首页> 外文OA文献 >Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces
【2h】

Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces

机译:温度和降水对欧洲样带小麦产量的影响:使用冲击响应面的作物模型整体分析

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to + 9 degrees C) and precipitation (-50 to + 50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development
机译:这项研究探索了冲击响应面(IRS)方法在调查大范围气候变化下模型合作物产量响应中的效用。春季和冬季小麦普通小麦单产的国税局是由一个基于过程的作物模拟模型的26名成员组成的,该模型用于横跨横向样带的芬兰,德国和西班牙。通过修改每日基准值(1981年至2010年),并固定CO2浓度,测试了模型化的产量对温度变化(-2至+ 9摄氏度)和降水(-50至+ 50%)的系统增量的敏感性。在360 ppm。 IRS方法提供了一种刻画气候变化下模型行为的有效方法,并且具有分析,比较和呈现多模型集成模拟结果的优势。尽管个别模型的行为偶尔会明显偏离平均值,但各个地点和作物品种的总体中值响应表明,产量随温度升高而下降,降水量减少,而降水量增加。在为IRS定义的不确定性范围内,收益对温度的敏感性比芬兰站点的降水变化更为敏感,而德国和西班牙站点的敏感度则有所不同。在较高的温度变化下,沉淀作用减弱。尽管分析的双变量和多模型特征对解释施加了一些限制,但IRS方法仍然提供了对模型间和年际变异敏感性的更多见解。综合起来,这些敏感性可能有助于查明诸如热应激,春化或干旱效应等需要在未来模型开发中进行完善的过程

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号