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

Funding: The Monitoring Whales by Satellite Project (Projeto Monitoramento de Baleias por Satélite, PMBS) research cruises were sponsored by Shell Brasil. The Federal University of Rio Grande (FURG) and the R/V Atlântico Sul crew provided essential support during fieldwork. G.A.B.’s PhD work is fund...

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Bibliographic Details
Published in:Marine Ecology Progress Series
Main Authors: Bortolotto, Guilherme A., Zerbini, Alexandre, Thomas, Len, Andriolo, Artur, Hammond, Philip Steven
Other Authors: University of St Andrews.School of Biology, University of St Andrews.Statistics, University of St Andrews.Marine Alliance for Science & Technology Scotland, University of St Andrews.Centre for Research into Ecological & Environmental Modelling, University of St Andrews.Sea Mammal Research Unit, University of St Andrews.Scottish Oceans Institute
Format: Article in Journal/Newspaper
Language:English
Published: 2023
Subjects:
Megaptera novaeangliae
Ecology
Conservation
Marine mammals
Population recovery
GC Oceanography
QH301 Biology
NDAS
MCC
GC
QH301
Online Access:https://hdl.handle.net/10023/28569
https://doi.org/10.3354/meps14404
Description
Summary:Funding: The Monitoring Whales by Satellite Project (Projeto Monitoramento de Baleias por Satélite, PMBS) research cruises were sponsored by Shell Brasil. The Federal University of Rio Grande (FURG) and the R/V Atlântico Sul crew provided essential support during fieldwork. G.A.B.’s PhD work is funded by the Brazilian National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Science Without Borders, scholarship number 208203/2014-1). 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 ...

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