Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches
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Published:2021-05-21
Issue:2
Volume:12
Page:635-670
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ISSN:2190-4987
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Container-title:Earth System Dynamics
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language:en
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Short-container-title:Earth Syst. Dynam.
Author:
Obermeier Wolfgang A.ORCID, Nabel Julia E. M. S.ORCID, Loughran Tammas, Hartung KerstinORCID, Bastos AnaORCID, Havermann Felix, Anthoni PeterORCID, Arneth AlmutORCID, Goll Daniel S.ORCID, Lienert SebastianORCID, Lombardozzi Danica, Luyssaert SebastiaanORCID, McGuire Patrick C.ORCID, Melton Joe R.ORCID, Poulter BenjaminORCID, Sitch Stephen, Sullivan Michael O.ORCID, Tian HanqinORCID, Walker Anthony P.ORCID, Wiltshire Andrew J., Zaehle SoenkeORCID, Pongratz JuliaORCID
Abstract
Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC yr−1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC yr−1). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).
Funder
Met Office Agence Nationale de la Recherche National Natural Science Foundation of China Horizon 2020 Framework Programme Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung Oak Ridge National Laboratory
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
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