Dataset Information

Birds of three worlds: moult migration to high Arctic expands a boreal-temperate flyway to a third biome.

ABSTRACT:

Background

Knowledge on migration patterns and flyways is a key for understanding the dynamics of migratory populations and evolution of migratory behaviour. Bird migration is usually considered to be movements between breeding and wintering areas, while less attention has been paid to other long-distance movements such as moult migration.

Methods

We use high-resolution satellite-tracking data from 58 taiga bean geese Anser fabalis fabalis from the years 2019-2020, to study their moult migration during breeding season. We show the moulting sites, estimate the migratory connectivity between the breeding and the moulting sites, and estimate the utilization distributions during moult. We reveal migration routes and compare the length and timing of migration between moult migrants and successful breeders.

Results

All satellite-tracked non-breeding and unsuccessfully breeding taiga bean geese migrated annually to the island of Novaya Zemlya in the high Arctic for wing moult, meaning that a large part of the population gathers at the moulting sites outside the breeding range annually for approximately three months. Migratory connectivity between breeding and moulting sites was very low (r_m = - 0.001, 95% CI - 0.1562-0.2897), indicating that individuals from different breeding grounds mix with each other on the moulting sites. Moult migrants began fall migration later in autumn than successful breeders, and their overall annual migration distance was over twofold compared to the successful breeders.

Conclusions

Regular moult migration makes the Arctic an equally relevant habitat for the taiga bean goose population as their boreal breeding and temperate wintering grounds, and links ecological communities in these biomes. Moult migration plays an important role in the movement patterns and spatio-temporal distribution of the population. Low migratory connectivity between breeding and moulting sites can potentially contribute to the gene flow within the population. Moult migration to the high Arctic exposes the population to the rapid impacts of global warming to Arctic ecosystems. Additionally, Novaya Zemlya holds radioactive contaminants from various sources, which might still pose a threat to moult migrants. Generally, these results show that moult migration may essentially contribute to the way we should consider bird migration and migratory flyways.

SUBMITTER: Piironen A

PROVIDER: S-EPMC8444479 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background:For 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. Methods:We 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. Results:Utilisation 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. Conclusions:We 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.

Project description:Many polar species and habitats are now affected by man-made global climate change and underlying infrastructure. These anthropogenic forces have resulted in clear implications and many significant changes in the arctic, leading to the emergence of new climate, habitats and other issues including digital online infrastructure representing a 'New Artic'. Arctic grazers, like Eastern Russian migratory populations of Tundra Bean Goose Anser fabalis and Greater White-fronted Goose A. albifrons, are representative examples and they are affected along the entire flyway in East Asia, namely China, Japan and Korea. Here we present the best publicly-available long-term (24 years) digitized geographic information system (GIS) data for the breeding study area (East Yakutia and Chukotka) and its habitats with ISO-compliant metadata. Further, we used seven publicly available compiled Open Access GIS predictor layers to predict the distribution for these two species within the tundra habitats. Using BIG DATA we are able to improve on the ecological niche prediction inference for both species by focusing for the first time specifically on biological relevant population cohorts: post-breeding moulting non-breeders, as well as post-breeding parent birds with broods. To assure inference with certainty, we assessed it with 4 lines of evidence including alternative best-available open access field data from GBIF.org as well as occurrence data compiled from the literature. Despite incomplete data, we found a good model accuracy in support of our evidence for a robust inference of the species distributions. Our predictions indicate a strong publicly best-available relative index of occurrence (RIO). These results are based on the quantified ecological niche showing more realistic gradual occurrence patterns but which are not fully in agreement with the current strictly applied parsimonious flyway and species delineations. While our predictions are to be improved further, e.g. when synergetic data are made freely available, here we offer within data caveats the first open access model platform for fine-tuning and future predictions for this otherwise poorly represented region in times of a rapid changing industrialized 'New Arctic' with global repercussions.