OVERVIEW OF ATLSS SPATIALLY-EXPLICIT INDEX (SESI) MODELS E. Jane Comiskey(1), John Curnutt(2) and Louis J. Gross(1) (1)The Institute for Environmental Modeling Departments of Ecology and Evolutionary Biology and Mathematics University of Tennessee, Knoxville 37996-1610 (2)Biological Resources Division U. S. Geological Survey Gainesville, FL 32653-3071 ASSESSMENT OBJECTIVES The ATLSS hierarchy of models is designed to utilize varying levels of detail and data availability to assess the relative impact of alternative hydrological plans on the biotic components of South Florida. A key segment of this hierarchy includes models that make use of information on breeding and foraging requirements for species and how these relate to habitat and hydrologic conditions, but do not attempt to track in detail the population dynamics or behavior of individuals for these species. These are Spatially-Explicit Species Index (SESI) models which make use of the spatially-explicit, within-year dynamics of hydrology to compare the relative potential for breeding and/or foraging across the landscape. SESI models are viewed as approximations which are useful in coarse evaluations of scenarios and are an aid in interpreting the more detailed models. SESI models have been constructed and applied during the Restudy to the Cape Sable Seaside Sparrow, the Snail Kite, Short- and Long-Legged Wading Birds, and White-tailed Deer, with an additional model for Alligators now near completion. These models have been applied on a regular basis during the Restudy to assess the relative effects of alternative scenarios compared to F2050 as the base scenario. METHODS Habitat Suitability Index (HSI) models have been developed for many wildlife species, with the objective of evaluating the potential effects of management decisions which modify habitat conditions for these species. SESI models differ from traditional HSI models in that they: (1) have a temporal component and, thus, incorporate both static and dynamic landscape features; (2) are based on a 'landscape structure' which, once established, can be used to model the responses of any species in the system; and (3) can provide a relatively easy means of comparing species responses to more complex ATLSS models including process models, size-structured population models and individual-based models. SESI models are based on both static and dynamic landscape information. The first step in producing an SESI model is to provide a 'landscape structure' using a Geographical Information System (GIS). This structure includes both static information (e. g., surface elevations, aspect, soil type, vegetation type and structure, physical structures) and dynamic information (e. g., changing water levels, fire, vegetation dynamics). The landscape is divided into equally-sized spatial cells, each with a suite of values that correspond to the parameters included in the model. The inclusion of static and dynamic information results in an interdependence of the values assigned to each cell. The next step in developing a SESI model is to decide what aspect of the species' ecology will be used as the index. Often, when considering the effects of habitat management activities on only one species, breeding habitat - how much of the landscape will be suitable for successful breeding during the breeding season - is the most direct statistic for comparison. If the species has special breeding requirements that can not easily be incorporated into the structural landscape or if breeding is not spatially limited, another aspect of the species biology could form the basis of the model index. One such other aspect we have used is foraging potential, in which site-specific information can be used to assess foraging success dynamically. The ATLSS SESI models have involved both breeding and foraging aspects in developing appropriate index values. The Cape Sable Seaside Sparrow SESI model focuses on breeding rules, all based on the results of intensive field studies. These rules consider how the dynamics of hydrology affect the duration and spatial extent of the annual dry season during which the water level in any cell remains below the nesting threshold level. The index then estimates the potential number of breeding cycles in cells with appropriate levels of preferred habitat. The SESI model for the Snail Kite focuses on estimating appropriate foraging conditions during the kite breeding season for these raptors which are obligate predators of the apple snail. The requirements for appropriate foraging sites include: (1) having the potential for a substantial population of apple snails; (2) having surface water present; and (3) surface water depth must not be too deep (or else the kites cannot locate and catch snails). The ATLSS Wading Bird Foraging Conditions Index Model uses knowledge of how hydrologic factors affect the concentration and availability of food resources during the breeding season to compute a Foraging Conditions Index (FCI) for wading birds. The FCI is a composite index of spatial and temporal patterns. It expresses the effects of proposed hydrologic scenarios as changes in the spatial pattern of foraging potential over the model area for the simulation period. It calculates the FCI to represent two different types of wading birds: (1) a "long-legged forager" type with a feeding depth range of 5-35 cm and a long nesting cycle (during which a major water level reversal would cause nesting failure and decrease the index value to zero); and (2) a "short-legged forager" type with a feeding depth range of 0-20 cm and a shorter nesting cycle (with potentially multiple opportunities for nesting during a single dry season). The ATLSS White-tailed Deer SESI model also uses knowledge of how hydrologic factors affect the production and availability of food resources and the availability of dry bedding sites during the breeding season to compute an index for deer. FUTURE PLANS Several modifications are planned for the already constructed SESI models in addition to construction of new models. A SESI model for alligators is currently near completion and it is expected that there will be some SESI models constructed for the Florida Panther during the process of revising the individual-based Panther model. Planned extensions of to improving the current SESI models involves incorporation of methods to account for successional changes in habitat due to hydrology, as well the impact of fire. REFERENCES Curnutt, J. L., E. J. Comiskey, M. P. Nott and L. J. Gross. 1999. Developing and Using Landscape-based Spatially-explicit Species Index Models for Natural System Planning. Ecological Applications (Submitted)