| Worldwide, anthropogenic activities such as the clearing of land for agricultural production and the grazing of cattle have dramatically altered the spatial arrangement and composition of native habitat patches. Within heterogeneous landscapes generalist predators often thrive, causing cascading effects on local biological communities, yet there are few data to suggest how attributes of fragmentation influence the ecology of these species. I used a combination of radio-telemetry data collected from 2003-2005 and mark-recapture data collected from 2004-2009 in an agricultural ecosystem in north-central Indiana to elucidate the influence of local and landscape level habitat attributes on spatial and temporal variation in raccoon movement behavior and population dynamics. Using these data I also compared intrapatch variation in demography with fine-scale genetic characteristics to determine whether underlying demographic characteristics were reflective of observed genetic outcomes. The results of this research clearly demonstrate that agricultural ecosystems support increased densities of raccoons relative to other rural landscapes, but that spatial variation in habitat attributes directly influences both raccoon movement behavior and population dynamics. Moreover, I observed nearly complete concordance between fine-scale genetic characteristics and long-term population demography. Collectively, my results indicate that, despite the high densities of raccoons in agricultural ecosystems, all patches do not contribute equally to the regional abundance and persistence of this species and that ultimately raccoons are persisting in a source-sink population structure in this landscape. However, my data suggest that all habitat patches cannot be explicitly defined as sources or sinks, rather a continuous distribution exists that likely is tied to both underlying variance in habitat quality and additional variance associated with sampling error. Given the significant role of raccoons and other generalist predators in avian nest predation, disease transmission, and scavenging dynamics, these data will greatly facilitate the optimization of management strategies for these species in agricultural ecosystems. |
