The effects of space and diversity of interaction types on the stability of complex ecological networks |
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Authors: | Miguel?Lurgi Daniel?Montoya Email author" target="_blank">José?M?MontoyaEmail author |
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Institution: | 1.CREAF,Barcelona,Spain;2.School of Biological Sciences, Life Science Building,University of Bristol,Bristol,UK;3.Ecological Networks and Global Change Group, Experimental Ecology Station,Centre National de la Recherche Scientifique,Moulis,France;4.Environment Institute and School of Biological Sciences,University of Adelaide,North Terrace,Australia |
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Abstract: | The relationship between structure and stability in ecological networks and the effect of spatial dynamics on natural communities have both been major foci of ecological research for decades. Network research has traditionally focused on a single interaction type at a time (e.g. food webs, mutualistic networks). Networks comprising different types of interactions have recently started to be empirically characterized. Patterns observed in these networks and their implications for stability demand for further theoretical investigations. Here, we employed a spatially explicit model to disentangle the effects of mutualism/antagonism ratios in food web dynamics and stability. We found that increasing levels of plant-animal mutualistic interactions generally resulted in more stable communities. More importantly, increasing the proportion of mutualistic vs. antagonistic interactions at the base of the food web affects different aspects of ecological stability in different directions, although never negatively. Stability is either not influenced by increasing mutualism—for the cases of population stability and species’ spatial distributions—or is positively influenced by it—for spatial aggregation of species. Additionally, we observe that the relative increase of mutualistic relationships decreases the strength of biotic interactions in general within the ecological network. Our work highlights the importance of considering several dimensions of stability simultaneously to understand the dynamics of communities comprising multiple interaction types. |
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