Year-round spatiotemporal distribution pattern of a threatened sea duck species breeding on Kolguev Island, south-eastern Barents Sea.

BACKGROUND: The long-tailed duck (Clangula hyemalis) was categorized as ´Vulnerable` by the IUCN after a study revealed a rapid wintering population decline of 65% between 1992-1993 and 2007-2009 in the Baltic Sea. As knowledge about the European long-tailed duck's life cycle and movement ecology is limited, we investigate its year-round spatiotemporal distribution patterns. Specifically, we aimed to identify the wintering grounds, timing of migration and staging of this population via light-level geolocation. RESULTS: Of the 48 female long-tailed ducks tagged on Kolguev Island (western Russian Arctic), 19 were recaptured to obtain data. After breeding and moulting at freshwater lakes, ducks went out to sea around Kolguev Island and to marine waters ranging from the White Sea to Novaya Zemlya Archipelago for 33 ± 10 days. After a rapid autumn migration, 18 of 19 birds spent their winter in the Baltic Sea and one bird in the White Sea, where they stayed for 212 ± 3 days. There, they used areas known to host long-tailed ducks, but areas differed among individuals. After a rapid spring migration in mid-May, the birds spent 23 ± 3 days at sea in coastal areas between the White Sea and Kolguev Island, before returning to their freshwater breeding habitats in June. CONCLUSIONS: The Baltic Sea represents the most important wintering area for female long-tailed ducks from Kolguev Island. Important spring and autumn staging areas include the Barents Sea and the White Sea. Climate change will render these habitats more exposed to human impacts in the form of fisheries, marine traffic and oil exploitation in near future. Threats that now operate in the wintering areas may thus spread to the higher latitude staging areas and further increase the pressure on long-tailed ducks.

Model-based selection of areas for the restoration of Acrocephalus paludicola habitats in NE Germany.

The global Aquatic Warbler (Acrocephalus paludicola, Vieillot, 1817) population has suffered a major decline due to the large-scale destruction of its natural habitat (fen mires). The species is at risk of extinction, especially in NE Germany/NW Poland. In this study, we developed habitat suitability models based on satellite and environmental data to identify potential areas for habitat restoration on which further surveys and planning should be focused. To create a reliable model, we used all Aquatic Warbler presences in the study area since 1990 as well as additional potentially suitable habitats identified in the field. We combined the presence/absence regression tree algorithm Cubist with the presence-only algorithm Maxent since both commonly outperform other algorithms. To integrate the separate model results, we present a new way to create a metamodel using the initial model results as variables. Additionally, a histogram approach was applied to further reduce the final search area to the most promising sites. Accuracy increased when using both remote sensing and environmental data. It was highest for the integrated metamodel (Cohen's Kappa of 0.4, P < 0.001). The final result of this study supports the selection of the most promising sites for Aquatic Warbler habitat restoration.