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As part of a multi-year study of top predators in Antarctica, we conducted a seabird shipbased survey on board Almirante Irizar icebreaker in the Weddell Sea to the Filchner Ice Shelf in the austral summer 2020. We carried out 10-minute counts along 1843 km during 125 hours of observation. We analyzed the species distributions and the relationships with the ice cover. We registered 15 species of which four represented more than 85% of the total abundance: Antarctic petrel Thalassoica antarctica (43.9%), snow petrel Pagodroma nivea (16.3%), Arctic tern Sterna paradisaea (15.2%) and emperor penguin Aptenodytes forsteri (10.1%). Species distribution and its relationship with ice cover were analyzed statistically. The ice cover concentration was estimated by using satellite images. We compared our results with the first ship-based bird survey conducted up to the Filchner Ice Shelf in the austral summer 1955/56 to analyze possible changes in the bird community over time. Out of 13 recorded species in the 1955/56 cruise, 11 were present in this study with similar abundance proportions. In both cruises, the bird community consisted of a group of non-numerous species associated with icefree waters and another group of very numerous species associated with high concentrations on ice cover. The similarities between the two cruises, spaced 65 years apart, suggest a temporal persistence of the bird community of the central and the southern Weddell Sea that could be explained by the dynamics of the ice cover and the presence of reproductive colonies within the study site. The current environmental warming is alarming in this bird community because more than 85% of all its individuals belong to four species strongly dependent on ice cover.

Estimating species’ potential distribution is one of the main objectives of macroecology, especially when sampling biases can affect knowledge on how environmental variables affect species distribution. Ecological niche models estimate species’ environmental niches from different variables and their occurrences. Using the presence‐only data from eight Amazonian fish species, which inhabit rivers and streams, we aimed to (a) explore the effect of different sets variables on the spatial distributions of target species and (b) evaluate the predictive responses of MaxEnt to sets of variables with different degrees of complexity. MaxEnt has high flexibility in relation to the input data and its performance is influenced by a moderate number of adjustable parameters, allowing for high precision results when balancing underestimation and overestimation errors. We used environmental predictors in MaxEnt the principal components of climatic, topographic and edaphic variables as inputs. The combination of topographic and edaphic variables produced more precise and spatially restricted distribution ranges for all species when compared to those generated with climatic variables. All models reached high AUC values, especially for stream species. Modelled range sizes were broader for the river species, suggesting different tolerance thresholds and habitat preferences when compared to stream species. The complexity of the different variables sets did not affect MaxEnt's prediction capacity. However, for stream species, MaxEnt showed a greater predictive power. This work increases the knowledge with regards to the influence of different environmental predictors on the spatial patterns of the distribution of Amazonian fish.

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