Simulating the Effects of Fire on Forests in the Russian Far East: Integrating a Fire Danger Model and the FAREAST Forest Growth Model Across a Complex Landscape
Nancy
J
Sherman, University of Virginia, njs6f@virginia.edu
(Presenting)
Tatiana
Loboda, University of Maryland, tloboda@hermes.geog.umd.edu
(Presenting)
Ivan
Csiszar, University of Maryland, icsiszar@hermes.geog.umd.edu>
Herman
H
Shugart, University of Virginia, hhs@virginia.edu
Guoqing
Sun, University of Maryland, guoqing@ltpmail.gsfc.nasa.gov
The remaining natural habitat of the Siberian, or Amur, tiger (Panthera tigris altaica) is a vast, biologically and topographically diverse area in northeastern Asia marked by disturbances such as fires, logging, and human activity. Non-recurring, low intensity fires can improve habitat by clearing underbrush and nourishing soil, but severe or repeated fires can re-set the process of forest succession. In the case of extremely severe or repeated fires, the original forest may take centuries to re-grow.
The FAREAST model is an individual, gap-based model that simulates forest growth in a single location. Using species-specific vegetative processes and requirements, climate inputs, soil conditions and conditions associated with geographic location, the model can demonstrate succession leading to mature forests.
FAREAST was developed and verified using data from Changbai Mountain, a diverse forested area in China near the border of North Korea. This is the first attempt to merge FAREAST with a fire disturbance model, to validate it across a large region at a very detailed scale, and to compare it to remotely sensed data products, including land cover and LIDAR estimates of biomass.
We ran the FAREAST model at 1,000 randomly selected points within forested areas in tiger habitat in the Russian Far East (RFE). At each point, the model was calibrated for temperature, precipitation, slope, elevation, and fire probability using a fire danger model developed at the University of Maryland. Spatially interpolated 30-year mean (1971-2000) weather parameters for daily maximum and minimum temperatures, and precipitation from 36 weather stations in the RFE, also were applied for each point. The output was in terms of biomass for 44 tree species, grouped by genus, that occur in Russia and northeastern China.
The results were compared with landscape cover classifications derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, Russian forest inventory records, and LIDAR estimates of biomass. This project represents an initial exploration of a potentially useful tool to understand and predict forest mosaic dynamics in Amur tiger and Amur leopard habitat.
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