Abstract
| Original language | English |
|---|---|
| Article number | 1003 |
| Journal | Scientific Reports |
| Volume | 8 |
| Early online date | 17 Jan 2018 |
| DOIs | |
| Publication status | Published - 2018 |
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- 10.1038/s41598-017-18927-1Licence: CC BY
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Species distribution modelling: Contrasting presence-only models with plot abundance data. / Gomes, Vitor H. F.; Ijff, Stéphanie D.; Raes, Niels et al.
In: Scientific Reports, Vol. 8, 1003, 2018.Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Species distribution modelling: 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 - de Souza Coelho, Luiz
AU - de Almeida Matos, Francisca Dionízia
AU - Castilho, Carolina V.
AU - de Andrade Lima Filho, Diogenes
AU - López, Dairon Cárdenas
AU - Guevara, Juan Ernesto
AU - Magnusson, William E.
AU - Phillips, Oliver L.
AU - Wittmann, Florian
AU - de Jesus Veiga Carim, Marcelo
AU - Martins, Maria Pires
AU - Irume, Mariana Victória
AU - Sabatier, Daniel
AU - Molino, Jean-François
AU - Bánki, Olaf S.
AU - da Silva Guimarães, José Renan
AU - Pitman, Nigel C. A.
AU - Piedade, Maria Teresa Fernandez
AU - Mendoza, Abel Monteagudo
AU - Luize, Bruno Garcia
AU - Venticinque, Eduardo Martins
AU - De Leão Novo, Evlyn Márcia Moraes
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 - de Sousa Farias, Emanuelle
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 C., Gerardo A.
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 - de Andrade Miranda, Ires Paula
AU - Guillaumet, Jean-Louis
AU - Pinto, Linder Felipe Mozombite
AU - de Matos Bonates, Luiz Carlos
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
Y1 - 2018
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.
U2 - 10.1038/s41598-017-18927-1
DO - 10.1038/s41598-017-18927-1
M3 - Article
VL - 8
JO - Scientific Reports
JF - Scientific Reports
SN - 2045-2322
M1 - 1003
ER -