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The way animals select their breeding habitat may have great impacts on individual fitness. This complex process depends on the integration of information on various environmental factors, over a wide range of spatiotemporal scales. For seabirds, breeding habitat selection integrates both land and sea features over several spatial scales. Seabirds explore these features prior to breeding, assessing habitats' quality. However, the information-gathering and decision-making process by seabirds when choosing a breeding habitat remains poorly understood. We compiled 49 historical records of larids colonies in Cuba from 1980 to 2020. Then, we predicted potentially suitable breeding sites for larids and assessed their breeding macrohabitat selection, using deep and machine learning algorithms respectively. Using a convolutional neural network and Landsat satellite images we predicted the suitability for nesting of non-monitored sites of this archipelago. Furthermore, we assessed the relative contribution of 18 land- and marine-based environmental covariates describing macrohabitats at three spatial scales (i.e. 10, 50 and 100 km) using random forests. Convolutional neural network exhibited good performance at training, validation and test (F1-scores >85%). Sites with higher habitat suitability (p > .75) covered 20.3% of the predicting area. Larids breeding macrohabitats were sites relatively close to main islands, featuring sparse vegetation cover and high chlorophyll-a concentration at sea in 50 and 100 km around colonies. Lower sea surface temperature at larger spatial scales was determinant to distinguish the breeding from non-breeding sites. A more comprehensive understanding of the seabird breeding macrohabitats selection can be reached from the complementary use of convolutional neural networks and random forest models. Our analysis provides crucial knowledge in tropical regions that lack complete and regular monitoring of seabirds' breeding sites.

Seabirds play important roles as marine ecosystem sentinels. Studying their at-sea ecology is essential for understanding how environmental variability affects their populations. However, the at-sea ecology of small-sized temperate seabirds remains poorly studied. We explored the at-sea ecology of the Critically Endangered MacGillivray’s prion Pachyptila macgillivrayi breeding on the subtropical Saint Paul Island. Using global location sensor loggers and stable isotope analysis, we investigated movements, migratory strategies, at-sea activity and moulting period, and characterized the isotopic niche of tracked individuals. During incubation, MacGillivray’s prions remained in temperate waters north of the Subtropical Front, possibly feeding on prey caught in cold eddies. During the inter-breeding period, individuals wintered almost equally to the north and south of the Subtropical Front in 2 distinct sectors (Tasman Sea and Southwest Indian Ridge). Daily activity varied seasonally, and individuals overwintering in the Tasman Sea spent more time flying at night when moonlight intensity was high. Moulting occurred after the breeding period and lasted longer compared to other prion species. Isotopic data suggest a higher dietary proportion of low trophic-level prey for MacGillivray’s prions than for Antarctic and slender-billed prions, highlighting trophic segregation in relation to bill width. Our study provides new evidence to understand the suite of adaptations allowing the abundant prion species to coexist by feeding on prey of different sizes. Contrary to the majority of seabird species, MacGillivray’s prions from Saint Paul Island exhibited 2 migratory tactics with associated differences in at-sea activity, leading to questions about the origin of these differences.