Title: Density-Weighted Connectivity for Landscape Management and Connectivity Conservation

Abstract:  Many conservation efforts are focused on maintaining connectivity of protected areas or reserves as a biodiversity or species conservation strategy.  The intended purpose of such corridors is to provide regions of the landscape that facilitate movement of individuals. Specific objectives include increasing gene flow, reducing isolation and inbreeding, increasing fitness and survival of species, and allowing species to move and adapt to changes in the landscape. Corridor conservation typically focuses on either 1) conserving areas that support high abundance of species to reduce the risk of demographic stochasticity or 2) conserving areas that allow individuals to move between reserve areas to maintain gene flow. Most corridor design applications focus on patterns of habitat and landscape structure (structural connectivity). However, the impetus of corridor design is the process of animal movement (functional connectivity). Functional connectivity considers the degree to which the landscape facilitates or impedes the movement of organisms and is the product of landscape structure and the response of organisms to this structure. However, maintenance of spatially structured populations requires considerations of both species abundance as well as functional landscape connectivity. I present a model for corridor design in the Choc√≥-Andean region of Ecuador, home to the endangered Andean bear (Tremarctos ornatus) and numerous endemic and threatened birds and describe a novel metric related to biodiversity conservation and corridor design. We use the ecological distance-based spatial capture-recapture model that simultaneously estimates species density and spatial aspects of animal population structure. The density-weighted connectivity metric is derived from encounter history data commonly collected in capture-recapture studies. I highlight how this metric can be used in reserve design or landscape management frameworks to inform conservation decision making.

Bio:  Angela Fuller is the Leader of the New York Cooperative Fish and Wildlife Research Unit and an Associate Professor at Cornell University. Angela’s research focuses on applied conservation and management of mammals, specifically related to population dynamics and the influence of human-induced landscape changes on populations. The second major program area of her research is applying structured decision making and adaptive management for aiding natural resource management and policy decisions. Her recent work has focused on informing agency decision making for managed species such as black bears, white-tailed deer, wild turkeys, and fishers; designing resilient and sustainable landscapes that support human quality of life and conserve biodiversity, with a focus on endangered Andean bears in Ecuador; and developing new methods for sampling and monitoring wildlife populations such as black bear, moose, mink, and fisher.