Abstract: Tracking data of marine predators are increasingly used in marine spatial management. We developed a spatial data set with estimates of the monthly distribution of 6 pelagic seabird species breeding in the Northeast Atlantic. The data set was based on year-round global location sensor (GLS) tracking data of 2356 adult seabirds from 2006-2019 from a network of seabird colonies, data describing the physical environment and data on seabird population sizes. Tracking and environmental data were combined in monthly species distribution models (SDMs). Cross-validations were used to assess the transferability of models between years and breeding locations. The analyses showed that birds from colonies close to each other (<500 km apart) used the same nonbreeding habitats, while birds from distant colonies (>1000 km) used colony-specific and, in many cases, non-overlapping habitats. Based on these results, the SDM from the nearest model colony was used to predict the distribution of all seabird colonies lying within a species-specific cut-off distance (400-500 km). Uncertainties in the predictions were estimated by cluster bootstrap sampling. The resulting data set consisted of 4692 map layers, each layer predicting the densities of birds from a given species, colony and month across the North Atlantic. This data set represents the annual distribution of 23.5 million adult pelagic seabirds, or 87% of the Northeast Atlantic breeding population of the study species. We show how the data set can be used in population and spatial management applications, including the detection of population-specific nonbreeding habitats and identifying populations influenced by marine protected areas.

Abstract: Water isotope ratios of ice cores are a key source of information on past temperatures. Through fractionation within the hydrological cycle, temperature is imprinted in the water isotopic composition of snowfalls. However, this signal of climatic interest is modified after deposition when snow remains at the surface exposed to the atmosphere. Comparing time series of surface snow isotopic composition at Dome C with satellite observations of surface snow metamorphism, we found that long summer periods without precipitation favor surface snow metamorphism altering the surface snow isotopic composition. Using excess parameters (combining D,17O, and 18O fractions) allow the identification of this alteration caused by sublimation and condensation of surface hoar. The combined measurement of all three isotopic compositions could help identifying ice core sections influenced by snow metamorphism in sites with very low snow accumulation.