Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co‐variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant–hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis‐based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.

中文翻译：

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比较沿环境梯度的物种相互作用网络

需要以相互作用网络的形式了解物种组成及其相互作用，以了解塑造它们随时间和空间分布的过程。因此，比较沿环境梯度的生态网络代表了一种了解生命组织的有前途的新研究途径。沿着环境梯度的网络内联系的位置和强度的变化可能是由物种组成的更替、物种丰度的变化以及对物种相互作用的非生物影响驱动的。虽然调查物种组成的变化有着悠久的传统，但到目前为止，只有少数研究检查了网络之间物种相互作用的变化，通常采用不同的方法。这里，我们回顾了调查网络结构沿环境梯度变化的研究，强调了关于标准化的方法论决定如何影响他们的结论。由于其复杂性，生态网络之间的变化经常使用总结交互分布或拓扑结构的属性进行研究，例如链接数、连接性或模块性。这些属性可以直接比较，也可以使用标准化程序进行比较。虽然网络结构的度量可以与沿环境梯度的变化直接相关，但经常使用标准化来通过控制一些协变量或通过空模型来促进对网络属性变化的解释。零模型允许比较经验网络与随机预期的偏差，并有望在生态网络与功能特征耦合时提供对塑造生态网络的因素的更机械的理解。作为说明，我们比较了量化特征匹配在驱动植物-蜂鸟互惠网络结构中的作用的方法，即直接比较，由零模型和基于假设的元网络标准化。总的来说，我们的分析警告不要对依赖于不同标准化形式的研究进行比较，因为它们可能会突出不同的信号。更好地了解可用的分析工具及其检测到的信号将有助于深入了解生态网络如何以及为何随环境梯度变化。