Spatial Dynamic Study Might Help to Shed Light on Conservation Strategies for Lower Keys Marsh Rabbit

Mitchell Eaton, Research Ecologist at the Southeast Climate Science Center just published a paper, Testing metapopulation concepts: effects of patch characteristics and neighborhood occupancy on the dynamics of an endangered lagomorph, in Oikos. Click here to view abstract.
Dr. Eaton writes, in a post on the Oikos Blog:
Can hard-to-detect individuals of an endangered and declining population allow for testing of some of the major tenets of metapopulation theory while contributing to conservation efforts? A new multi-season occupancy model combined with observations on the Lower Keys marsh rabbit may have done just that. Read the Early View paper “Testing metapopulation concepts: effects of patch characteristics and neighborhood occupancy on the dynamics of an endangered lagomorph” by Mitchell J. Eaton and co-workers. below is their summary of the paper:
The Lower Keys marsh rabbit (LKMR, Sylvilagus palustris hefneri) is an endemic species found only on a handful of islands in the lower Florida Key islands. Following decades of decline caused by habitat fragmentation and degradation, sea-level rise and high rates of mortality inflicted by non-native predators, the LKMR was listed as endangered under the U.S. Endangered Species Act in 1990. Although several of these contributors to population decline have been improved, the distribution of the marsh rabbit continues to fall. With limited dispersal abilities, this secretive species persists in isolated habitat patches found within a highly fragmented landscape, challenging managers to identify viable solutions for their conservation and recovery. Given these conditions, a better understanding of the spatial aspects of marsh rabbit population dynamics could provide important insights and contribute to management efforts. We believed that a metapopulation framework would be the most useful for describing these dynamics. We were concerned, however, that existing metapopulation models were more theoretical than practical, based on too many assumptions and insufficient for dealing with the realities of a rare and hard-to-detect species. Therefore, we developed a new, flexible multi-season occupancy model that could test the concepts and assumptions of metapopulation theory, while investigating the dynamics of this species for the ultimate purpose of making recommendations for species management and recovery.
Since its introduction in the 1960s, and following years of model development and application to natural systems, the theoretical underpinnings of metapopulation ecology have been strongly tied to assumptions about the relationship between neighboring patches, non-habitat (‘matrix’) characteristics and the probabilities of focal-patch extinction and colonization. Much recent work in metapopulation ecology has focused on developing advanced models that allow for incorporation of more detailed biological information to explain patterns in patch dynamics. Many of these models, however, have not taken into account the realities of imperfect detection in field sampling. As a result, only incomplete information on the abundance or occupancy levels of the surrounding landscape is available when making inference on the dynamics of a focal patch. As such, metapopulation models often rely on neighboring patch characteristics (e.g., perceived quality or size) as a proxy for the existence or abundance of colonizers and assume that local colonization will increase with patch connectivity. Local extinction probability has traditionally been modeled as a function of patch size, but is also predicted to be influenced by connectivity with neighboring habitat via a ‘rescue effect’. This latter process similarly depends on assumptions about the relationship between measurable patch characteristics and neighborhood occupancy, which can be difficult to quantify without consideration of the possibilities of non-detection.
Building on recent advancements of the use of so-called ‘autologistic’ covariate models, we have developed a new multi-season occupancy model to explicitly incorporate estimates of neighborhood occupancy when modeling the dynamics of a metapopulation. Rather than treating the status or condition of a neighboring patch as certain (i.e., as a traditional, known covariate) we consider the occupancy of neighboring patches as an unobservable variable to be estimated. Our flexible model specification allows the ‘neighborhood’ to be defined in any number of ways, permitting nearly any a priori biological hypothesis to be tested. The model allows inclusion of a gradation of neighboring patch influence on the focal patch (e.g., habitat quality, distance, etc.) using patch-specific weights, as well as the quantification of non-habitat (e.g., water bodies) within the neighborhood. Using this modeling approach, we recast many of the assumptions of metapopulation theory as hypotheses to be tested explicitly.