Modelling wildlife connectivity in the KAZA transfrontier region

One of the objectives in designing effective conservation landscapes is to ensure that the space needs of wildlife species are met across large scales and in areas where wild lands are interspersed with anthropogenic land... [ view full abstract ]

One of the objectives in designing effective conservation landscapes is to ensure that the space needs of wildlife species are met across large scales and in areas where wild lands are interspersed with anthropogenic land uses. The use of modern connectivity science methods can help in achieving this objective by providing a science-based, data-driven assessment of the opportunities and limitations of a landscape to provide connectivity for wildlife.  Here, we use methods from the movement ecology field, including migration characterization, resistance surface modeling, and circuit theory, to evaluate connectivity for multiple large wildlife species in the central part of the Kavango-Zambezi transfrontier conservation area.  We used >150,000 GPS locations from a number of herbivore and predator species, including elephant (Loxodonta africana), buffalo (Syncerus caffer), zebra (Equus burchelli), wild dog (Lycaon pictus), and lion (Panthera leo), as well as associated environmental data, to develop a variety of quantitative models of animal movement.  We characterized migratory movements using patterns of net squared displacement and evaluated triggers for large-scale movements using associated data on vegetation and climatic conditions.  We also modelled landscape resistance to movement across the study area as an input into circuit theory modelling, in order to assess how well connectivity levels were captured by proposed large-scale Wildlife Dispersal Areas within KAZA and by wildlife corridors that have been designated by local communities.  We find variable levels of effectiveness in these proposed corridors; some corridors appear to capture high levels of connectivity, while others are not optimally located.  Our models allow us to identify the relative impacts of anthropogenic barriers to movement versus natural environmental heterogeneity, and provide a means of simulating how future changes in landscapes may affect wildlife movements and resulting landscape connectivity.  These results have practical implications for the design and implementation of wildlife connectivity conservation efforts in the world's largest transfrontier conservation landscape.  Modern connectivity science approaches can help evaluate where in a landscape wildlife movements are likely to be highest, as well as the management conditions that are most likely to sustain such movements.