Forecasting Net Forest Biomass Changes for Land Management in Interior Alaska
Abstract
Changes in boreal forests, including forest productivity and biomass, are important factors in calculating carbon budgets and informing management decisions. However, there is a lack of short-term, high-resolution predictions (5-30 years) of aboveground biomass changes tailored to specific sites. This study seeks to provide high resolution (30m) forecasts of aboveground biomass within interior Alaska. Using forest inventory data collected between 2001-2021 at various sites, we calculated tree and plot specific biomass using allometric equations specific to Alaska. We then predicted short-term aboveground biomass gains and losses using an ensemble of machine learning models that linked the biomass data with Landsat time series, climate, permafrost, and soil data. To allow easy access of biomass predictions for resource managers we then create a visualization application in Google Earth Engine that maps biomass predictions at a fine scale.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.B52I0956D