Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/30030
Title: Assessing Accuracy Methods of Species Distribution Models: AUC, Specificity, Sensitivity and the True Skill Statistic
Contributor(s): Kumar, Lalit  (author)orcid ; Shabani, Farzin  (author); Ahmadi, Mohsen (author)
Publication Date: 2018
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/30030
Open Access Link: https://globaljournals.org/GJHSS_Volume18/E-Journal_GJHSS_(B)_Vol_18_Issue_1.pdfOpen Access Link
Abstract: We aimed to assess different methods for evaluating performance accuracy in species distribution models based on the application of five types of bioclimatic models under three threshold selections to predict the distributions of eight different species in Australia, treated as an independent area. Five discriminatory correlative species distribution models (SDMs), were used to predict the species distributions of eight different plants. A global training data set, excluding the Australian locations, was used for model fitting. Four accuracy measurement methods were compared under three threshold selections of i) maximum sensitivity + specificity, ii) sensitivity = specificity and iii) predicted probability of 0.5 (default). Results showed that the choice of modeling methods had an impact on potential distribution predictions for an independent area. Examination of the four accuracy methods underexamined threshold selections demonstrated that TSS is a more realistic and practical method, in comparison with AUC, Sensitivity and Specificity. Accurate projection of the distribution of a species is extremely complex.
Publication Type: Journal Article
Source of Publication: Global Journal of Human-Social Science, 18(1), p. 7-18
Publisher: Global Journals Inc
Place of Publication: United States of America
ISSN: 2249-460X
0975-587X
Fields of Research (FoR) 2008: 050101 Ecological Impacts of Climate Change
Fields of Research (FoR) 2020: 410102 Ecological impacts of climate change and ecological adaptation
Socio-Economic Objective (SEO) 2008: 960501 Ecosystem Assessment and Management at Regional or Larger Scales
Socio-Economic Objective (SEO) 2020: 180403 Assessment and management of Antarctic and Southern Ocean ecosystems
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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