ORIGINAL RESEARCH article
Front. Mar. Sci.
Sec. Marine Conservation and Sustainability
Volume 12 - 2025 | doi: 10.3389/fmars.2025.1599553
Estimating the breeding population size of short-tailed shearwaters using a nesting habitat suitability model
Provisionally accepted
- 1Deakin University, Geelong, Australia
- 2Institute for Marine and Antarctic Studies, College of Sciences and Engineering, University of Tasmania, Hobart, Tasmania, Australia
- 3Université de la Rochelle, La Rochelle, Poitou-Charentes, France
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Population size estimates are important for conservation management. Conducting ground surveys is the most common approach used to providing population estimates but financial and logistical constraints often make this untenable for seabird species breeding on remote islands. The present study used previously collected count data of short-tailed shearwater burrows in conjunction with remote sensed environmental data to develop nesting habitat suitability models using generalised additive models (GAMs). A global Generalised Additive Mixed Model (GAMM) including data from 14 islands around Wilsons Promontory (Bass Strait, Australia) revealed a preference in short-tailed shearwaters for coastal grassland on a south-east terrain aspect with moderate incline to establish their breeding areas. The highest density areas were also away from the shoreline and with lower elevation. This global model, projected on 258 colonies representing the currently known breeding range of the species, predicted 11.26 (11.17-11.35) million burrows which, accounting for incomplete burrow occupancy, provided a total breeding population estimate of 12.84 (11.51-14.17) million individuals. While an increased spatial balance in training dataset could greatly improve the accuracy of global models, the estimate results of the present study are consistent with previous findings. This demonstrates the advantages of combining limited ground surveys data collection with such modelling approaches in comparison to more traditional ground survey extrapolations to produce species population estimates for burrowing seabirds.
Keywords: burrowing seabird colonies, burrow density ground surveys, remote sensed environmental data, generalised additive model prediction, Occupancy rate, Southern Australia
Received: 25 Mar 2025; Accepted: 11 Jun 2025.
Copyright: © 2025 De Almeida E Silva, Monk, Bustamante and Arnould. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Nicolas De Almeida E Silva, Deakin University, Geelong, Australia
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