Gridded estimates of aboveground biomass by plant functional type within Alaska and Yukon, 1985-2020

• Main Author: Kathleen Orndahl
• Format: Dataset
• Language: unknown
• Published: Arctic Data Center 2022
• Subjects: Landsat; remote sensing; tundra; unmanned aerial vehicle; fire; plant functional type; aboveground biomass; Arctic; boreal; Canada; Yukon; Tundra; Alaska
• Online Access: https://doi.org/10.18739/A2Q52FF2B

This dataset includes 30 meter (m) resolution gridded estimates of live aboveground biomass (AGB) for five common plant functional types (PFTs; deciduous shrubs, evergreen shrubs, forbs, graminoids and lichens) within Alaska and northwest Canada. Estimates were produced for single years, every five years from 1985 to 2020. To model AGB we used a multi-scale approach, scaling from field harvest data and unmanned aerial vehicle (UAV)-based biomass predictions. Estimates were produced using linear mixed effects models with LASSO (Least Absolute Shrinkage and Selection Operator) regularization and were based on gridded climatological, topographic, phenological, PFT cover, and Landsat spectral predictors. A Monte Carlo approach with 100 iterations was used to propagate uncertainty. For each PFT and each year, this dataset provides the 2.5th percentile estimates (lower bound), 50th percentile estimates (best estimate) and 97.5th percentile estimates (upper bound) from the Monte Carlo analysis. These maps capture vegetation changes occurring within the Arctic/boreal region, including increasing shrub biomass and decreasing lichen and graminoid biomass. They also demonstrate the role of disturbances such as wildfire in shaping vegetation change trajectories.