Back to Search Start Over

Modelled land use and land cover change emissions-a spatio-Temporal comparison of different approaches

Authors :
Obermeier, W. A.
Nabel, J. E. M. S.
Loughran, T.
Hartung, K.
Bastos, A.
Havermann, F.
Anthoni, P.
Arneth, A.
Goll, D. S.
Lienert, S.
Lombardozzi, D.
Luyssaert, S.
McGuire, P. C.
Melton, J. R.
Poulter, B.
Sitch, S.
Sullivan, M. O.
Tian, H.
Walker, A. P.
Wiltshire, A. J.
Zaehle, S.
Pongratz, J.
Publisher :
Copernicus Publications

Abstract

Quantifying the net carbon flux from land use and land cover changes (f$_{LULCC}$) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale f$_{LULCC}$ 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, f$_{LULCC}$ estimates are not directly comparable between these two different model types. As an important example, DGVM-based f$_{LULCC}$ 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 f$_{LULCC}$ 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 f$_{LULCC}$ 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 f$_{LULCC}$ estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO$_{2}$-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global f$_{LULCC}$ (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 f$_{LULCC}$ accumulated to 189��56 PgC with 40��15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient f$_{LULCC}$ 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 f$_{LULCC}$ estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of f$_{LULCC}$ 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 f$_{LULCC}$ that is more robust against these choices, for example by estimating a mean DGVM ensemble f$_{LULCC}$ and LASC for a defined reference period and homogeneous environmental changes (CO$_{2}$ only).

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi...........50315f123c2522f6e78213c12e055068