Themes

Research

The workflow for the WildCRU Landscape Ecology Laboratory analyses to support conservation planning at multiple scales consists of six main elements:

This work is based on WildCRU’s extensive camera trap and GPS telemetry datasets, which provide a unique and unprecedented empirical base for robust inference about species distributions, habitat relationships and the factors that drive patterns of movement.

Our analytical team (led by Samuel Cushman of the US Forest Service with Zaneta Kaszta) develop optimized multi-scale models predicting species distribution and relative abundance for multiple species.

We use movement data or habitat suitability proxies to estimate landscape resistance to movement, and then applies advanced connectivity modelling algorithms (e.g. resistant kernel and factorial least cost path analysis) to predict and map core areas and corridors for multiple species.

Then we use individual-based, spatially explicit population and genetics models (e.g., CDPOP) to predict population size, distribution, density, genetic diversity and gene flow as functions of habitat suitability and landscape connectivity.

We work with national governments to co-create realistic and useful scenarios for alternative landscape planning, incorporating national development goals, conservation priorities, and other sociological and political factors. We project these scenarios forward modelling future landscape change, and then repeat the process 1-4 above to evaluate the impacts of the alternative scenarios on habitat quality, connectivity, population size and genetic diversity.

Finally, we are developing a user-friendly, intuitively interactive Decision Support System that allows non-technical users to interact with the models and their results to facilitate their understanding of the implications of each alternative scenario.