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Fitness consequences of centrality in mutualistic individual-based networks

机译:互惠的基于个人的网络中集中性的适应性后果

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摘要

The relationships among the members of a population can be visualized using individual networks, where each individual is a node connected to each other by means of links describing the interactions. The centrality of a given node captures its importance within the network. We hypothesize that in mutualistic networks, the centrality of a node should benefit its fitness. We test this idea studying eight individual-based networks originated from the interaction between Erysimum mediohispanicum and its flower visitors. In these networks, each plant was considered a node and was connected to conspecifics sharing flower visitors. Centrality indicates how well connected is a given E. mediohispanicum individual with the rest of the co-occurring conspecifics because of sharing flower visitors. The centrality was estimated by three network metrics: betweenness, closeness and degree. The complex relationship between centrality, phenotype and fitness was explored by structural equation modelling. We found that the centrality of a plant was related to its fitness, with plants occupying central positions having higher fitness than those occupying peripheral positions. The structural equation models (SEMs) indicated that the centrality effect on fitness was not merely an effect of the abundance of visits and the species richness of visitors. Centrality has an effect even when simultaneously accounting for these predictors. The SEMs also indicated that the centrality effect on fitness was because of the specific phenotype of each plant, with attractive plants occupying central positions in networks, in relation to the distribution of conspecific phenotypes. This finding suggests that centrality, owing to its dependence on social interactions, may be an appropriate surrogate for the interacting phenotype of individuals.
机译:人口成员之间的关系可以使用单独的网络可视化,其中每个人都是通过描述相互作用的链接相互连接的节点。给定节点的中心性抓住了它在网络中的重要性。我们假设在互惠网络中,节点的中心性应有利于其适应性。我们测试了这个想法,研究了八种基于个体的网络,这些网络起源于大叶菊花和它的花朵访客之间的相互作用。在这些网络中,每个植物都被视为一个节点,并连接到共享花朵访客的物种上。中心性表明由于共享鲜花访客,给定的中空肠埃希菌个体与其余共生物种之间的联系程度很高。中心性是通过三个网络指标来估计的:中间性,亲密性和程度。通过结构方程模型探索了中心性,表型和适应性之间的复杂关系。我们发现植物的中心性与其适应性有关,占据中心位置的植物具有比占据外围位置的植物更高的适应性。结构方程模型(SEM)表明,对健身的集中度影响不仅是访客数量的丰富和访客物种丰富度的影响。即使同时考虑这些预测因素,中心性也会起作用。 SEM还表明,对适应性的中心作用是由于每种植物的特定表型,相对于特定表型的分布,有吸引力的植物在网络中占据中心位置。这一发现表明,中心性由于其对社会互动的依赖,可能是个体相互作用表型的适当替代。

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