Flyway connectivity and exchange primarily driven by moult migration in geese

Abstract

BackgroundFor the conservation and management of migratory species that strongly decrease or increase due to anthropological impacts, a clear delineation of populations and quantification of possible mixing (migratory connectivity) is crucial. Usually, population exchange in migratory species is only studied in breeding or wintering sites, but we considered the whole annual cycle in order to determine important stages and sites for population mixing in an Arctic migrant.MethodsWe used 91 high resolution GPS tracks of Western Palearctic greater white-fronted geese (Anser A. albifrons) from the North Sea and Pannonic populations to extract details of where and when populations overlapped and exchange was possible. Overlap areas were calculated as dynamic Brownian bridges of stopover, nest and moulting sites.ResultsUtilisation areas of the two populations overlapped only somewhat during spring and autumn migration stopovers, but much during moult. During this stage, non-breeders and failed breeders of the North Sea population intermixed with geese from the Pannonic population in the Pyasina delta on Taimyr peninsula. The timing of use of overlap areas was highly consistent between populations, making exchange possible. Two of our tracked geese switched from the North Sea population flyway to the Pannonic flyway during moult on Taimyr peninsula or early during the subsequent autumn migration. Because we could follow one of them during the next year, where it stayed in the Pannonic flyway, we suggest that the exchange was long-term or permanent.ConclusionsWe have identified long-distance moult migration of failed or non-breeders as a key phenomenon creating overlap between two flyway populations of geese. This supports the notion of previously suggested population exchange and migratory connectivity, but outside of classically suggested wintering or breeding sites. Our results call for consideration of moult migration and population exchange in conservation and management of our greater white-fronted geese as well as other waterfowl populations.

Individual Black-Tailed Godwits Do Not Stick to Single Routes: A Hypothesis on How Low Population Densities Might Decrease Social Conformity

“…Because they rely on distinct and widely dispersed food-rich freshwater or coastal mudflats, long-distance migratory shorebirds like Godwits are expected to exhibit high consistency in migratory routes (Newton 2008, Ruthrauff et al 2019. The flexibility to switch between routes observed in Polish Godwits during both southward and northward migration, contradicts this expectation and suggests that Godwits either (1) have an innate map of different suitable migratory routes, (2) continuously learn through the use of social information, or (3) discover and switch routes through a form of asocial learning (Kendal et al 2005, Creswell 2014, Flack et al 2012, Mueller et al 2013, Berdahl et al 2018, Mouritsen 2018, Kölzsch et al 2019. Unfortunately, we only tracked experienced adult birds and in the absence of information on the composition of migratory flocks, we are unable to assess whether the conditions for individual learning and social knowledge sharing existed.…”

“…Bauer & Hoye 2014, Winkler et al 2016. At the same time, the increasing number of repeated individual tracks reveal an intriguing palette of intraspecific variation in the spatial and temporal consistency of migration, which continues to develop our understanding of the various factors influencing the spatial and temporal patterns of migration (Bairlein 2003, Conklin et al 2013, Kölzsch et al 2019.…”

Nesting attempts and success of Arctic-breeding geese can be derived with high precision from accelerometry and GPS-tracking

“…Our main approach acquires a high level of precision and can detect nest attempts as short as 3 days, which is not easily achievable with methods based on only GPS without additional sensor data. For example, [21] suggest for three bird species that nesting attempts below 7-14 days can usually not be detected based on GPStracking data, and [19] and [20] use for two goose species a minimum duration of 10 days. The power of including sensor data in the analysis lies in the fact that one can specifically select GPS-fixes (or days) with a certain body motion of interest and exclude those that are part of other activities than nesting, e.g., foraging or preening.…”

“…Breeding events have been detected in previous studies based on GPS data [e.g., 19,20,21], but additional sensors, especially an accelerometer, are expected to increase the power and precision of nest(ing) detection. Accelerometry enables us to focus on GPS-fixes, or days, on which the bird displayed an activity level or body orientation of interest [e.g.…”

“…Previous studies on wood stork (Mycteria americana), lesser kestrel (Falco naumanni), Mediterranean gull (Ichthyaetus melanocephalus) [21] concluded that nesting attempts shorter than 7-14 days can usually not be detected based on GPS-tracking data. Also, [19] and [20] defined nests of GPS-tracked barnacle geese (Branta leucopsis) and greater white-fronted geese (Anser albifrons) as locations from which geese stayed within 2 km for at least 10 days, during a defined breeding season. However, a more precise method which can detect short nesting attempts is important to distinguish a low breeding propensity from a high breeding failure.…”