Modelling heterogeneity in the classification process in multi‐species distribution models can improve predictive performance

Modelling heterogeneity in the classification process in multi‐species distribution models can improve predictive performance

Abstract Species distribution models and maps from large‐scale biodiversity data are necessary for conservation management. One current issue is that biodiversity data are prone to taxonomic misclassifications. Methods to account for these misclassifications in multi‐species distribution models have...

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Bibliographic Details
Main Authors: Kwaku Peprah Adjei, Anders Gravbrøt Finstad, Wouter Koch, Robert Brian O'Hara
Format: Article
Language:English
Published: Wiley 2024-03-01
Series:Ecology and Evolution
Subjects:
Bayesian models
citizen science
false positives
machine learning
misclassification
multi‐species distribution models
Online Access:https://doi.org/10.1002/ece3.11092

Internet

https://doi.org/10.1002/ece3.11092

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