Abstract
Abstract. Uncertainties in the estimation of tree biomass carbon storage across large areas pose challenges for the study of forest carbon cycling at regional and global scales. In this study, we attempted to estimate the present aboveground biomass (AGB) in Alberta, Canada, by taking advantage of a spatially explicit data set derived from a combination of forest inventory data from 1968 plots and spaceborne light detection and ranging (lidar) canopy height data. Ten climatic variables, together with elevation, were used for model development and assessment. Four approaches, including spatial interpolation, non-spatial and spatial regression models, and decision-tree-based modeling with random forests algorithm (a machine-learning technique), were compared to find the "best" estimates. We found that the random forests approach provided the best accuracy for biomass estimates. Non-spatial and spatial regression models gave estimates similar to random forests, while spatial interpolation greatly overestimated the biomass storage. Using random forests, the total AGB stock in Alberta forests was estimated to be 2.26 × 109 Mg (megagram), with an average AGB density of 56.30 ± 35.94 Mg ha−1. At the species level, three major tree species, lodgepole pine, trembling aspen and white spruce, stocked about 1.39 × 109 Mg biomass, accounting for nearly 62% of total estimated AGB. Spatial distribution of biomass varied with natural regions, land cover types, and species. Furthermore, the relative importance of predictor variables on determining biomass distribution varied with species. This study showed that the combination of ground-based inventory data, spaceborne lidar data, land cover classification, and climatic and environmental variables was an efficient way to estimate the quantity, distribution and variation of forest biomass carbon stocks across large regions.
Highlights
Forest ecosystems, accounting for over 80% of terrestrial vegetation biomass, play a major role in balancing the regional and global carbon (C) budget and analyzing the fate of carbon dioxide produced by the burning of fossil fuels and forest harvesting (Dixon et al, 1994; Brown et al, 1997; Houghton et al, 2009)
Direct field measurements yielded an estimate of 128.24 ± 76.64 Mg ha−1 for the density of aboveground biomass (AGB) for Alberta forests, with a range from nearly zero to 450.64 Mg ha−1 in these inventory plots
Total AGB was 0.50 × 109 Mg, of which 78 % is distributed in the Boreal region
Summary
Forest ecosystems, accounting for over 80% of terrestrial vegetation biomass, play a major role in balancing the regional and global carbon (C) budget and analyzing the fate of carbon dioxide produced by the burning of fossil fuels and forest harvesting (Dixon et al, 1994; Brown et al, 1997; Houghton et al, 2009). A proper assessment of actual and potential roles of forest ecosystems in the global C cycle requires accurate information about carbon storage and change over space and time (Botkin and Simpson, 1990). Such accurate information has been lacking at regional and global scales. Houghton et al (2001) compared several biomass estimates for the Brazilian Amazon forests and found very low agreement across the estimates, with the values ranging from 39 to 93 gigatons (Gt) of carbon. Blackard et al (2008) compared several estimates of C pools in living forest biomass of the continental U.S forests and found that satellite-imagebased estimation was two times higher than estimates based on inventory data
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