作者: Miguel Ruiz-Ramos , Roberto Ferrise , A Rodríguez , IJ Lorite , Marco Bindi
DOI: 10.1016/J.AGSY.2017.01.009
关键词: Agricultural engineering 、 Phenology 、 Vernalization 、 Soil type 、 Environmental science 、 Irrigation 、 Climate change 、 Cropping 、 Adaptation 、 Mediterranean climate 、 Agronomy
摘要: Adaptation of crops to climate change has be addressed locally due the variability soil, and specific socio-economic settings influencing farm management decisions. rainfed cropping systems in Mediterranean is especially challenging projected decline precipitation coming decades, which will increase risk droughts. Methods that can help explore uncertainties projections crop modelling, such as impact response surfaces (IRSs) ensemble then valuable for identifying effective adaptations. Here, an 17 models was used simulate a total 54 adaptation options winter wheat (Triticum aestivum) at Lleida (NE Spain). To support building, ex post quality check model simulations based on several criteria performed. Those were “According Our Current Knowledge” (AOCK) concept, been formalized here. Adaptations changes cultivars regarding phenology, vernalization, sowing date irrigation. The effects under changed (P), temperature (T), [CO2] soil type analysed by constructing surfaces, we termed, accordance with their purpose, (ARSs). These created assess effect adaptations through range plausible P, T perturbations. results indicated impacts altered predominantly negative. No single capable overcoming detrimental complex interactions imposed perturbations except supplementary irrigation (sI), reduced potential most Yet, combination dealing demonstrated possible Lleida. Combinations cultivar without vernalization requirements showed good wide potential. Few combined performed well conditions. However, sI sufficient develop high potential, including mainly spring wheat, current cycle duration early date. Depending local environment (e.g. type), many these maintain yield levels moderate some also strong changes. We conclude ARSs offer useful tool supporting planning field level conditions uncertainty.