Species Distribution Modelling: Contrasting presence-only models with plot abundance data

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.

Metadata

Item Type:	Article
Authors/Creators:	Gomes, VHF IJff, SD Raes, N Amaral, IL Salomão, RP de Souza Coelho, L de Almeida Matos, FD Castilho, CV de Andrade Lima Filho, D López, DC Guevara, JE Magnusson, WE Phillips, OL https://orcid.org/0000-0002-8993-6168 Wittmann, F de Jesus Veiga Carim, M Martins, MP Irume, MV Sabatier, D Molino, J-F Bánki, OS da Silva Guimarães, JR Pitman, NCA Piedade, MTF Mendoza, AM Luize, BG Venticinque, EM de Leão Novo, EMM Vargas, PN Silva, TSF Manzatto, AG Terborgh, J Reis, NFC Montero, JC Casula, KR Marimon, BS Marimon, B-H Honorio Coronado, EN Feldpausch, TR Duque, A Zartman, CE Arboleda, NC Killeen, TJ Mostacedo, B Vasquez, R Schöngart, J Assis, RL Medeiros, MB Simon, MF Andrade, A Laurance, WF Camargo, JL Demarchi, LO Laurance, SGW de Sousa Farias, E Nascimento, HEM Revilla, JDC Quaresma, A Costa, FRC Vieira, ICG Barcante Ladvocat Cintra, B Castellanos, H Brienen, R Stevenson, PR Feitosa, Y Duivenvoorden, JF Aymard C, GA Mogollón, HF Targhetta, N Comiskey, JA Vicentini, A Lopes, A Damasco, G Dávila, N García-Villacorta, R Levis, C Schietti, J Souza, P Emilio, T Alonso, A Neill, D Dallmeier, F Ferreira, LV Araujo-Murakami, A Praia, D do Amaral, DD Carvalho, FA Coelho de Souza, F Feeley, K Arroyo, L Pansonato, MP Gribel, R Villa, B Licona, JC Fine, PVA Cerón, C Baraloto, C Jimenez, EM Stropp, J Engel, J Silveira, M Mora, MCP Petronelli, P Maas, P Thomas-Caesar, R Henkel, TW Daly, D Paredes, MR Baker, TR Fuentes, A Peres, CA Chave, J Pena, JLM Dexter, KG Silman, MR Jørgensen, PM Pennington, T Di Fiore, A Valverde, FC Phillips, JF Rivas-Torres, G von Hildebrand, P van Andel, TR Ruschel, AR Prieto, A Rudas, A Hoffman, B Vela, CIA Barbosa, EM Zent, EL Gonzales, GPG Doza, HPD de Andrade Miranda, IP Guillaumet, J-L Pinto, LFM de Matos Bonates, LC Silva, N Gómez, RZ Zent, S Gonzales, T Vos, VA Malhi, Y Oliveira, AA Cano, A Albuquerque, BW Vriesendorp, C Correa, DF Torre, EV van der Heijden, G Ramirez-Angulo, H Ramos, JF Young, KR Rocha, M Nascimento, MT Medina, MNU Tirado, M Wang, O Sierra, R Torres-Lezama, A Mendoza, C Ferreira, C Baider, C Villarroel, D Balslev, H Mesones, I Giraldo, LEU Casas, LF Reategui, MAA Linares-Palomino, R Zagt, R Cárdenas, S Farfan-Rios, W Sampaio, AF Pauletto, D Sandoval, EHV Arevalo, FR Huamantupa-Chuquimaco, I Garcia-Cabrera, K Hernandez, L Gamarra, LV Alexiades, MN Pansini, S Cuenca, WP Milliken, W Ricardo, J Lopez-Gonzalez, G Pos, E Ter Steege, H
Copyright, Publisher and Additional Information:	(c) 2018, The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
Dates:	Published: 17 January 2018 Accepted: 20 December 2017
Institution:	The University of Leeds
Academic Units:	The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Ecology & Global Change (Leeds)
Funding Information:	Funder Grant number NERC NE/I028122/1
Depositing User:	Symplectic Publications
Date Deposited:	22 Jan 2018 16:04
Last Modified:	22 Jan 2018 16:04
Status:	Published
Publisher:	Springer Nature
Identification Number:	10.1038/s41598-017-18927-1
Related URLs:	Author
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:126459

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Species Distribution Modelling: Contrasting presence-only models with plot abundance data

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