Principal Investigator:
Dr S Carver
Dates:
15th February 1999 – 30th September 2002
Grant:
USDA Forest Service
Summary:
The project objectives are:
- To test for effects of climate and site productivity on Alaskan tree and under story vegetation biodiversity and community characteristics
- To develop randomization methods for spatial pattern matching and apply them to statistical analyses of Southeast Alaska Inventory Data
- Compare the growth rates, competitive interactions, spatial structure, and disease incidence of ecologically core and marginal tree populations and communities
- Extrapolate neural network models of forest classification outside of the existing GRID survey dataset, specifically to designated Wilderness areas
- Diversify and optimize neural network forest classification models, using additional data field and scales of analysis
Explore and investigate further areas such as:
- The effects of environment, species mix and distance from remaining forest on the rate or re-growth of harvested forest stands
- Documenting spatial scaling relationships in the Alaskan tree flora
- Testing for effects of forest harvest on the biology of nearby intact forest stands
- Comparing recent satellite imagery with earlier images to test for changes in forest properties due to climate change or other factors
- Developing accurate surface interpolations of meteorological data for the SE Alaska Area
- Expanding neural network models to cover other FIM GRID survey areas as available
- Improving the spatial resolution of our models by incorporating new generation satellite data, if available
- Investigating other methods of spatial data interpolation and their application to the SE Alaska Inventory
- Examining the influence of human activity on wildlife habitat usage and populations
- Mapping and modelling wilderness quality and biodiversity
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