Drivers and patterns of land biosphere carbon balance reversal

Abstract

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.

Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation

“…Next to differences in spatial resolution, sub-models are either hard-or soft-coupled. For example, IMAGE-LandManagement is hard-coupled to LPJmL which means that data is exchanged on an annual basis (see also Müller et al (2016)). In contrast, IMAGE-LandManagement is softcoupled to TIMER through an iterative process of scenario data exchange.…”

Balancing trade-offs between ecosystem services in Germany’s forests under climate change

“…One reason for this is that pine trees experience a high increase in growth in the climate change scenarios (Gutsch et al 2016). Another reason is that for the warmer and drier regions of Germany, where the 'plant available water' limits growth, high biomass accumulation in old pine forests is hampered by strong water competition and mortality (McDowell et al 2013, Müller et al 2016. Also, the low nutrition status of the soils in these regions caused a comparatively low carbon storage in tree biomass (Ying-Ping et al 2015).…”

Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0)

“…Climate-carbon cycle feedbacks have become integral parts of Earth system models (ESMs) for climate change projections. However, the terrestrial carbon cycle dynamic are not only driven by climate and carbon dioxide (CO 2 ) fertilization (Schimel et al, 2015;Norby et al, 2005), but also by land use change (Müller et al, 2006(Müller et al, , 2016Arneth et al, 2017;Le Quéré et al, 2016) and vegetation dynamics (Müller et al, 2016, and references therein). Nutrient limitations, especially from nitrogen, are also important constraints on vegetation growth and the terrestrial carbon cycle.…”