Complex positive connections between functional groups are revealed by neural network analysis of ecological time series.

Abstract

The relationships between functional linkages within communities and community dynamics are fundamental to biodiversity-stability relationships. By teasing apart the hidden layers within artificial neural networks (ANNs), we developed webs defining how functional groups influence each other's temporal dynamics. ANNs were based on 15 years of bimonthly monitoring of macrobenthic communities on three intertidal sandflats in Manukau Harbor (New Zealand). Sites differed in web topology and diversity, with the site dominated by one functional group exhibiting only a few strong links, the lowest alpha-, beta-, and gamma-diversity, and the highest temporal stability in alpha-diversity. However, positive interactions between functional groups, nonconcordant with harborwide or site-specific environmental variables, always dominated the interaction webs. The increased number of links we observed with increased temporal variation of species richness within functional groups and overall diversity supports the insurance hypothesis. While our findings suggest that there may be no consistent model characterizing the topology of temporal interactions between functional groups, decreasing diversity is likely to decouple interactions between functional groups and decrease ecosystem functionality.

DOI: 10.1086/587069

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Cite this paper

@article{Thrush2008ComplexPC, title={Complex positive connections between functional groups are revealed by neural network analysis of ecological time series.}, author={Simon F Thrush and Giovanni Coco and Judi E. Hewitt}, journal={The American naturalist}, year={2008}, volume={171 5}, pages={669-77} }