Highly variable species distribution models in a subarctic stream metacommunity: Patterns, mechanisms and implications

Abstract Metacommunity theory focuses on assembly patterns in ecological communities, originally exemplified through four different, yet non‐exclusive, perspectives: patch dynamics, species sorting, source‐sink dynamics, and neutral theory. More recently, three exclusive components have been propose...

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Bibliographic Details
Published in:Freshwater Biology
Main Authors: de Mendoza, Guillermo, Kaivosoja, Riikka, Grönroos, Mira, Hjort, Jan, Ilmonen, Jari, Kärnä, Olli‐Matti, Paasivirta, Lauri, Tokola, Laura, Heino, Jani
Other Authors: Suomen Akatemia
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2017
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Online Access:http://dx.doi.org/10.1111/fwb.12993
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Ffwb.12993
https://onlinelibrary.wiley.com/doi/pdf/10.1111/fwb.12993
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Summary:Abstract Metacommunity theory focuses on assembly patterns in ecological communities, originally exemplified through four different, yet non‐exclusive, perspectives: patch dynamics, species sorting, source‐sink dynamics, and neutral theory. More recently, three exclusive components have been proposed to describe a different metacommunity framework: habitat heterogeneity, species equivalence, and dispersal. Here, we aim at evaluating the insect metacommunity of a subarctic stream network under these two different frameworks. We first modelled the presence/absence of 47 stream insects in northernmost Finland, using binomial generalised linear models ( GLM s). The deviance explained by pure local environmental (E), spatial (S), and climatic variables (C) was then analysed across species using beta regression. In this comparative analysis, site occupancy, as well as taxonomic and biological trait vectors obtained from principal coordinate analysis, were used as predictor variables. Single‐species distributions were better explained by in‐stream environmental and spatial factors than by climatic forcing, but in a highly variable fashion. This variability was difficult to relate to the taxonomic relatedness among species or their biological trait similarity. Site occupancy, however, was related to model performance of the binomial GLM s based on spatial effects: as populations are likely to be better connected for common species due to their near ubiquity, spatial factors may also explain better their distributions. According to the classical four‐perspective framework, the observation of both environmental and spatial effects suggests a role for either mass effects or species sorting constrained by dispersal limitation, or both. Taxonomic and biological traits, including the different dispersal capability of species, were scarcely important, which undermines the patch dynamics perspective, based on differences in dispersal ability between species. The highly variable performance of models makes the reliance on an ...