Files and links (1)
Published VersionCC BY-NC-ND V4.0, Open Access
Journal article
Developing a regional species distribution model and validating with independent survey data: a case study of an avian apex predator, the greater sooty owl (Tyto tenebricosa)
Wildlife Research, Vol.52(9), pp.1-13
2025
Abstract
Context Comprehensive understanding of the distribution and habitat requirements of wildlife species is crucial for the development of effective conservation strategies. For cryptic predators, such as owls, obtaining accurate population metrics can be challenging. The rise of citizen science has created large amounts of data, which are increasingly being used for conservation purposes.Aims To create, and externally validate, a species distribution model (SDM) for the greater sooty owl (Tyto tenebricosa) throughout south-east Queensland (SEQ), Australia.Methods A Maxent model was developed by combining citizen science records and environmental variables relevant to greater sooty owl ecology. The resulting model was then validated by incorporating Maxent-derived habitat suitability values as a variable in occupancy modelling performed on an independent dataset collected in the field across agricultural, suburban and remnant forest landscapes.Key results The Maxent model showed good discriminatory ability (the area under the receiver operating curve (AUC) = 0.95), with vegetation type (36.4%), elevation (26.8%) and annual precipitation (18.4%) contributing most to the model. Estimated detection probability and occupancy (psi) from field surveys were 0.19 and 0.31, respectively. Maxent-derived habitat suitability values had a significant positive relationship with occupancy and performed best in predicting greater sooty owl occupancy compared with other covariates.Conclusions The species distribution model showed good discriminatory ability and was validated externally highlighting the potential value of citizen science data. The model suggests that rainforest and wet eucalypt open forest vegetation types, high rainfall and elevation provide optimal greater sooty owl habitat in SEQ.Implications Our study represents a baseline that can be used to identify current greater sooty owl habitat, monitor habitat into the future and guide conservation actions and further research. We recommend further surveys into areas of identified high potential habitat and advocate for increased protection of important owl resources such as roosting and nesting sites.
Details
- Title
- Developing a regional species distribution model and validating with independent survey data: a case study of an avian apex predator, the greater sooty owl (Tyto tenebricosa)
- Authors
- Dylan M. Westaway (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science and Engineering - LegacyYoko Shimizu (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringChris J. Jolly - Macquarie UniversityScott E. Burnett (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Wildlife Research, Vol.52(9), pp.1-13
- Publisher
- CSIRO Publishing
- Date published
- 2025
- DOI
- 10.1071/WR25062
- ISSN
- 1448-5494; 1035-3712
- Copyright note
- © 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
- Data Availability
- Data will be made available on request.
- Grant note
- Funding was provided by the University of the Sunshine Coast, the Friends of Mary Cairncross and the Environmental Legacy Foundation.
- Organisation Unit
- School of Science and Engineering - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991173845602621
- Output Type
- Journal article
Metrics
2 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Ecology
- Zoology