projects > across trophic level system simulation program for the everglade/big cypress region > work plan
U.S. Geological Survey, Greater Everglades Priority Ecosystems Science (GE PES)Fiscal Year 2007 Study Work PlanA. GENERAL INFORMATION Project Title: Across Trophic Level System Simulation Program for the Everglade/Big Cypress Region Other Investigator(s): Dr. Lou Gross Other Investigator(s): Dr. Jimmy Johnston Other Investigator(s): Kenneth G. Rice, USGS; Frank J. Mazzotti, University of Florida Overview and Objectives: An essential component of restoration planning in South Florida has been the development and use of computer simulation models for the major physical processes driving the system, notably models of hydrology incorporating effects of alternative human control systems and non controlled inputs such as rainfall. The USGS's ATLSS (Across Trophic Level System Simulation) Program utilizes the outputs of such physical system models as inputs to a variety of ecological models that compare the relative impacts of alternative hydrologic scenarios on the biotic components of South Florida. The immediate objective of ATLSS is to provide a rational, scientific basis for ranking the water management scenarios as part of to the planning process for Everglades restoration. The longer term goals of ATLSS are to help achieve a better understanding of components of the Everglades ecosystem, to provide an integrative tool for empirical studies, and to provide a framework monitoring and adaptive management schemes. The ATLSS Program coordinates and integrates the work of modelers and empirical ecologists at many universities and research centers. ATLSS (Across Trophic Level System Simulation) program addresses CERP's need for quantitative projections of effects of scenarios on biota of the Greater Everglades and can provide guidance to monitoring in an adaptive assessment framework. It does this through creating a suite of models for selected Everglades biota, which can translate the hydrologic scenarios into effects on habitat and demographic variables of populations. ATLSS is constructed as a multimodel, meaning that it includes a collection of linked models for various physical and biotic systems components of the Greater Everglades. The ATLSS models are all linked through a common framework of vegetative, topographic, and land use maps that allow for the necessary interaction between spatially explicit information on physical processes and the dynamics of organism response across the landscape. This landscape modeling approach is the work of USGS scientists and collaborators from several universities. The South Florida Water Management Model provides hydrology for ATLSS models at a 2 x 2 mile spatial resolution. The ATLSS multimodeling approach starts with models that translate this coarse-scale hydrology output to a finer resolution appropriate for biotic components. This is achieved through use of GIS vegetation maps and empirical information relating hydroperiods with vegetation types, to develop an approximate hydrology at 500 x 500 m resolution from the 2 x 2 mile hydrology model. The simplest ecological models in the ATLSS family are the Spatially Explicit Species Index (SESI) models, which compute indices for breeding or foraging potential for key species. These models use the fine resolution hydrology output, combining several attributes of hydrology that are relevant to the well-being of particular species to derive an index value for every 500 x 500 spatial cell in the landscape. This can be done for hydrology data for any given year under any alternative water management scenario. SESI models have been constructed and applied during the Central and Southern Florida Comprehensive Review Study (Restudy) to the Cape Sable seaside sparrow, the snail kite, short and long legged wading birds, the white tailed deer, the American alligator, two species of crayfish, and the Florida panther. A considerably more spatially explicit simulation model, ALFISH, has been developed for the distribution of functional groups of fish across the freshwater landscape. This model considers the size distribution of large and small fish as important to the basic food chain that supports wading birds. It has been applied to assess the spatial and temporal distribution of availability of fish prey for wading birds. This simulation modeling approach is being extended to crayfish. Spatially explicit individual based (SEIB) models, which track the behavior, growth and reproduction of individual organisms across the landscape, have been constructed for the Cape Sable seaside sparrow (SIMSPAR), the snail kite (EVERKITE), the white tailed deer (SIMDEL), the Florida panther, the American crocodile (CROCMOD), and various wading bird species. The models include great mechanistic detail on the behavioral and physiological aspects of these species. An advantage of these detailed models is that they link each individual animal to specific environmental conditions on the landscape. These conditions (e.g., water depth, food availability) can change dramatically through time and from one location to another, and determine when and where particular species will be able to survive and reproduce. ATLSS models have been developed and tested in close collaboration with field ecologists who have years of experience and data from working with the major animal species of South Florida. The ATLSS integrated suite of models has been used extensively in Everglades Restoration planning. Restoration goals include recovery of unique Everglades species, including snail kites and Florida panthers. The quantity, quality, timing, and distribution of deliveries of water to the Greater Everglades are keys to the restoration of natural functions. The challenge is to provide the hydrologic conditions needed by communities of plants and animals, while maintaining water supplies and flood control for a large and expanding human population. The role of USGS's ATLSS Program is to predict the effects of changes in water management on Greater Everglades species and biological communities, as an aid to identifying and selecting those changes most effective for the restoration effort. To date, the focus of ATLSS to date has been on the freshwater systems, with emphasis on the intermediate and upper trophic levels. ATLSS will be extended estuarine and near shore dynamic models once physical system models for these regions are completed. Modeling of the mangrove vegetative community and estuarine fish is now underway. There are four tasks in this project. The first (DeAngelis) involves the coordination of the other tasks. The second task (Gross) involves the development and running of the ATLSS computer simulation models. The third task (Rice) involves developing restoration success indicators for the amphibian community. The fourth task (Johnston) involves upgrading of a ATLSS Data Visualization system. Specific Relevance to Major Unanswered Questions and Information Needs Identified: Many of the ATLSS models were used during scenario evaluation (1997-99). In this process, hydrology model output for scenarios was sent from the SFWMD to the U. of Tennessee. Hydrology output was used to drive the following ATLSS models: SESI models: Cape Sable seaside sparrow, snail kite, American alligator, long- and short-legged wading birds, white-tailed deer. SEIB model: Cape Sable seaside sparrow (SIMSPAR). Spatially explicit number/biomass density model: Freshwater fish (ALFISH). ATLSS output was sent to the Alternative Evaluation Team (AET), composed of representatives of agencies in South Florida, and used extensively in its evaluations and recommendations. ATLSS models will continue to be used for scenario evaluations for the Comprehensive Everglades Restoration Plan. Publications (2004-2006): Koslow, J., and D. L. DeAngelis. 2006. Host mating system and the prevalence of a disease in a plant population. Proceedings of the Royal Society of London B 273: 1825-1831. Holland, J. N., and D. L. DeAngelis. 2006. Interspecific population regulation and the stability of mutualism: fruit abortion and density-dependent mortality of pollinating seed-eating moths. Oikos 113:563-571. DeAngelis, D. L., and J. N. Holland. 2006 Emergence of ratio-dependent and predator-dependent functional responses for pollination mutualism and seed parasitism. Ecological Modelling 191:551-556. Binshamlan, M., H.-L. Koh, L.-H. Lee, and D. L. DeAngelis. 2005. Modeling bioaccumulation of mercury in the Everglades fishes. Proceedings of International Conference on Reservoir Operation and River Management, Guangzhou & Three Gorges, China, September 17-23, 2005. Published in: Advances in Reservoir Operation and River Management (Yangbo Chen, ed.) Grimm, V, E.. Revilla, U. Berger, F. Jeltsch, W. M. Mooij, S. F. Railsback, H.-H. Thulke, J. Weiner, T. Wiegand, and D. L. DeAngelis. 2005. Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science 310:987-991. DeAngelis, D. L., and W. M. Mooij. 2005. Individual-based modeling of ecological and evolutionary processes. Annual Reviews of Ecology and Evolutionary Systematics 36:147-168. DeAngelis, D. L., J. C. Trexler, and W. F. Loftus. 2005. Life history trade-offs and community dynamics of small fishes in a seasonally pulsed wetland. Canadian Journal of Fisheries and Aquatic Sciences 62:781-790. Vos, M., B. W. Kooi, D. L. DeAngelis and W. M. Mooij. 2005 . Inducible defenses in food webs. Pages 114-127 in "Dynamic Food Webs". P. de Ruiter, V. Wolters and J. Moore (eds.), Elsevier Press, The Netherlands. Immanuel, A., M. W. Berry, L. J. Gross, M. Palmer, and D. Wang. 2005. A parallel implementation of ALFISH: simulating hydrological compartmentalization effects on fish dynamics in the Florida Everglades. Simulation Modelling Practice and Theory 13:55-76. Wang Y.Q., D. A. Williams, and M. S. Gaines. 2005 Evidence for a recent genetic bottleneck in the endangered Florida Keys silver rice rat (Oryzomys argentatus) revealed by microsatellite DNA analyses. Conservation Genetics 6 (4): 575-585 July 2005 Wang, D., E. Carr, M. Palmer, M. W. Berry, and L. J. Gross. 2005. A Grid Service Module for Natural Resource Managers. IEEE Internet Computing 9:35-41. Wang, D., E. Carr, L. J. Gross, and M. W. Berry. 2005. Toward ecosystem modeling on computing grids. Computing in Science and Engineering 7:44-52. Wang, D., M. W. Berry, and L. J. Gross. 2005. A parallel structured ecological model for high-end shared memory computers. First International Workshop on Open MP. Lecure Notes in Computer Science (in press). Vos, M., A. M. Verschoor, B. W. Kooi, F. L. Wackers, D. L. DeAngelis, and W. M. Mooij. 2004. Inducible defences and trophic structure. Ecology 85:2783-2794. Richards, P. M., W. M. Mooij, and D. L. DeAngelis. 2004. Evaluating the effect of salinity on a simulated American Crocodile (Crocodylus acutus) population with applications to conservation and Everglades restoration. Ecological Modelling 180:371-394. Comiskey, E. J., A. C. Eller, Jr., and D. W. Perkins. 2004. Evaluating impacts to Florida panther habitat: how porous is the umbrella. Southeastern Naturalist 3(1):51-74. Holland, J. N. , D. L. DeAngelis, and S. Schultz. 2004. Evolutionary stability of mutualism: interspecific population regulation as an evolutionarily stable strategy. Proceedings of the Royal Society of London B 271:1807-1814. Gaff, H., J. Chick, J. Trexler, D. DeAngelis, L. Gross, and R. Salinas. 2004. Evaluation of and insights from ALFISH: a spatially explicit landscape-level simulation of fish populations in the Everglades. Hydrobiologia 520:73-87. Jost, C., C. Rhodes, F. Campolongo, W. van de Bund, S. Hill, and D. L. DeAngelis. 2004. The effects of mixotrophy on the stability and dynamics of a simple planktonic food web. Theoretical Population Biology 66(1):37-51. Dreitz, V. J., W. M. Kitchens, and D. L. DeAngelis. 2004. The effects of natal departure and water level on survival of juvenile snail kites in Florida. The Auk 121:894-903. Vos, M., B. W. Kooi, D. L. DeAngelis, and W. M. Mooij. 2004. Inducible defences and the paradox of enrichment. Oikos 105:471-480. Holland, J. N., J. L. Bronstein, and D. L. DeAngelis. 2004. Testing hypotheses for excess flower production and low fruit-to-flower ratios in a pollinating seed-consuming mutualism. Oikos 105:633-640. DeAngelis, D. L., and P. J. Mulholland. 2004. Dynamic consequences of allochthonous nutrient input into freshwater systems. Pages 12-24, In: G. A. Polis, M. E. Power, and G. R. Huxel (eds.), Food Webs at the Landscape Level. University of Chicago Press. Vanni, M. J., D. L. DeAngelis, D. E. Schindler, and G. R. Huxel. 2004. Introduction: Cross-habitat flux of nutrients and detritus. Page 3-11, In: G. A. Polis, M. E. Power, and G. R. Huxel. (eds.) Food Webs at the Landscape Level. In press or submitted: Mooij, W. M., J. Martin, W. M. Kitchens, and D. L. DeAngelis. Exploring the temporal effects of seasonal water availability on the snail kite of Florida. Pulsed Resources and Wildlife Population Response: The Importance of Time. Editors: John Bissonette and Ilse Storch. Springer-Verlag Publisher. (In press.) Rashleigh, B, and D. L. DeAngelis. Conditions for coexistence between parasitic freshwater mussels. Ecological Modelling (in press). Call, E. M., L. A. Brandt, and D. L. DeAngelis. Old World climbing fern (Lygodium microphyllum) spore germination in natural substrates. Florida Scientist (in press). Volker Grimm, Uta Berger, Finn Bastiansen, Sigrunn Eliassen, Vincent Ginot, Jarl Giske, John Goss-Custard, Tamara Grand, Simone Heinz, Geir Huse, Andreas Huth, Jane U. Jepsen, Christian Jørgensen, Wolf M. Mooij, Birgit Müller, Guy Pe'er, Cyril Piou, Steven F. Railsback, Andrew M. Robbins, Martha M. Robbins, Eva Rossmanith, Nadja Rüger, Espen Strand, Sami Souissi, Richard Stillmann, Rune Vabø, Ute Visser, Donald L. DeAngelis. A standard protocol for describing individual-based and agent-based models. Ecological Modelling (in press). Al-Rabai'ah, Hussam, H.- L. Koh, D. L. DeAngelis, H.-L. Lee, Modeling long-term effects of PCBs on the Everglades fish communities. Wetland Ecology and Management (in press). Petersen, J. H., D. L. DeAngelis, and C. P. Paukert. Developing bioenergetics and life history models for rare and endangered species. Transactions of the American Fisheries Society (in press). DeAngelis, D. L, M. Vos, W. M. Mooij, and P. A. Abrams. Feedback effects between the food chain and induced defense strategies. In: From Energetics to Ecosystems: The Dynamics and Structure of Ecological Systems N. Rooney, K. McCann and D. Noakes (eds). Springer-Verlag (In press.) Sternberg, L. D. L. DeAngelis, S. Ewe, and F. Wilhelm-Miralles. A dynamic model of ecosystem shifts at the saline/freshwater vegetation ecotone. Ecosystems (submitted). Presentations: DeAngelis, D. L., and W. M. Mooij. 2005. Individual-based modeling and fundamental theoretical questions in ecology. Keynote Speech. Annual Meeting, British Ecological Society, Hatfield, England. DeAngelis, D. L. 2006. Coupling population and biomass in individual-based models. Keynote Speech, International Society of Ecological Modelling, Yamaguchi, Japan. Mooij, W. M., J. Martin, W M. Kitchens, and D. L. DeAngelis. 2006. Modeling snail kites in a variable environment. GEER Meeting, Lake Buena Vista, FL Gaines, M. S., D. L. DeAngelis, M. Fernandes, J. Warren, and H. Beck. 2006. Effects of Patch Size and Hydrology on Population Dynamics of Small Mammals in the Everglades. GEER Meeting, Lake Buena Vista, FL Planned Products: See tasks below Project Budget and Time Frame: Collaborators: Collaborators have included the following: Florida International University, Southwestern Louisiana University, University of Florida, University of Maryland, University of Miami, University of Tennessee, University of Washington, University of West Florida, National Wetland Research Center (USGS), Institute for Bird Populations, Everglades Research Group, and the Netherlands Institute of Ecology. Clients: National Park Service, U.S. Fish and Wildlife Service. WORK PLAN Title of Task 1: Coordination of the projects and tasks under ATLSS Work to be undertaken during the proposal year and a description of the methods and procedures: During the next year there will be especially heavy need for working with the DOI agencies (National Park Service and Fish and Wildlife Service) to perform the needed ATLSS model simulations for CERP evaluations. Part of this work will involve making ATLSS models more directly accessible to agencies. A meeting with agency representatives on September 22, 2005, indicated that there is now an urgent need to test a number of different water regulation scenarios in a short time, as well as to be able to make minor alterations in the models. This requires rapid turnaround of results (within a day or two). The leader of this task will work to achieve this goal both through interactions with Lou Gross of the University of Tennessee as well as by improving the capabilities at the Joint Ecological Modeling (JEM) Center. Currently the USGS's Across Trophic Level System Simulation (ATLSS) models are run at the University of Tennessee using 2 x 2 mile hydrology provided by the South Florida Water Management Model (SFWMM). But the DOI agencies need to have ATLSS models working in South Florida on PCs. Currently the USGS's Across Trophic Level System Simulation (ATLSS) models are run at the University of Tennessee using 2 x 2 mile hydrology provided by the South Florida Water Management Model (SFWMM). The initial step in this process is converting SFWMM topography and hydrology to the 500 x 500 meter scale of resolution used by the ATLSS models. The 500-m hydrology is used in the ATLSS models, which include Spatially Explicit Species Index (SESI) models for wading birds, snail kites, white-tailed deer, American alligator, Cape Sable seaside sparrow, crayfish, Florida panthers, and apple snails, as well as population demographic models of the American alligator and the forage fish functional group (ALFISH model). In order to transfer these functions to DOI agencies, the University of Tennessee is now cooperating in training between two and four persons from these agencies during a series of visits to the University of Tennessee beginning in early 2006. In addition, source code and documentation of the models and procedures will be transferred to the involved agencies. The task leader has been organizing and participating in visits by DOI staff to the University of Tennessee to learn how the processes needed to run ATLSS models. The task leader will also coordinate with other modeling research in order to incorporate new models in the ATLSS framework. The task leader is also engaged in other project related to Everglades research and restoration.
Deliverables:
Title of Task 2: Development of Selected Model Components of an Across-Trophic-Level System Simulation (ATLSS) for the Wetland Systems of South Florida Task Summary and Objective(s): The ongoing goals in this project 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; 5) a variety of visualization and evaluation tools to aid model development, validation, and comparison to field data, and 6) developing an efficient way for agencies in South Florida to use models. 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. The objectives of the proposed study are as follows:
Work to be undertaken during the proposal year and a description of the methods and procedures: The emphasis on work being done under Task 2 shifted during FY06 due to the changing needs of agencies in South Florida. It was originally intended to continue development of a system (through an NSF-funded project at the University of Tennessee) to allow dispersed resource managers to access remotely, through the Web, the capabilities of the SInRG (Scalable Intracampus Research Grid) at the University of Tennessee. This would have allowed users at resource agencies in South Florida, with relatively little computer expertise, to initiate ATLSS simulations on the computers at the University of Tennessee. The Web-based use of the ATLSS models was progressing rapidly, using software, called NetSolve, developed at the University of Tennessee. Completion of this task would have left time to continue development of ATLSS (Version 3) and a number of other subtasks. However, a meeting with agency representatives on September 22, 2005, indicated that there is now an urgent need to test a number of different water regulation scenarios in a short time, as well as to be able to make minor alterations in the models. This requires rapid turnaround of results (within a day or two). This requires having ATLSS models to run locally on agency PCs. In order to provide this capability the objectives of Task 2 were changed during FY06. Work is now underway to transfer the expertise in using the ATLSS (Version 2.0) models and in performing the model runs to DOI agencies in southern Florida. In order to transfer these functions to DOI agencies, the University of Tennessee is training between two and four persons from DOI agencies and collaborators during a series of visits to the University of Tennessee that began in early 2006. In addition, source code and available documentation of the models and procedures are being shared with the involved agencies. The specific objectives of the proposed work begun during FY06 were specified as the following,
The following progress on these objectives has been made through August 2006.
A second piece of information that was learned about in July, 2006, is that the new model of the South Florida Water Management District, the Regional Simulation Model (RSM) is expected to be ready earlier than previously anticipated; in fact, perhaps be January 2006. Use of this would require an entire revision of the ATLSS models to the ATLSS Version 3. There are three subtasks to the proposed work for FY07:
The methods for the first two subtasks are as follows.
The methods for the third subtask have been described in previous SOWs. Work to be undertaken during future FY's and proposed funding: Recent Products: See earlier list Specific Task Products:
Title of Task 3: Use of Amphibian Communities as Indicators of Restoration Success We will use established sampling methodologies such as PVC refugia trapping to investigate amphibian occupancy rates, develop new methods for sampling across hydroperiod gradients (drift fence arrays, PVC arrays), and use newly developed statistical techniques to estimate the proportion of area occupied by and to define amphibian communities. Our objectives include:
Work to be undertaken during the proposal year and a description of the methods and procedures: During FY07, we will concentrate our work on:
Duellman and Schwartz (1958) produced the first scientific survey of the amphibians of south Florida. This work serves as an excellent reference for the historical distribution of many species before the extensive habitat loss in south Florida during the second half of the 20th century. Meshaka et al. (2000) produced a species list of the herpetofauna for ENP, but little information about the habitat associations and population status of the species was contained in that report. Dalrymple (1988) provided a good description of the herpetofauna of the Long Pine Key area in ENP, but no attempt has been made to sample amphibians throughout the Everglades. We used 2 primary methods to accomplish the objectives of the project:
Proportion area occupied by a species (Field work FY04-FY05, Analysis FY06).-- One problem with many of the methods used to sample amphibians is the lack of any control of the myriad environmental factors that affect the behavior and activity of the animals. Abiotic factors like temperature, humidity and hydrology as well as biotic factors like the presence of predators or conspecifics can affect the observability of amphibians. The observability of species' population is a function of the population size, the behavior of the individuals, and the ability of the observer to locate the animals in the particular habitat. Many monitoring programs simply count animals and do not control for this observability or capture probability (p). Therefore, comparisons over time or space are not possible or are biased. If the monitoring program can assume the cost of marking individual animals, then p can be determined and population size or density determined (standard mark-recapture methods, see Williams, et al. 2002). However, this would be cost prohibitive in a monitoring program for all amphibian species throughout the Everglades. MacKenzie, et al. (2002) has developed a novel approach to this problem. Rather than mark the individual, we mark the species. Therefore, presence/absence data from several plots within a habitat (or along a hydroperiod gradient in our study) provided an estimate of p and will allow estimation of the proportion of a stratum occupied by a given species at a given time. Sampling units were chosen randomly within each stratum. Within Everglades National Park these were along the Main Park Road and Context Road. We chose 5 permanent sites along each road accessed by foot. The sites were located within 300 to 900 feet of the road. In Water Conservation Area 3A, we selected 5 permanent sites in each stratum along a North-South transect from I75 to SR41. Each stratum was defined by the hydroperiod observed from existing hydrologic data and habitat type as defined by existing GIS vegetation layers. Sites were visited twice biweekly, April through September. Further sites in each stratum were visited twice during the study to provide further information on a broader geographic scale. Additional sites will be established in Big Cypress National Preserve (Bear Island and Addition Lands) and Florida Panther National Wildlife Refuge to fill in data gaps from previous studies on the distribution of treefrog species. Also, we will establish sites within slough and prairie habitats in Big Cypress National Preserve to further investigate distribution patterns of aquatic amphibians. Our standardized sampling unit was a circular plot of 20m radius. Plots were sampled after dark to increase the probability of observing nocturnal amphibians. At each plot 2-3 person crews began by listening for anuran vocalizations for 10 minutes. The abundance of each species was categorized as: no frogs calling, one frog calling, 2-5 calling, 6-10 calling, >10 calling, or large chorus. The intensity of the vocalizations were categorized as: no frogs calling, occasional, frequent, or continuous. After the vocalization survey, we performed a 30-minute visual encounter survey (VES) in each plot. During this time, all individual amphibians observed were identified to species and captured if possible. We recorded the species, categorized the age (egg, larvae, juvenile, sub-adult, or adult), measured and recorded the snout-to-vent length and recorded the sex when possible. The animal was released at the original capture site. We also recorded the substrate and perch height of the animal. A University of Florida Institutional Animal Care and Use Committee approval was obtained for animal capture. In addition to VES, we used funnel traps to attempt to capture aquatic amphibians. We also recorded several ancillary variables at each plot (air temperature, relative humidity, presence of water, water temperature, wind speed, cloud cover). In addition, 20-1m tall, 5 cm diameter PVC removable pipes were installed in each site for refugia of treefrog species. During each visit, animals were removed from the pipe for identification and measurement as outlined above. All animals were released into the original PVC refugia. All PVC was removed at the end of the study. At 10 sites in ENP (5 along Context Road and 5 along Main Park Road) we installed 20m of drift fence for capture of aquatic salamanders. The drift fence consisted of removable erosion control fence with a funnel trap incorporated at each end. The fence was arrayed as 4 separate 5-m fences in a grid around the center of the site. Traps were placed along the fence for 5 consecutive days once per month during May through October. The traps were checked each day in the morning to minimize heat stress on captured animals. Animals were measured as outlined above and released at the capture site. All traps and drift fences were removed during non-capture periods and at the end of the study. Analysis during FY07. - Individual species capture histories (matrix of presence/absence of each species at a sampling period and plot) and corresponding covariates (habitat, hydroperiod, temperature, humidity) will be assembled. We will then estimate the proportion of each stratum occupied by a species and the capture probability (using MLE and the logistic regression for covariates; MacKenzie et al. 2002). The best model will minimize AIC and adequately estimate the parameters in the model (the candidate model list will be developed a priori based on ecological knowledge and will not include all possible combinations). We can then use these estimates to construct appropriate communities for each stratum (see proportion of area occupied by a community below). Proportion area occupied by a community. - Given that species occupancy rates differ across hydroperiod gradients and that hydrology is the controlling factor of this difference (see above), we can begin to construct communities. In Figure 1 below (letters represent species, the size of the circle represents PAO, numbers represent hydroperiod), we can see that in short hydroperiod sites, species A and D dominate. However, as we move to longer hydroperiod sites, other species emerge as the dominate species in the community. This pattern of species composition and PAO forms the set of communities along the hydroperiod gradient.
We have seen this pattern begins to emerge in preliminary data from the Everglades (Table 1). At present, the method for defining and then predicting community composition and PAO is not complete. This study will develop this methodology for the Everglades. Index of Biological Integrity. -- Indices of biological integrity (IBI) were originally developed to assess conditions of riverine systems (Karr 1991, 1993) and also have been developed successfully for use in terrestrial environments (O'Connell et al. 1998). The basic premise of IBI's is that a range of conditions of ecological integrity can be defined based on the structure and composition of a selected biological community (e.g. amphibians, fish, birds, macroinvertebrates). The concept of biological integrity provides an ecologically-based framework in which species-assemblage data can be ranked in a manner that is more informative than traditional measures such as richness and diversity (Karr and Dudley 1981, Brooks et al. 1998). Therefore, the final step in this project will be to develop an amphibian community index (ACI) for evaluating the success of restoration and management of Greater Everglades Ecosystems. The ACI will be modeled after previously developed IBI's (Cronquist and Brooks 1991, Karr 1991,1993, Books et al. 1998, O'Connell et al. 1998). Essentially, we will use the PAO of communities estimated above to index or define the integrity of a given stratum. As restoration proceeds, we can use changes in the index to make informed management decisions and to measure success. Further, we can use the pattern of these communities based on hydropattern to develop restoration targets and to compare alternatives. By providing a reliable and repeatable measure of ecological quality an ACI will help managers reach scientifically defensible decisions (Brooks et al. 1998). Work to be undertaken during future FY's and proposed funding: This project is scheduled to end in FY07. Literature Cited: Boughton, R. G., J. Staiger, and R. Franz. 2000. Use of PVC pipe refugia as a sampling technique for hylid treefrogs. American Midland Naturalist 144: 168-177. Brooks, R.P., O'Connell, T.J., Wardrop, D.H., and Jackson, L.E.: 1998, 'Towards a Regional Index of Biological Integrity: The Example for Forested Riparian Systems,' Environmental Monitoring and Assessment, 51, 131-143. Croonquist, M.J. and Brooks, R.P.: 1991, 'Use of avian and mammalian guilds as indicators of cumulative impacts in riparian-wetland areas,' Environmental Management 15, 701-714. Dalrymple, G. H. 1988. The herpetofauna of Long Pine Key, Everglades National Park, in relation to vegetation and hydrology. Pp 72-86 In: Szaro, R. C., K. E. Stevenson, and D. R. Patton, eds. The management of amphibians, reptiles and small mammals in North America. U.S. Dept. of Agriculture, U.S. Forest Service Symposium, Gen. Tech. Rept. RM-166, Flagstaff, AZ. Donnelly, M. A., C. Guyer, J. E. Juterbock, and R. A. Alford. 1994. Techniques for marking amphibians. In Heyer, W. R., M. A. Donnelly, R. W. McDiarmid, L. C. Hayek, and M. S. Foster, editors. Measuring and monitoring biological diversity: Standard methods for amphibians. Smithsonian Institution. Washington, D.C. Duellman, W.E. and A. Schwartz. 1958. Amphibians and reptiles of southern Florida. Bull. Florida State Mus., no. 3. Enge, K. M. 1997. A standardized protocol for drift-fence surveys. Florida Game and Fresh Water Fish Commission Technical Report No. 14. Tallahassee. 69 pp. Karr, J.R. : 1991, 'Biological integrity: a long-neglected aspect of water resource management,' Ecological Applications 1, 66-84. Karr, J.R. : 1993, 'Defining and assessing ecological integrity: beyond water quality,' Environmental Toxicology and Chemistry 12, 1521-1531. Karr, J.R. and Dudley, D.R. : 1981, 'Ecological perspective on water quality goals,' Environmental Management 5, 55-68. MacKenzie, D.I., J.D. Nichols, G.B. Lachman, S. Droege, J.A. Royle, and C.A. Langtimm. 2002. Estimating site occupancy rates when detection probabilities are less than one, Ecology. In Press. Meshaka, W.E., W.F. Loftus, and T. Steiner. 2000. The Herpetofauna of Everglades National Park. Florida Scientist 63(2): 84-103. O'Connell, T. J., Jackson, L.E., and Brooks, R.P. : 1998, 'A Bird Community Index of Biotic Integrity for the Mid-Atlantic Highlands,' Environmental Monitoring and Assessment, 51, 145-156. Williams, B.K., J.D. Nichols, and M.J. Conroy. 2002. Analysis and management of animal populations. Academic Press, London. 817 pp. Specific Task Product(s):
Title of Task 4: Development of an Internet Based GIS to Visualize ATLSS Datasets For Resource Managers Task Summary and Objectives:
This project concerns the development of a customized spatial query and visualization tool that provide capabilities of loading ATLSS models data and showing, in the Everglades/Big Cypress area, alternative water management changes and their effects on numerous species modeled in ATLSS (i.e. Cape Sable seaside sparrow, Snail Kite, wading birds, white-tailed deer, American alligator, Florida panther), as opposed to one species, and compare numerous scenarios for one species. The overall goal is to provide an easy-to-use tool capable to access the vast amounts of data produced by the ATLSS models, display and integrate spatial and non-spatial information from different sources, interactively extract statistics for user-specified areas, allowing the users to produce easy-to-read outputs in form of maps, time series graphs, summarized tables, reports and metadata. Particular attention is being devoted in:
Continuous feedback will be requested to ATLSS models developers and potential final users to release a finished product that fulfills the initial planning tasks. This project will be used as prototype server application for an Internet based visualization tool. The above goals have largely been completed. In addition, DVS has been upgraded to ATLSS Data Visualization System (DVS) 2.0. The upgrades include
Work to be undertaken during the proposal year and a description of the methods and procedures:. The proposed work will continue the replacement of the ATLSS Data Viewer based on ArcView 3.x with a version based on ArcGIS by ESRI. The development of the ArcGIS version will be coordinated with other ATLSS activities.
The delivery of several ATLSS SESI models to ENP and JEM is scheduled for the end of October, 2006. Soon after that time, there should be training sessions at those locations for the use of the new version of the ATLSS DVS. Work on upgrading EVERKITE will begin in January, 2007, and output from EVERKITE Version 3 should be ready for use in early summer of 2007. In Spring of 2007, there will be coordination between EVERKITE and the ATLSS DVS to make the changes in the DVS that are necessary to view EVERKITE Version 3 output. I have not worried too much about the ATLSS Data Viewer up to this point, but we will need the latest version of the ATLSS DVS as soon as the SESI models are running here. There is funding for continued work on the ArcGIS version and for training of the folks at ENP, JEM, and maybe FWS. In addition, I think that EVERKITE output will finally be available on a grid basis that we can use in the ADV. I will have someone here at UM working on EVERKITE, so it will be easier to work with you on that. The translation to ArcGIS will be completed under FY07 funding. In addition, the investigators will work with the Interagency Modeling Center located at the South Florida Water Management District, and with the new Joint Ecological Modeling center at the University of Florida, Fort Lauderdale, to integrate the ATLSS DVS into their model development plans. Work to be undertaken during future FY's and proposed funding: Work scheduled to end at the end of FY07. Recent Products: ATLSS Data Viewing System 2.0 Specific Task Products: Completion of translation of ATLSS Data Viewing System 2.0 from ArcView basis to ArcGIS basis |
U.S. Department of the Interior, U.S. Geological Survey
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Last updated: 05 February, 2008 @ 04:31 PM(TJE)