Rastislav Skalský

Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations.

Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather. Increasing applications of fertilizer and irrigation reduce this variability until it is practically negligible. Importantly, estimated climate change effects on yield can be either negative or positive depending on the chosen soil type. Soils thus have the capacity to either buffer or amplify these impacts. Our findings call for improvements in soil data available for crop modelling and more explicit accounting for soil variability in GGCM simulations.

African crop yield reductions due to increasingly unbalanced Nitrogen and Phosphorus consumption

The impact of soil nutrient depletion on crop production has been known for decades, but robust assessments of the impact of increasingly unbalanced nitrogen (N) and phosphorus (P) application rates on crop production are lacking. Here, we use crop response functions based on 741 FAO maize crop trials and EPIC crop modeling across Africa to examine maize yield deficits resulting from unbalanced N : P applications under low, medium, and high input scenarios, for past (1975), current, and future N : P mass ratios of respectively, 1 : 0.29, 1 : 0.15, and 1 : 0.05. At low N inputs (10 kg ha(-1)), current yield deficits amount to 10% but will increase up to 27% under the assumed future N : P ratio, while at medium N inputs (50 kg N ha(-1)), future yield losses could amount to over 40%. The EPIC crop model was then used to simulate maize yields across Africa. The model results showed relative median future yield reductions at low N inputs of 40%, and 50% at medium and high inputs, albeit with large spatial variability. Dominant low-quality soils such as Ferralsols, which are strongly adsorbing P, and Arenosols with a low nutrient retention capacity, are associated with a strong yield decline, although Arenosols show very variable crop yield losses at low inputs. Optimal N : P ratios, i.e. those where the lowest amount of applied P produces the highest yield (given N input) where calculated with EPIC to be as low as 1 : 0.5. Finally, we estimated the additional P required given current N inputs, and given N inputs that would allow Africa to close yield gaps (ca. 70%). At current N inputs, P consumption would have to increase 2.3-fold to be optimal, and to increase 11.7-fold to close yield gaps. The P demand to overcome these yield deficits would provide a significant additional pressure on current global extraction of P resources.

Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

Changes in Organic Carbon Pool in Agricultural Soils and its Different Development in Individual Agro-Climatic Regions of Slovakia

Soil organic carbon (SOC) is one of the basic parameters of soil productivity and quality. Generally soil has potential to sequestrate or release organic carbon depending on land use/management and climatic conditions. The main aim of this article is to show changes in SOC in agricultural land of Slovakia over almost the last 40 years on the basis of modelling data of SOC stock by the RothC model and unequal development of SOC stock on agro-climatic regions of Slovakia. The results received show that average SOC stock [t/ha] in Slovakia is higher on grasslands in comparison to arable land. However, total SOC pool (t) in top of 0.2 m of soil on the modelling area of agricultural Slovak land shows that a considerable part of SOC stock is located in arable land and is approximately four times greater than on grasslands because the arable land represents about 80% of the modelling area. In the first modelling period (1970-1994), the SOC stock gradually increased, but in the second modelling period (1995-2007) no significant changes in SOC stock on the arable land were observed. In the southwest part of Slovakia, increasing of SOC stock during all modelling periods was observed; however, in the northeast part a slight increase of SOC stock only in the first modelling period (1970-1994) was found and in the second modelling period (1995-2007) decrease of SOC accumulation was observed. The results of this statistical analysis show significant relationship between carbon input/SOC stock as independent variables and agro-climatic regions as dependent variable.

Labile forms of carbon and soil aggregates

Tobiašová E., Barančíková G., Gömöryová E., Makovníková J., Skalský R., Halas J., Koco Š., Tarasovičová Z., Takáč J., Špaňo M. (2016): Labile forms of carbon and soil aggregates. Soil & Water Res., 11: 259−266. Soil organic matter (SOM) plays an important role in the soil aggregation and vice versa, its incorporation into the soil aggregates is one of the mechanisms of soil organic carbon stabilization. In this study the influence of labile carbon fractions on the fractions of dry-sieved (DSA) and wet-sieved (WSA) macro-aggregates and the relationship between the content of total organic carbon (TOC) and its labile fractions in the soil and in the fractions of macro-aggregates were determined. The experiment included six soil types (Eutric Fluvisol, Mollic Fluvisol, Haplic Chernozem, Haplic Luvisol, Eutric Cambisol, Rendzic Leptosol) in four ecosystems (forest, meadow, urban, and agro-ecosystem). In the case of DSA, the contents of labile fractions of carbon, in particular cold water extractable organic carbon (CWEOC) and hot water extractable organic carbon (HWEOC), had a higher impact on the proportions of larger fractions of macro-aggregates (3–7 mm), while in the case of WSA, the impact of labile fractions of carbon, mainly labile carbon (CL) oxidizable with KMnO4, was higher on the proportions of smaller fractions of aggregates (0.25–1 mm). The WSA size fraction of 0.5–1 mm seems an important indicator of changes in the ecosystems and its amounts were in a negative correlation with CL (r = –0.317; P < 0.05) and HWEOC (r = –0.356; P < 0.05). In the WSA and DSA size fractions 0.5–1 mm, the highest variability in the contents of TOC and CL was recorded in the forest ecosystem > meadow ecosystem > urban ecosystem > agro-ecosystem. The higher were the inputs of organic substances into the soil, the greater was the variability in their incorporation into the soil aggregates. The influence of the content of TOC and its labile forms on their contents in the DSA and WSA was different, and the contents of TOC and CL in the aggregates were more significantly affected by the CL content than by water soluble carbon. In the case of WSA fractions, their carbon content was more affected in the 1–2 mm than in 0.5–1 mm fraction.

Analyzing and modelling the effect of long-term fertilizer management on crop yield and soil organic carbon in China

This study analyzes the influence of various fertilizer management practices on crop yield and soil organic carbon (SOC) based on the long-term field observations and modelling. Data covering 11 years from 8 long-term field trials were included, representing a range of typical soil, climate, and agro-ecosystems in China. The process-based model EPIC (Environmental Policy Integrated Climate model) was used to simulate the response of crop yield and SOC to various fertilization regimes. The results showed that the yield and SOC under additional manure application treatment were the highest while the yield under control treatment was the lowest (30%-50% of NPK yield) at all sites. The SOC in northern sites appeared more dynamic than that in southern sites. The variance partitioning analysis (VPA) showed more variance of crop yield could be explained by the fertilization factor (42%), including synthetic nitrogen (N), phosphorus (P), potassium (K) fertilizers, and fertilizer NPK combined with manure. The interactive influence of soil (total N, P, K, and available N, P, K) and climate factors (mean annual temperature and precipitation) determine the largest part of the SOC variance (32%). EPIC performs well in simulating both the dynamics of crop yield (NRMSE = 32% and 31% for yield calibration and validation) and SOC (NRMSE = 13% and 19% for SOC calibration and validation) under diverse fertilization practices in China. EPIC can assist in predicting the impacts of different fertilization regimes on crop growth and soil carbon dynamics, and contribute to the optimization of fertilizer management for different areas in China.

Impacts and Uncertainties of +2°C of Climate Change and Soil Degradation on European Crop Calorie Supply

Abstract Even if global warming is kept below +2°C, European agriculture will be significantly impacted. Soil degradation may amplify these impacts substantially and thus hamper crop production further. We quantify biophysical consequences and bracket uncertainty of +2°C warming on calories supply from 10 major crops and vulnerability to soil degradation in Europe using crop modeling. The Environmental Policy Integrated Climate (EPIC) model together with regional climate projections from the European branch of the Coordinated Regional Downscaling Experiment (EURO‐CORDEX) was used for this purpose. A robustly positive calorie yield change was estimated for the EU Member States except for some regions in Southern and South‐Eastern Europe. The mean impacts range from +30 Gcal ha−1 in the north, through +25 and +20 Gcal ha−1 in Western and Eastern Europe, respectively, to +10 Gcal ha−1 in the south if soil degradation and heat impacts are not accounted for. Elevated CO2 and increased temperature are the dominant drivers of the simulated yield changes in high‐input agricultural systems. The growth stimulus due to elevated CO2 may offset potentially negative yield impacts of temperature increase by +2°C in most of Europe. Soil degradation causes a calorie vulnerability ranging from 0 to 50 Gcal ha−1 due to insufficient compensation for nutrient depletion and this might undermine climate benefits in many regions, if not prevented by adaptation measures, especially in Eastern and North‐Eastern Europe. Uncertainties due to future potentials for crop intensification are about 2–50 times higher than climate change impacts.

The Value of Global Earth Observations

Humankind has never been so populous, technically equipped, and economically and culturally integrated as it is today. In the twenty-first century, societies are confronted with a multitude of challenges in their efforts to manage the Earth system.