Species distribution modelling: contrasting presence-only models with plot abundance data

Gomes, Vitor H.F.; IJff, St?phanie D.; Raes, Niels; Amaral, I?da Le?o; Salom?o, Rafael P.; de Souza Coelho, Luiz; de Almeida Matos, Francisca Dion?zia; Castilho, Carolina V.; de Andrade Lima Filho, Diogenes; L?pez, Dairon C?rdenas; Guevara, Juan Ernesto; Magnusson, William E.; Phillips, Oliver L.; Wittmann, Florian; de Jesus Veiga Carim, Marcelo; Martins, Maria Pires; Irume, Mariana Vict?ria; Sabatier, Daniel; Molino, Jean-Fran?ois; B?nki, Olaf S.; da Silva Guimar?es, Jos? Renan; Pitman, Nigel C.A.; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; de Le?o Novo, Evlyn M?rcia Moraes; Vargas, Percy N??ez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S.; Marimon, Ben-Hur; Coronado, Euridice N. Honorio; Feldpausch, Ted R.; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicol?s Casta?o; Killeen, Timothy J.; Mostace...

Abstract

Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species’ area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.

Citation

Gomes, V. H., IJff, S. D., Raes, N., Amaral, I. L., Salomão, R. P., de Souza Coelho, L., de Almeida Matos, F. D., Castilho, C. V., de Andrade Lima Filho, D., López, D. C., Guevara, J. E., Magnusson, W. E., Phillips, O. L., Wittmann, F., de Jesus Veiga Carim, M., Martins, M. P., Irume, M. V., Sabatier, D., Molino, J.-F., Bánki, O. S., …ter Steege, H. (in press). Species distribution modelling: contrasting presence-only models with plot abundance data. Scientific Reports, 8(1), Article 1003. https://doi.org/10.1038/s41598-017-18927-1

• Journal Article Type: Article
• Acceptance Date: Dec 20, 2017
• Online Publication Date: Jan 17, 2018
• Deposit Date: Feb 26, 2018
• Publicly Available Date: Feb 26, 2018
• Journal: Scientific Reports
• Electronic ISSN: 2045-2322
• Publisher: Nature Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 8
• Issue: 1
• Article Number: 1003
• DOI: https://doi.org/10.1038/s41598-017-18927-1
• Keywords: biodiversity; ecological modelling
• Public URL: https://nottingham-repository.worktribe.com/output/905023
• Publisher URL: https://doi.org/10.1038/s41598-017-18927-1
• Contract Date: Feb 26, 2018