California Gnatcatcher

Habitat Modeling Based on GIS Data:

        We used GIS data (raster maps exported from ARC/INFO) on the vegetation and topography of an approximately 850 km² region of Orange County, California. Using these data and the locations of gnatcatcher pair observations, we estimated a habitat model with logistic regression. Significant variables included percentage of coastal sage scrub, elevation, distance from grasslands, and distance from "trees" (forest, woodland, chapparal), and various interactions among these variables. We validated the model by estimating the habitat function using only data on gnatcatcher locations in the northern half of the study area, and predicting the habitat suitability of the locations where gnatcatcher pairs were observed in the southern half. We entered the habitat model in RAMAS GIS to create a habitat suitability map (see Figure).

Metapopulation Modeling

        We used RAMAS GIS to identify patches in the habitat suitability map. A habitat patch is a cluster of suitable cells that can support a local gnatcatcher population. The collection of these local populations make up the gnatcatcher metapopulation in the study area. Thus we used the habitat model to calculate the spatial structure of the metapopulation, including size and location of habitat patches and the distances among them. RAMAS GIS also calculated the average and total habitat suitability in each patch. We combined the spatial structure of the model with demographic parameters (such as survival, fecundity, dispersal, and catastrophes) that we estimated with data from field studies This resulted in a stage-structured, stochastic, spatially-explicit metapopulation model. Using this model, we simulated the dynamics of the metapopulation under various assumptions.

Results and Future Directions

        The model predicted a high risk of decline in the next 50 years with most combinations of parameters. However, there was a considerable range of outcomes due to uncertainties in parameters. Results were most sensitive to density-dependent effects, the probability of weather-related catastrophes, adult survival, and adult fecundity. Based on data used in the model, the greatest difference in results was given when the simulation's time horizon was only a few decades, suggesting that modeling based on longer or shorter time horizons may underestimate the effects of alternative management actions. For more information see Akçakaya and Atwood (1997; Conservation Biology 11:422-434).

        In the future, we are planning to refine the model, and use it to assess or rank management and conservation alternatives. One type of management that can be evaluated with this kind of a model is habitat conservation and restoration. Suppose, for example, that three of the habitat patches identified in this study are potential candidates for habitat conservation and restoration. If these patches vary in size, then there would a total of 7 alternatives (ranging from restoring only the smallest patch to restoring all three). These, plus the "no action" alternative, can be evaluated by running a series of simulations that incorporate the expected improvements in the carrying capacity and other parameters of the patches where habitat would be restored.

        The 8 options can then be ranked in order of increasing effectiveness (in, for example, reducing the risk of extinction). For this example, we might expect that the larger the area where habitat is improved, the lower the extinction risk of the gnatcatchers. The obvious choice is to improve the habitat in all three patches. In reality the choices are much less obvious, because improving all three patches may cost more than what is available for California gnatcatcher habitat management, which means we need to consider the costs as well. We could rank the 8 options with respect to both their benefit (reduction in risk of extinction) and with respect to their cost (see Figure above). Such a graph allows the evaluation of each conservation action in terms of costs and benefits, without falling into the trap of assigning a monetary value to the existence of a species.