Standardised empirical dispersal kernels emphasise the pervasiveness of long-distance dispersal in European birds
Author(s): Fandos, G., Talluto, M., Fielder, W., Robinson, R.A., Thorup, K. & Zurell, D.
Published: November 2022
Journal: Journal of Animal Ecology
Digital Identifier No. (DOI): 10.1111/1365-2656.13838
In a study conducted in collaboration with BTO, scientists estimated the dispersal patterns of 234 European bird species using data from the EURING (European Union for Bird Ringing) Databank of birds ringed and subsequently re-encountered (either alive or dead). Information on where ringed birds had been recaptured or found dead demonstrated how far they had travelled. The raw data were first processed in order to reduce the bias caused by an uneven ringing effort across the continent.
The scientists then used these data to create a ‘dispersal kernel’ for each species. Dispersal kernels describe the number of birds moving different distances; most don’t disperse very far, but a few individuals can move a long way. A number of different methods for estimating dispersal kernels already exist, each of which has its own set of assumptions about the birds’ behaviour, and the team compared four of these to determine which was the best fit for their ringing data. They could then better quantify the bird’s behaviour based on the assumptions of the best fitting method.
Being able to describe dispersal in this way makes it possible to incorporate this information into other analyses; for example, investigations into how changes in the environment might influence population change. The scientists were also able to compare dispersal characteristics between the sexes and investigate if the patterns seen were different depending on whether it was natal or breeding dispersal.
The scientists found that the data for almost all of the featured species were best described by so-called ‘heavy-tailed’ kernels. This means that for most species, although most individual birds are unlikely to travel far, more individuals than might be expected undertake long-distance movements. These long-distance dispersal events can introduce new species or genes into an area, but they are very rarely detected. By developing these methods as part of this analysis, this paper may help others to make more accurate predictions of bird movements in the future.
As predicted, the scientists also found that birds tended to travel further during natal dispersal than breeding dispersal. When leaving the area in which they were born, birds travelled (on average) more than twice the distance they covered when swapping breeding sites (7.74 km compared to 2.83 km). Putting some distance between yourself and your immediate family may help to avoid inbreeding or prevent direct competition with siblings.Surprisingly, the study did not find any widespread sex-biased dispersal patterns. In many bird species, it is thought that the females engage in dispersal more regularly than males; however, these patterns were not replicated in this study. In future, considering how dispersal differences between the sexes might change with age could shed some light on this discrepancy.
Testing statistical methods using empirical data is crucial to appraise their accuracy and understand their limitations. The methods included in this study will help future work produce more realistic models, paving the way for scientists to address many of those unanswered questions on avian dispersal patterns. As species continue to adjust their ranges in response to climate change, this information could have considerable conservation value.
Dispersal is a key life-history trait for most species and is essential to ensure connectivity and gene flow between populations and facilitate population vi-ability in variable environments. Despite the increasing importance of range shifts due to global change, dispersal has proved difficult to quantify, limiting empirical understanding of this phenotypic trait and wider synthesis.
Here, we introduce a statistical framework to estimate standardised dispersal kernels from biased data. Based on this, we compare empirical dispersal kernels for European breeding birds considering age (average dispersal; natal, before first breeding; and breeding dispersal, between subsequent breeding attempts) and sex (females and males) and test whether different dispersal properties are phylogenetically conserved.
We standardised and analysed data from an extensive volunteer-based bird ring-recoveries database in Europe (EURING) by accounting for biases related to different censoring thresholds in reporting between countries and to migratory movements. Then, we fitted four widely used probability density functions in a Bayesian framework to compare and provide the best statistical descriptions of the different age and sex-specific dispersal kernels for each bird species.
The dispersal movements of the 234 European bird species analysed were statistically best explained by heavy-tailed kernels, meaning that while most individuals disperse over short distances, long-distance dispersal is a prevalent phenomenon in almost all bird species. The phylogenetic signal in both median and long dispersal distances estimated from the best-fitted kernel was low (Pagel's λ< 0.25), while it reached high values (Pagel's λ>0.7) when comparing dispersal distance estimates for fat-tailed dispersal kernels. As expected in birds natal dispersal was on average 5 km greater than breeding dispersal, but sex- biased dispersal was not detected.
Our robust analytical framework allows sound use of widely available mark-recapture data in standardised dispersal estimates. We found strong evidence that long-distance dispersal is common among European breeding bird species and across life stages. The dispersal estimates offer a first guide to selecting appropriate dispersal kernels in range expansion studies and provide new avenues to improve our understanding of the mechanisms and rules underlying dispersal events.
NotesThe authors thank the Euring DataBank managers (most recently Dorian Moss) for curating and supplying the data, and the many thousands of ringers and members of the public who generated the data in the first place. They extend special thanks to Stephen R. Baillie for helpful comments on a previous version of this paper. Open Access funding enabled and organized by Projekt DEAL. GF and DZ were supported by the German Science Foundation (DFG) under grant agreement No. ZU 361/1-1.
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