Comparing soil inventory with modelling: Carbon balance in central European forest soils varies among forest types

Abstract

Forest soils represent a large carbon pool and already small changes in this pool may have an important effect on the global carbon cycle. To predict the future development of the soil organic carbon (SOC) pool, well-validated models are needed. We applied the litter and soil carbon model Yasso15 to 1838 plots of the German national forest soil inventory (NFSI) for the period between 1985 and 2014 to enables a direct comparison to the NFSI measurements. In addition, to provide data for the German Greenhouse Gas Inventory, we simulated the development of SOC with Yasso15 applying a climate projection based on the RCP8.5 scenario. The initial model-calculated SOC stocks were adjusted to the measured ones in the NFSI. On average, there were no significant differences between the simulated SOC changes (0.25 ± 0.10 Mg C ha a) and the NFSI data (0.39 ± 0.11 Mg C ha a). Comparing regional soil-unit-specific aggregates of the SOC changes, the correlation between both methods was significant (r = 0.49) although the NFSI values had a wider range and more negative values. In the majority of forest types, representing 75% of plots, both methods produced similar estimates of the SOC balance. Opposite trends were found in mountainous coniferous forests on acidic soils. These soils had lost carbon according to the NFSI (-0.89 ± 0.30 Mg C ha a) whereas they had gained it according to Yasso15 (0.21 ± 0.10 Mg C ha a). In oligotrophic pine forests, the NFSI indicated high SOC gains (1.36 ± 0.17 Mg C ha a) and Yasso15 much smaller (0.29 ± 0.10 Mg C ha a). According to our results, German forest soils are a large carbon sink. The application of the Yasso15 model supports the results of the NFSI. The sink strength differs between forest types possibly because of differences in organic matter stabilisation.

Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation

“…More specifically, we wanted to determine both how the total carbon measurements affect the individual model pools and how many measurement points need to be included to start impacting the future predictions in a noticeable manner. The decades-long SOC dataset measured at bare fallow agricultural fields around Europe (Barré et al, 2010) was used along with Yasso (Tuomi et al, 2011; https: //github.com/YASSOModel, last access: 11 March 2020), a SOC decomposition model that has been shown to perform well for long-term SOC projections (Ortiz et al, 2013;Ziche et al, 2019), to test whether updating the model projection with observations has an impact on future state predictions. The bare fallow sites do not include the uncertainty of litter input estimates and, thus, allowed us to focus more on the impact SDA has on the model projections.…”

Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations

“…Low C stock for Robinia pseudoacacia (RP) and other coniferous (OC) forests was most likely related to their presence on poorest sites, which was represented in the litterfall data, as site productivity was not included in the biomass simulation. On the other side, both models operate with average environmental conditions and annual time step, which support the option of validation at the regional scale, rather than granular one [37]. Including environmental parameters, as well as better consideration of continuous and categorical features, on top of forest type specificity, improves the predictability of soil C stocks [54,55].…”

“…Both are tools for projecting C stocks in forest mineral soils, while CBM allows enhanced representation of all key ecological processes, e.g., biomass growth and soils decomposition [35]. Yasso15 performed satisfactorily in various inter-model comparisons (for Finland [30,36]), calibration by litter bag decomposition experiments [17] or against measured data [37]. CBM-CFS3 provides a resolution at the level of 11 dead organic matter pools which allows matching to the three pools defined by [14], namely dead wood, litter and soils organic matter.…”

Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

“…To estimate the tree height development from 1961 to 2019, the height development from digital yield tables [48] was adjusted to the measured heights. Leaf area index (LAI) was modeled by using the tree data of consecutive forest inventories in combination with allometric functions for individual tree biomass (see Ziche et al [49] for more details), and specific leaf area (SLA) values from the database of life-history traits of Northwest European flora (LEDA) [50]. The stem area index (SAI) was estimated with diameter at breast height (DBH) based functions [51].…”