Habitat use models of spatially auto-correlated data: a case study of the common bottlenose dolphin, Tursiops truncatus truncatus, in southeastern Brazil

ABSTRACT

A common approach to studying habitat use in cetaceans is to conduct line-transect surveys, to investigate their distribution. In developing countries, there are limited resources for data collection. One solution is to employ field surveys to collect a wide range of ecological and behavioural data, for which a haphazard sampling schedule is adopted, to optimize the cost–benefit ratio. As with line-transect surveys, the haphazard sampling may lead to spatial autocorrelation (SAC), an overlooked problem in ecology. Here, we investigated common bottlenose dolphins (Tursiops truncatus truncatus) habitat use on an upwelling area and tested an approach that can improve model-based inference on auto-correlated data. We collected data in Cabo Frio, Rio de Janeiro, photo-identified 429 individuals and compared the predictions and model coefficients of standard generalized linear model (GLM) without correcting for spatial autocorrelation with a spatial eigenvector generalized linear model (SEV-GLM) which compensates for SAC. Our best SEV-GLM predicted dolphins are more likely to occur on cold waters with increased chlorophyll concentration, indicating dolphins are influenced by the upwelling. Moreover, by correcting for SAC, our models had a better fit to data, magnified the relevance of significant variables and showed smaller and less clumped residuals than when not correcting.

SUBJECT EDITOR:

• Rus Hoelzel

KEYWORDS:

• Species distribution model
• spatial filtering
• spatial autocorrelation
• odontocetes
• Cabo Frio
• habitat model

Acknowledgements

We thank Israel Sá Maciel, Luciana D. Figueiredo, Liliane Lodi, Carine Gonçalves and Marco Aurelio B. Crespo for valuable field support. We also thank the contribution of the reviewers that greatly improved the paper. Stephen Ferrari reviewed the English.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Rodrigo H. Tardin http://orcid.org/0000-0002-0807-6937

Yongwan Chun http://orcid.org/0000-0002-4957-1379

Maria Alice S. Alves https://orcid.org/0000-0002-0622-270X

Additional information

Funding

The authors gratefully acknowledge research grants from Conselho Nacional de Desenvolvimento Científico e Tecnológico — CNPq (Grant # 479348/2010-3) and the Fundação Boticário de Proteção a Natureza (Grant #0997_20132), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) for scholarship and fellowship to R.H. Tardin, respectively (Processes # E-26/100.866/2011 and E-26/ 202.803/ 2016) and Conselho Nacional de Desenvolvimento Cientifico e Tecnologico for Productivity Grant to M.A.S. Alves (Process # 308792/2009-2 and 305798/2014-6).