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Impacts of species misidentification on species distribution modeling with presence-only data

Costa, Hugo; Foody, Giles M.; Jiménez, Sílvia; Silva, Luís

Authors

Hugo Costa lgxhag@nottingham.ac.uk

GILES FOODY giles.foody@nottingham.ac.uk
Professor of Geographical Information

Sílvia Jiménez

Luís Silva



Abstract

Spatial records of species are commonly misidentified, which can change the predicted distribution of a species obtained from a species distribution model (SDM). Experiments were undertaken to predict the distribution of real and simulated species using MaxEnt and presence-only data “contaminated” with varying rates of misidentification error. Additionally, the difference between the niche of the target and contaminating species was varied. The results show that species misidentification errors may act to contract or expand the predicted distribution of a species while shifting the predicted distribution towards that of the contaminating species. Furthermore the magnitude of the effects was positively related to the ecological distance between the species’ niches and the size of the error rates. Critically, the magnitude of the effects was substantial even when using small error rates, smaller than common average rates reported in the literature, which may go unnoticed while using a standard evaluation method, such as the area under the receiver operating characteristic curve. Finally, the effects outlined were shown to impact negatively on practical applications that use SDMs to identify priority areas, commonly selected for various purposes such as management. The results highlight that species misidentification should not be neglected in species distribution modeling.

Journal Article Type Article
Publication Date Dec 1, 2015
Journal ISPRS International Journal of Geo-Information
Electronic ISSN 2220-9964
Publisher MDPI
Peer Reviewed Not Peer Reviewed
Volume 4
Issue 4
APA6 Citation Costa, H., Foody, G. M., Jiménez, S., & Silva, L. (2015). Impacts of species misidentification on species distribution modeling with presence-only data. ISPRS International Journal of Geo-Information, 4(4),
Keywords species mis-identification; false positive error; presence-only; MaxEnt 2497
Publisher URL http://www.mdpi.com/2220-9964/4/4/2496
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0





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