An evaluation of methods for modelling distribution of Patagonian insects

Various studies have shown that model performance may vary depending on the species being modelled, the study área, or the number of sampled localities, and suggest that it is necessary to assess which model is better for a particular situation. Thus, in this study we evalúate the performance of dif...

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Autores principales:	TOGNELLI,MARCELO F, ROIG-JUÑENT,SERGIO A, MARVALDI,ADRIANA E, FLORES,GUSTAVO E, LOBO,JORGE M
Lenguaje:	English
Publicado:	Sociedad de Biología de Chile 2009
Materias:	Expert opinión model evaluation Patagonia pseudo-absence data species distribution modelling
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-078X2009000300003
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spelling	oai:scielo:S0716-078X20090003000032009-11-19An evaluation of methods for modelling distribution of Patagonian insectsTOGNELLI,MARCELO FROIG-JUÑENT,SERGIO AMARVALDI,ADRIANA EFLORES,GUSTAVO ELOBO,JORGE M Expert opinión model evaluation Patagonia pseudo-absence data species distribution modelling Various studies have shown that model performance may vary depending on the species being modelled, the study área, or the number of sampled localities, and suggest that it is necessary to assess which model is better for a particular situation. Thus, in this study we evalúate the performance of different techniques for modelling the distribution of Patagonian insects. We applied eight of the most widely used modelling methods (artificial neural networks, BIOCLIM, classification and regression trees, DOMAIN, generalized additive models, GARP, generalized linear models, and Maxent) to the distribution of ten Patagonian insect species. We compared model performance with five accuracy measures. To overeóme the problem of not having reliable absence data with which to evalúate model performance, we used randomly selected pseudo-absences located outside of the polygon área defined by taxonomic experts. Our analyses show significant differences among modelling methods depending on the chosen accuracy measure. Maxent performed the best according to four out of the five accuracy measures, although its accuracy did not differ significantly from that obtained with artificial neural networks. When assessed on per species basis, Maxent was also one of the strongest performing methods, particularly for species sampled from a relatively low number of localities. Overall, our study identified four groups of modelling techniques based on model performance. The top-performing group is composed of Maxent and artificial neural networks, followed closely by the DOMAIN technique. The third group includes GARP, GAM, GLM, and CART, and the fourth best performer is the BIOCLIM technique. Although these results may allow obtaining better distributional predictions for reserve selection, it is necessary to be cautious in their use due to the provisional nature of these simulations.info:eu-repo/semantics/openAccessSociedad de Biología de ChileRevista chilena de historia natural v.82 n.3 20092009-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-078X2009000300003en10.4067/S0716-078X2009000300003
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Expert opinión model evaluation Patagonia pseudo-absence data species distribution modelling
spellingShingle	Expert opinión model evaluation Patagonia pseudo-absence data species distribution modelling TOGNELLI,MARCELO F ROIG-JUÑENT,SERGIO A MARVALDI,ADRIANA E FLORES,GUSTAVO E LOBO,JORGE M An evaluation of methods for modelling distribution of Patagonian insects
description	Various studies have shown that model performance may vary depending on the species being modelled, the study área, or the number of sampled localities, and suggest that it is necessary to assess which model is better for a particular situation. Thus, in this study we evalúate the performance of different techniques for modelling the distribution of Patagonian insects. We applied eight of the most widely used modelling methods (artificial neural networks, BIOCLIM, classification and regression trees, DOMAIN, generalized additive models, GARP, generalized linear models, and Maxent) to the distribution of ten Patagonian insect species. We compared model performance with five accuracy measures. To overeóme the problem of not having reliable absence data with which to evalúate model performance, we used randomly selected pseudo-absences located outside of the polygon área defined by taxonomic experts. Our analyses show significant differences among modelling methods depending on the chosen accuracy measure. Maxent performed the best according to four out of the five accuracy measures, although its accuracy did not differ significantly from that obtained with artificial neural networks. When assessed on per species basis, Maxent was also one of the strongest performing methods, particularly for species sampled from a relatively low number of localities. Overall, our study identified four groups of modelling techniques based on model performance. The top-performing group is composed of Maxent and artificial neural networks, followed closely by the DOMAIN technique. The third group includes GARP, GAM, GLM, and CART, and the fourth best performer is the BIOCLIM technique. Although these results may allow obtaining better distributional predictions for reserve selection, it is necessary to be cautious in their use due to the provisional nature of these simulations.
author	TOGNELLI,MARCELO F ROIG-JUÑENT,SERGIO A MARVALDI,ADRIANA E FLORES,GUSTAVO E LOBO,JORGE M
author_facet	TOGNELLI,MARCELO F ROIG-JUÑENT,SERGIO A MARVALDI,ADRIANA E FLORES,GUSTAVO E LOBO,JORGE M
author_sort	TOGNELLI,MARCELO F
title	An evaluation of methods for modelling distribution of Patagonian insects
title_short	An evaluation of methods for modelling distribution of Patagonian insects
title_full	An evaluation of methods for modelling distribution of Patagonian insects
title_fullStr	An evaluation of methods for modelling distribution of Patagonian insects
title_full_unstemmed	An evaluation of methods for modelling distribution of Patagonian insects
title_sort	evaluation of methods for modelling distribution of patagonian insects
publisher	Sociedad de Biología de Chile
publishDate	2009
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-078X2009000300003
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An evaluation of methods for modelling distribution of Patagonian insects

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