Abstract

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 527:233-246 (2015) - DOI: https://doi.org/10.3354/meps11262 Time-in-area represents foraging activity in a wide-ranging pelagic forager V. Warwick-Evans1,*, P. W. Atkinson2‎, R. D. Gauvain3, L. A. Robinson1, J. P. Y. Arnould4, J. A. Green1 1School of Environmental Sciences, University of Liverpool, Liverpool L69 3GP, UK 2British Trust for Ornithology, The Nunnery, Thetford IP24 2PU, UK 3Alderney Wildlife Trust, St Annes, Alderney GY9 3TA, Channel Islands 4School of Life and Environmental Sciences, Deakin University, Melbourne 3215, Australia *Corresponding author: v.warwick-evans@liverpool.ac.uk ABSTRACT: Successful Marine Spatial Planning depends upon the identification of areas with high importance for particular species, ecosystems or processes. For seabirds, advancements in biologging devices have enabled us to identify these areas through the detailed study of at-sea behaviour. However, in many cases, only positional data are available and the presence of local biological productivity and hence seabird foraging behaviour is inferred from these data alone, under the untested assumption that foraging activity is more likely to occur in areas where seabirds spend more time. We fitted GPS devices and accelerometers to northern gannets Morus bassanus and categorised the behaviour of individuals outside the breeding colony as plunge diving, surface foraging, floating and flying. We then used the locations of foraging events to test the efficiency of 2 approaches: time-in-area and kernel density (KD) analyses, which are widely employed to detect highly-used areas and interpret foraging behaviour from positional data. For KD analyses, the smoothing parameter (h) was calculated using the ad hoc method (KDad hoc), and KDh=9.1, where h = 9.1 km, to designate core foraging areas from location data. A high proportion of foraging events occurred in core foraging areas designated using KDad hoc, KDh=9.1, and time-in-area. Our findings demonstrate that foraging activity occurs in areas where seabirds spend more time, and that both KD analysis and the time-in-area approach are equally efficient methods for this type of analysis. However, the time-in-area approach is advantageous in its simplicity, and in its ability to provide the shapes commonly used in planning. Therefore, the time-in-area approach can be used as a simple way of using seabirds to identify ecologically important locations from both tracking and survey data. KEY WORDS: Northern gannet · Biologging · Marine Spatial Planning · Accelerometer · GPS tracking · Morus bassanus Full text in pdf format Supplementary material PreviousNextCite this article as: Warwick-Evans V, Atkinson‎ PW, Gauvain RD, Robinson LA, Arnould JPY, Green JA (2015) Time-in-area represents foraging activity in a wide-ranging pelagic forager. Mar Ecol Prog Ser 527:233-246. https://doi.org/10.3354/meps11262 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 527. Online publication date: May 07, 2015 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2015 Inter-Research.

Highlights

  • IntroductionOur understanding of seabird behaviour and spatial ecology has improved recently, due to the advancement of biologging technologies, which has resulted in loggers becoming smaller and more affordable (Burger & Shaffer 2008)

  • Marine Spatial Planning (MSP) is a key tool to address trade-offs between the economic, ecological and social objectives of marine management (Ehler & Douvere 2009)

  • We found little evidence to suggest that the removal of night-time data results in a higher proportion of all foraging events occurring in the core foraging areas designated using either of the methods (Table 2)

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Summary

Introduction

Our understanding of seabird behaviour and spatial ecology has improved recently, due to the advancement of biologging technologies, which has resulted in loggers becoming smaller and more affordable (Burger & Shaffer 2008) Devices such as time depth recorders (Tremblay et al 2003) and accelerometers (Ropert Coudert et al 2003) can be used to measure the behaviour of seabirds. Combining these tools with tracking devices, such as GPS loggers, would be the ideal method to identify foraging areas (Burger & Shaffer 2008). The usual assumption is that highly-used areas reflect regions of important ecological processes, where individuals congregate to forage (Le Corre et al 2012), though it should be noted that seabirds flock together for other reasons such as information exchange (Burger 1997)

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