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Why large-scale climate indices seem to predict ecological processes better than local weather

机译:为什么大型气候指数似乎比当地天气更好地预测生态过程

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Large-scale climatic indices such as the North Atlantic Oscillation(1) are associated with population dynamics(2), variation in demographic rates(3) and values of phenotypic traits(4,5) in many species. Paradoxically, these large-scale indices can seem to be better predictors of ecological processes than local climate(5-8). Using detailed data from a population of Soay sheep(9,10), we show that high rainfall, high winds or low temperatures at any time during a 3-month period can cause mortality either immediately or lagged by a few days. Most measures of local climate used by ecologists fail to capture such complex associations between weather and ecological process, and this may help to explain why large-scale, seasonal indices of climate spanning several months can outperform local climatic factors. Furthermore, we show why an understanding of the mechanism by which climate influences population ecology is important. Through simulation we demonstrate that the timing of bad weather within a period of mortality can have an important modifying influence on intra-specific competition for food, revealing an interaction between climate and density dependence(11) that the use of large-scale climatic indices or inappropriate local weather variables might obscure.
机译:诸如北大西洋涛动(1)之类的大规模气候指数与许多物种的种群动态(2),人口变化率(3)和表型特征值(4,5)相关。自相矛盾的是,与地方气候相比,这些大规模指数似乎可以更好地预测生态过程(5-8)。使用来自Soay绵羊种群的详细数据(9,10),我们显示在3个月的任何时间中的高降雨量,大风或低温都可能导致立即死亡或几天后死亡。生态学家使用的大多数当地气候测量方法都无法捕捉到天气与生态过程之间的这种复杂联系,这可能有助于解释为什么跨越数月的大规模季节性季节指数可以胜过当地气候因素。此外,我们说明了为什么了解气候影响人口生态的机制很重要。通过模拟,我们证明了死亡期间恶劣天气的时机可能对种内竞争对食物产生重要的修正影响,揭示了气候与密度依赖性之间的相互作用(11),即使用大规模气候指数或不适当的当地天气变量可能会模糊不清。

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