Species interactions are known to structure ecological communities. Still, the influence of climate change on biodiversity has primarily been evaluated by correlating individual species distributions with local climatic descriptors, then extrapolating into future climate scenarios. We ask whether predictions on arctic arthropod response to climate change can be improved by accounting for species interactions. For this, we use a 14-year-long, weekly time series from Greenland, resolved to the species level by mitogenome mapping. During the study period, temperature increased by 2°C and arthropod species richness halved. We show that with abiotic variables alone, we are essentially unable to predict species responses, but with species interactions included, the predictive power of the models improves considerably. Cascading trophic effects thereby emerge as important in structuring biodiversity response to climate change. Given the need to scale up from species-level to community-level projections of biodiversity change, these results represent a major step forward for predictive ecology.

中文翻译：

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考虑物种相互作用对于预测北极节肢动物群落如何应对气候变化是必要的

已知物种相互作用可以构建生态群落。尽管如此，气候变化对生物多样性的影响主要是通过将个体物种分布与当地气候描述符相关联，然后外推到未来的气候情景来评估的。我们询问是否可以通过考虑物种相互作用来改善对北极节肢动物对气候变化反应的预测。为此，我们使用格陵兰岛为期 14 年的每周时间序列，通过有丝分裂基因组图解析到物种水平。在研究期间，温度升高了 2°C，节肢动物物种丰富度减半。我们表明，仅凭非生物变量，我们基本上无法预测物种反应，但包括物种相互作用，模型的预测能力显着提高。因此，级联的营养效应在构建生物多样性对气候变化的响应中变得同样重要。鉴于需要将生物多样性变化的物种级别预测扩大到社区级别，这些结果代表了预测生态学向前迈出的重要一步。