Get access

Spatial variation in maximum dive depth in gray seals in relation to foraging

Authors

  • Theoni Photopoulou,

    Corresponding author
    1. Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, Scotland KY16 8LB, United Kingdom
    2. Centre for Research into Ecological and Environmental Modelling, The Observatory, University of St Andrews, Scotland KY16 9LZ, United Kingdom
    Current affiliation:
    1. Department of Statistical Sciences, University of Cape Town, Rondebosch 7701, Cape Town, South Africa
    2. Animal Demography Unit, University of Cape Town, Rondebosch 7701, South Africa
    Search for more papers by this author
  • Michael A. Fedak,

    1. Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, Scotland KY16 8LB, United Kingdom
    Search for more papers by this author
  • Len Thomas,

    1. Centre for Research into Ecological and Environmental Modelling, The Observatory, University of St Andrews, Scotland KY16 9LZ, United Kingdom
    Search for more papers by this author
  • Jason Matthiopoulos

    1. Institute of Biodiversity, Animal Health and Comparative Medicine, Graham Kerr Building, University of Glasgow, Glasgow, Scotland G12 8QQ, United Kingdom
    Search for more papers by this author

Abstract

Habitat preference maps are a way of representing animals' space use in two dimensions. For marine animals, the third dimension is an important aspect of spatial ecology. We used dive data from seven gray seals Halichoerus grypus (a primarily benthic forager) collected with GPS phone tags (Sea Mammal Research Unit) to investigate the distribution of the maximum depth visited in each dive. We modeled maximum dive depth as a function of spatiotemporal covariates using a generalized additive mixed model (GAMM) with individual as a random effect. Bathymetry, horizontal displacement, latitude and longitude, Julian day, sediment type, and light conditions accounted for 37% of the variability in the data. Persistent patterns of autocorrelation in the raw data suggest that individual intrinsic rhythm might be an important factor, not captured by external covariates. The strength of using this statistical method to generate spatial predictions of the distribution of maximum dive depth is its applicability to other plunge and pursuit divers. Despite being predictions of a point estimate, these maps provide some insight into the third dimension of habitat use in marine animals. The capacity to predict this aspect of vertical habitat use may help avoid conflict between animal habitat and coastal or offshore developments.

Ancillary