Breeding density, fine‐scale tracking, and large‐scale modeling reveal the regional distribution of four seabird species

Abstract

Abstract. Population-level estimates of species' distributions can reveal fundamental ecological processes and facilitate conservation. However, these may be difficult to obtain for mobile species, especially colonial central-place foragers (CCPFs; e.g., bats, corvids, social insects), because it is often impractical to determine the provenance of individuals observed beyond breeding sites. Moreover, some CCPFs, especially in the marine realm (e.g., pinnipeds, turtles, and seabirds) are difficult to observe because they range tens to ten thousands of kilometers from their colonies. It is hypothesized that the distribution of CCPFs depends largely on habitat availability and intraspecific competition. Modeling these effects may therefore allow distributions to be estimated from samples of individual spatial usage. Such data can be obtained for an increasing number of species using tracking technology. However, techniques for estimating population-level distributions using the telemetry data are poorly developed. This is of concern because many marine CCPFs, such as seabirds, are threatened by anthropogenic activities. Here, we aim to estimate the distribution at sea of four seabird species, foraging from approximately 5,500 breeding sites in Britain and Ireland. To do so, we GPS-tracked a sample of 230 European Shags Phalacrocorax aristotelis, 464 Black-legged Kittiwakes Rissa tridactyla, 178 Common Murres Uria aalge, and 281 Razorbills Alca torda from 13, 20, 12, and 14 colonies, respectively. Using Poisson point process habitat use models, we show that distribution at sea is dependent on (1) density-dependent competition among sympatric conspecifics (all species) and parapatric conspecifics (Kittiwakes and Murres); (2) habitat accessibility and coastal geometry, such that birds travel further from colonies with limited access to the sea; and (3) regional habitat availability. Using these models, we predict space use by birds from unobserved colonies and thereby map the distribution at sea of each species at both the colony and regional level. Space use by all four species' British breeding populations is concentrated in the coastal waters of Scotland, highlighting the need for robust conservation measures in this area. The techniques we present are applicable to any CCPF.

Seasonal shifts in foraging distribution due to individual flexibility in a tropical pelagic forager, the Ascension frigatebird

“…These predators are constrained to a central location during the breeding season when they need to return to their nest to feed offspring, which results in strong intraspecific competition that can lead to individually varying foraging strategies (Ashmole 1963, Wakefield et al 2013, Wakefield et al 2017. In temperate species, intraspecific competition can be reduced by individuals specialising on a narrow foraging strategy, either in terms of behaviour or in repeatedly exploiting a specific area (Votier et al 2010.…”

Using habitat models for chinstrap penguins Pygoscelis antarctica to advise krill fisheries management during the penguin breeding season

“…Previous studies provide strong evidence that habitat availability and competition are major drivers in the at-sea distribution of central place foragers (Ainley, Nur, & Eric, 1995;Raymond et al, 2015;Trathan et al, 2006;Wakefield et al, 2017). Optimal foraging theory suggests that animals will forage in areas abundant in resources, while minimizing the costs associated with travelling from the colony (MacArthur & Pianka, 1966).…”

“…Additionally, the relative availability of habitats may vary between sites. This would result in variation in habitat selection between colonies and lead to models with poor predictive power (Matthiopoulos, 2003;Wakefield et al, 2017). Previous studies where habitat models for central place foragers maintained high predictive power when extrapolated into new locations frequently include availability (e.g., distance from the colony) and competition as important predictor variables (Raymond et al, 2015;Wakefield et al, 2011), and environmental variables were often less important.…”

Ecological costs of climate change on marine predator–prey population distributions by 2050

“…In the North Sea and Atlantic region long-term (up to 40 years) surveys for fish, fish larvae (Edwards et al, 2011;ICES, 2016), seabirds (Kober et al, 2010), and marine mammals (Hammond et al, 2013), as well as more recent use of tagged mammals and seabirds (Jones et al, 2013;Wakefield et al, 2017), have allowed the creation of seasonal and annual spatial distributions of either density or abundance depending on the data for the mobile species (see section on "Study Area and Species"). These outcomes can then be used in ecosystem models as predictors of the amount of future population change for a given stressor, that is, climate change or largescale renewable developments.…”

“…We use a selected group of important biological and physical variables (see section "Physical Environmental Variables" for more details) that will change with climate change and have been shown to be important to marine mammals and seabirds and their prey (Carroll et al 2015, Chavez-Rosales, Palka, Garrison, & Josephson, 2019, Sadykova et al, 2017, Wakefield et al 2017. The three aims of this study are first to compare joint model distributions of a range of contrasting seabird and mammal species from the present to future (2050) climate change projections.…”