Foraging range scales with colony size in high latitude seabirds
Density dependent prey depletion around breeding colonies has long been considered an important factor controlling the population dynamics of colonial animals1–4. Ashmole proposed that as seabird colony size increases intraspecific competition leads to declines in reproductive success as breeding adults must spend more time and energy to find prey farther from the colony1. Seabird colony size often varies over several orders of magnitude within the same species and can include millions of individuals per colony5,6. As such, colony size likely plays an important role in determining the individual behaviour of its members and how the colony interacts with the surrounding environment6. Using tracking data from murres (Uria spp.), the world’s most densely breeding seabirds, we show that the distribution of foraging trip distances scales to colony size0.33 during the chick-rearing stage, consistent with Ashmole’s halo theory1,2. This pattern occurred across colonies varying in size over three orders of magnitude and distributed throughout the North Atlantic region. The strong relationship between colony size and foraging range means that foraging areas for some colonial species can be estimated from colony sizes, which is more practical to measure over a large geographic scale. Two-thirds of the North Atlantic murre population breed at the 16 largest colonies; by extrapolating predicted foraging ranges to sites without tracking data, we show that only two of these large colonies have significant coverage by marine protected areas. Our results are an important example of how theoretical models, in this case Ashmole’s version of central place foraging theory, can be applied to inform conservation and management in colonial breeding species. This dataset includes three .txt files of all raw data used in the analyses described in Patterson et al 2022. These files are the raw GPS tracking data (gpsTracks.txt), foraging trip data (tripSummary.txt), and colony size data (clusteredColonies.txt). The dataset also includes an RStudio project (uria-aht.zip) with all R scripts used in the analysis. The scripts can be opened using R, original analysis was done with R version 4.1.3. The project includes '.RDS' versions of all '.txt' data files, which can be read directly into R. Within the project there is a file named 'wei_cs_null.RDS', which contains the main brms model developed in the paper. This file can be used to recreate all analysis that builds on that model or to develop new analysis from the models predictions.