Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

被引:132
作者
Giovanelli, Joao G. R. [1 ,2 ]
de Siqueira, Marinez Ferreira [3 ]
Haddad, Celio F. B. [1 ]
Alexandrino, Joao [1 ]
机构
[1] Univ Estadual Paulista UNESP, Inst Biociencias, Dept Zool, BR-13506970 Rio Claro, SP, Brazil
[2] Univ Estadual Paulista UNESP, Inst Biociencias, Grad Program Zool, BR-13506970 Rio Claro, SP, Brazil
[3] Inst Pesquisas Jardim Bot Rio de Janeiro, Rio De Janeiro, Brazil
基金
巴西圣保罗研究基金会;
关键词
Amphibia; BIOCLIM; Calibration area; DOMAIN; MAXENT; OM-GARP; Pseudoabsence; SVM; Minimum presence threshold; SAMPLE SELECTION BIAS; SPECIES DISTRIBUTION; TRANSFERABILITY; PREDICTION; GARP;
D O I
10.1016/j.ecolmodel.2009.10.009
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
We here examine species distribution models for a Neotropical anuran restricted to ombrophilous areas in the Brazilian Atlantic Forest hotspot. We extend the known occurrence for the treefrog Hypsiboas bischoffi (Anura: Hylidae) through GPS field surveys and use five modeling methods (BIOCLIM, DOMAIN, OM-GARP, SVM, and MAXENT) and selected bioclimatic and topographic variables to model the species distribution. Models were first trained using two calibration areas: the Brazilian Atlantic Forest (BAF) and the whole of South America (SA). All modeling methods showed good levels of predictive power and accuracy with mean AUC ranging from 0.77 (BIOCLIM/BAF) to 0.99 (MAXENT/SA). MAXENT and SVM were the most accurate presence-only methods among those tested here. All but the SVM models calibrated with SA predicted larger distribution areas when compared to models calibrated in BAF. OM-GARP dramatically overpredicted the species distribution for the model calibrated in SA, with a predicted area around 10(6) km(2) larger than predicted by other SDMs. With increased calibration area (and environmental space), OM-GARP predictions followed changes in the environmental space associated with the increased calibration area, while MAXENT models were more consistent across calibration areas. MAXENT was the only method that retrieved consistent predictions across calibration areas, while allowing for some overprediction, a result that may be relevant for modeling the distribution of other spatially restricted organisms. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:215 / 224
页数:10
相关论文
共 46 条
[1]   Evaluating predictive models of species' distributions: criteria for selecting optimal models [J].
Anderson, RP ;
Lew, D ;
Peterson, AT .
ECOLOGICAL MODELLING, 2003, 162 (03) :211-232
[2]  
[Anonymous], 2002, DIVA GIS GEOGRAPHIC
[3]  
Busby J. R., 1991, Plant Protection Quarterly, V6, P8
[4]   DOMAIN - A FLEXIBLE MODELING PROCEDURE FOR MAPPING POTENTIAL DISTRIBUTIONS OF PLANTS AND ANIMALS [J].
CARPENTER, G ;
GILLISON, AN ;
WINTER, J .
BIODIVERSITY AND CONSERVATION, 1993, 2 (06) :667-680
[5]   A large-scale model of wolf distribution in Italy for conservation planning [J].
Corsi, F ;
Duprè, E ;
Boitani, L .
CONSERVATION BIOLOGY, 1999, 13 (01) :150-159
[6]   Modelling ecological niches with support vector machines [J].
Drake, John M. ;
Randin, Christophe ;
Guisan, Antoine .
JOURNAL OF APPLIED ECOLOGY, 2006, 43 (03) :424-432
[7]   Profiling ecosystem vulnerability to invasion by zebra mussels with support vector machines [J].
Drake, John M. ;
Bossenbroek, Jonathan M. .
THEORETICAL ECOLOGY, 2009, 2 (04) :189-198
[8]  
Duellman W.E., 1994, BIOL AMPHIBIANS, DOI 10.56021/9780801847806
[9]  
Elith J, 2002, PREDICTING SPECIES OCCURRENCES: ISSUES OF ACCURACY AND SCALE, P303
[10]   Novel methods improve prediction of species' distributions from occurrence data [J].
Elith, J ;
Graham, CH ;
Anderson, RP ;
Dudík, M ;
Ferrier, S ;
Guisan, A ;
Hijmans, RJ ;
Huettmann, F ;
Leathwick, JR ;
Lehmann, A ;
Li, J ;
Lohmann, LG ;
Loiselle, BA ;
Manion, G ;
Moritz, C ;
Nakamura, M ;
Nakazawa, Y ;
Overton, JM ;
Peterson, AT ;
Phillips, SJ ;
Richardson, K ;
Scachetti-Pereira, R ;
Schapire, RE ;
Soberón, J ;
Williams, S ;
Wisz, MS ;
Zimmermann, NE .
ECOGRAPHY, 2006, 29 (02) :129-151