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

TY - JOUR

T1 - Species Distribution Modelling

T2 - Contrasting presence-only models with plot abundance data

AU - Gomes, Vitor H.F.

AU - Ijff, Stéphanie D.

AU - Raes, Niels

AU - Amaral, Iêda Leão

AU - Salomão, Rafael P.

AU - Coelho, Luiz De Souza

AU - Matos, Francisca Dionízia De Almeida

AU - Castilho, Carolina V.

AU - Filho, Diogenes De Andrade Lima

AU - López, Dairon Cárdenas

AU - Guevara, Juan Ernesto

AU - Magnusson, William E.

AU - Phillips, Oliver L.

AU - Wittmann, Florian

AU - Carim, Marcelo De Jesus Veiga

AU - Martins, Maria Pires

AU - Irume, Mariana Victória

AU - Sabatier, Daniel

AU - Molino, Jean François

AU - Bánki, Olaf S.

AU - Guimarães, José Renan Da Silva

AU - Pitman, Nigel C.A.

AU - Piedade, Maria Teresa Fernandez

AU - Mendoza, Abel Monteagudo

AU - Luize, Bruno Garcia

AU - Venticinque, Eduardo Martins

AU - Novo, Evlyn Márcia Moraes De Leão

AU - Vargas, Percy Núñez

AU - Silva, Thiago Sanna Freire

AU - Manzatto, Angelo Gilberto

AU - Terborgh, John

AU - Reis, Neidiane Farias Costa

AU - Montero, Juan Carlos

AU - Casula, Katia Regina

AU - Marimon, Beatriz S.

AU - Marimon, Ben Hur

AU - Coronado, Euridice N.Honorio

AU - Feldpausch, Ted R.

AU - Duque, Alvaro

AU - Zartman, Charles Eugene

AU - Arboleda, Nicolás Castaño

AU - Killeen, Timothy J.

AU - Mostacedo, Bonifacio

AU - Vasquez, Rodolfo

AU - Schöngart, Jochen

AU - Assis, Rafael L.

AU - Medeiros, Marcelo Brilhante

AU - Simon, Marcelo Fragomeni

AU - Andrade, Ana

AU - Laurance, William F.

AU - Camargo, José Luís

AU - Demarchi, Layon O.

AU - Laurance, Susan G.W.

AU - Farias, Emanuelle De Sousa

AU - Nascimento, Henrique Eduardo Mendonça

AU - Revilla, Juan David Cardenas

AU - Quaresma, Adriano

AU - Costa, Flavia R.C.

AU - Vieira, Ima Célia Guimarães

AU - Cintra, Bruno Barçante Ladvocat

AU - Castellanos, Hernán

AU - Brienen, Roel

AU - Stevenson, Pablo R.

AU - Feitosa, Yuri

AU - Duivenvoorden, Joost F.

AU - Aymard, Gerardo A.C.

AU - Mogollón, Hugo F.

AU - Targhetta, Natalia

AU - Comiskey, James A.

AU - Vicentini, Alberto

AU - Lopes, Aline

AU - Damasco, Gabriel

AU - Dávila, Nállarett

AU - García-Villacorta, Roosevelt

AU - Levis, Carolina

AU - Schietti, Juliana

AU - Souza, Priscila

AU - Emilio, Thaise

AU - Alonso, Alfonso

AU - Neill, David

AU - Dallmeier, Francisco

AU - Ferreira, Leandro Valle

AU - Araujo-Murakami, Alejandro

AU - Praia, Daniel

AU - Do Amaral, Dário Dantas

AU - Carvalho, Fernanda Antunes

AU - De Souza, Fernanda Coelho

AU - Feeley, Kenneth

AU - Arroyo, Luzmila

AU - Pansonato, Marcelo Petratti

AU - Gribel, Rogerio

AU - Villa, Boris

AU - Licona, Juan Carlos

AU - Fine, Paul V.A.

AU - Cerón, Carlos

AU - Baraloto, Chris

AU - Jimenez, Eliana M.

AU - Stropp, Juliana

AU - Engel, Julien

AU - Silveira, Marcos

AU - Mora, Maria Cristina Peñuela

AU - Petronelli, Pascal

AU - Maas, Paul

AU - Thomas-Caesar, Raquel

AU - Henkel, Terry W.

AU - Daly, Doug

AU - Paredes, Marcos Ríos

AU - Baker, Tim R.

AU - Fuentes, Alfredo

AU - Peres, Carlos A.

AU - Chave, Jerome

AU - Pena, Jose Luis Marcelo

AU - Dexter, Kyle G.

AU - Silman, Miles R.

AU - Jørgensen, Peter Møller

AU - Pennington, Toby

AU - Di Fiore, Anthony

AU - Valverde, Fernando Cornejo

AU - Phillips, Juan Fernando

AU - Rivas-Torres, Gonzalo

AU - Von Hildebrand, Patricio

AU - Van Andel, Tinde R.

AU - Ruschel, Ademir R.

AU - Prieto, Adriana

AU - Rudas, Agustín

AU - Hoffman, Bruce

AU - Vela, César I.A.

AU - Barbosa, Edelcilio Marques

AU - Zent, Egleé L.

AU - Gonzales, George Pepe Gallardo

AU - Doza, Hilda Paulette Dávila

AU - Miranda, Ires Paula De Andrade

AU - Guillaumet, Jean Louis

AU - Pinto, Linder Felipe Mozombite

AU - Bonates, Luiz Carlos De Matos

AU - Silva, Natalino

AU - Gómez, Ricardo Zárate

AU - Zent, Stanford

AU - Gonzales, Therany

AU - Vos, Vincent A.

AU - Malhi, Yadvinder

AU - Oliveira, Alexandre A.

AU - Cano, Angela

AU - Albuquerque, Bianca Weiss

AU - Vriesendorp, Corine

AU - Correa, Diego Felipe

AU - Torre, Emilio Vilanova

AU - Van Der Heijden, Geertje

AU - Ramirez-Angulo, Hirma

AU - Ramos, José Ferreira

AU - Young, Kenneth R.

AU - Rocha, Maira

AU - Nascimento, Marcelo Trindade

AU - Medina, Maria Natalia Umaña

AU - Tirado, Milton

AU - Wang, Ophelia

AU - Sierra, Rodrigo

AU - Torres-Lezama, Armando

AU - Mendoza, Casimiro

AU - Ferreira, Cid

AU - Baider, Cláudia

AU - Villarroel, Daniel

AU - Balslev, Henrik

AU - Mesones, Italo

AU - Giraldo, Ligia Estela Urrego

AU - Casas, Luisa Fernanda

AU - Reategui, Manuel Augusto Ahuite

AU - Linares-Palomino, Reynaldo

AU - Zagt, Roderick

AU - Cárdenas, Sasha

AU - Farfan-Rios, William

AU - Sampaio, Adeilza Felipe

AU - Pauletto, Daniela

AU - Sandoval, Elvis H.Valderrama

AU - Arevalo, Freddy Ramirez

AU - Huamantupa-Chuquimaco, Isau

AU - Garcia-Cabrera, Karina

AU - Hernandez, Lionel

AU - Gamarra, Luis Valenzuela

AU - Alexiades, Miguel N.

AU - Pansini, Susamar

AU - Cuenca, Walter Palacios

AU - Milliken, William

AU - Ricardo, Joana

AU - Lopez-Gonzalez, Gabriela

AU - Pos, Edwin

AU - Ter Steege, Hans

PY - 2018/12/1

Y1 - 2018/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85041379841&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041379841&partnerID=8YFLogxK

U2 - 10.1038/s41598-017-18927-1

DO - 10.1038/s41598-017-18927-1

M3 - Article

C2 - 29343741

AN - SCOPUS:85041379841

VL - 8

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 18927

ER -