Wild cricket social networks show stability across generations.
Wild cricket social networks show stability across generations.
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DOI：
10.1186/s12862-016-0726-9
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发表时间：
2016-07-27
影响因子：
3.4
通讯作者：
Tregenza T
中科院分区：
文献类型：
--
作者：
Fisher DN;Rodríguez-Muñoz R;Tregenza T
动物环境的核心部分是它与同种动物的相互作用。人们对以社交网络的形式捕捉这些互动的潜力越来越感兴趣。这样的网络可以用来研究个体之间的关系如何影响生态和进化过程。然而，在选择和进化的背景下，这种方法的效用依赖于跨代持续存在的社会网络结构。这是一个很难测试的假设，因为没有跨多代的网络。我们构建了社交网络的6年一次的一个为期8年的野生种群蟋蟀Gryllus campestris。通过使用指数随机图模型（ERGMs），我们发现任何一年的网络都能够预测其他年份的网络结构。任何一年的网络模型预测其他年份的网络的能力，并不取决于这些年份在时间上相隔多远。相反，网络模型预测另一年网络结构的能力取决于这些年之间人口规模的相似性。我们的研究结果表明，板球社会网络结构抵制个人的营业额，是稳定的跨代。这将允许依赖于网络结构的进化过程发生。网络规模的影响可能表明，将关于社会行为的研究结果从小群体扩大到大群体将是困难的。我们的研究还说明了ERGMs比较网络的实用性，一个有效的方法一直难以捉摸的任务。本文的在线版本（doi：10.1186/s12862-016-0726-9）包含补充材料，可供授权用户使用。
A central part of an animal's environment is its interactions with conspecifics. There has been growing interest in the potential to capture these interactions in the form of a social network. Such networks can then be used to examine how relationships among individuals affect ecological and evolutionary processes. However, in the context of selection and evolution, the utility of this approach relies on social network structures persisting across generations. This is an assumption that has been difficult to test because networks spanning multiple generations have not been available. We constructed social networks for six annual generations over a period of eight years for a wild population of the cricket Gryllus campestris. Through the use of exponential random graph models (ERGMs), we found that the networks in any given year were able to predict the structure of networks in other years for some network characteristics. The capacity of a network model of any given year to predict the networks of other years did not depend on how far apart those other years were in time. Instead, the capacity of a network model to predict the structure of a network in another year depended on the similarity in population size between those years. Our results indicate that cricket social network structure resists the turnover of individuals and is stable across generations. This would allow evolutionary processes that rely on network structure to take place. The influence of network size may indicate that scaling up findings on social behaviour from small populations to larger ones will be difficult. Our study also illustrates the utility of ERGMs for comparing networks, a task for which an effective approach has been elusive. The online version of this article (doi:10.1186/s12862-016-0726-9) contains supplementary material, which is available to authorized users.