Evaluation of climate‐related carbon turnover processes in global vegetation models for boreal and temperate forests

Abstract

Turnover concepts in state‐of‐the‐art global vegetation models (GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate (k) derived from a combination of remote sensing based products of biomass and net primary production (NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation‐based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation‐based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation‐based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large‐scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models.

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long‐term data assimilation

“…The robustness of MTT_SSA_I estimations in the 10 ecosystems has been assessed with respect to MTT_OBS_I, which is generally recognized as a benchmark in current research (e.g., Thurner et al., ). Although eddy covariance measurements for MTT_OBS_I estimation are lacking for some of the sites, the MOD17A2H product performed as a suitable alternative for GPP observations because its spatial resolution is finer than the footprint of the flux towers (Mi, Yu, Wang, Wen, & Sun, ; Zhao et al., ).…”

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

“…To avoid the effect of autocorrelation, we also calculated the CUE values from MTE GPP (Jung et al, 2011) and MODIS NPP and this overestimation trend was still validated ( Figure S8). The overestimation of τ veg in the East Asian Monsoon region was also found in global vegetation models participating in ISI-MIP (Thurner et al, 2017). Longterm satellite-derived LAI products (MOD15A2-LAI, GLOPMAP-LAI, GLASS-LAI, GIMMS3g LAI, etc.)…”

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

“…Our results show the need for improvements of models in carbon turnover processes, a current limitation in stateof-the-art LSMs (Thurner et al, 2017). Tree-ring widths can provide reliable estimates of biomass increment, but repeated surveys of forests are required to estimate stem turnover in nonequilibrium stands (Alexander et al, 2017;Dye et al, 2016;Klesse et al, 2016;Babst et al, 2014).…”

“…Tree-ring widths can provide reliable estimates of biomass increment, but repeated surveys of forests are required to estimate stem turnover in nonequilibrium stands (Alexander et al, 2017;Dye et al, 2016;Klesse et al, 2016;Babst et al, 2014). However, whole-ecosystem C turnover will encompass processes other than mortality, including disturbances and land-use and landcover change (Masek et al, 2008;Erb et al, 2016;Thurner et al, 2017). Some of the aforementioned processes are already partially incorporated in LSMs, in particular land-use and land-cover change, but the lack of a mechanistic representation of the remaining processes is therefore indirectly represented in stem turnover rates.…”