Initial results using NASA’s Invasive Species Forecasting System to support National Park Service decisions on fire management activities and invasive plant species control.
Jeffrey
Thomas
Morisette, NASA GSFC, jeff.morisette@nasa.gov
(Presenting)
Nate
Benson, National Park Service, Nate_Benson@nps.gov
Kara
Paintner, National Park Service, kara_paintner@nps.gov
Neal
Most, NASA GSFC/Innovim, neal.most@gsfc.nasa.gov
Pete
Ma, NASA GSFC/Innovim, pma@Innovim.com
Asad
Ullah, NASA GSFC/SSAI, asad_ullah@ssaihq.com
Weijie
Cai, George Mason University, wcai@gmu.edu
Monique
Rocca, Colorado State University, rocca@warnercnr.colostate.edu
Joel
Silverman, Colorado State University, jfsilver@warnercnr.colostate.edu
Jeff
Pedelty, NASA GSFC, Jeff.Pedelty@nasa.gov
John
Schnase, NASA GSFC, John.Schnase@nasa.gov
NASA Goddard Space Flight Center has worked in conjunction with the US Geological Survey to develop invasive plant habitat models through the Invasive Species Forecasting System (ISFS). NASA, as part of the transferring ISFS to operational capability, is working with the National Park Service to explore the use and usefulness of ISFS and the predictive maps produced for three major park systems: Yellowstone/Tetons, Sequoia/Kings Canyon and throughout Alaska. The work with the National Park Service started in early 2006 and this poster describes our work to-date. The first step was to work with each park system to select two top-priority species. Once focal species were selected, numerous sources of presence/absence data were aggregated for these species in and around the Parks. During this process a Series of interviews were conducted with Park Service Personnel and volunteers to develop base-line “expert opinion” maps on areas likely to support the selected invasives. In parallel, we used logistic regression to couple the presence/absence points with environmental data layers, available through ISFS, to construct preliminary ISFS habitat maps. The ISFS habitat maps are more quantitative, less subjective, and built through a repeatable process. However, the expert opinion maps serve as a reality check against model results, reflect human knowledge gained through working experience and can inform model selection. Future work will involve compiling additional field data on the distribution of invasive species, building additional predictive environmental data layers from satellite data products and fire history records, and using ISFS with the expert opinion maps serving as a priori information, to generate more accurate and useful predictive habitat models with our agency collaborators.