Knowledge of seabird distributions plays a key role in seabird conservation and sustainable marine management, underpinning efforts to designate protected areas or assess the impact of human developments. Technological advances in animal tracking devices increasingly allow researchers to acquire information on the movement of birds from specific colonies. Nevertheless, most seabird colonies have not been subject to such tracking and another means must be found to assess their likely foraging distribution. Consequently, foraging range data collated and summarized across other tracking studies has often been used to estimate species‐level foraging distances for use within applied settings. However, generic species‐specific foraging ranges must be used with caution because of the amount of variation in seabird foraging behaviour at both the individual and colony levels. Specifically, although current reviews of seabird foraging ranges provide summary estimates of maximum foraging range, they typically do not assess the extent of among‐colony or among‐individual variation around such estimates. To address this, we conducted a variance component analysis of the maximum distance reached from the breeding colony per foraging trip (foraging range) using multi‐colony tracking datasets to estimate the degree of between‐individual, between‐year and between‐colony variation in foraging range in four UK breeding seabirds (Black‐legged Kittiwake Rissa tridactyla , Common Guillemot Uria aalge , Razorbill Alca torda and European Shag Gulosus aristotelis ). We also provide updated estimates of typical foraging ranges for each species and quantify the influence of breeding stage and colony size. Overall, between‐colony variation was typically the largest variance component, explaining 20–30% of the observed variation in foraging range across the four species. Individual‐level variation was also relatively large among Shag. In Kittiwake, Guillemot and Shag, but not Razorbill, average foraging ranges were positively associated with colony size. In addition, Kittiwake and Razorbill travelled further during incubation than during chick‐rearing. More generally, our estimates of mean foraging ranges for each species were subject to a high degree of uncertainty, which should be incorporated into impact assessments carried out using such data.

Tracking tags have been used to map the distributions of a wide variety of avian species, but few studies have examined whether the use of these devices has impacts on the study animals that may bias the spatial data obtained. As Global Positioning System (GPS) tags small enough for deployment on terns (family: Laridae) have only recently become available, until now tracking of this group has been conducted by following unmanipulated individuals by boat, which offers a means of comparing distributions obtained from GPS‐tracking. We compared the utilization distributions (UDs) of breeding Arctic Terns Sterna paradisaea obtained by GPS‐tracking 10 individuals over 2 weeks, with UDs derived from contemporaneous visual boat tracks from 81 individuals. The 50% and 95% UDs of both methods had high similarity scores, indicating good agreement in the density distributions derived from the two methods. The footprints of the UDs of tagged birds were ~ 75–80% larger, which may reflect an effect of tagging on foraging range or the occasional inability to follow by boat individuals which roamed further from the colony. We also compared the nest attendance and chick provisioning rates of adults that were (1) fitted with a GPS tag and leg‐flag, (2) handled and marked with a leg‐flag but not tagged and (3) fitted with a leg‐flag in a previous year but unhandled in the year of the study. There was some evidence that birds fitted with both a GPS tag and leg‐flag spent slightly less time at the nest compared with unhandled birds and those fitted with a leg‐flag only. Both treatments where birds were fitted with a leg‐flag in the year of the study had similarly lower provisioning rates to those of unhandled control birds > 48 h after handling, suggesting that negative effects on provisioning are due to capture and handling or leg‐flag attachment rather than to GPS tag attachment/loading per se . Overall brood‐provisioning rate was compensated for by the increased effort by the unhandled partner. Our study suggests that despite slight effects of GPS‐tagging on behaviour, the estimates of marine density distribution obtained were very similar to those of unmanipulated birds.

Lesser Spotted Woodpecker Dendrocopos minor numbers have declined greatly in England since the early 1980s for reasons that are not yet fully understood. It has been suggested that the species' decline may be linked to the increase in Great Spotted Woodpeckers Dendrocopos major, changes in woodland habitat quality (such as deadwood abundance) and landscape-scale changes in tree abundance. We tested some of these hypotheses by comparing the characteristics of woods in southern England where the species is still relatively numerous with those of woods used in the 1980s before the major decline. In each time period, habitat, predator and landscape information from woods known to be occupied by Lesser Spotted Woodpeckers was compared with those found to be unoccupied during surveys. Before the main period of decline, Lesser Spotted Woodpeckers used oak-dominated, mature, open woods with a large amount of standing deadwood. Habitat use assessed from recent data was very similar, the species being present in mature, open, oak-dominated woodlands. There was a strong relationship between wood use probability and the extent of woodland within a 3-km radius, suggesting selection for more heavily wooded landscapes. In recent surveys, there was no difference in deadwood abundance or potential predator densities between occupied and unoccupied woods. Habitat management should focus on creating and maintaining networks of connected woodlands in areas of mature, open woods. Finer-scale habitat selection by Lesser Spotted Woodpecker within woodlands should be assessed to aid development of beneficial management actions.