Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model.
Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model.
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DOI：
10.1111/oik.00857
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发表时间：
2014-10-01
期刊：
影响因子：
--
通讯作者：
Scheffler K
中科院分区：
文献类型：
--
作者：
Minoarivelo HO;Hui C;Terblanche JS;Pond SL;Scheffler K
生态相互作用网络，例如描述植物与其传粉者之间或植物与其食果动物之间的互利相互作用的网络，表现出非随机的结构特性，无法用简单的网络形成模型来解释。影响这种网络的形成和最终结构的因素之一是它的进化历史。我们认为，在许多情况下，这与参与相互作用的物种的进化历史密切相关。事实上，对相互作用网络以及相互作用物种的系统发育的实证研究已经证明了系统发育和网络结构之间的显着关联。然而，迄今为止，还没有提出生成模型来解释单个物种的进化如何影响相互作用网络的进化。我们提出了一个模型，利用分子进化的系统发育模型，将成对相互作用的进化描述为分支马尔可夫过程。利用相互作用物种的系统发育知识，我们的模型明显更好地拟合了一组植物 - 传粉媒介和植物 - 食果动物互惠网络的 21％。这凸显了在绝大多数情况下继承交互模式的重要性，而不排除生态新颖性在形成当前网络架构中的潜在作用。我们建议，在评估其他因素在塑造生态网络出现中的作用时，我们的模型可以用作控制进化信号的零模型。
Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non-random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant – pollinator and plant – frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks.
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影响因子：
3.4
作者：
Almeida-Neto, Mario;Guimaraes, Paulo;Ulrich, Werner
通讯作者：
Ulrich, Werner
影响因子：
8.8
作者：
Encinas-Viso, Francisco;Revilla, Tomas A.;Etienne, Rampal S.
通讯作者：
Etienne, Rampal S.
影响因子：
8.8
作者：
Guimaraes, Paulo R., Jr.;Jordano, Pedro;Thompson, John N.
通讯作者：
Thompson, John N.
影响因子：
3.4
作者：
Anderson B;Terblanche JS;Ellis AG
通讯作者：
Ellis AG
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y