PROJECT BRIEF

Understanding wildlife connectivity is critical to species and ecosystem conservation. Using custom-derived, high-resolution data on agricultural land cover and human land use impacts, we are developing national models of potential wildlife connectivity across agricultural lands in the contiguous U.S. We are serving project results in a powerful, web-based tool for land managers and planners to identify agricultural areas that facilitate animal movement and prioritize them for protection.

PROJECT DESCRIPTION

Preserving wildlife movement pathways and linkages between areas of intact natural habitat is key to mitigating the current biodiversity crisis. At the same time, protecting the highest quality agricultural land is similarly critical to our long-term food security. Indeed, many organisms depend on agricultural landscapes for their movements between core habitat areas or for other fundamental ecological processes, such as breeding and foraging.

In partnership with American Farmland Trust and Microsoft Corporation, this project is utilizing contemporary, cutting-edge spatial data on agricultural land cover and use intensity to identify agricultural areas across the U.S. that are likely to provide important benefits to wildlife. Specifically, we are drawing on concepts from electronic circuit theory to estimate landscape resistance to movement and map the likely pathways for wildlife species that depend on agricultural landscapes to connect their populations. This work provides a substantial advancement over existing models of wildlife connectivity by incorporating new data on agricultural land cover and quality that provide a more nuanced view of the potential for wildlife movement across working landscapes using a consistent framework. Moreover, the computational power needed to efficiently deploy these complex models has only recently become available. Staff with the Analytics Lab at CSP are leveraging novel implementations of the Julia programming language and Microsoft’s Azure cloud computing platform to make this work possible and useful.