Synopsis

APowell

Scaling tree-level measurements of diameter-at-breast-height (DBH) and tree height to stand, landscape, regional, and national-level estimates of biomass is inherently challenging and difficult to validate. Because of this the selection of biomass allometric approach and associated equations introduce a significant source of uncertainty into carbon accounting efforts. A recent study using forest inventory plot data in Oregon compared three popular biomass allometric scaling approaches ranging along a continuum from regionally-specific to nationally-generic (Zhou and Hemstrom 2009). It found that the nationally-generic approach yielded biomass estimates that were between 17-21% higher than the two regionally-specific approaches. This finding has broad implications for large-scale carbon accounting work. Our work here expands upon this recent comparison study by deriving spatially and temporally explicit maps of biomass and carbon for forested ecosystems in Washington, Oregon, and California based on each biomass allometric approach. Biomass maps were developed by linking together 20 years of annual Landsat observations with regional inventory plot data, including Forest Inventory and Analysis (FIA) data, within a gradient nearest neighbor (GNN) imputation framework. The overall objective of our analysis was to determine the range of uncertainty introduced into regional biomass/carbon mapping projects by the selection of allometric approach. Within that broad objective our goals were to understand how the range of uncertainty varied across the entire study area and the scale of analysis (both spatial and temporal), and how it manifested itself with respect to forest type, stand age, disturbance history, and other environmental factors.

The three approaches that we compared, in order from regionally-specific to nationally-generic were the regional approach (Zhou and Hemstrom 2010), the component ratio method (CRM) (Heath et al. 2008), and the Jenkins model (Jenkins et al. 2003). The regional approach is based on local to regional-scale tree biomass equations derived directly from DBH and tree height. The CRM is the approach currently employed by FIA to estimate nation-wide biomass stocks. It is an attempt to standardize what are viewed as idiosyncrasies in the regional approach. Because it is based on FIA tree volume estimates and a biomass expansion factor approach, the CRM is also an attempt to synchronize tree-level volume and biomass estimates. The Jenkins model is a set of 10 nationally consistent aboveground biomass equations derived directly from DBH for species group associations. For specific validation sites across the three state study area (Yosemite, CA; HJ Andrews, OR; Wind River, WA) we will synchronize the selection of biomass allometric equations with a parallel lidar-based biomass mapping effort. This will provide additional insight into the range of uncertainty introduced by the choice of allometric approach by comparing biomass estimates from fundamentally different scaling approaches.

The results of this study demonstrate the spatial variability of uncertainty tied directly to the selection of biomass allometric approach. Biomass/carbon maps for each of the three allometric approaches were analyzed at multiple spatial and temporal scales and with respect to forest type, stand age, disturbance history, and a suite of biophysical variables. We acknowledge that no single approach is inherently “correct”, as validation of regional-scale biomass/carbon maps is fundamentally problematic. However, the comparison of multiple approaches, including the Jenkins model that is currently used by the U.S. EPA in accordance with the United Nations Framework Convention on Climate Change (UNFCCC) for national-level greenhouse gas accounting (U.S. EPA 2011), as well as the CRM approach that is currently being used by FIA for national-level biomass/carbon estimates, offers invaluable insight into how the differences among approaches manifest themselves at various spatial and temporal scales.

Collaborators

  • Robert Kennedy, Boston University
  • Janet Ohmann, USDA Forest Service
  • Warren Cohen, USDA Forest Service
  • Matt Gregory, Oregon State University
  • Heather Roberts, Oregon State University
  • Van Kane, University of Washington
  • Jim Lutz, University of Washington