Biotic interactions boost spatial models of species richness
Biotic interactions are known to affect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter‐specific interactions. Here, we test whether incorporating biotic interaction...
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Online Access: | http://dx.doi.org/10.1111/ecog.01129 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fecog.01129 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.01129 |
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crwiley:10.1111/ecog.01129 2024-06-02T08:02:21+00:00 Biotic interactions boost spatial models of species richness Mod, Heidi K. le Roux, Peter C. Guisan, Antoine Luoto, Miska 2015 http://dx.doi.org/10.1111/ecog.01129 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fecog.01129 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.01129 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Ecography volume 38, issue 9, page 913-921 ISSN 0906-7590 1600-0587 journal-article 2015 crwiley https://doi.org/10.1111/ecog.01129 2024-05-03T11:24:46Z Biotic interactions are known to affect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter‐specific interactions. Here, we test whether incorporating biotic interactions into high‐resolution models alters predictions of species richness as hypothesised. We included key biotic variables (cover of three dominant arctic‐alpine plant species) into two methodologically divergent species richness modelling frameworks – stacked species distribution models (SSDM) and macroecological models (MEM) – for three ecologically and evolutionary distinct taxonomic groups (vascular plants, bryophytes and lichens). Predictions from models including biotic interactions were compared to the predictions of models based on climatic and abiotic data only. Including plant–plant interactions consistently and significantly lowered bias in species richness predictions and increased predictive power for independent evaluation data when compared to the conventional climatic and abiotic data based models. Improvements in predictions were constant irrespective of the modelling framework or taxonomic group used. The global biodiversity crisis necessitates accurate predictions of how changes in biotic and abiotic conditions will potentially affect species richness patterns. Here, we demonstrate that models of the spatial distribution of species richness can be improved by incorporating biotic interactions, and thus that these key predictor factors must be accounted for in biodiversity forecasts. Article in Journal/Newspaper Arctic Wiley Online Library Arctic Ecography 38 9 913 921 |
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description |
Biotic interactions are known to affect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter‐specific interactions. Here, we test whether incorporating biotic interactions into high‐resolution models alters predictions of species richness as hypothesised. We included key biotic variables (cover of three dominant arctic‐alpine plant species) into two methodologically divergent species richness modelling frameworks – stacked species distribution models (SSDM) and macroecological models (MEM) – for three ecologically and evolutionary distinct taxonomic groups (vascular plants, bryophytes and lichens). Predictions from models including biotic interactions were compared to the predictions of models based on climatic and abiotic data only. Including plant–plant interactions consistently and significantly lowered bias in species richness predictions and increased predictive power for independent evaluation data when compared to the conventional climatic and abiotic data based models. Improvements in predictions were constant irrespective of the modelling framework or taxonomic group used. The global biodiversity crisis necessitates accurate predictions of how changes in biotic and abiotic conditions will potentially affect species richness patterns. Here, we demonstrate that models of the spatial distribution of species richness can be improved by incorporating biotic interactions, and thus that these key predictor factors must be accounted for in biodiversity forecasts. |
format |
Article in Journal/Newspaper |
author |
Mod, Heidi K. le Roux, Peter C. Guisan, Antoine Luoto, Miska |
spellingShingle |
Mod, Heidi K. le Roux, Peter C. Guisan, Antoine Luoto, Miska Biotic interactions boost spatial models of species richness |
author_facet |
Mod, Heidi K. le Roux, Peter C. Guisan, Antoine Luoto, Miska |
author_sort |
Mod, Heidi K. |
title |
Biotic interactions boost spatial models of species richness |
title_short |
Biotic interactions boost spatial models of species richness |
title_full |
Biotic interactions boost spatial models of species richness |
title_fullStr |
Biotic interactions boost spatial models of species richness |
title_full_unstemmed |
Biotic interactions boost spatial models of species richness |
title_sort |
biotic interactions boost spatial models of species richness |
publisher |
Wiley |
publishDate |
2015 |
url |
http://dx.doi.org/10.1111/ecog.01129 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fecog.01129 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.01129 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Ecography volume 38, issue 9, page 913-921 ISSN 0906-7590 1600-0587 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1111/ecog.01129 |
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Ecography |
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38 |
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9 |
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913 |
op_container_end_page |
921 |
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1800746859483889664 |