The mutual importance of anthropogenically and climate‐induced changes in global vegetation cover for future land carbon emissions in the MPI‐ESM CMIP5 simulations

Abstract

Based on the Max Planck Institute Earth System Model simulations for the Coupled Model Intercomparison Project Phase 5 and on simulations with the submodel Cbalone we disentangle the influence of natural and anthropogenic vegetation changes on land carbon emissions for the years 1850 until 2300. According to our simulations, climate‐induced changes in distribution and productivity of natural vegetation strongly mitigates future carbon (C) emissions from anthropogenic land‐use and land cover change (LULCC). Depending on the assumed scenario, the accumulated carbon emissions until the year 2100 are reduced between 22 and 49% and until 2300 between 45 and 261%. The carbon storage due to climate‐induced vegetation change is generally stronger under the presence of LULCC. This is because the natural vegetation change can reestablish highly productive extratropical forests that are lost due to LULCC. After stopping anthropogenic vegetation changes in the year 2100 the refilling of depleted C pools on formerly transformed land takes (dependent on the scenario) time scales of centuries.

Strong dependence of CO2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization

“…Furthermore, we found uncertainties in decadal fluxes due the parametrization of decomposition and direct emissions which are up to 0.6 Pg C yr −1 (Table ) 3 times as large as the uncertainties attributed previously to model and method by Houghton et al []. The actual uncertainties due to model and method are likely higher, as, for example, it was shown that the assumption about preferentially used land for pastures has a significant effect on LULCC emissions [ Reick et al , ; Schneck et al , ], but it is not included in this uncertainty assessments. Thus, the overall accuracy of estimates of sinks and source due to LULCC is lower than usually suggested [ Houghton et al , ; Ciais et al , ; Pongratz et al , ].…”

“…Using the difference between a pair of simulations under identical LULCC and fossil fuel-influenced environmental conditions is the most common method to quantify the LULCC flux on global scale (D3 in Pongratz et al [2014]). It allows a direct comparison of our results to previous studies on the factors influencing the sources and sinks of carbon from LULCC in MPI-ESM [Schneck et al, 2015;Wilkenskjeld et al, 2014].…”

“…Furthermore, the model evaluation is severely hampered by lack of appropriate data [Houghton et al, 2012;Reick et al, 2013]. Even though biases in the land cover simulated by MPI-ESM are known [Brovkin et al, 2013b], it has not been addressed how far they affect the net LULCC flux and other carbon fluxes [Brovkin et al, 2013a;Reick et al, 2013;Schneck et al, 2015;Wilkenskjeld et al, 2014].…”

A Large Committed Long‐Term Sink of Carbon due to Vegetation Dynamics

“…This is particularly the case for vegetation dynamics and most starkly demonstrated by boreal treeline advance. Although historical changes in land cover are probably dominated by anthropogenic disturbances over the last 1000 years, it has been shown that over the 20th century, dynamic land‐cover changes in response to climate change may be equally as large as human interference (Davies‐Barnard et al, ; Schneck et al, ). The results here show that the subsequent, committed changes in tree cover due to vegetation dynamics are larger still.…”

Modelling land use/cover change in Lake Mogan and surroundings using CA-Markov Chain Analysis

“…Rapid and extensive urban growth accompanied by the economic activities results in the necessity of more land for housing, public infrastructure, industrial and commercial developments (Weng, 2007), which results in changes in land use/cover (Long et al, 2007), but in turn causes profound impact on the environment (Turner and Meyer, 1994). Land use/cover changes are a global concern due to their adverse effects on climate (Foley et al, 2000;Foley et al, 2005;Pielke, 2005), biodiversity (Sala et al, 2000;Rizzoli, 2003), biogeochemical cycle (Pouyat et al, 2007;Klumpp et al, 2009;Schneck et al, 2015) and hydrology (Matheussen et al, 2000;Tu, 2006).…”