How are species interactions structured in species-rich communities? A new method for analysing time-series data.

Published

Journal Article

Estimation of intra- and interspecific interactions from time-series on species-rich communities is challenging due to the high number of potentially interacting species pairs. The previously proposed sparse interactions model overcomes this challenge by assuming that most species pairs do not interact. We propose an alternative model that does not assume that any of the interactions are necessarily zero, but summarizes the influences of individual species by a small number of community-level drivers. The community-level drivers are defined as linear combinations of species abundances, and they may thus represent e.g. the total abundance of all species or the relative proportions of different functional groups. We show with simulated and real data how our approach can be used to compare different hypotheses on community structure. In an empirical example using aquatic microorganisms, the community-level drivers model clearly outperformed the sparse interactions model in predicting independent validation data.

Full Text

Duke Authors

Cited Authors

  • Ovaskainen, O; Tikhonov, G; Dunson, D; Grøtan, V; Engen, S; Sæther, B-E; Abrego, N

Published Date

  • May 2017

Published In

Volume / Issue

  • 284 / 1855

PubMed ID

  • 28539525

Pubmed Central ID

  • 28539525

Electronic International Standard Serial Number (EISSN)

  • 1471-2954

International Standard Serial Number (ISSN)

  • 0962-8452

Digital Object Identifier (DOI)

  • 10.1098/rspb.2017.0768

Language

  • eng