AUTHORS: Robert Fletcher, University of Florida; Caroline Poli*, University of Florida; Miguel Acevedo, University of Puerto Rico; Jorge Sefair, Arizona State University; Divya Vasudev, Wildlife Conservation Society; Varun Goswami, Wildlife Conservation Society
ABSTRACT: Connectivity is fundamental to ecology, evolution, and conservation. Despite the increasing emphasis on connectivity across fields, accurately predicting and mapping connectivity in space and time has been challenging. Here we derive connectivity models from first principles regarding individual movement behavior and mortality risk across landscapes. We develop these models based on the framework of Absorbing Markov chains. These models isolate the role of the matrix on movement behavior and mortality risk, allow for straightforward integration of propagule pressure (e.g., occupancy and abundance), and provide analytical solutions for connectivity parameters of interest (e.g., probabilities of dispersal success) that explicitly acknowledge temporal variation in connectivity. We illustrate the modeling framework with both data from an experimental model system undergoing habitat loss and fragmentation as well as for human-wildlife conflict issues for elephant conservation across a broad region of India. Results from the experimental model system illustrate that this framework better predicts observed movement than existing frameworks for connectivity. Application to elephant conservation highlights how this framework can identify key areas for promoting connectivity while minimizing human-wildlife conflict. Importantly, the incorporation of mortality risk fundamentally alters predictions for connectivity. We provide guidance for the application of this framework for connectivity conservation.
Monday April 9, 2018 11:15am - 11:30am CDT
Adams Room