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Meta‐analyzing the likely cross‐species responses to climate change
Ecological Niche Models (ENMs) have different performances in predicting potential geographic distributions. Here we meta‐analyzed the likely effects of climate change on the potential geographic distribution of 1,205 bird species from the Neotropical region, modeled using eight ENMs and three Atmos...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6802043/ https://www.ncbi.nlm.nih.gov/pubmed/31641461 http://dx.doi.org/10.1002/ece3.5617 |
Sumario: | Ecological Niche Models (ENMs) have different performances in predicting potential geographic distributions. Here we meta‐analyzed the likely effects of climate change on the potential geographic distribution of 1,205 bird species from the Neotropical region, modeled using eight ENMs and three Atmosphere‐Ocean General Circulation Models (AOGCM). We considered the variability in ENMs performance to estimate a weighted mean difference between potential geographic distributions for baseline and future climates. On average, potential future ranges were projected to be from 25.7% to 44.5% smaller than current potential ranges across species. However, we found that 0.2% to 18.3% of the total variance in range shifts occurred “within species” (i.e., owing to the use of different modeling techniques and climate models) and 81.7% to 99.8% remained between species (i.e., it could be explained by ecological correlates). Using meta‐analytical techniques akin to regression, we also showed that potential range shifts are barely predicted by bird biological traits. We demonstrated that one can combine and reduce species‐specific effects with high uncertainty in ENMs and also explore potential causes of climate change effect on species using meta‐analytical tools. We also highlight that the search for powerful correlates of climate change‐induced range shifts can be a promising line of investigation. |
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