Melinda Firds Program Management Unit Assistant
World Agroforestry (ICRAF)
Jl. CIFOR, Situ Gede, Sindang Barang,
Bogor Barat - Indonesia 16115
Tel: +62 2511 8625415
Fax: +62 2511 8625416
Email: icrafseapub@cgiar.org
Applying BioMod for Model-Ensemble in Species Distributions: a Case Study for Tsuga chinensis in China
Author
Bi Ying Feng, Xu Jianchu, Qiaohong Li, Antoine Guisan, Wilfried Thuiller, Niklaus E. Zimmermann, Yongping Yang and Xue-Fei Yang
Year
2013
Journal Title
Plant Diversity and Resources
Volume
35
Issue
5
Pages
647-655
Call Number
JA0558-14
Keywords
Species distribution model, Tsuga chinensis, Model assembly, Biogeography, BioMod
Abstract:
The integration of new statistical techniques and increasing availability of multi-sources and multi-scale
data sets promote the development of species distribution modeling. Yet, choice of data sets, different model types
and their underlying ecological theories and assumptions can cause uncertainty in model predictions. In order to decrease prediction uncertainty, studies using model ensemble are gaining in popularity. In this paper we apply the BioMod package developed under R environment to predict the spatial distribution of Tsuga chinensis using nine different models. Our aims were to evaluate model performance, select explanatory variables, and assemble the best predictive output. Random Forest, MARS and GAM performed the best amongst the nine models compared, while SRE
was the worst. The ensemble models predicted that the areas of high probability for T. chinensis presence lie mainly in
Southwest China and the periphery of the Sichuan basin, and are also distributed sporadically in South China and Taiwan. These predictions reflect the actual distribution pattern of T. chinensis, and show high agreement with other analyses. The application of BioMod for model ensemble lowers uncertainty and improves the prediction performance.
Download file(s):Click icon to download/open file.
