Abstract

Anticipating the ecological effects of climate change to inform natural resource climate adaptation planning represents one of the primary challenges of contemporary conservation science. Species distribution models have become a widely used tool to generate first-pass estimates of climate change impacts to species probabilities of occurrence. There are a number of technical challenges to constructing species distribution models that can be alleviated by the use of scientific workflow software. These challenges include data integration, visualization of modeled predictor–response relationships, and ensuring that models are reproducible and transferable in an adaptive natural resource management framework. We used freely available software called VisTrails Software for Assisted Habitat Modeling (VisTrails:SAHM) along with a novel ecohydrological predictor dataset and the latest Coupled Model Intercomparison Project 5 future climate projections to construct species distribution models for eight forest and shrub species in the Greater Yellowstone Ecosystem in the Northern Rocky Mountains USA. The species considered included multiple species of sagebrush and juniper, Pinus flexilis, Pinus contorta, Pseudotsuga menziesii, Populus tremuloides, Abies lasciocarpa, Picea engelmannii, and Pinus albicaulis. Current and future species probabilities of occurrence were mapped in a GIS by land ownership category to assess the feasibility of undertaking present and future management action. Results suggested that decreasing spring snowpack and increasing late-season soil moisture deficit will lead to deteriorating habitat area for mountain forest species and expansion of habitat area for sagebrush and juniper communities. Results were consistent across nine global climate models and two representative concentration pathway scenarios. For most forest species their projected future distributions moved up in elevation from general federal to federally restricted lands where active management is currently prohibited by agency policy. Though not yet fully mature, custom scientific workflow software shows considerable promise to ease many of the technical challenges inherent in modeling the potential ecological impacts of climate change to support climate adaptation planning.

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