HR: 1340h
AN: B43B-1161    [Abstracts]
TI: Ecosystem Performance Anomalies in the Bonanza Creek Area, Alaska
AU: * Bliss, N B
EM: bliss@usgs.gov
AF: SAIC, contractor to the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS), Sioux Falls, SD 57198 Work performed under USGS contract 03CRCN0001., 47914 252nd St., Sioux Falls, SD 57198, United States
AU: Wylie, B K
EM: wylie@usgs.gov
AF: SAIC, contractor to the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS), Sioux Falls, SD 57198 Work performed under USGS contract 03CRCN0001., 47914 252nd St., Sioux Falls, SD 57198, United States
AU: Ji, L
EM: lji@usgs.gov
AF: SAIC, contractor to the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS), Sioux Falls, SD 57198 Work performed under USGS contract 03CRCN0001., 47914 252nd St., Sioux Falls, SD 57198, United States
AU: Zhang, L
EM: lizhang@usgs.gov
AF: SAIC, contractor to the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS), Sioux Falls, SD 57198 Work performed under USGS contract 03CRCN0001., 47914 252nd St., Sioux Falls, SD 57198, United States
AB: Central Alaska is ecologically sensitive and experiencing stress in response to marked regional warming. We need a better ability to monitor ecosystem processes that are responding to climate change, fire, and insect damage, and to predict responses to future climate and environmental conditions. We have developed a method for analyzing ecosystem performance that illustrates the status and trends of ecosystem changes and that separates the influences of climate and local site conditions from the influences of disturbances and land management practices. The poster shows results of the method via a time series graph of ecosystem performance anomalies for each remotely sensed pixel of a boreal forest area that includes the Bonanza Creek Long Term Ecological Research (LTER) site near Fairbanks, Alaska. Measures of "ecosystem performance" are based on a seasonally integrated normalized difference vegetation index using composited data acquired by NOAA's Advanced Very High Resolution Radiometer (AVHRR). We define an "expected ecosystem performance" to represent the greenness response of vegetation that is expected in a particular year given the climate of that year, and we distinguish "performance anomalies" as cases where the ecosystem response is significantly different than the expected ecosystem performance. This poster illustrates Ecosystem Performance Anomaly Trends (EPAT). The magnitude of the ecosystem performance anomaly is separated into three categories: 1) performing better than expected, 2) performing within the expected range, or 3) performing more poorly than expected. A pixel is classed as anomalously overperforming (or underperforming) if it is above (or below) the 90-percent significance line in 6 of the 8 years modeled. Within each category, we also show if the trend is 1) decreasing, 2) nearly level, or 3) increasing. Combining these dimensions gives nine categories for the map. Recent fires are clearly detected by the method, but other areas of ecosystem stress are also identified.
DE: 0414 Biogeochemical cycles, processes, and modeling (0412, 0793, 1615, 4805, 4912)
DE: 0439 Ecosystems, structure and dynamics (4815)
DE: 0475 Permafrost, cryosphere, and high-latitude processes (0702, 0716)
DE: 0480 Remote sensing
DE: 1615 Biogeochemical cycles, processes, and modeling (0412, 0414, 0793, 4805, 4912)
SC: Biogeosciences [B]
MN: 2007 Fall Meeting