Refining predictions of metacommunity dynamics by modeling species non-independence

Oystein H. Opedal, Mikael von Numers, Gleb Tikhonov, Otso Ovaskainen

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
44 Downloads (Pure)

Abstract

Predicting the dynamics of biotic communities is difficult because species’ environmental responses are not independent, but covary due to shared or contrasting ecological strategies and the influence of species interactions. We used latent‐variable joint species distribution models to analyze paired historical and contemporary inventories of 585 vascular plant species on 471 islands in the southwest Finnish archipelago. Larger, more heterogeneous islands were characterized by higher colonization rates and lower extinction rates. Ecological and taxonomical species groups explained small but detectable proportions of variance in species’ environmental responses. To assess the potential influence of species interactions on community dynamics, we estimated species associations as species‐to‐species residual correlations for historical occurrences, for colorizations, and for extinctions. Historical species associations could to some extent predict joint colonization patterns, but the overall estimated influence of species associations on community dynamics was weak. These results illustrate the benefits of considering metacommunity dynamics within a joint framework, but also suggest that any influence of species interactions on community dynamics may be hard to detect from observational data.
Original languageEnglish
Article numbere03067
JournalEcology
Volume101
Issue number8
DOIs
Publication statusPublished - Aug 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • island biogeography
  • joint species distribution models
  • metacommunity dynamics
  • species interactions
  • topographic complexity
  • vegetation dynamics

Fingerprint

Dive into the research topics of 'Refining predictions of metacommunity dynamics by modeling species non-independence'. Together they form a unique fingerprint.

Cite this