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Project Work Plan

U.S. Geological Survey Greater Everglades Science Initiative (Place-Based Studies)

Fiscal Year 2004 Project Work Plan



Project Title: Across-Trophic-Level System Simulation (ATLSS) for the Wetland Systems of South Florida

Project Start Date: September 1, 2003 Project End Date: June 30, 2006

Project Funding: USGS Place-Based Studies Initiative

Principal Investigator: Donald L. DeAngelis
Email address:
Phone: 305-284-1690 Fax:

Overview of the ATLSS Program

The ongoing goals in the ATLSS Program have been to produce models capable of projecting and comparing the effects of alternative hydrologic scenarios on various trophic components of the Everglades. The methodology involves: 1) a landscape structure; 2) a high resolution topography to estimate high resolution water depth across the landscape; 3) models to calculate spatially explicit species indices (SESI) for breeding and foraging success measures across the landscape; 4) spatially explicit individual-based (SEIB) computer simulation models of selected species populations; and 5) ability to plug into variety of visualization and evaluation tools to aid model development, validation, and comparison to field data. Included in this are numerous sub-projects for different species, vegetation succession, analysis of alternative approaches to developing high resolution, models which deal with estuarine systems, methods to allow users from a variety of agencies to access and run the models, and methods to enhance the computational efficiency of the simulations. The continuing general objective is to provide a flexible, efficient collection of methods, utilizing the best current science, to evaluate the relative impacts of alternative hydrologic plans on the biotic systems of South Florida. This is done in a spatially-explicit manner which allows different stakeholders to evaluate the impacts based upon their own criteria for the locations and biotic systems under consideration.

Currently, two important new developments are taking place. First the ATLSS models will soon migrate to a Web-based availability, so that they can be run remotely for various hydrologic scenarios and a set of different assumptions. Second, a vegetation succession model is being completed, which will allow projection of changes in vegetation types across the Everglades landscape as a function of changing hydrology, fire frequency, and nutrient loading.

These dramatic improvements in ATLSS models that will be entailed by these current developments are a strong motivation for completing important upgrading and validation testing of the existing ATLSS models and filling in several key gaps in the models. There are currently only limited funds to do this, so a carefully focused request for funding of several vital areas needed to complete the ATLSS program is proposed here. The specific projects, which are budgeted individually below, are the following.

Project 1. ATLSS Model Use in CERP Evaluations, Model Testing and Extension to Web-Based Interface This project involves completing the estuarine fish model and linkage with SICS, and a user interface for the Cape Sable Seaside Sparrow model, SIMSPAR

Project 2. Development of an Internet Based GIS to Visualize ATLSS Datasets For Resource Managers. This project involves ATLSS Data Viewer improvement, training, expansion to web.

Project 3. Spatial Decision Support for Biodiversity and Indicator Species Responses to CERP Project Activities. This project involves putting ATLSS and other models and data into a Decision Support System

Project 4. Integrating Wading Bird Empirical Data into a Model of Wading Bird Foraging Success as a Function of Hydrologic Conditions. This project involves using the most recent data on wading bird foraging parameters to complete the development of the wading bird SESI and Demographic Models.

Information Needs and Uses of ATLSS Program

It was identified early in the planning for the Everglades Restoration that models would have to play a key role in the process of choosing a restoration plan and evaluating its success. The ATLSS models have done and are doing this in the following ways, which are only a part of the overall products from ATLSS.

  • Over thirty detailed biotic assessments of alternative hydrologic plans were provided throughout the Restudy and Mod Water design process
  • A general modeling protocol was developed to link dynamic ecological models to spatial information, including that available through a geographic information system
  • High resolution topography and water depths for interpretation of alternative hydrologic plans at appropriate scales was developed and applied throughout the Restudy and Mod Water design processes
  • Spatially explicit, size-structured fish functional group model were applied throughout the Restudy design process, providing a relative assessment of alternative plans effects on availability of prey for wading birds
  • Spatially explicit species index (SESI) models for short- and long-legged wading birds were applied throughout the Restudy and Mod Water design processes, providing a relative assessment of alternative plans
  • Spatially explicit species index model and individual-based model for the Cape Sable Seaside Sparrow were applied throughout the Restudy and Mod Water design processes, providing a relative assessment of alternative plans
  • Spatially explicit species index model for the Snail Kite was applied throughout the Restudy and Mod Water design processes, providing a relative assessment of alternative plans
  • Spatially explicit species index model for alligator was applied to various Restudy plans, providing a relative assessment of alternative plans
  • Spatially species index model for two species of crayfish has been developed.
  • The above SESI models have been converted into a form that can be used independently by agencies and turned over to Everglades National Park, the U.S. Fish and Wildlife Service, and the South Florida Water Management District.
  • Models for conducting population viability analyses of various endangered species (Cape Sable Sparrow, Florida Panther, Snail Kite) under alternative hydrologic management were developed.
  • A tracking tool, PanTrack, was developed for telemetry data on Florida panther providing spatially-explicit analysis of panther movements and behavior related to demographic and habitat information. This has been provided to the Fish and Wildlife Service.
  • A paper based on analysis of Florida panther habitat has been accepted by the journal Conservation Ecology
  • Development and maintenance of as a data repository for model results and analyses related to ATLSS is being performed.
  • An estuarine fish model has been completed and is being used by Jerry Lorenz of the Audubon Society.

ATLSS Program: Key Findings from First 6 Years

The ATLSS Program has received support from the Critical Ecosystems Studies Initiative (CESI) for the past 6 years. The program has produced a set of models of spatially explicit species index, population demography, and ecosystem process models that are available for application to the Comprehensive Everglades Restoration Program (CERP). In addition, the program has supported field studies designed to produce data for model construction and validation. The main products of the modeling work are described below.

Spatially Explicit Species Index (SESI) Models. These models quantify relative effects of hydrologic conditions on the habitat suitability of species. There are several currently available ATLSS SESI models:

  • Cape sable seaside sparrow breeding potential index (Version 1.1)
  • Snail kite breeding potential index (Version 1.1)
  • Long-legged wading bird foraging condition index (Version 1.1)
  • Short-legged wading bird foraging condition index (Version 1.1)
  • Empirically-based fish biomass index (Version 1.1)
  • White-tailed deer breeding potential index (Version 1.1)
  • American alligator breeding potential index (Version 1.1)
  • Everglades and slough crayfish (Version 1.1)
  • Apple snail SESI model (Version 1.1)

The ATLSS SESI models accomplish the following. They produce values for habitat suitability ranging from 0.0 to 1.0 for all 111,000 cells of the 500 x 500 m array. These can be calculated for every individual year in the historical 31-year sequence (1975-1995), or averages can be taken over any set of years (e.g., wet years, dry years, all 31 years). The SESI models are intended to be used to make relative comparisons between scenarios, not to produce absolute evaluations of habitat quality. The output can be viewed using the ATLSS Data Viewer, which allows viewing at any scale and performing of statistics. The ATLSS Data Viewer is available to all agencies that are interested. Training sessions can be scheduled when requested


Spatially Explicit Demographic Models. There are currently three available ATLSS Demographic Models. The ATLSS demographic models are spatially explicit individual-based (SEIB) models of the dynamics of the populations:

  • Cape sable seaside sparrow demographic model (SIMSPAR - Version 1.3)

The spatially explicit individual-based model, SIMSPAR, was developed as a management tool for the Cape Sable seaside sparrow (Ammodramus maritimus mirabilis) of the Florida Everglades, as part of the Across Trophic Level System Simulation (ATLSS) package of models. Concern for this endangered seaside sparrow centers on a reversing the declining population trend and developing appropriate management policies for hydrology and fire. A detailed approach to modeling the population viability under different water regulation scenarios is feasible because the main threat to the population is disruption of reproduction due to flooding, which can be simulated through a combination of hydrologic modeling and modeling of the reproductive phase of the sparrow life cycle. The behavior of the sparrows during reproduction and the influence of water levels on the initiation or continuation of reproductive behavior are relatively well known from field studies.

  • Snail kite demographic model (EVERKITE - Version 3.1)

EVERKITE (Version 3.00) is an individual-based, spatially explicit model that aims at predicting temporal and spatial patterns of snail kite numbers under various hydrological scenarios. It does so by following the lives of individual kites on a weekly time step. The spatial structure of the model consists of a network fifteen wetlands, each representing one of the major wetlands inhabited by snail kites in southern and central Florida. This model was developed for application to evaluating scenarios for the Comprehensive Everglades Restoration Program.

  • Alligator demographic model (Version 1.1)

The alligator demographic model (ADM) uses water data from historical measurements, and alternatively simulated water data from the various restoration alternatives. Daily water levels were modeled by the South Florida Water Management District. The model also obtains input from the ATLSS American alligator SESI production index (API). The API model uses the water data in combination with the underlying topography and vegetation distribution to predict the probability that (1) a female alligator in a model cell will breed and construct a nest that year, (2) that the nest will not flood, and (3) that the habitat is favorable for nesting. The core of the ADM is a 3-D matrix that records the density of each stage of alligator in each 500 x 500 m spatial location. The density matrix interacts with survival and condition matrices calculated for each time step based on water level, crowding, etc. To disperse alligators, a discrete spatial convolution method is used. Output of the model is a 3-D alligator density matrix, with space along two axes (x and y), and the stage classes along the third axis (z). Also included in the matrix is a "running average" of the historical health and survival rates of each stage in each cell. This construct can easily be summed to obtain the total alligator population, or subsampled to verify agreement with field data. Instantaneous densities and local rates-of-change can be calculated from this model.

Spatially Explicit Functional Group Models. The ATLSS Structured Functional Group models simulate the size-structured and biomass dynamics of the population

There is currently one available ATLSS Structured Functional Group model:

  • Freshwater fish dynamics (ALFISH - Version 3.1.17)

The ATLSS Landscape Fish model (ALFISH) has as its main objective the capability to compare in a spatially-explicit manner the relative effects of alternative hydrologic scenarios on fresh-water fish densities across South Florida. Another objective is to provide a measure of the dynamic, spatially-explicit food resources available to wading birds. By providing a model for the key resource base for wading birds, ALFISH allows the linkage of the hydrologic effects on fish densities with models for wading bird foraging. ALFISH has been developed in regular consultation with several field biologists and has made use of a variety of data sources on fish distributions to estimate parameters.

GIS Animal Movement Tracking Tool. As a component of the development of population models, a GIS tracking tool has been developed to analyze radio-monitoring data of animals.

  • Florida panther tracking tool (PANTRACK - Version 1.1)

This tool is designed to analyze radio-telemetry monitoring data, such as that collected for Florida panthers, and display observations overa variety of background maps. Subsetting of monitoring data, by time periods and/or by individuals, allows movement patterns to be analyzed and interpreted in terms of factors such as habitat variability, seasonality, age, gender, reproductive status, and causes of mortality. PANTRACK can help wildlife biologists and modelers translate raw location data into information about key animal behaviors, such as territoriality and movement patterns, breeding, predation, social interactions, dispersal patterns, aggressive encounters and habitat use. This information can be used to expand what is known about the animal being tracked, suggest topics for research, guide management decisions, and develop behavior rules for predictive models to evaluate the effects of various management options. PANTRACK was developed to help define panther behavior rules for the spatially explicit, individual-based ATLSS Deer/Panther model. The effectiveness of individual-based models depends on the availability of detailed observations about individuals on the landscape, and on the ability to find patterns in these observations that provide insight into key animal behaviors.

Landscape Models: There are background models that provide landscape information for other ATLSS models:

  • High Resolution Topography (HRT - Version 1.4.8)
  • Vegetation productivity (HTDAM -Version 1.1)
  • High Resolution Hydrology (HRH - Version 1.4.8)

Landscape structure and High Resolution Hydrology:
Two primary components of the ATLSS project have been development of methodologies for linking dynamic ecological models to spatially explicit information which can itself be dynamic, and development of a high resolution hydrology. The first of these, called the ATLSS Landscape Structure Model, provides the primary interface between all ATLSS component models and landscape data, as well as providing a framework for communication of spatially explicit information between ATLSS components. The High Resolution Hydrology model translates coarse resolution hydrologic information to a finer resolution appropriate for the biotic components in ATLSS.

Use of ATLSS Models. ATLSS model runs for scenario evaluations can be made in the following ways for particular models. The Snail kite demographic model (EVERKITE) is available in PC form for use (can be downloaded from Web) and user support for those wanting to use this model. Alternatively, this model will be run at the University of Miami and results posted. Currently, the remaining ATLSS models can be run at the University of Tennessee, which is funded to carry out several such runs. Results will be posted. Also, these models can be installed at agencies with Unix workstations. A NSF-funded project at the University of Tennessee is currently underway to allow dispersed resource managers to access remotely the capabilities of the SInRG (Scalable Intracampus Research Grid) at the University of Tennessee. This will allow users at resource agencies in South Florida, with relatively little computer expertise, to initiate ATLSS simulations on the computers at the University of Tennessee.

Documentation of ATLSS Models. Technical documentation of ATLSS models is available on the ATLSS web site (ATLSS.ORG) and listed in ATLSS Program Publications (available) - but will be improved. Open literature publications exist for the available ATLSS models. Nearly all models have appeared in open-literature, peer-reviewed papers (see ATLSS Publications). An internal USGS panel reviewed the ATLSS Program in May 2002. Additional review by the Model Refinement Team of CERP is planned.

Validation of ATLSS Models. Validation of models is an important issue. Some degree of model validation has been performed on some models (SIMSPAR, ALFISH). Model validation on other models will be performed depending on availability of data sets. Now data sets are becoming available for several species, and new data for others is being collected. A "validation tool", which can be applied along with the ATLSS Data Viewer, allows empirical data (e.g., nest success rate, fish biomass) to be compared spatially with SESI index values at any spatial scale. Statistical testing can be done via Excel spreadsheets. Validation is being done, or will be done soon on Cape Sable seaside sparrow, snail kite, and American alligator SESI models.

Key Current Progress

New Models. ATLSS models nearly completed or under development include:

  • Vegetation Succession Model (to be delivered in July 2003)

The development of a set of vegetative succession models for the main vegetative types in the Everglades region is generally regarded as being essential, if scientists and managers are to be able to project the possible effects of changes in the hydrology of the region. Vegetation responds sensitively to changes in hydroperiod and limiting nutrient concentration. Furthermore, important animal species, such as wading birds, the snail kite, and the Cape Sable seaside sparrow, have specific habitat needs that are tied to particular types of vegetation. The basic goal is to develop predictive vegetation succession models for the targeted habitats, describing how they are affected by changes in hydrology and available nutrients. Disturbance regimes are the third major landscape driver that we assume is strongly coupled to succession, so fire scenarios are also built into the models. Three basic community types will be included in the modeling. These are "pine/scrub/flatwood", "cypress forest", and "herbaceous plant communities". The model will cover most the natural areas in South Florida and will provide yearly estimates of vegetation at a 100x100 meter resolution. The background literature review for this model has been completed. The synthesis is available in two documents: "Plant Community Parameter Estimates and Documentation for the Across Trophic Level System Simulation (ATLSS)", and "Nutrient and Fire Disturbance and Model Evaluation Documentation for the Across Trophic Level System Simulation (ATLSS)". Both of these reports were prepared by Paul Wetzel. The first of these documents has been peer-reviewed, while the second is currently in review. These documents provide the foundation upon which the vegetation succession model will be constructed. These documents provide estimates for model parameters, indicate which biotic and abiotic factors should or should not be included in the model, and will guild the approaches used to model vegetation succession.

  • American Crocodile Model (to be delivered after review)

To answer the question of how the crocodile population will respond to alterations in hydrology we developed a spatially explicit individual based model designed to relate water levels, salinities, and dominant vegetation to crocodile distribution, abundance, population growth, individual growth, survival, nesting effort, and nesting success. The core of this model assumes that this relationship applies to the field, and to some extent, to individuals of all sizes. Four different combinations of base parameterizations and initial population size were examined with sensitivity analyses and a factorial manipulation of model salinities, to evaluate the effects of each on population size, nest number, and survivorship of young of the year crocodiles. The model will be linked to the SICS hydrology and salinity model.

  • Crayfish Structured Population Model (to be delivered in late 2003)-

During late 2002 and early 2003, a metapopulation model was developed to describe two Everglades crayfish species (Procamburus spp.). Metapopulation models have been used extensively to study populations that undergo periodic colonizations and extinctions in different sites. The spatial configurations of populations are important in metapopulation dynamics because suitable, empty habitat is most likely to be colonized from adjacent populations. Two criteria must be satisfied for successful colonization-suitable habitat and a colonization source. To investigate the spatial ecology of two crayfish species in the Florida Everglades, a spatially explicit metapopulation model with environmental fluctuation was explored. A two-stage estimation process was. First, the probability of colonization and the probability of persistence were estimated as a function of time since dry down. The Everglades crayfish (Procambarus alleni) had the highest probabilities of persistence and colonization when the years since dry-down were low, whereas the slough crayfish (P. fallax) had highest probabilities of colonization and persistence when the years since dry-down were high. In the second stage of estimation, the probability of colonization from the first analysis was modified to incorporate a ‘neighbor effect’, namely the effect of surrounding cells.

Improvements in Use of Models. User interfaces for running models and analyses have been developed.
  • Network access to ATLSS models (to be delivered in September 2003)
Progress is being made in making ATLSS runs available on the Web through new software (NetSolve and IBP). That is a huge step and is real state-of- the-art work. Users will be able to runfew different versions of the models, with different assumptions, and ill be able to look at the various individual 'layers' of the model output, as well as the whole index. Four projects needed to continue application of the ATLSS Program to CERP are described below. These projects are all deeply integrated and each will involve close interaction between the collaborating research groups at The University of Tennessee, University of Florida, Florida Atlantic University, and National Wetland Research Center.

Summary of ATLSS Program Needs from USGS Place-Based Funding

1. Project Title: ATLSS Model Use in CERP Evaluations, Model Testing and Extension to Web-Based Interface
Principal Investigator: Prof. Louis J. Gross, University of Tennessee, Knoxville, TN 37996-1610,
Duration of Proposed Work: July 1, 2004 - June 31, 2006

2. Project Title: Development of an Internet Based GIS to Visualize ATLSS Datasets For Resource Managers
Principal Investigator: James B. Johnston, USGS-BRD National Wetland Research Center
700 Cajundome Road, Lafayette, Louisiana 70506
Duration of Proposed Work: May 1, 2004 - April 30, 2006

3. Project Title: Spatial Decision Support for Biodiversity and Indicator Species Responses to CERP Project Activities
Principal Investigators: Leonard Pearlstine and Frank Mazzotti, University of Florida, 3205 College Ave, Davie, FL 33314 (954) 577-6304
Duration of Proposed Work: January 1, 2004 - December 31, 2005

4. Project Title: Integrating Wading Bird Empirical Data into a Model of Wading Bird Foraging Success as a Function of Hydrologic Conditions
Principal Investigator: Dale E. Gawlik, Florida Atlantic University, Boca Raton, Florida
Duration of Proposed Work: September 1, 2003 - August 31, 2005


Project Title: ATLSS Model Use in CERP Evaluations, Model Testing and Extension to Web-Based Interface

Principal Investigator: Prof. Louis J. Gross, University of Tennessee, Knoxville, TN 37996-1610,

Duration of Proposed Work: July 1, 2004 - June 30, 2006

Proposed Scope of Work

Task 1. Use of ATLSS Models in CERP, Testing Models Against Empirical Data, and Extension to Web-Based User Interface. Much of the empirical data needed to test the output of the SESI models has been collected over the period 1996-2000. This could not be used to test the SESI model output against because the South Florida Water Management Model (SFWMM) output was available only up to 1995. By the middle of 2003 output of the SFWMM-2000 (Version 5.5) will be available. This will make it possible to test the SESI models. This testing can be done by the University of Tennessee ATLSS group. However, this will be an intensive process that requires careful organization of model and empirical data, and development of statistical techniques for comparing these data. The second part of this task is the extension of models to interactive use through the web. A first version of this ATLSS Network Approach is now undergoing beta-testing and will be completed in September 2003. However continual improvements will be needed to make this approach optimally useful to CERP.

It is essential that the ATLSS models be run for all or a substantial number of the proposed CERP scenarios in 2003 and 2004. The University of Tennessee currently has $20K available for such model runs. This will probably not be sufficient for all of the demands on scenario evaluations. Some of the proposed $90K will support manpower to produce and post a large amount of SESI and other model output over the period 2003/2004.

ATLSS SESI model output is currently being used within the ATLSS DataViewer (a product of the NWRC staff of USGS) to allow ease of visualization of the basic yearly spatially-explicit indices produced by these models. Modifications to allow the output of other ATLSS models within this are underway, though the only effort to date has been with the ALFISH freshwater fish model. Yet to be developed are standards for visualizing the outputs of SEIB models, and that task will be ongoing during year one of the project. An additional task will be to include outputs from the ALFISHES estuarine fish model. A separate task concerns the development of a database structure for all ATLSS model output. Although a formal metadata structure has been established and utilized within the ATLSS models, there has not been any formal database constructed to maintain the results of ATLSS runs. With the decreasing cost of storage, it is now feasible to construct such a database (using Oracle), and allow web access to it from within the DataViewer to allow users to visualize alternative ATLSS model runs without having the files shipped to them on a CD. This database establishment effort will be ongoing throughout the two years of the project.

Task 2. Integrating Estuarine Fish Model (ALFISHES) with Southern Inland Coastal System (SICS) Model

The technical development of the estuarine fish model has been completed. However, testing, upgrading, and interfacing with the Southern Inland Coastal System (SICS) model and with users (e.g., Jerry Lorenz, Rob Bennetts) is still necessary. ALFISHES can be run remotely or on a PC, and is available to users.

Work has been done to try to get ALFISHES working correctly on the short-term without the SICS model. Hydrologic and salinity data from three of Jerry Lorenz's sites have been input to the ALFISHES, to generate fish densities in only these three sites (three pixels) over a multi-year period. This is being compared with empirical data on fish densities to see if the model is making prediction in the right ballpark. (Some modifications of ALFISHES will be needed to make it work for selected sites. In particular, consideration is needed of what assumptions to use regarding reintroduction of fish to a re-wetted cell following drying, when, since there will be no adjacent cells in the model.

It is anticipated that SICS will be providing 5-year outputs within a couple of months. It is essential that Jon Cline be able to interface SICS with ALFISHES and upgrade the model such that it can be used for scenario evaluations.

Task 3. Developing User Interface for Cape Sable Seaside Sparrow Model (SIMSPAR). The Cape Sable sparrow demographic model (SIMSPAR) is an excellent model that has undergone a great deal of testing. However, the model is not currently usable to a broad range of users. The effective use of SIMSPAR requires a good user interface that will adapt it to use on a PC. It is almost certain that this could be done within two to four months with an appropriate postdoctoral assistant.

Project Title. Development of an Internet Based GIS to Visualize ATLSS Datasets For Resource Managers

Principal Investigator: James B. Johnston, USGS-BRD National Wetland Research Center
700 Cajundome Road, Lafayette, Louisiana 70506

Duration of Proposed Work: May 1, 2004 - April 30, 2006

Proposed Scope of Work

The Across Trophic Level System Simulation (ATLSS) Program attempts to predict the responses of a suite of higher trophic level species to different alterations in the Everglades/Big Cypress region of South Florida to represent the biotic community and various factors that affect this community. A tremendous amount of digital data have resulted from running these scenarios. To make these data available to resource managers and scientists, the USGS-National Wetlands Research Center has developed the ATLSS Data Viewer System (ADV). It is a spatial query and visualization GIS tool that provides the capability of retrieving, displaying, and analyzing ATLSS model data by using a user-friendly graphical interface and project-oriented procedures: The project has

  • Designed a customized graphical user interface that makes the system user-friendly
  • Displayed the ATLSS SESI output data, performed analyses, and generated outputs that allow resource managers and decision makers to make informed decisions
  • Provided training courses for users.

The above goals have largely been completed. In addition, DVS has been upgraded to ATLSS Data Visualization System (DVS) 2.0. The upgrades include

  1. Addition of new base maps into the ATLSS DVS, such as Elevation Data from USGS, official version of GAP data, project boundaries for different projects within CERP, current satellite images.
  2. Addition to the DVS flow graphs and brief descriptions on SESI and other models.
  3. Use of DVS to visualize and analyze data from other ATLSS models like individual-based and dynamic model (ALFISH) added to the ATLSS DVS.
  4. Development of DVS's capability to input user's empirical data in order to determine the degree of correlation between models output and empirical data. Additional code will be necessary to allow users to import into the DVS a set of locations (UTM, decimal degrees, or degree, minute, second coordinates), extract ATLSS model values, and display the result or export it to external applications like MS Excel or the ATLSS Model Validation tool.
  5. Simplification DVS's capability of extracting mean index values based on user-defined areas.
  6. Development interface and functionality and upgrade code as needed to allow agencies capable of independently running ATLSS models (SFWMD and ENP) to read and display their runs into the ATLSS DVS.
  7. Improvement in the DVS user's Guide based on user's comments and suggestions.
  8. Improvement in the capability to display and analyze the output of the ATLSS simulation models

The ATLSS spatially-explicit species index (SESI) models were used in the Restudy evaluations and have continued to be used for subsequent evaluations. They are available for use in the many evaluations that must be made in the future. The ATLSS DVS developed by this project serves the following purposes

  • Providing easy access to much of the vast amounts of ATLSS models output;
  • Integrating ATLSS data with other spatial and non spatial data inside the same analytical tool;
  • Providing an easy-to-use, flexible, and effective tool to compare ATLSS model results for user-defined time intervals, scenarios, and geographic location through an heavily customization of graphical user interface and system functionality;
  • Focusing the analysis on specific sites by providing spatially-defined "on-fly" data statistics;
  • Supporting the process of making informed decisions by providing ready-to-use outputs like maps, graphs, tables;
  • Opening analysis results to external applications by providing saving capabilities to standard files format;
  • Minimizing the learning curve for users not highly trained in GIS by designing a task-oriented Graphical User Interface.

ATLSS Viewer has been developed by using ESRI-ArcView 3.2 GIS. Most procedures implemented in this project use raster-based functions provided by the ArcView extension Spatial Analyst 1.1. ATLSS Viewer provides the capability of converting binary raster files produced by running ATLSS models to ESRI ArcInfo grids. Annual data can be retrieved and displayed to show alternative water management changes and their effects on numerous species used in ATLSS, and compare numerous scenarios for one species. The viewer also allows the user to calculate average data based on specified time intervals or time points during the 31-years simulation period. Statistics and/or graph representations of the whole study area, or user-defined spatial subdivisions can be performed, displayed, and exported to other applications. Tables, histograms, maps, and metadata can be generated to report the comparison between a basic and an alternative scenario for the whole Restudy area or user-defined areas. A specific section of the project is devoted in providing detailed information about each ATLSS model included into the system. Several other procedures have also been developed to simplify project tasks and documents management.

The ATLSS Data Viewer system needs to be upgraded to allow a larger amount of ATLSS model output to be viewed and analyzed. More training sessions will be needed. Continued collaboration is needed between NWRC and the University of Tennessee group, Wolf Mooij, Ken Rice, and others to make sure that output from various ATLSS models is input to the Data Viewer. The Data Viewer must be extended to a Web-based system.

Although the ADV has been upgraded to display output of the ATLSS model ALFISH, it must be further upgraded to allow the display of other models, including both EVERKITE and the Alligator Demographic model.

Project Title. Spatial Decision Support for Biodiversity and Indicator Species Responses to CERP Project Activities

Principal Investigators: Leonard Pearlstine and Frank Mazzotti, University of Florida, 3205 College Ave, Davie, FL 33314 (954) 577-6304

Duration of Proposed Work: January 1, 2004 - December 31, 2005

Proposed Scope of Work

The objective of this project is to provide a working prototype spatial decision support system (SDSS) for impacts to biodiversity and indicator species in the landscape within and surrounding CERP projects. The proposed SDSS tools will be designed to assist managers and other users in understanding wildlife habitat response to hydropattern and land use changes. An integral task in the SDSS is the provision for assistance in defining the problem given uncertainty in the data and then providing problem specific models. Successful implementation of the SDSS presumes cooperative development with the users to meet resource manager’s needs.

Decision support systems (DSS) are broadly defined as computer-based systems used to aid decision makers using data and models to solve unstructured problems. These model and knowledge-based system tools become necessary when complex geographic or domain interrelationships are considered. The development of a computerized DSS makes economic sense in integrated Everglades restoration efforts because of the large amount of data that must be collected and processed to produce and analyze decision alternatives, decision-making procedures that are applied to many cases within a domain or periodically repeated, many potential users, short time frames for making critical decisions, the expense of accessing top-level expertise, and the possibility of a large number of alternative decisions with significant and different implications. This project is developing a spatial decision support system (SDSS) is proposed in which the decision models are tightly integrated with, or directly generated from, geographic information systems (GIS) analyses and display. This is integrating ATLSS and other models, as well as empirical data. The SDSS will incorporate analyses, but the scope and range of scales considered in the SDSS models will be carefully restrained to a specific subset of landscape problems. Part 1 of this work developed a framework for the SDSS. This will next be extended into concrete development of the SDSS.

This project addresses 2 high priority CESI science objectives: 3007-19, Monitor the status of indicator species, their communities, and species of special concern for evaluation of Everglades restoration success; and 3070-8, Develop and implement methodologies and decision support tools that will permit effective and timely assessment of CERP projects on DOI natural resources.

This project will develop a case study functioning spatial decision support system for a CERP project area using a modular architecture that allows rapid transfer of the prototype system to other project areas. The SDSS will assist managers in assessing issues and alternatives for wildlife habitat response to CERP project activities. Specific objectives in support of the goal include:

  • Habitat modeling of biodiversity (potential use of habitat by all native species, by guilds, and by species of special concern) and of indicator species (species most likely to respond to changes in the physical environment).
  • Make data, images, simulation models and textual information readily accessible through an intuitive user interface.
  • Provide a decision model for assistance in structuring the issues, designing and choosing among alternative actions, and resolving multiple, often conflicting, goals.
  • Facilitate adaptive management, depiction of uncertainty, and targeted monitoring.
  • Provide an adaptable, modular SDSS structure that allows incremental development, potential future interaction with other systems and various levels of sophistication.
  • Improve the effectiveness, thoroughness and documentation of decisions and the decision process.

The project area for prototyping the SDSS will be chosen as representative of diverse unstructured issues. The area will be selected with consultation and agreement from the RECOVER Leadership Group (RLG) and/or the RECOVER Regional Evaluation Team (RET). The study area will be defined for this project as the selected project area plus additional contiguous lands necessary to adequately model adjacent impacts of project activities.

Wildlife models to locate potential habitats suitable for the species will use land cover, hydroperiod, soils, and other available GIS data layers where appropriate. The wildlife models will allow for rapid incorporation of change scenarios from other existing models of land use and hydrology. Field surveys directed at sampling target species presence and abundance will validate the wildlife models. Field surveys will also address uncertainties in target species modeling parameters and be used to re-calibrate and improve the models in an adaptive approach.

The decision model will be selected after review of existing "off-the-shelf" knowledge-engines and DSS systems. The rationale is to not reinvent already effective solutions, but rather to wrap those solutions in an interface specific to the needs of the local projects. This approach is expected to reduce the time and costs of development and take advantage of solutions that have been proven in application. Development and programming will still be a major component of the project, however, as adaptation of the decision model goes through an evolutionary process of addressing local user needs, refinement and modification. Software development will be a dynamic process that responds to continuing user feedback as well as verification and validation of the refinements. Validation of the decision models will be performed with sensitivity analyses and empirical testing following accepted published methods.

The final report will include complete documentation of the final methods and programming code for both the wildlife habitat and decision models. All source code created for this project will be included. Field monitoring results will be summarized in GIS data layers and tables. Validation, verification and uncertainty analyses will be documented and summarized. The principal product will be a spatial decision support system for the selected project area, user documentation, a final workshop to introduce users to the system operation, and an example scenario, including GIS data layer inputs and outputs, using the SDSS to address a task or problem. Final products will include a manuscript submitted to a peer-reviewed scientific publication. Interim semi-annually reports will be provided to ensure communication between PIs and contract office technical representatives (COTR's). Annual reports will include data summaries that follow the data management policies of the SFNRC.

Project Title: Integrating Wading Bird Empirical Data into a Model of Wading Bird Foraging Success as a Function of Hydrologic Conditions

Principal Investigator: Dale E. Gawlik, Florida Atlantic University, Boca Raton, Florida
Duration of Proposed Work: September 1, 2003 - August 31, 2005

Project Scope of Work

Declining wading bird populations in the last century have been considered one of the most prominent signs of the degradation of the Everglades ecosystem. Consequently, recovery of these populations will be a key indicator of successful restoration efforts. It has been hypothesized that the specific mechanism by which Everglades degradation has led to declining bird populations is related to changes in hydropatterns. These changes have most likely altered the availability of prey to wading birds.

Prey availability is determined by both the abundance of prey and the vulnerability of prey to capture. Prey abundance is affected by factors such as nutrient levels and hydroperiod whereas vulnerability to capture is affected by such things as behavior of the prey species, water depth, vegetation density, and body size.

Each component of prey availability is affected differently under various water management scenarios. For example, management for long periods without severe drydowns changes the species composition of the fish community. Different species of fishes exhibit different behavioral response to predators, thus changing their availability to capture. Moreover, these behavioral differences of the prey may be dependent on water depths. When the water column is deep, social species like the golden shiner (Notemigonus crysoleucas) may occur in schools and present wading birds with a very different capture probability than more solitary fishes like the bluegill (Lepomis macrochirus). However, as the water level recedes, capture probabilities of the two species may converge.

Ongoing modeling efforts in south Florida, such as the Federal Across Trophic Level System Simulation (ATLSS) program, integrate information on hydrology and wading bird food availability to provide predictive power for future water management decisions. Currently, the biggest information gap limiting the wading bird component of ATLSS is foraging success as a function of prey availability and water depths. We conducted a series of experiments aimed at determining the effects of water management (manifested through changes in prey availability) on the use of foraging sites by wading birds. The wading bird data collected and analyzed provides strong evidence for the relationships of water depths, fish densities, fish sizes, and fish species to availability to wading birds.

These data complete what is needed to make the wading bird bioenergetic model developed by Wilfried Wolff a useful tool for science and management. The individual wading bird in that model is described by a set of species-specific rules that govern its behavioral activities. A model wading bird does not operate on a fixed time scale, because its behavioral activities are of different duration. Instead, the wading bird model uses an event-driven approach, in which each bird sets its own time scales depending on its current activities. In its current version, the wading bird model operates on spatial grid of 500 m x 500 m grid cells. The model keeps track of colony sizes and the number of nesting adults as well as the number of successfully fledged nestlings after the breeding season is over. Because energetic constraints drive most of their activities, in particular the onset and timing of nesting, different environmental conditions will lead to varying reproductive behavior and recruitment of young wading birds into the population.

  1. The basic structure of the wading bird model is complete and has been parameterized for the wood stork.
  2. The wood stork model has been linked to the landscape fish model (ALFISH). It is now producing output at the University of Florida.
  3. The model has been used to demonstrate that decreases in area available for foraging can have a major impact on nesting success.
Additional work is needed to integrate and test the new information on wading bird feeding with the ATLSS wading bird SESI model and Wolff's model and integrate in the new data and test. This can be accomplished through a graduate student who is familiar with the work working with UT.

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