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Volume 50, No. 2

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Nesting distribution of Masked Booby Sula dactylatra at Trindade Island, western South Atlantic Ocean


Authors

VICTÓRIA R.F. BENEMANN1*, LEONARDO D. ARAÚJO1,2, ARTHUR Z. FABBRIS1, ROSALINDA C. MONTONE3 & MARIA V. PETRY1
1Laboratory of Ornithology and Marine Animals, Vale do Rio dos Sinos University, São Leopoldo, Rio Grande do Sul, Brazil *(victoriabenemann@gmail.com)
2VizLab/X-Reality and Geoinformatics Lab, Vale do Rio dos Sinos University, São Leopoldo, Rio Grande do Sul, Brazil
3Laboratory of Organic and Marine Chemistry, Oceanographic Institute, University of São Paulo, São Paulo, Brazil

Citation

BENEMANN, V.R.F., ARAÚJO, L.D., FABBRIS, A.Z., MONTONE, R.C. & PETRY, M.V. 2022. Nesting distribution of Masked Booby Sula dactylatra at Trindade Island, western South Atlantic Ocean. Marine Ornithology 50: 189 - 195
http://doi.org/10.5038/2074-1235.50.2.1488

Received 15 March 2022, accepted 03 June 2022

Date Published: 2022/10/15
Date Online: 2022/09/22
Key words: sulidae, seabirds, spatial ecology, species distribution modelling

Abstract

The Masked Booby Sula dactylatra is a surface-nesting seabird that breeds on offshore islands across the tropical and subtropical oceans. On inaccessible rocky areas on Trindade Island, located about 1 200 km from Espírito Santo, Brazil, the nesting of this species has been poorly studied. To model the species' nesting habitat suitability at Trindade Island, we mapped active nests during the breeding seasons of 2017 and 2019, from October to November, using a hand-held Global Positioning System (GPS) receiver and an Unmanned Aerial Vehicle (UAV). In order to identify key areas, we created nesting habitat suitability maps using seven different algorithms (Random Forest, Gradient Boosting Machine, Artificial Neural Network, Maximum Entropy, Generalized Additive Model, Generalized Linear Model, and Multiple Adaptive Regression Splines) in response to five topographical variables and one vegetation-related variable. Our sample included 87 active nests. Models generated by all four best algorithms were considered satisfactory. Results indicate that elevation and terrain aspect are the main variables influencing booby selection of nesting sites. We found areas of very high nesting habitat suitability along the southwest and northwest faces of the island, mostly in elevations varying from 150 m to 450 m.

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