Document Type

Article

Publication Date

November 2015

Publication Title

Frontiers in Marine Science

Volume

2

DOI

10.3389/fmars.2015.00093

Keywords

biologging, telemetry, seabirds, kernel density, home range, distribution, albatross, movement ecology

Disciplines

Biology | Marine Biology

Abstract

Marine ecologists and managers need to know the spatial extent of at-sea areas most frequented by the groups of wildlife they study or manage. Defining group-specific ranges and distributions (i.e., space use at the level of species, population, age-class, etc.) can help to identify the source or severity of common or distinct threats among different at-risk groups. In biologging studies, this is accomplished by estimating the space use of a group based on a sample of tracked individuals. A major assumption of these studies is consistency in individual movements among members of a group. The implications of scaling up individual-level tracking data to infer higher-level spatial patterns for groups (i.e., size and extent of areas used, overlap or segregation among groups) is not well documented for wide-ranging pelagic species with high potential for individual variation in space use. We present a case study exploring the effects of sampling (i.e., number and identity of individuals contributing to an analysis) on defining group-specific space use with year-round multi-colony tracking data from two highly vagile species, Laysan (Phoebastria immutabilis) and black-footed (P. nigripes) albatrosses. The results clearly demonstrate that caution is warranted when defining space use for a specific species-colony-period group based on datasets of small, intermediate, or relatively large sample sizes (ranging from n = 3–42 tracked individuals) due to a high degree of individual-level variation in movements. Overall, we provide further support to the recommendation that biologging studies aiming to define higher-level patterns in space use exercise restraint in the scope of inference, particularly when pooled Kernel Density Estimation (KDE) techniques are applied to small datasets for wide-ranging species. Transparent reporting in respect to the potential limitations of the data can in turn better inform both biological interpretations and science-based management decisions.

Comments

Copyright © 2015 Gutowsky, Leonard, Conners, Shaffer and Jonsen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. This article was originally published in Frontiers in Marine Science Vol. 2, article 93, by Frontiers Media on November 12, 2015, DOI: 10.3389/fmars.2015.00093. The article is also available online at this link.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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