SIMSPAR: A Spatially Explicit Individual-based model for the Cape Sable Seaside Sparrow M. Philip Nott1 A 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. Conceptually, the model is designed as follows, based on empirical information. (1) The landscape of the sparrow's range is modeled explicitly as a set of spatial cells of fine enough resolution (500 x 500 meters) to represent areas of similar vegetation, topography, and hydrology. Relationships were identified between habitat type within a cell and its carrying capacity in terms of the maximum density of breeding territories. Water levels in each given cell were modeled on a daily time step. (2) Each individual sparrow in the population is modeled during the breeding period. In particular, the model tracks the sex, age, location and breeding status of each model individual from the egg stage to the end of its life. For mature males, the model tracks the establishment of breeding territories, finding a mate, the start of nesting, and the status of eggs and nestlings on a daily basis. (3) The relationship between sparrow breeding activity and water depth is modeled. A spatial cell is not available for breeding activity until the water level in that cell falls below a threshold of 5 centimeters. Any rise in the water level above 16 cm in a particular spatial cell during the nesting season is assumed to cause nest abandonment to the sparrows that have nests in that cell. (4) The sparrows are not modeled in detail during the non-breeding season, as that part of the annual cycle is probably not as sensitive to anthropogenic environmental conditions. Age-specific mortality rates are assigned during that period probabilistically (i.e., the model is a Monte Carlo simulation), based on empirical data. The following spring, when the next breeding season begins, older males return to their previous nesting territories. If they fail to breed successfully the year before, they move to a new habitable location, if one is available, as close as possible to the site they used last year. (5) In order to compare the model predictions with empirical data, in which only singing males are counted, the model simulated the helicopter survey, allowing a 'virtual' helicopter to survey the model landscape in the same way that the observations were made in the field. The Cape Sable sparrow model has been applied to a main subpopulation (the 'western' subpopulation, or subpopulation A) of the Cape Sable seaside sparrows on the western side of Shark Slough in the Everglades National Park/Big Cypress National Preserve. Six data points for total numbers in this region were available (1981, 1992-1996). Calibration and verification of the model was done using historic hydrologic data to determine water levels in the cells from 1977 to 1996. By trial and error, an initial population size was found for 1977 such that the model produced the population number observed in 1981. Using this initial value calibration, the model predictions were validated against that data on population numbers for 1992-1996. The model correctly predicts the rapid decline in population during the relatively wet years from 1992 to 1996. The behavior of the model was explored with respect to three measures of population viability: (1) mean time to population extinction, (2) probability of the population exceeding a specified value over time, and (3) probability of the population reaching some specified number sometime during the simulation. Sensitivity analysis was performed with the model with respect to the model's parameter values. Two parameter values in particular, female mobility and annual mortality rates, were found to be critical and to influence the three measures of population viability strongly. The model has been used as one of the key species assessment tools in the Central and Southern Florida Comprehensive Project Review Study (or Restudy). Changes to the hydrology of the southern Everglades, planned as part of a Everglades restoration project, could increase the water levels in parts of the sparrow's range and inavertently increase the risk to the reproductive success of the sparrow in certain areas. It is critical to predict how serious these risks are. Because the model is a Monte Carlo simulation, reflecting the demographic stochasticity that occurs in real populations, numerous replicate simulations can be performed over a given time period, so that the means and variances of the three measures of population viability can be computed. The model also allows the computation of a spatially explicit 'breeding potential index' that estimates the potential number of successful broods that can be achieved during a given year, under given hydrologic conditions, in each spatial cell of appropriate vegetation type. This index is based on continuous days in which the cell is dry during the breeding period. The Cape Sable sparrow model output was used in evaluating alternative water regulation scenarios as part of the Central and Southern Florida Comprehensive Review Study (Restudy). At this time, however, the model does not take into account possible changes in habitat through time, due to fire or prolonged changes in hydrologic conditions. We are currently working to achieve this. 1The Institute for Bird Populations, P. O. Box 1346, Point Reyes Station, California 94956-1346