Title :
Evaluation of integrating the invasive species forecasting system to support national park service decisions on fire management activities and invasive plant species control.
Author :
Ma, Peter ; Morisette, Jeffrey T. ; Rodman, Ann ; McClure, Craig ; Pedelty, Jeff ; Benson, Nate ; Paintner, Kara ; Most, Neal ; Ullah, Asad ; Cai, Weijie ; Rocca, Monique ; Silverman, Joel ; Schnase, John L.
Author_Institution :
NASA GSFC/Innovim, Praveen
Abstract :
The USGS and NASA, in conjunction with Colorado State University, George Mason University and other partners, have developed the Invasive Species Forecasting System (ISFS), a flexible tool that capitalizes on NASA\´s remote sensing resource to produce dynamic habitat maps of invasive terrestrial plant species across the United States. In 2006 ISFS was adopted to generate predictive invasive habitat maps to benefit noxious plant and fire management teams in three major National Park systems: The Greater Yellowstone Area (Yellowstone / Grand Tetons National Parks), Sequoia and Kings Canyon National Park, and interior Alaskan (between Denali, Gates of The Arctic and Yukon-Charley). One of the objectives of this study is to explore how the ISFS enhances decision support apparatus in use by National Park management teams. The first step with each park system was to work closely with park managers to select top-priority invasive species. Specific species were chosen for each study area based on management priorities, availability of observational data, and their potential for invasion after fire disturbances. Once focal species were selected, sources of presence/absence data were collected from previous surveys for each species in and around the Parks. Using logistic regression to couple presence/absence points with environmental data layers, the first round of ISFS habitat suitability maps were generated for each National Park system and presented during park visits over the summer of 2006. This first engagement provided a demonstration of what the park service can expect from ISFS and initiated the ongoing dialog on how the parks can best utilized the system to enhance their decisions related to invasive species control. During the park visits it was discovered that separate "expert opinion" maps would provide a valuable baseline to compare against the ISFS model output. Opinion maps are a means of spatially representing qualitative knowledge into a quantitative two-dim- ensional map. Furthermore, our approach combines the qualitative expert opinion habitat maps with the quantitative ISFS habitat maps in a difference map that shows where the two maps agree and disagree. The objective of the difference map is to help focus future field sampling and improve model results. This paper presents a demonstration of the habitat, expert opinion, and difference map for Yellowstone National Park.
Keywords :
ecology; environmental management; fires; vegetation; vegetation mapping; Grand Tetons National Park; Greater Yellowstone Area; ISFS; Invasive Species Forecasting System integration; Kings Canyon National Park; Sequoia National Park; United States; Yellowstone National Park; dynamic habitat maps; expert opinion maps; fire management activities; interior Alaskan parks; invasive plant species control; invasive terrestrial plant species; logistic regression; national park service decisions; noxious plant; qualitative knowledge; remote sensing resources; Arctic; Biological system modeling; Control systems; Councils; Fires; Logistics; MODIS; NASA; Remote sensing; Sampling methods; Greater Yellowstone Coordinating Committee (GYCC); ISFS; Invasive Species; MODIS; NASA; NPS; USGS; Yellowstone National Park;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4423342