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Abstract Human activities and climate change threaten seabirds globally, and many species are declining from already small breeding populations. Monitoring of breeding colonies can identify population trends and important conservation concerns, but it is a persistent challenge to achieve adequate coverage of remote and sensitive breeding sites. Southern giant petrels (Macronectes giganteus) exemplify this challenge: as polar, pelagic marine predators they are subject to a variety of anthropogenic threats, but they often breed in remote colonies that are highly sensitive to disturbance. Aerial remote sensing can overcome some of these difficulties to census breeding sites and explore how local environmental factors influence important characteristics such as nest-site selection and chick survival. To this end, we used drone photography to map giant petrel nests, repeatedly evaluate chick survival and quantify-associated physical and biological characteristics of the landscape at two neighboring breeding sites on Humble Island and Elephant Rocks, along the western Antarctic Peninsula in January–March 2020. Nest sites occurred in areas with relatively high elevations, gentle slopes, and high wind exposure, and statistical models predicted suitable nest-site locations based on local spatial characteristics, explaining 72.8% of deviance at these sites. These findings demonstrate the efficacy of drones as a tool to identify, map, and monitor seabird nests, and to quantify important habitat associations that may constitute species preferences or sensitivities. These may, in turn, contextualize some of the diverse population trajectories observed for this species throughout the changing Antarctic environment. 

ABSTRACT MotivationHere, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables IncludedThe database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and GrainSampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and GrainThe earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of MeasurementThe database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Formatcsv and. SQL.