Predicting current and potential species distributions and abundance is critical for managing invasive species, preserving threatened and endangered species, and conserving native species and habitats. Accurate predictive models are needed at local, regional, and national scales to guide field surveys, improve monitoring, and set priorities for conservation and restoration. Modeling capabilities, however, are often limited by access to software and environmental data required for predictions. To address these needs, we built a comprehensive web-based system that: (1) maintains a large database of field data; (2) provides access to field data and a wealth of environmental data; (3) accesses values in rasters representing environmental characteristics; (4) runs statistical spatial models; and (5) creates maps that predict the potential species distribution. The system is available online at www.niiss.org, and provides web-based tools for stakeholders to create potential species distribution models and maps under current and future climate scenarios.
|Title||Bringing modeling to the masses: A web based system to predict potential species distributions|
|Authors||Jim Graham, Greg Newman, Sunil Kumar, Catherine S. Jarnevich, Nick Young, Alycia W. Crall, Thomas J. Stohlgren, Paul Evangelista|
|Publication Subtype||Journal Article|
|Series Title||Future Internet|
|Record Source||USGS Publications Warehouse|
|USGS Organization||Fort Collins Science Center|