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Project Work Plan

Department of Interior USGS GE PES

Fiscal Year 2007 Study Work Plan

Study Title: Scientific and Technical Support for the Joint Ecosystem Modeling Laboratory
Study Start Date: FY 05/06 (Year 1); FY 06/07 (Year 2); FY 07/08 (Year 3); FY 08/09 (Year 4); FY 09/10 (Year 5)
Study End Date: FY 09/10
Location (Subregions, Counties, Park or Refuge): The boundaries for the Joint Ecosystem Modeling Laboratory are system-wide and include all of the boundaries defined by the South Florida Ecosystem Restoration Initiative, Comprehensive Everglades Restoration Plan, and the Multi-Species Recovery Plan.
Principal Investigator(s): Kenneth Rice, U.S. Geological Survey, Florida Integrated Science Center, Gainesville, FL
Project Officer: G. Ronnie Best, U.S. Geological Survey, Greater Everglades Priority Ecosystems Science (GE PES) Initiative, Fort Lauderdale, FL
Study Personnel: Don DeAngelis, USGS; Jerry Lorenz, National Audubon Society; Dale Gawlik, Florida Atlantic University; Greg Kiker, University of Florida, Frank Mazzotti, University of Florida; Laura Brandt, USFWS; Nate Dorn, Florida Atlantic University; Leonard Pearlstine, University of Florida, Carl Fitz, University of Florida
Supporting Organizations: University of Florida, Florida Atlantic University, Nova Southeastern University, USGS, USNPS, USFWS, USACOE, SFWMD
Associated / Linked Studies: Across Trophic Level System Simulation, Southwest Florida Feasibility Study

Overview & Objective(s): Ecosystem models are needed for evaluation and assessment of alternatives for restoration of Greater Everglades ecosystems. We need to determine current capabilities, and current and future needs for ecosystem models. Project evaluation will require the ability to compare restoration alternatives using quantitative and visual methods, and to convey the information learned to the appropriate user. The Interagency Modeling Center (IMC) has the responsibility to approve and apply hydrological and ecological models in support of the Comprehensive Everglades Restoration Plan (CERP). The Joint Ecosystem Modeling Laboratory (JEM Lab) will continue its responsibility of developing models and performing initial scenario evaluations as part of the process of testing, calibrating, validating, verifying, and improving models. Figure 1 shows how the IMC and JEM Lab are being integrated.

The objectives for the JEM Lab for FY 07/08 (Year 3) are: 1) to develop methods of scenario evaluation and decision support, and 2) provide oversight and coordination of modeling activities.

Project Background and Relation to CERP: A key component of CERP is the requirement for ecosystem models for project evaluation and assessment. Project evaluation includes forecasting effects of restoration alternatives and provides a basis for comparing alternatives. Project assessment occurs post project and requires more quantitative models of performance measures as a basis for setting restoration targets and assessing progress. The role of the JEM Lab is to provide research and development of ecosystem models to meet evaluation and assessment needs.

Flowchart showing Integration of the Interagency Modeling Center and the Joint Ecosystem Modeling Laboratory
Figure 1. Integration of the Interagency Modeling Center (IMC) and the Joint Ecosystem Modeling Laboratory (JEM Lab). [larger image]

Specific Relevance to Major Unanswered Questions and Information Needs Identified:

Relevance to DOI Science Plan: The study supports the DOI Science Plan by developing integrated evaluation and assessment tools to support landscape scale and project level decision-making.

The study supports the DOI Science Plan as it: 1) provides assessment tools that are a critical priority for making landscape level restoration decisions that consider multiple species or trophic levels or that maximize biodiversity with an ecological system; 2) spatially models impacts of hydrologic targets on ecological conditions and critical links between hydrology, water quality and ecological responses; 3) models how hydrologic and water quality targets relate to the landscape-scale assemblages of habitats needed to support fish and wildlife resources and particularly wide-ranging species; 4) provides geographic information system mapping for habitat database of hydrologic restoration contributions to listed species; and 5) aids in the identification of key indicators of desired ecological responses.

Specifically, this study supports the following science plan information needs:

Landscape-Scale Modeling
Critical Improved ecological models
Critical Integrated hydrology / water quality / ecology models
Critical Improved accessibility of modeling data
Critical Spatially explicit habitat suitability index models: indicator species sensitive to hydrologic change
Critical Incorporation of models into the monitoring and adaptive assessment program

This study supports information needs for activities that impact ecological communities. The decision aids and methodologies for decision-making are implicit in the DOI Science Plan which requires that gathered science be integrated and applied to restoration. The ecological modeling, synthesis of science information, and application of decision aids specifically supports CERP as it (1) helps with prioritization of science resource allocations; (2) helps decision-makers in establishing specific goals and objectives in the context of conflicting priorities and adaptive management; and (3) provides a systematic and documented procedure to evaluating alternatives for what actions will restore, protect, and manage natural resources in South Florida.

Relevance to MAP: This study supports the applied science strategy for monitoring and assessment plans by providing a quantitative approach for integrating hydrological and ecological models to establish targets for performance measures as defined by the Conceptual Ecological Models (CEM). Figure 2 shows the relationship of ecosystem models to MAP and CEM's.

Flowchart showing the relationship of ecosystem models to the conceptual ecological models and the Monitoring and Assessment Plan
Figure 2. Relationship of ecosystem models to the conceptual ecological models and the Monitoring and Assessment Plan [larger image]


Task 1: JEM administration and oversight.
Task Funding:
USGS Priority Ecosystems Science
Task Leader: Laura Brandt
Time Frame for Task 1: FY 05-09
Task Personnel: Don DeAngelis, Ronnie Best, Frank Mazzotti

Task Summary and Objectives: Administration and oversight of the JEM Lab will be a complex task that will require coordination among the different entities involved, and may on occasion require outside expertise and advice. The purpose of this task is to form an organizing council to oversee the JEM Lab and to determine needs for and to perform administration, oversight, and review.

Work to be undertaken during the proposal year and a description of the methods and procedures: The organizing council will continue selected current projects (see task 2) and initiate new projects with a small group of principal investigators. The council will provide oversight and review of all projects.

Specific Task Product(s):

Product Delivery Date
1st progress report Month 4
2nd progress report Month 8
Annual report/fact sheet Month 12

Task 2: Develop approaches and models to evaluate alternatives for ecosystem restoration and to communicate results to decision and policy makers.
Task Leaders: Don DeAngelis, Laura Brandt
Time Frame for Task 2: FY 05-09 (2.1, 05-08; 2.2, 06-08; 2.3, 05-08, 2.4, 05-08; 2.5, 07-09; 2.6, 05-09)
Task Personnel: Jerry Lorenz, Greg Kiker, Leonard Pearlstine, Dale Gawlik, Frank Mazzotti

Task Summary and Objectives: The applied science strategy for restoration of Greater Everglades ecosystems requires that alternatives be evaluated and compared for their impacts on natural systems and that ecosystem response to selected alternatives be assessed. It is important to not only do scenario evaluation and assessment but to be able to communicate information to the correct consumer. The objectives of this task are to develop models and methods for scenario evaluation and assessment and to craft a decision support system to transfer evaluations and assessments of restoration alternatives to decision makers.

Work to be undertaken during the proposal year and a description of the methods and procedures: The work to be undertaken in FY 07/08 (Year 3) is divided into the following subtasks.

Subtask 2.1: Response of roseate spoonbills nesting in Florida bay to hydrologic restoration: A performance measure of Everglades restoration - This project is designed to evaluate effects of hydrologic restoration on nesting distribution and success of Roseate Spoonbills (Ajaia ajaia) in Florida Bay and surrounding mangrove estuarine habitats. Previous monitoring of Roseate Spoonbills in Florida Bay over the past 50 years has shown that this species responds markedly to changes in hydrology and corresponding changes in prey abundance and availability. Shifts in nesting distribution and declines in nest success have been attributed to declines in prey populations as a direct result of water management. Consequently, the re-establishment of spoonbill colonies in northeast Florida Bay is one change predicted under a conceptual model of the mangrove estuarine transition zone of Florida Bay. Changes in nesting distribution and success will further be used as a performance measure for success of restoration efforts and will be incorporated in a model linking mangrove fish populations and spoonbills to alternative hydrologic scenarios.

The primary objectives of this task are to (1) quantify the changes in spatial distribution and success of nesting spoonbills relative to hydrologic patterns, (2) test hypotheses about the causal mechanisms for observed changes, (3) establish a science-based criteria for nesting distribution and success to be used as a performance measure for hydrologic restoration, and (4) estimate demographic parameters. To meet these objectives, we will use a combined field/modeling approach. Based on previous and concurrent research, hypothesized relationships between hydrology, fish populations, and spoonbill nesting distribution and success will be expressed in a simple, but spatially explicit, conceptual model.

Subtask 2.2: Decision support tools for adaptive ecosystem management - The conceptual foundations of risk and uncertainty are based in the fields of engineering (e.g., structural and nuclear engineering) and the environmental sciences related to chemical pollution (e.g., environmental toxicology). More recently, interest has been building to apply these same principles and approaches to a broader collection of environmental problems (e.g., habitat loss, modification and restoration, natural resource management, threatened and endangered species management). Along with increased interest for a broader application of structured, systematic and quantitative assessment, emphasis is also being given to performing such evaluations within an adaptive or comparative framework to provide a more comprehensive analysis of management alternatives being considered by decision makers. New adaptive decision frameworks are being designed to integrate information about risk, uncertainty, ecological processes and endpoints, socioeconomic factors and stakeholder values to organize and structure decision processes. Given that both stakeholders and outside reviewers are increasingly requiring that risk and uncertainty be clearly articulated in model simulations and decision-making, a systematic multi-criteria decision analysis (MCDA) framework would be useful within adaptive management efforts to complement on-going model development and integration activities. The specific objectives of the subtask are (1) Establish and test a set of decision management/support tools (including both software and hardware) to integrate discipline-specific information and decision preferences within the DAMP and (2) Facilitate several meetings or small workshops to introduce MCDA principles and to establish the DAMP decision objectives, criteria and ecosystem information into an MCDA decision software framework.

Subtask 2.3: Computer Simulation Modeling of Wading Birds of the Everglades/Big Cypress Region - The restoration of the Everglades and conservation of wading birds requires understanding how different water management strategies will affect foraging and breeding success of wading birds. We propose to use long term research and monitoring data on wading birds in southern Florida to complete a landscape model to evaluate restoration alternatives in Everglades wetlands and to extend the model to Big Cypress wetlands.

Subtask 2.4: Habitat suitability model for Everglades crayfish - Habitat suitability models for crayfish (Everglades crayfish, Procambarus alleni and Slough crayfish, Procambarus fallax) will be useful for comparing restoration alternatives in the Everglades. These species make up a significant fraction of the invertebrate biomass in the Everglades sloughs and prairies and can dominate invertebrate biomass in some shorter hydroperiod wetlands. They have been listed as critical features of the secondary production linked to success of wading birds and other fauna. The existing crayfish index model was developed in 1998. Since then, a number of field studies have been completed that provide new information for improved modeling of both species. Developing spatially and temporally explicit HSI models that predict relative crayfish abundance from environmental drivers (e.g., hydrology) is the objective of this project.

Subtask 2.5: Ecological assessment models - Once alternatives are selected, plans developed, and projects implemented, we have to address the question: are we successful? Is the ecosystem responding as we think it should? The Everglades Monitoring and Assessment Plan (MAP) is designed to address those questions. An important component of the MAP is establishing performance measures for ecosystem restoration and targets for those performance measures. The purpose of this subtask is to develop assessment models that will forecast responses of selected performance measures to restoration plans in a manner that is testable through research and monitoring. These assessments models also can be used to set hypothetical targets for restoration.

Subtask 2.6: User interface - A graphically-based, spatially referenced interface will be developed to integrate hydrological and ecological models. The interface will be able to input and output a variety of formats including ATLSS, ESRI grid, and ASCII files. The interface will allow users to compare multiple alternatives including current conditions and no action. The output will be graphical, with maps designating areas where change occurred and numerical. Since the interface will be spatially referenced, it also will generate habitat units in terms of area affected. An additional feature of the interface will be a project based accounting system for comparing alternatives. This relational database will link numerical and graphical outputs in a manner designed to facilitate retrieval, display, and evaluation.

Specific Task Product(s):

Product Delivery Date
1st progress report Month 4
2nd progress report Month 8
Annual report/fact sheet Month 12

Task 3: ELM support of ecological models for Everglades restoration
Task Funding: USGS Priority Ecosystems Science
Task Leader: Carl Fitz, University of Florida
Time Frame for Task 3: FY 07-08
Task Personnel:

Task Summary and Objectives: Applications of the Everglades Landscape Model (ELM), which simulates the dynamic ecosystem interactions among hydrology, water quality, plants, and soils at decadal time scales in a regional landscape may address several gaps in ecological modeling capabilities. The proposed work is considered within a framework of three major Tasks: 1) Understanding: Integrate Everglades Depth Estimation Network (EDEN) and ELM estimates of hydrologic and other ecological attributes of the Everglades; 2) Educating: Train agency modelers in advanced ELM applications; and 3) Applying: Provide regional ELM hydrologic applications at 500 m grid resolution.

Work to be undertaken during the proposal year and a description of the methods and procedures: The work to be undertaken in FY 07/08 (Year 3) is divided into the following subtasks.

Subtask 3.1: EDEN-ELM Integration - The Everglades Depth Estimation Network
(EDEN, http://sofia.usgs.gov/eden/) may be considered a (largely) correlative model of the spatial and temporal distribution of water stage and depths in most of the greater Everglades region. Similarly, the Everglades Landscape Model (ELM, http://my.sfwmd.gov/elm) estimates the spatio-temporal distribution of water stage and depth, albeit using more mechanistic algorithms. It is anticipated that the EDEN will serve as a unified framework for integrating ecological research with near-real time hydrologic attributes in the Everglades, in addition to being used to help assess the status of Everglades restoration projects. While the ELM is available to help evaluate the relative benefits of future plans for water management alternatives (see subtask 3.3), one of its primary goals is parallel to that of EDEN, i.e., the ELM is intended to also be an integrative framework for assessing the importance of multi-decadal interactions among the physical, chemical, and biological components of ecosystems distributed through the region. From a conceptual or theoretical perspective, there are strengths and weaknesses in both EDEN and ELM estimates, with each approach designed for different application goals. But beyond each model's specific goals, their integration may lead to new insights.

The result(s) of this subtask will be a consistent framework for better understanding spatial and temporal changes in land surface elevation, water levels, water quality, and aspects of plant/habitat distributions within most of the greater Everglades region. While EDEN-derived hydrologic attributes will aid researchers in assessing near-term hypotheses regarding cause-and-effect within a regional landscape, ELM ecological simulations will help extrapolate such process-oriented results to longer-term, multi-decadal ecosystem responses in the greater Everglades landscape. Completion of this subtask will include: reconciling topography data, integrating EDEN-ELM data sets by providing analysis of spatio-temporal consistency of water depth estimates from EDEN and ELM for their time domains, and providing temporal summaries of ELM output of ecological Performance Measures for incorporation into EDEN framework, with summaries of the apparent effects of ecological process feedbacks on hydrology, water quality, land elevation, and vegetation.

Subtask 3.2: ELM Training - The proposed advanced training in the use of the Everglades Landscape Model (ELM, http://my.sfwmd.gov/elm) is intended to expand on and enhance the prior training on ELM application that is planned (for August 2007 by the Interagency Modeling Center at the South Florida Water Management District). One of the primary goals of the proposed training is to expand the number of scientists and engineers who possess significant understanding of the hydrologic and ecological modeling capabilities of the ELM. While the priorities and budget at the South Florida Water Management District (SFWMD) may not immediately allow such investment, it is anticipated that the proposed training will provide a core group of modelers with improved understanding the complexities of regional hydro-ecological modeling via the ELM.

The result(s) of this subtask will be some students/trainees who are capable of preparing, running, and interpreting output from the regional ELM, either at the 500 or 1000 m grid scales (see subtask 3.3). This objective will likely be met for a somewhat limited subset of students who have prior experience in spatio-temporal hydrologic and/or ecosystem/landscape modeling. The initial subtask will involve the determination of the scope of the training, based on results of the initial training in August 2007 and agency needs. As with the initial August 2007 training sessions, the advanced sessions will attempt to be inclusive of individuals with somewhat limited experience in dynamic spatial modeling of hydrology and ecology.

Subtask 3.3: Fine-scale ELM Hydrology - The South Florida Water Management Model (SFWMM) forms the basis of planning alternatives to "restore" the greater Everglades region. While this simulation tool is the best available method to make (relative) predictions of managed hydrology for Future Project alternatives, the 10 km2 model grid resolution was not intended to meet all of the needs of comprehensive ecological analysis. To best meet specific objectives, there are ecological models hosted by the Joint Ecological Modeling (JEM) Lab that require a grid resolution that is at most 500 meters on a side, or 0.25 km2. For recent project evaluations, an innovative method was used to rescale the coarse scale SFWMM hydrologic outputs to the requisite 500 m resolution (see the "High Resolution Topography/Hydrology" documents at http://atlss.org). A variety of logistical and data-related concerns led the JEM Lab to seek additional methods to compute fine-scaled water depths in the Everglades landscape, given a SFWMM simulation of managed flows for any particular Future Project evaluation.

The proposed method of obtaining fine-scaled, 500 m grid hydrology is to refine the Everglades Landscape Model (ELM, http://my.sfwmd.gov/elm), in order to run regional ELM simulations at that resolution (instead of the current 1000 m resolution for the regional application). The layered 2D dynamic hydrology of the ELM includes overland, groundwater, and canal flows, and vertically integrates surface and ground water. The result(s) of this subtask will be an application of the regional (>10,000 km2) ELM at a 500 m grid scale, with (complete model and) output from this Open Source application made available for input to other ecological models for CERP and other Everglades restoration projects.

Specific Task Product(s):

Product Delivery Date
1st progress report Month 4
2nd progress report Month 8
Annual report/fact sheet Month 12

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Last updated: 04 September, 2013 @ 02:09 PM(KP)