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Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage.
Konowalik, Kamil; Nosol, Agata.
Afiliação
  • Konowalik K; Department of Plant Biology, Institute of Environmental Biology, Wroclaw University of Environmental and Life Sciences, Kozuchowska 5b, 51-631, Wroclaw, Poland. kamil.konowalik@upwr.edu.pl.
  • Nosol A; Department of Plant Biology, Institute of Environmental Biology, Wroclaw University of Environmental and Life Sciences, Kozuchowska 5b, 51-631, Wroclaw, Poland.
Sci Rep ; 11(1): 1482, 2021 01 15.
Article em En | MEDLINE | ID: mdl-33452285
ABSTRACT
We examine how different datasets, including georeferenced hardcopy maps of different extents and georeferenced herbarium specimens (spanning the range from 100 to 85,000 km2) 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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Polônia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Polônia