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ENMeval 2.0 : Redesigned for customizable and reproducible modeling of species’ niches and distributions

Kass, Jamie M. (author)
Biodiversity and Biocomplexity Unit Okinawa Institute of Science and Technology Graduate University Okinawa Japan;PhD Program in Biology The Graduate Center City University of New York New York NY USA;Department of Biology City College of New YorkCity University of New York New York NY USA
Muscarella, Robert (author)
Uppsala universitet,Växtekologi och evolution
Galante, Peter J. (author)
Center for Biodiversity and Conservation American Museum of Natural History New York NY USA
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Bohl, Corentin L. (author)
Innland County CouncilHadeland Videregående Skole Gran Norway
Pinilla‐Buitrago, Gonzalo E. (author)
PhD Program in Biology The Graduate Center City University of New York New York NY USA;Department of Biology City College of New YorkCity University of New York New York NY USA
Boria, Robert A. (author)
Quantitative and Systems Biology Graduate group University of California‐Merced Merced CA USA
Soley‐Guardia, Mariano (author)
Escuela de Biología Universidad de Costa Rica, and Ciudad Universitaria San Pedro Costa Rica
Anderson, Robert P. (author)
PhD Program in Biology The Graduate Center City University of New York New York NY USA;Department of Biology City College of New YorkCity University of New York New York NY USA;Division of Vertebrate Zoology (Mammalogy) American Museum of Natural History New York NY USA
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 (creator_code:org_t)
2021-06-04
2021
English.
In: Methods in Ecology and Evolution. - : John Wiley & Sons. - 2041-210X. ; 12:9, s. 1602-1608
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Quantitative evaluations to optimize complexity have become standard for avoiding overfitting of ecological niche models (ENMs) that estimate species’ potential geographic distributions. ENMeval was the first R package to make such evaluations (often termed model tuning) widely accessible for the Maxent algorithm. It also provided multiple methods for partitioning occurrence data and reported various performance metrics.Requests by users, recent developments in the field, and needs for software compatibility led to a major redesign and expansion. We additionally conducted a literature review to investigate trends in ENMeval use (2015–2019).ENMeval 2.0 has a new object-oriented structure for adding other algorithms, enables customizing algorithmic settings and performance metrics, generates extensive metadata, implements a null-model approach to quantify significance and effect sizes, and includes features to increase the breadth of analyses and visualizations. In our literature review, we found insufficient reporting of model performance and parameterization, heavy reliance on model selection with AICc and low utilization of spatial cross-validation; we explain how ENMeval 2.0 can help address these issues.This redesigned and expanded version can promote progress in the field and improve the information available for decision-making.

Subject headings

NATURVETENSKAP  -- Biologi -- Ekologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Ecology (hsv//eng)

Keyword

cross-validation
ecological niche model
metadata
model evaluation
model tuning
software
spatial
species distribution model

Publication and Content Type

ref (subject category)
art (subject category)

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