Abstract
Abstract. In a context of global changes, modeling and predicting the dynamics of soil carbon stocks (CSs) in forest ecosystems are vital but challenging. Yasso07 is considered to be one of the most promising models for such a purpose. We examine the accuracy of its prediction of soil carbon dynamics over the whole French metropolitan territory at a decennial timescale. We used data from 101 sites in the RENECOFOR network, which encompasses most of the French temperate forests. These data include (i) the quantity of above-ground litterfall from 1994 to 2008, measured yearly, and (ii) the soil CSs measured twice at an interval of approximately 15 years (once in the early 1990s and around 2010). We used Yasso07 to simulate the annual changes in carbon stocks (ACCs; in tC ha−1 yr−1) for each site and then compared the estimates with actual recorded data. We carried out meta-analyses to reveal the variability in litter biochemistry in different tree organs for conifers and broadleaves. We also performed sensitivity analyses to explore Yasso07's sensitivity to annual litter inputs and model initialization settings. At the national level, the simulated ACCs (+0.00±0.07 tC ha−1 yr−1, mean ± SE) were of the same order of magnitude as the observed ones (+0.34±0.06 tC ha−1 yr−1). However, the correlation between predicted and measured ACCs remained weak (R2<0.1). There was significant overestimation for broadleaved stands and underestimation for coniferous sites. Sensitivity analyses showed that the final estimated CS was strongly affected by settings in the model initialization, including litter and soil carbon quantity and quality and also by simulation length. Carbon quality set with the partial steady-state assumption gave a better fit than the model with the complete steady-state assumption. With Yasso07 as the support model, we showed that there is currently a bottleneck in soil carbon modeling and prediction due to a lack of knowledge or data on soil carbon quality and fine-root quantity in the litter.
Highlights
The current global carbon stock (CS) in soils, including forest litter and peatlands, is 1500 to 2400 GtC and greatly exceeds stocks in vegetation, found mainly in forests (350 to 550 GtC) and in the atmosphere (829 GtC in 2011; IPCC, 2014)
We tested the performance of the Yasso07 soil carbon model on decennial-scale French nationwide forest data collected through the RENECOFOR network
While the model’s estimates of CS to 1.0 m in depth and of annual changes in carbon stocks (ACCs) stayed within the same order of magnitude as observed values, the accordance between the observed and simulated ACCs at the site scale remained weak
Summary
The current global carbon stock (CS) in soils, including forest litter and peatlands, is 1500 to 2400 GtC and greatly exceeds stocks in vegetation, found mainly in forests (350 to 550 GtC) and in the atmosphere (829 GtC in 2011; IPCC, 2014). The typical time step for litter input demanded by most forest soil carbon models is yearly, rather than monthly (but see RothC, Coleman and Jenkinson, 1996) or daily (but see Romul in Chertov et al, 2001; Didion et al, 2016). At this yearly timescale, it is common to consider microbial communities and processes to be relatively stable factors (Todd-Brown et al, 2012); in this case, the assumption that carbon dynamics are governed by first-order decay may be reasonable
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