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ISPRS Int. J. Geo-Inf. 2017, 6(6), 176; doi:10.3390/ijgi6060176

Development and Comparison of Species Distribution Models for Forest Inventories

Department of Statistics and Operational Research, Faculty of Mathematics, University of Valencia, 46100 Burjassot (València), Spain
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Academic Editors: Duccio Rocchini and Wolfgang Kainz
Received: 19 January 2017 / Revised: 25 May 2017 / Accepted: 14 June 2017 / Published: 16 June 2017
(This article belongs to the Special Issue Spatial Ecology)
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Abstract

A comparison of several statistical techniques common in species distribution modeling was developed during this study to evaluate and obtain the statistical model most accurate to predict the distribution of different forest tree species (in our case presence/absence data) according environmental variables. During the process we have developed maximum entropy (MaxEnt), classification and regression trees (CART), multivariate adaptive regression splines (MARS), showing the statistical basis of each model and, at the same time, we have developed a specific additive model to compare and validate their capability. To compare different results, the area under the receiver operating characteristic (ROC) function (AUC) was used. Every AUC value obtained with those models is significant and all of the models could be useful to represent the distribution of each species. Moreover, the additive model with thin plate splines gave the best results. The worst capability was obtained with MARS. This model’s performance was below average for several species. The additive model developed obtained better results because it allowed for changes and calibrations. In this case we were aware of all of the processes that occurred during the modeling. By contrast, models obtained using specific software, in general, perform like “hermetic machines”, because it could sometimes be impossible to understand the stages that led to the final results. View Full-Text
Keywords: additive model; area under the curve; AUC; forest inventory; receiver operating characteristic; ROC; species distribution model additive model; area under the curve; AUC; forest inventory; receiver operating characteristic; ROC; species distribution model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rivera, Ó.R.; López-Quílez, A. Development and Comparison of Species Distribution Models for Forest Inventories. ISPRS Int. J. Geo-Inf. 2017, 6, 176.

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