estu aries performance measure that pertains to water levels along the southern coast of th e Everglades. The Coastal Salinity Gradients performance measure relates to surface wa ter salinity gradients in the southern Everglades.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-7 Figure 11-4. Tidal Creek Channel Conceptual Ec ological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-8 Figure 11-5. Coastal Salinity Gradients Con ceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-9 Movement of the freshwater/saltwater inte rface in the shallow aquifer depends on intensity and duration of freshw ater flows to the lower Everglades during the dry season. As freshwater flow has decreased, saltwater ha s intruded into the aquifer. Currently, two water supply performance measures have been developed to track saltwater intrusion into the aquifer: 1) Prevent Saltw ater Intrusion of Biscayne Aquifer - Meet Minimum Flows and Levels Criteria for Biscayne Aquifer and 2) Prevent Saltwater Intrusion of Biscayne Aquifer in South Miami-Dade County. While the measures do not deal with the ecological implications of saltw ater intrusion, they are currently the only saltwater intrusion performance measures that have been developed.

11.5 Mangrove Forest, Organic Soil Accumulation and Resilience

Phosphorus availability, mangrove production and soil elevation are driven by opposing influences of sea level and sheet flow ( Figure 11-6 ). Production and organic soil accretion in coastal Everglades mangrove forests are controlled by phosphorus availability. Increased freshwa ter sheet flow caused by CERP implementation is expected
to maintain low nutrient conditions in the Ev erglades mangrove estuaries, and is being tracked by two performance measures: 1) Grea ter Everglades Wetlands Total Phosphorus (TP) Concentrations in Surface Water and 2) Greater Everglades Wetlands Nutrient Total Nitrogen (TN) Concentrations in Surface Water. These low nutrient conditions are expected to enhance belowground productivity by mangroves, which will maintain peat production and soil elevation in creases, ultimately enhanci ng the ability of these low salinity forests to maintain themselves against sea level rise. The 1) TP Concentrations in Soil and 2) Mangrove Forest Production/Soil Accretion performance measures relate to peat production and soil elevation increases.

Resilience of the mangrove forests of the coastal Everglades after disturbance by hurricanes, fires, freezes or salinity changes, is depe ndent on hydrologic flushing by either fresh or saline water, which is dr iven by sea level and sheet flow from the Everglades. A sheet flow performance meas ure has recently been developed and is currently under review. In addition to th e sheet flow performance measure, two performance measures pertain to hydrologic flushing: 1) Water Le vels at Regionally Significant Gauges Stations in Everglades National Park and 2) Southern Estuaries Salinity. Both are Southern Estuaries perfor mance measures, but they pertain to the mangrove forest along the edge of the Greater Everglades module bounda ries. If flow and flushing diminish, then wetland communities collapse. Improved freshwater flow and flushing through the lower Ever glades and coastal wetlands are expected to aid in recovery of wetlands from catastrophic se tbacks. The Wetland La ndscape Patterns – Freshwater and Estuarine Vegetation Mosa ics performance measure includes these
wetland communities.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-10 Figure 11-6. Mangrove Forest Production, Organic Soil Accumulation, and Resilience Conceptual Ecological Model wi th associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-11 11.6 Ridge and Slough Landscape Dynamics Conceptual Ecological Model

Ridge and slough landscape dynamics are mainta ined by sheet flow interacting with hydroperiod, water depth, nutrient dynamics and fire to maintain organic soil accretion and loss in a state of dynamic equilibrium ( Figure 11-7 ). Dynamic equilibrium involves a balance of particulate organic matter transport, and accumulation, oxidation and combustion of organic soil. Altered sheet fl ow magnitude, duration and direction causes disequilibrium of accretion and loss processes. Disequilibrium is exacerbated by eutrophication. Disequilibrium of accretion and loss processes causes micro-topography degradation. Degradation of micro-topography interacts w ith hydroperiod, water depth, eutrophication, fire and cattail e xpansion to reduce natural hab itat diversity and stability.

Decompartmentalization, in combination with sheet flow resumption, will restore natural features of the Everglades ridge and sl ough landscape. A sheet flow performance measure has recently been developed and is under review. Hydroperiod and water depth in the ridge and slough landscape are being a ddressed by three performance measures: 1) Number and Duration of Dry Events for Shark River Slough, 2) Inundation Pattern in Greater Everglades Wetlands, and 3) Extrem e High and Low Water Levels in Greater Everglades Wetlands. The sheet flow performance measure has recently been developed and is currently under review. Nutrient dynami cs are being addressed with performance
measures for TP and TN concentrations in surface water and TP con centrations in peat soil. Two wetland landscape pattern perf ormance measures, Ridge and Slough Community Sustainability, and Freshwater and Estuarine Vegetation Mosaics, address habitat diversity and stability.

11.7 Plant Communities/Elevation Gradients Conceptual Ecological Model

Composition and distribution of plant co mmunities along elevation gradients are determined by patterns of hydroperiod, water de pth, nutrient dynamics and fire patterns ( Figure 11-8 ). Dynamic equilibrium of the vege tation mosaic is maintained if biogeochemical processes in so il support physiological requirem ents of vegetation. It is altered if water depths or hydroperiods decr ease or increase. Anth ropogenic disturbances of hydroperiods, water depths, eutrophication, fi re patterns, land use change, and spread of exotic plants have shifted the vegeta tion mosaic away fr om historic dynamic equilibrium. More natural hydroperiods, water depths and flow regimes will reestablish and sustain ridge and slough landscape patter ns without significan t infringement on adjacent marl prairies.

Performance measures have been developed to address plant communities and elevation gradients. A sheet flow performance measure has recently been developed and is under review. Hydroperiod and water depth patterns ar e being addressed by 1) Wet Prairie, 2) Number and Duration of Dry Events for Sh ark River Slough, 3) I nundation Pattern in Greater Everglades Wetlands, and 4) Extrem e High and Low Water Levels in Greater Everglades Wetlands. The Wet Prairie performance measure has recently been developed and is under review. Nutrient dynamics are be ing addressed with pe rformance measures for TP and TN. Two performance measures, 1) Freshwater and Estuarine Vegetation Mosaics and 2) Ridge and Slough Community Su stainability, address plant communities.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-12 Figure 11-7. Ridge and Slough Landscape Dynamics Conceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-13 Figure 11-8. Plant Communities/Elevation Gradients Conceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-14 11.8 Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base Conceptual Ecological Model

Wading bird nesting colony collapse in the southe rn Everglades is attributed to declines in population densities and seasona l concentrations of marsh fi shes and other aquatic prey organisms, a shift in location and timing of these seasonal concentrations, and reduced shallow water foraging options for wa ding birds along elevation gradients ( Figure 11-9 ). Wading bird forage base has been disrup ted by disruption of dr y season water level recession patterns, multi-year wet and dry cycles, and possibly, nutrient dynamics.

Population densities of aquatic fauna are low in much of the southe rn Everglades, while
densities have increased in the artificial pools of the WCAs, which now favor larger, longer-lived species. While increa sed prey densities in these artificial pools have attracted wading bird nesting colonies to those areas after coastal colony collapse, drying pattern interruptions in the WCAs of ten disrupt prey concentra tions that are required for successful foraging by wading birds, resul ting in failure of nesting colonies.

Restoration of natural hydrologic conditions by implementing CERP is expected to restore historical patterns of water level recession and drying edges. This will reestablish distributions of prey densit ies and concentrations across the landscape. It will also concentrate wading bird prey into a successi on of high-density patc hes throughout the dry season in the remaining ridge and slough, marl prairie and coastal la ndscapes. Prey base restoration is expected to reestablish wading bi rd nesting colonies in coastal and tributary regions of the southern Evergl ades and roseate spoonbill nesti ng colonies in northeastern Florida Bay. It is also expected to increas e numbers and success of nesting wading birds, wood storks and roseate spoonbills and to allow wood storks to initiate nesting no later than January in most years.

Unusually large aggregations of nesting wa ding birds, referred to as super colonies, consisting of mostly white ibis, formed in the predrainage system in response to extreme, natural patterns of drought prior to colony fo rmation. Super colonies periodically formed along the freshwater-estuarine transition zone at lower reaches of Everglades and Big Cypress basins. A substantial reduction in freq uency of super colonies is attributed to disrupted multi-year wet and dry cycles. Reducti on in super colony size may be related to reductions in wading bird prey. Population dyna mics of crayfish may play an important role, since super colonies form when marsh fish populations would be expected to be minimal, and because white ibis feed primarily on crayfish, which are affected by both hydroperiod and nutrient dynamics.

Multi-year wet and dry cycles will also be restored by the restoration of natural hydrologic conditions. This is expected to stim ulate pulses of secondary productivity that will likely involve crayfish populations. Pulses in secondary production are expected to result in an increase in return frequency a nd size of ibis-dominated super colonies in tributary headwaters of Shark River and othe r Gulf of Mexico ma ngrove estuaries at a frequency of two or more events per decade.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-15 Figure 11-9. Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base Conceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-16 Several hydrologic performan ce measures pertain to this model: 1) Wet Prairie, 2) Number and Duration of Dry Events for Shark River Slough, 3) Inundation Pattern in Greater Everglades Wetlands, and 4) Extrem e High and Low Water Levels in Greater Everglades Wetlands. The Wet Prairie performance measure has recently been developed
and is under review. Site nutrient state is be ing addressed by TP and TN concentration measures for surface water, and TP in soils. Prey base response to restoration efforts will be tracked by the Regional Populations of Fishes, Crayfish, Grass Shrimp and Amphibians performance measure. A perfor mance measure has been developed to address wading bird foraging patterns a nd two performance measures have been developed to addre ss nesting patterns.

11.9 Linkage of Periphyton to Higher Trophi c Levels Conceptual Ecological Model

Floating mats of periphyton and bladderwor ts, which require long hydroperiods and low
TP levels to survive and e xpand, provide critical support to the Everglades’ food web, both as a food source and a refuge for aquatic macroinvertebrates ( Figure 11-10 ). These macroinvertebrates are consumed by small fis h, crayfish and grass shrimp, which in turn, are consumed by higher trophic levels such as wading birds, alligators and crocodiles. Increased freshwater delivery due to CERP implementation may broaden the zone of high periphyton productivity.

Several performance measures pertain to th is model. Response of hydroperiod to CERP restoration is being tracked by three perfor mance measures: 1) Number and Duration of Dry Events for Shark River Slough, 2) In undation Pattern in Greater Everglades Wetlands, and 3) Extreme High and Low Water Levels in Gr eater Everglades Wetlands. The Greater Everglades Wetlands TP Con centrations in Surface Water performance measure addresses site nutrient state, whic h affects periphyton mats . Several performance measures have been developed to addr ess trophic levels affected by periphyton: 1) Regional Populations of Fishes, Crayfis h, Grass Shrimp and Amphibians, 2) Wading Bird Foraging Patterns on Overdrained Wetlands, 3) American Alligator Distribution, Size, Nesting and Condition, and 4) American Crocodile-Juvenile Growth and Survival.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-17 Figure 11-10. Linkage of Periphyton to Higher Trop ic Levels Conceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-18 11.10

U Everglades Crocodilian Populations Conceptual Ecological Model

American Alligator

American alligator distribution, abundance, reproduction and body condition in the Everglades are controlled by hydroperiod and water table in rocky glades, salinity in mangrove estuaries, and water depth patterns in ridge and slough landscapes, all of which were driven by direct rainfall and sheet flow prior to drainage ( Figure 11-11 ). Shortened hydroperiod and lowered water table in rocky glades have reduced alligator abundance and reproduction because of aquatic habitat loss and reduced aquatic prey base. A positive feedback loop of increased alligato r populations and alligator holes (aquatic refugia) leading to increased aquatic fauna density (alligator prey) has been disrupted. Reduced freshwater flow into mangrove estu aries has resulted in succession of former freshwater mangrove areas to saltwater system s, reducing alligator populations in tidal rivers and tributaries. Compartmentalizati on, disrupted sheet flow , and regulatory water releases restrict alligator populations in the ridge and slough landscape by causing nest flooding, unsuitable overdrained and pooled ha bitats in WCAs, and low hatchling and juvenile survival in canal s during low water periods.

With resumption of natural flow patterns to the Everglades as CERP is implemented, the American alligator is expect ed to repopulate and resume ne sting in rocky glades and
freshwater reaches of tidal rivers in mangrove estuarie s and will increase in population size and improve in body condi tion. Three performance measur es will track response of hydroperiod and water depth patterns to CERP implementation: : 1) Number and Duration of Dry Events for Shark River Slough, 2) Inundation Pattern in Greater Everglades Wetlands, and 3) Extreme High and Low Water Levels in Greater Everglades Wetlands. Response of salinity in tidal rivers and tributaries are addressed by the Coastal Salinity Gradients performance measure. Res ponse of aquatic prey base is addressed by the Regional Populations of Fishes, Crayfis h, Grass Shrimp and Amphibians performance measure. A performance measure has also b een developed to track American alligator distribution, size and condition.

American Crocodile

In estuaries, crocodiles orient towards ar eas of low salinity and freshwater sources. Alteration of location and quantity of freshwater flow to Southern Estuaries has lowered relative density of crocodiles in estuarine areas from which fresh water has been diverted and decreased growth and survival of juven ile crocodiles throughout the estuary in areas of higher salinities ( Figure 11-11 ). Restoration of freshwater flow will result in an increase in relative density of crocodiles in areas of restored flow, such as Taylor Slough/Taylor River drainage. Reestablishing sa linity gradients will increase growth and survival of juvenile crocodiles.

Two performance measures address salinity in areas inhabited by cr ocodiles: 1) Coastal Salinity Gradients and 2) Frequency of Low Salinities and High Salinities in Florida Bay (a Southern Estuaries perf ormance measure). A performance measure has also been developed for American crocodile juvenile growth and survival.11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-19 Figure 11-11. Everglades Crocodilian Population Conceptual Ecological Model with associated performance measures11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-20 11.11 Greater Everglades Wetlands Performance Measures

Greater Everglades Wetlands perfor mance measures are as follows:

• Sheet flow in the Everglades Ri dge and Slough Landscape (under review)

• Wet Prairie (under review)

• Number and Duration of Dry Events for Shark River Slough

• Inundation Pattern in Greater Everglades Wetlands

• Extreme High and Low Water Levels in Greater Everglades Wetlands

• Greater Everglades Wetlands TP Concentrations in Surface Water

• Greater Everglades Wetlands Basinwide TP Loading and Flow-Weighted
Mean Concentration in Inflows

• Greater Everglades Wetlands Nutrient TN Concentrations in Surface Water

• TN Loads/Flow-Weighted Mean Con centration in Inflows to Greater Everglades Wetlands

• TP Concentrations in Soil

• Greater Everglades Tracer of Stor mwater Treatment Area Bypass Flows

• Greater Everglades Wetlands Sulfate Concentrations in Surface Water

• Greater Everglades Wetlands Conductivity in Surface Water

• Greater Everglades Wetlands Coastal Salinity Gradients

• Wetland Landscape Patterns - Freshwater and Estuarine Vegetation Mosaics

• Wetland Landscape Patterns - Marl Prai rie Cape Sable Sparrow Habitat

• Wetland Landscape Patterns - Ridge a nd Slough Community Sustainability

• Wetland Landscape Patterns - Tidal Creek Sustainability

• Wetland Trophic Relatio nships - Periphyton

• Wetland Trophic Relationships - Mangrove Forest Production/Soil Accretion

• Wetland Trophic Relationships - Regional Populations of Fishes, Crayfish, Grass Shrimp and Amphibians

• Wetland Trophic Relationships - Wadi ng Bird Foraging Patterns on
Overdrained Wetlands

• Wetland Trophic Relationships - Wading Bird Nesting Patterns

• Roseate Spoonbill Nesting Patterns

• Wetland Trophic Relationships - Ameri can Alligator Distribution, Size, Nesting and Condition

• American Crocodile – Juvenile Growth and Survival11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

11-21 Documentation sheets can be accessed fr om the Greater Everglades Performance Measures web page: http://www.evergladesplan.or g/pm/recover/perf_ge.aspx

.

11.12 References

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. http://www.evergladesplan.org/pm/recover/recover_map.aspx12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-1 

### 12.0 Southern Estuaries CERP-Specific Conceptual Ecological Models
and Performance Measures

Southern Estuaries influenced by CERP incl ude Florida Bay, coastal lakes inland from Florida Bay, Biscayne Bay, and estuaries with in southwest Florida’s mangrove zone from Whitewater Bay to Lostman’s River ( Figure 12-1 ). The final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP (RECOVER 2006), referred to as the Assessment Strate gy presents six CERP-specific conceptual ecological models for the Northern Estuaries. These models provide a visual description of causal pathways described in hypotheses clusters. These clusters reflect major attributes and/or stressors of systems exp ected to be affected by CERP: water quality, submerged aquatic vegetation (SAV), nearshor e community structure, nearshore nursery function, and toxins and contaminants.

Figure 12-1. Southern Estuaries within CERP’s influence12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-2 The following sections briefly summarize desc riptive text for hypot heses clusters and present conceptual ecological model diag rams along with asso ciated performance measures. Application of performance me asures during evalua tion (planning) and assessment processes, using the hypothesis-ba sed approach, are discussed in more detail in Section 2. Full discussions of hypotheses clusters from the draft Assessment Strategy can be accessed from the CERP System-wide Performance Measures web page: http://www.evergladesplan.org/pm/recove r/recover_docs/et/060507_pm_report/hypothesi s_clusters_se.pdf

.

12.1 Water Quality

Water quality in the Southern Estuaries is dependent upon the quantity, quality, timing
and distribution of fresh wate r flowing to the system ( Figure 12-2 ). Restoration of freshwater flow, both surface and ground water, by CERP will alter nutrient inputs and estuarine salinity, which will affect internal nutrient cycling and bioavailability of
nutrients. Nutrient accumulation and retention in estuaries is also affected by episodic storm events, which can export nutrient rich sediments. Spatial ex tent, duration, density and composition of phytoplankton blooms are cont rolled by several factors that will be influenced by CERP: external nutrient load ing, internal nutrient cycling (e.g., seagrass productivity/die-off, sediment resuspension), light availability, water residence time, and biomass of benthic grazers.

Figure 12-2. Southern Estuaries Water Quality Conceptual Ecological Model with associated performance measures12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-3 Four performance measures relate to the Wa ter Quality Conceptual Ecological Model. A performance measure has been developed for water levels in Everglades National Park (ENP). The Southern Estuaries Salinity pe rformance measure addresses both surface water discharge targets and salinity patterns. The Southern Estuaries Water Quality performance measure addresses both nutrients and algal blooms. A performance measure has also been developed for SAV.

12.2 Submerged Aquatic Vegetation

In Southern Estuaries, water management and land use, and episodic events affect freshwater flow, sediment loads and water quality ( Figure 12-3 ). Changes in salinity and water quality result in changes in both seagrass and benthic algae. S eagrass is affected by changes in light penetration, epiphyte load, nutrient availability, salinity, hypoxia/anoxia, sulfide toxicity and disease. Benthic alga e is affected by light penetration, nutrient availability, salinity, temperature and ch anges in seagrass density and species composition. Significant changes in benthic al gae and seagrass distribution and density can affect susceptibility to sediment resuspen sion and stability of mud banks as well as nutrient availability to other primary producers.

Figure 12-3. Submerged Aquatic Vegetation Con ceptual Ecological Model with associated performance measures12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-4 CERP implementation will alter volume, timi ng and spatial distribution of freshwater
inflow to Southern Estuaries. These alteratio ns are expected to result in changes in nutrients and salinity patterns, which will affect seagrass and benthic algae.

Several performance measures have been developed to track affects of CERP implementation on Southern Estuaries. A pe rformance measure has been developed for water levels in Everglades National Park. The Southern Estuary Salinity performance measure has targets for both salinity patterns and surface water discharge. The Southern Estuaries Water Quality performance measure has targets for nutrient loads and concentrations, water clarity/light penetrati on, algal blooms and toxicants and pathogens. An SAV performance measure has also been developed.

12.3 Nearshore Nursery Function

Shoreline and bottom configura tion, vegetation and salinity patterns are characteristics that define estuarine nursery habitat and de termine their productive capacity, and thereby abundance of species. Complex habitats increase productive capacity by reducing predation, providing a wider variety and a bundance of food organism s, reducing physical disturbance, and providing substrates for a ttachment. Alteration of volume, timing and spatial distribution of freshwater inflow th at occurred with past water management practices has decreased productive capacity of estuarine nursery gr ounds by altering both bottom and shoreline vegetation and salinity pa tterns and the area over which favorable zones of bottom vegetation and salinity overlap ( Figure 12-4 ).

One of CERP’s goals is to expand, in both space and time, favorable conditions for estuarine species that were historically char acteristic of coastal wetlands and nearshore zones. Increased availability of complex mangrove-shoreline and se agrass habitat and a broadened salinity gradient will increase fish and macroinvertebrates diversity. Several performance measures have been develope d for tracking CERP success in restoring nearshore community structure. Freshwater inflow patterns are simulated and determined using water levels at Everglades Nationa l Park gauge stations and surface water discharges. Surface water discharges are used as surrogate indicators in the Southern Estuaries Salinity performance measure. This measure also uses salinity patterns/gradients as indicators. Several at tributes including SAV, pink shrimp and associated epifauna, and fish are also used as indicators in performance measures for the
Southern Estuaries.

12.4 Nearshore Community

Many nearshore community habitats in Southe rn Estuaries have been diminished or eliminated by past and current water manageme nt practices. Waters that are consistently of intermediate salinity tend to support highly productive, but relatively low diversity, plant and animal communities. In many near shore areas of Biscayne and Florida Bays,
freshwater flow is so variable that dow nstream salinity regimes are suboptimal for freshwater, brackish and ma rine organisms alike.12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-5 Figure 12-4. Nearshore Nursery Function Conceptual Ecological Model with associated performance measures

CERP is expected to restore freshwater infl ow patterns to this re gion, which is expected to restore salinity patterns, and seagrass and mangrove communities ( Figure 12-5 ). Restoration of salinity regime and plan t communities and will provide dynamic and structural habitat, and habitat overlap for nearshore animal communities.

Performance measures have been developed to track the CERP success in restoring nearshore community in the Southern Estuar ies. Two performance measures have been developed for stressors: water levels in ENP and salinity. The salinity performance measure has targets for surface water discharges, as well as for salinity patterns/gradients.
Performance measures have also been deve loped for three attrib utes of Southern Estuaries nearshore community structure: SAV, fish community, and juvenile pink shrimp and associated epifauna.12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-6 Figure 12-5. Nearshore Community Conceptual Ec ological Model with associated performance measures

12.5 Toxins and Contaminants

Toxins and other contaminants are conveyed through surface and ground water to estuaries, where they accumulate in sediment s, and eventually increase contaminant and toxin burdens in organism s inhabiting estuaries ( Figure 12-6 ). Implementation of CERP along with increased urban and agricultural development will result in changes in
distribution and sources of fr esh and ground water entering estuaries. Sources of new
water will include waste water reuse and urban and agricultural runoff, which may
increase loads to estuaries. Water will al so be routed through areas undergoing rapid urban development and redevelopment, whic h may also increase contaminant loads. Rerouting of water through coastal wetlands may reduce loads to bays. Increase in contaminants is expected to affect bent hic community composition; growth, survival, development of invertebrates and fish; and dolphi n health. It is also expected to increase prevalence of abnormal fish changes. Change s that occur in fish and pink shrimp and associated epifauna will be tracked by performance measures developed for these
attributes.12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-7 Figure 12-6. Toxins and Contaminants Conceptual Ecological Model with associated performance measures12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

12-8 12.6 Southern Estuaries Performance Measures

The performance measures for the Sout hern Estuaries region are as follows:

• Southern Estuaries Salinity

• Water Level at Regionally Significant Gauge Stations in Everglades National Park

• Southern Estuaries Submerged Aquatic Vegetation

• Southern Estuaries Juvenile Pink Shrimp and Associated Epifauna

• Southern Estuaries Fish Community

• Southern Estuaries Water Quality

Documentation sheets can be accessed fr om the Southern Estuaries Performance Measures web page: http://www.evergladesplan.or g/pm/recover/perf_se.aspx

.

12.7 References

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. http://www.evergladesplan.org/pm/recover/recover_map.aspx13.0 Water Supply and Flood Protection Performance Measures October 17, 2007

13-1 

### 13.0 Water Supply and Flood Protection Performance Measures

As CERP projects are built, they will store water in reservoirs and underground wells that now discharge to tide. Ultimately, this will incr ease availability of fresh water resulting in
fewer water restrictions for South Florid a residents and less competition for water between people and the natural system. The Stat e of Florida’s planning goal for people’s needs is to meet existing and future municipal, industrial and agricultural water supply requirements in the region during a 1-in-10 ye ar drought event: CERP will help to meet these needs. Not only will water supplies be enhanced, but flood protection will be maintained, and in some situations, will be improved.

South Florida water managers have designa ted two service areas for water supply purposes. Lake Okeechobee Service Area (LOSA) ( Figure 13-1 ) provides water supply to the Everglades Agricultural Area, north shore of Lake Okeechobee, Caloosahatchee and St. Lucie basins, and Seminole Trib e of Florida’s Bri ghton and Big Cypress Reservations. Lower east coast counties, Palm Beach, Broward, Miami-Dade, and Monroe, are collectively referred to as Lower East Coast (LEC) Service Areas ( Figure
13-2 ). Performance measures have been develo ped for water restrictions in these areas based upon Section 373.0361(2)(a )(1) of the Florida Stat utes. Each area has a performance measure for frequency of water restrictions and duration and severity of
water restrictions.

Figure 13-1. Lake Okeechobee Service Area13.0 Water Supply and Flood Protection Performance Measures October 17, 2007

13-2 Figure 13-2. Lower East Coast Service Areas

Performance measures have also been develope d for saltwater intrusion into the Biscayne aquifer and flood protection. Sa ltwater intrusion performance measures are based upon Chapter 40E-8 of the Florid a Administrative Code and S ection 373.044 of the Florida Statutes. Flood protection performance meas ures were developed based on the Draft Interim Operational Plan (Dial and Cordy and Associates 2001).

13.5 Summary of Water Supply and Flood Protection Performance Measures

RECOVER has developed eight performance m easures to evaluate CERP effects on water supply and flood protection duri ng plan formulation and revision:

• Frequency of Water Restrictions for Lake Okeechobee Service Area

• Frequency of Water Restrictions fo r Lower East Coast Service Area13.0 Water Supply and Flood Protection Performance Measures October 17, 2007

13-3 • Potential for High Water Levels in South Miami-Dade Agricultural
Area

• Prevent Saltwater Intrusion of Bi scayne Aquifer - Meet Minimum Flows and Levels Criteria for Biscayne Aquifer

• Prevent Saltwater Intrusion of Bis cayne Aquifer in South Miami-Dade County

• Comparison of Stage Differences ofWater Levels in South MiamiDade Agricultural Area

Documentation sheets can be accessed from the Water Supply and Flood Protection Performance Measures web page: http://www.evergladesplan.org/pm /recover/perf_water_supply.aspx

.

13.6 References

Dial Cordy and Associates. 2001. Draft Environmental Impact Statement Interim Operational Plan (IOP) for the Protecti on of the Cape Sable Seaside Sparrow. Prepared for the United States Army Corp s of Engineers, Jacksonville District, Jacksonville, Florida. February 2001.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-1 

### 14.0 Total System CERP-Specific Con ceptual Ecological Models and
Performance Measures

The total South Florida ecosystem encomp asses all natural areas that were once
interconnected and embedded within the va st Everglades basin, which once extended from coast to coast and from the upper Kissim mee basin headwaters south to the Gulf or Mexico and Florida and Biscayne Bays ( Figure 14-1 ). This area includes all areas already covered by regional modules (Lake Okeechobee, Northern Estuaries, Greater Everglades and Southern Estuaries).

A conceptual ecological model has been deve loped for the total South Florida system, referred to as the Total System (Ogden et al. 2005). This model is based on defining
characteristics of the South Florida ecosystem: 1) abundant large vertebrates and aquatic prey bases, 2) animals with large spat ial requirements, 3) healthy, dynamically sustainable estuaries, 4) oligotrophic fres hwater wetlands, and 5) complex landscape mosaics and interactions. Restoration of this system will be successful once defining characteristics of the pre-altered system are recovered to the extent possible given reduction of spatial extent.

Neither the CERP Monitoring and Assessment Plan: Part 1, Monitoring and Supporting
Research (RECOVER 2004) nor th e final draft of the Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessmen t Strategy for the MAP (RECOVER 2006), referred to as the Assessment Strategy, contains a Total Sy stem module. Therefore, CERP-specific models for the Total System are presented here for the first time and the section is much longer than preceding regional sections. Like regional conceptual ecological models presented in proceeding sections, these models contain only those stressors and attributes expected to be affected by CERP.

Boundaries of the Total System ( Figure 14-1 ) used by RECOVER to consider CERP’s system-wide effects are the same as those us ed in the overarching conceptual ecological model (Ogden et al. 2005). For the most pa rt, regional modules have smaller boundaries
to limit the area considered to that affected by CERP. The purpose of the Total System module is to look at CERP’s effects system-w ide, whether effects were expected in an

area or not.

Only a few total system performance measur es have been developed to date, but many indicators in regional performance measures will provide information related to defining characteristics. These measures have been added to the CERP-specific Total System Conceptual Ecological Model di agrams along with the total sy stem measures. Additional total system performance meas ures are currently being deve loped and existing measures are being refined.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-2 Figure 14-1. Total System Conceptual Ecological Model boundary14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-3 14.1 Abundant Large Vertebrates and Aquatic Prey Bases

Large vertebrates that were abundant in the pre-drainage Everglades include white ibis, wood stork and American alligator. These species, and populations of major prey organisms upon which they feed, including marsh fishes and crayfish, represent defining characteristics of the Everglades. These attrib utes are all affected by marsh aquatic fauna prey base, hydroperiod and depth patterns, an d habitat availability and fragmentation ( Figure 14-2 ). Water management and land use pr actices have resulted in increased inputs of nutrients; loss of connectivity, sheet flow and spatial extent; introduction and spread of exotic plants and animals; and altered volume and timing of flow, distribution of regional hydropatterns, salinity gradie nts, geomorphology and topography. The relationship between large vertebrates and aqua tic prey base has also been addressed in the Predator-Prey Interactions of Wadi ng Birds and Aquatic Fauna Forage Base Conceptual Ecological Model ( Figure 11-9 ) in the Greater Everglades section of this
document.

Performance measures develope d for Greater Everglades and Southern Estuaries regions relate to stressors, effects and attributes within the A bundant Large Vertebrates and Aquatic Prey Bases pathway ( Figure 14-3 ). Measures have been developed for phosphorus and nitrogen input into and surf ace water concentrations within Greater Everglades wetlands. Hydrology performance m easures have been developed for sheet flow, water levels, flows, dry events and i nundation pattern for Greater Everglades and Southern Estuaries. Salinity performance meas ures have been developed for the southern edge of the Everglades. Greater Everglades performance measur es pertaining to attributes of this model include those for wading bi rd foraging patterns; wading bird nesting patterns; fish, crayfish, gra ss shrimp and amphibian popula tions; and alligators. These
attributes are discussed in more de tail in the following sub-sections.

White Ibis

White ibis was, and remains, the numerically dominant species of wading bird in South Florida wetlands. As many as 50,000 to 100,000 pairs nested in some years during the 1930s to early 1940s in large “super colonies” located in inland headwaters of tidal
streams at the lower end of the Everglades system (Ogden 1994). Ibis forage to a large extent in very shallow water on freshwater cr ayfish, as well as on high concentrations of
smaller size-classes of fishes. White ibis are much more nomadic than traditional in selecting nesting colony sites, with larg e numbers of birds moving quickly to form nesting colonies wherever fo raging conditions are locally favorable (Frederick and Ogden 1997). This reproductive strategy works well when ibis can forage over extensive areas of
wetlands.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-4 Figure 14-2. Abundant Large Vertebrates and Aquatic Prey Bases Conceptual Ecological Model and associated performance measures14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-5 Wood Stork

Historically, well over one-half of the total U.S. population of wood storks nested in 3-5 large colonies in South Florida (Ogden 1978) . Total number of nesting storks in South Florida prior to about 1960 may have ranged annually between 7,000 and 10,000 pairs (Ogden 1994). Storks nest primarily in locati ons where drying of wetlands produces high concentrations of right size classes of fishes (Kushlan et al. 1975, Ogden et al. 1978). Stork’s foraging strategy is to soar for long distances out of nesting colonies to locate places where water depths and fish concentrat ions are appropriate. These long foraging flights were an important factor that made it possible for storks to return annually to traditional colony sites in an environment that under natural conditions had highly variable water depth and distribution patt erns. The great expanse of pre-drainage wetlands provided an overall a bundance of prey as well as many options for long-flying adults to exploit a succession of drying wetl ands over about a four-month nesting cycle for storks. Overall, wood stork epitomized pre-drainage wetland s, in that it is a species that developed a large local population by exploiting extensive space and variable habitat
conditions that characterized the South Florida system.

Marsh Fishes

Population density, size struct ure and relative abundance of fishes in South Florida wetlands are regulated by annual duration of uninterrupted flooding. Relative abundance of fish species also responds to hydroperi od. Relative abundance a ffects size structure. Marsh fishes and associated aquatic fauna concentrate in high-density patches where birds can feed effectively as water levels recede during the dry season.

Crayfish

Crayfish are an abundant and important prey resource for many faunal species of South Florida, including several species of wadi ng birds, reptiles, amphibians and mammals (Kushlan and Kushlan 1979, Ashton and As hton 1988, Conant and Collins 1991, Choate et al. 1994, Fredrick and Spalding 1994, Tenant 1997). As prey, they provide important links between energy stored in detrital and herbaceous matter and hi gher order ve rtebrate predators (Momot et al. 1978).

American Alligator

American alligator was an abundant and ubiq uitous animal in pre-drainage wetlands. Alligators are dependent on hydrologic conditions for growth and survival (Hines et al. 1968, Fogarty 1974, Wilkinson 1983). Open wate r is required for breeding (McIlhenny 1935, Garrick and Lang 1975, Garrick and La ng 1977, Vliet 1987). Nesting success is also dependent on egg survival during an exte nded incubation period, when they can be exposed to flooding or desiccating conditions (Joanen 1969, Kushlan and Jacobsen 1990, Fleming 1991). Alligator are an important keys tone species in South Florida, where its activities have shaped the la ndscape by creating ponds and tra ils that provide important survival, foraging and movement functions for many species.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-6 14.2 Animals with Large Spatial Requirements

Animals within the South Florida system that require large spatia l requirements include white ibis, wood stork, Florid a panther and snail kite. Thes e are affected by habitat availability and fragmentation ( Figure 14-3 ). Habitat is affected by three stressors, which are driven by water management and land use: loss of connectivity, loss of spatial extent, and introduction and spread of exotic plants and animals.

White Ibis and Wood Stork

The pre-drainage Everglades system was dom inated by large populations of two species of wading birds, white ibis and wood stork, with different foraging habitats and nesting strategies (Ogden 1994, Frederick and Ogden 1997) . Ibis forage in very shallow water in wetlands that dried annually in most years. Ib is tend to forage for prey close to colony locations and, therefore, reloca te their colony sites and alter timing of nesting from year to year in responses to shifti ng locations of high prey densit ies. Storks forage on larger marsh fish, often in deeper pools that did not dry annually. As me ntioned above, storks routinely soar to forage great distances from colony sites. Historically, ibis initiated nesting in most years in mid- to late dr y seasons when regional water levels were generally low, while storks initiated nesting early in dry seasons wh en water levels were generally higher. With a comparatively short nesting cycle for ibis and a much longer cycle for storks, both species fledged young bird s into regional marshes at about the same time in the late dry season when prey concentrations in late-drying parts of the system were high. The Everglades system could support contrasting behavior al patterns of these two species because of the large spatial exte nt of the system and temporal and spatial complexity of landscape mosaics and water depths. Greater Everglades Performance measures have been developed for wadi ng bird foraging and nesting patterns ( Figure 14-
3 ).

Snail Kite

Prior to the 1920s, kites in Florida were commonly ob served at many shallow, freshwater, long-hydroperiod wetl and sites throughout much of the peninsula. Population size in pre-drainage Florida is unknown but must have numbered in the thousands. The Florida subspecies, commonly know n as the snail kite, was federally listed as endangered in 1967. Kites are highly nomadic, roost and nest colonially or in loose aggregations, and are specialized predators of freshwater ap ple snails. Long-term survival of healthy populations of kites depends on availability of numerous habitat options where kites can relocate in response to spatia lly and temporally complex we t and dry climate patterns. A Total System performance measure has been developed for snail ki te foraging conditions ( Figure 14-3 ).14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-7 Figure 14-3. Animals with Large Spatial Requirements Conceptual Ecological Model and associated performance measures14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-8 Florida Panther

Prior to drainage, Florida panthers occu rred throughout uplands and short hydroperiod wetlands of Florida. Panthers require larg e home ranges. Numerous factors influence actual home range size and repr oductive success, including ha bitat quality, prey density and landscape configuration. Panther dispersal tends to be interrupted by natural barriers (e.g., large water bodies) and anthropogenic barriers (e.g., hi ghways, urban areas, large expanses of row crops and improved pastur e) (Maehr et al. 2002, Beier et al. 2003). White-tailed deer and wild hogs are dominan t prey for panthers, while rabbits, raccoon
and armadillos were of seconda ry importance (Beier et al. 20 03). As Florida panthers are scarce and hard to track, white deer are used as a surrogate indicator ( Figure 14-3 ).

14.3 Healthy, Dynamically Sustainable Estuaries

Water management and land use changes, along with sea level rise, have altered volume, timing and distribution of fresh wate r to South Florida’s estuaries ( Figure 14-4 ). These alterations have altered natural salinity grad ients. Restoration of more natural salinity gradients and nutrient dynamics is necessa ry for healthy, dynamically sustainable estuaries. CERP goals include reestablishing more natural salinity gradients by restoring freshwater flow to estuaries. Several perf ormance measures have been developed for
freshwater flow and sali nity gradients/patterns ( Figure 14-4 ). A sheet flow performance measure has been developed for the ridge and slough landscape and is curren tly under review. The Southern Estuaries Salinity pe rformance measure has targets for surface water flow and salinity envel opes. Another Southern Estuaries performance measure has targets for water levels at gauges in Evergl ades National Park from which water flows into Florida Bay. Salinity gradient performan ce measures have also been developed for Northern Estuaries and Everglades mangrove estuaries.

Nutrient inputs to the Everglades and Lake Okeechobee have increased as a result of water management and land use changes. Increased inputs have the potential to affect nutrient dynamics within estuaries, especially with reestablishment of freshwater flow to Southern Estuaries via the Everglades. Nutrie nt input increases to Lake Okeechobee have already affected Northern Estuaries. Winds from three recent hurricanes, Francis and Jeanne in 2004 and Wilma in 2005, have caused resuspension of phosphorus-rich
sediments within Lake Okeechobee’s water column. Heavy rains have required largescale releases of these phos phorus-laden waters to tide vi a St. Lucie and Caloosahatchee Estuaries resulting in extensive algal blooms. As these events have occurred after the Total System Conceptual Ecological Model (O gden et al. 2005) was written, they are not currently reflected in the following discussions. Performance measures have been developed for nutrients in estuaries ( Figure 14-4 ).

Four indicators have been chosen to best represent estuary c onditions: 1) functional submerged aquatic vegetation (SAV)-phytopla nkton balance, 2) nitrogen-phosphorus balance, 3) American oyster, and 4) nurse ry ground function. Reasons these indicators
were chosen are discussed below.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-9 Figure 14-4. Healthy, Dynamically Sustainable Estuaries Conceptual Ecological Model and associated performance measures14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-10 Functional SAV-Phytoplankton Balance

Within estuaries and coastal lakes of the South Florida ecosystem, SAV provides habitat and nursery grounds for many fish and i nvertebrate communities (Gilmore 1977, Ogden and Zeiman 1977, Gilmore et al. 1981, Fu rse and Fox 1994). Changes in SAV distribution, composition and density due to changes in quantity, quality, timing and
distribution of freshwater flow s into coastal water bodies ( Figure 14-4 ) can be detected and remotely mapped at a system-wide scale. SAV is sensitive to water clarity, nutrient levels and salinity (Hurley 1991, Denni son et. al. 1993, Morris and Tomasko 1993, Stevenson et al. 1993). SAV communities may no t only be directly influenced by nutrient inputs from a watershed; they may influence e ffects of these nutrients by competing with phytoplankton for them and altering nutrient cy cles. Performance measures for SAV and algal blooms have been developed for Northern and Southern Estuaries ( Figure 14-4 ).

Nitrogen-Phosphorus Balance

With strong phosphorus retention, the pre-deve lopment Everglades watershed probably released low phosphorus concentrations to downstream estuaries. Even with land development and phosphorus enrichment of th e Everglades, phosphorus loads to the coast through the Everglades remain low (Rudnick et al. 1999). Hydrologic conditions strongly influence nutrient uptake via changing plant community structure and productivity,
nutrient retention and release via changing microbial (inclu ding periphyton) activity in and above the soil ( Figure 14-4 ), and changing transport. In particular, nitrogen transformations are highly sensitive to molecular oxygen concentration, and thus sensitive to hydrologic conditions. Likewise, wi thin estuaries, nutrient (both nitrogen and phosphorus) processing and availability are strongly influenced by community structure and oxygen concentrations that are in turn influenced by salinity conditions, which will change with restoration (Rudnick et al. 2005). The Southern Estuaries Water Quality performance measure pertains to nutrients.

American Oyster

Oyster reefs constitute a major habitat and their presence is indicative of a functional mesohaline community dependent upon upstream freshwater inflows ( Figure 14-4 ). Decreases in oyster harvests are attributed to habitat loss, disease and water quality problems. The primary ecological importance of the American oyster is as a filter-feeding primary consumer, as prey for numerous higher consumers, and as habitat. All of these are important in overall estuarine ecology. The filtration process resu lts in greater light penetration, promoting SAV growth immedi ately downstream from oyster bars. The American oyster is highly se nsitive to salinity and siltation. A performance measure has been developed for Northern Estuaries oyster habitat ( Figure 14-4 ).

Nursery Ground Function

South Florida forage fish and invertebrate communities fill a critical role in the estuarine food web by serving as prey for higher trophi c level species, such as game fish, water birds and dolphin. Pink shrimp is ecologica lly important in Flor ida Bay, Biscayne Bay14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-11 and mangrove estuaries of southwest Florida as a major link between food web base and top consumers, including game fish (Rut herford et al. 1982, 1983, Schmidt 1989, Koenig et al. 2001) and wading birds (P almer 1962). Pink shrimp is also economically important
as the basis of the multi-million-dollar To rtugas fishery (Upton et al. 1992) and other fisheries. Pink shrimp spawn on Tortugas groun ds; resulting larvae/post-larvae migration to Florida Bay, where they spe nd their juvenile stage, then return to Tortugas grounds to spawn. The entire cycle occurs in just a fe w months, enhancing potential for determining influencing factors. A performance measure ha s been developed for juvenile pink shrimp and associated epifauna ( Figure 14-4 ).

SAV communities within estuaries provide nurser y habitat for juvenile stages of reef and recreationally important fishes (Virnstein et al. 1983, Lewis 1984). Spotted seatrout is almost entirely dependent on estuaries thr oughout its life cycle (I verson and Tabb 1962) because it does not move offshore to spawn (Bryant et al. 1989) and may not move out of the home estuary throughout its entire life (Weinstein and Ye rger 1976). For this reason, its status may be indicative of local estu arine conditions. Performance measures have been developed for Northern and Southern Estuaries fish communities ( Figure 14-4 ).

14.4 Oligotrophic Freshwater Wetlands

Prior to development and drainage, the Ever glades was an oligotrophic wetland system that received external water and nutrient inpu ts primarily from direct rainfall (Davis 1994). Inputs of nutrients to the pre-drainage Everglades were non-point source rainfall and sheet flow with relatively low concentr ations of phosphorus. Construction of the C&SF Project’s drainage system of canals, pump stations and levees, and subsequent conversion of sawgrass plain to the Everglad es Agricultural Area, changed patterns of nutrient input to point source di scharges of agricultural drainage water (Light and Dineen 1994).

Input of nutrients, mainly phosphorus, and al teration of regional hydropatterns, which have resulted from the water management sy stem and land use changes, have affected nutrient status and dynamics of Everglades wetlands ( Figure 14-5 ). Increased nutrient
concentration in surface water and soil within these wetlands has resulted in changes to the periphyton community (Browder et al. 1994, McCormick et al. 2002) and has caused
a dramatic shift from diverse herbaceous communities to communities dominated by a few invasive exotic and native species (Davis 1994). Greater Everglades nutrient loading and hydrological performance measures relate to stressors affecti ng indicators of this defining characteristic. Hydr ologic performance measures include 1) Sheet Flow in Everglades Ridge and Slough Landscape, 2) Wet Prairie, 3) Number and Duration of Dry Events for Shark River Slough, 4) Inundation Pattern in Gr eater Everglades Wetlands, and 5) Extreme High and Low Water Levels in Greater Everglades Wetlands. The sheet flow and wet prairie performance measures are still under review.

.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-12 Figure 14-5. Oligotrophic Freshwater Wetlands Conceptual Ecological Model and associated performance measures14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-13 Indicators for this defining characteristi c are soil nutrients, surface water nutrients, periphyton community and vegetation mosaic ( Figure 14-5 ). Performance measures have been developed for the Greater Everglades re gion that relate to these indicators. Total Phosphorus (TP) Concentrations in Soil relate s to soil nutrients. Performance measures have been developed for both TP and TN c oncentrations in surf ace water and periphyton. Three Greater Everglades performance me asures pertain to vegetation mosaic: 1) Freshwater and Estuarine Vegetation Mosa ics, 2) Marl Prairi e Cape Sable Sparrow Habitat, and 3) Ridge and Sl ough Community Sustainability

14.5 Complex Landscape Mosaics and Interactions

Major landscape and topographic features of South Florida form a mosaic and a dynamic continuum from upland to freshwater wetla nd to estuarine habitats. Scrub forests, rockland hardwood and pine forests, hydric pine flatwoods, sawgrass plains, southern marl prairies, ridge and slough peatlands, cypress and hardwood swamp forests, oligohaline wetlands, mangrove forests, and es tuarine lagoons transition along gradients of elevation, substrate, hydropattern, fire a nd salinity. They are affected by alterations in gradient as well as by loss of spatial extent, inputs of nutrients, and introduction of exotic plants and animals ( Figure 14-6 ). Performance measures ha ve been developed for the Greater Everglades for nutrient inputs a nd altered hydrology. Tw o broad ecological functions of the Everglades at the total system, biodiversity a nd foraging options for mobile vertebrates, are indicators fo r this defining characteristic.

Biodiversity

Spatial extent of many South Florida landscapes is sufficiently large to sustain communities and reproducing populations of indigenous plants and animals, many of
which are limited in distributi on to specific landscapes or ha bitats. Examples include the Cape Sable seaside sparrow breeding popul ation (Pimm 1995) that are endemic to southern marl prairies and more than 100 plan t species that have been reported from that landscape (Olmstead and Loope 1984). Multiple landscapes of sufficient size thus support a species richness for th e total Everglades ecosystem that is high in comparison to that of specific landscapes and to other wetland systems with lesser landscape complexity and spatial extent. Flora co mprises approximately 850 species in 20 associations across major South Florida landscapes.

Upland landscapes strongly contribute to pl ant and vertebrate speci es richness in South Florida despite their limited spatial extent in comparison to wetlands. Rockland pine forests support 186 species of understory pl ant species (Loope et al. 1979) and 50-75 species of hardwoods, mostly of West Indian origin (Taylor and Herndon 1981), including 51 species of special concern, most of which are endemic (Gunderson 1994). Rockland tropical hammock forests support the gr eatest number of rare and threatened plants in South Florida, in cluding 59 taxa (Gunderson 1994 ). Endemic vertebrates are concentrated in limited upland areas in co mparison to more expansive wetlands, and vertebrate species that are represented by rela tively small populations are more numerous in upland habitats (Robert son and Frederick 1994).14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-14 Figure 14-6. Complex Landscape Mosaics and Interactions Conceptual Ecological Model and associated performance measures14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-15 Several performance measures have been develo ped that can be used to track biodiversity during CERP implementation. Within the Greater Everglades region, measures have been developed for the following wetland landsca pe patterns: freshwater and estuarine vegetation mosaics, marl prairie Cape Sabl e seaside sparrow habitat, ridge and slough community, and tidal creeks. Measures have been developed for vegetation mosaics
within Lake Okeechobee. Northern and S outhern Estuaries have SAV measures.

Foraging Options for Mobile Vertebrates

The large spatial extent of the natural system included topographic and physiographic variations that provided a “hierarchy of choi ces” for vertebrates in the system (Holling et al. 1994). Resulting range of foraging options sustained highly mobile fauna, including water birds, snail kites and Florida panthers during annual and inter-annual fluctuations in climate and hydrology (Ogden et al. 1978, Browder 1984, Hoffman et al. 1994). For this indicator, two Total System performance measures have been developed: Snail Kite Foraging Conditions and, as a surrogate for the Florida panther, White Tail Deer Breeding Potential.

Receding water levels produced water depths and prey concentrations suitable for wading bird foraging early in the dry season in shor t-hydroperiod wetlands, such as southern marl prairies, to be followed by a succession of favorable fora ging conditions in longerhydroperiod ridge and slough and oligohaline habitats as the dry season progressed (Ogden 1994) ( Figure 14-7 ). Progression of water-level succession and prey concentration across short and long-hydroperiod landscapes supported successful wading bird nesting from its early initiation through fledging before advent of summer rains and dispersion of prey. A performance measure ha s been developed for wading bird foraging patterns in the Greater Everglades region.

14.6 Summary of Total System Performance Measures

As mentioned in the introducti on to this section, most indi cators within this model are covered by performance measures develope d for the regions. Exceptions to this are measures for snail kite and white tail deer, wh ich is a surrogate for the Florida panther. A performance measure has also been develope d for system-wide mercury but it is not linked to this or any other c onceptual ecological model. The CERP Monitoring and Assessment Plan: Part 1, M onitoring and Supporting Research (RECOVER 2004) does contain a South Florida Mercury Bioaccumu lation Module. A summary list of Total System performance measures is as follows:

• Snail Kite Foraging Conditions

• White Tail Deer Breeding Potential

• Mercury Bioaccumulation

Documentation sheets for these performance measures can be found on the Total System Performance Measures web page: http://www.evergladesplan.org/pm /recover/perf_total_system.aspx

.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-16 14.7 References

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14-18 Joanen, T. 1969. Nesting ecology of alligators in Louisiana. Proceedings of the Annual
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Koening, C., F. Coleman, J. Cabin and T.W. Schmidt. 2001. Diet of Red Drum Sciaenops
ocellatus , and Common Snook, Centropomus undecimalis , in Florida Bay and Adjacent Waters. Final Report to Evergl ades National Park by Florida State University, Tallahassee, FL. Contract CA5280-9-9001.

Kushlan, J.A, J.C. Ogden and A.L. Higer. 1975. Relation of Water Level and Fish Availability to Wood Stork Reproduction in the Southern Everglades, Florida. United States Geological Survey, Wa shington, DC. Open File Report 75-434.

Kushlan J.A. and M.S. Kushlan. 1979. Observa tions on the crayfish in the Everglades, Florida, USA. Crustacea, supplement 5:115-120.

Kushlan, J.A. and T. Jacobsen. 1990. Envir onmental variability and the reproductive success of Everglades alligators. Journal of Herpetology 24:176-184.

Lewis, F.G. III. 1984. Distribution of m acrobenthic crustaceans associated with
Thalassia

, Halodule and bare sand substrata. Marine Ecology Progress Series
19:101-113.

Light, S.S. and J.W. Dineen. 1994. Water c ontrol in the Everglades: a historical perspective. Pages 47-84 in Davis, S.M. and J.C. Ogden (eds.), Everglades, the Ecosystem and its Restoration. St. Lucie Press, Delray Beach, FL.

Loope, L.L., D.W. Black, S. Black and G. N. Avery. 1979. Distribution and Abundance of
Flora in Limestone Rockland Pine Forests of Southeastern Flor ida. South Florida Research Center, Everglades National Park, Homestead, FL.

Maehr, D.S., E.D. Land, D.B. Shindle, O.L. Bass and T.S. Hoctor. 2002. Florida panther dispersal and conservation. Bi ological Conservation 106:187–197.

McCormick, P.V., S. Newman, S. Miao, D.E. Gawlik, D. Marley, K.R. Reddy and T.D. Fontaine. 2002. Effects of anthropogeni c phosphorus inputs on the Everglades. Pages 83-126 in Porter, K.G. (ed.), The Everglades, Florida Bay, and Coral Reefs of the Florida Keys: an Ecosystem Sourcebook. CRC Press, Boca Raton, FL.

McIlhenny, E.A. 1935. The Alligators Life History. Christopher Publishing House, Boston, MA.

Momot, W., H. Gowing and P. Jones. 1978. The dynamics of crayfish and their role in the ecosystem. American Midland Naturalist 99:10-35.

Morris, L. and D. Tomasko. 1993. Proceedi ngs and Conclusions for the Submerged Aquatic Vegetation Initiative and th e Photosynthetic Active Radiation14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-19 Workshops. St. Johns River Water Manage ment District, Palatka, FL. Special
Publication SJ93-SP13.

Ogden, J.C. 1978. Recent population trends of co lonial wading birds on the Atlantic and Gulf coastal plains. Pages 137-154 in A. Sprunt, IV, J.C. Ogden and S. Winkler (eds.), Wading Birds Restoration. Na tional Audubon Society, New York, NY, Report No. 7.

Ogden, J.C. 1994. A comparison of wading bird nesting colony dynamics (1931-1946 and 1974-1989) as an indication of ecosystem conditions in the southern Everglades. Pages 533-570 in Davis, S.M. and J.C. Ogden (eds.), Everglades, the Ecosystem and its Restoration. St. Lucie Press, Delray Beach, FL.

Ogden, J.C., J.A. Kuslan and J.T. Tilmant. 1978. The food habits and nesting success of wood storks in Everglades National Park in 1974. United States Department of the Interior, National Park Service, Wa shington, D.C. Natural Resources Report
16.

Ogden, J.C. and J.C. Zeiman. 1977. Ecologi cal aspects of cora l reef-seagrass bed contracts in the Caribbean. Pages 377-382 in Proceedings of the Third International Symposium on Coral Reefs, Un iversity of Miami, Coral Gables, FL.

Ogden, J.C., S.M. Davis, T.K. Barnes, K.J. Jacobs and J.H. Gentile. 2005. Total system conceptual ecological model. Wetlands 25(4):955-979. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_total_system. pdf

Olmstead, I.C. and L.L. Loope. 1984. Plant communities of Everglades National Park. Pages 167-184 in Gleason, P.J. (ed.), Envir onments of South Florida: Past and Present II, Miami Geological Society, Coral Gables, FL.

Palmer, R.S. 1962. Handbook of North American Birds, Volume 1. Yale University Press, New Haven, CT.

Pimm, S.L. 1995. Population Ecology of the Cape Sable Seaside Sparrow ( Ammodramus
maritima mirabilis ), Annual Report 1995. Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN.

RECOVER. 2004. CERP Monitoring and Asse ssment Plan: Part 1 Monitoring and Supporting Research. Restoration Coordina tion and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water Management District, West Palm Beach, FL.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-20 RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. http://www.evergladesplan.org/pm/recover/recover_map.aspx

Robertson, Jr., W.B. and P.C. Frederick. 1994. The faunal chapters: contexts, synthesis, and departures. Pages 709-740 in Davis, S. M. and J.C. Ogden (eds.), Everglades, the Ecosystem and its Restoration. St . Lucie Press, Delray Beach, FL.

Rudnick, D.T., Z. Chen, D. Childers, J. Boyer and T. Fontaine. 1999. Phosphorus and nitrogen inputs to Florida Bay: the im portance of the Everglades watershed.
Estuaries 22:398-416.

Rudnick, D.T., P.B. Ortner, J.A. Browder a nd S.M. Davis. 2005. Florida Bay conceptual ecological model. Wetlands 25(4):870-883.

Rutherford, E., E. Thue and D. Buker. 1982. Population Characteristics, Food Habits and Spawning Activity of Spotted Seatrout Cynoscion nebulosus in Everglades National Park, Florida. South Florida Res earch Center, Everglades National Park, Homestead, FL. Report T-668.

Rutherford, E.S., E.B. Thue and D.G. B uker. 1983. Population Structure, Food Habits, and Spawning Activity of Gray Snapper, Lutjanus griseus , in Everglades National Park. South Florida Research Center, Ev erglades National Park, Homestead, FL.
SFRC-83/02.

Schmidt, T.W. 1989. Food habits, length-weig ht relationship, and condition factor of young great barracuda, Sphyraena barracuda , (Walbaum) from Florida Bay, Everglades National Park, Florida. Bulletin of Marine Science 44:163-170.

Stevenson, J.C., L.W. Staver and K.W. Staver. 1993 Water quality associated with survival of submerged aquatic vegetation along an estuarine gradient. Estuaries
16:346-361.

Taylor, D.L. and A. Herndon. 1981. Impact of 22 Years of Fire on Understory Hardwood
Shrubs in Slash Pine Communities with in Everglades National Park. South Florida Research Center, Everglades National Park, Homestead, FL. Report T640.

Tenant, A. 1997. A Field Guide to Snakes of Florida. Gulf Publishing Company, Houston, TX.

Upton, H.F., P. Hoar and M. Upton. 1992. The Gulf of Mexico Shrimp Fishery: Profile of
a Valuable National Resource. Center for Marine Conservation, Washington, DC.14.0 Total System CERP-Specific Conceptual October 17, 2007 Ecological Models and Performance Measures

14-21 Virnstein, R.W., P.S. Mickke lson, K.D. Cairns and M.A. Capone. 1983. Seagrass beds versus sand bottoms: the trophic impor tance of their associated benthic
invertebrates. Florid a Scientist 46:363-381.

Vliet, K.A. 1987. A Quantitative Analysis of the Courtship Behavior of the American Alligator ( Alligator mississippiensis ). Ph.D. Dissertation. University of Florida, Gainesville, FL.

Weinstein, M.P. and R.W. Yerger. 1976. Elect rophoretic investiga tion of subpopulations of the spotted seatrout, Cynoscion nebulosus (Cuvuer), in the Gu lf of Mexico and Atlantic coasts of Florida. Comprehe nsive Biochemical Physiology 54B:97-102.

Wilkinson, P.M. 1983. Nesting Ecology of the American Alligator in Coastal South Carolina, Study Completion Report. A ugust 1978-September1983, South Carolina Wildlife and Marine Research Department, Charleston, SC.15.0 Review Process October 17, 2007

15-1 

### 15.0 Review Process

Performance measures will be periodically added and refined by RECOVER to incorporate new scientific information and as additional tools become available. Development of and revisions to performan ce measures are initiated within Evaluation Team regional subteams and Assessment Team module teams based on their needs for evaluating or assessing CERP success. The Ev aluation Team has four regional subteams - Greater Everglades, Southern Estuaries, Nort hern Estuaries and Lake Okeechobee - and a subteam for water supply and flood protec tion - Lake Okeechobee Service Area/Lower
East Coast Service Area. The Assessment Team has module teams (referring to modules in the CERP Monitoring and Assessmen t Plan documents [RECOVER 2004, 2006]): Greater Everglades, Southern Estuaries, No rthern Estuaries and Lake Okeechobee. Any participant in RECOVER can propos e a new performance measure to a module or a regional team

.
Ideally, a performance measure will have both evaluation and assessment applications and regional subteams and module teams will wo rk together to develop and refine a single measure. Some measures will only have one or the other due to lack of tools or information. In this case, subteams and mo dule teams will fill out portions of the performance measure documentation sheet pertaining to their application.

Basic steps of the review and acceptance process are presented in Figure 15-1 . The Evaluation Team regional subteam or Asse ssment Team module team will document the performance measure using guidelines provided in Section .0 Criteria and Guidelines for Performance Measure Development. The documentation sheet will be posted on evergladesplan.org for a 14-day review. The website will clearly note that the performance measure is “under development”. Notification will be sent via email to a broad list of interested parties, including the public, with the link to the website and an
invitation to comment. Comments will be sent to a designated editor who will address editorial comments. Technical comments will be forwarded to the team that developed the performance measure. Once comments are incorporated by the team and no controversy has arisen due to comments, th e documentation sheet will be reposted and
the notation on the we bsite will be changed to “acc epted” and the date added. If comments can not be easily addressed or a controversy develops, the performance measure will not be deemed “acceptable”. Inst ead it will stay “under development” until
issues are resolved.

An email with links to accepted performance m easures, will be sent to the same mailing list announcing when a final performance measure has been accepted and posted. The accepted performance measure is now ready to be applied for use in conducting regional evaluations/assessments. These applications in clude 1) regional evaluations conducted by the Evaluation Team, 2) development of proj ect-level performance measures by project teams, 3) development of assessment protocol s by the Assessment Team, and 4) interim goals and interim targets recommendations.15.0 Review Process October 17, 2007

15-2 Figure 15-1. Performance measure review process

15.1 References

RECOVER. 2004. CERP Monitoring and Asse ssment Plan: Part 1 Monitoring and Supporting Research. Restoration Coordina tion and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water Management District, West Palm Beach, FL. http://www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. http://www.evergladesplan.org/pm/recover/recover_map.aspx16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-1 

### 16.0 Uncertainty Associated with P erformance Measure Application

The Everglades ecosystem is complex and our understanding of its physical and biological processes, organiza tions and functions is incomplete so uncertainty is common. In general, uncertainty refers to a degree of dissatisfaction of some knowledge and expectations (Breckling an d Dong 2000). A subject is uncertain when it is not exactly known or determined, or can not be reliab ly predicted (Prigogine and Stengers 1984, Lemons 1996). Specific meaning of uncertainty may vary in different situations and is dependent on context. In our performance measures, uncertainty exists in targets, protocols, quantitative models and verbal descriptions. Uncertainty varies among performance measures in terms of types, sources and magnitude. Decision-making in ecosystem restoration always faces uncer tainty; therefore, documentation and characterization of uncertainty are important. They provide decision makers a certain level of confidence, while warning against a false sense of accuracy.

A desirable and widely used method of charact erizing uncertainty in models is to identify a probability distribution of errors in m odel output based on field data. Inferential
statistics can then be used to define confidence intervals, a nd a threshold level of risk can be assigned. When possible and appropriate, this method should be used and statistics should be documented. However, this met hod requires a large quantity of quality data. For restoration of a complex system, such as the Everglades ecosystem, long-term, sitespecific data at a large spatial scale are needed. At present, these data are lacking for many performance measures. In this situation, recognizing presence of uncertainties, their sources and trade-offs among them is the first step in characterization and can offer very
useful information to decision makers.

16.1 General Classification of Uncertainty

Uncertainty can be classified in various ways . Regan et al. (2002) cat egorized uncertainty into two main types: epistemic and linguistic uncertainty. These tw o types are discussed in the following paragraphs.

Epistemic uncertainty is associ ated with knowledge of the stat e of a system. It includes uncertainty due to limitations of measuremen t devices, insufficient data, extrapolations and interpolations, and variability over time or space. A main epistemic uncertainty for CERP pertains to hydrological and ecologica l history of the Everglades. Epistemic uncertainty includes several types:

• Measurement error and systematic error – our mental and physical limitation to observe the physical or biological world accurately

• Natural variation and inherent randomness - our ability to predict to a certain range of accuracy and inability to predict to a desired degree of accuracy

• Subjective judgment - result of interpretation of data, particularly when data are scarce and error prone. Subjectivity is a major source of16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-2 disagreement, another kind of uncertainty. Subjectivity and disagreement are to be expected when human values are involved.

Linguistic uncertainty includes vagueness, co ntext dependence, ambiguity, indeterminacy of theoretical terms, and under specificity. All of these uncerta inties arise in both natural and scientific language. Restoration effo rts involve a multidisciplinary approach incorporating many scientific, engineering, sociological, ec onomic and other disciplines. Inconsistency exists among vocabularies of th ese disciplines. Meaning of words evolves as restoration proceeds and they evolve among people at different rates. While RECOVER works hard to reduce linguistic uncer tainty, we recognize th at it still exists within the program.

It is important to recognize that tradeoff exists among different types of uncertainties. Because of these tradeoffs, we need compleme ntary targets, protocols and models. Below we briefly discuss target uncertainty and protocol uncertainty. Since models often determine both targets and protocols, model uncertainty also will be briefly discussed.
Please note that these uncertainties are all interrelated.

16.2 Target Uncertainty

Two types of targets are common in performance measures: numerical estimates and directional comparisons. Numeri cal estimates are exact numbers or ranges of numbers. In plan evaluations, quantitative projections are co mpared against the target number to assist in selecting the best alternat ive. Directional comparison does not need an exact number.
It seeks an increase or decrease.

Plans with these two types of targets may be susceptible to different kinds of uncertainty. Tradeoffs exist. For example, directional comparison often is less susceptible to systematic biases. If biases can be reasonabl y assumed to be consistent and thus cancelled in comparisons, they would not influence ra nk of plans during comparisons. On the other hand, if the target is a numerical estimate, bias more likely influences rank of plans during comparison. However, difference in di rectional comparison may or may not be interpretable, physically or biologically, or in terms of restoration success. Often, directional comparison is not adequate for quantifying restoration success and numerical
estimates are needed.

Knowledge of uncertainties is important when both potential benefits and potential damages are key concerns. If target uncertainty is high and if potential damage is costly or difficult to reverse, we may need to set a minimum safe threshold level as a constraint in plan optimization. In other words, uncerta inty is a determining factor in deciding
whether we need to focus on maximization of benefits or mini mization of potential damage or both.16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-3 16.3 Protocol Uncertainty

Often, uncertainty is lower if a performance measure is spatially or temporally more aggregated. For example, yearly averages of water elevation or animal abundance are much less uncertain than daily values. On the other hand, high levels of aggregation will miss important information, often leadi ng to homogenization and loss of natural variation. For example, timing of seasona l processes and spatia l configuration of biological communities are important components of ecosystem health and integrity. Using yearly average will to tally miss seasonal timing, a nd using seasonal averages cannot help much in restorati on of natural timing. A small error in timing can lead to a large rounding error, such as a change in month when monthl y average data are used. In the same light, selection of spatial regime al so affects uncertainty. Each indicator region, transect and sub-region has its own level of uncertainty. Again, if uncertainty of a performance measure target is high and if potential damage is costly or difficult to reverse, we may need to set a minimum safe th reshold level in protocol as a constraint in plan optimization.

16.4 Model Uncertainty

Many performance measures require models to evaluate projections or assess of system response. Models synthesize empirical in formation, including professional judgments, into a formal organized framework, and generate logical, qua ntitative projections according to given assumptions. Common a ssumptions in hydrologic planning include those about climate condition, water control structures and water control operations. Model projections based on these assumptions ca n be compared quantita tively to evaluate consequences of these assumptions in term s of specific performance measures. Thus, model projections are extremely useful for scenario selecti on. Models are also used to support monitoring design since models can be used to identify critical components of the system and missing links among components. B ecause models have formal structures, they also allow people to evaluate and characterize uncertainty explicitly and quantitatively.

Models are simplified, quantitat ive representations of real systems. Models are usually comprised of state variables and mathematic al equations linking state variables. State
variables describe state or c onditions of system components, which often are issues in decision-making and management. Equations us ually have specific functional forms and contain some prefixed numbers. These num bers are parameters. Other explicit and implicit model components include boundary conditions and spatial-temporal domains. For dynamic simulation, state variables have initial conditions. Uncertainties are associated with these model components in various ways.

A model may be used to address different qu estions and to support different performance measures. Uncertainty varies with questions, because different parts of model output vary in sensitivity to uncertainty sources and differe nt targets and protocols vary in sensitivity to model uncertainty.16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-4 Additional discussion of model uncertainty can be found in the Model Uncertainty Workshop Report (RECOVER 2002). This report can be found at the following web site: http://www.evergladesplan.org/pm/recover/ recover_docs/et/052402_mrt_uncertainty_rep ort.pdf.

Sources of Model Uncertainty

Uncertainty in model output ha ve at least four potential sources: ignorance, errors, stochasticity and inherent unpr edictability. These potential sources are discussed in the following paragraphs.

Ignorance can be a consequence of lack of knowledge, or a consequence of a conscious decision, based on technical or non-technica l considerations. Many interactions and environmental factors are ignored in models. Usually only variables of primary interest are included. In models, all ignored influen ces are implicitly represented by parameters
and functional forms thus assumed constant. Wh en these influences change, particularly
when CERP scenarios alter these influences , this kind of ignorance will bring about biases or errors in model projections.

Errors can occur in estimation of parameters , formulation of mode ls, specification of boundary and initial conditions, and comput ational procedures caused by epistemic constraints, mismatches of model representa tions and field observations, and mismatches of spatial and temporal scales. Note that er rors and bias from one source could propagate and amplify through model structure, and le ad to both qualitative and quantitative uncertainties in modeling outcomes (Gardner et al. 1980). Model parameters for three classes of models - hydrologi c, biogeochemical and ecological - vary and each has an associated level of uncertainty. In general, state-based parameters (e.g., water stage, abundance of organisms) perf orm better than rate-based parameters (e.g., water flow, productivity). Parameter error consequences can be analyzed via a technique called “uncertainty analysis”. Nevertheless, comple te, quantitative consequence characterization
of all errors and their interactions is difficult.

Many model parameters are inherently stoc hastic. They can be characterized by a probability distribution but not by one accurate number. Uncertainty due to stochasticity can be reduced by using data with a large sample size.

The system could be intrinsically unstable. Some models contain nonlinear equations and
chaos could occur in these models. When chao s occurs, even a high level of accuracy and precision in measuring state variables, parameters and model formation will not improve long-term prediction. Magnitude of uncertainty in prediction approaches the magnitude of the overall variability of th e system quickly through time.

U Simple versus Complex Models

Different types of models exist. Some are si mple and some are complex. Trade-offs exist among different types of models with respect to uncertainty. For example, simple models16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-5 may involve more ignorance. One common way to reduce uncertainty caused by ignorance is to include additional variable s into models, making them more complex. Complex models contain more parameters and ot her specific details. They represent more specific information, and thus they are more realistic. However, data requirement grow very fast to avoid potential bias in pa rameter estimation, and potential errors in
identification of functional form ula and interplay of these errors increase quickly with the level of complexity. Such kinds of errors a nd biases may bring about a large uncertainty in model outcomes. Gardner et al. (1980) f ound that complex ecological models usually amplify parameter errors.

Further, with simple models, analytical solu tions exist, which provi de a convenient base for statistics. Statistics can pr ovide measures of stochasticit y. It is very difficult to find analytical solutions for complex models. T hus, it is more difficult to design a general statistical formula for complicated simulation models. This statistical difficulty leaves room for uncertainty about and caused by stochasticity. Complex models usually 'postdict' better but may not necessarily pr edict better (Gauch 1993) . Disagreement exists among modelers in favor of simple versus co mplex models. Given a specific question, an optimal level of complexity may be r eached (Costanza and Sklar 1985, Hilborn and Mangel 1997).

Classes of Models: Hydrologic, Biogeochemical and Ecological

Three classes of models are used to support CERP planni ng: hydrologic, biogeochemical and ecological models. Each has associated uncertainty. Model uncertainty generally increases when moving from hydrologic models, to biogeochemical models, to ecological
models due to increase in both model structur al error and parameter uncertainty. Usually, hydrological data are much more abundant than that of biogeochemistry, which are much more abundant than ecological data. Another key factor that leads to this pattern of increasing uncertainty is th e relationship between hydrolog ic models and biogeochemical and ecological models. Hydrologic model output is usually used as an input parameter for both ecological and biogeochemical models. Th is linkage can lead to error propagation and magnification due to initial error in hydrol ogic models. Further discussion of specific parameter uncertainty is provided under the detailed model class discussions below.

Hydrologic Models

All CERP projects must be evaluated for hydrologic effects. Hydr ologic, hydraulic and hydrodynamic models have been proposed and developed for these projects. They are spatially-explicit, deterministic simulation models. Modeling applications include simulation of surface water system, groundwat er system, and interactive surface watergroundwater system. Water eleva tion is a common, focal-state variable for all of these models. Among them, the South Florida Wate r Management Model (SFWMM) is most frequently used in regional decision-making.16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-6 Compared with biogeochemical and ecologi cal models, hydrologic models generally have lower uncertainty due to abundant data and reliable physical rules. Usually, uncertainty of water elevation is lower than uncertainty of flow in model output.

Uncertainty analyses have been conducted at various degrees in applications of these models, although insufficiently. These analyses quantify responses of model output to errors in parameters and provide very valuable information for decision makers. Uncertainties originating from other sour ces have rarely been analyzed. A major uncertainty in application of model output is scale mismatch.

Biogeochemical Models (Water Quality Models)

A large number of biogeochemical models, or water quality models, have been planned or developed for South Florida systems. So me are spatially explicit and some are not. Focal-state variables and spat ial domains also vary. Some simulate phosphorus, and some simulate other chemicals, including meta ls. Some models simulate biogeochemical dynamics, using hydrologic model output as in put, and some have their own hydrologic engines. Most of thes e models are still under development or still require peer review.
Characterization and documentation of uncer tainty associated with output of these models are generally lacking.

Hydrologic projects undoubtedly affect biogeochemical dynamics. One particularly important aspect of uncertainty in CERP decision-making is propagation or bounding of uncertainty originated from hydrologic models. Propagation processes are not understood. Analyses are generally needed to understand and charac terize uncertainty of this group of models. In general, biogeochemi cal models have less uncertainty associated with them than ecological models.

Ecological Models and Tools

A large number of ecological models and tools have been proposed and developed for South Florida systems. This is a very di verse group of tools. They can simulate ecosystem processes, focus on community dyna mics, investigate population changes, or present landscape patterns and processes. Some models are deterministic; some stochastic. They are spatially explicit or sp atially implicit. Spatial domains vary, as do temporal resolutions and scales. Ecosystems are complex and hierarchical, and ecosystem components respond to environmental changes at different spatial and temporal scales
and domains.

Uncertainty associated with these ecological models varies greatly. When used together, these ecological models may complement each other. Common conclusion from a diverse group of models can provide a high level of confidence, which a single model alone would not be able to provide. When diffe rent models suggest opposite directions, uncertainty needs to be identified and analyzed.16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-7 When each ecological model or tool is evalua ted alone, uncertainty level is usually high
because of trade-off of various kinds of uncer tainty, such as trade-off between simple and complex designs. A universally optimal design of ecological tools is not available, although given a specific question, a specific design can be most useful and can give the
maximum level of confidence.

A particular group of ecologi cal tools are hydrologic suita bility indices. This group includes habitat suitability indices (HSIs) and spatially-explicit suitability indices (SESI). These tools are extremely simplified presenta tions of hydrologic-ecologic links. They are so simplified that they do not contain state va riables of ecological entities, and therefore do not really simulate ecological interactions . They assume that ecological processes and ecological history are unimporta nt and thus can be ignored . Often, a hydrologic surrogate is used as an ecological index. Simplicity allo ws them to be very user-friendly and easy to implement, and the results are easy to communicate. Ignorance of these tools makes them extremely unrealistic and thus difficult to link them with field observations. Often, numbers generated by these index tools are difficult to interpret ecologically.

Simplicity of HSIs allows some uncertainties to be analyzed and characterized without tremendous difficulties. Usually, uncertain ty from hydrologic model output will propagate in computation and propagation ca n be tracked. For example, averaging and aggregation of indices can lead to additiona l uncertainty. Averaging across a period of time is sensitive to uncertainty genera ted by ignorance of history leading to underestimation or under representation in indices of chronic e ffects of ecological disasters and damages. Ecological systems ty pically experience hysteresis. Hysteresis means that ecological disasters and damages occur in a short time period, and recovery from disasters and damages takes a much longer time. Slow recovery is not considered by indices. When averaged across a time period, infrequent disaster or damage and longterm consequences may not be seen.

Ignorance, unrealistic ecological presentati on, and loose link between the indices and field measurements, makes uncertainty eval uation based on field data difficult. Many indices are not scale specific and appear scale independent. This makes them easy to use with models of different scales, bu t often leads to scale mismatch.

Simulation models are more realistic presen tations. They allow ke y ecological processes to be represented and are extremely useful and can complement simple indices. Some ecological simulations are complex, and eco logical data are usually difficult and expensive to collect accurately. Thus, level of uncertainty is high, in terms of errors in parameter estimation, equation identification, natural variability a nd stochasticity, and nonlinear error propagation. Due to the comp lexity of model structure and model implementation, a high level of expertise is usually needed when applying these models to support decision-making. Communication of model uncertainty is extremely important and usually difficult. Relatively poor comm unication between modelers and model users adds another barrier and difficulty to the un certainty issue. Documentation needs to be clear, complete and easy to read. When si mulation output is used in decision making, caveats provided in the documenta tion need to be considered.16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-8 16.5 Dealing with Uncertainty

Factors Increasing Uncertainty

Complex feedback among modeling, planning, operation, management and engineering design may cause uncertainty propagation, pa rticularly in context of an evolving restoration project. Unexpected changes take place all the time. Local, regional, national and global environments change, and these ch anges are often beyond our control. Goals, objectives and constraints of projects sometim es also change. These changes may bring in more uncertainty to models, because models are forced to perform functions for which they were not originally designed. For exam ple, the SFWMM is now carrying out many jobs that had not been antic ipated when the model was conceived. Some projects may change model boundary conditions. Some projects are covering areas outside model spatial domain. Some projects need informa tion in a much bigger spatial resolution. Efforts need to be made to reduce this kind of uncertainty.

Measures Reducing Uncertainty

Standardized procedures and an integrated approach are needed to handle and control uncertainty. Breckling and Dong ( 2000) suggested the following:

• Collect available hydrologic and ecological information. These data, especially data from long-te rm observations, are necessary to evaluate temporal and sp atial variability and to identify inconsistencies in a priori model information.

• Increase field observations. Large samples can reduce errors of estimated parameters if stochasticity is the major source of uncertainty. Statistical methods provide a repert oire to estimate this uncertainty aspect. If repeated observations fail to follow presumed statistical distributions, inherent in stability or lack of knowledge of important factors may be the reason.

• Compare related cases. Comparison of similar cases may reveal a lack of information. Important proce sses and effects may be obscure in one case but more apparent in another.

• Combine different approaches. Different types of models may complement each other in terms of uncertainty. If models prone to different types of uncertainty poin t to the same direction, decisionmaking confidence increases.

• Embrace different predictions. Divergence of predictions from different types of models or among experts indicates large uncertainty. Different models may give different re sults trying to simulate the same thing and are a good indicator of uncer tainty; therefore having multiple models simulating the same thing is desirable. For example, in hurricane track predictions, multiple models are used to lend16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-9 confidence to tracks. Meteorologists spend a lot of time focusing on confidence zones in these simulations when forecasting landfall of a

storm.

• Think nonlinearly. 1) Pay attention to poten tial phase transitions and hysteresis effects. In nonlinear dynamical systems, state shift and hysteresis can occur. A small cha nge of only one of the system parameters or a marginal extern al influence can cause dramatic changes of the whole system’s beha vior and organization. Dramatic state change and hysteresis can brin g about surprises and irreversible, undesirable consequences if ecol ogists ignore signals of nonlinear processes and structural instability (Carpenter et al. 1999, Dong et al 2002). 2) Consider chaos (predict able unpredictability). Chaos prevents long-term predictions. Chao tic systems inherently increase
small uncertainties to a macros copic level. These systems are predictable only for the short term. With sound knowledge of underlying structure and processes of a system, the usual time span of reliable prediction can be estimated. In ecology, we usually do not deal with pure chaotic systems but w ith an overlay of ignorance, stochasticity, errors and chaotic dynamics.

• Be aware of scales, hierarchy and emergent properties. Observed patterns at lower organizational levels and finer spatial-temporal scales may or may not match with patterns at higher levels or large scales. The whole may be greater than the su m of the parts. Linear scaling up or down may produce biases, and scale mismatch may lead to surprise later. Multi-scale investigation and experimentation may provide further insight and reduce pot ential bias and uncertainty.

Quantification, Presentation and Documentation of Uncertainty

Decision-making needs to consider uncertainty. Thus, uncertainty needs to be
characterized and documented so that caveats can be provided to decision makers and stakeholders when performance measures are used. Complete and a ccurate quantification of uncertainty are desirable, but often impractical. Nevert heless, some measures of uncertainty can be made and are useful.

Formal uncertainty analysis and sensitivity analysis offer a variety of metrics that characterize uncertainty. Note that uncertainty analysis and sensitivity analysis are two types of techniques that typical ly characterize outcomes of parameter uncertainty, but not influences of other uncertainties. Comparis ons between model outpu t and expert opinions and among outputs of different models are very useful in identifying inconsistencies and gaps for each performance measure. Resultin g agreements and disagreements measure uncertainty. Consensus often increases conf idence; disagreements indicate uncertainty, and sometimes provide clues of potential surpri ses. Opinions of independent peer reviews can present the degree of satisfaction a nd dissatisfaction, thus are a measure of16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-10 uncertainty. Results of uncertainty and sensitiv ity analyses, expert technical reviews and independent peer reviews should be documented.

Decision-making and Uncertainty

Decision-making is often difficult in CERP planning, not only because of uncertainty involved in performance measure restoration targets, evaluation protocols and models, but also due to the complexity of the decision-making proce ss itself. Yet decisions have to be made in a timely manner. Not deciding what actions to take and delaying decisionmaking both are de facto options, which are of ten very costly and thus bad decisions.

It is desirable to make robust decisions that are error tolerant. Management should always consider potential failures in advance. Considerations should be given to both benefit maximization and minimization of damages. Ec ological damage can be very costly and difficult to reverse, including damages that result from taking no action. CERP itself is a result of regret caused by previous hydrol ogical alterations. We need to minimize potential future regret caused by insufficient restoration.

Planners should always cons ider potential failures in advance, use the Adaptive Management Strategy (RECOVER 2006), and follow precautionary principles. The Adaptive Management Strategy allows perf ormance measures, quantitative tools and project plans to evolve with new informa tion and monitoring feedback. As CERP is implemented, the Everglades ecosystems also will evolve. Monitoring projects will detect newly emerging processes and developments. C oncerns of uncertainty are also context dependent, and may vary in different situa tions. Planning and decision-making will be a continuous optimization process that continuous ly revises and adjusts project plans and designs, based on new information. Planners particularly need to be sensitive to surprises and unintended ecological consequences.

One robust strategy in ecological restorati on is to minimize human intervention and
control. Restoration decisions should atte mpt to minimize interv entions, so that enough room will be left for systems to recover from damages caused by human intervention and some safety margins will be kept. Plans with the least human intervention and controls should be chosen if ecological benefits are not significantly different among the alternatives given the uncertainty involved.

Uncertainty should not be overemphasized and should not be used as a main reason to delay decision-making. For example, overempha sis of quantitative uncertainty in ecology would put overdue burden on eco logical studies that often require long-term data.

For CERP decision-making, critical uncertain ties include quantifica tion of ecological benefits, apparent conflicts among species and ecosystem components, nature-society conflicts, and conflicts among interest groups. It is a great challenge to re duce these kinds
of uncertainties.16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-11 16.6 References

Breckling, B. and Q. Dong. 2000. Uncertainty in ecology and ecological modeling. Pages 51-73 in Joergensen, S.E. and F. Muller (eds.), Handbook of Ecosystem Theories and Management. CRC Press, Boca Raton, FL.

Carpenter, S.R., D. Ludwig and W.A. Brock. 1999. Manageme nt of eutrophication for lakes subject to potentially irreversible change. Ecol ogical Applications 9: 751-
771.

Costanza, R. and F. H. Sklar. 1985. Artic ulation, accuracy, and effectiveness of
mathematical models: a review of fres hwater wetland applic ations. Ecological Modeling 27:45-68.

Dong, Q., P. V. McCormick, F. H. Sklar, and D. L. DeAngelis. 2002. Structural instability, multiple stable states, and hysteresis in periphyton driven by phosphorus enrichment in the Everglades . Theoretical Population Biology 61(1):
1-13.

Gardner et al. 1980. Gardner, R.H.; O'Ne ill, R.V.; Mankin, J.B.; Kumar, D. 1980: Comparative error analysis of six pr edator-prey models. Ecology 61(2): 323-332.

Gauch 1993. Gauch, Jr. H.G. 1993: Prediction, parsimony and noise. American Scientist
81: 468 - 478.

Hilborn, E and H. Mangel. (eds ) 1997. The ecological detectiv e confronting models with data, University Press, Princeton, New Jersey.

Lemons, J. 1996. Scientific Uncertainty and Environmental Problem Solving. Blackwell Science, Cambridge, MA.

Prigogine, I. and I. Stengers. 1984. Order Out of Chaos: Man's New Dialogue with Nature, Bantam Books, New York, NY.

Regan, H.M., M. Colyvan, and M.A. Burg man. 2002. A taxonomy and treatment of uncertainty for ecology and conserva tion biology. Ecologica l Applications, 12(2):618-628.

RECOVER. 2002. Model Uncertainty Report. Re storation Coordinati on and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. www.evergladesplan.org/pm/recover/r ecover_docs/et/052402_mrt_uncertainty_re port.pdf

RECOVER. 2006. Comprehensive Everglades Restoration Plan Adaptive Management Strategy. Restoration Coordination and Ve rification Program, c/o United States16.0 Uncertainty Associated with Performance Measure Application October 17, 2007

16-12 Army Corps of Engineers, Jacksonville District, Jacksonville, Florida. April 2006. http://www.evergladesplan.org/pm/rec over/recover_docs/am/rec_am_stategy_bro chure.pdf17.0 Next Steps October 17, 2007

17-1 

### 17.0 Next Steps

RECOVER has identified needs to improve performance measure development and application. Each section below gives a brie f overview of identified needs and general information about how RECOVER expects to address them. Performance measure development and refinement is a dynamic process and actions identified below are first in a series of steps to continually approve upon ecological meaningful ness of performance

measures.

17.1 Future Evaluation Tools

At present, evaluation components of CERP system-wide performance measures are highly dependent on hydrologi c model output, primarily the South Florida Water Management Model (SFWMM). The SFWMM is a useful tool, but it needs to be supplemented by other hydrologic models. Als o, we need water quality and ecological models/tools to evaluate and assess performance measures.

The South Florida Water Management Dist rict (SFWMD) is developing the Regional Simulation Model (RSM). This model is a regional hydrologi c model designed to simulate coupled movement of groundwater and surface water in South Florida. Major
benefits of the RSM include increased re solution of topography over that of the SFWMM, as well as a reduced and variable grid size. Also, specific components can be developed for use with the RSM and can be ‘plugged’ into the overall model. More information on the RSM and updates on its de velopment can be found at the following
web site:

T www.sfwmd.gov/site/index.php?id=342

U T .
In an effort to identify models currently used to evaluate RECOVER performance measures, as well as unmet model needs, three classes of ex isting models were investigated: 1) hydrologic, hydraulic and hydrodynamic, 2) biogeochemical or water quality, and 3) ecological. Several major s hortcomings were recognized: 1) RECOVER lacks easily applicable ecological models; 2) RECOVER lacks peer reviewed, regionalscale water quality models; and 3) RECOVER l acks the ability to link the three classes of models listed above. Specific recommendations can be found in the Report on Evaluation Tools, Models, Work Plan, and Budgets (RECOVER 2006a). This report can be found at http://www.evergladesplan.org/pm/r ecover/system_wide_modeling.aspx . Additionally,
evaluation and assessment tool needs are id entified directly on performance measure documentation sheets posted on the web at http://www.evergladesplan.org/pm/r ecover/eval_team_perf_measures.aspx

.
Efforts are ongoing to refine and develop future tools to evaluate eco logical responses to varying project alternatives. Habitat suitabi lity indices (HSIs) and Across Trophic Level System Simulation (ATLSS) spatially-exp licit species index (SESI) models have potential, but require further cal ibration, validation and/or peer review before application. SESI models exist for American alligator, snai l kite, apple snail, wading birds, and white tailed deer. In addition to SESI models, A TLSS models include those for fish (ALFISH and ALFISHES) and sparrows, as well as high-resolution topography and hydrology
models.17.0 Next Steps October 17, 2007

17-2 Similarly, water quality models are need ed to simulate nitrogen and phosphorus dynamics. In the absence of applicable wate r quality models, regi onal evaluations will use water quality proxies such as duration and intensity of dry down, structural flows, and stormwater treatment area bypasses (freque ncy and volume). These proxies should refined in the short term to make them more quantitative until appropriate water quality models are available. Several water quali ty models are being developed. Hydrodynamic and water quality modeling tools specific to the Arthur R. Marshall Loxahatchee National Wildlife Refuge are being developed by the U.S. Fish and Wildlife Service ( sofia.usgs.gov/lox_monitor_model/ ). The SFWMD, in conjunction with the US Geological Survey (USGS) and the University of Florida, is developing a water quality
module for the RSM.

Long-term plans should link the three classes of models - hydrology, water quality and ecology - through a graphical user interface (GU I). A GUI will facilita te model runs and make them more robust by providing dynamic linkages, which allow feedback between
the different class of models.

17.2 Sensitivity of Evaluation Tools

Current modeling tools as well as related performance measures are often not sensitive enough to evaluate system-wide effects of varyi ng project alternatives. This is the result of low resolution of model input variable s, coarse resolution of the SFWMM, and disconnects between spatio-temporal scale of the SFWMM and performance measure parameter inputs. Currently, the SFWMM is the main hydrologic model used to investigate RECOVER performance measures. Low resolution of input variables comes from both lack of accuracy of field measur ements and lack of field measurements altogether throughout the system. Current meas uring tools will require further refinement to increase sensitivity of input values. Due to the vast size of the South Florida landscape, it is not always feasible to take measurem ents across the entire system. Therefore, extrapolations are made. For example, water depth measurements at gauging stations are used to estimate water depths in other locations where gauges do not exist. Depth estimates are merely extrapolations/regress ions from known depths. With increased monitoring and assessment activities and increa sed sensitivity of measurement tools will come the ability to reduce uncertainty a ssociated with these extrapolations. The implementation of the CERP Monitoring and Assessment Plan, Part 1, Monitoring and Supporting Research (RECOVER 2004) and the final draft of the Monitoring and Assessment Plan (MAP), Part 2 2006 Assessment Strategy for the MAP (RECOVER 2006b), referred to as the Assessment Strategy has begun this process.

In addition to resolution of model inputs, the SFWMM is very insensitive to project
alternative effects outside the model domain as well as small project s within the domain. The SFWMM was originally used to compar e alternative plans dur ing the Restudy (see Section 6.1 and Appendix D for more detaile d discussion of the Restudy and Appendix D. On this broad scale, which containe d all CERP projects, the SFWMM was very effective at understanding system -wide effects. When the sele cted plan is divided into component projects, the model is not as effective. The SFWMM is extremely coarse, based on a 2-mile by 2-mile mesh grid size. A two-mile transect in the landscape may17.0 Next Steps October 17, 2007

17-3 cross several habitat types including ridge a nd slough, wet prairie and tree island habitats.
The RSM will have increased resolution of topography and reduced grid size compared to the SFWMM. Reducing the grid size from 2 miles by 2 miles to a variable-mesh triangular matrix approximately 0.5 miles and 1.0 mile per side for urban and natural areas, respectively, will provide greater sensitivity. Greater sensitivity will potentially make current performance measures more eff ective at detecting differences in project
alternatives.

Additionally, vertical accuracy (depth and elevation) of the SFWMM is within ± 6 inches. This resolution makes it very difficult to determine effects of project alternatives. Based on Natural System Model (NSM) topography, from Indicator Region 110 in northern WCA 2A to Indicator Region 129 in northeast Shark River Slough (Everglades National Park), the change in elevation is a pproximately 7 feet, or 2.1 inches per mile,
across the 40-mile transect. To determine e ffects of individual or smaller groups of projects, increased sensiti vity will be required.

Disconnect between timing and distribution of field measurements (and performance measure inputs) and optimal timing of the SFWMM can cause additi onal problems with sensitivity. Many field measurements, such as those taken at water management structures, are taken at scales of seconds to mi nutes or hours, wher eas SFWMM functions more appropriately on longer time-steps. Th is disconnect between resolution of field
measures and resolution needed for model inputs can cause problems with performance measure model coding as well interp retation of model outputs. Stronger synchronization/standardization between fiel d measurements and model time-steps is needed to reduce uncertainty and increase sensitivity of performance measures. The
Evaluation and Assessment Teams need to consult with those developing and using models to synchornize/standard ize timing and scale of data being collected with those being used in models and performance measures.

17.3 Performance Measure Sensitivity, Calibration and Validation

Sensitivity analysis, calibration and validation need to be performed for each performance measure used for evaluating a lternative plans. Without these technical processes, we have no objective way of de termining whether or not a difference in indicator response exists between alternatives.

Performance measure sensitivity analysis is requ ired to determine if a metric is sensitive to simulated changes in the system. While an indicator and its associated performance measure metric may be known in the real world to be linked to water management features, it is not a given that in an eval uative model, the metric will vary in any predictable way. Sensitivity analysis will give a measure of confidence that a performance measure can detect and track water management changes proposed by CERP projects. It will also discern problems and allow an estimate of whether the problem is specific to the performance meas ure metric, to the model used, or if the problem can actually be attr ibuted to project design.17.0 Next Steps October 17, 2007

17-4 Each performance measure needs to be calib rated and validated. This will allow us to determine if the performance measure is accura tely representing the real-world variable, will allow improvement of models, and will ach ieve a more accurate evaluation of actual project effects.

17.4 Less Reliance on Model-Based Targets

Currently, RECOVER relies upon regional hydrol ogic models to simulate alternative project plans and represent the pre-drainage Everglades. Supplemental models simulate
runoff from the Caloosahatchee and St Lu cie Estuaries and canal discharges.

Dependence on models, especially the NSM, to simulate the pre-drainage Everglades began early in the Restudy process. NSM desc ribes conditions prior to human alteration. These conditions are not fully known or understood. NSM completed a picture only partially described by researc h. It was corroborated by hist orical descriptions of the ecosystem and reference conditions; however, this was a sporadic endeavor that did not result in substantial modifications. Knowing that this simulation model is limited by its assumptions, including a relatively short peri od of record (31-36 y ears), greater reliance on independently identified (empiric ally-based) targets is sought.

The model-independent approach has several ot her advantages. Such an approach can be more consistent in developing and reviewi ng performance measures and their targets, including scientific and statistical criteria for their acceptance. Model-independent targets could be a means to synthesize the vast amount of information on hydrologic and ecologic characteristics of the pre-drainage Everglades. In addition, independently set targets enable performance measures to be re fined with new data and information without the additional step of incorporating them into a computer model. No longer would scientists need to explai n performance of models, onl y support identified targets. Additionally, consensus on re storation targets would be come the goal instead of defaulting to model-based targets.

17.5 Refinement of Evaluation -Assessment Feedback Loop

One component of the Adaptive Manage ment Strategy (RECOVER 2006c) is the essential feedback loop from monitoring data to evaluation tools. Areas of uncertainty
associated with evaluation tools and models need refinement. Ongoing monitoring and assessment activities will provide needed data at varying scales to refine current models. As sample sizes increase and a better understanding of field conditions including processes, mechanisms and rates is gained, assessment information will be fed back into evaluation models resulting in increased sensitivity and reduced uncertainty. In addition to increased sample sizes and a better understanding of ec ological relationships, the ability to make measurements more prec ise will provide increased sensitivity. This ongoing feedback between evaluation and asse ssment functions will help to identify knowledge/data gaps and focus mon itoring and assessment activities.17.0 Next Steps October 17, 2007

17-5 17.6 Future Performance Measures

The current set of performance measures doe s not include critical components of CERP restoration such as spatial extent and eco logical connectivity. The final draft of the Assessment Strategy ( RECOVER 2006b) identifies several stressors that are operative in the system for which RECOVER has not yet developed performance measures or guidance for evaluation and assessment. These include exotic species, climate change and climate variability.

Spatial Extent and Connectiv ity Performance Measures

An essential characteristics of the pre-drainage system was a hydrologic regime featuring dynamic storage and sheet flow. The Central and Southern Florida (C&SFs) Project has altered hydrology in the Evergl ades and has resulted in redu ced flows, fragmented and impounded wetland areas, and reduced spatial extent. The CERP will restore a more natural hydrologic regime. Simple, model- independent performance measures that characterize ecological connectivity, lands cape fragmentation, spatial extent and landscape corridors should also be adopted.

Exotic Species

Exotic plant and animal species threaten natural ecological communities within CERP boundaries. It is estimated that over 32,000 exotic species (25,000 plants and 7,000 animals) have been introduced into Florida (Stein et al. 2000 ). Florida has approximately 4,000 to 5,000 native species of plants and animals. The nu mber of exotic species that have been introduced is eight times the total nu mber of native species in the entire state. Within CERP boundaries just 6 species of invasive exotic plants have replaced approximately 1.9 million acres of habitat (D oren and Ferriter 2001). One species alone, Old World climbing fern, has spread exponentia lly during the last two years. Its current range covers over 125,000 acres within CERP boundaries and model results for this species estimates over 5 million acres will be covered by 2014 (Ferriter et al. 2006). Replacement of native plant and animal sp ecies by exotics can potentially cause irreversible alterations in ecological commun ity structure and function by altering fire regime, surface water flow, salinity, water quality, primary productivity and food web structure, to name a few. Given curre nt and potential impacts on non-indigenous organisms in South Florida, we are obliged to begin to factor these exotic species and their impacts into our pla nning and research. The Asse ssment Strategy (RECOVER 2006b) contains a more detailed discussion of this issue.

More Attribute-Based Evaluation Metrics

More metrics measures that correspond to the attributes in the conceptual ecological models published in Wetlands (Barnes 2005, Browder et al . 2005, Crigger et al. 2005, Davis et al. 2005a, 2005b, Duever 2005, Have ns 2005, Ogden 2005, Ogden et al. 2005, Rudnick et al. 2005, Sime 2005, VanArman et al. 2005) are needed for evaluations of alternative plans. Without these, the set of performance measures may be insufficient in its ability to evaluate potential effect s on important ecosystem attributes.17.0 Next Steps October 17, 2007

17-6 17.7 Implications of Climate Change and Climate Variability upon CERP

Given CERP’s geographic scope and multi-decadal planning and implementation horizons, management decisions need to be co nsistent with and adapt to global climate change and inter-decadal climatic variability. Global changes include sea level rise, sea surface temperature change, atmospheric carbon dioxide and large-scale changes in participation patterns. Climate variability in cludes the Atlantic Multi-decadal Oscillation, El Nino/El Nina, Sahel drought, and tropical st orm impact. These factors will have to be considered during CERP assessments, ev aluations and recommended management alternatives. The Assessment Strategy (RECOVER 2006b) contains a more detailed
discussion of this issue.

17.8 Consistency of Performance Measures and Interim Goals and Targets

Performance measures and interim goals and ta rgets were developed as separate efforts. While they were based on th e same underlying information, there are inconsistencies
between them. These inconsistencies need to be eliminated. The RECOVER Team’s Recommendations for Interim Goals and In terim Targets for the Comprehensive Everglades Restoration Plan (RECOVER 2005) can be found at http://www.evergladesplan.org/pm/recover/igit_subteam.aspx

.

17.9 References

Barnes, T. 2005. Caloosahatchee Estuary conceptual ecological model. Wetlands 25(4):884-897. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_caloosahatch ee_est.pdf

Browder, J.A., R. Alleman, S. Markley, P. Ortner, and P.A. Pitts. 2005. Biscayne Bay Conceptual Ecological M odel. Wetlands 25(4):854-869. http://www.evergladesplan.org/pm/rec over/recover_docs/cems/cem_biscayne_ba y.pdf

Crigger, D.K., G.A. Graves, and D.L. Fike. 2005. Lake Worth Lagoon Conceptual Ecological Model. Wetlands 25(4):943-954. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_lake_worth_l agoon.pdf

Davis, S.M., W.F. Loftus, E.E. Gaiser and A.E. Huffman. 2005a. Southern marl prairies conceptual ecological model. Wetlands 25(4):821-831. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_southern_ma rl.pdf

Davis, S.M., D.L. Childers, J.J. Lorenz and T.E. Hopkins. 2005b. A conceptual model of ecological interactions in the mangrove estuaries of the Florida Everglades. Wetlands 25(4):832-842.17.0 Next Steps October 17, 2007

17-7 http://www.evergladesplan.org/pm/rec over/recover_docs/cems/cem_eg_mangrov e.pdf

Doren, R.F. and A.P. Ferriter (eds.). 2001. W eeds Won’t Wait! Part 1, and Assessment of Invasive Plants in Florida. A report to the South Florida Ecosystem Restoration Task Force and Working Groups, Miami, FL.

Duever, M.J. 2005. Big Cypress regional ec osystem conceptual ecological model. Wetlands 25(4):843-853. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_big_cypress. pdf

Ferriter, A., B. Doren, C. Goodyear, D. Thayer , J. Burch, L. Toth, M. Bodle, J. Lane, D. Schmitz, P. Pratt, S. Snow and K. Langeland. 2006. Chapter 9: The status of nonindigenous species in the South Florida environment. In: SFWMD, 2006 South Florida Environmental Report, Sout h Florida Water Management District, West Palm Beach, FL

Havens, K.E. 2005. Lake Okeechobee conceptual ecological model. Wetlands 25(4):908-
925. http://www.evergladesplan.org/pm/r ecover/recover_docs/cems/cem_low.pdf

Ogden, J.C. 2005. Everglades ridge and slough conceptual ecological model. Wetlands 25(4):810-831. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_eg_ridge_slo ugh.pdf

Ogden, J.C., S.M. Davis, T.K. Barnes, K.J. Jacobs and J.H. Gentile. 2005. Total system conceptual ecological model. Wetlands 25(4):955-979.

http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_total_system. pdf

RECOVER. 2004. CERP Monitoring and Asse ssment Plan: Part 1 Monitoring and Supporting Research. Restoration Coordina tion and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water Management District, West Palm Beach, FL. http://www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2005. The RECOVER Team’s Reco mmendations for Interim Goals and Interim Targets for the Comprehensive Ev erglades Restorati on Plan. Restoration Coordination and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonv ille, Florida, and South Florida Water Management District, West Palm Beach, FL. http://www.evergladesplan.org/pm/recover/igit_subteam.aspx

RECOVER. 2006a. Report on Evaluation Tool s, Models, Work Plan, and Budgets. Model Needs Subteam, Restoration Coordi nation and Verification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville,17.0 Next Steps October 17, 2007

17-8 Florida, and South Florida Water Manage ment District, West Palm Beach, FL. http://www.evergladesplan.org/pm/r ecover/system_wide_modeling.aspx

.
RECOVER. 2006b. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment Strategy for the MAP, Final Draft. Re storation Coordination and Verification Program, c/o United States Army Corps of Engineers, Jack sonville District, Jacksonville, FL, and South Florida Wate r Management District, West Palm Beach, FL. December 2006. http://www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2006c. Comprehensiv e Everglades Restoration Plan Adaptive Management Strategy. Restoration Coordination and Ve rification Program, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, Florida. April 2006. http://www.evergladesplan.org/pm/rec over/recover_docs/am/rec_am_stategy_bro chure.pdf

Rudnick, D.T., P.B. Ortner, J.A. Browder a nd S.M. Davis. 2005. Florida Bay conceptual ecological model. We tlands 25(4):870-883. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_florida_bay.p
df

Sime, P. 2005. St. Lucie Estuary and Indian River Lagoon conceptual ecological model. Wetlands 25(4):898-907. http://www.evergladesplan.org/pm/recover/ recover_docs/cems/cem_st_lucie_irl.p
df

Stein, B.A., L.S. Kutner and J.S. Adams (e ds.). 2000. Precious Heritage, the Status of Biodiversity in the United States. Ox ford University Press, Oxford, UK.

VanArman, J., G.A. Graves and D.L. Fi ke. 2005. Loxahatchee Watershed conceptual ecological model. We tlands 25(4):926-942. http://www.evergladesplan.org/pm/recove r/recover_docs/cems/cem_loxahatchee. pdfAppendix A – Models Used with Performance Measures October 17, 2007
to Evaluate Alternative Plans

A-1 

### Appendix A.

U 

### Models Used with Performa nce Measures to Evaluate
Alternative Plans

RECOVER currently uses the South Flor ida Water Management Model (SFWMM) version 5.4.3, Natural Systems Model (NSM ) version 4.6 and Sens 4.0, Lake Okeechobee Water Quality Model (LOWQM), and Lake Okeechobee Environmental Model (LOEM) to evaluate performance of alternative plans ( Table A-1 ). The Across Trophic Level Simulation System (ATLSS) models, S outh Florida Regional Simulation Model (SFRSM), and the Everglades Landscape Mode l (ELM) are being considered for future application ( Table A-1 ). Brief descriptions of each of these models are provided below.

Table A-1. Models Used to Evaluate CERP Performance Measures

Model Calibration/
Validation status Peer Review Status Notes

SFWMM Documentation provided on the SFWMM web page Peer review of updates conducted Sept. 21-22,
2005 http://www.sfwmd.gov/org/pld/hs
m/models/sfwmm/index.html

NSM Based on peer review
of SFWMM http://www.sfwmd.gov/org/pld/hs
m/models/nsm/index.html LOWQM Completed and
documented Published in peer reviewed journals,
based on US
Environmental Protection Agency’s Water Quality Analysis Simulation Program (WASP)

LOEM SFRSM Currently under development Individual components are being developed independently and are in various stages of completion. http://www.sfwmd.gov/org/pld/hs
m/models/sfrsm/index.html ATLSS Mostly complete, some ongoing efforts Additional peer review pending Currently not being applied to performance measures, efforts are underway to move ATLSS spatially explicit suitability indices (SESI) models to the Interagency Modeling Center for regional evaluation production runs http://www.atlss.org ELM Peer review complete Has been approved for limited
CERP use.Appendix A – Models Used with Performance Measures October 17, 2007
to Evaluate Alternative Plans

A-2 South Florida Water Management Model

The SFWMM is a regional-scale computer model that simulates hydrology and management of water resources from Lake Okeechobee to Florida Bay (SFWMD 2005). It covers an area of 7,600 square miles using a grid of 2-mile by 2-mile cells. In addition, it includes inflows from Kissimmee River, a nd runoff and demands in Caloosahatchee River and St. Lucie Canal basins. The large scal e and spatial extent of the model allows it to simulate system-wide effects.

The model simulates major components of Sout h Florida’s hydrologic including rainfall, evapotranspiration, infiltration, overland and groundwater flow, canal flow, canalgroundwater seepage, levee s eepage and groundwater pumping. It incorporates current or proposed water management control structures and current or proposed operational rules. The SFWMM simulates hydrology on a daily basi s using climatic data for the 1965-2000 period, which includes both drought and wet pe riods. The model has been calibrated and verified using water level and discharge measurements at hundreds of locations distributed throughout the region within model boundaries. The SFWMM is widely accepted as the best available tool for anal yzing regional-scale structural and/or operational changes to the complex water management system in South Florida.

Parameter uncertainty is estimated runni ng a series of SFWMM simulations using historic flows assigned at majo r control structures where re liable flow records exist. Parameters are incrementally varied one at a time from original calibrated parameters to estimate the 90% certainty band for each pa rameter. Compartmentalization of South Florida’s hydrologic system by structures a nd levees presents a unique situation that allows effects of varying individual parameters within several regional compartments at

the same time



### . The same parameter value is a pplied everywhere the physical characteristic is the same, restricting the range in which a specific parameter value may be varied without causing major impacts to calibration of one or more compartment. The effect of compartmentalization is to reduce uncertainty associated with selection of parameter values. Acceptable ranges of varia tion for key input parameters are presented
in Table A-2 . Uncertainty of a given model output variable can be represented by the half-width of the 90% uncertainty band. The general rule is the narrower the bands, the greater the level of certainty.

Table A-2. Ninety Percent Confidence Range for Variation in the SFWMM

Parameter/Process % Change from Calibrated Values Manning's n 50% Wetland evapotranspiration 6% Coastal evapotranspiration 15% EAA evapotranspiration 5% Detention parameter 50% Canal-groundwater hydraulic conductivity 50% Aquifer permeability 50% Levee seepage 50%Appendix A – Models Used with Performance Measures October 17, 2007
to Evaluate Alternative Plans

A-3 The estimate of performance measure uncerta inty was made with version 2.4 of the
SFWMM. Structural flows were estimated ba sed on operational rules in place at the time of the simulations (1995) for high and low values recommended from sensitivity analysis. Parameter uncertainty was estimated by comparing water levels measured at a particular
site to those simulated with the calibrati on version (historical fl ows assigned to major structures) of the SFWMM for the 2-by-2 mile cell that contains the measurement site. A large portion of uncertainty that exists in simulated water levels in this analysis is associated with scaling, process aggregation, location of gauging site within the cell, and estimates of regional rainfall and evapotrans piration. These types of uncertainty can be reduced by considering 1) re gional performance measures that include model output simulated at several cells and 2) relative benefits of system performance measures
between an alternative and the base condition or between alternatives.

When considering uncertainty of simulate d performance measures, it is important to realize that the certainty of meeting individual performance measures depends on the priority that a particular water management objective has relative to other water management objectives. Therefore, simu lated performance measure uncertainty associated with the SFWMM is estimated by re placing historical flows of the calibration version of the model with simulated flows estimated within the operational version of the model and varying parameters. The same exercise would need to be completed for each alternative as performance measure uncertainty will vary with each alternative. This can require a great deal of effort that may not be practicable when considering cost-benefit ratios of taking on such a task and consideri ng that other causes of uncertainty outside the modeling realm may be greater than those of the modeling realm. A large portion of uncertainty that exists in estimating performa nce measures is caused by such factors as
natural climate vari ability, anthropogenic climate change and sea level rise.

Natural System Model

The NSM simulates the hydrologic response of a pre-drainage Everglades system (VanZee 1999). It does not attempt to simula te pre-drainage hydrol ogy, since input data necessary to perform such a simulation do not ex ist. Rather, more recent climatic data is used to simulate pre-drainage hydrologic re sponse to current hydrologic input. Use of recent data allows for meaningful comparis ons between the current managed system and the natural system under iden tical climatic conditions.

The landscape of present day South Flor ida has been greatly affected by land reclamation, flood control and water management activities that have occurred since the early 1900s. The complex network of canals, structures and le vees in the current system are replaced in the NSM with rivers, creeks a nd transverse glades that were present prior to the construction of drainage canals. Vegetation and topography are based on predrainage conditions, except for topography south of Tamiami Trail, which is the same as that used in the SFWMM. Recent updates (v ersion Sens 4.0) to topography account for subsidence. Land cover simulated by the model is static, i.e., the model does not attempt to simulate vegetation succession.Appendix A – Models Used with Performance Measures October 17, 2007
to Evaluate Alternative Plans

A-4 Use of the NSM is closely linked to the SFWMM. They use the same climatic input, model parameters and computational methods . Since traditional calibration/verification methods cannot be applied to the NSM, m odel parameters are based on the SFWMM.

Lake Okeechobee Water Quality Model

The LOWQM simulates average, lake-wid e phosphorus, nitrogen and phytoplankton concentrations. It simulates eutrophication processes in both the water column and underlying sediments (James et al. 1997). It ca n be applied to SFWMM’s simulations, but because observed water quality data for La ke Okeechobee are limited prior to 1972, it only simulates the 28-year period from 1973 to 2000.

This model simulates the lake on a lake-wid e average scale. Significant changes are observed in this model only if nutrient loads to the lake change significantly. This model does not consider unique zones that occur in the lake. Nor does it have features that explicitly respond to changes in water le vel, and it does not include submerged or emergent plants. It is expected that the LOWQM will continue to be used for planning studies that require long-term (e.g., 25 or more years) model runs.

Lake Okeechobee Environmental Model

The LOEM is a spatially-explicit hydrodynami c, sediment-transport and water quality model of the ecosystem ( Jin et al. 2000, Jin et al. 2002, Jin and Ji 2004) . It simulates nutrient and algal dynamics, as well as growth of subm erged aquatic plants. It is anticipated that the LOEM will more accurately simulate impact s of lake level on lake water quality than the LOWQM.

This model will not replace the existing Lake Okeechobee Water Quality Model (LOWQM), but rather, will be used in tandem with it. The LOEM will be used to provide critical information about spatial variation in responses of the lake , in terms of physical, chemical and biological (submerged vegetation) conditions, for relatively short (1-5 year) simulation periods. The LOWQM will provide more coarse-s cale information, but can be used for long-term (decades or even centu ries) simulations of lake response to management alternatives.

South Florida Regional Simulation Model

The SFRSM will be the next generation SFWMM. It is expected that the SFRSM will eventually replace the existing SFWMM. As did the SFWMM, the SFRSM model simulates hydrology and manmade water control features of South Florida to determine consequences of implementing physical and ope rational alternatives designed to address changing water management priorities and issues.

The SFRSM is being develope d using recent advances in computer technology, in particular, geographic information systems (G IS), databases, and object-oriented model development. The new SFRSM will also make use of more realis tic, accurate andAppendix A – Models Used with Performance Measures October 17, 2007
to Evaluate Alternative Plans

A-5 efficient numerical algorithms to simulate hydrology and water management in South Florida using a variable mesh structure. Existing algorithms and procedures in SFWMM
that are efficient and accurate will be duplicated while s earching for ways to improve them or develop new ones.

The SFRSM is a component-based model. It wi ll be an assembly of different components that can be swapped in and out as the mode l evolves. Individual components are being developed independently and are in various stages of completion. Years of development and testing will be needed before SFRSM becomes fully operational for the entire system.

Key processes that will be modeled by th e SFRSM are overland and groundwater flow, precipitation, evapotranspirati on, infiltration, levee seepage an d canal and structure flow.

Four major project components are being de veloped concurrently. They include the following:

• Hydrologic Simulation Engine (HSE ) - simulates the hydrology in South Florida, including Central and South Florida (C&SF) Project canals, structures and levees

• Management Simulation Engine (MSE) - simulates management activities in South Florida, incl uding operation of the C&SF Project

• Graphical User Interface (GUI) - a simple, easy to use tool for graphically setting up a SFRSM mode l and interpreting its results

• DataBase (DB) - a convenient storag e and retrieval facility of SFRSM
data

Across Trophic Level Simulation System Models

ATLSS models integrate three approaches fo r different trophic levels of the system: 1) process models for lower trophic levels, including benthic invert ebrates, periphyton and zooplankton, 2) structured population models for five functional groups of fish and macroinvertebrates, and 3) individual-based models for large consumers, such as wood stork, great blue heron, white ibis, Ameri can alligator, white-tailed deer and Florida panther. Models are integrated across fres hwater landscapes of the Everglades and Big Cypress Swamp and coupled to GIS maps for c over type. Spatial scales of resolution for models are as small as 100 meters, with the capability to vary th is based upon scale of available input data. The system is then coupl ed to a hydrology model, and used to assess effects of alternative proposed restora tion scenarios on trophi c structure. SFWMM hydrologic output is converted to high resolution hydrology and then input into ATLSS
models.

Everglades Landscape Model

The ELM is a process-based, spatially dist ributed simulation of ecosystem dynamics across a heterogeneous landscap e at a grid resolution 10 tim es finer than the SFWMMAppendix A – Models Used with Performance Measures October 17, 2007
to Evaluate Alternative Plans

A-6 (Fitz and Trimble 2006a, 2006b). Everglades ’ hydrology, soil, periphyton, plants and nutrients are evaluated using a set of interacti ng physical, chemical and biological processes. Hydrology and water quality are two principal “l andscape drivers” that are
simulated in the ELM. Because of uncertain ty of many details and complexity of parameterizing them, the model simplifies the system into a small number of interacting ecological modules. While each module is a great simplification of natural system dynamics, they are designed to capture funda mental ecological processes in a changing environment. Important to ELM functionality are positive and negative feedbacks among these fully-integrated ec ological processes.

A variety of summary statistics indicated that the ELM can be effective in simulating principal spatial gradients of water quality across the landscape, capturing long-term seasonal dynamics. A principal component of th e uncertainty of historical simulations of water quality observations was sparse model i nput data on nutrient loads. Applications of
ELM and other models should be based on rela tive performance of a lternative scenarios, not on precise results at specific spatial or temporal locations.

A peer review of ELM version 2.5 was comp leted in January 2007 (M itsch et al. 2007). The model has been approved for limited us e by the CERP program with specific contraints outlined in Mitsch et al. ( 2007). RECOVER will determine if and how the model will be used with the Greater Evergl ades water quality performance measures.

Literature Cited

Fitz, H.C. and B. Trimble. 2006a. Document ation of the Everglades Landscape Model: ELM v2.5. South Florida Water Management District, West Palm Beach, FL.

Fitz, H.C. and B. Trimble. 2006b. Document ation of the Everglades Landscape Model: ELM version 2.5, Overview of the Full Re port. South Florida Water Management District, West Palm Beach, FL.

James, R.T., J. Martin, T. Wool and P. F. Wang. 1997. A sediment resuspension and water quality model of Lake Okeechob ee. Journal of the American Water
Resources Association 33: 661-679.

Jin, K.R., J.H. Hamrick and T. Tisdale. 2000. Application of a three-dimensional hydrodynamic model for Lake Okeechobee. Journal of Hydraulic Engineering
126: 758-771.

Jin, K.R., Z.G. Ji and J.H. Hamrick. 200 2. Modeling winter ci rculation in Lake Okeechobee, Florida. Journal of Waterway, Port, Coastal, and Ocean Engineering, ASCE 128: 114-125.

Jin, K.R. and Z.G. Ji. 2004. Case study: mode ling of sediment tran sport and wind-wave impact in Lake Okeechobee. Journal of Hydraulic Engineering, ASCE 130(11):
1055-1067.

Mitsch, W.J., L.E. Band and C.F. Cerc o. 2007. Everglades Landscape Model (ELM), Version 2.5, Peer Review Panel Report. Submitted to South Florida Water Management District, West Palm Beach, FL.Appendix A – Models Used with Performance Measures October 17, 2007
to Evaluate Alternative Plans

A-7 SFWMD. 2005. Documentation of the South Florida Water Management Model Version 5.5. South Florida Water Management District, West Palm Beach, FL.

VanZee, R. 1999. Natural System Model Ve rsion 4.5 Documentation Report. South Florida Water Management Dist rict, West Palm Beach, FL.Appendix B – Crosswalk of Performance Measures October 17, 2007B-1Appendix B.UCrosswalk of Performance MeasuresCurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasureLake OkeechobeeLO-E1 Lake Okeechobee Extreme Low LakeStageLO-A1 Lake Okeechobee Extreme Low LakeStageLO-E3 Lake Okeechobee Extreme High LakeStageLO-A3 Lake Okeechobee Extreme High LakeStageLake Okeechobee Lake StageLO-E10 Lake Okeechobee Stage Envelope LO-A21 Lake Okeechobee Stage EnvelopeLO-E6 Lake Okeechobee Total PhosphorusConcentrationsLO-A14 Lake Okeechobee Total PhosphorusConcentrationLO-5 Lake Okeechobee Phosphorus Loads LO-A19 Lake Okeechobee Phosphorus LoadsLO-E7 Lake Okeechobee Total Nitrogen:TotalPhosphorus RatioLO-A15 Lake Okeechobee TotalNitrogen:Total Phosphorus RatioLO-E9 Lake Okeechobee Algal BloomFrequencyLO-A17 Lake Okeechobee Algal BloomFrequencyLO-9 Lake Okeechobee Water Clarity LO-A18 Lake Okeechobee Water ClarityLake Okeechobee Water QualityLO-10 Lake Okeechobee Class I Water QualityParametersLO-A20 Lake Okeechobee Class I WaterQuality ParametersLake OkeechobeeDiatom:Cyanobacteria RatioLO-E8 Lake Okeechobee Diatom:CyanobacteriaRatioLO-A16 Lake OkeechobeeDiatom:Cyanobacteria RatioLake Okeechobee VegetationMosaicLO-A6 Lake Okeechobee Native VegetationMosaic - Littoral Plant Communities andBulrushLO-A7 Lake Okeechobee Native VegetationMosaic – Submerged Aquatic VegetationAppendix B – Crosswalk of Performance Measures October 17, 2007B-2CurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasureLake Okeechobee Fish PopulationDensity, Age Structure, andConditionLO-A11 Lake Okeechobee Fish PopulationDensity, Age Structure, and ConditionLO-16 Lake OkeechobeeMacroinvertebratesLO-A8 Lake Okeechobee Fish and AquaticFauna (Fish and Invertebrates)Northern EstuariesNorthern Estuaries Salinity NE-E1 St Lucie Estuary Salinity EnvelopeNE-E2 Lake Worth Lagoon Salinity EnvelopeNE-E3 Caloosahatchee Estuary Salinity EnvelopeNE-E4 Loxahatchee River Estuary SalinityEnvelopeNE-A1 St. Lucie Estuary Salinity EnvelopeNE-A2 Lake Worth Lagoon Salinity EnvelopeNE-A3 Caloosahatchee Estuary SalinityEnvelopeNE-A4 Loxahatchee River Estuary SalinityEnvelopeNorthern Estuaries Water Quality NE-A11 St. Lucie Estuary Nutrient (TP andTN) Loading and ConcentrationNE-A14 Lake Worth Lagoon Nutrient (TPand TN) Load and ConcentrationNE-A10 Caloosahatchee Estuary Nutrient (TPand TN) Loading and ConcentrationNE-A13 Loxahatchee River Estuary Nutrient(TP and TN) Load and ConcentrationNE-A12 South IndianRiver Lagoon Nutrient(TP and TN) Load and ConcentrationNE-A16 Northern Estuaries Contaminants(Toxicants and Pathogens)NE-A17 Northern Estuaries Water ClarityNE-A15 Northern Estuaries Algal BloomFrequencyAppendix B – Crosswalk of Performance Measures October 17, 2007B-3CurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasureNorthern Estuary Oyster Habitat NE-A5 Northern Estuary Oyster HabitatNorthern Estuaries BenthicMacroinvertebratesNE-A6 Northern Estuaries BenthicMacroinvertebratesNorthern Estuaries FishCommunitiesNE-A7 Northern Estuaries Fish CommunitiesNorthern Estuaries SubmergedAquatic VegetationNE-A8 Northern Estuaries SubmergedAquatic VegetationGreater EvergladesSheet Flow in Everglades Ridge andSlough LandscapeWet PrairieNumber and Duration of Dry Eventsfor Shark River SloughGE-E1 Number and Duration of Dry Events forShark River SloughGE-A1 Greater Everglades WetlandsHydropatternInundation Pattern in GreaterEverglades WetlandsGE-E2 Inundation Pattern in Greater EvergladesWetlandsGE-A1 Greater Everglades WetlandsHydropatternExtreme High and Low WaterLevels in Greater EvergladesWetlandsGE-E3 Extreme High and Low Water Levels inGreater Everglades WetlandsGE-A1 Greater Everglades WetlandsHydropatternGreater Everglades Wetlands TotalPhosphorus (TP) Concentrations inSurface WaterGE-E7 Greater Everglades Wetlands TPConcentrations in Surface WaterGE-A14 Greater Everglades WetlandsNutrient Concentrations in Surface WatersGreater Everglades WetlandsBasinwide TP Loading and FlowWeighted Mean Concentration inInflowsGE-E8 Greater Everglades Wetlands BasinwideTP Loading; GE-E9 Greater Everglades WetlandsBasinwide TP Loading and Flow-Weighted MeanConcentration in InflowsGE-A19 Total Phosphorus Loads/FlowWeighted Mean Concentration in Inflows tothe Greater EvergladesAppendix B – Crosswalk of Performance Measures October 17, 2007B-4CurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasureGreater Everglades WetlandsNutrient TN Concentrations inSurface WaterGE-A14 Greater Everglades WetlandsNutrient TN Concentrations in Surface WaterTotal Nitrogen Loads/FlowWeighted Mean Concentration inInflows to the Greater EvergladesWetlandsGE-A20 Total Nitrogen Loads/FlowWeighted Mean Concentration in Inflows tothe Greater Everglades WetlandsTotal Phosphorus Concentrations inSoilGE-A15 Total Phosphorus Concentrations inSoilGreater Everglades Tracer of STABypass flowsGE-E10 Tracer of STA Bypass flowsGreater Everglades Wetlands SulfateConcentrations in Surface WaterGE-A16 Greater Everglades Wetlands SulfateConcentrations in Surface WaterGreater Everglades WetlandsConductivity in Surface WaterGE-A17 Greater Everglades WetlandsConductivity in Surface WaterGreater Everglades Wetlands CoastalSalinity GradientsGE-A12 Greater Everglades Wetlands CoastalSalinity GradientsWetland Landscape Patterns –Freshwater and Estuarine VegetationMosaicsGE-A2 Wetland Landscape Patterns –Freshwater and Estuarine Vegetation MosaicsWetland Landscape Patterns - MarlPrairie Cape Sable Sparrow HabitatGE-A5 Wetland Landscape Patterns - MarlPrairie Cape Sable Sparrow HabitatWetland Landscape Patterns - Ridgeand Slough CommunitySustainabilityGE-E6 Species Richness Suitability forEverglades Tree IslandsGE-E14 Ridge and Slough Habitat SuitabilityIndex; GE-E15 Tree Island Flooding/DroughtHabitat Suitability IndexGE-A3 Wetland Landscape Patterns - Ridgeand Slough Community SustainabilityAppendix B – Crosswalk of Performance Measures October 17, 2007B-5CurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasureWetland Landscape Patterns - TidalCreek SustainabilityGE-A4 Wetland Landscape Patterns - TidalCreek SustainabilityWetland Trophic Relationships –PeriphytonGE-E11 Periphyton Habitat Suitability IndexGE-A10 Wetland Trophic Relationships –PeriphytonWetland Trophic Relationships -Mangrove Forest Production/SoilAccretionGE-A11 Wetland Trophic Relationships -Mangrove Forest Production/Soil AccretionWetland Trophic Relationships -Regional Populations of Fishes,Crayfish, Grass Shrimp andAmphibiansGE-E16 Fish Habitat Suitability Index GE-A6 Wetland Trophic Relationships -Regional Populations of Fishes, Crayfish,Grass Shrimp and AmphibiansWetland Trophic Relationships –Wading Bird Foraging Patterns onOverdrained WetlandsGE-E20 Long-Legged Birds Foraging ConditionsGE-E21 Short-Legged Birds Foraging ConditionsGE-A7 Wetland Trophic Relationships –Wading Bird Foraging Patterns onOverdrained WetlandsWetland Trophic Relationships –Wading Bird Nesting PatternsGE-E13 Wading Bird HabitatSuitability Index GE-A8 Wetland Trophic Relationships –Wading Bird Nesting PatternsRoseate Spoonbill Nesting Patterns GE-A18 Roseate Spoonbill Nesting PatternsWetland Trophic Relationships -American Alligator Distribution,Size, Nesting and ConditionGE-E12 Alligator Habitat Suitability IndexGE-E23 Alligator Production IndexGE-A9 Wetland Trophic Relationships -American Alligator Distribution, Size,Nesting and ConditionAmerican Crocodile - JuvenileGrowth and SurvivalGE-A13 American Crocodile - JuvenileGrowth and SurvivalAppendix B – Crosswalk of Performance Measures October 17, 2007B-6CurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasureSouthern EstuariesSouthern Estuaries Salinity SE-E2Frequency of Low Salinities and HighSalinities in Florida BaySE-E9 Whitewater Bay hydrology- SalinityRelationships Using Watershed Water LevelsSE-E3 Freshwater Flow to Biscayne Bay from theMiami RiverSE-E4 Salinity Patterns in, and Timing ofFreshwater Inputs to, Manatee Bay and CoastalEmbayments of Barnes SoundSE-E5 South Biscayne Bay – Salinity Gradientsalong Western Shore of Biscayne Bay betweenShoal Point and Turkey PointSE-E6 North Biscayne Bay – Surface WaterDischarges to North Biscayne Bay to PreserveExisting Seagrass CommunitiesSE-E7 Central Biscayne Bay – Surface WaterDischarges from Snapper Creek Canal tomaintain salinity in nearshore Biscayne Bay.SE-E8 Snake Creek Surface Water Discharges toNorth Biscayne BaySE-A2 Southern Estuaries Salinity PatternSE-A1 Surface Water Discharges to BiscayneBayWater Level at RegionallySignificant Gauge Stations inEverglades National ParkSE-E10 Water Level at Regionally SignificantGauge Stations in Everglades National ParkSE-A3 Water level atregionally significantgauge stations in Everglades National ParkSouthern Estuaries SubmergedAquatic VegetationSE-A3 Southern Estuaries SubmergedAquatic VegetationAppendix B – Crosswalk of Performance Measures October 17, 2007B-7CurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasureSouthern Estuaries Juvenile PinkShrimp and Associated EpifaunaSE-A4 Southern Estuaries Juvenile PinkShrimp and Associated EpifaunaSouthern Estuaries Fish Community SE-A5 Southern Estuaries Shoreline FishCommunitySE-A6 Florida Bay Juvenile Spotted SeatroutSouthern Estuaries Water Quality SE-A9 Southern Estuaries NutrientConcentrations in Surface WaterSE-A10 Southern Estuaries Nutrient LoadsSE-A11 Southern Estuaries Algal BloomsSE-A12 Southern Estuaries WaterClarity/Light PenetrationSE-E13 Contaminants (Toxicants andPathogens) in BiscayneBay Tributaries andCoastal SedimentsTotal SystemSnail Kite Foraging ConditionsGE-E17 Apple Snail ReproductionGE-E18 Snail Kite Foraging Habitat VegetationStructureWhite Tail Deer Breeding Potential(panther surrogate)GE-E22 White Tail Deer Breeding Potential(panther surrogate)Mercury Bioaccumulation TS-3 Mercury BioaccumulationWater SupplyFrequency of Water Restrictions forthe Lake Okeechobee Service AreaWS-1 Frequency of Water Restrictions for theLake Okeechobee Service AreaFrequency of Water Restrictions forthe Lower East Coast Service AreaWS-2 Frequency of Water Restrictions for theLower East Coast Service AreaAppendix B – Crosswalk of Performance Measures October 17, 2007B-8CurrentPerformance MeasureFormer EvaluationPerformance MeasureFormer AssessmentPerformance MeasurePotential for High Water Levels inSouth Miami-Dade AgriculturalAreaWS-3 Potential for High Water Levels in SouthMiami-Dade Agricultural AreaPrevent Saltwater Intrusion of theBiscayne Aquifer - Meet MFLCriteria for Biscayne AquiferWS-4 Prevent Saltwater Intrusion of the BiscayneAquifer - Meet MFL Criteria for BiscayneAquiferPrevent Saltwater Intrusion of theBiscayne Aquifer in South MiamiDade CountyWS-5 Prevent Saltwater Intrusion of the BiscayneAquifer in South Miami-Dade CountyComparison of Stage Differences ofWater Levels in South Miami-DadeAgricultural AreaWS-6 Comparison of Stage Differences of WaterLevels in South Miami-Dade Agricultural AreaAppendix C – Legal Justification for Performance Measures October 17, 2007

C-1 

### Appendix C. Legal Justification for Performance Measures

Both federal and state laws and regulations ar ticulate the need to measure and evaluate system-wide response to CERP implementati on. Performance measures provide tools to
fulfill this need. Performance measures doc ument success and failures to help identify when the CERP needs to be altered through adaptive management.

Water Resources Development Act of 2000

Through enactment of the Water Resources Development Act (WRDA) of 2000 (Public Law 106-541), Congress approved the Comprehens ive Plan as a framework and guide to modify the Central and Southern Florida (C&S F) Project. CERP’s scope, complexity and importance and the significant outlay of public funds necessary for implementation dictate the need to measure, assess a nd report progress towards achieving CERP’s objectives. Therefore, Section 601(b)(2 )(C) of the WRDA 2000 gives specific authorization for an adaptive assessment an d monitoring program. This program is essential for ensuring incorporation of new scientific and technical information into
CERP. See www.evergladesplan.org/wrda2000/wrda.aspx for more information on
WRDA 2000.

Programmatic Regulations

In the Programmatic Regulations for the Compre hensive Everglades Restoration Plan;
Final Rule , which became effective on December 12, 2003 (DOD 2003), RECOVER is charged with “Developing proposed evaluati on performance measures for evaluating alternative plans developed for the Pr oject Implementation Report” (Section 385.20(e)(2)(i)) and “Developing proposed a ssessment performance measures for assessing progress toward the goals and purpos es of the Plan” (Sect ion 385.20(e)(1)(i)).

Guidance Memoranda

Programmatic regulations require guidanc e memoranda be developed to apply performance measures to 1) evaluate system -wide effects of alternatives developed for project implementation reports (Section 385. 26(b)(1)) and 2) develop an assessment program to assess system responses to CERP implementation (Section 385.31(b)). The
final draft Assessing the Response of the Everglades Ecosystem to Implementation of the Comprehensive Everglades Restoration Plan (RECOVER 2004) guidance memoranda fulfills this requirement. This guidance is included in the Comprehensive Everglades Restoration Plan, Programmatic Regulations , Six Program-Wide Guidance Memoranda document (USACE and SFWMD 2007).

United States Army Corps of Engineers Planning Guidance

System-wide evaluation performance measur es presented in this document follow principles and guidelines set forth by the Water Resources Council in accordance with
Section 103 of the Water Resources Pla nning Act (Public Law 89-80) and ExecutiveAppendix C – Legal Justification for Performance Measures October 17, 2007

C-2 Order 11747. According to this regulation, the United States Army Corps of Engineers’ ecosystem restoration planning objective is “to contribute to national ecosystem restoration” by increasing “t he net quantity and/or qual ity of desired ecosystem resources.” National ecosystem restoration is determined by measuring improvement in habitat quality and/or quantity. The United St ates Army Corps of Engineers developed the Planning Guidance Notebook (Engineering Regulation 1105-2-100, USACE 2000) to set forth a planning process grounded in thes e principles and guidelines. In evaluating national ecosystem restoration, Engineering Regulation 1105-2-100 requires that outputs be “clearly identified and quantified in appr opriate units”. Some examples of possible metrics that may be used include habitat units , increase in number of breeding birds, and diversity indices. System-wide evaluation pe rformance measures presented in this document follow these principles and guide lines. The Corps of Engineers Planning Guidance (USACE 2000) does not pertain to assessment performance measures.

Florida Law

Florida Law requires water resource issues to be addressed in CERP planning activities. Section 373.1501(5)(a), Florida Statutes (F .S.), requires the South Florida Water Management District to “analyze and evaluate all needs to be met in a comprehensive manner and consider all applicable water resource issues, including water supply, water quality, flood protection, thre atened and endangered species and other natural system and habitat needs” during development of proj ect components. To fulfill this mandate, ecological effects of each project will be qua ntitatively and qualitatively analyzed and evaluated using project-level performance measures adopte d (consistent with RECOVER performance measures) by each project delivery team. These resource issues will also be analyzed and evaluated using the set of system-wide perfor mance measures presented in this document. Examples of performance measures based on Florida’s water supply planning law include establishment of minimu m flows and levels pur suant to subsection 373.0361(2)(g), F.S., and capability of meeti ng the water supply demands in a 1 in-10 year drought pursuant to section 373.0361(2)(a) 1, F.S. These analyses and evaluations will be documented for compliance with Section 373.1501(5)(a), F.S., in project implementation reports.

References

DOD. 2003. Programmatic Regulations for the Comprehensive Everglades Restoration Plan; Final Rule. Department of Defe nse, 33 CFR Part 385, Federal Register, November 12, 2003. http://www.evergladesplan.org/pm /progr_regs_final_rule.aspx

RECOVER. 2004. Assessing the Response of the Everglades Ecosystem to Implementation of the Comprehensive Ever glades Restoration Plan, Final Draft. Integrative Assessment Team, Restora tion Coordination and Verification, c/o United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water Management Di strict, West Palm Beach, FL. December
2004.Appendix C – Legal Justification for Performance Measures October 17, 2007

C-3 http://www.evergladesplan.org/pm/rec over/recover_docs/aat/rec_prelim_guid_de c_2004.pdf

USACE. 2000. Corps of Engineers Pl anning Guidance Notebook. ER-1105-2-00. United States Army Corps of Engineers, Washington, D.C.

USACE and SFWMD. 2007. Comprehensive Ever glades Restoration Plan, Programmatic Regulations, Six Program-Wide Guidan ce Memoranda. United States Army Corps of Engineers, Jacksonville, FL , and South Florida Water Management District, West Palm Beach, FL. http://www.evergladesplan.org/pm/p m_docs/prog_regulations/072707_prog_regs _rev_final_dft_gm.pdfAppendix D – History of Restudy Performance Measures October 17, 2007

D-1 

### Appendix D. History of Restudy Pe rformance Measures

Restudy Performance Measures

During the Central and Southern Florida (C &SF) Project Comprehensive Review Study, referred to as the Restudy, performance measur es were developed to evaluate relative ability of plans to meet ecological and hydrological objectives . These performance measures are documented in Appendix D of the Restudy’s final feasibility report (USACE and SFWMD 1999). Many performance measures used during the Restudy to evaluate hydrology and water qu ality of the system are stil l being used, but they have been refined and grouped into a smaller set of performance measures. Also, performance measures were updated to incorporate resu lts from new model ve rsions, including an expansion of period of record simulated. Below is a summary of major revisions and additions to performance measures used for evaluation during the Restudy. Additional performance measures with ecological indicat ors have been developed since the Restudy.

Greater Everglades Wetlands

During the Restudy, 51 separate performance meas ures were used to evaluate hydrology. Some of these have now been grouped into a smaller set of performance measures. In addition, interpretation of performance relative to their targets was altered, instead of trying to meet the target (Natural System s Model or South Florida Water Management Model 2000 existing condition) at discreet loca tions, an envelope or range of targets was developed for each landscape type based on model results for the entire landscape. Using an envelope captures some of the uncertainty of the mode l results without losing the scientific underpinnings of the target.

While refining Greater Everglad es performance measures, locations of indicator regions, which are locations used to evaluate performance, were refined. The process for determining indicator regions is descri bed in Appendix E of this document.

Northern Estuaries

For Caloosahatchee and St Lucie Estuaries, th e number of events outside of the salinity envelope was revisited to accommodate the lo nger period of record in SFWMM version 5.0. Additionally, two performance measures ha ve been added for Lake Worth Lagoon and Loxahatchee River Estuary salinity envelopes.

Southern Estuaries

Salinity envelopes were identified for most of contributing basins for Biscayne Bay, and seasonal flow targets were created for Miam i River and South Bay, while Snake Creek’s target was revised. These salinity envelopes are based on estimated requirements of target communities or organisms and regression analyses relating salinity to flows from selected coastal control structures in the C&SF Projec t. A separate season al flow target andAppendix D – History of Restudy Performance Measures October 17, 2007

D-2 performance measure was established to create a persistent positive freshwater gradient from freshwater wetlands into the bay.

New regression analyses relating Florida Bay salinity to water stages in Everglades National Park were completed and improved by focusing on gauges located nearest to each basin and incorporating additional environmental variables. Targets were expressed in terms of salinity references rather than stage references for Joe Bay, Little Madiera Bay, Terrapin Bay, Garfield Bight and North River Mouth. Performance measures with targets were created for two additional em bayments: Manatee Bay and Barnes Sound.

Water Supply

Frequency of water restrictions performance measures were revisited to ensure they focus on regionally significant water restriction even ts. Local or insignificant water restriction events are no longer considered.

Flood Protection

The Restudy performance measure for flood protection in the South Miami-Dade Agricultural Area was updated to incorporat e calibration and valid ation results from SFWMM version (5.0). The target is base d on 1983-1993 stage hydrographs of seven
selected cells. A new measure was added to evaluate performance relative to Interim Structural Operation Plan 2001 citations operations.

Water Quality

Twenty-four performance measures were developed by Dr. William W. Walker and used by the water quality sub- team during the Restudy to evaluate effect of a lternatives on performance of the Everglades Construction Project. A s ubset of these performance
measures has been modified to evaluate hydrologic conditions and ecological during CERP implementation. The evaluation method us ed by Dr. Walker during the Restudy is not incorporated in the current set of perf ormance measures due in large part to its inclusion of all CERP components to evaluate plan alternatives rather than individual project alternative plans.

References

USACE and SFWMD. 1999. Central and Sout hern Florida Project Comprehensive Review Study Final Integrated Feas ibility Report and Programmatic Environmental Impact Statement. Unite d States Army Corps of Engineers, Jacksonville District, Jacksonville, Florid a, and South Florida Water Management District, West Palm Beach, FL. http://www.evergladespla n.org/pub/restudy_eis.aspxAppendix E – Indicator Region Documentation October 17, 2007

E-1 

### Appendix E. Indicator Region Documentation

Many of the performance measures develo ped for the natural areas were based on hydrologic patterns simulated by the Natural Sy stem Model (NSM). The NSM is likely to be more accurate in its simulations of regi onal or subregional hydrol ogical patterns than with simulations of local or point hydrological conditions (Bales et al. 1997). Therefore, indicator regions were created to reduce th e degree of uncertainty or error among the NSM-based targets of these performance meas ures. For most performance measures that have NSM-based hydrological targets, target parameters were established for indicator regions rather than for singl e cells or point locations.

Indicator regions are groups of adjacent 2-by-2 mile cells w ithin the South Florida Water Management Model (SFWMM) and Natural System Model (NSM) grids intended to show hydrological behavior of small, logical subregions common both to present and predrainage Everglades systems. Because in dicator regions have ground elevations and community structure that are similar to much more extensive areas of the natural system, hydrologic patterns in each indicator region can be used to evaluate how well alternative plans achieve hydrological restoration targets at subregional and re gional scales. The set of performance measures developed for the Greater Everglades are applied to these regions in order to avoid ma king cell-by-cell comparisons with the NSM when evaluating model output.

Since the Restudy discussed in Section 6.1 a nd Appendix D of this report, many of the performance measures, as well as the indicat or regions associated with them, have undergone significant revision. As new inform ation becomes available, performance measures and associated indicator regions may be revised, replaced or added to. RECOVER has the responsibility of reviewi ng and refining both ev aluation performance measures and indicator regions.

To make performance measures more consistent within the remaining Everglades, several regions that were evaluated separately dur ing the Restudy were combined, including southern Everglades, northern and central Everglades, Bi g Cypress, Rotenberger and Holey Land Wildlife Management Areas a nd Pennsuco Wetlands. Several workshops were held in 2000, 2001 and 2002 to review and refine perf ormance measures for these areas. During those workshops it became obviou s that improvement to indicator regions was also necessary. A list of criteria fo r revising indicator re gions was developed:

• Indicator regions with homogene ous topography (less than 1-foot difference with area) are best.

• Cells within a region should have homogeneous soil and vegetation types and be consistent between NSM and SFWMM. Consistent topography is more important than vegetation or soils.

• A region should be small enough to represent an area of interest.

• Ideally, a region should contain at least 5 cells for accuracy.Appendix E – Indicator Region Documentation October 17, 2007

E-2 • A region should contain a calibration gauge, if possible, preferably one
that has a correlation coefficient (r 2 ) of more than 0.6.

• Cells should be 2 or more cells away from the model(s) edge. Cells on the edge are strongly affected by boundary conditions and, therefore, are subject to greater uncertainty.

• A region should avoid havi ng cells with canals or other structures in
them.

These criteria were followed as much as po ssible to develop a revised set of indicator regions ( Figure E-1) . This set was accepted by the RECOVER in April 2003.
RECOVER will continue to refine indicat or regions. These refinements include determining uncertainty associated with each indicator region, incorporating improvements in topography, and continuing research to better describe hydrologic
conditions that will define “restoration” in each region of the Greater Everglades. The team is finalizing a standard operating procedur e for refining the set of indicator regions. The process is being designed to be flexible enough to allow the team to use the best available information at any given time, yet be sensitive to changi ng evaluation tools in the midst of plan evaluations.

References

Bales, J., L. DeLong and E. Swain. 1997. Review and Evaluation of Selected Features of
the NSM. Submitted to the United States Army Corps of Engineers and the South Florida Water Management District, by the United States Geological Survey, Raleigh, North Carolina.Appendix E – Indicator Region Documentation October 17, 2007

E-3 Figure E-1. RECOVER Indicator Regions for th e Greater Everglades WetlandsMAP, Part 2 – Draft Final December 2006 142 9.4.3 Submerged Aquatic Vegetation Conceptual Ecological Model

The model below summarizes environmental in teractions that are known to affect SAV areal distribution and density in Lake Okeechobee. Many of these parameters are currently being monitored and will be used in the development of assessment tools based on the hypotheses listed below.

Figure 9-4-2 : SAV Conceptual Ecological Model Water Management

Turbidity 

### Lake Stage Wind Waves Nutrient Concentrations

Native SAV
and Associated Epiphytes 

### Light conditions Sediment Type

Exotic

SAV Nutrient Load Management

Algal bloom Sediment Resuspension Physical DisturbanceMAP, Part 2 – Draft Final December 2006 143 9.4.4 Submerged Aquatic Vegetation Hypotheses

Hypothesis 1 Lake stage is a major determining factor in the aerial extent and density of SAV in the littoral-pelagic fringe zo ne of Lake Okeechobee.

Rationale : At higher lake stages, li ght penetration to the botto m is reduced and the area capable of supporting dense SAV is smaller. In addition, at higher lake stages the pelagic and littoral fringe zones of the lake become hydrologically connected resulting in increased turbidity which further decreases li ght availability for S AV growth (James and Havens 2005). Conversely, at lower lake stages , larger areas of the lake bottom receive adequate light to support SAV growth and much of the potential SAV growth zone becomes partially hydrologically uncoupled fro m the pelagic zone, and sheltered from prevailing wave action. This re sults in reduction in turbidity and further improvements in the light climate.

Hypothesis 2 Major wind and wave events can result in large scale destruction of SAV by direct physical tearing and uprooting of plants.

Rationale : Following hurricanes Frances and Jeanne in 2004, and Wilma in 2005 observational and monitoring data indicated a rapid and nearly inst antaneous decline in SAV density and distribution. Although this phenomenon would occur sporadically and is independent of CERP effects, it has pot ential major consequences for the ecological
health of Lake Okeechobee.

Hypothesis 3
Nutrient concentrations influence SAV areal coverage and density through their effects on phytoplankton density.

Rationale : Elevated nutrient concentrations stimulate dense phytoplankton blooms which reduce the light available for SAV grow th. This causes reductions in SAV areal coverage and density and can lead to the development of a persistent turbid water state. When SAV density is high, or nutrient conc entrations are low, plants out compete phytoplankton thereby maintaining a persistent clear water state (Phi lips et al. 1993).

Hypothesis 4 Under physical conditions that result in low light leve ls the exotic SAV species Hydrilla may have a competitive advantage over more desirable native SAV species.

Rationale : Mesocosm experiments conducted under natural light indicate that Hydrilla has a lower light requirement than any of the major native SAV species of Lake
Okeechobee.MAP, Part 2 – Draft Final December 2006 144 Hypothesis 5 Changes in the extent of mud sediments in the littoral-pelagic fr inge zone of Lake Okeechobee resulting from changes in nutrien t loading and runoff influence the potential area available for colonization by SAV.

Rationale : In Lake Okeechobee SAV colonizes peat and sand sediment but does not grow in mud sediment. Changes in nutrient loading and runoff are expected to reduce and/or cap mud sediments and increase the area potentially available for colonization by
SAV.

9.4.5 Macroinvertebrate Conceptual Ecological Model

The model below summarizes environmental interactions that are known to affect macroinvertebrate distribution, abundance and species diversity in Lake Okeechobee. A number of these parameters are currently being monitored and wi ll be used in the development of assessment tools ba sed on the hypotheses listed below.

Figure 9-4-3 : Macroinvertebrate Conceptual Ecological Model Water Management

Macroinvertebrates Sediment Type Nutrient Load Management

Littoral Emergent Vegetation Mosaic SAV and Associated Epiphytes Water QualityMAP, Part 2 – Draft Final December 2006 145 9.4.6 Macroinvertebrate Hypotheses

Hypothesis 1 The presence of dense SAV and emergent plan t beds results in hi gher macroinvertebrate diversity and fewer polluti on-tolerant organisms.

Rationale: Research has suggested that macroinvert ebrate densities ineutrophic lakes are higher in vegetated areas than they are in non-vegetated areas (Edwards and Cowell 1992, Petridis 1993, Kurashov et al. 1996). In Lake Okeechobee, Warren and Vogel (1991) have found that macroinvertebrate biom ass and diversity were highest in dense plant beds under low to moderate lake stag e (Havens and Gawlik 2005). The presence of dense SAV and emergent plant beds as a resu lt of water management and nutrient load
reduction activities should result in more habitat and improved water quality, thus facilitating a reduction in the density and numb er of pollution-tolerant macroinvertebrate

taxa.

Hypothesis 2 The macroinvertebrate assemblage is more diverse and comprised of fewer pollutiontolerant taxa in regions of th e lake underlain by sand and peat sediments than it is in areas underlain by mud sediments.

Rationale: The 1990-91 Lake Okeechobee benthic macroinvertebrate survey conducted by Warren et al. (1995) showed that the macroinvertebrate assemblage inhabiting the mud sediments was comprised of a small numb er of organic polluti on- and low dissolved oxygen-tolerant species. They also found that species richness was hi gher at sites located in sand and peat sediments, re lative to those found at the site s located in mud sediments. Changes in nutrient loading and runoff are ex pected to reduce and/or cap mud sediments thereby increasing the percenta ge of the macroinvertebrate assemblage comprised of non pollution-tolerant taxa.

Hypothesis 3
Reduction in nutrient loads will result in in creased macroinvertebrate diversity and a reduction in the number of pollution- tolerant macroinvertebrate taxa.

Rationale: Macroinvertebrate diversity in a La ke Champlain wetland declined as nutrient loading increased (Schwartz and Gr uendling 1985). In La ke Erie decreased diversity and increased number of pollution-tolerant taxa occu rred with increased nutrient loading (Krieger 1984). Warren et al. (1995) documented a large decrease in Lake Okeechobee benthic macroinvertebrate diversity compared to measurements made 20 years previously (Joyner 1974). Reducing nutrient loading in Lake Okeechobee is expected to result in a reversal of this trend and a return to an increasingly diverse macroinvertebrate community with a reduced number of pollution-tolerant taxa.MAP, Part 2 – Draft Final December 2006 146 9.4.7 Phytoplankton Conceptual Ecological Model

The model below summarizes environmental interactions that are known to affect phytoplankton distribution, abundance and species diversity in Lake Okeechobee. Phytoplankton has been routinely monitored in Lake Okeechobee for more than a decade and the results will be used in the development of assessment tools based on the hypotheses listed below.

Figure 9-4-4 : Phytoplankton Conceptual Ecological Model Water Management

Turbidity Lake levels Wind Waves Nutrient Concentrations

SAV and Associated Epiphytes Light conditions Nutrient Load Management

Phytoplankton Biovolume and Taxonomic Composition Sediment Resuspension N/P RatiosMAP, Part 2 – Draft Final December 2006 147 9.4.8 Phytoplankton Hypotheses

Hypothesis 1
Lake water levels infl uence phytoplankton growth.

Rationale : At high lake stage both turbidity and phosphorus leve ls are elevated in the pelagic region due to wind driv en resuspension of phosphorus laden mud sediments. The reduced irradiance levels that prevail unde r these conditions have a negative impact on phytoplankton growth. High lake levels also result in greater horizontal mixing which increases nutrient transport into the less turbid near-shore and littoral areas thereby increasing phytoplankton growth rates and th e frequency of occurrence and intensity of algal blooms in these areas (Maceina 1993, James and Havens 1996).

Hypothesis 2 Nutrient concentrations directly in fluence phytoplankton biovolume and taxonomic composition.

Rationale : Prolonged high rates of external lo ading of phosphorus (P) from the watershed have resulted in a surplus of phosphorus relative to algal demands. The enrichment of P has altered the nitrogen to phosphorus ratio (N:P) shifting conditions from a P limited to an N limited system, whenev er the system isn’t light limited (East and Sharfstein 2006). P limitation favors dom inance of the more desirable non bloomforming algal species while N limitati on favors dominance by undesirable noxious bloom-forming cyanobacteria. These bloom-f orming cyanobacteria can remain buoyant in the water column and obtain nitrogen from the atmosphere by the process of nitrogen fixation (Horne 1977) thus having a competitive advantage over the non nitrogen-fixing, non bloom-forming species. Consequently, the frequency of severe cyanobacterial
blooms increases under these conditions.

Hypothesis 3 Underwater irradiance (light level) regulates phytoplankton taxonomic composition.

Rationale : Low light conditions favor the prolifer ation of low light adapted non bloomforming species while high light conditions are dominated by the high light adapted bloom-forming species. Although the N:P ratio in the lake provides nutrient conditions that are potentially favorable for dominan ce by the bloom-forming cyanobacteria, their occurrence is often restricted by low light availability (Havens et al. 2003). Therefore, in the shallower, less turbid n ear-shore region N limitation pr evails (Aldridge et al. 1995, East and Sharfstein 2006) and the bloom-f orming cyanobacteria dominate while in the deeper more turbid pelagic region light is the limiting factor so the non bloom-forming cyanobacteria dominate.

Hypothesis 4 The presence or absence of submerged aq uatic vegetation (SAV) and associated epiphytes has an impact on phytoplankton biovolume.MAP, Part 2 – Draft Final December 2006 148 Rationale : SAV and its associated epiphytes have the ability to reduce water column P concentrations by direct uptak e or by mediating changes in pH causing copr ecipitation of
P with calcium. Rooted SAV also stabilizes the sediment preventing the resupension of
sediment and P back into the water colu mn. SAV and epiphytes also compete for nitrogen and other nutrients with phytoplan kton. Therefore the presence of submerged plants in the littoral-pelagic fringe has the potential to i nhibit phytoplankton growth and algal bloom frequency and intensity when nutrient concentrations are high.

9.4.9 Native Fish Species Co nceptual Ecological Model

The model below summarizes environmental in teractions that are understood to affect native fish abundance and diversity in Lake Okeechobee. A number of these parameters are currently being monitored, and some, such as sport fish abundance and recruitment have been monitored by The Florida Fish and Wildlife Conservation Commission (FFWCC) for decades. Monitoring results will be used in the development of assessment tools based on the hypotheses listed below.MAP, Part 2 – Draft Final December 2006 149 Figure 9-4-5 : Native Fish Species Conceptual Ecological Model Water Management

Macro Inverts Sediment Type Nutrient Load Management

Phytoplankton Taxa Littoral Emergent Vegetation Mosaic SAV and Associated Epiphytes

Zooplankton

Fish Habitat (Cover, Forage, Spawning) Fish Forage

Desirable Native Fish Abundance and Diversity Exotic Fauna Bacteria Water Quality Lake LevelMAP, Part 2 – Draft Final December 2006 150 9.4.10 Native Fish Species Hypotheses

Hypothesis 1 Increases in SAV density, biomass, and aeria l coverage improve fish habitat and fish foraging opportunities and improve desirable native fish abundance and diversity.

Rationale : Havens et al. (2005) observed a signif icant recruitment of largemouth bass in Lake Okeechobee that coincided with improved diversity and complexity of the SAV and emergent vegetation in 2002, afte r years of high water and lo w SAV. Similar results for Lake Okeechobee were reported by Chick and McIvor (1994, 1997) and Furse and Fox (1994). Increasing complexity of the areas for fish forage, fish spawning, and shelter for prey species, will increase fish abundance and diversity.

Hypothesis 2 Decreases in nutrient loads and improvements in water quality will result in increased fish diversity and a shift from less desirabl e rough fish to more desirable game fish.

Rationale : Reduced nutrient loads will lead to improved water quality and shifts in phytoplankton taxa from cyanobacteria, which are often inedible, toxic, or indigestible by zooplankton, to diatoms, which are preferred foods. Load reduction will also lead to a change in the relative proportion of hetero trophic carbon producti on to autotrophic carbon production which will lead in turn to an increase in food for zooplankton and forage fish and a shift from planktivorous and benthivorous specie s to more desirable piscivores.

Hypothesis 3 Competition from introduced exotic fauna exer ts negative pressure on desirable native
fish.

Rationale : Exotic animals in Lake Okeechobee now include fish, amphibians, reptiles,
mollusks and macroinvertebrates, as well as av ifauna and mammals. Each of these species exerts different impacts on the ecosystem. Many of these species have been accidentally introduced to the lake, and this situ ation is likely to continue, as new species
are introduced to the United States and s ubsequently spread by boats and other
mechanisms into Florida waters. While the specific effects of exotic animals on Lake Okeechobee are for the most part unknown, resu lts from other ecosystems suggest that exotic fauna displace native species, disrupt established trophic relationships and may
serve as reservoirs or vectors for disease.

Hypothesis 4 Reduction in mud sediment as a conseque nce of water management will improve macroinvertebrate species diversity resulti ng in a positive impact on the food web and in an increase in desirable fish species.

Rationale : The macroinvertebrates surviving in Lake Okeechobee mud sediments are burrowing species (primarily oligochaetes ) that are common in polluted and anoxicMAP, Part 2 – Draft Final December 2006 151 sediments (Warren et al. 1995). Reducing and or capping mud sediments will shift the taxonomic composition of macroinvertebrate fauna towards more pollution-sensitive species that will enhance the available macroinvertebrate food supply for fish.

Hypothesis 5 Prolonged low lake stage, particularly duri ng the breeding season, removes large areas of fish foraging and spawning habitat from us e and negatively impacts recruitment and ultimately fish abundance.

Rationale : When lake stage declines to 12 feet approximately 17 percent of the littoral zone is dry. When lake stage is 11 feet, the entire littoral zone is dry. At these low lake stages vast areas normally available for us e as fish spawning a nd foraging habitat are gone. It is worth noting that while excessively high lake st ages remove littoral fringe habitat from use by fish due to negative impacts on submerged and emergent aquatic vegetation, high lake stages have a compensa tory mechanism in that they open up more upland marsh habitat to potential use by fis h, and may therefore not be as damaging as prolonged low lake stages.

Hypothesis 6 Elevated nutrient loads and high water leve ls favor the development of dense algal
blooms which can result in fish kills and ne gative impacts on other wildlife either through development of anoxic condition when blooms senesce and decay or through the direct effects of cyanotoxin production.

Rationale : As algal blooms declin e, oxygen is consumed and a mmonia is released as the mass of algae degrades. Fish exposed to anoxic conditions or high ammonia concentrations will die if there is no escape. In addition, the dominant cyanobacteria in Lake Okeechobee, Microcystis spp . is capable of producing toxins that are directly
harmful to fish and other wildlife if present in sufficient concentrations.

9.4.11 Littoral Zone Emergent Vegetation Mosaic Ecological Conceptual Model

The model below summarizes environmental interactions that are known to affect emergent vegetation density, ae rial distribution and species composition in the littoral zone of Lake Okeechobee. Emergent vege tation mapping using aerial photography has been conducted at approximately annual intervals in the Lake Okeechobee marsh since 1999. Results from this work will be used in the development of assessment tools based on the hypotheses listed below.MAP, Part 2 – Draft Final December 2006 152 Water

Management

Turbidity Lake levels Wind Waves

Nutrient Concentrations

Littoral Native Emergent Vegetation Mosaic Light conditions

Sediment Type Nutrient Load Management

Sediment Resuspension

Physical Disturbance Exotic Vegetation

Seed Germination

Physiological Stress Exotic Vegetation Management

Non Target Plant Damage

Figure 9-4-6: Littoral Zone Emergent Vegetation Mo saic Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 153 9.4.12 Littoral Zone Emergent Vegetation Mosaic Hypotheses

Hypothesis 1 Prolonged periods of high lake stage have direct and i ndirect negative impacts on shoreline and interior marsh vegetation.

Rationale : Desirable native shoreline ve getation including bulrush ( Scirpus californicus ) and SAV are more likely to be uprooted by wind driven waves when la ke stage is high. Following a reduction in the spatial extent of rooted macrophytes, tu rbidity will increase, light availability will be reduced and plan t growth will be inhibited due to poor water quality conditions. Additionally, the transport of pelagic water (TP > 100 ppm) into interior regions of the marsh where TP con centrations are often le ss than 15 ppm occurs most often at high lake stage. An increase in nutrients in the interior marsh will result in the loss of desirable vegetation such as spik erush and the expansion of cattail and other less desirable vegetation.

Physically, rooted macrophytes help stabilize bottom sediments thereby reducing sediment resuspension during wind/wave ev ents. During the late 1990s shoreline vegetation was commonly exposed to inundation depths > 2 m. This resulted in the uprooting and elimination of 1000s of acres of emergent macrophytes. The loss of shoreline vegetation also was accompanied by an increase in turbidity and a decrease in light availability. The negative feed back loop associated with high lake stage, decreases in the spatial coverage of rooted macrophytes , and declines in wate r quality will further inhibit the growth of desi rable rooted vegetation.

Depth and duration of flooding ar e important in determining th e distribution of emergent macrophytes. In deep water, emergent spec ies may not have enough leaf area above the surface of the water to obtain the oxygen need ed for respiration and/or the carbon dioxide needed for photosynthesis. Reduced oxygen uptake through the leav es can lead to inadequate supplies of oxygen to the roots an d rhizomes and eventually lead to plant death. Thus, high lake stage creates physiolo gical stress in rooted emergent macrophytes that can result in plant death if the water depth exceeds a plants flood tolerance (Van der Valk 1994).

Seeds of a number of desirable emergent species (bulrush for example) will not germinate under flooded conditions. Theref ore, in the absence of draw downs, recruitment of new plants from the seed ba nk will not occur. Prolonged high lake stage inhibits/prevents the germination of many de sirable plant species in the marsh (Williges and Harris 1995). Without recruitment of new plants from the seed bank, the expansion and persistence of desirable marsh vegetation will occur only from vegetative reproduction.

Operating Lake Okeechobee at lower overall la ke stages and providing periodic recession events will reverse these trends and encourag e the expansion of desirable native emergent vegetation.MAP, Part 2 – Draft Final December 2006 154 Hypothesis 2
The occurrence of low water events accelerat es the spread of exotic and nuisance invasive vegetation such as torpedograss, Melaleuca and cattail. However, low water events also will stimulate the germination of desirable native vege tation (e.g., spikerush, beakrush, and bulrush) and enc ourage the occurrence of fire which may help control nondesirable exotic and invasive species.

Rationale : Exotic and invasive species including torpedograss, Melaleuca and cattail grow well in exposed moist soil environments and shallow water habitats. These species commonly form dense monodominant communities that out compete and displace native plant communities, due in part to the absence of their native biocontrol organisms that prevent the exotic plants from becoming inva sive weeds in their original range. Although low water conditions favor the growth of ma ny non-desirable species, it also promotes seed germination of desirabl e native plants and allows for natural and controlled fires which can be effectively used with other mana gement tools to control exotic and invasive species. Periodic low water events occurring with a frequency of approximately once per decade are postulated to provide an appr opriate balance between the positive and negative effects of low water events.

Hypothesis 3 Floating exotic vegetation can have a negative impact on bulru sh and other native plants which is further exacerbated under high lake stage conditions.

Rationale : High lake stage enhances the wind driv en transport of floa ting exotics (water hyacinth and water lettuce) from previously isolated locations (interior areas of Torry and Kreamer Islands) and from the watershed into open shoreline regions of the marsh. These exotics, especially water hyacinth, comm only form large floating mats that exceed 50 m in length. These mats can cause ex tensive physical damage through uprooting and/or breaking emergent plant stems (e.g., bulrush) as they are pushed around the lake by wind and waves.

Hypothesis 4 Exotic vegetation management activities can ha ve a negative impact on bulrush and other native non-target species.

Rationale : Floating mats of water hyacinth and water lettuce commonly occur along the littoral-pelagic interface (shoreline). To redu ce the areal coverage of these exotic species and maintain navigational access to the lake, th ese mats are often spra yed with herbicide. Because the mats are commonly entangled in stands of bulrush and other native vegetation, some non-target plant damage is lik ely to occur during treatment. While it is recognized that chemical control of exo tics is an unavoidable necessity on Lake Okeechobee (see section 9.4.7) at times, the non-target damage can be extensive.MAP, Part 2 – Draft Final December 2006 155 Water Management

Exotic and Invasive Plants Nutrient Load Management

Exotic and Invasive Control Programs

Lake Levels Introduction of Exotic Species 9.4.13 Exotic Vegetation Ecological Conceptual Model

The model below summarizes our current un derstanding regarding control of exotic and/or invasive vegetation in the littoral zone of Lake Okeechobee. Despite the environmental changes that will eventually be brought about by CE RP projects, it seems clear that ongoing vegetation management activiti es will nevertheless continue to be an essential component of lake management activities for the foreseeable future.

Figure 9-5-7 : Exotic Vegetation Conceptual Ecological Model

9.4.14 Exotic Vegetation Hypotheses

Hypothesis 1 Vegetation management activities can effec tively control exotic and invasive plant species in Lake Okeechobee. When exotic vegetation is removed from the landscape, native plants are likely to become reestablish in previously impacted areas.

Rationale : Floating mats of water hyacinth and wa ter lettuce and monodominant stands of torpedograss, Melaleuca , and Brazilian Pepper trees have effectively been controlled with herbicides. Both aerial and ground based treatments have been effective. However, in some areas non-target damage to nativ e vegetation may be a serious concern.MAP, Part 2 – Draft Final December 2006 156 Spikerush and other native plants have beco me established in many areas previously impacted by torpedograss.

Hypothesis 2 The transport of pelagic water (TP > 100 ppm) into interior regions of the marsh where
TP concentrations are often less than 15 ppm occurs most often at high lake stage. Eutrophication of the interior marsh will result in the loss of desirable vegetation such as spikerush and sawgrass and lead to the e xpansion of cattail and other non-desirable vegetation.

Rationale : The expansion of cattail into Moonshine Bay in the 1980s first occurred along open airboat trails and in Cochran’s pa ss. These areas were connected to the littoral-pelagic interface and likely received periodic inputs of P rich water during periods of high lake stage. Since th e 1990s, hundred’s of acres of frag rant water lily also have become established along the lake’s shoreline and at interior marsh sites including Moonshine Bay.

9.5 Water Supply and Flood Protection

The AT currently does not have guidance for the assessment of water supply and flood protection. However, Renken et al. (2005) have prepared a review of the impacts of anthropogenic development on the coastal ground-water hydrology in Southeastern Florida from the period 1900-2000. The follow ing is a summary of the findings of this study and will served as an introduction to th e problem of conducting assessments on this topic.

The urban and agricultura l corridor of southern Florida lies between the Everglades and
water-conservation areas to the west and the At lantic Ocean to the east. The area, which includes eastern Miami-Dade, Broward, and Palm Beach Counties, has experienced explosive population growth (from less than 4,000 residents in 1900 to 5 million residents in 2000), and as such is subj ect to widely conflicting stre sses on the environment. A highly controlled water-management system evolved during the 20th century largely to provide drained land for a rapidly expanding population. Reclamation of Everglades wetland areas provided the opportunity for west ward expansion of agricultural, mining,
and urban activities. Surface water is im pounded in water-conservation areas that lie west of the protective levee sy stem, partly to: (1) sustain an Everglades ecosystem, (2) keep overland sheetflow from moving eastw ard and flooding urban and agricultural areas, and (3) use for water supply.

Parallel environmental interests exist in coastal areas of the urban-agricultural corridor.
Coastal residential and urba n areas must be drained for flood control, whereas the underlying surficial aquifer system must simulta neously serve as the principal source for water supply, and ground-water heads must be ma intained to prevent saltwater intrusion. Changes in predevelopment gr ound-water flow patterns and the associated reduction in ground-water discharge to coastal bays have altered salinity and affected the local ecology. Active since the earl y 1920s, extractive mining ha s increased considerably,MAP, Part 2 – Draft Final December 2006 83 9.1.3 Oyster Conceptual Ecological Model

The model below summarizes environmental in teractions that are known to effect oyster health and abundance. Many of these paramete rs are currently being monitored and will be used in the assessment process ba sed on the hypotheses listed below.

9.1.4 Oyster Hypotheses

Hypothesis 1
Undesirable shifts in the estuarine salinit y envelope result in decreased survival, reproduction, spat recruitment, growth and increased susceptibility to predation and
diseases such as Perkinsus marinus (DERMO) and Haplosporidium nelsoni (MSX) in the southeast estuaries oysters.

Rationale: Large rainfall events a nd subsequent watershed r un-off, or large volume releases from Lake Okeechobee cause large vo lumes of freshwater ove r a short period of time to enter the estuary causing a sudden drop in salinity. This s udden drop can lead to significant mortality in the oys ter population, changes in food type and availability and Water Management

Hydrodynamics Sedimentation (muck and rate) Salinity Adult Density Temperature

Predation

Dissolved Oxygen Larval Recruitment

Disease Food Reproduction

Substrate

Oyster Abundance and Health

Figure 9-1-3 : Oyster Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 84 decreased growth, reproduction, and spat re cruitment. Extreme droughts can also negatively impact oysters by making them prone to disease and predation.

Hypothesis 2 Accumulation of muck (high organic content depositional matter) on available substrate or nearby areas will make substrate unsuita ble for oyster larval settlement and thus recruitment and growth of larv al oysters. In addition, acc umulation of muck may also impact the dissolved oxygen content making the area / substrate unsuitable for larval settlement and growth.

Rationale: Oyster recruitment is negatively e ffected by the accumulation of mucky sediments in the estuary. Muck is unsuitabl e substrate for spat settlement. Areas that
once contained sand and/or shell have been covered by these very soft, unconsolidated
sediments. Freshwater inflow carries sediment s with silt, clay and high organic content.
Freshwater inflow from canals can also result in an increase in the transport of floating aquatics, which then degrade and contribute to the rate of muck accumulation.

Hypothesis 3
Increased sediment loads in the water column impair respiration and feeding of oysters resulting in decreased growth and condition index or reproduc tive health of oysters. In addition, sediment accumulation on oyster shel l negatively affects spat recruitment.

Rationale: Oyster populations are affected by incr eased sediment loads resulting from alterations to the natural hydrology. A dult oysters have effective morphological adaptations for feeding in much higher leve ls of suspended solids than are usually encountered under normal conditions. Oysters fr om relatively turbid estuaries appear to be capable of feeding at to tal suspended solid concentra tions as high as 0.4 g/l but significantly reduce their pumping rates at concentrations as low as 0.1 g/l. Suspended solids may clog gills and interfere with filtering and respiration of oysters. Deposition of sediment on oyster shells also makes them unsuitable for spat settlement.

Hypothesis 4 Increase in oyster reef coverage will enhance secondary habitat for other estuarine species resulting in increase d diversity and abundance.

Rationale: Oysters are natural components of South Florida estuaries and were documented to be abundant in the system . Although currently less abundant, they continue to be important. Reduction in oyster coverage was la rgely due to altered freshwater inflow, shell mining, and cha nges in hydrodynamics. This decrease has resulted in a loss of oyster reef community and the estuarine species that use this habitat.MAP, Part 2 – Draft Final December 2006 85 9.1.5 Fish Conceptual Ecological Model

The model below summarizes environmental in teractions that are known to effect fish abundance. Many of these parameters are curre ntly being monitored and will be used in the assessment process based on the hypotheses listed below.

9.1.6 Fish Hypotheses

The fish model ranks water quality para meter hypotheses in order based on their importance and value to fish physiology in a su btropical/tropical setti ng. This ranking is based on research results in northern estuary seagrass, mangrove and freshwater tributary studies. Relevant parameters are ranked as follows: 1- Dissolved oxygen; 2- Nutrients; 3 - Salinity; 4 - pH; 5 - Temperature.

Hypothesis 1 Dissolved oxygen levels within the northern estuaries will directly influence fish population dynamics within these estuaries.

Figure 9-1-4 : Fish Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 86 Rationale: Dissolved oxygen. Tropical/subtropical systems are warm thus reducing the oxygen carrying capacity of water. Warm wate r systems often have high productivity if sufficient nutrients are present, thus ofte n eutrophicating aquatic systems, increasing BOD. Since prolonged extreme (< 18 C) cold water periods are rare, particularly in the St. Lucie River system, primary production and detrital production occurs year round.
This environmental condition is common throughout the world tropics. For this reason the indigenous tropical fish community shows physiological adaptations to low DO conditions. For instance: tarpon, gar, a nd mudfish are obligate air breathers; snook, bigmouth sleepers, fat sleepers, crested gobies , rivulus, mosquitofish, and tropical mullet species are facultative air breathers and surface water sippers, all capab le of withstanding DO levels as low as 1.0 ppm or lower. Most temperate to wa rm temperate fishes, spotted seatrout, red drum, black drum, sand seatrout , and Atlantic toadfi sh apparently do not have the capability to withstand low oxygen conditions. This complex scenario with a complex indigenous fish fauna means that our studies of water quality impacts on fish populations will have to be exam ined at the species level.

Hypothesis 2
Nutrient concentrations in the Northern Estuar ies are directly associated with fish health and mortality in these estuaries.

Rationale: Nutrients. It is apparent from rese nt observations over the past 30 yrs that plankton and harmful algal blooms (HABs) fe d by nutrient loading have had substantial impacts on fish health and survival in the nor thern estuaries. The list of impacted species continues to grow annually to th e point that no species can be left out of this analysis. Initially 1970's observations indicated that mu llet were most likely to be impacted by HABs. We assume that nutrient levels, wa ter turbulence and sedi ment resuspension produce conditions that are fa vorable for algal blooms. Nutrient levels can have substantial impact on HAB production and primar y production levels in general, thus increase BOD/system eutrophicati on and decrease dissolved oxygen.

Hypothesis 3 Rapid and substantial water salinity changes as a result of water management and at levels not typically observed under natural dr y season conditions will have a significant
deleterious effect on stenohaline fish egg/larval, juvenile su rvival at northern estuary spawning and nursery sites.

Rationale: Salinity. Since larval fish and eggs require specific sa linity conditions for survival and fish spawning sites are located within the Northern Estuaries. There is a direct relationship between fres hwater flow and quantity, ambi ent salinities, and potential egg/larval survival. There is a very species ri ch resident and migrator y fish fauna that is distinctly marine, particularly on the Florida east coast, which is very sensitive to salinity change as larvae, juveniles and adults. Ste nohaline larval stages and species use of the northern estuaries is directly associated with ambient water quality with salinity thought to be the most relevant. In contrast, many euryhaline members of the indigenous
estuarine fish fauna of south Florida are notorio us for not being reliant on specific salinity patterns. They have the capability as juvenile s and adults, but not necessarily as eggs andMAP, Part 2 – Draft Final December 2006 87 larvae, to enter freshwater tributaries from the Ocean or Gulf with little or no acclimation. Species that show this mari ne-freshwater migratory patter n are snook, tarpon, bull sharks, sheepshead, striped mullet, various gobies and gray snapper.

Hypothesis 4 Maintenance of water pH levels above 5.0, a nd near neutral, 7 - 8.0 in the Northern Estuaries is beneficial to fish survival, health and mortality in these estuaries.

Rationale: pH: There is little information on pH effects on Florida fish physiology other than major fish mortalities documented in association with phosphate-gypsum storage
mound leaks into the Peace River and Alafia River in recent decades. Extremely low pH levels (< 3.0) are lethal. We do not believe pH will be a problem in the northern
estuaries. Florida freshwater tributaries typically contain large enough concentrations of carbonates that the water appears to be bu ffered. Sulfides in mangrove swamps and backwater sloughs may reduce both DO and pH in localized areas.

Hypothesis 5 Water management impacts on ambient water temperature do not show a direct correlation with fish population dynamics, life history, survival and mortality in the
northern estuaries.

Rationale: Temperature: Since there is apparently very little ambient water temperature change in the northern estuaries associated with water management, water temperature is predicted to not be of much concern. Howe ver, it is recognized that there is a very distinct biogeographic difference between th e Gulf and Atlantic estuarine fish faunas principally due to very diffe rent ambient water temperatur e regimes and ocean current patterns associated with both coastal system s (Caloosahatchee River/Charlotte Harbor: @ 250 fish species versus St. Lucie River/I ndian River Lagoon: @ 500 fish species). Because of this, a stenothermic tropical fi sh fauna is found in the St. Lucie ecosystem that is not present in the Caloosahatchee ec osystem. Due to the endemism of these species within the St. Lucie/Indian River Lagoon systems relative to the United States as a whole, many of these east coast fish species have been of concern for listing as rare, endangered and threatened species by regiona l and national biologists over the past 30

years.

Hypothesis 6
Water flow rates and volumes within the St. Lucie and Caloosahatchee estuaries have a direct influence on fish population dynamics, distribution and migration within these
estuaries.

Rationale : Arrows have been added from the “Hydrodynamics and Oceanography” box in the Fish Conceptual Ecol ogical Model box connecting these physical conditions to the “Fish Prey” and “Fish Foraging” boxes as hydrodynamics and oceanography (water level, bathymetry, tides, winds, current flow rates) have direct influe nce on fish population dynamics, distribution, migration an d survival. This is particul arly true for fish eggs and
larvae.MAP, Part 2 – Draft Final December 2006 88 Hypothesis 7 Changes in the salinity envelope in the nor thern estuaries will not have a detrimental effect if they mimic natural climatically driven salinity regimes (e.g., wet season vs. dry season), and if salinity shifts are more gra dual and extreme rapid changes are avoided.

Rationale: Estuarine populations of stenohaline fishes are most sensitive to atypical salinity regimes as either larvae (spotted seatrout ), juveniles (tropical reef fish: yellowtail, lane and mutton snapper) or adults (spawning spotted se atrout and common snook). Therefore the timing and severity of salinity fl uctuations becomes an important factor in reproduction and growth. Euryhaline fish populations that often associate with oligohaline habitats show a positive associati on with increased freshwater flows relative to food availability (e.g., feeding adult common snook).

Hypothesis 8 Soft sediments that occur naturally in estuarine systems support healthy estuarine fish communities while excessive anthropogenically accelerated accumulations of anoxic muck can have a negative influence on the community.

Rationale: Soft sediment (mud) fish communiti es have a positive association with healthy fine sediments, mud and their be nthic animal communities as a food source (primarily gerreids, mugilids and engraulids) and habitat source (gobioid fishes). Benthic
soft sediment invertebrate communities support the largest biomass component of indigenous St. Lucie/Loxahatchee River fish communities. In contrast, abiotic fine sediments (“muck”) do not support this same soft sediment (mud) fish community and
can create a bottom devoid of life of ten accompanied by anoxic conditions.

Hypothesis 9 Riverine and estuarine sediment compositi on and dynamics dictates recruitment success in centropomids, gerreids, and gobioids de pendent on the northern estuaries.

Rationale: Sediment deposition and distribution is directly associat ed with stream configuration (e.g., meander vs. straight ened) and topography, flow dynamics, water depth and stream bank location and proximit y, thus directly influencing the population status of fish species that associate with shallow marginal sediment deposits (centropomids, gerreids, and gobioids).

Hypothesis 10 Health oyster bed habitat is essential for the survival of oyster reef dwelling fish. Population dynamics in Gobiosoma bosc (Gobiidae) is influen ced by: (1) oyster reef structure; (2) live vs. dead oyster reef struct ure; (3) age and degrad ation/deterioration of oyster reef systems.

Rationale: Gobiosoma bosc plays a major trophic role in northern estuaries due to its
numerical dominance of rive rine ichthyoplankton and as the major vertebrate species directly associated with oyster reefs as crit ical habitat, feeding and spawning sites.MAP, Part 2 – Draft Final December 2006 89 G obiosoma bosc is a major prey item for plankti vorous fishes, chaetognaths, ctenophora, and as an adult prey for juvenile gray snapper Lutjanus griseus

.

Hypothesis 11 Populations of juvenile reef fish (lutjanids , serranids, scorpeanids, gobiids, blenniids and labrisomids) that are dependent on estuarin e seagrass and nearshore hardbottom show a positive relationship with salinity, ex. higher densities at higher salinities,

Rationale: Spawning populations of seagrass and reef associated marine/ mesohaline/ polyhaline fish species are most affected by atypical (aseasonal) re duced salinities during their spawning period. Life history, growth and mortality of marine/ mesohaline/ polyhaline seasgrass/reef associated fish sp ecies are negatively influenced by atypical
and/or aseasonal reduced salini ties which occur both from th e overly ditched and drained watershed as well as from Lake Okeechobee discharges.

Hypothesis 12 Healthy freshwater emergent herbaceous vegeta tion is directly related to oligohaline fish populations.

Rationale: Population dynamics, distribution and survival in syngnathids (opossum pipefish, Microphis brachyurus lineatus ), eleotrids (fat sleeper, Dormitator maculatus ; spinycheek sleeper, Eleotris pisonis ), poeciliids and centrarchids are influenced by freshwater emergent vegetation species distri bution quantity and vegetative structure. The ability to obtain and maintain a healthy freshwater emergent vegetation zone depends on being able to avoid large fluxuations in salini ty in the riverine port ions that feed into the main estuary.

9.1.7 Submerged Aquatic Vegetation Conceptual Model

The model below summarizes environmental in teractions that are known to affect the cover, abundance and productivity of subm erged aquatic vegeta tion. Many of these parameters are currently being monitored and will be used in the assessment process based on the hypotheses listed below.MAP, Part 2 – Draft Final December 2006 90 9.1.8 SAV Hypotheses

Hypothesis 1 Extreme fluctuations in estuarine salinity resulting from hydrologic alterations, water management practices, and sea level rise ha ve had a negative effect on SAV function and have resulted in large decreases in spatial extent of SAV in the Northern Estuaries.

Rationale: Species composition and density of SAV communities are directly linked to the mean salinity and the variation around the mean at any given lo cation. In the upper estuary, the naturally occurring submerged grass species, Vallisneria americana, will not survive prolonged periods of elevated salinity that occur as a re sult of manipulated
freshwater flow. Halodule wrightii persists in areas with hi gh variation in salinity.
Thalassia testudinum and Syringodium filiforme will not tolerate prolonged periods of reduced salinity as a result of freshwater discharges from the local basin or Lake Okeechobee, and persist in areas with relatively low variation in salinity.

Hypothesis 2 Large deposits of organic, fine silt, and clay materials, i.e ., muck, have displaced normal sandy substrate in the Northern Estuaries, thereby contributing to the decrease in extent
of SAV beds. Figure 9-1-5 : Submerged Aquatic Vegetation Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 91 Rationale: Sediment characterist ics (e.g. nutrients, oxygen, microbial communities) are important to SAV survival; these characteristics will be altered by the increased deposition of fine silts and orga nic matter. Fast growing SAV (e.g. Halodule wrightii ) requires higher nutrient levels in the se diment, than slower growing forms (e.g. Thalassia
testudinum ). Anoxic sediment will lead to sulphide intrusion in SAV rhizomes leading to die-back. Microbial communities are important to the biochemical reactions occurring
around the SAV rhizomes.

Hypothesis 3 Input of increased levels of nutrients, dissolved organic ma tter and turbidity affect SAV abundance and health by increas ing phytoplankton levels and wa ter color, which in turn decreases the amount of light that penetrates the water column to become available to
SAV.

Rationale: Sediment loads (turbidity), color and chlorophyll increas e light attenuation which is directly correlated to decreased de pth distribution and s hoot density of SAV. Seagrasses require more light than macro- algae or phytoplankton, therefore decreased light (increased light attenuation) will reduce the ability of se agrass to compete with these other species. Halodule wrightii and Syringodium filiforme require less light than
Thalassia testudinum , therefore a prolonged in crease in light attenua tion will lead to a shift in species composition. Sulphide toxici ty occurs as a result of increased light attenuation and a decreased ability for plants to photosynthesize and oxygenate the sediments surrounding the rhizomes.

Hypothesis 4 Negative changes in SAV community structur e and function along with changes in the natural salinity regime have resulted in a decrease in larval and adult fish recruitment in
the Northern Estuaries.

Rationale: There is a quantifiable relationship be tween fish and seagrass habitat that is influenced by ambient salinity regimes. Es tuarine seagrass and nearshore hardbottom dependent populations of juvenile tropical reef fish (lutjanids, serranids, scorpeanids, gobiids, blenniids and labrisomids) show a pos itive relationship with salinity, e.g. higher densities at higher salinities. Extreme and ra pid salinity fluctuations degrade SAV habitat that many estuarine dependant fish rely on for spawning, nursery and foraging habitat.

Hypothesis 5 Increased epiphyte growth can be caused by both increases in available nutrients that accelerate growth and/or a decrease in grazing pressure.

Rationale: SAV losses have been associated wi th over-enrichment of estuarine waters, which stimulates growth of epiphytes, resu lting in reduction of phot osynthetically active radiation (PAR) at the SAV blades. Herbiv orous grazing on epiphytes can partially relieve SAV growth inhibition at moderate nut rient loading rates but does not seem to significantly alter plant response at higher nutrient levels.MAP, Part 2 – Draft Final December 2006 92 9.1.9 Benthic Infaunal Community Conceptual Ecological Model

The model below summarizes e nvironmental inte ractions that are known to effect benthic community structure. Many of these paramete rs are currently being monitored and will be used in the assessment process ba sed on the hypotheses listed below.

Water Management

Nutrients

Sedimentation (muck and rate) Hydrodynamics

Substrate Dissolved Oxygen Salinity

Hydrogen Sulfide

Benthic Community Structure

9.1.10 Benthic Infaunal Community Hypotheses

Hypothesis 1 Irregular and extreme shifts in salinity in the St. Lucie Estuary prevent the establishment of a natural healthy estuarine infaunal community

Rationale : In contrast to a natura l estuary where the riverine input is relatively stable, and/or relatively predictable, throughout th e year, resulting in a wedge-shape bottom layer of higher salinity (strong pycnocline), th e irregular and massive freshwater releases from the primary SFWMD canals which drain the estuary’s expanded basin and regulatory releases from La ke Okeechobee to both the Ca loosahatchee and St. Lucie Estuaries lead to sudden and dramatic drops in salinity in the entire water column. These unstable conditions prevent the establishment of a diverse and healthy estuarine benthic infaunal community (a very important food source for many fish and bird species). Benthic animals are directly or indirectly involved in most physical and chemical

Figure 9-1-6 : Benthic Infaunal Community Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 93 processes that occur in estuaries, processe s that will be dist urbed by these salinity changes.

Hypothesis 2 The anthropogenically exacerbated accumulatio n of soft unconsolidated and strongly reducing sediments in the estu ary inhibits the establishment of infaunal species resulting in an impoverished community character ized by low diversity and density.

Rationale : Abiotic factors, such as sediment grain size and quality determine broadscale benthic community patterns . Fine sediment deposits are a typical characteristic feature of most estuaries; however, wide s cale predominance of fine sediments at the expense of other typical estuarine sediment type s, as is present in the St. Lucie estuary, constitutes a patently man-i nduced geologic imbalance that is necessarily reflected in both the benthic community and the higher trophic level species which rely on the
benthos.

Hypothesis 3 The frequent re-suspension of fine sediment s in the St. Lucie Estuary severely impacts certain infaunal species important for the ecosystem stability.

Rationale : Suspension feeders, such as many bi valves tend to predominate in sandier sediments. They feed and eliminate wa stes by either pumping water through their burrows, where it is filtered out and pump ed out, or by extending feeding structures above the bottom through which water is pumped and filtered. The increase in suspended sediments likely clogs the filtering apparatus of the suspension feeders, resulting in a community dominated by deposit feeders, i. e., a community not in balance among functional groups.

Hypothesis 4 Low oxygen concentrations, and at time s significant concentrations of H 2 S in the waters adjacent the bottom sediments often occurs re sulting in mass mortality and prevents the settling of larvae, adversely affecting the infaunal communities.

Rationale : As a result of the widespread depos ition of typically strongly reducing fine unconsolidated sediments, bottom waters are likely to exhibit depressed oxygen concentrations, and in some events cont ain significant quantit y of sulfide from decomposition processes occurring in the se diment. Such conditions may likely be extensive on occasions when temperatures ar e higher (during the su mmer) or when wind induced mixing is low. Low oxygen concentr ations have also been associated with freshwater discharge (Stanl ey and Nixon 1992). Such h ypoxic, anoxic, and/or toxic conditions result in mortality of the sessile benthic communities, which may be followed by a rapid establishment of opportunistic speci es. Overall these conditions result in a severe disturbance of the entire estuarine ecosystem.

Hypothesis 5 Increases in nutrient concentrations may direct ly or indirectly seriously impact benthic abundance, biomass, diversity and species composition.MAP, Part 2 – Draft Final December 2006 94 Rationale : All benthic heterotrophs regenerate nutrients that can stimulate primary production. This primary production may be be neficial for some benthic animals (e.g. suspension feeders), but a high primary production caused by nutrient increases can often lead to lower oxygen concentrations near, and at the bottom. This may be devastating to a large number of infaunal species, and lead to higher relative abundances of species tolerant to low oxygen levels. This commun ity will also usually wind up dominated by a few opportunistic (r-strategists ) species. These species usually occu r in large numbers, but with a very low diversity, and may impact other species (fish, larg e invertebrates) that are dependent on a diverse bottom community as the food source.

9.2 Greater Everglades Wetlands Module

9.2.1 Module Location Descriptio n and Background Information

The remaining portion of the Greater Evergl ades Wetlands includes a mosaic of interconnected freshwater wetlands and estuarie s (Figure 9.2.1). A ridge and slough system of patterned, freshwater p eatlands extends throughout the Water Conservation Areas (WCAs) into Shark River Slough in Everglad es National Park. The ridge and slough
wetlands drain into tidal rive rs that flow through mangrove estuaries into the Gulf of Mexico. Higher elevation wetlands that are ch aracterized by marl substrates and exposed
limestone bedrock flank either side of Shar k River Slough. The marl prairies and rocky glades to the east of Shark River Slough include the drainage basin for Taylor Slough, which flows through an estuar y of dwarf mangrove forests into northeast Florida Bay. The Everglades marshes merge with the fo rested wetlands of Big Cypress National
Preserve to the west of WC A 3 and Everglades National Pa rk. Also included in the Greater Everglades Wetlands are the Lake Okeechobee littoral zone and the hydric pinelands and seasonal wetlands of the J.W. Corbett/Pal Ma r Wildlife Management Area.

The Greater Everglades Wetlands Module combines four conceptual ecological models:

1) Everglades Ridge and Slough 2) Everglades Southern Ma rl Prairies including th e Taylor Slough basin 3) Everglades Mangrove Estuaries including the mangrove estuaries of Florida Bay and
the Gulf of Mexico westward to Lostman’s River 4) Big Cypress Basin eastern portions that will be influenced by the CERP

Major stressors currently impacting Greater Everglades Wetlands in clude disruption of sheet flow and associated hydropatterns, sea level rise, nutrient inputs and eutrophication, and non-native plants and animals. The Greater Everglades Wetlands Module includes
five clusters of in terrelated hypotheses:

• Integrated Hydrology And Water Quality

• Coastal Transgression, Tidal Channel Char acteristics, Salinity Gradients, and Mangrove Forest Productivity

• Wetland Landscape and Plant Community Dynamics

• Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage BaseMAP, Part 2 – Draft Final December 2006 97 Timing Trophic Level – Wood Stork and Roseate Spoonbill Nesting Success 3.1.3.14 Underway (USGS/UF, ENP/ FAU), started July 2004

American Crocodile Juvenile Growth
and Survival 3.1.3.16 Underway (USGS/UF), started July 2004 Factors Affecting Successful Snail Kite (Rostrhamus sociabilisplumbeus) Nests in the KissimmeeOkeechobee Everglades Basin Proposed for USACE FY06 budget

Key Uncertainties and Supporting Research Coastal Wetland and Berm Systems:
Sea Level and CERP Influences 3.1.4.1

Tidal and Freshwater Creek Dynamics: Sea Level and CERP
Influences 3.1.4.2

Productivity in Coastal Ecotone: Sea
Level and CERP Influences 3.1.4.3

Ridge and Slough Landscape Pattern Sustainability 3.1.4.4. SFWMD to implement research
in FY06 Technology Development: NASA Vegetation Mapping 3.1.4.5

Crayfish Population Dynamics – Hydrological Influences 3.1.4.6 Underway, started June 2004

Aquatic Refugia – Coastal Ecotone, Alligator Holes and Solution Holes 3.1.4.7

Ecological Effects of Canals and Other Artificial Deep Water Habitats 3.1.4.8 Proposed for USACE FY06 budget

Synthesis of Wading Bird Distribution Surveys 1985-2001 3.1.4.9 Contract currently in
amendment for time due to modeling delays

Sub-lethal Effects of Contaminants on Wading Bird Reproduction 3.1.4.10 Phase I underway-Aviary construction and stocking with
White Ibis

9.2.3 Integrated Hydrology and Water Quality

Direct rainfall and discharge from Lake Okeechobee onto a vast wetland landscape of low topographic relief, a pervious limerock ge ological setting, and a subtropical climate resulted in sheet flow and low levels of phos phorus and other chemical constituents in the pre-drainage Everglades. Together, these physical-che mical drivers defined the Everglades as a unique ecosystem and are a major influence on all of its ecological processes and attributes.

Restoration of the Everglades ecosystem de pends on restoration of the volume, timing,
and distribution of sheet flow and on rest riction of inputs of phosphorus and other chemical constituents to levels approximating those in direct rainfall.MAP, Part 2 – Draft Final December 2006 98 Sheet flow and inputs of phosphorus and othe r chemical constituents fundamentally affect all working hypotheses for greater Ev erglades wetlands ridge and slough landscape dynamics, plant community distributions al ong elevation gradients, predator-prey interactions of wading birds and their aqua tic fauna forage base, crocodilian population dynamics, coastal salinity gradients, co astal transgression, and mangrove forest production.

Direct Rainfall as Primary Water Source Integrated Hydrology and Water Quality Conceptual Ecological Model

Sheet
Flow Low Inputs of P and Other Chemical Constituents

Natural System Hydrologic Characteristics

•Hydroperiod & water depth patterns •Rainfall-driven pulsed flow events •Hydraulic residence time •Landscape form & pattern
•Surface water contact with substrates & biota •Surface water/groundwater interactions
•Freshwater flows to estuaries

Wetland Nutrient State

Periphyton Mat

Greater Everglades Wetlands Working Hypotheses

•Ridge & slough landscape dynamics •Plant community distribution along elevation gradients •Coastal transgression, tidal channels, salinity, & mangrove forests •Wading bird predator/prey interactions •Crocodilian population dynamics

Figure 9-2-2 : Integrated Hydrology and Water Quality Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 99 Hypothesis 1
Rainfall and Sheet Flow as Determinants of Natural System Hydrologi c Characteristics in the Everglades

The volume, timing, and distribution of sheet fl ow, in combination with direct rainfall, produced fundamental hydrologic and landscape characteristics of the pre-drainage Everglades that can be described by the following parameters:

• Hydroperiod and water depth patterns

• Rainfall-driven pulsed flow events

• Hydraulic residence time

• Landscape form and pattern

• Surface water contact with substrates and biota

• Surface water/groundwater interactions

• Freshwater flows supporting beneficial sa linity patterns in th e mangrove estuaries of Florida Bay and the Gulf of Mexico

Compartmentalization has altered or eliminat ed sheet flow and related natural system hydrologic and landscape characterist ics throughout the Everglades. Decompartmentalization, combined with resump tion of natural volume, distribution, and timing of freshwater delivery is expected to restore sheet flow and pre-drainage hydrologic and landscape characte ristics to an undivided ecosystem encompassing much of Water Conservation Area 3A, Water Conser vation Area 3B, easter n Big Cypress, and Everglades National Park.

Rationale: Specific hydrologic restoration target s associated with the resumption of sheet flow and related hydrol ogic characteristics include:

• Multi-year hydrope riods in ridge and slough landscape

• Conditions conducive to peat forma tion in ridge and slough landscape

• Hydropatterns that sustain co-existi ng sloughs and sawgrass ridges in the ridge and slough landscape

• No distinct or persistent changes in water levels across boundaries such as canals, levees, or roads

• Large-scale surface water flow directi ons that follow the historic landscape directionality

• Hydropatterns that support th e long-term stability of tree islands in ridge and slough landscape

• Hydroperiods from two months to le ss than one year conducive to marl formation and muhly grass ( Muhlenbergia filipes ) community persistence in Southern marl prairiesMAP, Part 2 – Draft Final December 2006 100 • Persistent pools of fresh to oligoh aline water along the interface of the freshwater Everglades and the mangrove ecotone of Florida Bay and the Gulf
of Mexico

• Dry season water recession patterns c onducive to successful wading bird foraging

• Multi-year flood and drought cycles s upporting formation of wading bird super-colonies

• Absence of harmful regulatory releases of excess fresh water to the Greater Everglades

• Freshwater flow discharges to Flor ida Bay and the Gulf estuaries that maintain a near shore salinity gradie nt characteristic of pre-drainage
conditions.

Natural system hydrologic restoration targ ets are necessarily qualitative due to uncertainty regarding pre-drainage hydrology. Successive iterations of the Natural System Hydrology Model (NSM) quantify thes e targets for planning purposes despite high levels of uncertainty. Successful restoration of natu ral system hydrologic characteristics as CERP is implemented ultimately must be guided by AM based on measured responses of the ecosystem to hydrologic changes.

Hypothesis 2 Nutrient Inputs and Sheet Flow as Determinants of Wetland Nutrient State in the Everglades

The dominance of direct rainfall as the primary source of water and phosphorus, in
combination with sheetflow a nd related hydrologic and climatic characteristics, resulted in an oligotrophic, phosphorus-limited nutrien t state throughout the greater Everglades wetlands prior to drainage.

Rationale: Increased phosphorus concentrations and loads in agricultural runoff water, and replacement of sheet flow with canal flows and point-source discharges, have produced phosphorus concentration gradients do wnstream of canal discharge structures, shifting wetlands from oligotrophic to eutrophic states. Water column total P concentrations are below ~10 ppb under non-en riched conditions in the Everglades. Most harmful ecological responses to P enrichment occur within a range of mean annual water column total P concentrations between ~10-30 ppb.

Reduction of the magnitude of nutrient inputs to the Greater Everglades will have the following effects:

• Reductions in phosphorus in inflow wate rs to the Greater Everglades will influence the downstream rate of recovery of ecosystem components.

• Existing gradients of phosphorus, nitrogen and sulfur will decrease between input locations and Everglades National Park.MAP, Part 2 – Draft Final December 2006 101 • Where water quality constituent gradients currently do not exist, none will form.

• Non-impacted areas immediately downstream of impacted areas may be affected by phosphorus currently present in the impacted areas, i.e., presently enriched zones in WCAs will continually move south, especially under sheet flow
conditions.

• Phosphorus and nitrogen concentrations in soil, flocculent organic matter, and periphyton will reflect patterns and tre nds in surface water concentrations, integrated over various time s cales, from months to years.

Hypothesis 3 Nitrogen Dynamics in the Everglades

Nitrogen dynamics, such as rates of nitrif ication, denitrification, uptake of inorganic nitrogen species, and production of organic nitrogen, are dominated by local cycling and processing under natural conditions in the Everglades.

Rationale. The importance of local nitrogen cyc ling and processing presently increases
with distance from surface wa ter inflow locations, while th e importance of surface water nitrogen loading concurrently decreases. This trend is expected to continue under restored water inflows and associated nitrogen loadings.

Hypothesis 4 Periphyton Mat as an Indicator of Integr ated Hydrology and Water Quality in the Everglades

Periphyton mat structure and community composition integrate hydrology and water quality across the enti re wetland system of the Everglad es. Hydrology and water quality interact to create a mosaic of periphyton community types throughout the Everglades.

Rationale: Periphyton responds quickly (weeks to months) to alterations in water management and can serve as early wa rning indicators of ecosystem change.

Shortened hydroperiods cause:

• Reduced proportion of diatoms and green algae relative to cyanobacteria

• Increased calcareous blue-green alg ae, possibly reducing food value of periphyton

• Increased proportion of sediment or plan t-stem associated mats as opposed to floating mats attached to floating macrophytes (such as Utricularia purpurea ).

• Decreased organic ash wei ght ratio of periphyton

Phosphorus enrichment through increased loading causes:

• Elevated nutrient conten t of periphyton material

• Increased organic content of periphyton communitiesMAP, Part 2 – Draft Final December 2006 102 • Reduced calcareous floating and epiphytic periphyton mats

• Replacement of low nutrient-tolerant species by non-mat forming filamentous green algal species

Periphyton productivity is very high in the olig ohaline zone of the southern Everglades. Increased freshwater delivery may broaden this zone of high periphyton productivity.

Detection of periphyton response to changes in hydrology and water quality needs to be based on comparison to a habitat-specific base line (i.e. ridge and slough, marl prairie, rocky glades, or oligohaline zone). In addition, the effect s of grazing on the periphyton community composition should be quantified.

9.2.4 Coastal Transgression, Tidal Channel Ch aracteristics, Salinity Gradients, and Mangrove Forest Productivity

Ecological processes and attributes in the mangrove coastlines of the southern Everglades are hydrologically controlled by interact ions between overla nd sheet flow from
freshwater wetlands and the waters of the Gu lf of Mexico and Florida Bay. Changes in freshwater flow from the implementation of CERP projects are rela tively short-term in comparison to the longer-term, progressively increasing changes in salinity and coastal hydrologic budgets resulting from relative sea level rise.

The rate of relative sea-level rise in sout h Florida increased began increasing in about 1930. Since that time, relative sea-level in south Florida has increased about 23 centimeters (9 inches), or 30 cm (one foot) per century. Anticipated responses of sea level rise to global warming is projected to re sult in a global increase in sea level of about 60 centimeters (two feet) in the coming century.

The CEMs presented in this section differ from the others in this document in that the endpoints are the results of the impact of th e stressors as manifest through the causal pathways.MAP, Part 2 – Draft Final December 2006 103 Coastal Transgression Conceptual Ecological Model

Sea Level/
Freshwater Flow
Interaction Disturbance Events

Hurricanes
•Fires
•Freezes

Coastal Sediment Import/Export

Coastal Substrate Accretion/Overtopping

•Red mangrove
•Marl embankment •Oyster communities Hydrologic Flushing

Encroachment

Of Marine Conditions

Destabilization, Collapse, & Subsidence Of Coastal Wetland Communities

Conversion of Coastal Wetlands To Sub-aqueous Environments

Figure 9-2-3 : Coastal Transgression Conceptual Ecological Model

Hypothesis 1
Sea Level and Freshwater Flow as De terminants of Coastal Transgression

Sustained substrate buildup by physical and bi ological processes in many coastal marl and mangrove environments of South Florid a may not be capable of keeping up with rates of sea-level rise during the 21 st century.MAP, Part 2 – Draft Final December 2006 104 Where rates of peat or marl elevation buildup do not keep up with ra tes of sea level rise, shoreline transgression and landward salinity intrusion into mangrove and freshwater
wetlands will occur.

Rationale: Red mangrove forests in south Florid a can potentially accrete organic peat substrate at 2-6 mm/year. Disturbances (m ajor hurricanes, fire, freeze, and changing flushing) disrupt these peat accretion rates and commonly result in alternating phases of substrate subsidence and decay. Salinity stress may also reduce accretion rates. In this time of rapidly rising sea level, most mangr ove communities are presently losing area of coverage. In the coming century the coasta l mangrove community may be expected to become increasingly dissected. Sustained rates of accretion of coastal marl shorelines of Florida Bay may also be incapable of keeping up with the rate of sea level rise, and overtopping and breaching of embankments duri ng storm events are likely under future scenarios of rising sea level.

Where rates of peat or marl elevation buildup do not keep up with ra tes of sea level rise, shoreline transgression and la ndward salinity intrusion will lead to mangrove erosion along shorelines and mangrove movement into in terior landscapes. Sa line intrusion into
freshwater wetlands underlain by peat substrate may lead to wetland community collapse and transformation to open, saline ponds and estuaries. Saline in trusion into marl
substrate wetlands results in an advancing zone of diminished productivity (this is often called the “white zone”). Restoration of fres hwater flow volume, timing, and distribution may slow the inland movement but it is not e xpected to change the rate of erosion along
the shoreline.

Hypothesis 2
Sea Level and Freshwater Flow as Determ inants of Tidal Channel Characteristics

The dendritic pattern, channel width and depth, flow volume, and material transport of tidal watercourses and channels through the co astal mangrove estuaries are controlled by sea level interacting with the volume, timing, and distribution of sh eet flow and channel flow from the southern Everglades.

Rationale: Restored freshwater inflow from the Ev erglades is expected to help sustain open watercourses through the estuary that will more closely resemble historic patterns, and re-open some channels that have partly fi lled because of reduced flow. Sea-level rise is expected to modify the patterns of connectivity and channel patterns through the
coastal wetlands and create increased sediment loads.

With rising sea level, offshore marine waters become connected to interior depressions (interior lakes and collapsed freshwater marsh areas) by a combination of connecting channels, sheet flow through wetlands, and/or flow across inundated ridges, such as the
buttonwood embankment. These connections increase the flood tidal prism (area and volume of flood tidal water) and result in enha nced flood and especially ebb tidal flow. This process is expected to result in str onger tidal currents through channels resulting in enhanced erosion and widening of those channe ls. Such conditions are expected to resultMAP, Part 2 – Draft Final December 2006 105 in an increased import and/or export (depending on setting) of particulates, nutrients and dissolved organics. Sea-level rise is expected to destabil ize many coastal and nearshore marine sedimentary environments resulting in increased movement of fine-grained sediment in the coastal zone. Significant portions of this sediment probably will be moved inwards through tidal channels into interior coastal bays and wetlands.MAP, Part 2 – Draft Final December 2006 106 Tidal Channel Characteristics Conceptual Ecological Model

Sea Level/
Freshwater Flow
Interaction

Tidal Channel Characteristics

•Dendritic pattern •Channel width & depth
•Flow volume •Material transport Increased Connection of Offshore Marine

Waters to Interior

Water Bodies

Increased Tidal
Flow Volume

& Velocity

Channel Erosion & Widening

Increased Import/Export Of Particulates, Nutrients,

& Dissolved Organics

Figure 9-2-4 : Tidal Channel Characteristics Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 107 Hypothesis 3
Sea Level and Freshwater Flow as Dete rminants of Coastal Salinity Gradients

Sheet flow in the southern Everglades prio r to drainage produced prolonged pooling of fresh water upstream of the mangrove estuarie s and prolonged patterns of freshwater flow into the mangrove estuaries.

The freshwater pooling and in flow supported a wide salinity gradient, including a broad oligohaline zone, in the mangrove estuary.

A combination of historical reduced freshwater flow and increased relative sea level rise has resulted in higher salinities in the formally estuarine mangrove zone and significant
saline intrusion into former freshwat er marshes of the lower Everglades.

Rationale: Increasing seasonal freshwater sheet flow to the lower Everglades is expected to provide a broader zone of salinity grad ients in the lower Everglades and coastal wetlands and should, in the short term, re-est ablish an oligohaline zone in the coastal
wetlands.

Although surface water salinities fluctuate laterally through the wet and dry seasons, saline groundwater intrusion has moved and remains far inland of the position at the turn of the last century. The freshwater/saltwater interface in the shallow aquifer is slower to respond. The response or movement of th e interface depends on the intensity and duration of freshwater flow stoppage to th e lower Everglades during the dry season.

Over a long-term period, rising sea level is expected to result in high tides overtopping coastal marl ridges an d saline waters penetra ting more deeply thr ough tidal channels and mangrove forests, shifting inland the areas of fresh and lowe r salinity waters.MAP, Part 2 – Draft Final December 2006 108 Coastal Salinity Gradients Conceptual Ecological Model

Sea Level/
Freshwater Flow
Interaction

Prolonged Pooling of Fresh Water Along Estuarine/Freshwater
Interface of Southern Everglades

Shallow Aquifer Freshwater/Saltwater
Interface Surface Water Salinity Gradients

•Location
•Width •Seasonality •Oligohaline Zone

Figure 9-2-5 : Coastal Salinity Gradients Conceptual Ecological Model

Hypothesis 4 Sea Level, Freshwater Flow and Phosphorus inputs as De terminants of Above and Belowground Production, Organic Soil Accreti on, and Resilience of Coastal Mangrove
ForestsMAP, Part 2 – Draft Final December 2006 109 Production and organic soil accretion in the ma ngrove forests of the coastal Everglades are controlled by phosphorus availability, with relatively high inputs from marine sources and low inputs from freshwater sources. P hosphorus availabilit y, mangrove production, and soil elevation are thus driven by the oppo sing influences of s ea level and sheet flow from the Everglades.

Resilience of the mangrove forests of the coastal Everglades after disturbance is dependent on hydrologic flushing by either fres h or saline water, which is driven by sea level and sheet flow from the Everglades. Resilience also varies with soil fertility.

Rationale: Aboveground biomass and production in the mangrove forests of Shark River Slough and other Gulf estuaries increase from the ecotone toward the Gulf of Mexico, reflecting the direct connection of these syst ems to the marine phos phorus source. Trees
in the forests near the Gulf are able to allocate more biomass to aboveground growth. The dwarf mangrove forests along the northern margin of Fl orida Bay reflect suppressed levels of aboveground productivity, as influe nced by minimal P supply from either the oligotrophic marshes of the southern Ever glades or Florida Bay. High belowground production rates in the dwarf mangrove fore sts appear to be a biomass allocation phenomenon in which mangroves in the oligot rophic southern Everglades are foraging for nutrients. The counter-intuitive expectat ion is that maintenance of oligotrophic
conditions in the southern Ev erglades [by increased freshw ater inflows] may promote peat accretion in these mangroves.

Increased freshwater sheet flow caused by impl ementation of CERP projects is expected
to maintain low nutrient conditions in the so uthern Everglades mangr ove estuaries and in the oligohaline ecotone forest s of the western mangrove estu aries. These low nutrient conditions are expected to enhance belo wground productivity by mangroves, which will maintain peat production and so il elevation increases—ultimately enhancing the ability of these low salinity forests to maintain themselves against sea level rise.

An important feature for maintenance of an existing wetland environment, its recovery following disturbance events such as hurricanes, freezes, fires, or salinity changes, or the successful shift from one wetland type to another is maintenance of good flushing by
either fresh or saline waters. This leads to an inland expansion of the white zone, or the mangrove-freshwater interface. Contraction an d expansion of this “white zone” are regulated by freshwater flow dynamics and sea level rise. This phenomenon has implications for the long-term maintenan ce of mangrove communities and for mangrove communities trying to move into former sawg rass wetlands. Improved freshwater flow and flushing through the lower Everglades and coastal wetlands (through both channel and sheet flow) are expected to aid in rec overy of wetlands from catastrophic setbacks (from hurricanes, fire, freeze and salinity changes).MAP, Part 2 – Draft Final December 2006 110 Mangrove Forest Production, Organic Soil Accumulation, and Resilience Conceptual Ecological Model

Minimal P Source From

Florida Bay Low Nutrient Conditions in

Southern Everglades Marine P Source From Gulf of
Mexico Hydrologic Flushing Sea Level/
Freshwater Flow
Interaction Disturbance
Events

•Hurricanes
•Fires
•Freezes

High Belowground
Production Rates In Florida Bay Dwarf Mangroves Productivity Gradient Toward GOM In Gulf Mangrove Forests

Peat Production & Soil Elevation Increase Maintenance of Collapse of Coastal Wetland Communities White
Zone

Figure 9-2-6 : Mangrove Forest Production, Organi c Soil Accumulation, and Resilience Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 111 9.2.5 Wetland Landscape and Plant Community Dynamics

Hypothesis 1 Everglades Ridge and Slough Mi cro-topography in Relation to Organic Soil Accretion
and Loss

Sheet flow interacts with hydroperiod, wate r depth, fire, and nutrient dynamics to maintain organic soil accretion and lo ss in a state of dynamic equilibrium.

Rationale: The dynamic equilibrium involves a ba lance of particulate organic matter transport, and the accumulation, oxidation, and combustion of organic soil. Altered magnitude, duration, and direction of sheet flow causes disequilibrium of accretion and loss processes. The disequilibrium is exa cerbated by eutrophicati on. Disequilibrium of accretion and loss processes causes degradatio n in the ridge, slough, and tree island micro-topography toward a flattening of the landscape.

Restoration of sheet flow in combination wi th related hydrology, wa ter quality, and fire patterns will re-establish the feedback condi tions that sustain the micro-topography of ridges, sloughs, and tree islands.

Hypothesis 2 Everglades Ridge and Slough Landscape Patt ern in Relation to Micro-topography

Degradation of micro-topography, changes in hydroperiod, water depth, eutrophication, fire, and vegetation, especially nonnative and invasive species, can reduce the diversity and stability of habitats which were previ ously long-term, large-sc ale features of the ridge and slough landscape.

Rationale: Decline in ridge and slough habitat di versity and stability includes expansion of sawgrass into sloughs and wet prairies , tree island drowni ng, tree island burn-out,
conversion to cattail under eu trophic conditions, and takeover by exotic species, such as, Melaleuca quinquenervia and Lygodium microphyllum

.

Resumption of sheet flow and related pattern s of hydroperiod, water depth, water quality, and fire will significantly restore and sustain the micr otopography, directionality, and spatial extent of ridges and sl oughs and improve the he alth of tree islands in the ridge and slough landscape.MAP, Part 2 – Draft Final December 2006 112 Ridge & Slough Landscape Dynamics Conceptual Ecological Model

Sheet Flow Eutrophication & Nutrient Dynamics Exotic Plants

Hydroperiod & Water Depth
Patterns Cattail Expansion

Particulate Organic Matter Transport Fire Frequency & Intensity

Disequilibrium of Accretion & Loss Processes

•Slough sediment accretion •Organic soil oxidation
•Peat fires

Degradation of Ridge, Slough, &

Tree Island Microtopography

Decline in Habitat Diversity & Stability

•Sawgrass expansion •Tre island drowning
•Tree island Burnout •Cattail Conversion

• Melaleuca & Lygodium

Figure 9-2-7 : Ridge and Slough Landscape Dynamics Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 113 Hypothesis 3 Plant Community Dynamics along Elevation Gradients

The composition and distribution of plant communities along elevation gradients are determined by patterns of hydroperiod, water de pth, nutrient dynamics, and fire patterns throughout freshwater wetlands of the Greater Everglades.

Rationale: The dynamic equilibrium of the vegeta tion mosaic in relation to elevation gradients is maintained if biogeochemical pr ocesses in the soil s upport the physiological requirements of the vegetation. The dynamic equilibrium is altered if water depths or hydroperiods decrease or increase. Anthropogenic disturbances (i.e. past 100+ years) of hydroperiods, water depths, eutrophication, fire patterns, land use change, and the spread of exotic plants and animals have shifted th e vegetation mosaic away from the historic dynamic equilibrium. These hypotheses are de signed to focus monitoring and modeling
at the ecotone boundaries between vegetation types which may be an early location of change.

In most of the greater Everglades wetland s where hydroperiods and water depths have decreased, the hydrologic tolerances of the surviving plant communities are adapted to greater hydroperiods and water depths than ar e currently maintaine d. For example, with regional drainage and altered fire regimes in the Big Cypress region there has been a gradual shift in landscape patterns, resulting in an increase in mesic rather than hydricdominated communities.

Vegetation gradients between higher elevation marl prairies and lower elevation ridge and slough communities are of particular concer n in the southern Everglades. Although a potential trade-off exists between ridge and slough habitat restorati on and the extent and quality of habitat in adjacent marl prairies . It is thought that longer hydroperiods, greater water depths, and appropriate flow regimes w ill re-establish and sustain ridge and slough landscape patterns without significantly infringi ng on adjacent marl prairies, where shorthydroperiod, tussock growth habitats will persist.MAP, Part 2 – Draft Final December 2006 114 Plant Communities/Elevation Gradients Conceptual Ecological Model

Sheet Flow Exotic
Plants Eutrophication & Nutrient Dynamics

Hydroperiod & Water Depth
Patterns

Fire
Patterns

Biogeochemical Processes In Soils

Physiological Requirements Of Plant Communities

Dynamic Equilibrium of Plant Communities Along Elevation Gradients

•Ridge & slough landscape dynamics •Ridge & slough/marl prairie trade-off •Eastern Big Cypress hydric-to-mesic dominated communities

Figure 9-2-8 : Plant Communities/Elevation Gradie nts Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 115 9.2.6 Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base

The collapse of wading bird ne sting colonies in the southern Everglades is attributed to declines in population densitie s and seasonal concen trations of marsh fishes and other aquatic prey organisms.

Restoration of natural hydrologic conditions will re-establish dist ributions of prey densities and concentrations across the landscap e that in turn will support the return of large, successful wading bird nesting co lonies to the southern Everglades.

Hypothesis 1 Aquatic Fauna Wet Season Prey Population

The wet-season density, size structure, and re lative abundance of ma rsh fishes and other aquatic wading bird prey are directly related to the time since the last dry-down and the length of time the marsh was dry. Aquatic prey populations are further affected by salinity in coastal ecotones a nd by site nutrient status. Responses are non-linear and species specific.

Rationale: Persistent pools of fresh water, with multi-year hydroperiods and gradual water recession rates, occurr ed in ridge and slough lands capes and adjacent coastal ecotones of the southern Evergl ades under pre-drainage condi tions. Expansive, naturally occurring pools in the southern Everglad es have been replaced by artificial impoundments in the lower ends of Water Co nservation Areas. As a result, population densities of aquatic fauna are low in much of the southern Everglades, while densities
have increased in the artifi cial pools of the Water Conser vation Areas, which now favor larger, longer-lived species.

Resumption of natural volume, timing, and dist ribution of freshwater flow will restore historical hydroperiods and sa linity distributions to the southern Everglades. These changes are expected to increase wet-season density and size stru cture of wading bird prey in the southern Everglades within a four to seven year timeframe.MAP, Part 2 – Draft Final December 2006 116 Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base Conceptual Ecological Model

Crayfish Population Dynamics Dry Season Aquatic Refugia

Aquatic Fauna Wet Season Prey Popultions

Extreme Peaks In Prey
Abundance Dry Season Prey Concentrations

Wading Bird Foraging Distribution
& Abundance

Wading Bird Nesting Colony Location, Size, & Timing

Wading Bird Super Colony

Formation Wading Bird Nesting Success Hydroperiod & Site
Nutrient

State

Multi-year Wet & Dry

Cycles Drought Severity

Dry Season
Water Level

Recession

Patterns Prey Populations

Sub-lethal
Effects of Toxins On Wading Bird Reproduction

Wading Birds

Figure 9-2-9 : Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 117 Hypothesis 2 Aquatic Fauna Dry Season Prey Concentration

The concentration of marsh fishes and other wading bird prey into high-density patches where wading birds can feed effectively is controlled by the rate of dry-season waterlevel recession and local topogr aphy/habitat heterogeneity.

Rationale: Erratic water-level fluctuation in th e remaining managed system, particularly in the Water Conservation Areas, comm only cause drying pattern interruptions, ultimately leading to ill-timed, fewer or less dense concentrations of aquatic fauna that serve as wading bird prey.

Drying edges extended along elevation gradient s from upland pine flatwoods, and moved across marl prairies, to the lower-elevation ridge and slough and coastal landscapes as dry seasons progressed under pre-dr ainage conditions in the southern Everglades. The drying edges concentrated aquatic prey organisms a nd made them availabl e to wading birds. Urban and agricultural development of the higher elevation eastern fringes of the southern Everglades, in comb ination with drying of marl prairies earlier in the dry season, have truncated in time and space the dr ying marsh edge and the concentration of aquatic prey organisms. During very wet year s, the edge no longer occurs or occurs only briefly at the end of the dry season. In years with more typical rainfall, the edge may occur throughout the dry season, bu t it passes through the marl prairies very early and is well into the center of Shark Slough by the time it is needed to fuel wading bird nesting.

Resumption of natural volume, timing, and di stribution of freshw ater flow to the Everglades is expected to re store historical patterns of water level recession and drying edges, which will concentrate wading bird pr ey into a succession of high-density patches throughout the dry season in the remaining ri dge and slough, marl prairie, and coastal landscapes.

Hypothesis 3 Wading Bird Nesting Colony Location, Size, and Timing

The collapse of wading bird nesting colonies in the tributary headwaters and southern mainland of the Everglades, the abandonment of Roseate Spoonbill nesting colonies in islands of northeast Florida Bay, and delay in the annual initiation of Wood Stork nesting have been caused by:

• decreased population densities of marsh fishes and othe r aquatic prey organisms in the southern Everglades, as described under Hypothesis 1

• a shift in the location and timing of seasonal concentrations of marsh fishes and other aquatic prey organisms, as described under Hypothesis 2

• reduced shallow-water foraging options for wading birds along elevation gradients

Rationale: Increased prey densities in artificial pools of the Water Conservations Areas have attracted wading bird nesti ng colonies to those areas afte r the collapse of the coastalMAP, Part 2 – Draft Final December 2006 118 colonies. However, dr ying pattern interruptions in the Water Conservation Areas often disrupt prey concentrations that are required for successful foraging by the wading birds, resulting in failure of nesting colonies.

Restoration of historic spatio -temporal patterns of prey production and concentration is expected to reestablish wading bird nesting colonies in the coastal and tributary regions of the southern Everglades and Roseate S poonbill nesting colonies in northeast Florida Bay. This restoration is also expected to increase numbers and success of nesting wading birds, Wood Storks, and Roseate Spoonbills a nd to cause Wood Storks to initiate nesting no later than January in most years.

Hypothesis 4 Wading Bird Super Colony Formation

Unusually large aggregations of nesting wading birds (super colonies) consisting of mostly White Ibis formed in the pre-draina ge system in response to the effects of extreme, natural patterns of dr ought prior to colony formation.

Rationale: Super colonies periodic ally formed along the freshwater-estuarine transition zone (sawgrass-mangrove ecotone) at the lo wer reaches of the Everglades and Big Cypress basins. A substantial reduction in freq uency of super colonies is attributed to disrupted multi-year wet and dry cycles, due to altered volume, tim ing, and distribution of flow in the managed system. Reduction in the size of super colonies may be related to reductions in wading bird prey populations due to reduced hydrope riods and disrupted water level recession patterns as described under Hypotheses 1 and 2.

Periods of extreme drought in natural multi-year wet and dry cycles appear to cue the occurrence of large pulses of secondary productivity that support the large nesting colonies which form after such droughts. The mechanisms by which these pulses are organized are poorly understood, but the effects of droughts on crayfish, predatory fishes, or nutrient dynamics may be involved. Population dynamics of crayfish ( Procambarus
alleni and P. falax ) may play an important role, since the super colonies form when marsh fish populations would be expected to be minimal, and because White Ibis feed primarily on crayfish.

Resumption of natural pa tterns of volume, timing, and distri bution of flow to the southern Everglades, in combination with interannual variation in rainfall, will restore natural multi-year wet and dry cycles as they would ha ve occurred prior to drainage the southern Everglades. This is expected to stimulate pu lses of secondary produc tivity that will likely involve Everglades crayfish populations. The pulses in seconda ry production are expected to result in an increase in the retu rn frequency and size of ibis-dominated super colonies in the tributary headwaters of the Shark River and other Gulf of Mexico mangrove estuaries at a frequency of two or more events per decade.

Hypothesis 5 Linkage of Periphyton to Higher Trophic LevelsMAP, Part 2 – Draft Final December 2006 119 The floating mat comprised of the periphyton complex and various bl adderworts provides critical support of the o ligohaline Everglades food web, both as a food source and a refuge for aquatic invertebra tes that are consumed by sma ll fish, crayfish, and grass shrimp.

Rationale: The floating mat provides both food (algae and detritus) and habitat structure (hiding places) for macroinvertebrates, in cluding midge larvae, nematodes, amphipods, and juvenile snails. The floating mat complex harbors much higher density of macroinvertebrates than epiphyton and benthic substrates; the daytime water column of oligotrophic Everglades wetlands is remarkably devoid of plankton, and relatively low densities of invertebrates emerge into the wa ter column at night, compared to other North American ecosystems. These small inverteb rates serve as a cri tical food source for Everglades consumers, including small fis h, crayfish, and grass shrimp. Lengthened hydroperiods expand the aerial coverage of ha bitats where these food-rich mats are abundant. Shortened hydroperiod reduces the area of extensive floating mats and decreases the length of the season when habita t is available for aquatic organisms. These losses decrease standing crops available fo r consumption by higher trophic levels.

Higher nutrient levels stimulate inverteb rate productivity, but change community composition to favor pollution-tolerant ta xa. Short-lived low-level phosphorus enrichment leads to higher periphyton TP, which stimulates increased biomass and density of floating mat macroinvertebrate infauna. Macroinvertebrate community composition (relative abundance) changes with low-level nutri ent enrichment, well below amounts favoring loss of the periphyton mat. The relative abundance of oligochaetes increases with enrichment, while amphipods and chironomids decline. However,
sustained TP enrichment leads to dissolution of the floating mat, and loss of that habitat.

This hypothesis links the Everglades floati ng mat, and particularly periphyton primary productivity and detrital production, to hi gher trophic levels, which are the focus of management action.MAP, Part 2 – Draft Final December 2006 120 Linkage of Periphyton to Higher Trophic Levels Conceptual Ecological Model

Site Nutrient State Hydroperiod & Water Depth
Patterns

Floating Periphyton/Bladderwort Mat Aerial Coverage, Composition, & Structure

Habitat Structure Edible Algae
& Detritus
Food Resources

Macroinvertebrate
Infauna
Food Resources

Wet Season Populations Of Small Fish, Crayfish, & Grass Shrimp Wet Season Large Fish Populations

Predator-Prey Interactions of Wading Birds & Aquatic Fauna Forage Base Everglades Crocodilian Populations

Figure 9-2-9 : Linkage of Periphyton to Higher Troph ic Levels Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 121 9.2.7 Everglades Crocodilian Populations

Hypothesis 1 American alligator populations in relation to hydroperiod, water table, water depth, and salinity in the Everglades.

American alligator distribution, abundan ce, reproduction, and body condition in the Everglades are controlled by hydr operiod and water table in th e Rocky Glades, salinity in the mangrove estuaries, and wa ter depth patterns in the ridg e and slough system, all of which were driven by direct rainfall and sheet flow prior to drainage.

Compartmentalization, disrupte d sheet flow, and regulatory water releases restrict alligator populations in th e ridge and slough landscape by causing nest flooding, unsuitable over-drained and pooled habitats in the Water Conservation Areas, and low hatchling and juvenile survival in canals during low water periods.

Rationale: Shortened hydroperiod and lowered wate r table in the rocky glades have reduced alligator abundance and reproduction b ecause of loss of aquatic habitat required for survival and reduced aquatic prey ba se. A positive feedback loop of increased alligator populations and alli gator holes (aquatic refugia) leading to increased aquatic fauna density (alligator prey) has been disrupt ed. That feedback loop is assumed to have been functional under pre-drainage conditions in the rocky glades where alligators were formerly abundant, although it is clearly not functional in the drained marshes today.

Reduced freshwater flow into the mangrove estuaries of the southern Everglades has
resulted in succession of former freshwat er mangrove areas to saltwater systems, reducing American alligator populations in tidal rivers and tributaries.

American alligator populations remain viab le throughout most of the ridge and slough system. However, increased water depths durin g nesting seasons particularly near canals,
the southern ends of each Water Conservati on Area (1, 2, and 3), and Shark River Slough have led to high levels of nest flooding in some years. Alligator body condition is poor throughout the system during prolonged period s of increased wate r depth. Alligator density at the northern ends of the WCA’s is low due to overdrained conditions leading to poor rates of survival and growth. Finally, a large portion of the adult population exists in canals but does not contribute to population growth due to the combination of increased nest flooding and decreased hatchlin g and juvenile survival during low water periods (predation and cannibalism).

With the resumption of natural patterns of volume, timing, and distribution of flow to the Everglades, the American alligator is expect ed to repopulate and resume nesting in the rocky glades and the freshwater reaches of tid al rivers in the mangrove estuaries and will increase in population size and body condition throughout most of the Greater Everglades
wetlands.MAP, Part 2 – Draft Final December 2006 122 Everglades Crocodilian Populations Conceptual Ecological Model

Alligator Body Condition Aquatic Fauna

Prey Base Alligator
Hole
Abundance &

Distribution Alligator

Nest
Abundance &

Distribution Alligator
Abundance &

Distribution Hatching Success Hatchling
& Juvenile

Survival Estuarine
Freshwater

Flow & Salinity

Hydroperiod Influence Of Canal
Habitat

Water Depth
Patterns Juvenile Growth & Survival

Crocodile Relative Density

American Alligator American Crocodile

Figure 9-2-11 : Everglades Crocodilian Populations Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 123 Hypothesis 2 American Crocodile Relative Density and Juvenile Growth, Survival, and Condition in Relation to Salinity in Ever glades Mangrove Estuaries

American crocodile relative density and j uvenile crocodile growth, survival, and condition increase when salinity fluctuates below 20 ppt in shor eline, pond, and creek habitats in Everglades mangrove estuaries.

Rationale: Availability of freshwater limits th e distribution and abunda nce of reptiles in estuaries. In estuaries, crocodilians of all species orient towards areas of low salinity and
sources of freshwater. The American crocod ile is a flagship endangered species that charismatically represents this relationshi p. In northeastern Florida Bay, diversion of freshwater flow, crocodiles have poorer growth rates and higher mortality than elsewhere
in Florida.

Restoration of location of freshw ater flow will result in an increase in relative density of crocodiles in areas of restored flow, such as Taylor Slough/Tayl or River drainage. Reestablishing the salinity gradient in the es tuary will increase growth and survival of juvenile crocodiles throughout the estuary.

9.3 Southern Estuaries Module

9.3.1 Module Location Description and Background Information

The Southern Estuaries influenced by the Co mprehensive Everglades Restoration Plan (CERP) include Florida Bay, the coastal lake s inland from Florida Bay, Biscayne Bay,
and estuaries within southwest Florida’s mangrove zone from Whitewater Bay to Lostman’s River (Figure 1). Altered freshwat er inflows have affected circulation and salinity patterns of the Southern Estuaries, in turn altering the st ructure and function of these ecosystems. Changes in habitat structur e and distribution have been of particular concern because of their effects on animal populations.MAP, Part 2 – Draft Final December 2006 127 9.3.3 Water Quality Conceptual Ecological Model

Water quality in South Florida estuaries is dependent upon the volume, distribution, and quality of freshwater flowing to the system. The biotic components (e.g., phytoplankton, benthic habitats) of estuaries are sensitive to nutrient loading which may be modified by CERP. Complex interactive mechanisms be tween water quality and hydrologic drivers as well as internal nutrient cycli ng will influence CERP effects.

Figure 9-3-1 : Water Quality Conceptual Ecological Model

9.3.4 Water Quality Hypotheses

• Through modifications of quantity, quality, timing and distribution of freshwater, CERP implementation will affect dissolved and particulate nutrie nts delivered to the estuaries and alter estuarine water quality. These modifications will affect primary production and food webs in estuaries. These modifications include:

1) changes in the distribution and timing of nutrient input s through increased flow via Shark River Slough and diversion of canal flows from ‘point source’ to more ‘diffuse’ delivery through coastal wetlands and creeks; CERP Im plem entation and
other water m anagem ent and land use changes Episodic events Open Keys’ passes

Restored
freshwater flow (quantity, tim ing, distribution, quality)

Altered nutrient input (concentration and load)

Groundwater inputs Restored
estuarine salinity

Internal
nutrient cycling and bioavailability Restored SAV

com m

unity Light availability changed benthic grazing changed

Sedim ent stability, resuspension, and export changed Phytoplankton
bloom response Estuarine
residence
tim

e / flushingMAP, Part 2 – Draft Final December 2006 128 2) changes in the quantity of nutrient inputs to the estuaries th rough alteration of the mobilization and release of nutrients from developed and agricultural areas, through nutrient uptake in treatment area s, and through ch anges in nutrient processing and retention in the Everglades;

3) changes in the bioavailability of nutrients which depend on both the quality of nutrients (e.g., inorganic nutrients and DOM) from the watershed and internal estuary mechanisms (e.g., P limitation of DOM decomposition);

• Internal nutrient cy cling rates (e.g., nitrogen fixation and denitrification) and biogeochemical processes, such as phos phate sorption, will change with CERP implementation because of salinity and benthic habitat changes.

• Nutrient accumulation and retention in estu aries is affected by episodic storm events, which can export nutrient rich sediments. CERP implementation will modify benthic habitats and nutrient loading whic h will affect this export.

• The spatial extent, duration, density, and composition of phytoplankton blooms are controlled by several factors that will be influenced by CERP. These include:

1) external nutrient loading;

2) internal nutrient cycling (seagrass productivity/die-off, sediment resuspension);

3) light availability (e.g., modified by sediment resuspension and CDOM);

4) water residence time; and

5) biomass of grazers (e.g., zoopla nkton, benthic filter-feeders).

• Nutrients inputs from groundwat er discharges may affect water quality in coastal wetlands and estuaries. CERP implementa tion will modify these discharges in the
coastal zone which will alter nut rient loads to the estuaries.

9.3.5 Benthic Submerged Aquatic Vegetati on Conceptual Ecological Model

Seagrasses, along with attached and drifting macro algae and Chara (in the coastal lakes inland from Florida Bay), comprise most of the benthic submerged aquatic vegetation (SAV) within the Southern Estuaries region. Seagrasses are the dominant biological community in South Florida coastal waters (Fourqurean et al. 2002), including Florida Bay (Zieman et al. 1989, Fourqurean and Robblee 1999, Durako et al. 2002) and Biscayne Bay. Seagrasses form a highly prod uctive ecosystem that is the basis of the food web and provides habitat for most r ecreationally- and commercially-important fisheries species in the SEM region (Zieman 1982, Thayer et al. 1999). Seagrasses also
have a m ajor effect on water quality and clar ity through nutrient uptake and storage and by increasing sedimentation and sediment stab ilization via their physic al structure (Prager and Halley 1999).MAP, Part 2 – Draft Final December 2006 129 The catastrophic die-off of seagrasses, primarily Thalassia testudinum , in the late 1980’s was accompanied by a cascade of ecological changes, including widspread and persistent phytoplankton blooms, increased turbidity, and dramatic faunal changes (Butler et al. 1995, Philips and Badylak 1996, Matheson et al. 1999, Prager and Halley 1999). The cause of the widespread die-off is not known, but is thought to have been related to changes in salinity, nutrient av ailability, sulfide t oxicity, and disease (Robblee et al 1991, Carlson et al 1994, Durako and Kuss 1994, R udnick et al 1999). Recent evidence suggests that one mechanism of Thalassia short-shoot mortality is the result of internal oxygen stress and sulfide toxicity (Borum et al. 2004), but how these are related to growth conditions or if this is the proximal cause of the initial die-off are still unknown.

Because of their benthic habit and persistenc e, seagrasses and macro-algae integrate and respond to changes in water quality. Thus, benthic SAV distribu tion and abundance are valuable ecological indicators of the “health” of the SEM region. In Florida Bay, the state of the seagrass communities is being used as a success criterion for CERP implementation. By altering the volume, timing, and spatial distribu tion of freshwater inflow, one goal of CERP is to restore and maintain the estuarine character of Florida Bay and in turn to produce a more diverse and sustainable seagrass community.

Figure 9-3-2 : SAV Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 130 9.3.6 Benthic Submerged Aquatic Vegetation Hypotheses

• Changes in both salinity and water quality resulting from CERP implementation are expected to result in ch anges in seagrass cover, biomass, distribution, species composition and diversity t hough the combined and inte rrelated effects of light penetration, epiphyte load, nutrient av ailability, salinity, hypoxia/anoxia, sulfide toxicity, and disease.

• Changes related to CERP implementation wi ll include an expans ion of areas with
Halodule and Ruppia cover and a reduction in areas of Thalassia monoculture along the northern third of Florida Bay. Based on forecasted changes in hydrology, seagrass density and species composition in the southern two thirds of Florida Bay are not expected to change.

• Changes in both salinity and water quality resulting from CERP implementation are expected to change benthic algae cover, biomass, distribution, species composition and diversity though the combined and interr elated effects of light penetration, nutrient availability, salinity, temperatur e, and changes in seagrass density and species composition .

• Significant changes in benthi c algae and seagrass distribu tion and density can affect susceptibility to sediment resuspension and the stability of mudbanks as well as nutrient availability to other primary producers.

9.3.7 Nearshore Nursery Function Conceptual Ecological Model

Estuaries provide critical nursery habitat for many species of fish and macroinvertebrates, many of which are spawned offshore. So me, such as pink shrimp, are harvested primarily in offshore fisheries, although inshore live bait fisheries ta rget juveniles in Biscayne Bay. Shoreline and bottom configur ation, vegetation, and salinity patterns are characteristics that define nursery habi tat and determine their productive capacity, thereby the abundance of favored species. The fundamental assumption of CERP is that
the alteration of volum e, timing, and spatial distributio n of freshwater inflow that occurred with past water management practi ces has decreased the productive capacity of estuarine nursery grounds by altering both bo ttom and shoreline vegetation and salinity patterns and the area over which favorable zones of bottom vege tation and salinity overlap. One purpose of CERP is to expand, in both space and time, favorable conditions for the estuarine species that were historica lly characteristic of the coastal wetland and nearshore zone. This includes oysters, re d drum, pink shrimp, spotted seatrout, and species of snappers and grunts that use this habitat at various life stages. Increased availability of complex mangrove-shoreline and seagrass habitat (including a wider representation of seagrass species, e.g., Ruppia and Halodule , as well as Thalassia ) and a broadened salinity gradient will increase the diversity of fish and macroinvertebrates that will be accommodated. Complex habitats increase productive capacity by reducing predation, providing a w ider variety and a bundance of food organisms, reducing physical disturbance, and providing substrates for at tachment. The formulation and monitoring ofMAP, Part 2 – Draft Final December 2006 131 performance measures that adequately reflec t nursery function are essential elements of the CERP monitoring program.

Figure 9-3-3 : Nearshore Nursery Function Conceptual Ecological ModelMAP, Part 2 – Draft Final December 2006 132 9.3.8 Nearshore Nursery Function Hypotheses

Hypothesis 1 The implementation of CERP will affect the life cycle and abundance of fishery species not only through habitat dependencies (e.g., rega rding food availability and shelter) but also through the direct phys iological effects of salinity upon growth and survival.

Rationale : Species abundance and recruitment to adult populations is a function of the area of overlap of favorable habitat and favorab le salinities for each species. Maintaining a discernable spatial salinity gradient with persistent salinities in the lower range will result in an expansion of the area of optimal nursery habitat for estuarine dependent species and this, in turn, will increase th e overall abundance (density x area) of
invertebrate and verteb rate species, includ ing pink shrimp, pinfis h, rainwater killifish, mojarras, gray snapper, and spotted seatrout.

Hypothesis 2 Responses to change in both biotic (vegeta tion structure and cover) and abiotic (salinity pattern) aspects of habitat may vary.

Rationale : Responses may vary by life stag e because habitat use and salinity requirements often differ depending on life stage. Responses vary by species both because of different salinity tolerances and be cause of life-history di fferences that affect requirements and when required conditions are needed. Responses may be stepwise for some species/stages versus continuous for ot hers because of physiological or behavioral
influences.

Hypothesis 3 There is a direct quantitative relationship be tween the abundance of small juvenile pink shrimp in Biscayne Bay and Florida Bay and ca tch per unit effort of larger juveniles and adult pink shrimp in fisheries.

Rationale : Small juvenile pink shrimp beco me recruits to the fisheries.

Hypothesis 4 The annual production of small prey fish in nearshore shallow water habitat, as determined by salinity patterns and other factor s affected by freshwater inflow, will be reflected in annual production rates of their consumers in the mangrove prop-root habitat of coastal creeks and shorelines (e.g., gray snapper and other species).

Rationale : The fish that shelter in mangrove prop-root habitat of coastal creeks and shorelines are thought to forage in grassb eds; therefore the a bundance of small prey species in nearshore flats may be reflected in the growth rates of the consumers.MAP, Part 2 – Draft Final December 2006 133 Hypothesis 5
Redistribution of flow from canals to coastal creeks and a reliable supply of fresh water to the creeks during the dry season will increase the epifaunal abundance and substrate coverage (percent available). Species composition will include oysters and their
associates.

Rationale : A change in the spatial and temporal distribution of freshw ater inflow will result in changes in the abundance, subs trate coverage, and species composition of epifauna on mangrove prop-roots.

9.3.9 Nearshore Community Structu re Conceptual Ecological Model

Many of South Florida’s estuarine habitats ha ve been diminished or eliminated by past and current water management practices. Waters that are consistently of intermediate salinity (e.g., 5-20 psu) tend to support highl y productive, but relatively low diversity, plant and animal communities. In many near shore areas of Bisca yne and Florida Bays,
freshwater flow is so variable that dow nstream salinity regimes are suboptimal for freshwater, brackish and marine organisms a like. Among the objectives of the CERP is
to restore the function of the coastal creek s that once supplied diffuse, but consistent, freshwater flow to southern Biscayne Bay. The restoration of a more natural freshwater delivery regime and associated salinity pa tterns would be accomplished by diverting a portion of the surface flow carried to the bay area by canals. An understanding the interaction of salinity pattern and habitat with the sp ecies composition, diversity and abundance of the nearshore fish, invertebrate and seagrasss commun ities is critically needed to develop appropriate performance measures.MAP, Part 2 – Draft Final December 2006 134 Figure 9-3-4 : Nearshore Community Structure Conceptual Ecological Model

9.3.10 Nearshore Community Structure Hypotheses

Hypothesis 1
Shoreline and nearshore benthic communities are directly impacted by (and to some degree reflect) the volume, timing and variatio n in freshwater inflow, salinity patterns, and the range and rapidity of salinity fluctuation.

Rationale : Even estuarine species are more abundant somewhere within the full salinity range found in south Florida estuaries (i.e., 0-70 psu), rather than across the entire range. Few estuarine species can tolerate rapid high amplitude fluctuations in salinity. Taxonomic Composition/Richness/

Diversity/Evenness Fish & Invertebrate Community
Extent & Biomass Manatee Canal
Utilization

Time Time Time Habitat Overlap (e.g., mesohaline seagrass) Structural
Habitat (e.g., seagrass) Dynamic
Habitat (i.e., salinity

regime)

Taxonomic Composition/Richness/

Diversity/Evenness Fish & Invertebrate Community
Extent & Biomass Manatee Canal
Utilization

Time Time Time Taxonomic Composition/Richness/

Diversity/Evenness Fish & Invertebrate Community
Extent & Biomass Manatee Canal
Utilization

Time Time Time Habitat Overlap (e.g., mesohaline seagrass) Structural
Habitat (e.g., seagrass) Dynamic
Habitat (i.e., salinity

regime)MAP, Part 2 – Draft Final December 2006 135 Hypothesis 2 Reestablishing a persistent nearshore positiv e salinity gradient will increase the optimal
habitat and abundance of estuarine fishes, oysters and other species.

Rationale : Estuarine species presently are limited by the lack of a persistent positive salinity gradient in both Bi scayne Bay and Florida Bay.

Hypothesis 3 CERP implementation will lead to an expa nded community of estuarine species and new estuarine habitat will be created (e.g., oyster beds).

Rationale : Plant and animal diversity will increase as more natural freshwater flows, and salinity regimes, are restored.

Hypothesis 4 Oyster populations will increase when fresh wa ter destined for estuar ies is routed through new/restored coastal marshes, which will reduce sediment loads and areas with soft,
unconsolidated substrate.

Rationale : High sediment loads and benthic “m uck” accumulation can deleteriously affect oyster recruitment, growth and surv ival. Reducing the lo ads will improve oyster spat recruitment a nd oyster growth.

Hypothesis 5 Changes in timing, location and volume of freshwater inflow will affect manatee distribution and manatee use of canal habitat, which will in turn affect their susceptibility to mortality from motorboats and water control gates.

Rationale : Manatees are attracted to freshwater sources. Pr esently the sources are the canals. When freshwater creeks provide a more continuous source of fresh water, the
manatees will orient toward the cree k mouths and away from the canals.

9.3.11 Toxins and Contaminants

Because contaminants are conveyed to th e estuaries through surface and ground-water flux, changes in distribution or sources of fr eshwater or ground-water stages may affect the fate, amount, and pattern of toxicants and other contaminants introduced to bay waters sediments and biological resources which will in turn affect estuarine organisms, populations, and communities as follows: Accu mulated toxicants and other contaminants will eventually cause stress in organism s. Stress would initially be expressed biochemically as changes in osmoregula tion, clinical hematology, immunology, and histopathology, etc. Biochemical and physiologi cal changes could lead to adverse effects on survival, growth, development and reprodu ction. The level of stress created by divalent metals would depend upon their bioavailability, a function of partition coefficients and factors influencing e quilibrium (e.g., redox potential); OrganismalMAP, Part 2 – Draft Final December 2006 136 affects can affect populations and population changes in turn can result in community
shifts.

9.3.12 Status of Toxins/Contaminants MAP Monitoring

Revised MAP Monitoring Components:

Monitoring Components MAP Section STATUS

Sediment Contaminants Proposed; no funding

source. Contaminant Loading Proposed

Existing MAP Key Uncertaint ies and Supporting Research

Monitoring Components MAP Section STATUS
Causal Factors of Fish Abnormalities in Biscayne Bay 3.2.4.8 No funding

Bottlenose Dolphin Health Assessment in Biscayne Bay Mercury Module 3.2.4.9 Funding uncertain and inadequate at present

Revised MAP Key Uncertainties and Supporting Research

Monitoring Components MAP Section STATUS Risk assessment for Biscayne Bay ProposedMAP, Part 2 – Draft Final December 2006 137 Figure: 9-3-5 : Hypothesis Flow Chart for Toxins and Contaminants in the SEMAP, Part 2 – Draft Final December 2006 138 9.3.13 Toxins and Contaminants Hypotheses

• CERP is going to change the quantity, timi ng and distribution of in flow to the
southern estuaries and the s ource of this freshwater is expected to include waste water reuse and both urban and agricu lture runoff, which may increase the
contaminant load to the estuaries.

• Water will be routed th rough areas undergoing rapid urban development and redevelopment which will may also increase contaminant loads

• Contaminant loads to the bays will also be affected by the planned rerouting of water through coastal wetlands. Coastal we tland soils and vege tation may take up and retain organic contaminants and hea vy metals, reducing loads to the bays and
associated contaminant concentrations in surface sediments.

• With the increased input loading sediment concentrations and associated sediment toxicity, as indicated in bi oassays (.e.g., clam bioassays), is expected to change.

• Organic contaminant and heavy metal burdens in the biota will change over time reflecting changes in contaminant load ing and concentrations in surface
sediments.

o Body burdens and biochemicals in sentinel organisms with limited mobility (e.g., mollusks) will reflect sediment chemical concentrations, and biological effects, if occurring, will be indicated by biochemical
markers.

• Increasing body burdens will eventually result in increased stress upon the organisms

• This stress will be reflected in the fo llowing changes in monitored parameters:

o Benthic community composition (i.e., of burrowing, infaunal, epibenthic species) will change in response to changes in sediment contamination.

o Filter feeders (e.g., oysters) and organisms in the water column (e.g., zooplankton, fish, shrimp) will be a ffected (survival, growth, etc.) by resuspension of contaminants from sediment.

o The prevalence of fish with morphological abnormalities will change in response to changes in sediment toxicants and other contaminants.

o The health of the resident bottlenose dolphin population will change in response to exposure, as reflected by changes in body burdens, and body
burdens will reflect sediment concentr ations of heavy metals and organic
contaminants.