Abstract
BackgroundQuantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Forest inventories, processes-based biogeochemical models, and inversion methods have all been used to estimate the contribution of U.S. forests to the global terrestrial carbon sink. However, estimates have ranged widely, largely based on the approach used, and no single system is appropriate for operational carbon quantification and forecasting. We present estimates obtained using a new spatially explicit modeling framework utilizing a “gain–loss” approach, by linking the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3).ResultsWe estimated forest ecosystems in the conterminous United States stored 52.0 Pg C across all pools. Between 2001 and 2020, carbon storage increased by 2.4 Pg C at an annualized rate of 126 Tg C year−1. Our results broadly agree with other studies using a variety of other methods to estimate the forest carbon sink. Climate variability and change was the primary driver of annual variability in the size of the net carbon sink, while land-use and land-cover change and disturbance were the primary drivers of the magnitude, reducing annual sink strength by 39%. Projections of carbon change under climate scenarios for the western U.S. find diverging estimates of carbon balance depending on the scenario. Under a moderate emissions scenario we estimated a 38% increase in the net sink of carbon, while under a high emissions scenario we estimated a reversal from a net sink to net source.ConclusionsThe new approach provides a fully coupled modeling framework capable of producing spatially explicit estimates of carbon stocks and fluxes under a range of historical and/or future socioeconomic, climate, and land management futures.
Highlights
Quantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches
In this paper we present the results of our efforts to improve our existing Land Use and Carbon Simulator (LUCAS) framework by adding the rich suite of carbon dynamics embodied within the existing CBM-CFS3, creating an operational forecasting tool capable of rapidly generating spatially explicit estimates of historical and future carbon stocks and fluxes, under alternative future land management scenarios, for any forested location in the conterminous U.S (CONUS)
We used the CBM-CFS3 model of carbon dynamics to parameterize a stock-flow sub-model and added a dynamic growth module to represent the effects of climate variability and change on the net primary productivity (NPP) of forested ecosystems
Summary
Quantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Uncertainties in the size and future direction of this forest-based sink remain, due in large part to limitations regarding the methodological approaches used to estimate the net carbon flux [5] Given their importance in the global carbon cycle, U.S forests are increasingly looked to as a potential means of offsetting greenhouse-gas emissions from fossil fuel consumption and land use. The implementation of natural climate solutions, representing portfolios of land management policies and actions aimed at increasing sequestration of ecosystem carbon, provides an opportunity to make land management decisions today that will serve to maintain, and possibly increase, this key carbon sink into the future [7,8,9] Such decisions, require robust methods and tools in order to meaningfully quantify, compare and contrast the projected response of U.S carbon stocks and fluxes to these alternative land management strategies
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