Abstract

As environmental conditions fluctuate across years, seasonal migrants must determine where and when to move without comprehensive knowledge of conditions beyond their current location. Animals can address this challenge by following cues in their local environment to vary behaviour in response to current conditions, or by moving based on learned or inherited experience of past conditions resulting in fixed behaviour across years.It is often claimed that long‐distance migrants are more fixed in their migratory behaviour because as distance between breeding and wintering areas increases, reliability of cues to predict distant and future conditions decreases. While supported by some population‐level studies, the influence of migration distance on behavioural variation is seldom examined on an individual level.Lesser black‐backed gulls Larus fuscus are generalist seabirds that use a diversity of migration strategies. Using high‐resolution multi‐year GPS tracking data from 82 individuals from eight colonies in Western Europe, we quantified inter‐ and intra‐individual variation in non‐breeding distributions, winter site fidelity, migration routes and timing of migration, with the objectives of determining how much variation lesser black‐backed gulls have in their migratory behaviour and examining whether variation changes with migration distance.We found that intra‐individual variation was significantly lower than variation between individuals for non‐breeding distributions, winter site fidelity, migration routes and timing of migration, resulting in consistent individual strategies for all behaviours examined. Yet, intra‐individual variation ranged widely among individuals (e.g. winter site overlap: 0–0.91 out of 1; migration timing: 0–192 days), and importantly, individual differences in variation were not related to migration distance.The apparent preference for maintaining a consistent strategy, present in even the shortest distance migrants, suggests that familiarity may be more advantageous than exactly tracking current environmental conditions. Yet, variation in behaviour across years was observed in many individuals and could be substantial. This suggests that individuals, irrespective of migration distance, have the capacity to adjust to current conditions within the broad confines of their individual strategies, and occasionally, even change their strategy.

Highlights

  • Seasonal environments offer animals predictable periods of high productivity, though presenting the challenge of scarcity during the other portion of the annual cycle

  • We found that intra-­individual variation was significantly lower than variation between individuals for non-­breeding distributions, winter site fidelity, migration routes and timing of migration, resulting in consistent individual strategies for all behaviours examined

  • No clear effect of migration distance on individual variation was found in lesser black-­backed gulls from these populations. This is in contrast to numerous phenological studies, covering a range of avian taxa, which have found that species migrating long distances are more fixed in their timing of spring migration compared to short-­to-­ mid-­distance migrants, both in response to long-­term climate change (Hagan et al, 1991; Miller-­Rushing et al, 2008; Murphy-K­ lassen et al, 2005; Rubolini et al, 2010) and year-­to-­year changes in environmental conditions (La Sorte et al, 2016; Rainio et al, 2006)

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Summary

| INTRODUCTION

Seasonal environments offer animals predictable periods of high productivity, though presenting the challenge of scarcity during the other portion of the annual cycle. Short-­distance migrants, on the other hand, are generally expected to adjust migratory behaviour based on current conditions, resulting in intra-­individual variation across years. This may be done by either following current resource gradients (i.e. surfing resource waves, Armstrong et al, 2016; Van der Graaf et al, 2006) or using local environmental cues such as temperature (Deutsch et al, 2003) or vegetation (Balbontín et al, 2009; Merkle et al, 2016; Van der Graaf et al, 2006) to predict remote and future resource patterns.

| MATERIALS AND METHODS
Findings
| DISCUSSION
| CONCLUSIONS
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