Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling

Statistical modelling of animal distributions has been widely applied to explain how mobile species use their habitats. The distribution of and habitat use by humpback whales Megaptera novaeangliae off the eastern coast of Brazil have previously been investigated by modelling visual survey data. Her...

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Published in:Marine Ecology Progress Series
Main Authors: Bortolotto, Guilherme A., Zerbini, Alexandre, Thomas, Len, Andriolo, Artur, Hammond, Philip Steven
Format: Article in Journal/Newspaper
Language:English
Published: 2023
Subjects:
Online Access:https://research-portal.st-andrews.ac.uk/en/publications/3cfdbd1c-39ef-4416-adcd-8e739d3aced2
https://doi.org/10.3354/meps14404
https://research-repository.st-andrews.ac.uk/bitstream/10023/28569/1/Bortolotto_2023_MEPS_DistributionHabitat_AAM.pdf
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author Bortolotto, Guilherme A.
Zerbini, Alexandre
Thomas, Len
Andriolo, Artur
Hammond, Philip Steven
author_facet Bortolotto, Guilherme A.
Zerbini, Alexandre
Thomas, Len
Andriolo, Artur
Hammond, Philip Steven
author_sort Bortolotto, Guilherme A.
collection University of St Andrews: Research Portal
container_start_page 161
container_title Marine Ecology Progress Series
container_volume 720
description Statistical modelling of animal distributions has been widely applied to explain how mobile species use their habitats. The distribution of and habitat use by humpback whales Megaptera novaeangliae off the eastern coast of Brazil have previously been investigated by modelling visual survey data. Here, we modelled distribution in their breeding range using individual tracking data to compare ecological inferences with those from previous models from line transect data. A generalised estimating equation framework was used to model the tracking data and pseudo-absences as functions of spatial covariates. Covariates considered were latitude and longitude, sea surface temperature (SST), current and wind speeds near the surface, distances to shelf-break and the coast, sea bottom depth and slope, and a factor variable representing ‘shelter’. Two modelling exercises were developed: a habitat use model (HUM) and a distribution model (DIM). Covariates retained in the selected HUM were SST, distance to coast and shelf-break, current and wind speeds and shelter. Covariates retained in the selected DIM were latitude/longitude, current speed and distances to shelf-break and coast. The modelled relationships between whale occurrence and environmental covariates using tracking data were similar to those using line transect data. Distribution maps were also similar, supporting higher densities around the Abrolhos Archipelago and to its south. We showed that habitat use and distribution of this population in the area could be similarly inferred by modelling either line transect or tracking data. Using these 2 approaches in conjunction can strengthen the understanding of important ecological aspects of animal populations.
format Article in Journal/Newspaper
genre Megaptera novaeangliae
genre_facet Megaptera novaeangliae
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language English
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op_container_end_page 174
op_doi https://doi.org/10.3354/meps14404
op_rights info:eu-repo/semantics/openAccess
op_source Bortolotto , G A , Zerbini , A , Thomas , L , Andriolo , A & Hammond , P S 2023 , ' Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling ' , Marine Ecology Progress Series , vol. 720 , pp. 161-174 . https://doi.org/10.3354/meps14404
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spelling ftunstandrewcris:oai:research-portal.st-andrews.ac.uk:publications/3cfdbd1c-39ef-4416-adcd-8e739d3aced2 2025-02-16T15:06:21+00:00 Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling Bortolotto, Guilherme A. Zerbini, Alexandre Thomas, Len Andriolo, Artur Hammond, Philip Steven 2023-10-05 application/pdf https://research-portal.st-andrews.ac.uk/en/publications/3cfdbd1c-39ef-4416-adcd-8e739d3aced2 https://doi.org/10.3354/meps14404 https://research-repository.st-andrews.ac.uk/bitstream/10023/28569/1/Bortolotto_2023_MEPS_DistributionHabitat_AAM.pdf eng eng info:eu-repo/semantics/openAccess Bortolotto , G A , Zerbini , A , Thomas , L , Andriolo , A & Hammond , P S 2023 , ' Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling ' , Marine Ecology Progress Series , vol. 720 , pp. 161-174 . https://doi.org/10.3354/meps14404 Megaptera novaeangliae Ecology Conservation Marine mammals Population recovery article 2023 ftunstandrewcris https://doi.org/10.3354/meps14404 2025-01-24T05:31:15Z Statistical modelling of animal distributions has been widely applied to explain how mobile species use their habitats. The distribution of and habitat use by humpback whales Megaptera novaeangliae off the eastern coast of Brazil have previously been investigated by modelling visual survey data. Here, we modelled distribution in their breeding range using individual tracking data to compare ecological inferences with those from previous models from line transect data. A generalised estimating equation framework was used to model the tracking data and pseudo-absences as functions of spatial covariates. Covariates considered were latitude and longitude, sea surface temperature (SST), current and wind speeds near the surface, distances to shelf-break and the coast, sea bottom depth and slope, and a factor variable representing ‘shelter’. Two modelling exercises were developed: a habitat use model (HUM) and a distribution model (DIM). Covariates retained in the selected HUM were SST, distance to coast and shelf-break, current and wind speeds and shelter. Covariates retained in the selected DIM were latitude/longitude, current speed and distances to shelf-break and coast. The modelled relationships between whale occurrence and environmental covariates using tracking data were similar to those using line transect data. Distribution maps were also similar, supporting higher densities around the Abrolhos Archipelago and to its south. We showed that habitat use and distribution of this population in the area could be similarly inferred by modelling either line transect or tracking data. Using these 2 approaches in conjunction can strengthen the understanding of important ecological aspects of animal populations. Article in Journal/Newspaper Megaptera novaeangliae University of St Andrews: Research Portal Marine Ecology Progress Series 720 161 174
spellingShingle Megaptera novaeangliae
Ecology
Conservation
Marine mammals
Population recovery
Bortolotto, Guilherme A.
Zerbini, Alexandre
Thomas, Len
Andriolo, Artur
Hammond, Philip Steven
Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling
title Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling
title_full Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling
title_fullStr Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling
title_full_unstemmed Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling
title_short Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling
title_sort distribution and habitat use modelling from satellite tracking data of humpback whales in brazil agree with shipboard survey data modelling
topic Megaptera novaeangliae
Ecology
Conservation
Marine mammals
Population recovery
topic_facet Megaptera novaeangliae
Ecology
Conservation
Marine mammals
Population recovery
url https://research-portal.st-andrews.ac.uk/en/publications/3cfdbd1c-39ef-4416-adcd-8e739d3aced2
https://doi.org/10.3354/meps14404
https://research-repository.st-andrews.ac.uk/bitstream/10023/28569/1/Bortolotto_2023_MEPS_DistributionHabitat_AAM.pdf