The application of complex network theory to community ecology has enabled quantification of interactions among large suites of species and clarified patterns of community structure across systems. Past analyses, however, have assumed that ecological networks are temporally static and persistent and spatially homogeneous, which could confound inference if species interactions vary over time and space. To evaluate temporal and spatial variation in mutualistic networks, therefore, we evaluated the consistency of a nectarivory/pollination network across years, by season, and over space. We tracked nectaring interactions among 37 butterfly and 58 flowering plant taxa during an 11‐yr period (2007–2017), across each summer and over a grassland landscape in Pennsylvania, USA. The composition of butterflies, plants, and their interactions varied markedly across years, months, and sites. Despite this compositional variation, one metric of network structure, nestedness, was invariant, with interactions much more nested than random across all years, months, and sites. Together with previous studies, this result suggests ecological interaction networks are generally more nested than expected by chance. Other measures of network structure were more variable, especially over time. Numbers of plants and interactions varied by year, month, and site. Connectance and numbers of butterflies varied annually and seasonally. Temporal variation in specialization was also evident for some species at an annual level and for the community across the season. We further found highly stable species were almost always generalists, while highly specialized species were almost always temporally and spatially variable, with few exceptions. Together, these results suggest communities are comprised of a reliable core of generalist species, accompanied by a changing suite of specialist species that, when participating in the network, primarily interact with the reliable core species. Our finding of nested mutualistic network centered on stable‐generalist species accompanied by a changing suite of sporadic specialists indicates dynamic changes in ecological communities vary with topological position. This finding further suggests that, even as rare species are highly threatened by species invasion, climate change, and other anthropogenic perturbations, network structure may be robust to species loss and compositional change from these perturbations.

中文翻译：

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稳定的通才种建立了动态​​授粉网络

复杂网络理论在社区生态学中的应用已实现了对大型物种之间相互作用的量化，并阐明了整个系统中社区结构的模式。然而，过去的分析假设生态网络在时间上是静态的，持久的并且在空间上是同质的，如果物种相互作用随时间和空间而变化，这可能会混淆推断。因此，为了评估互惠网络中的时间和空间变化，我们评估了跨年，按季节和跨空间的花蜜/授粉网络的一致性。我们追踪了在11年期间（2007年至2017年），整个夏季以及美国宾夕法尼亚州的草地景观中37种蝴蝶和58种开花植物类群之间的花蜜相互作用。蝴蝶，植物的组成，并且它们之间的互动在数年，数月和不同地点之间也存在显着差异。尽管存在这种组成差异，但网络结构的一种度量标准（嵌套）是不变的，在所有年份，月份和站点中，相互作用比嵌套的相互作用要多得多。与先前的研究一起，该结果表明，生态相互作用网络通常比偶然的预期嵌套得更多。网络结构的其他度量更具可变性，尤其是随着时间的推移。植物的数量和相互作用随年份，月份和地点的不同而变化。蝴蝶的连通性和数量每年和季节性变化。在某些物种的年度水平和整个季节的整个社区中，专业化的时间变化也很明显。我们还发现高度稳定的物种几乎总是通才，而高度专业化的物种几乎总是随时间和空间变化的，只有少数例外。总之，这些结果表明，社区由通才种的可靠核心组成，并伴随着不断变化的专业物种套件，这些专家物种在参与网络时主要与可靠的核心物种相互作用。我们发现，以稳定的贵族物种为中心的嵌套互惠网络，伴随着零星专家的变化，表明生态群落的动态变化随拓扑位置的变化而变化。这一发现进一步表明，即使稀有物种受到物种入侵，气候变化和其他人为干扰的高度威胁，网络结构也可能对这些干扰造成的物种损失和成分变化具有鲁棒性。