Multiyear heterotrophic soil respiration: Evaluation of a coupled CO2 transport and carbon turnover model

Future climate change will accelerate maize phenological development and increase yield in the Nemoral climate

Climate change will bring warmer and wetter conditions and more frequent extreme events in the Nemoral climate zone. These changes are expected to affect maize growth and yields. In this study, we applied the AgroC model to assess climate change impact on changes in growing environmental conditions, growing season length, yield and potential yield losses due to multiple abiotic stresses. The model was calibrated and validated using data from dedicated field experiments conducted in Lithuania during four meteorologically contrasting years (2015, 2016, 2017 and 2019). We simulated the climate impacts on rainfed maize for long-term future climate conditions from 2020 to 2100 under the RCP2.6 (low), RCP4.5 (medium) and RCP8.5 (high) emission scenarios. As a result, we found that air temperature, sum of growing degree days and amount of precipitation during the growing season of maize will increase, especially under medium and higher emission scenarios (RCP4.5 and RCP8.5), with significantly positive effect on yields. The simulation results showed that average maize grain yield will increase under RCP2.6 by 69 kg ha^-1 per decade, under RCP4.5 by 197 kg ha^-1 per decade and under RCP8.5 by 304 kg ha^-1 per decade. The future potential maize yield reveals a progressive increase with a surplus of +10.2% under RCP4.5 and +14.4% under RCP8.5, while under RCP2.6 the increase of potential yield during the same period will be statistically not significant. The yield gap under RCP2.6 and RCP4.5 will fluctuate within a rather narrow range and under RCP8.5, it will decrease.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Carbon Sequestration by Perennial Energy Crops: Is the Jury Still Out?

Soil organic carbon (SOC) changes associated with land conversion to energy crops are central to the debate on bioenergy and their potential carbon neutrality. Here, the experimental evidence on SOC under perennial energy crops (PECs) is synthesised to parameterise a whole systems model and to identify uncertainties and knowledge gaps determining PECs being a sink or source of greenhouse gas (GHG). For Miscanthus and willow (Salix spp.) and their analogues (switchgrass, poplar), we examine carbon (C) allocation to above- and belowground residue inputs, turnover rates and retention in the soil. A meta-analysis showed that studies on dry matter partitioning and C inputs to soils are plentiful, whilst data on turnover are rare and rely on few isotopic C tracer studies. Comprehensive studies on SOC dynamics and GHG emissions under PECs are limited and subsoil processes and C losses through leaching remain unknown. Data showed dynamic changes of gross C inputs and SOC stocks depending on stand age. C inputs and turnover can now be specifically parameterised in whole PEC system models, whilst dependencies on soil texture, moisture and temperature remain empirical. In conclusion, the annual net SOC storage change exceeds the minimum mitigation requirement (0.25 Mg C ha^-1 year^-1) under herbaceous and woody perennials by far (1.14 to 1.88 and 0.63 to 0.72 Mg C ha^-1 year^-1, respectively). However, long-term time series of field data are needed to verify sustainable SOC enrichment, as the physical and chemical stabilities of SOC pools remain uncertain, although they are essential in defining the sustainability of C sequestration (half-life >25 years).