How niche mismatches impair our ability to predict potential invasions
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| Format: | Dataset Open Access |
| Langue: | en |
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PANGAEA
2018
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| _version_ | 1867170086207356928 |
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| author | Andrade, André Velazco, Santiago José Elíaz De Marco Júnior, Paulo |
| author_facet | Andrade, André Velazco, Santiago José Elíaz De Marco Júnior, Paulo |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Accurately anticipating potential invasions is a crucial step to deal with invasive species. The most commonly used method to identify suitable areas for invasion is to build Ecological Niche Models (ENMs); nevertheless, the accuracy of these models might be highly overestimated. We explored how biogeographical, biological and methodological factors might affect our ability to identify suitable areas for invasions. We created virtual species to control and explore disagreements between the fundamental and the available niche in the native region. First, we explored how differences in species characteristics (climatic tolerance and dispersal capacity) might hinder our ability to predict invasions with ENMs. We also evaluated how different algorithms behave under those differences. Furthermore, we measured how prediction accuracy varies throughout the world, by evaluating the degree of niche mismatch in each zoogeographic region. In general, ENMs predictions were more accurate for species with broad tolerance, while species with narrow tolerance had high levels of overprediction. We were able to distinguish algorithms by how much they under or overestimate species fundamental niche. Some zoogeographic regions are indeed more error-prone, as levels of climatic incompleteness and fundamental niche representation within the distribution vary throughout the world. We demonstrate that predicting potential invasions with ENMs might incur in wrongful niche estimation, therefore, missing potential locations for invasion. Biological factors such as species tolerance and dispersal capacity must be considered when discussing model uncertainty. Besides, algorithms had different predictions, with high levels of under or over prediction. Therefore, when it comes to invasions predictions, we must be meticulous, considering that the fundamental niche might not be adequately expressed within the native region. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_892658 |
| institution | PANGAEA |
| language | en |
| publishDate | 2018 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | How niche mismatches impair our ability to predict potential invasions Andrade, André Velazco, Santiago José Elíaz De Marco Júnior, Paulo Accurately anticipating potential invasions is a crucial step to deal with invasive species. The most commonly used method to identify suitable areas for invasion is to build Ecological Niche Models (ENMs); nevertheless, the accuracy of these models might be highly overestimated. We explored how biogeographical, biological and methodological factors might affect our ability to identify suitable areas for invasions. We created virtual species to control and explore disagreements between the fundamental and the available niche in the native region. First, we explored how differences in species characteristics (climatic tolerance and dispersal capacity) might hinder our ability to predict invasions with ENMs. We also evaluated how different algorithms behave under those differences. Furthermore, we measured how prediction accuracy varies throughout the world, by evaluating the degree of niche mismatch in each zoogeographic region. In general, ENMs predictions were more accurate for species with broad tolerance, while species with narrow tolerance had high levels of overprediction. We were able to distinguish algorithms by how much they under or overestimate species fundamental niche. Some zoogeographic regions are indeed more error-prone, as levels of climatic incompleteness and fundamental niche representation within the distribution vary throughout the world. We demonstrate that predicting potential invasions with ENMs might incur in wrongful niche estimation, therefore, missing potential locations for invasion. Biological factors such as species tolerance and dispersal capacity must be considered when discussing model uncertainty. Besides, algorithms had different predictions, with high levels of under or over prediction. Therefore, when it comes to invasions predictions, we must be meticulous, considering that the fundamental niche might not be adequately expressed within the native region. |
| title | How niche mismatches impair our ability to predict potential invasions |
| topic | |
| url | https://doi.org/10.1594/PANGAEA.892658 |