Refined forest land use classification with implications for United States national carbon accounting

Abstract

a b s t r a c tThe United States provides annual estimates of carbon sources and sinks as part of its National Greenhouse Gas Inventory (NGHGI). Within this effort, carbon stocks and fluxes are reported for six land use categories that are relevant to economic sectors and land use policy. The goal of this study is to develop methodologies that will allow the US to align with an internationally agreed upon forest land use definition which requires forest to be able to reach 5 m in height at maturity. Models to assess height potential are available for a majority of US forests except for woodland ecosystems. We develop a set of models to assess height potential in these systems. Our results suggest that ∼13.5 million ha of forests are unlikely to meet the international definition of forests due to environmental limitations to maximum attainable height. The incorporation of this height criteria in the NGHGI results in a carbon stock transfer of ∼848 Tg from the forest land use to woodland land use (a sub-category of grasslands) with minimal effect on sequestration rates. The development of a forest land use definition sensitive to climatic factors in this study enables a land use classification system that can be responsive to climate change effects on land uses themselves while being more consistent across a host of international and domestic carbon reporting efforts.

Carbon stocks and stock change on federal forest lands of the United States

“…, Coulston et al. , U.S. EPA ) amounted to 3.99 million ha deducted from federal forests; this is 4.9% of all federal forest area and 30.7% of federal forests identified as woodland type groups (pinyon/juniper or woodland hardwoods). Ninety‐seven percent of these too‐short woodland hectares are in the Rocky Mountain region.…”

“…, Coulston et al. , U.S. EPA ). These too‐short woodlands are specifically identified (Coulston et al.…”

“…These too‐short woodlands are specifically identified (Coulston et al. ) and removed from U.S. EPA () reporting and similarly removed here. Note that neither of these modifications are as yet explicitly identified within the FIADB.…”

Relative density of United States forests has shifted to higher levels over last two decades with important implications for future dynamics

“…Assessing the status and trends of a forest size-density metric relative to a potential maximum (i.e., RD) is an additional tool for evaluation of forest establishment/management opportunities across large scales. Coincident with the contemporary maximum in forest land area potentially reached in the US 32 , US forests appear to be increasingly occupying their sites in terms of size-density relationships across most of the nation. Land usechange dynamics over the past 100 years, such as agricultural abandonment, has led to a substantial increase in forest land area and net carbon sequestration across much of the US 33 , with those stands established decades ago now reaching or exceeding medium levels of RD as highlighted in this analysis.…”

“…Land usechange dynamics over the past 100 years, such as agricultural abandonment, has led to a substantial increase in forest land area and net carbon sequestration across much of the US 33 , with those stands established decades ago now reaching or exceeding medium levels of RD as highlighted in this analysis. Although this trend of increasing forest land area appears to have come to an end in the US 32 , the resulting forest stands stemming from decades of reforestation and/or lack of active timber management on reserved public lands or fragmented/urbanized forests has most likely resulted in forests that have a medium RD classification, where populations of live trees are approaching biologically relevant thresholds such as canopy closure and subsequent self-thinning-induced mortality. While the RD metric provides an objective quantification of the size-density status of tree populations comprising forest stands, various other metrics (e.g., remotely-sensed canopy change detection 34 or landscape succession models 35 ) and associated decision support tools are needed to appropriately frame RD in the context of the challenges 36 facing contemporary forest assessment and management.…”