Soybean is one of the most important crops for global food security, and understanding the impacts of plant diseases on its productivity is essential, particularly under climate change. Among these diseases, soybean target spot (
Corynespora cassiicola
) has re-emerged as a significant constraint in Brazilian production systems. Current management strategies focus exclusively on yield preservation without accounting for the fossil energy consumed by intensive fungicide use, highlighting the need for an energy-based threshold. Because climate change alters the environmental conditions essential for pathogen development, it is critical to determine whether future scenarios will exacerbate or constrain disease severity, as this directly dictates the frequency of energetically justifiable interventions. This study assessed the future energetic feasibility of chemical control by integrating an epidemiological model with the CROPGRO-Soybean crop model (DSSAT) across 24 Brazilian locations, using five CMIP6 models under three emission scenarios (SSP1-RCP2.6, SSP3-RCP7.0, and SSP5-RCP8.5). Yield losses were converted into energy losses and compared with the energy required for fungicide manufacture and application, establishing the Energy Injury Level (EnIL). The EnIL acts as an energy-based decision threshold, justifying chemical control only when the energy preserved in crop yield surpasses the total energy invested in fungicide interventions. Results indicate that median energy losses decrease across most scenarios toward the end of the century, suggesting a gradual reduction in average disease pressure. However, maximum potential damage increases in the Central and South regions, indicating that severe epidemics may still occur. Consequently, the frequency of energetically justified fungicide applications declines over time. In practice, the EnIL framework provides a tactical tool to help stakeholders optimize fungicide programs, reducing fossil energy waste while ensuring interventions are sustainable under variable future climates.
Climate change poses significant threats to European agricultural production, with increasing frequency and severity of adverse weather events impacting crop yields. Agroforestry, the integration of woody elements into agricultural systems, is recognized as a vital agroecological approach for both climate change mitigation and adaptation, yet key mechanistic and long-term performance questions remain unresolved. This study utilized the mechanistic Hi-sAFe model to simulate 100 years (2001–2100) of silvoarable agroforestry performance at Wakelyns farm in southeastern England, focusing on winter wheat (Triticum aestivum) and pea (Pisum sativum) yields under intermediate (Representative Concentration Pathway 4.5) and very high (Representative Concentration Pathway 8.5) emissions scenarios. The research assessed yield stability, underlying microclimatic and phenological mechanisms, and long-term land-use efficiency (land equivalent ratio). This study demonstrates for the first time that agroforestry functions as a climate shock absorber by protecting crops during a critical early-season phenological window, preventing catastrophic yield failures under climate change scenarios. These protective effects were mechanistically linked to microclimatic modification, likely shade, provided by newly emerged walnut (Juglans regia) leaves during the early stages of crop flowering and grain filling, rather than during peak summer heat. While overall yield stability assessed statistically was not significantly enhanced, the mitigation of extreme downside risk represents a profound benefit for farm resilience. Analysis of land equivalent ratio revealed a substantial initial productivity lag, with consistent land equivalent ratio > 1 achieved only after 80 years for wheat and 40 years for pea, highlighting economic adoption barriers but also the potential for optimized system design and adaptive management to accelerate productivity gains. Overall, these results identify a previously unreported mechanistic and temporal basis for agroforestry’s capacity to buffer temperate arable crops against climate-induced yield shocks.
Colin R. Tosh, Christian Gossell, I. Lecomte et al.· Agronomy for Sustainable Dev...· 0 citations
Sustainable agriculture requires simultaneously increasing food production and mitigating climate change, yet the extent to which crop improvement strategies deliver co-benefits at regional scales remains poorly understood. Improving radiation-use efficiency (RUE) has been widely proposed as a pathway to increase crop productivity, but its potential benefits such as soil organic carbon (SOC) sequestration are not well understood. Here, we developed a hybrid modeling framework that integrates a process-based agricultural system model (APSIM) with machine learning to capture genetic × environment × management (G × E × M) interactions and their effects on crop yield and SOC dynamics across the North China Plain. The results show that improving RUE increases both crop yields and SOC, but the magnitude of these benefits is strongly modulated by nitrogen inputs and varies widely across the region. In the future period (2021–2060) under a moderate-emissions scenario SSP2-4.5, increasing RUE of current cultivars by 10% and 20% led to additional wheat yield gains of 1.1 (+16%) and 1.8 t ha−1 (+26%) and maize gains of 0.8 (+11%) and 1.1 t ha−1 (+14%), respectively. These productivity gains also translated into an increase in SOC sequestration (+10% and +26%, respectively), as a consequence of enhanced carbon inputs. Notably, the coupling between yield gains and SOC sequestration varied substantially across the region, indicating spatially differentiated benefits. Our results highlight that improving RUE can contribute to both productivity and soil carbon gains, but these co-benefits are not universal and depend on local environmental and management contexts. This study provides a scalable and feasible approach for evaluating crop improvement strategies and their environmental consequences represented by SOC dynamics, as well as demonstrate that RUE improvement offers great opportunities for sustainable agriculture.
This study used the DSSAT/CROPGRO-Cotton model and climate projections from EC-Earth3 (SSP2-4.5 and SSP5-8.5 scenarios) up to 2059 to assess the response of cotton yield components to climate change and the sensitivity of the crop genetic parameters in three municipalities representative of Brazilian producing regions: Sapezal (MT), Coromandel (MG) and Luiz Eduardo Magalhães (BA). In order to isolate the climate effect, soil, cultivar and management were kept constant across municipalities; simulations were run under rainfed conditions and without nitrogen limitation. Projections indicate progressive warming and increased interannual variability of maximum temperature and rainfall under SSP5-8.5, with median maximum temperatures approaching 40 °C in Luiz Eduardo Magalhães (BA). The yield response was regionally heterogeneous: Coromandel (MG) showed an increase in productivity up to the 2050s under SSP5-8.5, whereas Luiz Eduardo Magalhães (BA) exhibited a decline after the initial decade and Sapezal (MT) remained relatively stable. The Morris sensitivity analysis identified the maximum leaf photosynthesis rate (LFMAX) as the dominant parameter for total above-ground biomass (CWAD). For lint yield (LIWAM), threshing percentage (THRSH) became the main limiting factor, indicating that the bottleneck under future stress lies in reproductive allocation rather than in maximum carbon assimilation. The duration of the seed-filling phase to physiological maturity (SD-PM) showed increased sensitivity in Coromandel, associated with heat-induced cycle shortening. The σ/μ* ratio revealed a predominantly linear behaviour for LFMAX and THRSH and a non-linear or interaction-dominated response for SFDUR and PODUR. The results, which are comparative in nature across scenarios, support breeding strategies focused on THRSH and on reproductive thermal tolerance for the resilience of Brazilian cotton production.
Edson Magrine de Souza Cavalcante, Nicolas Rian Stenico, Iêdo Peroba de Oliveira Teodoro et al.· Revista de Geopolítica· 0 citations
