Intensive agriculture in Germany is not only highly productive but has also led to detrimental effects in the environment. Crop diversification together with new field arrangements considering soil heterogeneities can be an alternative to improve resource use efficiency (RUE), ecosystem services (ESS), and biodiversity. Agroecosystem models are tools that help us to understand and design diversified new field arrangements. The main goal of this study was to review the extent to which agroecosystem models have been used for crop diversification design at field and landscape scale by considering soil heterogeneities and to understand the model requirements for this purpose. We found several agroecosystem models available for simulating spatiotemporal crop diversification at the field scale. For spatial crop diversification, simplified modelling approaches consider crop interactions for light, water, and nutrients, but they offer restricted crop combinations. For temporal crop diversification, agroecosystem models include the major crops (e.g., cereals, legumes, and tuber crops). However, crop parameterization is limited for marginal crops and soil carbon and nitrogen (N). At the landscape scale, decision-making frameworks are commonly used to design diversified cropping systems. Within-field soil heterogeneities are rarely considered in field or landscape design studies. Combining static frameworks with dynamic agroecosystems models can be useful for the design and evaluation of trade-offs for ESS delivery and biodiversity. To enhance modeling capabilities to simulate diversified cropping systems in new field arrangements, it will be necessary to improve the representation of crop interactions, the inclusion of more crop species options, soil legacy effects, and biodiversity estimations. Newly diversified field arrangement design also requires higher data resolution, which can be generated via remote sensing and field sensors. We propose the implementation of a framework that combines static approaches and process-based models for new optimized field arrangement design and propose respective experiments for testing the combined framework.

Agro-ecosystem models are useful tools to assess crop diversification strategies or management adaptations to within-field heterogeneities, but require proper simulation of soil water dynamics, which are crucial for crop growth. To simulate these, the model requires soil hydraulic parameter inputs which are often derived using pedotransfer functions (PTFs). Various PTFs are available and show varying performance; therefore, in this study, we calibrated and validated an agro-ecosystem model using the Hypres PTF and the German Manual of Soil Mapping approach and adjusting bulk density for the top- and subsoil. Experimental data were collected at the “patchCROP” landscape laboratory in Brandenburg, Germany. The daily volumetric soil water content (SWC) at 12 locations and above ground biomass at flowering were used to evaluate model performance. The findings highlight the importance of calibrating agro-ecosystem models for spatially heterogeneous soil conditions not only for crop growth parameters, but also for soil water-related processes—in this case by PTF choice—in order to capture the interplay of top- and especially subsoil heterogeneity, climate, crop management, soil moisture dynamics and crop growth and their variability within a field. The results showed that while the impact of bulk density was rather small, the PTF choice led to differences in simulating SWC and biomass. Employing the Hypres PTF, the model was able to simulate the climate and seasonal crop growth interactions at contrasting soil conditions for soil moisture and biomass reasonably well. The model error in SWC was largest after intense rainfall events for locations with a loamy subsoil texture. The validated model has the potential to be used to study the impact of management practices on soil moisture dynamics under heterogeneous soil and crop conditions.

Within-field soil physical and chemical heterogeneity may affect spatio-temporal crop performance. Managing this heterogeneity can contribute to improving resource use and crop productivity. A simulation experiment based on comprehensive soil and crop data collected at the patchCROP landscape laboratory in Tempelberg, Brandenburg, Germany, an area characterized by heterogeneous soil conditions, was carried out to quantify the impact of within-field soil heterogeneities and their interactions with interannual weather variability on crop yield variability in summer and winter crops. Our hypothesis was that crop–soil water holding capacity interactions vary depending on the crop, with some crops being more sensitive to water stress conditions. Daily climate data from 1990 to 2019 were collected from a nearby station, and crop management model inputs were based on the patchCROP management data. A previously validated agroecosystem model was used to simulate crop growth and yield for each soil auger profile over the 30-year period. A total of 49 soil auger profiles were classified based on their plant available soil water capacity (PAWC), and the seasonal rainfall by crop was also classified from lowest to highest. The results revealed that the spatial variability in crop yield was higher than the temporal variability for most crops, except for sunflower. Spatial variability ranged from 17.3% for rapeseed to 45.8% for lupine, while temporal variability ranged from 10.4% for soybean to 36.8% for sunflower. Maize and sunflower showed a significant interaction between soil PAWC and seasonal rainfall, unlike legume crops lupine and soybean. As for winter crops, the interaction was also significant, except for wheat. Grain yield variations tended to be higher in years with low seasonal rainfall, and crop responses under high seasonal rainfall were more consistent across soil water categories. The simulated results can contribute to cropping system design for allocating crops and resources according to soil conditions and predicted seasonal weather conditions.

Aims: We investigated the effects of N and P omission on winter rye growth and root traits under field conditions. Methods: Sampling was conducted during the 2022 season at the long-term fertilizer experiment Dikopshof, Germany. Four fertilizer treatments were chosen: (1) fully fertilized including manure (m) and supplemental mineral fertilizer (s) (NPKCa + m + s), (2) fully fertilized without manure (NPKCa), (3) N omitted (_PKCa), and (4) P omitted (N_KCa). Shoot biomass, number of tillers and root traits: topsoil root biomass, nodal root number, root angle, root length density (RLD), specific root length (SRL), and root diameter were assessed at five growth stages from tillering to flowering. Results: Shoot and root biomass showed significant interaction between fertilizer treatments and sampling date. The NPKCa + m + s treatment led to the highest shoot biomass up to early boot stage. Around flowering the nutrient omission treatments resulted in the lowest shoot biomass compared with the NPKCa + m + s treatment. In contrast, root biomass showed non-significant differences among treatments at the beginning of the growing season and around early boot stage. All other root traits showed a non-significant interaction between fertilizer treatments and sampling dates, and while there was a significant impact of sampling dates, fertilizer treatments often led to non-significant differences. The N and P omission treatments showed the lowest RLD. Conclusions: These findings demonstrate the strong impact of nutrient omission and developmental stage on shoot and root growth of winter rye.

Nitrogen (N) and phosphorus (P) deficiencies can significantly reduce crop yield. Despite their importance, the impacts of N and P deficiencies under field conditions on cereal roots, particularly winter rye, remain poorly understood. This study investigates the effects of N and P deficiencies on winter rye growth and root architecture under field conditions. A sampling campaign was conducted during the 2022 season at the long-term fertilizer experiment Dikopshof, Germany. Four fertilizer treatments were chosen: (1) fully fertilized with manure (NPKCa+m+s), (2) fully fertilized without manure (NPKCa), (3) N omitted (_PKCa), and (4) P omitted (N_KCa). Shoot biomass was assessed at five growth stages, alongside with topsoil root biomass, number of nodal roots and tillers, and root angle. The results showed that shoot and root biomass were highest in the NPKCa+m+s treatment and lowest under N omission. Although the treatment ranking of root traits varied between dates, a trend for an enhanced number of roots in the N and P omission treatments was observed around flowering. P omission fostered an increased number of tillers and N omission caused steeper root angles compared to other treatments. These findings demonstrate the strong impact of the environment and development stage on root phenotypic plasticity.