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Journal article
Assessment of fuzzy logic to enhance species distribution modelling of two cryptic wood boring beetle species in Australia
Scientific reports, Vol.14(1), 27871
2024
Abstract
Fuzzy logic presents a promising approach for Species Distribution Modelling by generating a value that can be used for comparative purposes termed ‘environmental favourability’. In contrast to ‘presence probability’, ‘environmental favourability’ remains robust regardless of species prevalence. This characteristic facilitates effective comparisons across species with varying levels of prevalence. In this study, presence probability was predicted using three commonly used Species Distribution Models: Generalised Linear Model, Generalised Additive Modelling, and Boosted Regression Trees for two beetle species, Euwallacea fornicatus and Euwallacea perbrevis in Australia. Fuzzy logic was then employed to derive environmental favourability values based on these models. Additionally, Maxent modelling was included to compare prediction outputs and facilitate a comprehensive analysis. Model performance was evaluated using standard metrics (Area under the receiver operating characteristic curve, True statistical skill, Correct classification rate), as well as Hosmer-Lemeshow test. The research explored fuzzy similarity, fuzzy intersection and potential biotic interaction of these closely related borers, and revealed a favourable distribution pattern for Euwallacea fornicatus across Australia. This study supports the efficacy of fuzzy logic in Species Distribution Modelling and highlights the value of environmental favourability function in enhancing the comparative analysis of the geographical relationship across species. This approach offers a more nuanced perspective on Species Distribution Modelling.
Details
- Title
- Assessment of fuzzy logic to enhance species distribution modelling of two cryptic wood boring beetle species in Australia
- Authors/Creators
- Xingyu Li - Murdoch UniversityRobert N. Emery - Murdoch UniversityGrey T. Coupland - Murdoch UniversityYonglin Ren - Murdoch UniversitySimon J. McKirdy - Murdoch University
- Publication Details
- Scientific reports, Vol.14(1), 27871
- Publisher
- Nature Publishing Group UK
- Identifiers
- 991005716570307891
- Copyright
- © The Author(s) 2024
- Murdoch Affiliation
- Murdoch University; Harry Butler Institute; Centre for Biosecurity and One Health
- Language
- English
- Resource Type
- Journal article
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