Flexible or Familiar? Migrating Gulls are both!

This blog post is provided by Morgan Brown and tells the #StoryBehindThePaper for the article “Long‐distance migrants vary migratory behaviour as much as short‐distance migrants: An individual‐level comparison from a seabird species with diverse migration strategies”, which was recently published in Journal of Animal Ecology.
Morgan Brown is a PhD candidate with Prof. Judy Shamoun-Baranes and Prof. Willem Bouten in the Institute for Biodiversity and Ecosystem Dynamics at the University of Amsterdam. Her PhD focuses on the consequence of individual differences in migration strategies.

I have always been in awe of seasonal migrations undertaken by many animal species. Initially I was amazed at how migrating animals can endure the high energetic demands of traveling for hours on end, and the danger associated with finding food in an unfamiliar landscape.  More recently, however, I find myself contemplating the cognitive challenges migration poses. How do animal know when and where to migrate? This is an important decision to make, because the better an individual can match its migratory movements to patterns of food and weather across both space and time, the more it will benefit from its migratory trip. Is it better to follow a familiar route and schedule, or try to predict the best times and places to be based on information in their surrounding environment? As it turns out, the answer to this question may depend on how far an animal migrates.

A Lesser Black-Backed Gull with a GPS tracker. Does migration distance influence how it decides where and when to move? Photo: Kees Camphuysen

For the past 30 or so years, concern has been raised regarding whether seasonal migrants will be able to change their migratory behaviour alongside rapidly advancing climatic patterns. To address this, researchers have looked at past records of arrival times of avian species to their breeding grounds. Some of these studies suggest that species that winter closer to breeding areas change movement based on year-to-year variation, while species migrating long distances tend to arrive around the same calendar dates each year. One proposed explanation for this is that, because short-distance migrants have wintering areas near to breeding areas they share similar environmental patterns, providing reliable information that can be used to adjust migratory behaviour. Long-distance migrants on the other hand are more disconnected from their destination, making predicting of future and distant conditions unreliable, and instead should resort to following averages of past weather patterns. Differences in information quality by migration strategy is a challenge faced by individuals, so we thought it would be interesting to look into whether we could observe an influence of migration distance on variation in migratory behaviour at an individual level.  To properly look at variation in migratory behaviour at this scale, one needs to be able to repeatedly observe movement times and locations of the same individual across years, and such long-term data are rare.

During my PhD at the University of Amsterdam, I’ve been focusing on the migration ecology of lesser black-backed gulls (Larus fuscus).  This is a species notable for extreme individual differences in behaviours, from foraging specialisation right up to migration strategy.  If you follow two lesser black-backed gulls breeding side-by-side in a colony to their wintering destinations, you may find one moving only 50 km away to forage at a local chip factory all winter, while its neighbour flies 4000 km to spend the winter on the coast of West Africa. Fortunately, this species is large enough that we can actually follow these movements year round using small GPS trackers, and these solar powered devices will continue working for several years. By collaborating with gull researchers in Belgium and the UK, we were able to pull together a sufficiently large dataset to look at whether individual variation in migratory behaviour changes with migration distance. 

An adult lesser black-backed gull having a solar-powered GPS tracker harnessed to its back.  These trackers can follow movements of these birds for multiple years at resolutions of a few meters every 20 minutes! Photo: Roos Kentie.

These data are not only special for their longevity, but also the resolution of the data. GPS records the position of the gull down to a few meters, and we could record this hourly throughout the year. This allowed us to examine variation in migratory behaviours on several ecological scales: from measuring whether individuals deviated from previous migratory routes on the scale of meters and examining fidelity to wintering sites down to a half kilometre area, but also more classical behaviours such as the beginning and end dates of migration, and broad-scale use of stopover and wintering areas.

We certainly saw some impressive examples of individuals varying migratory behaviour across years. At the most extreme, one gull first over-wintered in Morocco, then stayed in the UK the next year, finally returning to Africa for its third winter! Another individual arrived at its wintering area in December during its first tracked migration, then after a brief return to the colony, returned to its wintering area for the rest of the summer, more than 6 months earlier than the previous year! Importantly, the most variable individuals were not linked with migration distance, and in fact, often different individuals were changing behaviour for different traits we examined. This leads us to believe than any individual could behave flexibly if required.  Does this mean that the future of long distance migrants is safe in a rapidly changing world?  Not at all. One of the major challenges we encounter working with the gulls is a poor understanding of the environmental conditions motivating their migration. Animals need not only the ability to change behaviour, which is what we measured, but must change it alongside key environmental conditions which will optimise survival and reproduction in a given year. Such associations are difficult to judge in such a generalist species.

The most extreme examples of variability we observed was this gull who changed migratory destination twice. Overall, 5 out of 62 individuals in this study changed their migratory destination.

Equally surprising was that in general gulls actually seemed to prefer to repeat behaviours across years, even in shorter distance migrants. While we tend to think of gulls, and other species that have adapted to use human-based resources as innovative and flexible, these gulls are truly creatures of habit. Once they find a good place to forage at a certain time of year, they seem to prefer to stick with it.  Perhaps this preference for the familiar is actually helped along by their generalist capabilities:  while natural food resources are more unpredictable and scarce at higher latitudes (promoting higher variability in migratory behaviour), anthropogenic resources should be dependable year-round, enabling behavioural consistency such as we observed in the gulls.

Repeatable migratory behaviours across years was a common trend across migratory traits and migration strategies.  Above is an example of extremely high winter site fidelity of a lesser black-backed gull during two consecutive years, demonstrated by almost perfect overlap in the contours demarking its probability of occurrence (years are coloured differently, with 25, 50, 75 and 95% contours shown). Background map from Stamen.

While this paper has raised many new questions that we look forward to diving into next, it presented an exciting opportunity to exploring an enduring ecological question from a new perspective!

Read the paper

Read the full paper here: Brown, JM, van Loon, EE, Bouten, W, et al. Long‐distance migrants vary migratory behaviour as much as short‐distance migrants: An individual‐level comparison from a seabird species with diverse migration strategies. J Anim Ecol. 2021; 00: 1– 13. https://doi.org/10.1111/1365-2656.13431

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s