Attributing seabirds at sea to appropriate breeding colonies and populations (CR/2015/18) : Scottish Marine and Freshwater Science Vol 8 No 22

• The aim of this research project was to utilise existing information to produce a new tool to apportion birds observed in transect surveys (i.e. ship-based and aerial surveys) to individual colonies. To do so, we used GPS tracking data available for a sample of colonies and colony size data for th...

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Bibliographic Details
Main Author: Marine Scotland
Format: Article in Journal/Newspaper
Language:English
Published: Marine Scotland Science 2020
Subjects:
Online Access:https://dx.doi.org/10.7489/2006-1
https://data.marine.gov.scot/dataset/attributing-seabirds-sea-appropriate-breeding-colonies-and-populations-cr201518
Description
Summary:• The aim of this research project was to utilise existing information to produce a new tool to apportion birds observed in transect surveys (i.e. ship-based and aerial surveys) to individual colonies. To do so, we used GPS tracking data available for a sample of colonies and colony size data for three species (black-legged kittiwake, common guillemot and razorbill). We used predicted spatial distributions from a recently published paper (Wakefield et al. 2017) estimated from GPS tracking data from breeding birds of these species as a basis for apportioning birds to colonies. We developed a simple tool, implemented within the free R statistical programming environment, to calculate apportioning percentages for a user-defined location using each of these four methods. : We implemented four different statistical methods for apportioning birds to breeding colonies. The four methods include the existing approach that is currently used in practice (the “SNH tool”) and three novel approaches based upon statistical modelling of GPS data. The first of these novel approaches (“WAKE”) derived the apportioning percentages associated with a statistical model (Wakefield et al., 2017) which describes the utilisation distribution of birds from a particular colony in terms of variables relating to accessibility, competition and environmental effects, and which can be used to predict the utilisation distribution of birds originating from each breeding colony in the British Isles. Wakefield et al. (2017) used colony size data derived from the Seabird 2000 census. The second novel approach (“UCC”) is similar to the first, but revised the calculations to use more recent colony size data, where available (and to impute more recent colony sizes in situations where data were not available). Wakefield et al. (2017) only considered breeding birds. The third novel approach (“BNB”) extends this, by using spatial survey data (both at-sea and aerial) to estimate the distribution of non-breeding as well as breeding birds, and thereby to calculate the apportioning percentages associated with all birds (whether breeding or non-breeding). The BNB model for kittiwake and razorbill estimated the distribution of breeding and non-breeding birds to be identical. This may either suggest that the distributions are genuinely similar, or that the data are insufficiently informative to be able to detect differences between the distributions. Therefore, the WAKE and BNB approaches only provide different results for guillemot.