Assessing Accuracy Methods of Species Distribution Models: AUC, Specificity, Sensitivity and the True Skill Statistic

Title
Assessing Accuracy Methods of Species Distribution Models: AUC, Specificity, Sensitivity and the True Skill Statistic
Publication Date
2018
Author(s)
Kumar, Lalit
( author )
OrcID: https://orcid.org/0000-0002-9205-756X
Email: lkumar@une.edu.au
UNE Id une-id:lkumar
Shabani, Farzin
Ahmadi, Mohsen
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Global Journals Inc
Place of publication
United States of America
UNE publication id
une:1959.11/30030
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.
Link
Citation
Global Journal of Human-Social Science, 18(1), p. 7-18
ISSN
2249-460X
0975-587X
Start page
7
End page
18
Rights
Attribution-NonCommercial 4.0 International

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