Dr Tom Hart

The microbiome is a key factor in the health, well-being, and success of vertebrates, contributing to the adaptive capacity of the host. However, the impact of geographic and biotic factors that may affect the microbiome of wild birds in polar environments is not well defined. To address this, we determined the bacterial 16S rRNA gene sequence profiles in faecal samples from pygoscelid penguin populations in the Scotia Arc, focusing on gentoo penguins. This mesopredatory group breeds in defined colonies across a wide geographic range. Since diet could influence microbiome structure, we extracted dietary profiles from a eukaryotic 18S rRNA gene sequence profile. The bacterial microbiome profiles were considered in the context of a diverse set of environmental and ecological measures. Integrating wide geographic sampling with bacterial 16S and eukaryotic 18S rRNA gene sequencing of over 350 faecal samples identified associations between the microbiome profile and a suite of geographic and ecological factors. Microbiome profiles differed according to host species, colony identity, distance between colonies, and diet. Interestingly there was also a relationship between the proportion of host DNA (in relation to total 18S rRNA gene signal) and the microbiome, which may reflect gut passage time. Colony identity provided the strongest association with differences in microbiome profiles indicating that local factors play a key role in the microbiome structure of these polar seabirds. This may reflect the influence of local transfer of microbes either via faecal-oral routes, during chick feeding or other close contact events. Other factors including diet and host species also associate with variation in microbiome profile, and in at least some locations, the microbiome composition varies considerably between individuals. Given the variation in penguin microbiomes associated with diverse factors there is potential for disruption of microbiome associations at a local scale that could influence host health, productivity, and immunological competence. The microbiome represents a sensitive indicator of changing conditions, and the implications of any changes need to be considered in the wider context of environmental change and other stressors.

Over the past decade, drones have become increasingly popular in environmental biology and have been used to study wildlife on all continents. Drones have become of global importance for surveying breeding seabirds by providing opportunities to transform monitoring techniques and allow new research on some of the most threatened birds. However, such fast-changing and increasingly available technology presents challenges to regulators responding to requests to carry out surveys and to researchers ensuring their work follows best practice and meets legal and ethical standards. Following a workshop convened at the 14th International Seabird Group Conference and a subsequent literature search, we collate information from over 100 studies and present a framework to ensure drone-seabird surveys are safe, effective, and within the law. The framework comprises eight steps: (1) Objectives and Feasibility; (2) Technology and Training; (3) Site Assessment and Permission; (4) Disturbance Mitigation; (5) Pre-deployment Checks; (6) Flying; (7) Data Handling and Analysis; and (8) Reporting. The audience is wide-ranging with sections having relevance for different users, including prospective and experienced drone-seabird pilots, landowners, and licensors. Regulations vary between countries and are frequently changing, but common principles exist. Taking-off, landing, and conducting in-flight changes in altitude and speed at ≥ 50 m from the study area, and flying at ≥ 50 m above ground-nesting seabirds/horizontal distance from vertical colonies, should have limited disturbance impact on many seabird species; however, surveys should stop if disturbance occurs. Compared to automated methods, manual or semi-automated image analyses are, at present, more suitable for infrequent drone surveys and surveys of relatively small colonies. When deciding if drone-seabird surveys are an appropriate monitoring method long-term, the cost, risks, and results obtained should be compared to traditional field monitoring where possible. Accurate and timely reporting of surveys is essential to developing adaptive guidelines for this increasingly common technology.

Due to its persistence and potential ecological and health impacts, mercury (Hg) is a global pollutant of major concern that may reach high concentrations even in remote polar oceans. In contrast to the Arctic Ocean, studies documenting Hg contamination in the Southern Ocean are spatially restricted and large-scale monitoring is needed. Here, we present the first circumpolar assessment of Hg contamination in Antarctic marine ecosystems. Specifically, the Adélie penguin (Pygoscelis adeliae) was used as a bioindicator species, to examine regional variation across 24 colonies distributed across the entire Antarctic continent. Mercury was measured on body feathers collected from both adults (n = 485) and chicks (n = 48) between 2005 and 2021. Because penguins’ diet represents the dominant source of Hg, feather δ13C and δ15N values were measured as proxies of feeding habitat and trophic position. As expected, chicks had lower Hg concentrations (mean ± SD: 0.22 ± 0.08 μg·g‒1) than adults (0.49 ± 0.23 μg·g‒1), likely because of their shorter bioaccumulation period. In adults, spatial variation in feather Hg concentrations was driven by both trophic ecology and colony location. The highest Hg concentrations were observed in the Ross Sea, possibly because of a higher consumption of fish in the diet compared to other sites (krill-dominated diet). Such large-scale assessments are critical to assess the effectiveness of the Minamata Convention on Mercury. Owing to their circumpolar distribution and their ecological role in Antarctic marine ecosystems, Adélie penguins could be valuable bioindicators for tracking spatial and temporal trends of Hg across Antarctic waters in the future.

The 20th century commercial whaling industry severely reduced populations of great whales throughout the Southern Hemisphere. The effect of this exploitation on genetic diversity and population structure remains largely undescribed. Here, we compare pre- and post-whaling diversity of mitochondrial DNA (mtDNA) control region sequences for 3 great whales in the South Atlantic, such as the blue, humpback, and fin whale. Pre-whaling diversity is described from mtDNA extracted from bones collected near abandoned whaling stations, primarily from the South Atlantic island of South Georgia. These bones are known to represent the first stage of 20th century whaling and thus pre-whaling diversity of these populations. Post-whaling diversity is described from previously published studies reporting large-scale sampling of living whales in the Southern Hemisphere. Despite relatively high levels of surviving genetic diversity in the post-whaling populations, we found evidence of a probable loss of mtDNA lineages in all 3 species. This is evidenced by the detection of a large number of haplotypes found in the pre-whaling samples that are not present in the post-whaling samples. A rarefaction analysis further supports a loss of haplotypes in the South Atlantic humpback and Antarctic blue whale populations. The bones from former whaling stations in the South Atlantic represent a remarkable molecular archive for further investigation of the decline and ongoing recovery in the great whales of the Southern Hemisphere.

As one of the best studied components of the Southern Ocean food web, Pygoscelis penguins serve as an important window into the larger marine ecosystem, but the patchiness and heterogeneity of the census data available have made it difficult to assess trends in a policy-accessible way. Here we introduce a Pygoscelis penguin-specific biodiversity index, the ‘Penguindex,’ using the framework of the Living Planet Index (LPI), distilling 40 year population trends of pygoscelid penguins for the first time into a single pan-Antarctic indicator for use by policymakers. We also calculate species- and region-specific indices from which discrete eras of population dynamics can be identified. These indices, similar to the LPI itself, do not provide estimates of changes in absolute abundance of species but, instead, reflect comparable population trends and the relative magnitude of these changes. We find that the Adélie Penguin (Pygoscelis adeliae) index was relatively stable across the Antarctic since 1980, with declines in regional indices across the Antarctic Peninsula region being contrasted by increases in regional indices for the Ross Sea and East Antarctica. The Chinstrap Penguin (Pygoscelis antarctica) index across the Antarctic declined by 61%. In stark contrast, the index for Gentoo Penguin (Pygoscelis papua) has increased seven-fold. Our analysis also identifies several marked eras of regional pygoscelid population change that may help identify key mechanistic drivers. We expect that the Penguindex will act as a useful reference tool for policymakers and hope that, by following this example, other taxonomic groups in the Antarctic might be tracked using the Living Planet Index framework. Importantly, our development of the Penguindex should facilitate the much-needed integration of Antarctic data into global biodiversity monitoring.

Fin whales Balaenoptera physalus were hunted unsustainably across the globe in the 19th and 20th centuries, leading to vast reductions in population size. Whaling catch records indicate the importance of the Southern Ocean for this species; approximately 730,000 fin whales were harvested during the 20th century in the Southern Hemisphere (SH) alone, 94% of which were at high latitudes. Genetic samples from contemporary whales can provide a window to past population size changes, but the challenges of sampling in remote Antarctic waters limit the availability of data. Here, we take advantage of historical samples in the form of bones and baleen available from ex-whaling stations and museums to assess the pre-whaling diversity of this once abundant species. We sequenced 27 historical mitogenomes and 50 historical mitochondrial control region sequences of fin whales to gain insight into the population structure and genetic diversity of Southern Hemisphere fin whales (SHFWs) before and after the whaling. Our data, both independently and when combined with mitogenomes from the literature, suggest SHFWs are highly diverse and may represent a single panmictic population that is genetically differentiated from Northern Hemisphere populations. These are the first historic mitogenomes available for SHFWs, providing a unique time series of genetic data for this species.