de Mendoza, G., Kaivosoja, R., Grönroos, M., Hjort, J., Ilmonen, J., Kärnä, O., Paasivirta, L., Tokola, L., Heino, J. (2017) Highly variable species distribution models in a subarctic stream metacommunity: Patterns, mechanisms and implications. , 63 (1), 33-47. doi:10.1111/fwb.12993
Highly variable species distribution models in a subarctic stream metacommunity : patterns, mechanisms and implications
|Author:||de Mendoza, Guillermo1,2; Kaivosoja, Riikka3; Grönroos, Mira4;|
1Centre for Advanced Studies of Blanes, Spanish National Research Council (CEAB‐CSIC), Blanes, Spain
2Laboratoire GEODE, UMR 5602 CNRS, Université Toulouse‐Jean Jaurès, Toulouse, France
3Geography Research Unit, University of Oulu, Oulu, Finland
4Department of Environmental Sciences, Section of Environmental Ecology, University of Helsinki, Lahti, Finland
5Metsähallitus, Natural Heritage Services, Vantaa, Finland
6Ruuhikoskenkatu 17, Salo, Finland
7Natural Environment Centre, Biodiversity, Finnish Environment Institute, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019060719501
John Wiley & Sons,
|Publish Date:|| 2019-06-07
1. 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.
2. We first modelled the presence/absence of 47 stream insects in northernmost Finland, using binomial generalised linear models (GLMs). 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.
3. 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 GLMs 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.
4. 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 entirely neutral framework unrealistic as well. According to the three‐component framework, our results suggest that the stream insect metacommunity is shaped by the effect of habitat heterogeneity (supporting both species‐sorting and mass effects), rather than species equivalence or dispersal limitation.
5. While the relative importance of the source‐sink dynamics perspective or the species‐sorting paradigm cannot be deciphered with the data at our disposal, we can conclude that habitat heterogeneity is an important driver shaping species distributions and insect assemblages in subarctic stream metacommunities. These results exemplify that the use of the three‐component metacommunity framework may be more useful than the classical four perspective paradigm in analysing metacommunities. Our findings also provide support for conservation strategies based on the preservation of heterogeneous habitats in a metacommunity context.
|Pages:||33 - 47|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
1181 Ecology, evolutionary biology
This study is part of the project “Spatial scaling, metacommunity structure and patterns in stream communities” that was supported financially by a grant from the Academy of Finland. Further support was provided by grants (no: 273557, no: 267995 and no: 285040) from the Academy of Finland. The authors declare no conflict of interest.
|Academy of Finland Grant Number:||
285040 (Academy of Finland Funding decision)
© 2017 John Wiley & Sons Ltd. This is the peer reviewed version of the following article: de Mendoza, G., Kaivosoja, R., Grönroos, M., Hjort, J., Ilmonen, J., Kärnä, O., Paasivirta, L., Tokola, L., Heino, J. (2017) Highly variable species distribution models in a subarctic stream metacommunity: Patterns, mechanisms and implications. , 63 (1), 33-47. doi:10.1111/fwb.12993. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.