Abstract
Mapping the distribution of seabirds at sea is fundamental to understanding their ecology and making informed decisions on their conservation. Until recently, estimates of at-sea distributions were generally derived from boat-based visual surveys. Increasingly however, seabird tracking is seen as an alternative but each has potential biases. To compare distributions from the two methods, we carried out simultaneous boat-based surveys and GPS tracking in the Minch, western Scotland, in June 2015. Over eight days, boat transect surveys covered 950 km, within a study area of approximately 6700 km2 centred on the Shiant Islands, one of the main breeding centres of razorbills and guillemots in the UK. Simultaneously, we GPS-tracked chick-rearing guillemots (n = 17) and razorbills (n = 31) from the Shiants. We modelled counts per unit area from boat surveys as smooth functions of latitude and longitude, mapping estimated densities. We then used kernel density estimation to map the utilisation distributions of the GPS tracked birds. These two distribution estimates corresponded well for razorbills but were lower for guillemots. Both methods revealed areas of high use around the focal colony, but over the wider region, differences emerged that were likely attributable to the influences of neighbouring colonies and the presence of non-breeding birds. The magnitude of differences was linked to the relative sizes of these populations, being larger in guillemots. Whilst boat surveys were necessarily restricted to the hours of daylight, GPS data were obtained equally during day and night. For guillemots, there was little effect of calculating separate night and day distributions from GPS records, but for razorbills the daytime distribution matched boat-based distributions better. When GPS-based distribution estimates were restricted to the exact times when boat surveys were carried out, similarity with boat survey distributions decreased, probably due to reduced sample sizes. Our results support the use of tracking data for defining seabird distributions around tracked birds’ home colonies, but only when nearby colonies are neither large nor numerous. Distributions of animals around isolated colonies can be determined using GPS loggers but that of animals around aggregated colonies is best suited to at-sea surveys or multi-colony tracking.
Highlights
Since the 1990s, new technology has allowed researchers to track the movements of seabirds using bird-borne devices that are sufficiently small and cost-effective to provide statistically robust sample sizes for a range of species (Burger and Shaffer, 2008)
Two guillemot tags and six razorbill tags returned no data so were excluded from further analyses, leaving sample sizes of 18 guillemots and 33 razorbills
The degree of similarity between seabird distributions derived from boat surveys and Global Positioning System (GPS) tracking differed between the two species: it was moderate for guillemots but somewhat stronger for razorbills
Summary
Since the 1990s, new technology has allowed researchers to track the movements of seabirds using bird-borne devices that are sufficiently small and cost-effective to provide statistically robust sample sizes for a range of species (Burger and Shaffer, 2008). In the UK, several seabird species have been tracked, with data collected on hundreds of individuals from tens of colonies (e.g., Harris et al, 2012; Chivers et al, 2013; Robertson et al, 2014; Dean et al, 2015; Soanes et al, 2016). As birds are usually caught on land, tracking data are obtained from birds known to have been attending specific colonies, and can be used to identify important areas for focal colonies (e.g., Chivers et al, 2013; Redfern and Bevan, 2014). Usually only a small number of birds can be tracked from each colony, and constraints on battery life or the opportunities to re-catch birds, mean that tags are often only deployed for days or weeks. Tracking indicates presence in an area, but not absence, potentially limiting interpretation of distribution estimates derived using this method
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