Abstract: 17O-excess (Δ17O = δ17O − 0.52 × δ18O) of sulfate trapped in Antarctic ice cores has been proposed as a potential tool for assessing past oxidant chemistry, while insufficient understanding of atmospheric sulfate formation around Antarctica hampers its interpretation. To probe influences of regional specific chemistry, we compared year-round observations of Δ17O of non-sea-salt sulfate in aerosols (Δ17O(SO42−)nss) at Dome C and Dumont d'Urville, inland and coastal sites in East Antarctica, throughout the year 2011. Although Δ17O(SO42−)nss at both sites showed consistent seasonality with summer minima (∼1.0‰) and winter maxima (∼2.5‰) owing to sunlight-driven changes in the relative importance of O3 oxidation to OH and H2O2 oxidation, significant intersite differences were observed in austral spring–summer and autumn. The cooccurrence of higher Δ17O(SO42−)nss at inland (2.0‰ ± 0.1‰) than the coastal site (1.2‰ ± 0.1‰) and chemical destruction of methanesulfonate (MS–) in aerosols at inland during spring–summer (October–December), combined with the first estimated Δ17O(MS–) of ∼16‰, implies that MS– destruction produces sulfate with high Δ17O(SO42−)nss of ∼12‰. If contributing to the known postdepositional decrease of MS– in snow, this process should also cause a significant postdepositional increase in Δ17O(SO42−)nss over 1‰, that can reconcile the discrepancy between Δ17O(SO42−)nss in the atmosphere and ice. The higher Δ17O(SO42−)nss at the coastal site than inland during autumn (March–May) may be associated with oxidation process involving reactive bromine and/or sea-salt particles around the coastal region.

Abstract: Managing marine systems is challenging, as many marine species are highly mobile. Albatross exemplify this paradigm, overlapping multiple threats at sea, including bycatch. The typical characterization of bycatch, the number of individuals, ignores the long-term, population-wide repercussions of bycatch. Including an estimate of the reproductive value (RV, the loss of future reproductive contributions, given bycatch) is a complementary tool, incorporating the population-wide repercussions of bycatch. While bycatch management via dynamic spatial management allows management boundaries to move, it requires monitoring and enforcement to be effective. We provide a proof of concept to optimize bycatch enforcement activities by dynamically targeting areas of concentrated future productivity characterized by RV. This paper examined a population of black-browed albatross (Thalassarche melanophris) as a case study. We calculate RV and apply it to at-sea distributions. This creates spatiotemporally explicit surfaces used to prioritize times and locations for bycatch mitigation enforcement. Dynamic enforcement has greater theoretical efficiency than static enforcement, but this difference decreases with increasing population-wide RV subject to enforcement. Though there are implementation challenges, many can be reduced with existing tools providing various opportunities. Incorporating RV when characterizing the impacts of bycatch on a population and strategically applying dynamic bycatch enforcement based on RV can be a powerful, efficient component of dynamic ocean management.

Abstract: Many seabirds are attracted to fishing boats where they exploit foraging opportunities, often involving bycatch-related mortality. Bycatch risk is generally estimated by overlapping seabirds foraging ranges with coarse-scale monthly maps of fishing efforts, but a more direct estimation would be the time birds actually spend attending fishing boats. Here we matched data from Automatic Identification Systems from all declared boats in the Southern Ocean, with 143 simultaneous foraging trips from all populations of large albatrosses (Diomedea amsterdamensis and Diomedea exulans) breeding in the Indian Ocean (Marion, Crozet, Kerguelen, Amsterdam islands). We quantified and compared real-time co-occurrence between boats and albatrosses, at different scales (100, 30 and 5 km). We also examined to what extent co-occurrence at a large-scale (5×5° grid cell) predicted fine-scale attendance (5 km). Albatrosses on average spent about 3 h per trip attending fishing boats (<5 km) at both Amsterdam and Marion and about 30 h per trip at Kerguelen. In all populations, >90% of declared fishing boat attendances occurred within Economic Exclusive Zones (EEZ) where bycatch mitigation measures are enforced. Outside EEZs, birds from all populations to a large extent also attended non-fishing boats. Fishing boat density at a large scale (5 × 5°, 100 km) was a poor predictor of time spent attending fishing boats (<5 km) across populations. Our results indicate a large variation in fishing boat densities within the foraging ranges of different populations and in the time birds spent attending boats. We discuss the pros and cons of considering bycatch risk at a large geographical scale and methods that can be implemented to improve the estimation of seabird vulnerability to fishing activities when fine-scale data are available, particularly for the conservation of those highly threatened species.

Abstract: Aim Here, we aim to: (a) investigate the local effect of environmental and anthropogenic factors on alien plant invasion in sub-Antarctic islands; and (b) explore whether and how functional traits affect alien species dependence on anthropogenic factors in these environments. Location Possession Island, Crozet archipelago (French sub-Antarctic islands). Methods Single-species distribution models were used to explore the effect of high-resolution topoclimatic and human-related variables on the occurrence of six alien plants colonizing French sub-Antarctic islands. Furthermore, plant responses to human-related variables and the effect of those variables in interaction with plant traits were analysed by means of a multi-species distribution model. This allowed identifying functional features mediating the influence of human activities on the occurrence probability of alien plant species. Results We observed two main invasion patterns: (a) species predicted to occur close to the introduction sites, whose occurrence probability appeared to be strongly affected by anthropogenic factors; and (b) species predicted to occur nearly everywhere on Possession Island, except in areas featuring particularly harsh climatic conditions. Differences in the influence of human-related variables on the occurrence of the alien species were mostly related to their life history, plant height and residence time, with perennial and low-statured species introduced earlier appearing less dependent on human-induced dispersal and disturbance. Conclusions We conclude that both topoclimatic and anthropogenic factors affect plant invasion on sub-Antarctic islands. Specifically, species predicted to occur close to their introduction sites appear much more dependent on human presence and activity, potentially due to the lack of key functional traits allowing them to spread successfully across Possession Island under the harsh sub-Antarctic climate. Yet, particularly severe abiotic conditions are a major constraint which equally limits the occurrence of all alien plants, irrespective of their dependence on anthropogenic factors.

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.