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首页> 外文期刊>Basic and Applied Ecology >Correlations between weather conditions and common vole (Microtus arvalis) densities identified by regression tree analysis
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Correlations between weather conditions and common vole (Microtus arvalis) densities identified by regression tree analysis

机译:通过回归树分析确定天气状况与普通田鼠(田鼠)密度之间的相关性

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Population dynamics of fluctuating and cyclic rodent populations can be impacted by particular weather parameters. In temperate areas there are interrelations between different weather parameters, which make identification difficult. However, this is necessary because small rodents are relevant for both the food web and crop damage especially in the face of climate change. We used both, boosted regression tree and classification and regression tree methods to identify weather conditions correlating with the active burrow index (ABI) of common voles (Microtus arvalis) from 1974 to 1998 in the high outbreak risk area of Central Germany. Highest ABI occurred in perennial crops in fall with a maximum of more than 2000 active burrows per 1000 m(2). Boosted regression tree analysis showed that between 12 and 20 weather parameters could have a relative influence on vole ABIs ranging from 2% to 19%. Classification and regression tree analysis highlighted that the number of days with snow cover in December and March, rainfall amount in spring and maximum temperature in October seem to be key indicators for ABIs in the following year in spring. Monthly maximum temperatures of February to June and the amount of precipitation in April and July were correlated to ABIs in fall. Quantitative validation showed an agreement of ABI distribution on regional scale >85%. This represents the first study to identify complex weather conditions including single parameter thresholds correlated with common vole abundance in a temperate area. The results have the potential to aid the development of predictive models for small rodent dynamics and they inspire further detailed search for regulative mechanisms of small mammal dynamics.
机译:波动和周期性啮齿动物种群的种群动态会受到特定天气参数的影响。在温带地区,不同的天气参数之间存在相互关系,这使识别变得困难。但是,这是必要的,因为小啮齿动物与食物网和农作物的损害都息息相关,尤其是面对气候变化时。我们使用增强回归树方法和分类回归树方法来确定与1974年至1998年德国中部高爆发风险地区普通田鼠(田鼠)的主动洞穴指数(ABI)相关的天气状况。秋季,多年生作物中的ABI最高,每1000 m(2)最多有2000多个活动洞穴。增强回归树分析表明,在12至20个天气参数之间,田鼠ABI的相对影响范围为2%至19%。分类和回归树分析强调,12月和3月有积雪的天数,春季的降雨量和10月的最高温度似乎是次年春季ABI的关键指标。 2月至6月的月最高气温以及4月和7月的降水量与秋季的ABI相关。定量验证显示,ABI分布在区域范围内> 85%的协议。这是首次确定复杂天气条件的研究,包括与温带地区普通田鼠丰度相关的单个参数阈值。这些结果有可能帮助开发小型啮齿动物动力学的预测模型,并激发对小型哺乳动物动力学的调控机制的进一步详细研究。

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