Abstract

Relatively simple foraging radius models have the potential to generate predictive distributions for a large number of species rapidly, thus providing a cost‐effective alternative to large‐scale surveys or complex modelling approaches. Their effectiveness, however, remains largely untested. Here we compare foraging radius distribution models for all breeding seabirds in Ireland, to distributions of empirical data collected from tracking studies and aerial surveys. At the local/colony level, we compared foraging radius distributions to GPS tracking data from seabirds with short (Atlantic puffin Fratercula arctica, and razorbill Alca torda) and long (Manx shearwater Puffinus puffinus, and European storm‐petrel Hydrobates pelagicus) foraging ranges. At the regional/national level, we compared foraging radius distributions to extensive aerial surveys conducted over a two‐year period. Foraging radius distributions were significantly positively correlated with tracking data for all species except Manx shearwater. Correlations between foraging radius distributions and aerial survey data were also significant, but generally weaker than those for tracking data. Correlations between foraging radius distributions and aerial survey data were benchmarked against generalised additive models (GAMs) of the aerial survey data that included a range of environmental covariates. While GAM distributions had slightly higher correlations with aerial survey data, the results highlight that the foraging radius approach can be a useful and pragmatic approach for assessing breeding distributions for many seabird species. The approach is likely to have acceptable utility in complex, temporally variable ecosystems and when logistic and financial resources are limited.

Highlights

  • Determining the distributions of species for conservation planning can present many challenges

  • To provide a benchmark for the correlation values between foraging radius distributions and empirical data, we model distributions from the aerial survey data using generalised additive models (GAMs), incorporating environmental predictors, as this approach is often considered to be the best method for modelling survey data (Booth and Hammond 2014, Potts and Rose 2018)

  • Overall the foraging radius method showed a good match with empirical GPS data at the colony level, and only slightly underperformed at the regional level compared to a much more complex model requiring extensive empirical survey and environmental data

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Summary

Introduction

Determining the distributions of species for conservation planning can present many challenges. There is often insufficient data to inform conservation planning in marine systems, leading to a difficulty in defining marine protected areas for many marine top predators (Game et al 2009, Dias et al 2017). This is especially true for seabirds, a taxonomic group for which there remains a major gap in the level of protection afforded at sea for even the most threatened species (McGowan et al 2017, Critchley et al 2018) and who face significant threats when foraging at sea (Croxall et al 2012, Dias et al 2019). This avoids any uncertainties about the relationship of observations with environmental data being propagated in the final model output

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