ArticleEcology and evolution2023
Not only climate: The importance of biotic interactions in shaping species distributions at macro scales.
Article in Ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 37 citations in OpenAlex.
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- Trophic Cascades and Habitat Suitability in Udanti Sitanadi Tiger Reserve: Impacts of Prey Depletion and Climate Change on Predator-Prey Dynamics.Zoological studies · 2025Article
- The role of species interactions in shaping the geographic pattern of ungulate abundance across African savannah.Scientific reports · 2024Article
- Extracting secondary data from citizen science images reveals host flower preferences of the Mexican grass-carrying waspEcology and evolution · 2024Article
- Soil nematode metacommunities in different land covers: Assessment at the local and regional scales.Ecology and evolution · 2024Article
- A dataset on African bats' functional traits.Scientific data · 2023Article
- Not only climate: The importance of biotic interactions in shaping species distributions at macro scales.Ecology and evolution · 2023Article
- Biotic interactions and their consequences for macroevolution: learning from the fossil record and beyond.Paleobiology · 2008Article
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abiotic factors are usually considered key drivers of species distribution at macro scales, while biotic interactions are mostly used at local scales. A few studies have explored the role of biotic interactions at macro scales, but all considered a limited number of species and obligate interactions. We examine the role of biotic interactions in large-scale SDMs by testing two main hypotheses: (1) biotic factors in SDMs can have an important role at continental scale; (2) the inclusion of biotic factors in large-scale SDMs is important also for generalist species. We used a maximum entropy algorithm to model the distribution of 177 bat species in Africa calibrating two SDMs for each species: one considering only abiotic variables (noBIO-SDMs) and the other (BIO-SDMs) including also biotic variables (trophic resource richness). We focused the interpretation of our results on variable importance and response curves. For each species, we also compared the potential distribution measuring the percentage of change between the two models in each pixel of the study area. All models gave AUC >0.7, with values on average higher in BIO-SDMs compared to noBIO-SDMs. Trophic resources showed an importance overall higher level than all abiotic predictors in most of the species (~68%), including generalist species. Response curves were highly interpretable in all models, confirming the ecological reliability of our models. Model comparison between the two models showed a change in potential distribution for more than 80% of the species, particularly in tropical forests and shrublands. Our results highlight the importance of considering biotic interactions in SDMs at macro scales. We demonstrated that a generic biotic proxy can be important for modeling species distribution when species-specific data are not available, but we envision that a multi-scale analysis combined with a better knowledge of the species might provide a better understanding of the role of biotic interactions.
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