Hydrology, habitat change and population demography: an individual-based model for the endangered Cape Sable seaside sparrow Ammodramus maritimus mirabilis.
Habitat destruction and fragmentation have led to precipitous declines in a number of species of concern. For these species, traditional models that group individuals into age or stage cohorts may not accurately capture the stochasticity associated with small populations. Additionally, traditional models do not explicitly incorporate landscape-level structure, which becomes increasingly important at small population sizes. Thus, for declining species, spatially explicit individual-based models (SEIBM) can be used to understand both population demography and the impacts of habitat destruction, and to guide management practices to increase the chances of species survival. To gauge the impacts of changes in habitat and also demographic rates on a US endangered species, we constructed an SEIBM for the Cape Sable seaside sparrow (Ammodramus maritimus mirabilis Howell) of the South Florida Everglades. The model simulates temporal and spatial dynamics of individual sparrows using local GIS-based topography, vegetation and hydrology along with behavioural and demographic rates derived from field studies. When adult mortality and, to a lesser extent, juvenile mortality were increased in model simulations, there was an increase in extinction risk and a decrease in population size, whereas changes in number of clutches or female mating range had little impact. In contrast to the effects of simulating changes in mortality rates, simulated landscape-level changes (increasing water levels or decreasing habitat availability) were associated with dramatic population declines and increases in extinction risk. The sparrow appears to be particularly sensitive to the loss of higher-elevation breeding habitat. These results highlight the importance of proper water- and land-use management in assuring the species' survival. Synthesis and applications. Although changes in demographic rates affect population growth and are often the focus of conservation efforts, changes in habitat structure can also dramatically alter population viability. When both landscape-level and demographic data are available, spatially explicit models are particularly advantageous. Not only do they allow researchers and resource managers to prioritize areas for habitat restoration and species management, but they can also be used to help focus future research efforts.