U 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 PROJECT 
Table 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 Adaptive 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 Conceptual Models and Performance Measures ... 10-1 

11.0 Greater Everglades CERP-Specific Conceptual 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 Protection 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 Performance Measure Application.................................. 16-1 

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

Appendix A. Models Used with Performance Measures 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 Restudy Performance Measures ........................................................... D-1 

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

ES-1 

Executive Summary 

Performance measures are tools based on a set of indicators used in project planning to 

evaluate the degree to which proposed alternative plans are likely to meet restoration 

objectives and to assess the success of implemented plans in meeting restoration 

objectives. Performance measures and their associated targets are integral components of 

the Comprehensive Everglades Restoration Plan (CERP) Adaptive Management Strategy. 

Most performance measures were developed through conceptual ecological models that 

identified key stressors and attributes of the natural system. Attributes are 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 derived from state and federal 

laws. CERP performance measures must fulfill the following: 

 The performance measure must address indicators that represent attributes or 

stressors of natural or human systems that CERP is expected to affect. 

 Targets must reflect the desired restoration condition, which is the maximum 

level of restoration possible given human inhabitation of South Florida. (The 

concept of desired restoration condition is currently being reexamined.) 

 The performance measure must provide an understanding of system-wide 

responses relative to how CERP implementation 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 Coordination and Verification (RECOVER) technical 

teams to date. Performance measures were developed 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, performance 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 are 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 measures 
Executive 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 Strategy (i.e., monitoring and 

assessment, interim goals and targets) 

• Relationship of performance measures 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 documented separately. A documentation sheet is 

maintained for each measure. 
1.0 Introduction October 17, 2007 

1-1 

1.0 U Introduction 

Restoration Coordination and Verification (RECOVER) has developed performance 

measures for evaluating modeled system-wide performance and assessing actual systemwide performance of CERP in meeting its goals and objectives. Performance measures 

are planning tools used to determine the degree 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 indicators expected to respond to CERP 

implementation. 

This document provides background on how system-wide performance measures are 

developed, revised and reviewed. It also describes performance measure application in 

CERP planning and some of the uncertainty associated with that application. The next 

steps that will be taken regarding performance measures are also discussed. Performance 

measures themselves are documented separately. 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 performance measures is a 

dynamic process that incorporates new scientific understandings and technical 

improvements. As our understanding of the ecosystem and the hypotheses that define 

ecologic relationships grows and new evaluation tools are developed, performance 

measures and this document will be refined, additional performance measures will likely 

be proposed, and some may be dropped. Refinement of performance measures is part of 

CERP’s Adaptive Management Strategy (RECOVER 2006). Therefore, this is a living 

document that will be continually updated as other RECOVER documents 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 Density, 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 Communities 
1.0 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 Basinwide Total Phosphorus Loading and FlowWeighted Mean Concentration in Inflows. 

• Greater Everglades Wetlands Nutrient Total Nitrogen Concentrations in 

Surface Water 

• Total Nitrogen Loads/Flow-Weighted Mean Concentration in Inflows to the 

Greater Everglades Wetlands 

• Total Phosphorus Concentrations in Soil 

• Greater Everglades Tracer of Stormwater 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 Prairie Cape Sable Sparrow Habitat 

• Wetland Landscape Patterns - Ridge and Slough Community Sustainability 

• Wetland Landscape Patterns - Tidal Creek Sustainability 

• Wetland Trophic Relationships–Periphyton 

• Wetland Trophic Relationships - Mangrove Forest Production/Soil Accretion 

• Wetland Trophic Relationships - Regional Populations of Fishes, Crayfish, 

Grass Shrimp and Amphibians 

• Wetland Trophic Relationships - Wading Bird Foraging Patterns on 

Overdrained Wetlands 

• Wetland Trophic Relationships - Wading Bird Nesting Patterns 

• Roseate Spoonbill Nesting Patterns 

• Wetland Trophic Relationships - American 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 Area 
1.0 Introduction October 17, 2007 

1-3 

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

• Prevent Saltwater Intrusion of the Biscayne Aquifer - Meet Minimum Flows 

and Level Criteria for Biscayne Aquifer 

• Prevent Saltwater Intrusion of the Biscayne 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 measures have recently been developed and are 

under review. The indicators used within the measures 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 Verification Program, c/o United States 

Army Corps of Engineers, Jacksonville District, Jacksonville, Florida, and South 

Florida Water Management District, West Palm Beach, FL. April 2006. 

www.evergladesplan.org/pm/recover/recover_docs/am/rec_am_stategy_brochure.

pdf
2.0 Performance Measure as Evaluation and Assessment Tools October 17, 2007 

2-1 

2.0 UPerformance Measures as Evaluation and Assessment Tools 

Performance measures will be used during two components of the adaptive management 

process: evaluation of expected plan performance 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 planning expectations. This requires that indicators used for 

planning be assessed during implementation. Indicators used for evaluations of plans are 

limited by available tools. Many more indicators can and will be monitored and assessed 

as CERP progresses. Additionally, 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 responses difficult. Methods that will reconcile 

the different metrics and targets to enable the comparison must be developed. 

The specific application of performance measures to evaluation (planning) and 

assessment processes is discussed in the following sections. In many cases, we are not yet 

able to apply performance measures 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 are specific. As additional research and 

monitoring are conducted, and ecological models 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 and 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 and objectives. Several simulation methods can 

be used to evaluate the system’s response to a possible alternative. These methods 

include computer simulation, post-processing of computer modeling results, and use of 

regression models. All simulation models are basically mathematical models that attempt 

to integrate and show interactions between multiple environmental and man-made 

components. 

Most, if not all, simulation methods 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 interpreted as predictions of actual conditions 

expected to occur at a given time in the future. We can only approximate how certain 

features of the natural system would have responded to the rainfall conditions present in 

the period of record in combination with a fixed set of land use characteristics 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 are 
2.0 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., rainfall, levee seepage). These models are 

designed to operate at very specific spatial 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 complex interactions occurring between climate 

and hydrologic cycles, trophic webs 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 for different alternatives of specific projects. Project teams 

usually develop or modify smaller scale models to compare alternatives. Currently, the 

Regional Simulation Model (RSM) is being developed. 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 assist 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 report. In the absence of 

adequate models, best available science and best professional judgment are used when 

conducting an evaluation. Assessments 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 individual performance 

measures with respect to individual targets. Instead, it uses a hypothesis-based approach, 

which is more robust, flexible and more consistent with an adaptive management process 

(see Section 3). The hypotheses are expected responses 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 performance 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 change in performance measures from 

reference state both annually and cumulatively over multiple years. 

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

3. Evaluate consistency of monitoring results with MAP hypotheses. 

4. Determine if unanticipated events are indicated. 

5. Describe how these events are affecting desired outcome. 

Physical, chemical and ecological data (i.e., multiple performance measures) are 

integrated and interpreted to assess causal inferences comprising each hypothesis. 

Integration and interpretation of multiple physical and chemical stressor impacts on a 

specific ecological attribute, as described in a CERP hypothesis, 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 characterize 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 relationships 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 information and an evaluation of CERP progress. 

This requires identifying those physical, chemical and ecological attributes 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 assessing 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 lines of evidence needed to evaluate defining 

characteristics or interim goals (see Section 5) are identified. Weighing relative 

importance of lines of evidence will make synthesis more robust. 

If monitoring trends and research results are inconsistent 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 cumulate 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 progress 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/recover_docs/cems/cem_use_of_cems.pdf

RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment 

Strategy for the MAP, Final Draft. Restoration Coordination 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. December 2006. 

www.evergladesplan.org/pm/recover/recover_map.aspx
3.0 Relationship to CERP Adaptive Management Framework October 17, 2007 

3-1 

3.0 URelationship to CERP Adaptive Management Framework 

Adaptive management provides resource managers with an active strategy for dealing 

with considerable uncertainties that characterize management of large natural 

ecosystems. Natural systems are remarkably complex and it is difficult to predict how the 

system will respond to restoration and management efforts. Adaptive management is used 

to develop opportunities to increase knowledge by applying methods of scientific inquiry 

to planning, implementation and assessment of ecosystem management projects. The 

CERP Adaptive Management Strategy (RECOVER 2006a) provides a formal process for 

CERP refinement and addressing uncertainties inherent in implementing and managing 

large-scale ecosystem restoration programs. This approach supports improved decision 

making and plan performance over time. Performance measures are an integral 

component of CERP adaptive management, allowing 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 framework identifies four major components 

of the CERP Adaptive Management Strategy and shows how these components link 

together (RECOVER 2006a). The four strategy components are Box 1: CERP Planning, 

Box 2: Performance Assessment, Box 3: Management and Science Integration, and 

Box 4: CERP Update Process. CERP system-wide performance measures are integral to 

CERP planning (Box 1) and performance assessment (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 component of these processes. 

Figure 3-1. CERP Adaptive Management Framework 
3.0 Relationship to CERP Adaptive Management Framework October 17, 2007 

3-2 

3.1 UBox 1: CERP Planning 

The goal of Box 1: CERP Planning is to apply adaptive management principles during 

system-wide and project planning by addressing performance uncertainties and 

incorporating performance-based versatility 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 major components broken down into over 40 

projects. Each project has or will have a project team that develops and uses project-level 

performance measures during the planning phase. RECOVER is responsible for 

providing technical and scientific support to CERP on a system-wide scale. To this end, 

RECOVER develops and uses system-wide performance measures. 

Within project planning (i.e., alternative plan development and formulation), RECOVER 

is responsible for evaluating performance of project alternative plans using CERP 

system-wide performance measures, project performance measures, and best professional 

judgment. RECOVER will also describe the ability of each alternative 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

RI Process

Actions to 

Reduce Project 

Uncertainties

Alternative 

Development & 

Formulation

Preliminary 

Design of TSP

Base Condition 

and Models

Detailed Design

Project 

Implementation

AFB

FSM

PM

PM
3.0 Relationship to CERP Adaptive Management Framework October 17, 2007 

3-3 

targets established for each performance measure and describe expected effects on the 

natural system. Similarly, when investigating system responses to large planning 

scenarios (e.g., sensitivity analysis of sea-level rise, updated modeling assumptions), 

RECOVER evaluates CERP’s ability to meet targets established for system-wide 

performance measures. 

3.2 UBox 2: Performance Assessment 

Monitoring and assessment of the South Florida ecosystem must be undertaken to 

determine success of CERP implementation and to provide a feedback mechanism to 

improve future planning decisions. RECOVER is using a hypothesis-based approach for 

assessment of system performance, which will provide a more robust and flexible 

approach than addressing individual performance measures. This approach takes into 

consideration complexities of ecological responses being measured by CERP systemwide and project-level monitoring by assessing their status and trends using multiple 

measures (clusters of physical, water quality and ecological attributes). This approach 

attempts to capture mechanistic interactions of multiple stressor-response pathways rather 

than relying on one metric to characterize 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 Strategy for the MAP (RECOVER 

2006b). 

RECOVER will produce technical reports (referred 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 conceptual ecological models that depict 

ecosystem relationships and system-wide performance measures developed from these 

models. Interim goals and targets are also part 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 assessment of monitoring data 

(Box 2; Figure 3-3) and. Because performance measures play an integral role in 

describing project performance at the system-wide scale, it is important that evaluation 

tools used to evaluate system-wide performance measures are developed, refined and 

revised as understanding of the ecosystem grows. It is through continual collection of 

monitoring data, calibration and verification of evaluation tools, and development of new 

tools to evaluate ecosystem responses to CERP implementation that the ability to plan 

projects to meet system-wide performance targets is improved. This feedback mechanism 

from monitoring and assessment data to evaluation tools for project planning is a key 

adaptive management principle incorporated into the CERP Adaptive Management 

Strategy. 
3.0 Relationship to CERP Adaptive Management 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 Assessment Plan: Part 1 Monitoring and 

Supporting Research. Restoration Coordination 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. Comprehensive Everglades Restoration Plan Adaptive Management 

Strategy. Restoration Coordination and Verification Program, c/o United States 

Army Corps of Engineers, Jacksonville District, Jacksonville, Florida. April 2006. 

www.evergladesplan.org/pm/recover/recover_docs/am/rec_am_stategy_brochure.

pdf

RECOVER. 2006b. Monitoring and Assessment Plan (MAP), Part 2 2006 Assessment 

Strategy for the MAP, Final Draft. Restoration Coordination and Verification 

Program, c/o United States Army Corps of Engineers, Jacksonville 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

PM
3.0 Relationship to CERP Adaptive Management Framework October 17, 2007 

3-5 

Jacksonville, FL, and South Florida Water Management District, West Palm 

Beach, FL. December 2006. 

www.evergladesplan.org/pm/recover/recover_map_part2.aspx

USACE and SFWMD. 2007. Comprehensive Everglades Restoration Plan Programmatic 

Regulations Six Program-wide Guidance Memoranda. United States Army Corps 

of Engineers, Jacksonville District, Jacksonville, FL, and South Florida Water 

Management District, West Palm Beach, FL. Revised Final Draft July 2007. 
4.0 Relationship of Performance Measures to CERP Success October 17, 2007 

4-1 

4.0 U CERP Success Points of Reference 

To determine CERP’s success in restoring the 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 aspect of measuring CERP progress. Figure 4-1

depicts each of these points, which are discussed in more detail below. 

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

U1. Pre-CERP Condition (condition prior to CERP implementation)

The first point of reference, pre-CERP condition, 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 obtained through implementation of a monitoring 

program developed specifically for the CERP. This program is laid out in the CERP 

Monitoring and Assessment Plan: Part 1, Monitoring and Supporting Research

(RECOVER 2004). Information about an indicator’s “pre-CERP condition” is provided 

under the Justification section on each performance measure documentation sheet. 

U2. Expected CERP Performance (evaluation of performance measures)

The second point of reference anticipates the system’s performance following full CERP 

implementation. This point of reference is currently determined during the planning 

process through use of hydrologic models, other evaluation tools, best available science, 

and best professional judgment. Performance measure indicators and targets are 

evaluated by comparing expected performance following full CERP implementation to 

the future without project scenario. This evaluation 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 provides valuable information regarding CERP’s expected 

performance in meeting restoration goals. It should be emphasized that expected CERP 

performance, even at full project 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

6
4.0 Relationship of Performance 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. 

U3. Interim CERP Performance (assessment of interim goals and interim targets)

The third point of reference is actual measured 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 measures, reflect expected performance of 

the plan through its implementation. Monitoring 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 Interim Goals and Interim Targets for the 

Comprehensive Everglades Restoration Plan (RECOVER 2005). If a performance 

measure is part of this subset it will be indicated under the Monitoring and Assessment 

Approach heading on performance 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 provide 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 (restoration completed) goal, not an interim goal 

or target. 

U4. CERP Performance (assessment of performance measures)

The fourth point of reference 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 reference refers to CERP performance as they relate to the causeand-effect hypotheses presented 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 two years in a System 

Status Report, this point of reference corresponds to assessment of indicators following 

full implementation. Also, assessment of interim 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 targets were developed for only a subset of 

performance measure indicators. The CERP assessment target for each measure is 
4.0 Relationship of Performance Measures to CERP Success October 17, 2007 

4-3 

provided under the Assessment Parameter and Target heading on performance measure 

documentation sheets. 

U5. Desired Restoration Condition

Desired restoration condition represents the condition necessary to provide a healthy and 

sustainable South Florida ecosystem. In many cases, desired restoration condition for an 

indicator is the same as pre-drainage, historical condition (or full restoration, sixth point 

of reference); however, it is not 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 condition is something 

different than historical condition. 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 spatial extent is, therefore, substantially lower 

than the historic condition, yet it is believed to be large enough to provide for a 

sustainable ecosystem. 

Desired restoration condition for each performance measure is outlined under 

the Restoration Expectation heading on performance measure documentation sheets. 

Setting performance measure targets based on desired restoration condition as opposed to 

expected performance (second point of reference) 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 direction 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 section will be updated if necessary upon 

instruction from the RLG. 

U6. Full Restoration

The sixth point of reference is full restoration. A fully restored South Florida ecosystem 

would be one that had returned to the pre-drainage condition. As discussed 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 accounts or computer models of the ecosystem without water 

management structures in place (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 Ecological Models, or Adaptive 

Assessment Hypothesis Clusters sections. 
4.0 Relationship of Performance Measures to CERP Success October 17, 2007 

4-4 

4.1 References 

RECOVER. 2004. CERP Monitoring and Assessment Plan: Part 1 Monitoring and 

Supporting Research. Restoration Coordination 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 Recommendations for Interim Goals and 

Interim Targets for the Comprehensive Everglades Restoration Plan. Restoration 

Coordination and Verification Program, c/o United States Army Corps of 

Engineers, Jacksonville District, Jacksonville, 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. Restoration Coordination 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. December 2006. 

www.evergladesplan.org/pm/recover/recover_map.aspx 
5.0 Relationship of Performance Measures to Interim Goals October 17, 2007 

 and Interim Targets 

5-1 

5.0 Relationship of Performance Measures to Interim Goals and 

Interim Targets 

CERP system-wide performance measures provide targets for restoration success in 

2050; interim goals and interim targets have been established to document CERP’s 

expected performance at five-year increments throughout implementation. Interim goals 

provide a means by which restoration success may be evaluated at specific points 

throughout the overall planning and implementation process. They are established to 

facilitate planning, monitoring and assessment. Interim targets provide a means by which 

CERP’s progress towards providing for water-related needs of the region may be 

evaluated. Interim goals and targets are described in The Recover Team’s 

Recommendations for Interim Goals and Interim 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 are not currently CERP 

system-wide performance measures. A sheet flow performance measure has recently 

being developed and is under review. If an indicator 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 Recommendations for Interim Goals and 

Interim Targets for the Comprehensive Everglades Restoration Plan. Restoration 

Coordination and Verification Program, c/o United States Army Corps of 

Engineers, Jacksonville District, Jacksonville, Florida, and South Florida Water 

Management District, West Palm Beach, FL. 

www.evergladesplan.org/pm/recover/igit_subteam.aspx
6.0 History of Performance Measure Development October 17, 2007 

6-1 

6.0 History of Performance 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 performance of plan alternatives and make 

performance-based recommendations. To evaluate alternatives, the interagency team was 

divided into subteams focusing on specific subregions, issues, or planning objectives and 

constraints. Each subteam developed their own set of performance measures, which were 

then used for alternative evaluation purposes. Restudy performance measures and 

evaluation results are documented in Appendix 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 1999). Some of the performance measures 

used to evaluate alternatives during the Restudy are still being used and some have been 

refined as appropriate. Detailed information regarding refinement of Restudy 

performance measures for use in current evaluations 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 assessed at regular intervals during CERP 

implementation. CERP-specific conceptual ecological models provided scientific basis 

for development of a system-wide monitoring 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, Monitoring 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 Assessment Strategy for the MAP, Final Draft

(RECOVER 2006). During development of this strategy, CERP-specific conceptual 

ecological models were revisited and revised. Hypothesis clusters representing causal 

linkages existing between ecosystem stressors and 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 clusters (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 developed to address water supply and flood 

protection needs of the human populace of South Florida. These measures are based on 

Florida Statutes, not conceptual ecological models. 

6.4 References 

RECOVER. 2004. CERP Monitoring and Assessment Plan: Part 1, Monitoring and 

Supporting Research. Restoration Coordination 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. Restoration Coordination 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. December 2006. 

www.evergladesplan.org/pm/recover/recover_map.aspx

RECOVER. 2007. Draft 2007 System Status Report. Restoration Coordination and 

Verification Team (RECOVER), U.S. Army Corps of Engineers, Jacksonville, 

FL, and South Florida Water Management District, West Palm Beach, FL. July 

2007. 

USACE and SFWMD. 1999. Central and Southern Florida Comprehensive Review Study 

Final Integrated Feasibility Report and Programmatic Environmental Impact 

Statement. United States Army Corps of Engineers, Jacksonville District, 

Jacksonville, FL, and South Florida Water Management District, West Palm 

Beach, FL. www.evergladesplan.org/pub/restudy_eis.aspx#mainreport
7.0 Criteria and Guidelines for Performance Measure Development October 17, 2007 

7-1 

7.0 Criteria and Guidelines for Performance Measure Development 

A set of criteria and guidelines has been established 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 performance 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 measures are listed below and must be followed 

when developing, revising and reviewing 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 characterize 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, energy transfer), 2) an important 

ecological structure (e.g., fragmentation, compartment-alization, 

succession, disturbance, biodiversity), or 3) major environmental 

change (e.g., hydrology, fire, water quality). 

• A performance measure indicator should be a regional or system-wide 

indicator of CERP performance. 

• A performance measure should provide information not provided by 

other performance measures being recommended for the 

physiographic region. 

• A performance measure indicator should 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 distinguished 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 Performance 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-listed threatened or endangered species? 

 Is the species a keystone species? 

 Does the species have high aesthetic value or high public appreciation or is it a 

symbol of the Everglades? 

 Does it have an important recreational value (e.g., value to fishermen, boaters or 

bird watchers)? 

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

7.2 Guidelines to Complete Performance Measure Documentation Sheets 

This section provides guidelines for completing 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 measure 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 developed as additional tools are developed and 

information becomes available. Though incomplete, these measures can still be used 

when performing alternative evaluations and assessments as long they 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 description of the region it is 

associated with (e.g., Greater Everglades, Total System, Water Supply and Flood 

Protection). The performance measure title should provide an adequate description of the 

performance measure without exceeding two lines 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 documentation 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 more detail in the following section. 
7.0 Criteria and Guidelines for Performance Measure Development October 17, 2007 

7-3 

1.0 Desired Restoration Condition. For each indicator, this section outlines conditions 

and ecological characteristics expected to represent desired restoration of a physiographic 

region or a specific attribute. The desired restoration condition does not necessarily 

reflect CERP expected performance; rather, it represents the level of restoration to 

achieve a healthy and sustainable ecosystem 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 the desired restoration condition. The desired 

restoration concept is currently 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 through simulation modeling or other methods. 

They are used to compare alternative project or program plan performance as 

determined through simulation modeling or other 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 nature and to be scientifically documented. If possible, it is 

important to identify if the performance measure 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 assess responses monitored in the field in 

natural and human systems during and following CERP implementation. Each 

assessment target identifies one or more elements to be monitored and is designed to 

assist in determining whether program objectives have been or are being attained. 

Assessment targets may be a quantitative restoration target, a minimum level of 

performance expected, or a direction of change (trend) toward an expected endpoint. 

2.0 Justification. The justification provides performance measure users with a brief, 

referenced history of the attribute or stressor being used as an indicator 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 description 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 relationship of the performance measure to 

conceptual ecological models and adaptive assessment hypotheses is provided to 

demonstrate the performance measure indicator’s relevance in determining restoration 

success with particular emphasis on how the indicator is expected to reflect CERP 

restoration. For those performance measures developed based on regulatory 

requirements, subsections will be removed and replaced by a citation for the statute or 

law that requires and authorizes the performance measure. 
7.0 Criteria and Guidelines for Performance 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 Assessment 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 reader to hypothesis clusters and conceptual 

ecological models provided as supplemental 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/recover/recover_docs/et/060507_pm_rep

ort/hypothesis_clusters_low.pdf 

• Northern Estuaries: 

www.evergladesplan.org/pm/recover/recover_docs/et/060507_pm_rep

ort/hypothesis_clusters_ne.pdf 

• Greater Everglades: 

www.evergladesplan.org/pm/recover/recover_docs/et/060507_pm_rep

ort/hypothesis_clusters_ge.pdf 

• Southern Estuaries: 

www.evergladesplan.org/pm/recover/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/recover/recover_docs/map_part2/section

_9_app_of_guidance_low.pdf

• Northern Estuaries: 

www.evergladesplan.org/pm/recover/recover_docs/map_part2/section

_9_app_of_guidance_ne.pdf 
7.0 Criteria and Guidelines for Performance Measure Development October 17, 2007 

7-5 

• Greater Everglades Module: 

www.evergladesplan.org/pm/recover/recover_docs/map_part2/section

_9_app_of_guidance_ge.pdf

• Southern Estuaries: 

www.evergladesplan.org/pm/recover/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 categories of information are necessary to perform 

an alternative evaluation: evaluation protocol, normalized performance output, model 

output, and uncertainty. 

4.1 Evaluation Protocol. The evaluation protocol provides details related to 1) the 

tool used to evaluate the performance 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 evaluation (e.g., specific comparisons 

to be made, different post-processing methods for individual locations, required 

statistical analysis of data). 

4.2 Normalized Performance Output. Numeric performance measure results are 

normalized and related to desired restoration condition. That is, if a performance 

measure does not meet its required evaluation target, what is the ecological 

significance of the difference between the evaluation result and the target? Typically, 

performance measure results are normalized on a scale from 0 to 1.0, with 0 

corresponding to fully degraded and 1.0 corresponding 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 provide output for each performance 

measure for the purposes of conducting an evaluation of alternatives. An example of 

output is provided to show evaluators how information will be presented during an 

evaluation and to aid in general understanding 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 continually reevaluated by comparison with assessment data in 

the adaptive management feedback loop between evaluation and assessment 

processes (see Section 3 of this document). Types of uncertainty associated with 

performance measure application are described in Section 16 of this document. 

Currently, this documentation sheet section 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 measure 
7.0 Criteria and Guidelines for Performance Measure Development October 17, 2007 

7-6 

indicator. These methods are found in other 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 additional tools or information to be used effectively and 

these needs are indicated on the documentation 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 information necessary to apply the performance 

measure are available, then this section of the documentation sheet is left blank. 

6.1 Evaluation Tools Needed. Specific tools needed to improve prediction of 

indicator performance when evaluating plans 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 documentation sheet is noted in this 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 Assessment Plan: Part 1, Monitoring and 

Supporting Research. Restoration Coordination and Verification Program, c/o 

United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, 
7.0 Criteria and Guidelines for Performance 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 Recommendations for Interim Goals and 

Interim Targets for the Comprehensive Everglades Restoration Plan. Restoration 

Coordination and Verification Program, c/o United States Army Corps of 

Engineers, Jacksonville District, Jacksonville, 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. Restoration Coordination 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. December 2006. 

www.evergladesplan.org/pm/recover/recover_map.aspx 
8.0 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 CERP’s ecological restoration success. These 

models were used to develop most of CERP’s system-wide performance measures. 

Hypotheses presented in the conceptual ecological models have 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 protection performance measures, which are based 

on legislative requirements. Models were developed using best available 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, environmental stressors and ecological responses, 

and provide a basis for developing and testing a set of causal hypotheses that best explain 

why natural systems in South Florida have been altered (Gentile et al. 2001). These 

models highlight attributes of natural systems that can serve as indicators of restoration 

program effectiveness. In general, conceptual ecological models developed for South 

Florida were designed to meet the following purposes: 

• Illustrate ecological links between physical, chemical and biological 

elements in specific physiographic regions of South Florida 

• Develop a suite of causal hypotheses linking the most important 

hydrological, physical and chemical stressors with major ecological 

effects and attributes as a basis for evaluating responses to restoration 

projects 

• Create a set of measurable indicators of success as a basis for 

evaluating and assessing how well projects meet broad, policy-level 

goals that have been established for regional restoration program 

These conceptual ecological models include all major external drivers, stressors, 

ecological effects, and attributes within the South Florida 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 Florida 
8.0 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 Estuaries (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). The purpose of this model is to identify 

primary ecosystem stressors and appropriate biological 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 also includes an introductory 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 CERP is only designed to address some of 

these stressors and effects. Also, CERP is expected to affect only portions of 

physiogeographic regions covered by the conceptual ecological models (Figure 8-2). 

CERP-specific conceptual ecological models were 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 interdependency of some hypotheses. 

CERP-specific conceptual ecological models depict stressors, attributes, and pathways 

CERP is expected to affect and how performance measures relate to them. CERP-specific 

conceptual ecological models from the Assessment 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 relationships that define the South Florida 

ecosystem, hypotheses and interactions that further define these relationships require 

further investigation. Linkages between attributes and stressors and specific hypotheses 

that govern ecosystem behavior are still being studied and discussed among scientists. 

Because a clear answer to these scientific differences is not yet available, testing and 

monitoring of these hypotheses is needed to refine scientific understandings. Monitoring 

activities based on CERP system-wide performance measures are expected to provide 

necessary data to answer some of theses scientific uncertainties 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/recover_docs/cems/cem_caloosahatchee_est

.pdf

Browder, J.A., R. Alleman, S. Markley, P. Ortner, P.A. Pitts. 2005. Biscayne Bay 

Conceptual Ecological Model. 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/recover_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/recover_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 ecosystem 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. Ecological 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/recover/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/recover_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 ecosystem restoration in South Florida. 

Wetlands 25(4):795-809. 

www.evergladesplan.org/pm/recover/recover_docs/cems/cem_use_of_cems.pdf

RECOVER. 2004. CERP Monitoring and Assessment Plan: Part 1, Monitoring and 

Supporting Research. Restoration Coordination 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. Restoration Coordination 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. 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. Wetlands 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/recover_docs/cems/cem_st_lucie_irl.pdf

VanArman, J., G.A. Graves, and D. Fike. 2005. Loxahatchee Watershed conceptual 

ecological model. Wetlands 25(4):926-942. 

www.evergladesplan.org/pm/recover/recover_docs/cems/cem_loxahatchee.pdf
9.0 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 Conceptual 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 measures relate to them. Application of 

performance measures during evaluation (planning) 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, nutrient 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 increased turbidity. Major wind and wave events 

can also increase turbidity and can result in large-scale destruction 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 desirable native SAV species. Changes in the 

extent of mud sediments in the littoral-pelagic fringe zone resulting from changes in 

nutrient loading and runoff influence potential 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 have been developed to assess and evaluate 

effects of CERP implementation on Lake Okeechobee 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 stage. The water quality performance measure 

includes nutrient concentrations, 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 management and nutrient load management 

changes are made as CERP is implemented and macroinvertebrate 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 vegetation increases. Reduced nutrient loads 

are expected to reduce and/or cap mud sediments, and increase areas underlain by sand 

and peat sediments. Presence of dense SAV and emergent vegetation, sand and peat 

sediments, and low nutrient loads will provide habitat that will sustain a more diverse 

population of macroinvertebrate species with less pollutant-tolerant species. 

A CERP system-wide performance measure has 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 measures 
9.0 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, phytoplankton growth rates and occurrence 

and intensity of algal blooms increase. 

Figure 9-4. Phytoplankton Conceptual Ecological Model with associated 

performance measures 
9.0 Lake Okeechobee CERP-Specific Conceptual October 17, 2007 

 Ecological Models and Performance Measures 

9-5 

Nitrogen to phosphorus ratio (N:P) has been altered, shifting conditions from a 

phosphorus-limited to an nitrogen-limited system whenever the system is not light 

limited. Frequency of severe cyanobacterial 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 species. SAV and associated epiphytes can 

reduce water column phosphorus concentrations and stabilize sediment preventing 

resuspension of phosphorus back into the water column. These conditions inhibit 

phytoplankton growth and algal bloom frequency and intensity when nutrient 

concentrations are high. 

A diatom-cyanobacteria ratio system-wide performance 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-phosphorus ratios and light conditions, 

which both affect phytoplankton biovolume and taxonomic composition. High lake stage, 

which also affects this attribute, is tracked by the lake stage performance measure. 

9.4 Native Fish Species 

Native fish species are affected by SAV, nutrient loads, sediment composition, exotic 

animal species and lake levels (Figure 9-5). Increases in SAV density, biomass and aerial 

coverage improve fish habitat and fish foraging opportunities and 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 mud 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, removes 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 development of dense algal blooms. 

These algal blooms can result in fish kills and negative impacts on other wildlife either 

through the development of anoxic conditions 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 condition in Lake Okeechobee (Figure 9-5). Performance 

measures have also been developed for lake stage, water quality, diatom-cyanobacteria 

ration, vegetation mosaic and macroinvertebrates, 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 Conceptual 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 waves, 2) transport pelagic water with high 

phosphorus concentrations into interior regions of the marsh, 3) cause physiological 

stress in rooted emergent macrophytes resulting 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 extensive physical damage through uprooting or 

breaking emergent plant stems. Operating Lake Okeechobee at lower overall lake stages 

and providing periodic recession events will reverse these trends and encourage 

expansion of desirable native emergent vegetation. On the other hand, low water events 

can accelerate spread of exotic and nuisance invasive vegetation such as torpedograss, 

melaleuca and cattail. However, low water events will stimulate germination of desirable 

native vegetation and encourage occurrence of fire, which may help control undesirable 

exotic and invasive species. Exotic vegetation 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 emergent vegetation response to CERP 

implementation (Figure 9-6). This measure includes reduction in exotic vegetation in its 

restoration expectation. The water quality performance measure has targets for light 

conditions and nutrient concentrations, which 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 Vegetation Mosaic Conceptual Ecological 

Model with associated performance measures 
9.0 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 controlling 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 quality performance measure. The lake stage 

performance measure includes targets for high lake stage. 

Figure 9-7. Exotic Vegetation Conceptual Ecological Model with associated 

performance measures 
9.0 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 that 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.org/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. Restoration Coordination 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. December 2006. 

http://www.evergladesplan.org/pm/recover/recover_map.aspx 
10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 

 Ecological Models and Performance Measures 

10-1 

10.0 Northern Estuaries CERP-Specific Conceptual Models and 

Performance Measures 

The Northern Estuaries region includes Caloosahatchee, St. Lucie and Loxahatchee 

Estuaries, and Lake Worth and Indian River 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-specific conceptual ecological models for 

Northern Estuaries. These models provide a visual description of causal pathways 

described in hypotheses clusters. Clusters reflect major attributes of estuarine systems 

expected to be affected by CERP: oyster, fish, submerged aquatic vegetation (SAV) and 

benthic infaunal community. 

The following sections briefly summarize descriptive text for hypotheses clusters and 

present conceptual ecological model diagrams along with how performance measures 

relate to them. Application of performance measures during evaluation (planning) 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/recover_docs/et/060507_pm_report/hypothesi

s_clusters_ne.pdf. 

Figure 10-1. Northern Estuaries Module boundary along the Gulf Coast 
10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 

 Ecological Models and Performance Measures 

10-2 

Figure 10-2. Northern Estuaries Module boundaries along the Atlantic Coast 
10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 

 Ecological Models and Performance Measures 

10-3 

10.2 Oyster 

Reduction in oyster coverage within Northern Estuaries is largely due to altered 

freshwater inflow and changes in hydrodynamics resulting from water management 

practices (Figure 10-3). These changes have altered salinity and led to sedimentation. 

Water management practices release significant volumes of fresh water over a short 

period of time into estuaries 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 salinity envelope can result in increased 

susceptibility to disease. 

Figure 10-3. Oyster Conceptual Ecological Model with associated performance 

measures 

In addition to altering salinity, freshwater inflow carries sediments with silt, clay and 

high organic content and result in increased transport of floating aquatics, which then 

degrade and contribute to muck accumulation 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 content making the area unsuitable for larval 
10.0 Northern Estuaries CERP-Specific Conceptual October 17, 2007 

 Ecological Models and Performance Measures 

10-4 

settlement and growth. Suspended solids may clog adult oyster gills 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 during and following CERP implementation 

10.3 Fish 

Fish communities within Northern Estuaries are negatively affected by changes in natural 

salinity regimes and sedimentation composition and rate as a result of water management 

practices (Figure 10-4). Timing and severity of salinity fluctuations affects reproduction 

and growth of fish and availability 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 habitat for estuarine fish. Healthy oyster bed 

habitat is essential for survival of oyster dwelling fish and, as discussed in the previous 

section, muck does not support oysters. SAV communities that serve as fish habitat are 

also affected by salinity regime. 

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

measures 
10.0 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 associated with stream configuration and topography, flow 

dynamics, water depth, and stream bank location and proximity, thus directly influencing 

fish species associated with shallow marginal sediment deposits. 

CERP implementation should result in more natural freshwater 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 sedimentation) stressors and the 

fish community attribute to CERP implementation. 

10.4 Submerged Aquatic Vegetation 

Water management practices have altered natural 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 large decreases in spatial extent and changes in SAV species 

composition. Large deposits of muck have displaced normal sandy substrate and altered 

sediment characteristics contributing to decreased extent of SAV beds. Increased 

nutrients, dissolved organic matter, and turbidity increase phytoplankton levels and water 

color, which decreases the amount of light that penetrates the water column, decreasing 

photosynthetically-active radiation (PAR) at SAV blades. PAR is further reduced by 

increased epiphyte growth caused by increased nutrient availability and/or decreased 

grazing pressure. 

CERP implementation is expected to provide more natural freshwater flows to Northern 

Estuaries, reducing stresses caused by changes to salinity regime, water quality and water 

clarity that are negatively affecting SAV. Performance measures have been developed for 

salinity and water quality stressors. Water quality indicators include water clarity and 

nutrient loads and concentrations. A SAV 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 Model 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 communities 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 and prevent larval recruitment. 

CERP implementation is expected to provide more natural freshwater flows to Northern 

Estuaries, reducing stresses caused by changes 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 Macroinvertebrates 
10.0 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 the Northern Estuaries Performance Measure 

web page: http://www.evergladesplan.org/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. Restoration Coordination 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. December 2006. 

http://www.evergladesplan.org/pm/recover/recover_map.aspx
11.0 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), Everglades National Park, mangrove estuaries 

along the southern coast, part 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 CERP 
11.0 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 interrelated hypotheses for the Greater 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 Aquatic Fauna Forage Base 

• Linkage of Periphyton to Higher Trophic Levels 

• Everglades Crocodilian Populations 

The following sections summarize descriptive text for hypotheses and present conceptual 

ecological models along with how performance measures relate to them. Application of 

performance measures during evaluation (planning) and assessment process, including 

the hypothesis-based approach, are 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/recover/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 inputs of phosphorus and other 

chemical constituents to levels approximating those in direct rainfall. 

Sheet flow, in combination with direct rainfall, produced fundamental hydrologic and 

landscape characteristics of the predrainage Everglades (Figure 11-2). 

Compartmentalization has altered or eliminated sheet flow and related natural system 

hydrologic and landscape characteristics throughout the Everglades. Decompartmentalization combined with resumption of natural volume, distribution, and timing of 

freshwater delivery is expected 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 Quality Conceptual Ecological 

Model with associated performance measures 
11.0 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 implementation: 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 measure has recently been developed and is 

under review. Performance measures have also been developed to measure hydrologic 

response of mangrove estuaries to altered freshwater flows resulting from CERP 

implementation: 1) Coastal Salinity Gradients and 2) Southern Estuaries Salinity. The 

second measure is a Southern Estuaries performance measure, but it also pertains to 

Everglades mangrove estuaries within the Greater Everglades module boundary. 

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 downstream of canal discharge structures, shifting 

wetlands from oligotrophic to eutrophic states. Nitrogen dynamics are dominated by local 

cycling and processing under natural 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’ shoreline and coastal wetland stability is determined by dynamic 

interaction of freshwater outflows, sea level rise, saline water inflow, sediment 

import/export rate, and response of sedimentary environment to water level changes 

(Figure 11-3). Sustained substrate buildup in coastal marl and mangrove environments 

are not capable of keeping up with sea level rise, resulting in encroachment of marine 

conditions inland. Also, organic peat substrates 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 Park, 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 interactions between freshwater flow and sea 

level rise are tracked using Coastal Salinity Gradients and Southern Estuaries Salinity 

performance measures. Coastal substrate accretion is tracked by the Mangrove Forest 

Production/Soil Accretion performance measure. Freshwater and Estuarine Vegetation 

Mosaics, and Southern Estuaries Submerged 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 

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Figure 11-3. Coastal Transgression Conceptual Ecological Model with associated 

performance measures 
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11-6 

11.3 Tidal Channel Characteristics 

Dendritic pattern, channel width and depth, flow volume, and material transport of tidal 

watercourses through coastal mangrove estuaries are controlled by sea level interacting 

with volume, timing and distribution of sheet flow and channel 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 vegetation of surrounding 

landscapes. Reduced freshwater flow volume and rising sea level are probable 

contributing factors. Restored freshwater inflow from the Everglades is expected to help 

sustain open watercourses through the estuary that will more closely resemble historic 

patterns, yet sea level rise is expected to modify patterns of connectivity through coastal 

wetlands and create increased sediment loads. With rising sea level, offshore marine 

waters become connected to interior lakes and 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 particulates, nutrients and 

dissolved organics. 

A performance measure, Tidal Creek Sustainability, has been developed to track effects 

of restoration and sea level rise on tidal creeks. Several 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 Everglades National Park, and 3) Southern 

Estuaries Salinity. These measures will track effects 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 Everglades prior to drainage produced prolonged pooling of fresh 

water upstream and prolonged patterns of freshwater flow into mangrove estuaries. 

Freshwater pooling and inflow supported a wide salinity gradient, including a broad 

oligohaline zone, in mangrove estuaries. Reduced freshwater flow and increased sea level 

rise have resulted in higher salinities in formally estuarine mangrove zones and 

significant saline intrusion into former freshwater 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 measure has recently been developed and is 

currently under review. The Water Levels at Regionally Significant Gauge Stations in 

Everglades National Park is a Southern Estuaries performance measure that pertains to 

water levels along the southern coast of the Everglades. The Coastal Salinity Gradients 

performance measure relates to surface water salinity gradients in the southern 

Everglades. 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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Figure 11-4. Tidal Creek Channel Conceptual Ecological Model with associated 

performance measures 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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11-8 

Figure 11-5. Coastal Salinity Gradients Conceptual Ecological Model with 

associated performance measures 
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11-9 

Movement of the freshwater/saltwater interface in the shallow aquifer depends on 

intensity and duration of freshwater flows to the lower Everglades during the dry season. 

As freshwater flow has decreased, saltwater has intruded into the aquifer. Currently, two 

water supply performance measures have been developed to track saltwater intrusion into 

the aquifer: 1) Prevent Saltwater 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 saltwater 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 freshwater sheet flow caused by CERP implementation is expected 

to maintain low nutrient conditions in the Everglades mangrove estuaries, and is being 

tracked by two performance measures: 1) Greater 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 increases, ultimately enhancing 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 dependent on hydrologic flushing by 

either fresh or saline water, which is driven by sea level and sheet flow from the 

Everglades. A sheet flow performance measure has recently been developed and is 

currently under review. In addition to the sheet flow performance measure, two 

performance measures pertain to hydrologic flushing: 1) Water Levels at Regionally 

Significant Gauges Stations in Everglades National Park and 2) Southern Estuaries 

Salinity. Both are Southern Estuaries performance measures, but they pertain to the 

mangrove forest along the edge of the Greater Everglades module boundaries. If flow and 

flushing diminish, then wetland communities collapse. Improved freshwater flow and 

flushing through the lower Everglades and coastal wetlands are expected to aid in 

recovery of wetlands from catastrophic setbacks. The Wetland Landscape Patterns – 

Freshwater and Estuarine Vegetation Mosaics performance measure includes these 

wetland communities. 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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Figure 11-6. Mangrove Forest Production, Organic Soil Accumulation, and 

Resilience Conceptual Ecological Model with associated performance measures 
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11.6 Ridge and Slough Landscape Dynamics Conceptual Ecological Model 

Ridge and slough landscape dynamics are maintained 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 flow 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 with hydroperiod, water depth, 

eutrophication, fire and cattail expansion to reduce natural habitat diversity and stability. 

Decompartmentalization, in combination with sheet flow resumption, will restore natural 

features of the Everglades ridge and slough 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 addressed by three performance measures: 

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. The sheet flow performance measure has recently been developed 

and is currently under review. Nutrient dynamics are being addressed with performance 

measures for TP and TN concentrations in surface water and TP concentrations in peat 

soil. Two wetland landscape pattern performance 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 communities along elevation gradients are 

determined by patterns of hydroperiod, water depth, nutrient dynamics and fire patterns 

(Figure 11-8). Dynamic equilibrium of the vegetation mosaic is maintained if 

biogeochemical processes in soil support physiological requirements of vegetation. It is 

altered if water depths or hydroperiods decrease or increase. Anthropogenic disturbances 

of hydroperiods, water depths, eutrophication, fire patterns, land use change, and spread 

of exotic plants have shifted the vegetation mosaic away from historic dynamic 

equilibrium. More natural hydroperiods, water depths and flow regimes will reestablish 

and sustain ridge and slough landscape patterns without significant 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 are being addressed by 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 measure has recently been developed 

and is under review. Nutrient dynamics are being addressed with performance measures 

for TP and TN. Two performance measures, 1) Freshwater and Estuarine Vegetation 

Mosaics and 2) Ridge and Slough Community Sustainability, address plant communities. 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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11-12 

Figure 11-7. Ridge and Slough Landscape Dynamics Conceptual Ecological Model 

with associated performance measures 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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11-13 

Figure 11-8. Plant Communities/Elevation Gradients Conceptual Ecological Model 

with associated performance measures 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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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 southern Everglades is attributed to declines 

in population densities and seasonal concentrations of marsh fishes and other aquatic prey 

organisms, a shift in location and timing of these seasonal concentrations, and reduced 

shallow water foraging options for wading birds along elevation gradients (Figure 11-9). 

Wading bird forage base has been disrupted by disruption of dry 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 southern Everglades, while 

densities have increased in the artificial pools of the WCAs, which now favor larger, 

longer-lived species. While increased 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 often disrupt prey concentrations that are required for 

successful foraging by wading birds, resulting 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 densities and concentrations across the landscape. It will also 

concentrate wading bird prey into a succession of high-density patches throughout the dry 

season in the remaining ridge and slough, marl prairie and coastal landscapes. Prey base 

restoration is expected to reestablish wading bird nesting colonies in coastal and tributary 

regions of the southern Everglades and roseate spoonbill nesting colonies in northeastern 

Florida Bay. It is also expected to increase 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 wading 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 formation. Super colonies periodically formed 

along the freshwater-estuarine transition zone at lower reaches of Everglades and Big 

Cypress basins. A substantial reduction in frequency of super colonies is attributed to 

disrupted multi-year wet and dry cycles. Reduction in super colony size may be related to 

reductions in wading bird prey. Population dynamics 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 stimulate pulses of secondary productivity that 

will likely involve crayfish populations. Pulses in secondary production are expected to 

result in an increase in return frequency and size of ibis-dominated super colonies in 

tributary headwaters of Shark River and other Gulf of Mexico mangrove estuaries at a 

frequency of two or more events per decade. 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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Figure 11-9. Predator-Prey Interactions of Wading Birds and Aquatic Fauna 

Forage Base Conceptual Ecological Model with associated performance measures 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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Several hydrologic performance 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) Extreme 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 being 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 performance measure has been developed to 

address wading bird foraging patterns and two performance measures have been 

developed to address nesting patterns. 

11.9 Linkage of Periphyton to Higher Trophic Levels Conceptual Ecological Model 

Floating mats of periphyton and bladderworts, which require long hydroperiods and low 

TP levels to survive and expand, 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 fish, 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 this model. Response of hydroperiod to CERP 

restoration is being tracked by three performance measures: 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. 

The Greater Everglades Wetlands TP Concentrations in Surface Water performance 

measure addresses site nutrient state, which affects periphyton mats. Several performance 

measures have been developed to address trophic levels affected by periphyton: 

1) Regional Populations of Fishes, Crayfish, 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 

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Figure 11-10. Linkage of Periphyton to Higher Tropic Levels Conceptual Ecological 

Model with associated performance measures 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

 Ecological Models and Performance Measures 

11-18 

11.10 UEverglades 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 alligator populations and alligator holes (aquatic 

refugia) leading to increased aquatic fauna density (alligator prey) has been disrupted. 

Reduced freshwater flow into mangrove estuaries has resulted in succession of former 

freshwater mangrove areas to saltwater systems, reducing alligator populations in tidal 

rivers and tributaries. Compartmentalization, disrupted sheet flow, and regulatory water 

releases restrict alligator populations in the ridge and slough landscape by causing nest 

flooding, unsuitable overdrained and pooled habitats in WCAs, and low hatchling and 

juvenile survival in canals during low water periods. 

With resumption of natural flow patterns to the Everglades as CERP is implemented, the 

American alligator is expected to repopulate and resume nesting in rocky glades and 

freshwater reaches of tidal rivers in mangrove estuaries and will increase in population 

size and improve in body condition. Three performance measures 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. Response of aquatic prey base is addressed by 

the Regional Populations of Fishes, Crayfish, Grass Shrimp and Amphibians performance 

measure. A performance measure has also been developed to track American alligator 

distribution, size and condition. 

American Crocodile

In estuaries, crocodiles orient towards areas 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 juvenile 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 salinity gradients will increase growth and 

survival of juvenile crocodiles. 

Two performance measures address salinity in areas inhabited by crocodiles: 1) Coastal 

Salinity Gradients and 2) Frequency of Low Salinities and High Salinities in Florida Bay 

(a Southern Estuaries performance 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 measures 
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11-20 

11.11 Greater Everglades Wetlands Performance Measures 

Greater Everglades Wetlands performance measures are as follows: 

• Sheet flow in the Everglades Ridge 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 Concentration in Inflows to Greater 

Everglades Wetlands 

• TP Concentrations in Soil 

• Greater Everglades Tracer of Stormwater 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 Prairie Cape Sable Sparrow Habitat 

• Wetland Landscape Patterns - Ridge and Slough Community Sustainability 

• Wetland Landscape Patterns - Tidal Creek Sustainability 

• Wetland Trophic Relationships - Periphyton 

• Wetland Trophic Relationships - Mangrove Forest Production/Soil Accretion 

• Wetland Trophic Relationships - Regional Populations of Fishes, Crayfish, 

Grass Shrimp and Amphibians 

• Wetland Trophic Relationships - Wading Bird Foraging Patterns on 

Overdrained Wetlands 

• Wetland Trophic Relationships - Wading Bird Nesting Patterns 

• Roseate Spoonbill Nesting Patterns 

• Wetland Trophic Relationships - American Alligator Distribution, Size, 

Nesting and Condition 

• American Crocodile – Juvenile Growth and Survival 
11.0 Greater Everglades CERP-Specific Conceptual October 17, 2007 

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Documentation sheets can be accessed from the Greater Everglades Performance 

Measures web page: http://www.evergladesplan.org/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. Restoration Coordination 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. December 2006. 

http://www.evergladesplan.org/pm/recover/recover_map.aspx
12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 

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12.0 Southern Estuaries CERP-Specific Conceptual Ecological Models 

and Performance Measures 

Southern Estuaries influenced by CERP include Florida Bay, coastal lakes inland from 

Florida Bay, Biscayne Bay, and estuaries within 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 Strategy 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 expected to be affected by CERP: water quality, 

submerged aquatic vegetation (SAV), nearshore community structure, nearshore nursery 

function, and toxins and contaminants. 

Figure 12-1. Southern Estuaries within CERP’s influence 
12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 

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The following sections briefly summarize descriptive text for hypotheses clusters and 

present conceptual ecological model diagrams along with associated performance 

measures. Application of performance measures during evaluation (planning) and 

assessment processes, using 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/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 water 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 extent, duration, density 

and composition of phytoplankton blooms are controlled by several factors that will be 

influenced by CERP: external nutrient loading, 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 measures 
12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 

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Four performance measures relate to the Water Quality Conceptual Ecological Model. A 

performance measure has been developed for water levels in Everglades National Park 

(ENP). The Southern Estuaries Salinity performance 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. Seagrass is affected by 

changes in light penetration, epiphyte load, nutrient availability, salinity, hypoxia/anoxia, 

sulfide toxicity and disease. Benthic algae is affected by light penetration, nutrient 

availability, salinity, temperature and changes in seagrass density and species 

composition. Significant changes in benthic algae and seagrass distribution and density 

can affect susceptibility to sediment resuspension and stability of mud banks as well as 

nutrient availability to other primary producers. 

Figure 12-3. Submerged Aquatic Vegetation Conceptual Ecological Model with 

associated performance measures 
12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 

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CERP implementation will alter volume, timing and spatial distribution of freshwater 

inflow to Southern Estuaries. These alterations 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 performance 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 penetration, algal blooms and toxicants and pathogens. 

An SAV performance measure has also been developed. 

12.3 Nearshore Nursery Function 

Shoreline and bottom configuration, vegetation and salinity patterns are characteristics 

that define estuarine nursery habitat and determine their productive capacity, and thereby 

abundance of species. Complex habitats increase productive capacity by reducing 

predation, providing a wider variety and abundance of food organisms, reducing physical 

disturbance, and providing substrates for attachment. Alteration of volume, timing and 

spatial distribution of freshwater inflow that occurred with past water management 

practices has decreased productive capacity of estuarine nursery grounds by altering both 

bottom and shoreline vegetation and salinity patterns 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 characteristic of coastal wetlands and nearshore 

zones. Increased availability of complex mangrove-shoreline and seagrass habitat and a 

broadened salinity gradient will increase fish and macroinvertebrates diversity. Several 

performance measures have been developed for tracking CERP success in restoring 

nearshore community structure. Freshwater inflow patterns are simulated and determined 

using water levels at Everglades National 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 attributes 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 Southern Estuaries have been diminished or 

eliminated by past and current water management practices. Waters that are consistently 

of intermediate salinity tend to support highly productive, but relatively low diversity, 

plant and animal communities. In many nearshore areas of Biscayne and Florida Bays, 

freshwater flow is so variable that downstream salinity regimes are suboptimal for 

freshwater, brackish and marine organisms alike. 
12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 

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Figure 12-4. Nearshore Nursery Function Conceptual Ecological Model with 

associated performance measures 

CERP is expected to restore freshwater inflow patterns to this region, which is expected 

to restore salinity patterns, and seagrass and mangrove communities (Figure 12-5). 

Restoration of salinity regime and plant 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 Estuaries. 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 developed for three attributes 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 

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Figure 12-5. Nearshore Community Conceptual Ecological 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 sediments, and eventually increase contaminant and 

toxin burdens in organisms inhabiting estuaries (Figure 12-6). Implementation of CERP 

along with increased urban and agricultural development will result in changes in 

distribution and sources of fresh 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 also be routed through areas undergoing rapid 

urban development and redevelopment, which may also increase contaminant loads. 

Rerouting of water through coastal wetlands may reduce loads to bays. Increase in 

contaminants is expected to affect benthic community composition; growth, survival, 

development of invertebrates and fish; and dolphin health. It is also expected to increase 

prevalence of abnormal fish changes. Changes that occur in fish and pink shrimp and 

associated epifauna will be tracked by performance measures developed for these 

attributes.
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Figure 12-6. Toxins and Contaminants Conceptual Ecological Model with 

associated performance measures 
12.0 Southern Estuaries CERP-Specific Conceptual October 17, 2007 

 Ecological Models and Performance Measures 

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12.6 Southern Estuaries Performance Measures 

The performance measures for the Southern 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 from the Southern Estuaries Performance 

Measures web page: http://www.evergladesplan.org/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. Restoration Coordination 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. December 2006. 

http://www.evergladesplan.org/pm/recover/recover_map.aspx
13.0 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 increase availability of fresh water resulting in 

fewer water restrictions for South Florida residents and less competition for water 

between people and the natural system. The State 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 year 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 designated 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 Tribe of Florida’s Brighton 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 developed for water restrictions in these areas 

based upon Section 373.0361(2)(a)(1) of the Florida Statutes. Each area has a 

performance measure for frequency of water restrictions and duration and severity of 

water restrictions. 

Figure 13-1. Lake Okeechobee Service Area 
13.0 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 developed for saltwater intrusion into the Biscayne 

aquifer and flood protection. Saltwater intrusion performance measures are based upon 

Chapter 40E-8 of the Florida Administrative Code and Section 373.044 of the Florida 

Statutes. Flood protection performance measures 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 measures to evaluate CERP effects on 

water supply and flood protection during plan formulation and revision: 

• Frequency of Water Restrictions for Lake Okeechobee Service Area 

• Frequency of Water Restrictions for Lower East Coast Service Area 
13.0 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 Biscayne Aquifer - Meet Minimum 

Flows and Levels Criteria for Biscayne Aquifer 

• Prevent Saltwater Intrusion of Biscayne Aquifer in South Miami-Dade 

County 

• Comparison of Stage Differences of Water 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 Protection of the Cape Sable Seaside Sparrow. 

Prepared for the United States Army Corps of Engineers, Jacksonville District, 

Jacksonville, Florida. February 2001. 
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14.0 Total System CERP-Specific Conceptual Ecological Models and 

 Performance Measures 

The total South Florida ecosystem encompasses all natural areas that were once 

interconnected and embedded within the vast Everglades basin, which once extended 

from coast to coast and from the upper Kissimmee 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 developed 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 spatial requirements, 3) healthy, dynamically 

sustainable estuaries, 4) oligotrophic freshwater 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 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, contains a Total System 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 used in the overarching conceptual ecological 

model (Ogden et al. 2005). For the most part, 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-wide, whether effects were expected in an 

area or not. 

Only a few total system performance measures 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 diagrams along with the total system measures. Additional 

total system performance measures are currently being developed and existing measures 

are being refined. 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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Figure 14-1. Total System Conceptual Ecological Model boundary 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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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 attributes are all affected by marsh aquatic fauna 

prey base, hydroperiod and depth patterns, and habitat availability and fragmentation 

(Figure 14-2). Water management and land use practices 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 gradients, geomorphology and topography. The 

relationship between large vertebrates and aquatic prey base has also been addressed in 

the Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base 

Conceptual Ecological Model (Figure 11-9) in the Greater Everglades section of this 

document. 

Performance measures developed for Greater Everglades and Southern Estuaries regions 

relate to stressors, effects and attributes within the Abundant Large Vertebrates and 

Aquatic Prey Bases pathway (Figure 14-3). Measures have been developed for 

phosphorus and nitrogen input into and surface water concentrations within Greater 

Everglades wetlands. Hydrology performance measures have been developed for sheet 

flow, water levels, flows, dry events and inundation pattern for Greater Everglades and 

Southern Estuaries. Salinity performance measures have been developed for the southern 

edge of the Everglades. Greater Everglades performance measures pertaining to attributes 

of this model include those for wading bird foraging patterns; wading bird nesting 

patterns; fish, crayfish, grass shrimp and amphibian populations; and alligators. These 

attributes are discussed in more detail 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 crayfish, 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 large numbers of birds moving quickly to form 

nesting colonies wherever foraging conditions are locally favorable (Frederick and Ogden 

1997). This reproductive strategy works well when ibis can forage over extensive areas of 

wetlands. 
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Figure 14-2. Abundant Large Vertebrates and Aquatic Prey Bases Conceptual 

Ecological Model and associated performance measures 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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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 locations 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 concentrations 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 patterns. The great expanse of pre-drainage 

wetlands provided an overall abundance of prey as well as many options for long-flying 

adults to exploit a succession of drying wetlands over about a four-month nesting cycle 

for storks. Overall, wood stork epitomized pre-drainage wetlands, 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 structure 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 hydroperiod. Relative abundance affects 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 wading birds, reptiles, amphibians and mammals 

(Kushlan and Kushlan 1979, Ashton and Ashton 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 higher order vertebrate 

predators (Momot et al. 1978). 

American Alligator

American alligator was an abundant and ubiquitous animal in pre-drainage wetlands. 

Alligators are dependent on hydrologic conditions for growth and survival (Hines et al. 

1968, Fogarty 1974, Wilkinson 1983). Open water is required for breeding (McIlhenny 

1935, Garrick and Lang 1975, Garrick and Lang 1977, Vliet 1987). Nesting success is 

also dependent on egg survival during an extended incubation period, when they can be 

exposed to flooding or desiccating conditions (Joanen 1969, Kushlan and Jacobsen 1990, 

Fleming 1991). Alligator are an important keystone species in South Florida, where its 

activities have shaped the landscape by creating ponds and trails that provide important 

survival, foraging and movement functions for many species. 
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14.2 Animals with Large Spatial Requirements 

Animals within the South Florida system that require large spatial requirements include 

white ibis, wood stork, Florida panther and snail kite. These 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 dominated 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. Ibis tend to forage for prey close to colony 

locations and, therefore, relocate their colony sites and alter timing of nesting from year 

to year in responses to shifting locations of high prey densities. Storks forage on larger 

marsh fish, often in deeper pools that did not dry annually. As mentioned above, storks 

routinely soar to forage great distances from colony sites. Historically, ibis initiated 

nesting in most years in mid- to late dry seasons when regional water levels were 

generally low, while storks initiated nesting early in dry seasons when water levels were 

generally higher. With a comparatively short nesting cycle for ibis and a much longer 

cycle for storks, both species fledged young birds 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 behavioral patterns of these 

two species because of the large spatial extent of the system and temporal and spatial 

complexity of landscape mosaics and water depths. Greater Everglades Performance 

measures have been developed for wading bird foraging and nesting patterns (Figure 14-

3). 

Snail Kite

Prior to the 1920s, kites in Florida were commonly observed at many shallow, 

freshwater, long-hydroperiod wetland 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 known 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 apple snails. Long-term survival of healthy 

populations of kites depends on availability of numerous habitat options where kites can 

relocate in response to spatially and temporally complex wet and dry climate patterns. A 

Total System performance measure has been developed for snail kite foraging conditions 

(Figure 14-3). 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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14-7 

Figure 14-3. Animals with Large Spatial Requirements Conceptual Ecological 

Model and associated performance measures 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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14-8 

Florida Panther

Prior to drainage, Florida panthers occurred throughout uplands and short hydroperiod 

wetlands of Florida. Panthers require large home ranges. Numerous factors influence 

actual home range size and reproductive success, including habitat 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., highways, urban areas, large 

expanses of row crops and improved pasture) (Maehr et al. 2002, Beier et al. 2003). 

White-tailed deer and wild hogs are dominant prey for panthers, while rabbits, raccoon 

and armadillos were of secondary importance (Beier et al. 2003). 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 water to South Florida’s estuaries (Figure 14-4). These 

alterations have altered natural salinity gradients. Restoration of more natural salinity 

gradients and nutrient dynamics is necessary for healthy, dynamically sustainable 

estuaries. CERP goals include reestablishing more natural salinity gradients by restoring 

freshwater flow to estuaries. Several performance measures have been developed for 

freshwater flow and salinity gradients/patterns (Figure 14-4). A sheet flow performance 

measure has been developed for the ridge and slough landscape and is currently under 

review. The Southern Estuaries Salinity performance measure has targets for surface 

water flow and salinity envelopes. Another Southern Estuaries performance measure has 

targets for water levels at gauges in Everglades National Park from which water flows 

into Florida Bay. Salinity gradient performance 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. Nutrient 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 phosphorus-laden waters to tide via St. Lucie and Caloosahatchee 

Estuaries resulting in extensive algal blooms. As these events have occurred after the 

Total System Conceptual Ecological Model (Ogden 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 conditions: 1) functional 

submerged aquatic vegetation (SAV)-phytoplankton balance, 2) nitrogen-phosphorus 

balance, 3) American oyster, and 4) nursery ground function. Reasons these indicators 

were chosen are discussed below. 
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Figure 14-4. Healthy, Dynamically Sustainable Estuaries Conceptual Ecological 

Model and associated performance measures 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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Functional SAV-Phytoplankton Balance

Within estuaries and coastal lakes of the South Florida ecosystem, SAV provides habitat 

and nursery grounds for many fish and invertebrate communities (Gilmore 1977, Ogden 

and Zeiman 1977, Gilmore et al. 1981, Furse and Fox 1994). Changes in SAV 

distribution, composition and density due to changes in quantity, quality, timing and 

distribution of freshwater flows 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, Dennison et. al. 1993, Morris and Tomasko 1993, 

Stevenson et al. 1993). SAV communities may not only be directly influenced by nutrient 

inputs from a watershed; they may influence effects of these nutrients by competing with 

phytoplankton for them and altering nutrient cycles. 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-development Everglades watershed probably 

released low phosphorus concentrations to downstream estuaries. Even with land 

development and phosphorus enrichment of the 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 (including 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, within 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 results in greater light 

penetration, promoting SAV growth immediately downstream from oyster bars. The 

American oyster is highly sensitive 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 trophic level species, such as game fish, water 

birds and dolphin. Pink shrimp is ecologically important in Florida Bay, Biscayne Bay 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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and mangrove estuaries of southwest Florida as a major link between food web base and 

top consumers, including game fish (Rutherford et al. 1982, 1983, Schmidt 1989, Koenig 

et al. 2001) and wading birds (Palmer 1962). Pink shrimp is also economically important 

as the basis of the multi-million-dollar Tortugas fishery (Upton et al. 1992) and other 

fisheries. Pink shrimp spawn on Tortugas grounds; resulting larvae/post-larvae migration 

to Florida Bay, where they spend their juvenile stage, then return to Tortugas grounds to 

spawn. The entire cycle occurs in just a few months, enhancing potential for determining 

influencing factors. A performance measure has been developed for juvenile pink shrimp 

and associated epifauna (Figure 14-4). 

SAV communities within estuaries provide nursery habitat for juvenile stages of reef and 

recreationally important fishes (Virnstein et al. 1983, Lewis 1984). Spotted seatrout is 

almost entirely dependent on estuaries throughout its life cycle (Iverson 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 Yerger 1976). For this reason, 

its status may be indicative of local estuarine 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 Everglades was an oligotrophic wetland system 

that received external water and nutrient inputs 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 concentrations 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 Everglades Agricultural Area, changed patterns of 

nutrient input to point source discharges of agricultural drainage water (Light and Dineen 

1994). 

Input of nutrients, mainly phosphorus, and alteration of regional hydropatterns, which 

have resulted from the water management system 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 affecting indicators of this 

defining characteristic. Hydrologic 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 Greater 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. 

. 
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Figure 14-5. Oligotrophic Freshwater Wetlands Conceptual Ecological Model and 

associated performance measures 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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14-13 

Indicators for this defining characteristic are soil nutrients, surface water nutrients, 

periphyton community and vegetation mosaic (Figure 14-5). Performance measures have 

been developed for the Greater Everglades region that relate to these indicators. Total 

Phosphorus (TP) Concentrations in Soil relates to soil nutrients. Performance measures 

have been developed for both TP and TN concentrations in surface water and periphyton. 

Three Greater Everglades performance measures pertain to vegetation mosaic: 

1) Freshwater and Estuarine Vegetation Mosaics, 2) Marl Prairie Cape Sable Sparrow 

Habitat, and 3) Ridge and Slough 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 wetland 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 estuarine lagoons transition along gradients 

of elevation, substrate, hydropattern, fire and 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 have been developed for the 

Greater Everglades for nutrient inputs and altered hydrology. Two broad ecological 

functions of the Everglades at the total system, biodiversity and foraging options for 

mobile vertebrates, are indicators for 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 distribution to specific landscapes or habitats. Examples include the 

Cape Sable seaside sparrow breeding population (Pimm 1995) that are endemic to 

southern marl prairies and more than 100 plant species that have been reported from that 

landscape (Olmstead and Loope 1984). Multiple landscapes of sufficient size thus 

support a species richness for the 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 comprises approximately 850 species in 20 

associations across major South Florida landscapes. 

Upland landscapes strongly contribute to plant and vertebrate species richness in South 

Florida despite their limited spatial extent in comparison to wetlands. Rockland pine 

forests support 186 species of understory plant 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 greatest number of rare and threatened 

plants in South Florida, including 59 taxa (Gunderson 1994). Endemic vertebrates are 

concentrated in limited upland areas in comparison to more expansive wetlands, and 

vertebrate species that are represented by relatively small populations are more numerous 

in upland habitats (Robertson and Frederick 1994). 
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Figure 14-6. Complex Landscape Mosaics and Interactions Conceptual Ecological 

Model and associated performance measures 
14.0 Total System CERP-Specific Conceptual October 17, 2007 

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14-15 

Several performance measures have been developed that can be used to track biodiversity 

during CERP implementation. Within the Greater Everglades region, measures have been 

developed for the following wetland landscape patterns: freshwater and estuarine 

vegetation mosaics, marl prairie Cape Sable seaside sparrow habitat, ridge and slough 

community, and tidal creeks. Measures have been developed for vegetation mosaics 

within Lake Okeechobee. Northern and Southern 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 choices” 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 short-hydroperiod wetlands, such as southern marl 

prairies, to be followed by a succession of favorable foraging 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 has been developed for wading bird foraging 

patterns in the Greater Everglades region. 

14.6 Summary of Total System Performance Measures 

As mentioned in the introduction to this section, most indicators within this model are 

covered by performance measures developed for the regions. Exceptions to this are 

measures for snail kite and white tail deer, which is a surrogate for the Florida panther. A 

performance measure has also been developed for system-wide mercury but it is not 

linked to this or any other conceptual ecological model. The CERP Monitoring and 

Assessment Plan: Part 1, Monitoring and Supporting Research (RECOVER 2004) does 

contain a South Florida Mercury Bioaccumulation 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 

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14.7 References 

Ashton, R.E. and P.S. Ashton. 1988. Handbook of Reptiles and Amphibians of Florida, 

Parts 1-3. Windward Publishing, Miami, FL. 

Beier, C., F. Moldan and R.F. Wright. 2003. Terrestrial ecosystem recovery – modeling 

the effects of reduced acidic inputs and increased inputs of sea-salts induced by 

climate change. Ambio 32:275-282. 

Browder, J.S. 1984. Wood stork feeding areas in southwest Florida. Florida Field 

Naturalist 12:81-96. 

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Frederick, P.C. and M.G. Spalding. 1994. Factors affecting reproductive success of 

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River Lagoon and Adjacent Waters, Florida. Harbor Branch Foundation, Fort 

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Gunderson, L.H. 1994. Vegetation of the Everglades: determinants of community 

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progress report. Proceedings of Annual Conference Southeastern Association of 

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the water conservation areas of the Everglades. Pages 585-614 in Davis, S.M. and 

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Delray Beach, FL. 

Holling, C.S., L.H. Gunderson and C.J. Walters. 1994. Vegetation of the Everglades: 

determinants of community. Pages 741-576 in S.M. Davis and J.C. Ogden (eds.), 

Everglades, the Ecosystem and its Restoration. St. Lucie Press, Delray Beach, FL. 

Hurley, L.M. 1991. Submerged aquatic vegetation. Pages 2-1 to 2-19 in Funderburk, 

S.L., J.A. Mihurshy, S.J. Jordan and D. Riley (eds.) Habitat Requirements for 

Chesapeake Bay Living Resources. Chesapeake Resource Consorium, Inc., 

Solomons, MD. 

Iverson, E.S. and D.S. Tabb. 1962. Subpopulations based on growth and tagging studies 

of spotted seatrout, Cynoscion nebulosus, in Florida. Copeia 1962:544-548. 
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Joanen, T. 1969. Nesting ecology of alligators in Louisiana. Proceedings of the Annual 

Conference of the Southeastern Association of the Game and Fish Commission 

23:141-151. 

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 Everglades 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, Washington, DC. Open File Report 75-434. 

Kushlan J.A. and M.S. Kushlan. 1979. Observations on the crayfish in the Everglades, 

Florida, USA. Crustacea, supplement 5:115-120. 

Kushlan, J.A. and T. Jacobsen. 1990. Environmental variability and the reproductive 

success of Everglades alligators. Journal of Herpetology 24:176-184. 

Lewis, F.G. III. 1984. Distribution of macrobenthic 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 control 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 Florida. 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. Biological 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 anthropogenic 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. Proceedings and Conclusions for the Submerged 

Aquatic Vegetation Initiative and the Photosynthetic Active Radiation 
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Workshops. St. Johns River Water Management District, Palatka, FL. Special 

Publication SJ93-SP13. 

Ogden, J.C. 1978. Recent population trends of colonial 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. National 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, Washington, D.C. Natural Resources Report 

16. 

Ogden, J.C. and J.C. Zeiman. 1977. Ecological aspects of coral reef-seagrass bed 

contracts in the Caribbean. Pages 377-382 in Proceedings of the Third 

International Symposium on Coral Reefs, University 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/recover/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.), Environments 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 Assessment Plan: Part 1 Monitoring and 

Supporting Research. Restoration Coordination 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. 
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RECOVER. 2006. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment 

Strategy for the MAP, Final Draft. Restoration Coordination 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. 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 importance of the Everglades watershed. 

Estuaries 22:398-416. 

Rudnick, D.T., P.B. Ortner, J.A. Browder and 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 Research Center, Everglades National Park, 

Homestead, FL. Report T-668. 

Rutherford, E.S., E.B. Thue and D.G. Buker. 1983. Population Structure, Food Habits, 

and Spawning Activity of Gray Snapper, Lutjanus griseus, in Everglades National 

Park. South Florida Research Center, Everglades National Park, Homestead, FL. 

SFRC-83/02. 

Schmidt, T.W. 1989. Food habits, length-weight 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 within 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. 
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Virnstein, R.W., P.S. Mickkelson, K.D. Cairns and M.A. Capone. 1983. Seagrass beds 

versus sand bottoms: the trophic importance of their associated benthic 

invertebrates. Florida 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. Electrophoretic investigation of subpopulations 

of the spotted seatrout, Cynoscion nebulosus (Cuvuer), in the Gulf of Mexico and 

Atlantic coasts of Florida. Comprehensive Biochemical Physiology 54B:97-102. 

Wilkinson, P.M. 1983. Nesting Ecology of the American Alligator in Coastal South 

Carolina, Study Completion Report. August 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 performance measures are initiated within Evaluation 

Team regional subteams and Assessment Team module teams based on their needs for 

evaluating or assessing CERP success. The Evaluation Team has four regional subteams - 

Greater Everglades, Southern Estuaries, Northern Estuaries and Lake Okeechobee - and a 

subteam for water supply and flood protection - Lake Okeechobee Service Area/Lower 

East Coast Service Area. The Assessment Team has module teams (referring to modules 

in the CERP Monitoring and Assessment Plan documents [RECOVER 2004, 2006]): 

Greater Everglades, Southern Estuaries, Northern Estuaries and Lake Okeechobee. Any 

participant in RECOVER can propose 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 work 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 module 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 Assessment 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, the documentation sheet will be reposted and 

the notation on the website will be changed to “accepted” and the date added. If 

comments can not be easily addressed or a controversy develops, the performance 

measure will not be deemed “acceptable”. Instead it will stay “under development” until 

issues are resolved. 

An email with links to accepted performance measures, 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 include 1) regional evaluations conducted by 

the Evaluation Team, 2) development of project-level performance measures by project 

teams, 3) development of assessment protocols 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 Assessment Plan: Part 1 Monitoring and 

Supporting Research. Restoration Coordination 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. Restoration Coordination 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. December 2006. 

http://www.evergladesplan.org/pm/recover/recover_map.aspx 
16.0 Uncertainty Associated with Performance Measure Application October 17, 2007 

16-1 

16.0 Uncertainty Associated with Performance Measure Application 

The Everglades ecosystem is complex and our understanding of its physical and 

biological processes, organizations and functions is incomplete so uncertainty is 

common. In general, uncertainty refers to a degree of dissatisfaction of some knowledge 

and expectations (Breckling and Dong 2000). A subject is uncertain when it is not exactly 

known or determined, or can not be reliably 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 uncertainty; 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 characterizing uncertainty in models is to identify 

a probability distribution of errors in model output based on field data. Inferential 

statistics can then be used to define confidence intervals, and a threshold level of risk can 

be assigned. When possible and appropriate, this method should be used and statistics 

should be documented. However, this method 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) categorized uncertainty 

into two main types: epistemic and linguistic uncertainty. These two types are discussed 

in the following paragraphs. 

Epistemic uncertainty is associated with knowledge of the state of a system. It includes 

uncertainty due to limitations of measurement devices, insufficient data, extrapolations 

and interpolations, and variability over time or space. A main epistemic uncertainty for 

CERP pertains to hydrological and ecological 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 of 
16.0 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, context dependence, ambiguity, indeterminacy 

of theoretical terms, and under specificity. All of these uncertainties arise in both natural 

and scientific language. Restoration efforts involve a multidisciplinary approach 

incorporating many scientific, engineering, sociological, economic and other disciplines. 

Inconsistency exists among vocabularies of these disciplines. Meaning of words evolves 

as restoration proceeds and they evolve among people at different rates. While 

RECOVER works hard to reduce linguistic uncertainty, we recognize that 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 complementary 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. Numerical estimates are exact numbers or ranges of numbers. In 

plan evaluations, quantitative projections are compared against the target number to assist 

in selecting the best alternative. 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 reasonably assumed to be consistent and thus cancelled 

in comparisons, they would not influence rank 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 directional 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, uncertainty is a determining factor in deciding 

whether we need to focus on maximization of benefits or minimization 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 leading to homogenization and loss of natural 

variation. For example, timing of seasonal processes and spatial configuration of 

biological communities are important components of ecosystem health and integrity. 

Using yearly average will totally miss seasonal timing, and using seasonal averages 

cannot help much in restoration of natural timing. A small error in timing can lead to a 

large rounding error, such as a change in month when monthly average data are used. In 

the same light, selection of spatial regime also 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 threshold 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 information, including professional judgments, 

into a formal organized framework, and generate logical, quantitative projections 

according to given assumptions. Common assumptions in hydrologic planning include 

those about climate condition, water control structures and water control operations. 

Model projections based on these assumptions can be compared quantitatively to evaluate 

consequences of these assumptions in terms of specific performance measures. Thus, 

model projections are extremely useful for scenario selection. 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. Because models have formal structures, 

they also allow people to evaluate and characterize uncertainty explicitly and 

quantitatively. 

Models are simplified, quantitative representations of real systems. Models are usually 

comprised of state variables and mathematical equations linking state variables. State 

variables describe state or conditions of system components, which often are issues in 

decision-making and management. Equations usually have specific functional forms and 

contain some prefixed numbers. These numbers 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 questions and to support different performance 

measures. Uncertainty varies with questions, because different parts of model output vary 

in sensitivity to uncertainty sources and different 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 have at least four potential sources: ignorance, errors, 

stochasticity and inherent unpredictability. 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-technical considerations. Many interactions and 

environmental factors are ignored in models. Usually only variables of primary interest 

are included. In models, all ignored influences are implicitly represented by parameters 

and functional forms thus assumed constant. When 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 models, specification of 

boundary and initial conditions, and computational procedures caused by epistemic 

constraints, mismatches of model representations and field observations, and mismatches 

of spatial and temporal scales. Note that errors and bias from one source could propagate 

and amplify through model structure, and lead to both qualitative and quantitative 

uncertainties in modeling outcomes (Gardner et al. 1980). Model parameters for three 

classes of models - hydrologic, biogeochemical and ecological - vary and each has an 

associated level of uncertainty. In general, state-based parameters (e.g., water stage, 

abundance of organisms) perform better than rate-based parameters (e.g., water flow, 

productivity). Parameter error consequences can be analyzed via a technique called 

“uncertainty analysis”. Nevertheless, complete, quantitative consequence characterization 

of all errors and their interactions is difficult. 

Many model parameters are inherently stochastic. 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 chaos 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 the system quickly through time. 

USimple versus Complex Models

Different types of models exist. Some are simple and some are complex. Trade-offs exist 

among different types of models with respect to uncertainty. For example, simple models 
16.0 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 variables into models, making them more complex. 

Complex models contain more parameters and other specific details. They represent more 

specific information, and thus they are more realistic. However, data requirement grow 

very fast to avoid potential bias in parameter estimation, and potential errors in 

identification of functional formula and interplay of these errors increase quickly with the 

level of complexity. Such kinds of errors and biases may bring about a large uncertainty 

in model outcomes. Gardner et al. (1980) found that complex ecological models usually 

amplify parameter errors. 

Further, with simple models, analytical solutions exist, which provide a convenient base 

for statistics. Statistics can provide measures of stochasticity. It is very difficult to find 

analytical solutions for complex models. Thus, 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 predict better (Gauch 1993). Disagreement exists 

among modelers in favor of simple versus complex models. Given a specific question, an 

optimal level of complexity may be reached (Costanza and Sklar 1985, Hilborn and 

Mangel 1997). 

Classes of Models: Hydrologic, Biogeochemical and Ecological

Three classes of models are used to support CERP planning: 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 structural 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 the relationship between hydrologic models and biogeochemical 

and ecological models. Hydrologic model output is usually used as an input parameter for 

both ecological and biogeochemical models. This linkage can lead to error propagation 

and magnification due to initial error in hydrologic 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. Hydrologic, 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, groundwater system, and interactive surface watergroundwater system. Water elevation is a common, focal-state variable for all of these 

models. Among them, the South Florida Water 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 ecological 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 sources 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. Some are spatially explicit and some are not. 

Focal-state variables and spatial domains also vary. Some simulate phosphorus, and some 

simulate other chemicals, including metals. Some models simulate biogeochemical 

dynamics, using hydrologic model output as input, and some have their own hydrologic 

engines. Most of these models are still under development or still require peer review. 

Characterization and documentation of uncertainty 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 characterize uncertainty of 

this group of models. In general, biogeochemical 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 diverse group of tools. They can simulate 

ecosystem processes, focus on community dynamics, investigate population changes, or 

present landscape patterns and processes. Some models are deterministic; some 

stochastic. They are spatially explicit or spatially 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 different models suggest opposite directions, 

uncertainty needs to be identified and analyzed. 
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When each ecological model or tool is evaluated alone, uncertainty level is usually high 

because of trade-off of various kinds of uncertainty, 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 ecological tools are hydrologic suitability indices. This group 

includes habitat suitability indices (HSIs) and spatially-explicit suitability indices (SESI). 

These tools are extremely simplified presentations of hydrologic-ecologic links. They are 

so simplified that they do not contain state variables of ecological entities, and therefore 

do not really simulate ecological interactions. They assume that ecological processes and 

ecological history are unimportant and thus can be ignored. Often, a hydrologic surrogate 

is used as an ecological index. Simplicity allows 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, uncertainty from hydrologic model output will 

propagate in computation and propagation can be tracked. For example, averaging and 

aggregation of indices can lead to additional uncertainty. Averaging across a period of 

time is sensitive to uncertainty generated by ignorance of history leading to 

underestimation or under representation in indices of chronic effects of ecological 

disasters and damages. Ecological systems typically 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 presentation, and loose link between the indices and 

field measurements, makes uncertainty evaluation 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, but often leads to scale mismatch. 

Simulation models are more realistic presentations. They allow key ecological processes 

to be represented and are extremely useful and can complement simple indices. Some 

ecological simulations are complex, and ecological 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 and stochasticity, and 

nonlinear error propagation. Due to the complexity 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 communication between modelers and model users 

adds another barrier and difficulty to the uncertainty issue. Documentation needs to be 

clear, complete and easy to read. When simulation output is used in decision making, 

caveats provided in the documentation need to be considered. 
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16.5 Dealing with Uncertainty 

Factors Increasing Uncertainty

Complex feedback among modeling, planning, operation, management and engineering 

design may cause uncertainty propagation, particularly in context of an evolving 

restoration project. Unexpected changes take place all the time. Local, regional, national 

and global environments change, and these changes are often beyond our control. Goals, 

objectives and constraints of projects sometimes 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 example, the SFWMM is now carrying out many 

jobs that had not been anticipated when the model was conceived. Some projects may 

change model boundary conditions. Some projects are covering areas outside model 

spatial domain. Some projects need information 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-term observations, are necessary to 

evaluate temporal and spatial 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 repertoire to estimate this uncertainty 

aspect. If repeated observations fail to follow presumed statistical 

distributions, inherent instability 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 processes 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 point 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 results trying to simulate the same 

thing and are a good indicator of uncertainty; therefore having multiple 

models simulating the same thing is desirable. For example, in 

hurricane track predictions, multiple models are used to lend 
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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 potential phase transitions and 

hysteresis effects. In nonlinear dynamical systems, state shift and 

hysteresis can occur. A small change of only one of the system 

parameters or a marginal external influence can cause dramatic 

changes of the whole system’s behavior and organization. Dramatic 

state change and hysteresis can bring about surprises and irreversible, 

undesirable consequences if ecologists ignore signals of nonlinear 

processes and structural instability (Carpenter et al. 1999, Dong et al 

2002). 2) Consider chaos (predictable unpredictability). Chaos 

prevents long-term predictions. Chaotic systems inherently increase 

small uncertainties to a macroscopic 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 with 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 sum 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 potential 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 accurate quantification 

of uncertainty are desirable, but often impractical. Nevertheless, 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 typically characterize outcomes of parameter uncertainty, but not 

influences of other uncertainties. Comparisons between model output and expert opinions 

and among outputs of different models are very useful in identifying inconsistencies and 

gaps for each performance measure. Resulting agreements and disagreements measure 

uncertainty. Consensus often increases confidence; disagreements indicate uncertainty, 

and sometimes provide clues of potential surprises. Opinions of independent peer reviews 

can present the degree of satisfaction and dissatisfaction, thus are a measure of 
16.0 Uncertainty Associated with Performance Measure Application October 17, 2007 

16-10 

uncertainty. Results of uncertainty and sensitivity 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 process 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 often 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. Ecological 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 hydrological alterations. We need to minimize 

potential future regret caused by insufficient restoration. 

Planners should always consider potential failures in advance, use the Adaptive 

Management Strategy (RECOVER 2006), and follow precautionary principles. The 

Adaptive Management Strategy allows performance measures, quantitative tools and 

project plans to evolve with new information and monitoring feedback. As CERP is 

implemented, the Everglades ecosystems also will evolve. Monitoring projects will detect 

newly emerging processes and developments. Concerns of uncertainty are also context 

dependent, and may vary in different situations. Planning and decision-making will be a 

continuous optimization process that continuously 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 restoration is to minimize human intervention and 

control. Restoration decisions should attempt to minimize interventions, 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, overemphasis of quantitative uncertainty in ecology 

would put overdue burden on ecological studies that often require long-term data. 

For CERP decision-making, critical uncertainties include quantification of ecological 

benefits, apparent conflicts among species and ecosystem components, nature-society 

conflicts, and conflicts among interest groups. It is a great challenge to reduce these kinds 

of uncertainties. 
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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. Management of eutrophication for 

lakes subject to potentially irreversible change. Ecological Applications 9: 751-

771. 

Costanza, R. and F. H. Sklar. 1985. Articulation, accuracy, and effectiveness of 

mathematical models: a review of freshwater wetland applications. 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'Neill, R.V.; Mankin, J.B.; Kumar, D. 1980: 

Comparative error analysis of six predator-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 detective 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. Burgman. 2002. A taxonomy and treatment of 

uncertainty for ecology and conservation biology. Ecological Applications, 

12(2):618-628. 

RECOVER. 2002. Model Uncertainty Report. Restoration Coordination 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_docs/et/052402_mrt_uncertainty_re

port.pdf

RECOVER. 2006. Comprehensive Everglades Restoration Plan Adaptive Management 

Strategy. Restoration Coordination and Verification Program, c/o United States 
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Army Corps of Engineers, Jacksonville District, Jacksonville, Florida. April 2006. 

http://www.evergladesplan.org/pm/recover/recover_docs/am/rec_am_stategy_bro

chure.pdf
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17.0 Next Steps 

RECOVER has identified needs to improve performance measure development and 

application. Each section below gives a brief 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 meaningfulness of performance 

measures. 

17.1 Future Evaluation Tools 

At present, evaluation components of CERP system-wide performance measures are 

highly dependent on hydrologic 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. Also, we need water quality and ecological 

models/tools to evaluate and assess performance measures. 

The South Florida Water Management District (SFWMD) is developing the Regional 

Simulation Model (RSM). This model is a regional hydrologic model designed to 

simulate coupled movement of groundwater and surface water in South Florida. Major 

benefits of the RSM include increased resolution 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 development can be found at the following 

web site: Twww.sfwmd.gov/site/index.php?id=342UT. 

In an effort to identify models currently used to evaluate RECOVER performance 

measures, as well as unmet model needs, three classes of existing models were 

investigated: 1) hydrologic, hydraulic and hydrodynamic, 2) biogeochemical or water 

quality, and 3) ecological. Several major shortcomings were recognized: 1) RECOVER 

lacks easily applicable ecological models; 2) RECOVER lacks peer reviewed, regionalscale water quality models; and 3) RECOVER lacks 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/recover/system_wide_modeling.aspx. Additionally, 

evaluation and assessment tool needs are identified directly on performance measure 

documentation sheets posted on the web at 

http://www.evergladesplan.org/pm/recover/eval_team_perf_measures.aspx. 

Efforts are ongoing to refine and develop future tools to evaluate ecological responses to 

varying project alternatives. Habitat suitability indices (HSIs) and Across Trophic Level 

System Simulation (ATLSS) spatially-explicit species index (SESI) models have 

potential, but require further calibration, validation and/or peer review before application. 

SESI models exist for American alligator, snail kite, apple snail, wading birds, and white 

tailed deer. In addition to SESI models, ATLSS models include those for fish (ALFISH 

and ALFISHES) and sparrows, as well as high-resolution topography and hydrology 

models. 
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Similarly, water quality models are needed to simulate nitrogen and phosphorus 

dynamics. In the absence of applicable water quality models, regional evaluations will 

use water quality proxies such as duration and intensity of dry down, structural flows, and 

stormwater treatment area bypasses (frequency and volume). These proxies should 

refined in the short term to make them more quantitative until appropriate water quality 

models are available. Several water quality 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 (GUI). A GUI will facilitate 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 varying project alternatives. This is the result 

of low resolution of model input variables, 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 measurements and lack of field measurements 

altogether throughout the system. Current measuring 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 measurements 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/regressions from known depths. With increased 

monitoring and assessment activities and increased sensitivity of measurement tools will 

come the ability to reduce uncertainty associated 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 projects within the domain. 

The SFWMM was originally used to compare alternative plans during the Restudy (see 

Section 6.1 and Appendix D for more detailed discussion of the Restudy and Appendix 

D. On this broad scale, which contained all CERP projects, the SFWMM was very 

effective at understanding system-wide effects. When the selected 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 may 
17.0 Next Steps October 17, 2007 

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cross several habitat types including ridge and 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 effective 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 approximately 7 feet, or 2.1 inches per mile, 

across the 40-mile transect. To determine effects of individual or smaller groups of 

projects, increased sensitivity will be required. 

Disconnect between timing and distribution of field measurements (and performance 

measure inputs) and optimal timing of the SFWMM can cause additional problems with 

sensitivity. Many field measurements, such as those taken at water management 

structures, are taken at scales of seconds to minutes or hours, whereas SFWMM functions 

more appropriately on longer time-steps. This disconnect between resolution of field 

measures and resolution needed for model inputs can cause problems with performance 

measure model coding as well interpretation of model outputs. Stronger 

synchronization/standardization between field 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/standardize 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 alternative plans. Without these technical 

processes, we have no objective way of determining whether or not a difference in 

indicator response exists between alternatives. 

Performance measure sensitivity analysis is required 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 evaluative 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 measure metric, to the model used, or if the 

problem can actually be attributed to project design. 
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Each performance measure needs to be calibrated and validated. This will allow us to 

determine if the performance measure is accurately representing the real-world variable, 

will allow improvement of models, and will achieve a more accurate evaluation of actual 

project effects. 

17.4 Less Reliance on Model-Based Targets 

Currently, RECOVER relies upon regional hydrologic models to simulate alternative 

project plans and represent the pre-drainage Everglades. Supplemental models simulate 

runoff from the Caloosahatchee and St Lucie Estuaries and canal discharges. 

Dependence on models, especially the NSM, to simulate the pre-drainage Everglades 

began early in the Restudy process. NSM describes conditions prior to human alteration. 

These conditions are not fully known or understood. NSM completed a picture only 

partially described by research. It was corroborated by historical 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 period of record (31-36 years), greater reliance 

on independently identified (empirically-based) targets is sought. 

The model-independent approach has several other advantages. Such an approach can be 

more consistent in developing and reviewing 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 refined with new data and information without 

the additional step of incorporating them into a computer model. No longer would 

scientists need to explain performance of models, only support identified targets. 

Additionally, consensus on restoration targets would become the goal instead of 

defaulting to model-based targets. 

17.5 Refinement of Evaluation-Assessment Feedback Loop 

One component of the Adaptive Management 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 ecological relationships, the 

ability to make measurements more precise will provide increased sensitivity. This 

ongoing feedback between evaluation and assessment functions will help to identify 

knowledge/data gaps and focus monitoring and assessment activities. 
17.0 Next Steps October 17, 2007 

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17.6 Future Performance Measures 

The current set of performance measures does not include critical components of CERP 

restoration such as spatial extent and ecological 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 Connectivity 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 Everglades and has resulted in reduced 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, landscape 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 number of exotic species that 

have been introduced is eight times the total number 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 (Doren and Ferriter 2001). One species alone, 

Old World climbing fern, has spread exponentially 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 species by exotics can potentially cause 

irreversible alterations in ecological community structure and function by altering fire 

regime, surface water flow, salinity, water quality, primary productivity and food web 

structure, to name a few. Given current 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 planning and research. The Assessment 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, Havens 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 effects on important ecosystem attributes. 
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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 consistent 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 includes the Atlantic Multi-decadal Oscillation, 

El Nino/El Nina, Sahel drought, and tropical storm impact. These factors will have to be 

considered during CERP assessments, evaluations 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 targets were developed as separate efforts. 

While they were based on the same underlying information, there are inconsistencies 

between them. These inconsistencies need to be eliminated. The RECOVER Team’s 

Recommendations for Interim Goals and Interim 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/recover/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 Model. Wetlands 25(4):854-869. 

http://www.evergladesplan.org/pm/recover/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/recover/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/recover/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. 
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17-7 

http://www.evergladesplan.org/pm/recover/recover_docs/cems/cem_eg_mangrov

e.pdf

Doren, R.F. and A.P. Ferriter (eds.). 2001. Weeds 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 ecosystem conceptual ecological model. 

Wetlands 25(4):843-853. 

http://www.evergladesplan.org/pm/recover/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, South 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/recover/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/recover/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/recover/recover_docs/cems/cem_total_system.

pdf

RECOVER. 2004. CERP Monitoring and Assessment Plan: Part 1 Monitoring and 

Supporting Research. Restoration Coordination 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 Recommendations for Interim Goals and 

Interim Targets for the Comprehensive Everglades Restoration Plan. Restoration 

Coordination and Verification Program, c/o United States Army Corps of 

Engineers, Jacksonville District, Jacksonville, 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 Tools, Models, Work Plan, and Budgets. 

Model Needs Subteam, Restoration Coordination 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 Management District, West Palm Beach, FL. 

http://www.evergladesplan.org/pm/recover/system_wide_modeling.aspx. 

RECOVER. 2006b. Monitoring and Assessment Plan (MAP), Part 2, 2006 Assessment 

Strategy for the MAP, Final Draft. Restoration Coordination 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. December 2006. 

http://www.evergladesplan.org/pm/recover/recover_map.aspx 

RECOVER. 2006c. Comprehensive Everglades Restoration Plan Adaptive Management 

Strategy. Restoration Coordination and Verification Program, c/o United States 

Army Corps of Engineers, Jacksonville District, Jacksonville, Florida. April 2006. 

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chure.pdf

Rudnick, D.T., P.B. Ortner, J.A. Browder and S.M. Davis. 2005. Florida Bay conceptual 

ecological model. Wetlands 25(4):870-883. 

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df

Sime, P. 2005. St. Lucie Estuary and Indian River Lagoon conceptual ecological model. 

Wetlands 25(4):898-907. 

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df

Stein, B.A., L.S. Kutner and J.S. Adams (eds.). 2000. Precious Heritage, the Status of 

Biodiversity in the United States. Oxford University Press, Oxford, UK. 

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ecological model. Wetlands 25(4):926-942. 

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pdf
Appendix A – Models Used with Performance Measures October 17, 2007 

 to Evaluate Alternative Plans 

A-1 

Appendix A. U Models Used with Performance Measures to Evaluate 

Alternative Plans 

RECOVER currently uses the South Florida 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, South Florida Regional Simulation Model 

(SFRSM), and the Everglades Landscape Model (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, and runoff and demands in Caloosahatchee 

River and St. Lucie Canal basins. The large scale and spatial extent of the model allows it 

to simulate system-wide effects. 

The model simulates major components of South Florida’s hydrologic including rainfall, 

evapotranspiration, infiltration, overland and groundwater flow, canal flow, canalgroundwater seepage, levee seepage 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 basis using climatic data for the 1965-2000 

period, which includes both drought and wet periods. 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 analyzing regional-scale structural and/or 

operational changes to the complex water management system in South Florida. 

Parameter uncertainty is estimated running a series of SFWMM simulations using 

historic flows assigned at major control structures where reliable flow records exist. 

Parameters are incrementally varied one at a time from original calibrated parameters to 

estimate the 90% certainty band for each parameter. Compartmentalization of South 

Florida’s hydrologic system by structures and 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 applied 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 variation 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 uncertainty was made with version 2.4 of the 

SFWMM. Structural flows were estimated based 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 calibration version (historical flows 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 evapotranspiration. These types of uncertainty can be 

reduced by considering 1) regional 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 simulated 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, simulated performance measure uncertainty 

associated with the SFWMM is estimated by replacing 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 considering 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 performance measures is caused by such factors as 

natural climate variability, 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 simulate pre-drainage hydrology, since input data 

necessary to perform such a simulation do not exist. Rather, more recent climatic data is 

used to simulate pre-drainage hydrologic response to current hydrologic input. Use of 

recent data allows for meaningful comparisons between the current managed system and 

the natural system under identical climatic conditions. 

The landscape of present day South Florida 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 levees in the current system 

are replaced in the NSM with rivers, creeks and 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 (version 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, model parameters are based on the SFWMM. 

Lake Okeechobee Water Quality Model 

The LOWQM simulates average, lake-wide phosphorus, nitrogen and phytoplankton 

concentrations. It simulates eutrophication processes in both the water column and 

underlying sediments (James et al. 1997). It can be applied to SFWMM’s simulations, but 

because observed water quality data for Lake 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-wide 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 level, 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 hydrodynamic, 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 submerged aquatic plants. It is anticipated that 

the LOEM will more accurately simulate impacts 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-scale information, but can be 

used for long-term (decades or even centuries) 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 operational alternatives designed to address 

changing water management priorities and issues. 

The SFRSM is being developed using recent advances in computer technology, in 

particular, geographic information systems (GIS), databases, and object-oriented model 

development. The new SFRSM will also make use of more realistic, accurate and 
Appendix 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 searching for ways to improve 

them or develop new ones. 

The SFRSM is a component-based model. It will be an assembly of different components 

that can be swapped in and out as the model 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 the SFRSM are overland and groundwater flow, 

precipitation, evapotranspiration, infiltration, levee seepage and canal and structure flow. 

Four major project components are being developed 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, including operation of the C&SF Project 

• Graphical User Interface (GUI) - a simple, easy to use tool for 

graphically setting up a SFRSM model and interpreting its results 

• DataBase (DB) - a convenient storage and retrieval facility of SFRSM 

data 

Across Trophic Level Simulation System Models 

ATLSS models integrate three approaches for different trophic levels of the system: 

1) process models for lower trophic levels, including benthic invertebrates, 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, American alligator, white-tailed deer and Florida 

panther. Models are integrated across freshwater landscapes of the Everglades and Big 

Cypress Swamp and coupled to GIS maps for cover type. Spatial scales of resolution for 

models are as small as 100 meters, with the capability to vary this based upon scale of 

available input data. The system is then coupled to a hydrology model, and used to assess 

effects of alternative proposed restoration scenarios on trophic 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 distributed simulation of ecosystem dynamics 

across a heterogeneous landscape at a grid resolution 10 times finer than the SFWMM 
Appendix 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 interacting physical, chemical and biological 

processes. Hydrology and water quality are two principal “landscape drivers” that are 

simulated in the ELM. Because of uncertainty 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 fundamental ecological processes in a changing 

environment. Important to ELM functionality are positive and negative feedbacks among 

these fully-integrated ecological 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 the uncertainty of historical simulations of 

water quality observations was sparse model input data on nutrient loads. Applications of 

ELM and other models should be based on relative performance of alternative scenarios, 

not on precise results at specific spatial or temporal locations. 

A peer review of ELM version 2.5 was completed in January 2007 (Mitsch et al. 2007). 

The model has been approved for limited use 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 Everglades water quality performance measures. 

Literature Cited 

Fitz, H.C. and B. Trimble. 2006a. Documentation of the Everglades Landscape Model: 

ELM v2.5. South Florida Water Management District, West Palm Beach, FL. 

Fitz, H.C. and B. Trimble. 2006b. Documentation of the Everglades Landscape Model: 

ELM version 2.5, Overview of the Full Report. 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 Okeechobee. 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. 2002. Modeling winter circulation 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: modeling of sediment transport 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. Cerco. 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 Version 4.5 Documentation Report. South 

Florida Water Management District, West Palm Beach, FL. 
Appendix B – Crosswalk of Performance Measures 

B-1 

Appendix B. U Crosswalk of Performance Measures 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

Lake Okeechobee 

LO-E1 Lake Okeechobee Extreme Low Lake Stage 

LO-A1 Lake OkeechobeStage 

LO-E3 Lake Okeechobee Extreme High Lake Stage 

LO-A3 Lake OkeechobeStage 

Lake Okeechobee Lake Stage 

LO-E10 Lake Okeechobee Stage Envelope LO-A21 Lake OkeechobLO-E6 Lake Okeechobee Total Phosphorus Concentrations 

LO-A14 Lake OkeechobConcentration 

LO-5 Lake Okeechobee Phosphorus Loads LO-A19 Lake OkeechobLO-E7 Lake Okeechobee Total Nitrogen:Total Phosphorus Ratio 

LO-A15 Lake OkeechobNitrogen:Total Phosphor

LO-E9 Lake Okeechobee Algal Bloom Frequency 

LO-A17 Lake OkeechobFrequency 

LO-9 Lake Okeechobee Water Clarity LO-A18 Lake Okeechob

Lake Okeechobee Water Quality 

LO-10 Lake Okeechobee Class I Water Quality Parameters 

LO-A20 Lake OkeechobQuality Parameters 

Lake Okeechobee Diatom:Cyanobacteria Ratio 

LO-E8 Lake Okeechobee Diatom:Cyanobacteria Ratio 

LO-A16 Lake OkeechobDiatom:Cyanobacteria R

Lake Okeechobee Vegetation Mosaic 

 LO-A6 Lake Okeechobe

Mosaic - Littoral Plant CBulrush LO-A7 Lake OkeechobeMosaic – Submerged Aq
Appendix B – Crosswalk of Performance Measures 

B-2 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

Lake Okeechobee Fish Population Density, Age Structure, and Condition 

 LO-A11 Lake Okeechob

Density, Age Structure, 

LO-16 Lake Okeechobee Macroinvertebrates 

 LO-A8 Lake Okeechobe

Fauna (Fish and Inverteb

Northern Estuaries Northern Estuaries Salinity NE-E1 St Lucie Estuary Salinity Envelope 

NE-E2 Lake Worth Lagoon Salinity Envelope NE-E3 Caloosahatchee Estuary Salinity Envelope

NE-E4 Loxahatchee River Estuary Salinity Envelope 

NE-A1 St. Lucie Estuary NE-A2 Lake Worth LagNE-A3 Caloosahatchee EEnvelope NE-A4 Loxahatchee RivEnvelope 

Northern Estuaries Water Quality NE-A11 St. Lucie Estua

TN) Loading and ConceNE-A14 Lake Worth Laand TN) Load and ConcNE-A10 Caloosahatchee and TN) Loading and CoNE-A13 Loxahatchee Ri(TP and TN) Load and CNE-A12 South Indian R(TP and TN) Load and CNE-A16 Northern Estua(Toxicants and PathogenNE-A17 Northern EstuaNE-A15 Northern EstuaFrequency 
Appendix B – Crosswalk of Performance Measures 

B-3 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

Northern Estuary Oyster Habitat NE-A5 Northern Estuary Northern Estuaries Benthic Macroinvertebrates 

 NE-A6 Northern Estuari

Macroinvertebrates 

Northern Estuaries Fish Communities 

 NE-A7 Northern Estuari

Northern Estuaries Submerged Aquatic Vegetation 

 NE-A8 Northern Estuari

Aquatic Vegetation 

Greater Everglades Sheet Flow in Everglades Ridge and Slough Landscape Wet Prairie Number and Duration of Dry Events for Shark River Slough 

GE-E1 Number and Duration of Dry Events for Shark River Slough 

GE-A1 Greater EvergladHydropattern 

Inundation Pattern in Greater Everglades Wetlands 

GE-E2 Inundation Pattern in Greater Everglades Wetlands 

GE-A1 Greater EvergladHydropattern 

Extreme High and Low Water Levels in Greater Everglades Wetlands 

GE-E3 Extreme High and Low Water Levels in Greater Everglades Wetlands 

GE-A1 Greater EvergladHydropattern 

Greater Everglades Wetlands Total Phosphorus (TP) Concentrations in Surface Water 

GE-E7 Greater Everglades Wetlands TP Concentrations in Surface Water 

GE-A14 Greater EverglaNutrient Concentrations 

Greater Everglades Wetlands Basinwide TP Loading and FlowWeighted Mean Concentration in Inflows 

GE-E8 Greater Everglades Wetlands Basinwide TP Loading; GE-E9 Greater Everglades Wetlands Basinwide TP Loading and Flow-Weighted Mean Concentration in Inflows 

GE-A19 Total PhosphorWeighted Mean Concenthe Greater Everglades 
Appendix B – Crosswalk of Performance Measures 

B-4 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

Greater Everglades Wetlands Nutrient TN Concentrations in Surface Water 

 GE-A14 Greater Evergla

Nutrient TN Concentrati

Total Nitrogen Loads/FlowWeighted Mean Concentration in Inflows to the Greater Everglades Wetlands 

 GE-A20 Total Nitrogen 

Weighted Mean Concenthe Greater Everglades W

Total Phosphorus Concentrations in Soil 

 GE-A15 Total Phosphor

Soil 

Greater Everglades Tracer of STA Bypass flows 

GE-E10 Tracer of STA Bypass flows 

Greater Everglades Wetlands Sulfate Concentrations in Surface Water 

 GE-A16 Greater Evergla

Concentrations in Surfac

Greater Everglades Wetlands Conductivity in Surface Water 

 GE-A17 Greater Evergla

Conductivity in Surface 

Greater Everglades Wetlands Coastal Salinity Gradients 

 GE-A12 Greater Evergla

Salinity Gradients 

Wetland Landscape Patterns – Freshwater and Estuarine Vegetation Mosaics 

 GE-A2 Wetland Landsc

Freshwater and Estuarin

Wetland Landscape Patterns - Marl Prairie Cape Sable Sparrow Habitat 

 GE-A5 Wetland Landsc

Prairie Cape Sable Sparr

Wetland Landscape Patterns - Ridge and Slough Community Sustainability 

GE-E6 Species Richness Suitability for Everglades Tree Islands GE-E14 Ridge and Slough Habitat Suitability Index; GE-E15 Tree Island Flooding/Drought Habitat Suitability Index 

GE-A3 Wetland Landscand Slough Community 
Appendix B – Crosswalk of Performance Measures 

B-5 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

Wetland Landscape Patterns - Tidal Creek Sustainability 

 GE-A4 Wetland Landsc

Creek Sustainability 

Wetland Trophic Relationships – Periphyton 

GE-E11 Periphyton Habitat Suitability Index GE-A10 Wetland Troph

Periphyton 

Wetland Trophic Relationships - Mangrove Forest Production/Soil Accretion 

 GE-A11 Wetland Troph

Mangrove Forest Produc

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

GE-E16 Fish Habitat Suitability Index GE-A6 Wetland Trophic 

Regional Populations of Grass Shrimp and Amph

Wetland Trophic Relationships – Wading Bird Foraging Patterns on Overdrained Wetlands 

GE-E20 Long-Legged Birds Foraging Conditions GE-E21 Short-Legged Birds Foraging Conditions

GE-A7 Wetland Trophic Wading Bird Foraging POverdrained Wetlands 

Wetland Trophic Relationships – Wading Bird Nesting Patterns 

GE-E13 Wading Bird Habitat Suitability Index GE-A8 Wetland Trophic 

Wading Bird Nesting Pa

Roseate Spoonbill Nesting Patterns GE-A18 Roseate SpoonbWetland Trophic Relationships - American Alligator Distribution, Size, Nesting and Condition 

GE-E12 Alligator Habitat Suitability Index GE-E23 Alligator Production Index 

GE-A9 Wetland Trophic American Alligator DistNesting and Condition 

American Crocodile - Juvenile Growth and Survival 

 GE-A13 American Croc

Growth and Survival 
Appendix B – Crosswalk of Performance Measures 

B-6 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

Southern Estuaries Southern Estuaries Salinity SE-E2 Frequency of Low Salinities and High 

Salinities in Florida Bay SE-E9 Whitewater Bay hydrology- Salinity Relationships Using Watershed Water Levels SE-E3 Freshwater Flow to Biscayne Bay from the Miami River SE-E4 Salinity Patterns in, and Timing of Freshwater Inputs to, Manatee Bay and Coastal Embayments of Barnes Sound SE-E5 South Biscayne Bay – Salinity Gradients 

along Western Shore of Biscayne Bay between Shoal Point and Turkey Point SE-E6 North Biscayne Bay – Surface Water Discharges to North Biscayne Bay to Preserve Existing Seagrass Communities SE-E7 Central Biscayne Bay – Surface Water Discharges from Snapper Creek Canal to maintain salinity in nearshore Biscayne Bay. SE-E8 Snake Creek Surface Water Discharges to North Biscayne Bay 

SE-A2 Southern EstuariSE-A1 Surface Water DBay 

Water Level at Regionally Significant Gauge Stations in Everglades National Park 

SE-E10 Water Level at Regionally Significant Gauge Stations in Everglades National Park 

SE-A3 Water level at reggauge stations in Evergla

Southern Estuaries Submerged Aquatic Vegetation 

 SE-A3 Southern Estuari

Aquatic Vegetation 
Appendix B – Crosswalk of Performance Measures 

B-7 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

Southern Estuaries Juvenile Pink Shrimp and Associated Epifauna 

 SE-A4 Southern Estuari

Shrimp and Associated E

Southern Estuaries Fish Community SE-A5 Southern Estuari

Community SE-A6 Florida Bay Juve

Southern Estuaries Water Quality SE-A9 Southern Estuari

Concentrations in SurfacSE-A10 Southern EstuarSE-A11 Southern EstuarSE-A12 Southern EstuarClarity/Light Penetration SE-E13 Contaminants (TPathogens) in Biscayne BCoastal Sediments 

Total System Snail Kite Foraging Conditions GE-E17 Apple Snail Reproduction 

GE-E18 Snail Kite Foraging Habitat Vegetation Structure 

White Tail Deer Breeding Potential (panther surrogate) 

GE-E22 White Tail Deer Breeding Potential (panther surrogate) 

Mercury Bioaccumulation TS-3 Mercury BioaccumWater Supply Frequency of Water Restrictions for the Lake Okeechobee Service Area 

WS-1 Frequency of Water Restrictions for the Lake Okeechobee Service Area 

Frequency of Water Restrictions for the Lower East Coast Service Area 

WS-2 Frequency of Water Restrictions for the Lower East Coast Service Area 
Appendix B – Crosswalk of Performance Measures 

B-8 

Current 

Performance Measure 

Former Evaluation 

Performance Measure 

Former As

Performanc

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

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

Prevent Saltwater Intrusion of the Biscayne Aquifer - Meet MFL Criteria for Biscayne Aquifer 

WS-4 Prevent Saltwater Intrusion of the Biscayne Aquifer - Meet MFL Criteria for Biscayne Aquifer 

Prevent Saltwater Intrusion of the Biscayne Aquifer in South MiamiDade County 

WS-5 Prevent Saltwater Intrusion of the Biscayne Aquifer in South Miami-Dade County 

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

WS-6 Comparison of Stage Differences of Water Levels in South Miami-Dade Agricultural Area 
Appendix 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 articulate the need to measure and evaluate 

system-wide response to CERP implementation. Performance measures provide tools to 

fulfill this need. Performance measures document 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 Comprehensive Plan as a framework and guide to 

modify the Central and Southern Florida (C&SF) Project. CERP’s scope, complexity and 

importance and the significant outlay of public funds necessary for implementation 

dictate the need to measure, assess and report progress towards achieving CERP’s 

objectives. Therefore, Section 601(b)(2)(C) of the WRDA 2000 gives specific 

authorization for an adaptive assessment and 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 Comprehensive Everglades Restoration Plan; 

Final Rule, which became effective on December 12, 2003 (DOD 2003), RECOVER is 

charged with “Developing proposed evaluation performance measures for evaluating 

alternative plans developed for the Project Implementation Report” (Section 

385.20(e)(2)(i)) and “Developing proposed assessment performance measures for 

assessing progress toward the goals and purposes of the Plan” (Section 385.20(e)(1)(i)). 

Guidance Memoranda 

Programmatic regulations require guidance 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 measures presented in this document follow 

principles and guidelines set forth by the Water Resources Council in accordance with 

Section 103 of the Water Resources Planning Act (Public Law 89-80) and Executive 
Appendix 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 “the net quantity and/or quality of desired ecosystem 

resources.” National ecosystem restoration is determined by measuring improvement in 

habitat quality and/or quantity. The United States Army Corps of Engineers developed 

the Planning Guidance Notebook (Engineering Regulation 1105-2-100, USACE 2000) to 

set forth a planning process grounded in these principles and guidelines. In evaluating 

national ecosystem restoration, Engineering Regulation 1105-2-100 requires that outputs 

be “clearly identified and quantified in appropriate 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 performance measures presented in this 

document follow these principles and guidelines. 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, threatened and endangered species and other natural system and 

habitat needs” during development of project components. To fulfill this mandate, 

ecological effects of each project will be quantitatively and qualitatively analyzed and 

evaluated using project-level performance measures adopted (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 performance measures presented in 

this document. Examples of performance measures based on Florida’s water supply 

planning law include establishment of minimum flows and levels pursuant to subsection 

373.0361(2)(g), F.S., and capability of meeting 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 Defense, 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 Everglades Restoration Plan, Final Draft. 

Integrative Assessment Team, Restoration Coordination and Verification, c/o 

United States Army Corps of Engineers, Jacksonville District, Jacksonville, FL, 

and South Florida Water Management District, West Palm Beach, FL. December 

2004. 
Appendix C – Legal Justification for Performance Measures October 17, 2007 

C-3 

http://www.evergladesplan.org/pm/recover/recover_docs/aat/rec_prelim_guid_de

c_2004.pdf

USACE. 2000. Corps of Engineers Planning Guidance Notebook. ER-1105-2-00. United 

States Army Corps of Engineers, Washington, D.C. 

USACE and SFWMD. 2007. Comprehensive Everglades Restoration Plan, Programmatic 

Regulations, Six Program-Wide Guidance Memoranda. United States Army 

Corps of Engineers, Jacksonville, FL, and South Florida Water Management 

District, West Palm Beach, FL. 

http://www.evergladesplan.org/pm/pm_docs/prog_regulations/072707_prog_regs

_rev_final_dft_gm.pdf
Appendix D – History of Restudy Performance Measures October 17, 2007 

 

D-1 

Appendix D. History of Restudy Performance Measures 

Restudy Performance Measures 

During the Central and Southern Florida (C&SF) Project Comprehensive Review Study, 

referred to as the Restudy, performance measures 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 quality of the system are still being used, but they have 

been refined and grouped into a smaller set of performance measures. Also, performance 

measures were updated to incorporate results from new model versions, 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 indicators have been developed since the Restudy. 

Greater Everglades Wetlands 

During the Restudy, 51 separate performance measures 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 Systems Model or South Florida Water Management 

Model 2000 existing condition) at discreet locations, 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 model results without losing the 

scientific underpinnings of the target. 

While refining Greater Everglades performance measures, locations of indicator regions, 

which are locations used to evaluate performance, were refined. The process for 

determining indicator regions is described in Appendix E of this document. 

Northern Estuaries 

For Caloosahatchee and St Lucie Estuaries, the number of events outside of the salinity 

envelope was revisited to accommodate the longer period of record in SFWMM version 

5.0. Additionally, two performance measures have 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 Miami 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 Project. A separate seasonal flow target and 
Appendix 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 embayments: Manatee Bay and Barnes Sound. 

Water Supply 

Frequency of water restrictions performance measures were revisited to ensure they focus 

on regionally significant water restriction events. 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 incorporate calibration and validation results from 

SFWMM version (5.0). The target is based 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 alternatives on 

performance of the Everglades Construction Project. A subset of these performance 

measures has been modified to evaluate hydrologic conditions and ecological during 

CERP implementation. The evaluation method used by Dr. Walker during the Restudy is 

not incorporated in the current set of performance 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 Southern Florida Project Comprehensive 

Review Study Final Integrated Feasibility Report and Programmatic 

Environmental Impact Statement. United States Army Corps of Engineers, 

Jacksonville District, Jacksonville, Florida, and South Florida Water Management 

District, West Palm Beach, FL. 

http://www.evergladesplan.org/pub/restudy_eis.aspx
Appendix E – Indicator Region Documentation October 17, 2007 

E-1 

Appendix E. Indicator Region Documentation 

Many of the performance measures developed for the natural areas were based on 

hydrologic patterns simulated by the Natural System Model (NSM). The NSM is likely to 

be more accurate in its simulations of regional or subregional hydrological patterns than 

with simulations of local or point hydrological conditions (Bales et al. 1997). Therefore, 

indicator regions were created to reduce the degree of uncertainty or error among the 

NSM-based targets of these performance measures. For most performance measures that 

have NSM-based hydrological targets, target parameters were established for indicator 

regions rather than for single cells or point locations. 

Indicator regions are groups of adjacent 2-by-2 mile cells within 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 indicator 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 regional scales. The set 

of performance measures developed for the Greater Everglades are applied to these 

regions in order to avoid making cell-by-cell comparisons with the NSM when evaluating 

model output. 

Since the Restudy discussed in Section 6.1 and Appendix D of this report, many of the 

performance measures, as well as the indicator regions associated with them, have 

undergone significant revision. As new information becomes available, performance 

measures and associated indicator regions may be revised, replaced or added to. 

RECOVER has the responsibility of reviewing and refining both evaluation performance 

measures and indicator regions. 

To make performance measures more consistent within the remaining Everglades, several 

regions that were evaluated separately during the Restudy were combined, including 

southern Everglades, northern and central Everglades, Big Cypress, Rotenberger and 

Holey Land Wildlife Management Areas and Pennsuco Wetlands. Several workshops 

were held in 2000, 2001 and 2002 to review and refine performance measures for these 

areas. During those workshops it became obvious that improvement to indicator regions 

was also necessary. A list of criteria for revising indicator regions was developed: 

• Indicator regions with homogeneous 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 (r2) 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 having cells with canals or other structures in 

them. 

These criteria were followed as much as possible 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 indicator 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 procedure 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 changing 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 the Greater Everglades Wetlands 
 

MAP, Part 2 – Draft Final December 2006 142

9.4.3 Submerged Aquatic Vegetation Conceptual Ecological Model 

The model below summarizes environmental interactions 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 

Disturbance 
 

MAP, 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 zone of Lake Okeechobee. 

Rationale: At higher lake stages, light penetration to the bottom 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 light availability for SAV 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 from the pelagic zone, and sheltered from 

prevailing wave action. This results 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 instantaneous decline in 

SAV density and distribution. Although this phenomenon would occur sporadically and 

is independent of CERP effects, it has potential 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 growth. 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 concentrations are low, plants out compete 

phytoplankton thereby maintaining a persistent clear water state (Philips et al. 1993). 

Hypothesis 4 

Under physical conditions that result in low light levels 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 fringe zone of Lake 

Okeechobee resulting from changes in nutrient 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 will be used in the 

development of assessment tools based 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 

Quality 
 

MAP, Part 2 – Draft Final December 2006 145

9.4.6 Macroinvertebrate Hypotheses 

Hypothesis 1 

The presence of dense SAV and emergent plant beds results in higher macroinvertebrate 

diversity and fewer pollution-tolerant organisms. 

Rationale: Research has suggested that macroinvertebrate densities in eutrophic 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 biomass and diversity were highest in dense 

plant beds under low to moderate lake stage (Havens and Gawlik 2005). The presence of 

dense SAV and emergent plant beds as a result 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 number of pollution-tolerant macroinvertebrate 

taxa. 

Hypothesis 2 

The macroinvertebrate assemblage is more diverse and comprised of fewer pollutiontolerant taxa in regions of the 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 number of organic pollution- and low dissolved 

oxygen-tolerant species. They also found that species richness was higher at sites located 

in sand and peat sediments, relative to those found at the sites located in mud sediments. 

Changes in nutrient loading and runoff are expected to reduce and/or cap mud sediments 

thereby increasing the percentage of the macroinvertebrate assemblage comprised of non 

pollution-tolerant taxa. 

Hypothesis 3 

Reduction in nutrient loads will result in increased macroinvertebrate diversity and a 

reduction in the number of pollution-tolerant macroinvertebrate taxa. 

Rationale: Macroinvertebrate diversity in a Lake Champlain wetland declined as 

nutrient loading increased (Schwartz and Gruendling 1985). In Lake Erie decreased 

diversity and increased number of pollution-tolerant taxa occurred 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 Ratios 
 

MAP, Part 2 – Draft Final December 2006 147

9.4.8 Phytoplankton Hypotheses 

Hypothesis 1 

Lake water levels influence phytoplankton growth. 

Rationale: At high lake stage both turbidity and phosphorus levels are elevated in the 

pelagic region due to wind driven resuspension of phosphorus laden mud sediments. The 

reduced irradiance levels that prevail under 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 the frequency of occurrence and intensity of 

algal blooms in these areas (Maceina 1993, James and Havens 1996). 

Hypothesis 2 

Nutrient concentrations directly influence phytoplankton biovolume and taxonomic 

composition. 

Rationale: Prolonged high rates of external loading 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, whenever the system isn’t light limited (East and 

Sharfstein 2006). P limitation favors dominance of the more desirable non bloomforming algal species while N limitation favors dominance by undesirable noxious 

bloom-forming cyanobacteria. These bloom-forming 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 proliferation 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 dominance by the bloom-forming cyanobacteria, their 

occurrence is often restricted by low light availability (Havens et al. 2003). Therefore, in 

the shallower, less turbid near-shore region N limitation prevails (Aldridge et al. 1995, 

East and Sharfstein 2006) and the bloom-forming 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 aquatic 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 uptake or by mediating changes in pH causing coprecipitation of 

P with calcium. Rooted SAV also stabilizes the sediment preventing the resupension of 

sediment and P back into the water column. SAV and epiphytes also compete for 

nitrogen and other nutrients with phytoplankton. Therefore the presence of submerged 

plants in the littoral-pelagic fringe has the potential to inhibit phytoplankton growth and 

algal bloom frequency and intensity when nutrient concentrations are high. 

9.4.9 Native Fish Species Conceptual Ecological Model 

The model below summarizes environmental interactions 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 Level 
 

MAP, Part 2 – Draft Final December 2006 150

9.4.10 Native Fish Species Hypotheses 

Hypothesis 1 

Increases in SAV density, biomass, and aerial coverage improve fish habitat and fish 

foraging opportunities and improve desirable native fish abundance and diversity. 

Rationale: Havens et al. (2005) observed a significant recruitment of largemouth bass in 

Lake Okeechobee that coincided with improved diversity and complexity of the SAV and 

emergent vegetation in 2002, after years of high water and low 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 desirable 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 heterotrophic carbon production 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 species to more desirable 

piscivores. 

Hypothesis 3 

Competition from introduced exotic fauna exerts negative pressure on desirable native 

fish. 

Rationale: Exotic animals in Lake Okeechobee now include fish, amphibians, reptiles, 

mollusks and macroinvertebrates, as well as avifauna 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 situation is likely to continue, as new species 

are introduced to the United States and subsequently 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, results 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 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. 

Rationale: The macroinvertebrates surviving in Lake Okeechobee mud sediments are 

burrowing species (primarily oligochaetes) that are common in polluted and anoxic 
 

MAP, 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 during the breeding season, removes large areas of 

fish foraging and spawning habitat from use 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 use as fish spawning and foraging habitat are 

gone. It is worth noting that while excessively high lake stages remove littoral fringe 

habitat from use by fish due to negative impacts on submerged and emergent aquatic 

vegetation, high lake stages have a compensatory mechanism in that they open up more 

upland marsh habitat to potential use by fish, and may therefore not be as damaging as 

prolonged low lake stages. 

Hypothesis 6 

Elevated nutrient loads and high water levels favor the development of dense algal 

blooms which can result in fish kills and negative 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 decline, oxygen is consumed and ammonia 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, aerial distribution and species composition in the littoral 

zone of Lake Okeechobee. Emergent vegetation 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 Mosaic Conceptual Ecological Model
 

MAP, 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 indirect negative impacts on 

shoreline and interior marsh vegetation. 

Rationale: Desirable native shoreline vegetation including bulrush (Scirpus californicus) 

and SAV are more likely to be uprooted by wind driven waves when lake stage is high. 

Following a reduction in the spatial extent of rooted macrophytes, turbidity will increase, 

light availability will be reduced and plant 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 concentrations are often less 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 spikerush and the expansion of cattail and other 

less desirable vegetation. 

Physically, rooted macrophytes help stabilize bottom sediments thereby reducing 

sediment resuspension during wind/wave events. 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 water quality will further 

inhibit the growth of desirable rooted vegetation. 

Depth and duration of flooding are important in determining the distribution of emergent 

macrophytes. In deep water, emergent species may not have enough leaf area above the 

surface of the water to obtain the oxygen needed for respiration and/or the carbon dioxide 

needed for photosynthesis. Reduced oxygen uptake through the leaves can lead to 

inadequate supplies of oxygen to the roots and rhizomes and eventually lead to plant 

death. Thus, high lake stage creates physiological 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. Therefore, in the absence of draw downs, 

recruitment of new plants from the seed bank will not occur. Prolonged high lake stage 

inhibits/prevents the germination of many desirable 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 lake stages and providing periodic recession 

events will reverse these trends and encourage the expansion of desirable native emergent 

vegetation. 
 

MAP, Part 2 – Draft Final December 2006 154

Hypothesis 2 

The occurrence of low water events accelerates 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 vegetation (e.g., spikerush, 

beakrush, and bulrush) and encourage 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 invasive weeds in their original range. Although 

low water conditions favor the growth of many non-desirable species, it also promotes 

seed germination of desirable native plants and allows for natural and controlled fires 

which can be effectively used with other management 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 appropriate balance between the positive and 

negative effects of low water events. 

Hypothesis 3 

Floating exotic vegetation can have a negative impact on bulrush and other native plants 

which is further exacerbated under high lake stage conditions. 

Rationale: High lake stage enhances the wind driven transport of floating 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, commonly form large floating mats that exceed 

50 m in length. These mats can cause extensive 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 have 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 reduce the areal coverage of these exotic species 

and maintain navigational access to the lake, these mats are often sprayed with herbicide. 

Because the mats are commonly entangled in stands of bulrush and other native 

vegetation, some non-target plant damage is likely to occur during treatment. While it is 

recognized that chemical control of exotics 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 understanding 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 CERP projects, it seems 

clear that ongoing vegetation management activities 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 effectively 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 water 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 native vegetation may be a serious concern. 
MAP, Part 2 – Draft Final December 2006 156

in 2000), and as such is subject to widely conflicting stresses 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 westward expansion of agricultural, mining, 

and urban activities. Surface water is impounded in water-conservation areas that lie 

west of the protective levee system, partly to: (1) sustain an Everglades ecosystem, (2) 

keep overland sheetflow from moving eastward 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 urban areas must be drained for flood control, whereas the 

underlying surficial aquifer system must simultaneously serve as the principal source for 

water supply, and ground-water heads must be maintained to prevent saltwater intrusion. 

Changes in predevelopment ground-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 early 1920s, extractive mining has increased considerably, 
 

MAP, Part 2 – Draft Final 83 December 2006 

9.1.3 Oyster Conceptual Ecological Model 

The model below summarizes environmental interactions that are known to effect oyster 

health and abundance. Many of these parameters are currently being monitored and will 

be used in the assessment process based on the hypotheses listed below. 

9.1.4 Oyster Hypotheses 

Hypothesis 1 

Undesirable shifts in the estuarine salinity 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 and subsequent watershed run-off, or large volume 

releases from Lake Okeechobee cause large volumes of freshwater over a short period of 

time to enter the estuary causing a sudden drop in salinity. This sudden drop can lead to 

significant mortality in the oyster population, changes in food type and availability and 

Water Management

Hydrodynamics Sedimentation

(muck and rate) Adult Density Salinity Temperature

Predation

Dissolved Oxygen

Larval Recruitment

Disease

Food

Reproduction

Substrate

Oyster Abundance and Health

Figure 9-1-3: Oyster Conceptual Ecological Model 
 

MAP, Part 2 – Draft Final 84 December 2006 

decreased growth, reproduction, and spat recruitment. 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 unsuitable for oyster larval settlement and thus 

recruitment and growth of larval oysters. In addition, accumulation of muck may also 

impact the dissolved oxygen content making the area / substrate unsuitable for larval 

settlement and growth. 

Rationale: Oyster recruitment is negatively effected by the accumulation of mucky 

sediments in the estuary. Muck is unsuitable substrate for spat settlement. Areas that 

once contained sand and/or shell have been covered by these very soft, unconsolidated 

sediments. Freshwater inflow carries sediments 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 reproductive health of oysters. In 

addition, sediment accumulation on oyster shell negatively affects spat recruitment. 

Rationale: Oyster populations are affected by increased sediment loads resulting from 

alterations to the natural hydrology. Adult oysters have effective morphological 

adaptations for feeding in much higher levels of suspended solids than are usually 

encountered under normal conditions. Oysters from relatively turbid estuaries appear to 

be capable of feeding at total suspended solid concentrations 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 increased 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 largely due to altered 

freshwater inflow, shell mining, and changes 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 85 December 2006 

9.1.5 Fish Conceptual Ecological Model 

The model below summarizes environmental interactions that are known to effect fish 

abundance. Many of these parameters are currently 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 parameter hypotheses in order based on their 

importance and value to fish physiology in a subtropical/tropical setting. 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 Model 
 

MAP, Part 2 – Draft Final 86 December 2006 

Rationale: Dissolved oxygen. Tropical/subtropical systems are warm thus reducing the 

oxygen carrying capacity of water. Warm water systems often have high productivity if 

sufficient nutrients are present, thus often 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, and 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 capable of withstanding 

DO levels as low as 1.0 ppm or lower. Most temperate to warm temperate fishes, spotted 

seatrout, red drum, black drum, sand seatrout, and Atlantic toadfish 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 examined at the species level. 

Hypothesis 2 

Nutrient concentrations in the Northern Estuaries are directly associated with fish health 

and mortality in these estuaries. 

Rationale: Nutrients. It is apparent from resent observations over the past 30 yrs that 

plankton and harmful algal blooms (HABs) fed by nutrient loading have had substantial 

impacts on fish health and survival in the northern estuaries. The list of impacted species 

continues to grow annually to the point that no species can be left out of this analysis. 

Initially 1970's observations indicated that mullet were most likely to be impacted by 

HABs. We assume that nutrient levels, water turbulence and sediment resuspension 

produce conditions that are favorable for algal blooms. Nutrient levels can have 

substantial impact on HAB production and primary production levels in general, thus 

increase BOD/system eutrophication 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 dry season conditions will have a significant 

deleterious effect on stenohaline fish egg/larval, juvenile survival at northern estuary 

spawning and nursery sites. 

Rationale: Salinity. Since larval fish and eggs require specific salinity conditions for 

survival and fish spawning sites are located within the Northern Estuaries. There is a 

direct relationship between freshwater flow and quantity, ambient salinities, and potential 

egg/larval survival. There is a very species rich resident and migratory fish fauna that is 

distinctly marine, particularly on the Florida east coast, which is very sensitive to salinity 

change as larvae, juveniles and adults. Stenohaline 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 notorious for not being reliant on specific salinity 

patterns. They have the capability as juveniles and adults, but not necessarily as eggs and 
 

MAP, Part 2 – Draft Final 87 December 2006 

larvae, to enter freshwater tributaries from the Ocean or Gulf with little or no acclimation. 

Species that show this marine-freshwater migratory pattern are snook, tarpon, bull sharks, 

sheepshead, striped mullet, various gobies and gray snapper. 

Hypothesis 4 

Maintenance of water pH levels above 5.0, and 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 buffered. 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. However, it is recognized that there is a very 

distinct biogeographic difference between the Gulf and Atlantic estuarine fish faunas 

principally due to very different ambient water temperature regimes and ocean current 

patterns associated with both coastal systems (Caloosahatchee River/Charlotte Harbor: @ 

250 fish species versus St. Lucie River/Indian River Lagoon: @ 500 fish species). 

Because of this, a stenothermic tropical fish fauna is found in the St. Lucie ecosystem 

that is not present in the Caloosahatchee ecosystem. 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 regional 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 Ecological 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 influence on fish population 

dynamics, distribution, migration and survival. This is particularly true for fish eggs and 

larvae. 
 

MAP, Part 2 – Draft Final 88 December 2006 

Hypothesis 7 

Changes in the salinity envelope in the northern 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 gradual 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 seatrout and common snook). 

Therefore the timing and severity of salinity fluctuations becomes an important factor in 

reproduction and growth. Euryhaline fish populations that often associate with 

oligohaline habitats show a positive association 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 communities have a positive association with 

healthy fine sediments, mud and their benthic 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 often accompanied by anoxic conditions. 

Hypothesis 9 

Riverine and estuarine sediment composition and dynamics dictates recruitment success 

in centropomids, gerreids, and gobioids dependent on the northern estuaries. 

Rationale: Sediment deposition and distribution is directly associated with stream 

configuration (e.g., meander vs. straightened) and topography, flow dynamics, water 

depth and stream bank location and proximity, 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 influenced by: (1) oyster reef 

structure; (2) live vs. dead oyster reef structure; (3) age and degradation/deterioration of 

oyster reef systems. 

Rationale: Gobiosoma bosc plays a major trophic role in northern estuaries due to its 

numerical dominance of riverine ichthyoplankton and as the major vertebrate species 

directly associated with oyster reefs as critical habitat, feeding and spawning sites. 
 

MAP, Part 2 – Draft Final 89 December 2006 

Gobiosoma bosc is a major prey item for planktivorous 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 estuarine 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) reduced salinities during 

their spawning period. Life history, growth and mortality of marine/ mesohaline/ 

polyhaline seasgrass/reef associated fish species are negatively influenced by atypical 

and/or aseasonal reduced salinities which occur both from the overly ditched and drained 

watershed as well as from Lake Okeechobee discharges. 

Hypothesis 12 

Healthy freshwater emergent herbaceous vegetation 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 distribution 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 salinity in the riverine portions that feed into 

the main estuary. 

9.1.7 Submerged Aquatic Vegetation Conceptual Model 

The model below summarizes environmental interactions that are known to affect the 

cover, abundance and productivity of submerged aquatic vegetation. 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 90 December 2006 

9.1.8 SAV Hypotheses 

Hypothesis 1 

Extreme fluctuations in estuarine salinity resulting from hydrologic alterations, water 

management practices, and sea level rise have 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 location. In the upper 

estuary, the naturally occurring submerged grass species, Vallisneria americana, will not 

survive prolonged periods of elevated salinity that occur as a result of manipulated 

freshwater flow. Halodule wrightii persists in areas with high 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 Model 
 

MAP, Part 2 – Draft Final 91 December 2006 

Rationale: Sediment characteristics (e.g. nutrients, oxygen, microbial communities) are 

important to SAV survival; these characteristics will be altered by the increased 

deposition of fine silts and organic matter. Fast growing SAV (e.g. Halodule wrightii) 

requires higher nutrient levels in the sediment, 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 matter and turbidity affect SAV 

abundance and health by increasing phytoplankton levels and water 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 increase light attenuation 

which is directly correlated to decreased depth distribution and shoot density of SAV. 

Seagrasses require more light than macro-algae or phytoplankton, therefore decreased 

light (increased light attenuation) will reduce the ability of seagrass to compete with these 

other species. Halodule wrightii and Syringodium filiforme require less light than 

Thalassia testudinum, therefore a prolonged increase in light attenuation will lead to a 

shift in species composition. Sulphide toxicity 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 structure 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 between fish and seagrass habitat that is 

influenced by ambient salinity regimes. Estuarine seagrass and nearshore hardbottom 

dependent populations of juvenile tropical reef fish (lutjanids, serranids, scorpeanids, 

gobiids, blenniids and labrisomids) show a positive relationship with salinity, e.g. higher 

densities at higher salinities. Extreme and rapid 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 with over-enrichment of estuarine waters, 

which stimulates growth of epiphytes, resulting in reduction of photosynthetically active 

radiation (PAR) at the SAV blades. Herbivorous grazing on epiphytes can partially 

relieve SAV growth inhibition at moderate nutrient loading rates but does not seem to 

significantly alter plant response at higher nutrient levels. 
 

MAP, Part 2 – Draft Final 92 December 2006 

9.1.9 Benthic Infaunal Community Conceptual Ecological Model 

The model below summarizes environmental interactions that are known to effect benthic 

community structure. Many of these parameters are currently being monitored and will 

be used in the assessment process based 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 natural estuary where the riverine input is relatively stable, 

and/or relatively predictable, throughout the year, resulting in a wedge-shape bottom 

layer of higher salinity (strong pycnocline), the irregular and massive freshwater releases 

from the primary SFWMD canals which drain the estuary’s expanded basin and 

regulatory releases from Lake Okeechobee to both the Caloosahatchee 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 Model 
 

MAP, Part 2 – Draft Final 93 December 2006 

processes that occur in estuaries, processes that will be disturbed by these salinity 

changes. 

Hypothesis 2 

The anthropogenically exacerbated accumulation of soft unconsolidated and strongly 

reducing sediments in the estuary inhibits the establishment of infaunal species resulting 

in an impoverished community characterized 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 scale predominance of fine sediments at the 

expense of other typical estuarine sediment types, as is present in the St. Lucie estuary, 

constitutes a patently man-induced 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 sediments in the St. Lucie Estuary severely impacts 

certain infaunal species important for the ecosystem stability. 

Rationale: Suspension feeders, such as many bivalves tend to predominate in sandier 

sediments. They feed and eliminate wastes by either pumping water through their 

burrows, where it is filtered out and pumped 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 times significant concentrations of H2S in the waters 

adjacent the bottom sediments often occurs resulting in mass mortality and prevents the 

settling of larvae, adversely affecting the infaunal communities. 

Rationale: As a result of the widespread deposition of typically strongly reducing fine 

unconsolidated sediments, bottom waters are likely to exhibit depressed oxygen 

concentrations, and in some events contain significant quantity of sulfide from 

decomposition processes occurring in the sediment. Such conditions may likely be 

extensive on occasions when temperatures are higher (during the summer) or when wind 

induced mixing is low. Low oxygen concentrations have also been associated with 

freshwater discharge (Stanley and Nixon 1992). Such hypoxic, anoxic, and/or toxic 

conditions result in mortality of the sessile benthic communities, which may be followed 

by a rapid establishment of opportunistic species. Overall these conditions result in a 

severe disturbance of the entire estuarine ecosystem. 

Hypothesis 5 

Increases in nutrient concentrations may directly or indirectly seriously impact benthic 

abundance, biomass, diversity and species composition. 
MAP, Part 2 – Draft Final 94 December 2006 

Major stressors currently impacting Greater Everglades Wetlands include 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 interrelated hypotheses: 

• Integrated Hydrology And Water Quality 

• Coastal Transgression, Tidal Channel Characteristics, Salinity Gradients, and 

Mangrove Forest Productivity 

• Wetland Landscape and Plant Community Dynamics 

• Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base 
MAP, Part 2 – Draft Final 97 December 2006 

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 geological setting, and a subtropical climate 

resulted in sheet flow and low levels of phosphorus and other chemical constituents in the 

pre-drainage Everglades. Together, these physical-chemical 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 depends on restoration of the volume, timing, 

and distribution of sheet flow and on restriction of inputs of phosphorus and other 

chemical constituents to levels approximating those in direct rainfall. 
 

MAP, Part 2 – Draft Final 98 December 2006 

Sheet flow and inputs of phosphorus and other chemical constituents fundamentally 

affect all working hypotheses for greater Everglades wetlands ridge and slough landscape 

dynamics, plant community distributions along elevation gradients, predator-prey 

interactions of wading birds and their aquatic fauna forage base, crocodilian population 

dynamics, coastal salinity gradients, coastal 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 Model 
 

MAP, Part 2 – Draft Final 99 December 2006 

Hypothesis 1 

Rainfall and Sheet Flow as Determinants of Natural System Hydrologic Characteristics in 

the Everglades 

The volume, timing, and distribution of sheet flow, 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 salinity patterns in the mangrove estuaries 

of Florida Bay and the Gulf of Mexico 

Compartmentalization has altered or eliminated sheet flow and related natural system 

hydrologic and landscape characteristics throughout the Everglades. 

Decompartmentalization, combined with resumption of natural volume, distribution, and 

timing of freshwater delivery is expected to restore sheet flow and pre-drainage 

hydrologic and landscape characteristics to an undivided ecosystem encompassing much 

of Water Conservation Area 3A, Water Conservation Area 3B, eastern Big Cypress, and 

Everglades National Park. 

Rationale: Specific hydrologic restoration targets associated with the resumption of 

sheet flow and related hydrologic characteristics include: 

• Multi-year hydroperiods in ridge and slough landscape 

• Conditions conducive to peat formation in ridge and slough landscape 

• Hydropatterns that sustain co-existing 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 directions that follow the historic landscape 

directionality 

• Hydropatterns that support the long-term stability of tree islands in ridge and 

slough landscape 

• Hydroperiods from two months to less than one year conducive to marl 

formation and muhly grass (Muhlenbergia filipes) community persistence in 

Southern marl prairies 
 

MAP, Part 2 – Draft Final 100 December 2006 

• Persistent pools of fresh to oligohaline 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 conducive to successful wading bird 

foraging 

• Multi-year flood and drought cycles supporting formation of wading bird 

super-colonies 

• Absence of harmful regulatory releases of excess fresh water to the Greater 

Everglades 

• Freshwater flow discharges to Florida Bay and the Gulf estuaries that 

maintain a near shore salinity gradient characteristic of pre-drainage 

conditions. 

Natural system hydrologic restoration targets are necessarily qualitative due to 

uncertainty regarding pre-drainage hydrology. Successive iterations of the Natural 

System Hydrology Model (NSM) quantify these targets for planning purposes despite 

high levels of uncertainty. Successful restoration of natural 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 and related hydrologic and climatic characteristics, resulted 

in an oligotrophic, phosphorus-limited nutrient 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 downstream of canal discharge structures, 

shifting wetlands from oligotrophic to eutrophic states. Water column total P 

concentrations are below ~10 ppb under non-enriched 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 waters 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 101 December 2006 

• 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 trends in surface water concentrations, 

integrated over various time scales, from months to years. 

Hypothesis 3 

Nitrogen Dynamics in the Everglades 

Nitrogen dynamics, such as rates of nitrification, 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 cycling and processing presently increases 

with distance from surface water inflow locations, while the 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 Integrated Hydrology and Water Quality in the 

Everglades 

Periphyton mat structure and community composition integrate hydrology and water 

quality across the entire wetland system of the Everglades. 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 warning indicators of ecosystem change. 

Shortened hydroperiods cause: 

• Reduced proportion of diatoms and green algae relative to cyanobacteria 

• Increased calcareous blue-green algae, possibly reducing food value of 

periphyton 

• Increased proportion of sediment or plant-stem associated mats as opposed to 

floating mats attached to floating macrophytes (such as Utricularia purpurea). 

• Decreased organic ash weight ratio of periphyton 

Phosphorus enrichment through increased loading causes: 

• Elevated nutrient content of periphyton material 

• Increased organic content of periphyton communities 
 

MAP, Part 2 – Draft Final 102 December 2006 

• 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 oligohaline 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 baseline (i.e. ridge and slough, marl prairie, 

rocky glades, or oligohaline zone). In addition, the effects of grazing on the periphyton 

community composition should be quantified.

9.2.4 Coastal Transgression, Tidal Channel Characteristics, Salinity Gradients, 

 and Mangrove Forest Productivity 

Ecological processes and attributes in the mangrove coastlines of the southern Everglades 

are hydrologically controlled by interactions between overland sheet flow from 

freshwater wetlands and the waters of the Gulf of Mexico and Florida Bay. Changes in 

freshwater flow from the implementation of CERP projects are relatively 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 south 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 result 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 the stressors as manifest through the causal 

pathways. 
 

MAP, Part 2 – Draft Final 103 December 2006 

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 Determinants of Coastal Transgression 

Sustained substrate buildup by physical and biological processes in many coastal marl 

and mangrove environments of South Florida may not be capable of keeping up with 

rates of sea-level rise during the 21st century. 
 

MAP, Part 2 – Draft Final 104 December 2006 

Where rates of peat or marl elevation buildup do not keep up with rates of sea level rise, 

shoreline transgression and landward salinity intrusion into mangrove and freshwater 

wetlands will occur. 

Rationale: Red mangrove forests in south Florida can potentially accrete organic peat 

substrate at 2-6 mm/year. Disturbances (major 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 mangrove communities are presently losing area of 

coverage. In the coming century the coastal 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 during storm events are likely under future 

scenarios of rising sea level. 

Where rates of peat or marl elevation buildup do not keep up with rates of sea level rise, 

shoreline transgression and landward salinity intrusion will lead to mangrove erosion 

along shorelines and mangrove movement into interior landscapes. Saline intrusion into 

freshwater wetlands underlain by peat substrate may lead to wetland community collapse 

and transformation to open, saline ponds and estuaries. Saline intrusion into marl 

substrate wetlands results in an advancing zone of diminished productivity (this is often 

called the “white zone”). Restoration of freshwater flow volume, timing, and distribution 

may slow the inland movement but it is not expected to change the rate of erosion along 

the shoreline. 

Hypothesis 2 

Sea Level and Freshwater Flow as Determinants of Tidal Channel Characteristics 

The dendritic pattern, channel width and depth, flow volume, and material transport of 

tidal watercourses and channels through the coastal mangrove estuaries are controlled by 

sea level interacting with the volume, timing, and distribution of sheet flow and channel 

flow from the southern Everglades. 

Rationale: Restored freshwater inflow from the Everglades 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 filled 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 enhanced flood and especially ebb tidal flow. 

This process is expected to result in stronger tidal currents through channels resulting in 

enhanced erosion and widening of those channels. Such conditions are expected to result 
 

MAP, Part 2 – Draft Final 105 December 2006 

in an increased import and/or export (depending on setting) of particulates, nutrients and 

dissolved organics. Sea-level rise is expected to destabilize 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 106 December 2006 

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 Model
 

MAP, Part 2 – Draft Final 107 December 2006 

Hypothesis 3 

Sea Level and Freshwater Flow as Determinants of Coastal Salinity Gradients 

Sheet flow in the southern Everglades prior to drainage produced prolonged pooling of 

fresh water upstream of the mangrove estuaries and prolonged patterns of freshwater flow 

into the mangrove estuaries. 

The freshwater pooling and inflow 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 freshwater marshes of the lower Everglades. 

Rationale: Increasing seasonal freshwater sheet flow to the lower Everglades is expected 

to provide a broader zone of salinity gradients in the lower Everglades and coastal 

wetlands and should, in the short term, re-establish 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 the interface depends on the intensity and 

duration of freshwater flow stoppage to the 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 and saline waters penetrating more deeply through tidal channels and 

mangrove forests, shifting inland the areas of fresh and lower salinity waters. 
 

MAP, Part 2 – Draft Final 108 December 2006 

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 Determinants of Above and 

Belowground Production, Organic Soil Accretion, and Resilience of Coastal Mangrove 

Forests
 

MAP, Part 2 – Draft Final 109 December 2006 

Production and organic soil accretion in the mangrove forests of the coastal Everglades 

are controlled by phosphorus availability, with relatively high inputs from marine sources 

and low inputs from freshwater sources. Phosphorus availability, mangrove production, 

and soil elevation are thus driven by the opposing influences of sea 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 fresh 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 systems to the marine phosphorus 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 Florida Bay reflect suppressed 

levels of aboveground productivity, as influenced by minimal P supply from either the 

oligotrophic marshes of the southern Everglades or Florida Bay. High belowground 

production rates in the dwarf mangrove forests appear to be a biomass allocation 

phenomenon in which mangroves in the oligotrophic southern Everglades are foraging 

for nutrients. The counter-intuitive expectation is that maintenance of oligotrophic 

conditions in the southern Everglades [by increased freshwater inflows] may promote 

peat accretion in these mangroves. 

Increased freshwater sheet flow caused by implementation of CERP projects is expected 

to maintain low nutrient conditions in the southern Everglades mangrove estuaries and in 

the oligohaline ecotone forests of the western mangrove estuaries. These low nutrient 

conditions are expected to enhance belowground productivity by mangroves, which will 

maintain peat production and soil 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 and expansion of this “white zone” are 

regulated by freshwater flow dynamics and sea level rise. This phenomenon has 

implications for the long-term maintenance of mangrove communities and for mangrove 

communities trying to move into former sawgrass wetlands. Improved freshwater flow 

and flushing through the lower Everglades and coastal wetlands (through both channel 

and sheet flow) are expected to aid in recovery of wetlands from catastrophic setbacks 

(from hurricanes, fire, freeze and salinity changes). 
 

MAP, Part 2 – Draft Final 110 December 2006 

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, Organic Soil Accumulation, and Resilience 

Conceptual Ecological Model
 

MAP, Part 2 – Draft Final 111 December 2006 

9.2.5 Wetland Landscape and Plant Community Dynamics 

Hypothesis 1 

Everglades Ridge and Slough Micro-topography in Relation to Organic Soil Accretion 

and Loss 

Sheet flow interacts with hydroperiod, water depth, fire, and nutrient dynamics to 

maintain organic soil accretion and loss in a state of dynamic equilibrium. 

Rationale: The dynamic equilibrium involves a balance 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 exacerbated by eutrophication. Disequilibrium of 

accretion and loss processes causes degradation in the ridge, slough, and tree island 

micro-topography toward a flattening of the landscape. 

Restoration of sheet flow in combination with related hydrology, water quality, and fire 

patterns will re-establish the feedback conditions that sustain the micro-topography of 

ridges, sloughs, and tree islands. 

Hypothesis 2 

Everglades Ridge and Slough Landscape Pattern 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 previously long-term, large-scale features of the 

ridge and slough landscape. 

Rationale: Decline in ridge and slough habitat diversity and stability includes expansion 

of sawgrass into sloughs and wet prairies, tree island drowning, tree island burn-out, 

conversion to cattail under eutrophic conditions, and takeover by exotic species, such as, 

Melaleuca quinquenervia and Lygodium microphyllum. 

Resumption of sheet flow and related patterns of hydroperiod, water depth, water quality, 

and fire will significantly restore and sustain the microtopography, directionality, and 

spatial extent of ridges and sloughs and improve the health of tree islands in the ridge and 

slough landscape. 
 

MAP, Part 2 – Draft Final 112 December 2006 

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 Model
 

MAP, Part 2 – Draft Final 113 December 2006 

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 depth, nutrient dynamics, and fire patterns 

throughout freshwater wetlands of the Greater Everglades. 

Rationale: The dynamic equilibrium of the vegetation mosaic in relation to elevation 

gradients is maintained if biogeochemical processes in the soil support 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 the vegetation mosaic away from the historic 

dynamic equilibrium. These hypotheses are designed 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 wetlands where hydroperiods and water depths have 

decreased, the hydrologic tolerances of the surviving plant communities are adapted to 

greater hydroperiods and water depths than are currently maintained. 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 concern in the southern Everglades. Although a 

potential trade-off exists between ridge and slough habitat restoration and the extent and 

quality of habitat in adjacent marl prairies. It is thought that longer hydroperiods, greater 

water depths, and appropriate flow regimes will re-establish and sustain ridge and slough 

landscape patterns without significantly infringing on adjacent marl prairies, where shorthydroperiod, tussock growth habitats will persist. 
 

MAP, Part 2 – Draft Final 114 December 2006 

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 Gradients Conceptual Ecological Model
 

MAP, Part 2 – Draft Final 115 December 2006 

9.2.6 Predator-Prey Interactions of Wading Birds and Aquatic Fauna Forage Base 

The collapse of wading bird nesting colonies in the southern Everglades is attributed to 

declines in population densities and seasonal concentrations of marsh fishes and other 

aquatic prey organisms. 

Restoration of natural hydrologic conditions will re-establish distributions of prey 

densities and concentrations across the landscape that in turn will support the return of 

large, successful wading bird nesting colonies to the southern Everglades. 

Hypothesis 1 

Aquatic Fauna Wet Season Prey Population 

The wet-season density, size structure, and relative abundance of marsh 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 and 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, occurred in ridge and slough landscapes and adjacent coastal 

ecotones of the southern Everglades under pre-drainage conditions. Expansive, naturally 

occurring pools in the southern Everglades have been replaced by artificial 

impoundments in the lower ends of Water Conservation Areas. As a result, population 

densities of aquatic fauna are low in much of the southern Everglades, while densities 

have increased in the artificial pools of the Water Conservation Areas, which now favor 

larger, longer-lived species. 

Resumption of natural volume, timing, and distribution of freshwater flow will restore 

historical hydroperiods and salinity distributions to the southern Everglades. These 

changes are expected to increase wet-season density and size structure of wading bird 

prey in the southern Everglades within a four to seven year timeframe. 
 

MAP, Part 2 – Draft Final 116 December 2006 

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 Model
 

MAP, Part 2 – Draft Final 117 December 2006 

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 topography/habitat heterogeneity. 

Rationale: Erratic water-level fluctuation in the remaining managed system, particularly 

in the Water Conservation Areas, commonly 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 gradients 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-drainage conditions in the southern Everglades. The drying 

edges concentrated aquatic prey organisms and made them available to wading birds. 

Urban and agricultural development of the higher elevation eastern fringes of the 

southern Everglades, in combination with drying of marl prairies earlier in the dry 

season, have truncated in time and space the drying marsh edge and the concentration of 

aquatic prey organisms. During very wet years, 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, but 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 distribution of freshwater flow to the 

Everglades is expected to restore historical patterns of water level recession and drying 

edges, which will concentrate wading bird prey into a succession of high-density patches 

throughout the dry season in the remaining ridge 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 other 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 nesting colonies to those areas after the collapse of the coastal 
 

MAP, Part 2 – Draft Final 118 December 2006 

colonies. However, drying 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 Spoonbill 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 and 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-drainage system in response to the effects of 

extreme, natural patterns of drought prior to colony formation. 

Rationale: Super colonies periodically formed along the freshwater-estuarine transition 

zone (sawgrass-mangrove ecotone) at the lower reaches of the Everglades and Big 

Cypress basins. A substantial reduction in frequency of super colonies is attributed to 

disrupted multi-year wet and dry cycles, due to altered volume, timing, 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 hydroperiods 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 patterns of volume, timing, and distribution 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 have occurred prior to drainage the southern 

Everglades. This is expected to stimulate pulses of secondary productivity that will likely 

involve Everglades crayfish populations. The pulses in secondary production are 

expected to result in an increase in the return 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 Levels 
 

MAP, Part 2 – Draft Final 119 December 2006 

The floating mat comprised of the periphyton complex and various bladderworts provides 

critical support of the oligohaline Everglades food web, both as a food source and a 

refuge for aquatic invertebrates that are consumed by small fish, crayfish, and grass 

shrimp. 

Rationale: The floating mat provides both food (algae and detritus) and habitat structure 

(hiding places) for macroinvertebrates, including 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 water column at night, compared to other North 

American ecosystems. These small invertebrates serve as a critical food source for 

Everglades consumers, including small fish, crayfish, and grass shrimp. Lengthened 

hydroperiods expand the aerial coverage of habitats where these food-rich mats are 

abundant. Shortened hydroperiod reduces the area of extensive floating mats and 

decreases the length of the season when habitat is available for aquatic organisms. These 

losses decrease standing crops available for consumption by higher trophic levels. 

Higher nutrient levels stimulate invertebrate productivity, but change community 

composition to favor pollution-tolerant taxa. 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 nutrient 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 floating mat, and particularly periphyton primary 

productivity and detrital production, to higher trophic levels, which are the focus of 

management action. 
 

MAP, Part 2 – Draft Final 120 December 2006 

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 Trophic Levels Conceptual Ecological Model
 

MAP, Part 2 – Draft Final 121 December 2006 

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, abundance, reproduction, and body condition in the 

Everglades are controlled by hydroperiod and water table in the Rocky Glades, salinity in 

the mangrove estuaries, and water depth patterns in the ridge and slough system, all of 

which were driven by direct rainfall and sheet flow prior to drainage. 

Compartmentalization, disrupted sheet flow, and regulatory water releases restrict 

alligator populations in the 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 water table in the rocky glades have 

reduced alligator abundance and reproduction because of loss of aquatic habitat required 

for survival and reduced aquatic prey base. A positive feedback loop of increased 

alligator populations and alligator holes (aquatic refugia) leading to increased aquatic 

fauna density (alligator prey) has been disrupted. 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 freshwater mangrove areas to saltwater systems, 

reducing American alligator populations in tidal rivers and tributaries. 

American alligator populations remain viable throughout most of the ridge and slough 

system. However, increased water depths during nesting seasons particularly near canals, 

the southern ends of each Water Conservation 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 periods of increased water 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 hatchling 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 expected to repopulate and resume nesting in the 

rocky glades and the freshwater reaches of tidal 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 122 December 2006 

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 Model
MAP, Part 2 – Draft Final 123 December 2006 

and estuaries within southwest Floridas mangrove zone from Whitewater Bay to 

Lostman’s River (Figure 1). Altered freshwater inflows have affected circulation and 

salinity patterns of the Southern Estuaries, in turn altering the structure and function of 

these ecosystems. Changes in habitat structure and distribution have been of particular 

concern because of their effects on animal populations. 
 

MAP, Part 2 – Draft Final 127 December 2006 

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 between water quality and hydrologic drivers 

as well as internal nutrient cycling 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 nutrients 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 inputs 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 Implementation and 

other water management and 

land use changes

Episodic events Open Keys’ passes

Restored 

freshwater flow 

(quantity, timing, 

distribution, 

quality)

Altered nutrient input 

(concentration and load)

Groundwater inputs

Restored 

estuarine 

salinity

Internal 

nutrient 

cycling and 

bioavailability 

Restored SAV 

community

Light 

availability 

changed benthic 

grazing 

changed

Sediment 

stability, 

resuspension, 

and export 

changed

Phytoplankton 

bloom response

Estuarine 

residence 

time / 

flushing
 

MAP, Part 2 – Draft Final 128 December 2006 

2) changes in the quantity of nutrient inputs to the estuaries through alteration of 

the mobilization and release of nutrients from developed and agricultural areas, 

through nutrient uptake in treatment areas, and through changes 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 cycling rates (e.g., nitrogen fixation and denitrification) and 

biogeochemical processes, such as phosphate sorption, will change with CERP 

implementation because of salinity and benthic habitat changes. 

• Nutrient accumulation and retention in estuaries is affected by episodic storm events, 

which can export nutrient rich sediments. CERP implementation will modify benthic 

habitats and nutrient loading which 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., zooplankton, benthic filter-feeders). 

• Nutrients inputs from groundwater discharges may affect water quality in coastal 

wetlands and estuaries. CERP implementation will modify these discharges in the 

coastal zone which will alter nutrient loads to the estuaries. 

9.3.5 Benthic Submerged Aquatic Vegetation 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 productive ecosystem that is the basis of the 

food web and provides habitat for most recreationally- and commercially-important 

fisheries species in the SEM region (Zieman 1982, Thayer et al. 1999). Seagrasses also 

have a major effect on water quality and clarity through nutrient uptake and storage and 

by increasing sedimentation and sediment stabilization via their physical structure (Prager 

and Halley 1999). 
 

MAP, Part 2 – Draft Final 129 December 2006 

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 availability, sulfide toxicity, and disease (Robblee et al 1991, 

Carlson et al 1994, Durako and Kuss 1994, Rudnick 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 persistence, seagrasses and macro-algae integrate and 

respond to changes in water quality. Thus, benthic SAV distribution 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 distribution 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 Model 
 

MAP, Part 2 – Draft Final 130 December 2006 

9.3.6 Benthic Submerged Aquatic Vegetation Hypotheses 

• Changes in both salinity and water quality resulting from CERP implementation are 

expected to result in changes in seagrass cover, biomass, distribution, species 

composition and diversity though the combined and interrelated effects of light 

penetration, epiphyte load, nutrient availability, salinity, hypoxia/anoxia, sulfide 

toxicity, and disease. 

• Changes related to CERP implementation will include an expansion 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 interrelated effects of light penetration, 

nutrient availability, salinity, temperature, and changes in seagrass density and 

species composition . 

• Significant changes in benthic algae and seagrass distribution 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. Some, such as pink shrimp, are harvested 

primarily in offshore fisheries, although inshore live bait fisheries target juveniles in 

Biscayne Bay. Shoreline and bottom configuration, vegetation, and salinity patterns are 

characteristics that define nursery habitat and determine their productive capacity, 

thereby the abundance of favored species. The fundamental assumption of CERP is that 

the alteration of volume, timing, and spatial distribution of freshwater inflow that 

occurred with past water management practices has decreased the productive capacity of 

estuarine nursery grounds by altering both bottom and shoreline vegetation and salinity 

patterns and the area over which favorable zones of bottom vegetation and salinity 

overlap. One purpose of CERP is to expand, in both space and time, favorable conditions 

for the estuarine species that were historically characteristic of the coastal wetland and 

nearshore zone. This includes oysters, red 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 wider variety and abundance of food organisms, reducing physical 

disturbance, and providing substrates for attachment. The formulation and monitoring of 
 

MAP, Part 2 – Draft Final 131 December 2006 

performance measures that adequately reflect nursery function are essential elements of 

the CERP monitoring program. 

Figure 9-3-3: Nearshore Nursery Function Conceptual Ecological Model 
 

MAP, Part 2 – Draft Final 132 December 2006 

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., regarding food availability and shelter) but 

also through the direct physiological 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 favorable 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 the overall abundance (density x area) of 

invertebrate and vertebrate species, including pink shrimp, pinfish, rainwater killifish, 

mojarras, gray snapper, and spotted seatrout. 

Hypothesis 2 

Responses to change in both biotic (vegetation structure and cover) and abiotic (salinity 

pattern) aspects of habitat may vary. 

Rationale: Responses may vary by life stage because habitat use and salinity 

requirements often differ depending on life stage. Responses vary by species both 

because of different salinity tolerances and because of life-history differences that affect 

requirements and when required conditions are needed. Responses may be stepwise for 

some species/stages versus continuous for others because of physiological or behavioral 

influences. 

Hypothesis 3 

There is a direct quantitative relationship between the abundance of small juvenile pink 

shrimp in Biscayne Bay and Florida Bay and catch per unit effort of larger juveniles and 

adult pink shrimp in fisheries. 

Rationale: Small juvenile pink shrimp become 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 factors 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 grassbeds; therefore the abundance of small prey 

species in nearshore flats may be reflected in the growth rates of the consumers. 
 

MAP, Part 2 – Draft Final 133 December 2006 

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 freshwater inflow will 

result in changes in the abundance, substrate coverage, and species composition of 

epifauna on mangrove prop-roots. 

9.3.9 Nearshore Community Structure Conceptual Ecological Model 

Many of South Florida’s estuarine habitats have 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 highly productive, but relatively low diversity, 

plant and animal communities. In many nearshore areas of Biscayne and Florida Bays, 

freshwater flow is so variable that downstream salinity regimes are suboptimal for 

freshwater, brackish and marine organisms alike. Among the objectives of the CERP is 

to restore the function of the coastal creeks that once supplied diffuse, but consistent, 

freshwater flow to southern Biscayne Bay. The restoration of a more natural freshwater 

delivery regime and associated salinity patterns 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 species composition, diversity and 

abundance of the nearshore fish, invertebrate and seagrasss communities is critically 

needed to develop appropriate performance measures. 
 

MAP, Part 2 – Draft Final 134 December 2006 

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 variation 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 135 December 2006 

Hypothesis 2 

Reestablishing a persistent nearshore positive 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 Biscayne Bay and Florida Bay. 

Hypothesis 3 

CERP implementation will lead to an expanded 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 water destined for estuaries is routed through 

new/restored coastal marshes, which will reduce sediment loads and areas with soft, 

unconsolidated substrate. 

Rationale: High sediment loads and benthic “muck” accumulation can deleteriously 

affect oyster recruitment, growth and survival. Reducing the loads will improve oyster 

spat recruitment and 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. Presently the sources are the 

canals. When freshwater creeks provide a more continuous source of fresh water, the 

manatees will orient toward the creek mouths and away from the canals. 

9.3.11 Toxins and Contaminants 

Because contaminants are conveyed to the estuaries through surface and ground-water 

flux, changes in distribution or sources of freshwater 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: Accumulated toxicants and other contaminants 

will eventually cause stress in organisms. Stress would initially be expressed 

biochemically as changes in osmoregulation, clinical hematology, immunology, and 

histopathology, etc. Biochemical and physiological changes could lead to adverse effects 

on survival, growth, development and reproduction. The level of stress created by 

divalent metals would depend upon their bioavailability, a function of partition 

coefficients and factors influencing equilibrium (e.g., redox potential); Organismal 
 

MAP, Part 2 – Draft Final 136 December 2006 

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 Uncertainties 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 

 Proposed 
 

MAP, Part 2 – Draft Final 137 December 2006 

Figure: 9-3-5: Hypothesis Flow Chart for Toxins and Contaminants in the SE 
 

MAP, Part 2 – Draft Final 138 December 2006 

9.3.13 Toxins and Contaminants Hypotheses 

• CERP is going to change the quantity, timing and distribution of in flow to the 

southern estuaries and the source of this freshwater is expected to include waste 

water reuse and both urban and agriculture runoff, which may increase the 

contaminant load to the estuaries. 

• Water will be routed through 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 wetland soils and vegetation may take up 

and retain organic contaminants and heavy 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 bioassays (.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 loading 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 following 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 affected (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 concentrations of heavy metals and organic 

contaminants.