This project investigates the effects of habitat fragmentation on the dispersal and connectivity of an early successional habitat specialist, the New England cottontail, in a patchy landscape. Among the most pervasive effects of human activities across the globe are changes in land use and land cover and the associated fragmentation of habitat. Understanding how natural populations respond to landscape features and restoring connectivity on a landscape scale are critical for effective biodiversity conservation today as well as planning for management that accounts for climate change. Issues of landscape structure and connectivity and the relationship of animal movements and landscape heterogeneity are also central themes in the field of landscape ecology. By investigating landscape connectivity in an under-studied ecosystem of early successional and shrub habitats, this project will extend fragmentation theory beyond forested ecosystems. Landscapes consisting of early successional habitats present an ideal framework for testing hypotheses about animal dispersal and fragmentation theory because they are ephemeral and patchy by nature and are heavily impacted by human modifications of the landscape and changes in land use. This project will apply geographic tools of remote sensing and spatial analyses with population genetic techniques, in a landscape genetics approach, to identify the influence of landscape features in facilitating and impeding cottontail dispersal. Early successional and shrub habitats will be characterized and mapped using data sets from moderate to high-resolution remote sensors that include passive optical, LiDAR and radar. Landscape and dispersal modeling will be conducted using least cost path, isolation-by-resistance, and graph theory. By comparison across multiple, replicated landscapes with varying degrees of habitat fragmentation and population density, this study will test hypotheses about the effects of fragmentation and effective population size on genetic structure, dispersal distances and sex-biased dispersal patterns and also about the two-pronged effects of roads as dispersal barriers and facilitators for early successional habitat specialists. Results will be synthesized to develop a model of cottontail gene flow in relation to landscape structure and a predictive model to identify hot spots of connectivity and to estimate patch-specific colonization probabilities in restoration landscapes.
This project contributes to the societal goal of mitigating consequences of human modifications of the landscape on natural populations and ecosystems. By focusing on a threatened species, the New England cottontail, in a declining habitat, the early successional forest, this project will generate information that will be directly used in the restoration of a vulnerable ecosystem. Maintaining a mosaic of forested landscapes that includes all successional stages will enhance biodiversity and maintain ecological integrity of this geographic region that continues to experience large-scale anthropogenic landscape change. Through identifying how the landscape influences the dispersal patterns and connectivity of cottontails and identifying key corridors to maintain population persistence, this project will provide key insight for habitat restoration and the conservation of this threatened species. Through established partnerships with state and federal agency biologists, the results of this project are shared with stakeholders, ensuring they will have maximal conservation impact. This project will contribute to the training of one graduate and several undergraduate students and foster cross-disciplinary training among the disciplines of natural resources, geography, and computer science. Spatial tools developed in this project and their application in conservation management will also be incorporated into undergraduate and graduate curricula.
