Environmental Research Letters (Jan 2016)

Drivers and patterns of land biosphere carbon balance reversal

  • Christoph Müller,
  • Elke Stehfest,
  • Jelle G van Minnen,
  • Bart Strengers,
  • Werner von Bloh,
  • Arthur H W Beusen,
  • Sibyll Schaphoff,
  • Tom Kram,
  • Wolfgang Lucht

DOI
https://doi.org/10.1088/1748-9326/11/4/044002
Journal volume & issue
Vol. 11, no. 4
p. 044002

Abstract

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The carbon balance of the land biosphere is the result of complex interactions between land, atmosphere and oceans, including climatic change, carbon dioxide fertilization and land-use change. While the land biosphere currently absorbs carbon dioxide from the atmosphere, this carbon balance might be reversed under climate and land-use change (‘carbon balance reversal’). A carbon balance reversal would render climate mitigation much more difficult, as net negative emissions would be needed to even stabilize atmospheric carbon dioxide concentrations. We investigate the robustness of the land biosphere carbon sink under different socio-economic pathways by systematically varying climate sensitivity, spatial patterns of climate change and resulting land-use changes. For this, we employ a modelling framework designed to account for all relevant feedback mechanisms by coupling the integrated assessment model IMAGE with the process-based dynamic vegetation, hydrology and crop growth model LPJmL. We find that carbon balance reversal can occur under a broad range of forcings and is connected to changes in tree cover and soil carbon mainly in northern latitudes. These changes are largely a consequence of vegetation responses to varying climate and only partially of land-use change and the rate of climate change. Spatial patterns of climate change as deduced from different climate models, substantially determine how much pressure in terms of global warming and land-use change the land biosphere will tolerate before the carbon balance is reversed. A reversal of the land biosphere carbon balance can occur as early as 2030, although at very low probability, and should be considered in the design of so-called peak-and-decline strategies.

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