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Modelling as a tool for analysing the temperature-dependent future of the Colorado potato beetle in Europe.

机译:作为分析欧洲科罗拉多马铃薯甲虫依赖温度的未来的工具进行建模。

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摘要

A warmer climate may increase the risk of attacks by insect pests on agricultural crops, and questions on how to adapt management practice have created a need for impact models. Phenological models driven by climate data can be used for assessing the potential distribution and voltinism of different insect species, but the quality of the simulations is influenced by a range of uncertainties. In this study, we model the temperature-dependent activity and development of the Colorado potato beetle, and analyse the influence of uncertainty associated with parameterization of temperature and day length response. We found that the developmental threshold has a major impact on the simulated number of generations per year. Little is known about local adaptations and individual variations, but the use of an upper and a lower developmental threshold gave an indication on the potential variation. The day length conditions triggering diapause are known only for a few populations. We used gridded observed temperature data to estimate local adaptations, hypothesizing that cold autumns can leave a footprint in the population genetics by low survival of individuals not reaching the adult stage before winter. Our study indicated that the potential selection pressure caused by climate conditions varies between European regions. Provided that there is enough genetic variation, a local adaption at the northern distribution limit would reduce the number of unsuccessful initiations and thereby increase the potential for spreading to areas currently not infested. The simulations of the impact model were highly sensitive to biases in climate model data, i.e. systematic deviations in comparison with observed weather, highlightening the need of improved performance of regional climate models. Even a moderate temperature increase could change the voltinism of Leptinotarsa decemlineata in Europe, but knowledge on agricultural practice and strategies for countermeasures is needed to evaluate changes in risk of attacks.Digital Object Identifier http://dx.doi.org/10.1111/gcb.12119
机译:气候变暖可能会增加害虫侵袭农作物的风险,有关如何适应管理实践的问题也产生了影响模型的需求。由气候数据驱动的物候模型可用于评估不同昆虫物种的潜在分布和伏安性,但是模拟的质量受到一系列不确定性的影响。在这项研究中,我们对科罗拉多马铃薯甲虫的温度依赖性活性和发育进行建模,并分析与温度和日长响应参数化相关的不确定性的影响。我们发现,发育阈值对每年模拟的世代数有重大影响。关于局部适应和个体变异知之甚少,但是使用较高和较低的发育阈值可以说明潜在的变异。触发滞育的日长条件仅针对少数人群。我们使用网格化的观测温度数据来估计局部适应性,假设寒冷的秋天可能由于未在冬季之前到达成年阶段的个体的低存活率而在种群遗传学中​​留下足迹。我们的研究表明,由气候条件引起的潜在选择压力在欧洲地区之间有所不同。只要有足够的遗传变异,在北部分布极限处的局部适应将减少未成功启动的数量,从而增加传播到目前未受感染的地区的可能性。影响模型的模拟对气候模型数据中的偏差高度敏感,即与观测到的天气相比存在系统偏差,这突出表明需要改善区域气候模型的性能。即使是适度的温度升高也可能改变欧洲Leptinotarsa decemlineata的侵染性,但需要农业实践知识和对策来评估攻击风险的变化。数字对象标识符http://dx.doi.org/10.1111/gcb .12119

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