An Innovative Approach to Effective Climate Science Application through Stakeholder Participation in Great Plains Grasslands

Abstract:

For natural resource managers and other Great Plains stakeholders, climate uncertainties further confound decision-making on a highly altered landscape. Partner organizations comprising the Great Plains Landscape Conservation Cooperative (GPLCC) acknowledge climate change as a high-priority threat to grasslands and associated habitats, affecting water availability, species composition, and other factors. Despite its importance, incorporation of climate change impacts into planning is hindered by high uncertainty and lack of translation to a tangible outcome: effects on species and their habitats. In 2014, the GPLCC initiated a Landscape Conservation Design (LCD) process to ultimately improve the size and connectivity of grasslands – informing land managers of the landscape-scale impacts of local decisions about where to restore, enhance, protect, and develop lands. Defining this goal helped stakeholders envision a tangible product. High resolution land cover data recently completed for Texas and Oklahoma represent current grassland locations. By focusing climate change models to project changes in these land cover datasets, resulting land cover projections can be directly incorporated into LCD-based models to focus restoration where future climates will support grasslands. Broad organizational cooperation has been critical for this USGS-led project, which uses downscaled climate data and other support from the South Central Climate Science Center Consortium and builds on existing work including LCD efforts of the Playa Lakes Joint Venture and the Bureau of Land Management’s Southern Great Plains Rapid Ecological Assessment. Ongoing stakeholder guidance through an advisory team ensures effective application of a product that will be both relevant to and understood by decision makers, for whom the primary role of research is to reduce uncertainties and clear the path for more efficient decision-making in the face of climatic uncertainty.