Climate change has caused widespread shifts in species' phenology, but the consequences for population and community dynamics remain unclear because of uncertainty regarding the species-specific drivers of phenology and abundance, and the implications for synchrony among interacting species. Here, we develop a statistical model to quantify inter-annual variation in phenology and abundance over an environmental gradient, and use it to identify potential drivers of phenology and abundance in co-occurring species. We fit the model to counts of ten butterfly species with single annual generations over a mountain elevation gradient, as an exemplar system in which temporally-limited availability of biotic resources and favorable abiotic conditions impose narrow windows of seasonal activity. We estimate parameters describing changes in abundance, and the peak time and duration of the flight period, over ten years (2004 to 2013) and across twenty sample locations (930 m to 2050 m in central Spain). We also use the model outputs to investigate relationships of phenology and abundance with temperature and rainfall. Annual shifts in phenology were remarkably consistent among species, typically showing earlier flight periods during years with warm conditions in March or May-June. In contrast, inter-annual variation in relative abundance was more variable among species, and generally less well associated with climatic conditions. Nevertheless, warmer temperatures in June were associated with increased relative population growth in three species, and five species had increased relative population growth in years with earlier flight periods. These results suggest that broadly coherent interspecific changes to phenology could help to maintain temporal synchrony in community dynamics under climate change, but that the relative composition of communities may vary due to interspecific inconsistency in population dynamic responses to climate change. However, it may still be possible to predict abundance change for species based on a robust understanding of relationships between their population dynamics and phenology, and the environmental drivers of both.

中文翻译：

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将山地蝴蝶群落的环境、物候和丰度的年际变化联系起来

气候变化已导致物种物候学发生广泛变化，但由于物候学和丰度的特定物种驱动因素以及相互作用物种之间同步性的影响存在不确定性，因此对种群和群落动态的影响仍不清楚。在这里，我们开发了一个统计模型来量化环境梯度上的物候和丰度的年际变化，并用它来确定共同出现的物种的物候和丰度的潜在驱动因素。我们将该模型拟合到在山海拔梯度上具有单年世代的十种蝴蝶物种的计数，作为一个示例系统，其中生物资源的时间有限可用性和有利的非生物条件施加了狭窄的季节性活动窗口。我们估计描述丰度变化的参数，以及飞行期的高峰时间和持续时间，超过十年（2004 年至 2013 年），跨越 20 个样本地点（西班牙中部 930 米至 2050 米）。我们还使用模型输出来研究物候和丰度与温度和降雨的关系。物种间物候的年度变化非常一致，通常在 3 月或 5 月至 6 月气候温暖的年份显示较早的飞行期。相比之下，相对丰度的年际变化在物种之间变化更大，并且通常与气候条件的相关性较差。尽管如此，6 月气温升高与三个物种的相对种群增长增加有关，并且在飞行期较早的年份中，五个物种的相对种群增长有所增加。这些结果表明，广泛一致的种间物候变化有助于在气候变化下保持群落动态的时间同步，但由于种群对气候变化的动态响应的种间不一致，群落的相对组成可能会有所不同。然而，基于对其种群动态和物候学之间关系以及两者的环境驱动因素之间的关系的深入了解，预测物种的丰度变化仍然是可能的。