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Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage
We examine how different datasets, including georeferenced hardcopy maps of different extents and georeferenced herbarium specimens (spanning the range from 100 to 85,000 km(2)) influence ecological niche modeling. We check 13 of the available environmental niche modeling algorithms, using 30 metric...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811024/ https://www.ncbi.nlm.nih.gov/pubmed/33452285 http://dx.doi.org/10.1038/s41598-020-80062-1 |
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author | Konowalik, Kamil Nosol, Agata |
author_facet | Konowalik, Kamil Nosol, Agata |
author_sort | Konowalik, Kamil |
collection | PubMed |
description | We examine how different datasets, including georeferenced hardcopy maps of different extents and georeferenced herbarium specimens (spanning the range from 100 to 85,000 km(2)) influence ecological niche modeling. We check 13 of the available environmental niche modeling algorithms, using 30 metrics to score their validity and evaluate which are useful for the selection of the best model. The validation is made using an independent dataset comprised of presences and absences collected in a range-wide field survey of Carpathian endemic plant Leucanthemum rotundifolium (Compositae). Our analysis of models’ predictive performances indicates that almost all datasets may be used for the construction of a species distributional range. Both very local and very general datasets can produce useful predictions, which may be more detailed than the original ranges. Results also highlight the possibility of using the data from manually georeferenced archival sources in reconstructions aimed at establishing species’ ecological niches. We discuss possible applications of those data and associated problems. For the evaluation of models, we suggest employing AUC, MAE, and Bias. We show an example of how AUC and MAE may be combined to select the model with the best performance. |
format | Online Article Text |
id | pubmed-7811024 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78110242021-01-21 Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage Konowalik, Kamil Nosol, Agata Sci Rep Article We examine how different datasets, including georeferenced hardcopy maps of different extents and georeferenced herbarium specimens (spanning the range from 100 to 85,000 km(2)) influence ecological niche modeling. We check 13 of the available environmental niche modeling algorithms, using 30 metrics to score their validity and evaluate which are useful for the selection of the best model. The validation is made using an independent dataset comprised of presences and absences collected in a range-wide field survey of Carpathian endemic plant Leucanthemum rotundifolium (Compositae). Our analysis of models’ predictive performances indicates that almost all datasets may be used for the construction of a species distributional range. Both very local and very general datasets can produce useful predictions, which may be more detailed than the original ranges. Results also highlight the possibility of using the data from manually georeferenced archival sources in reconstructions aimed at establishing species’ ecological niches. We discuss possible applications of those data and associated problems. For the evaluation of models, we suggest employing AUC, MAE, and Bias. We show an example of how AUC and MAE may be combined to select the model with the best performance. Nature Publishing Group UK 2021-01-15 /pmc/articles/PMC7811024/ /pubmed/33452285 http://dx.doi.org/10.1038/s41598-020-80062-1 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Konowalik, Kamil Nosol, Agata Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage |
title | Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage |
title_full | Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage |
title_fullStr | Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage |
title_full_unstemmed | Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage |
title_short | Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage |
title_sort | evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811024/ https://www.ncbi.nlm.nih.gov/pubmed/33452285 http://dx.doi.org/10.1038/s41598-020-80062-1 |
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