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Flower-power: Flower diversity is a stronger predictor of network structure than insect diversity in an Arctic plant-pollinator network

机译:花的力量:在北极植物-传粉媒介网络中,花的多样性比昆虫的多样性更能预测网络结构

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摘要

Both plant and insect communities undergo phenological changes across the season, leading to seasonal changes in species diversity and interactions. Network theory offers important tools for understanding how groups of flowering plants and insects interact. However, most studies of plant–pollinator networks aggregate samples over time, masking phenological changes in the network over the growing season. Furthermore, estimates of biodiversity are derived from network observations, meaning that the ecological community is not assessed independently from the structure of the network. Understanding how biodiversity influences network structure over time is important for predicting how global change will affect the ecological processes shaping networks. In this study, we sampled the flower community, insect community, and the pollination network of a high Arctic dwarf-shrub ecosystem over the course of an entire growing season. We found that the flower community was a stronger predictor of network complexity and interaction diversity than the insect community. We suggest that studying networks at scales relevant to both plants and pollinators can provide insight into the mechanisms underlying network formation. This improved knowledge could help to better understand and predict the ongoing phenological changes in Arctic and alpine ecosystems.
机译:植物和昆虫群落在整个季节都经历物候变化,从而导致物种多样性和相互作用的季节性变化。网络理论为理解开花植物和昆虫如何相互作用提供了重要的工具。但是,大多数关于植物-授粉媒介网络的研究会随时间聚集样本,从而掩盖了整个生长季节网络中的物候变化。此外,对生物多样性的估计是从网络观测中得出的,这意味着对生态群落的评估并非独立于网络的结构。了解生物多样性如何随着时间影响网络结构对于预测全球变化将如何影响塑造网络的生态过程非常重要。在这项研究中,我们在整个生长季节中对北极矮矮灌木生态系统的花群落,昆虫群落和授粉网络进行了采样。我们发现,花群落比昆虫群落更能预测网络的复杂性和相互作用的多样性。我们建议研究与植物和授粉媒介有关的规模的网络可以提供对网络形成基础机制的见解。知识的提高可以帮助更好地了解和预测北极和高山生态系统中正在进行的物候变化。

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