FitzPatrick Institute of African Ornithology

Zooplankton forms a key trophic interface in Arctic marine ecosystems, transferring both nutritional resources and contaminants to higher consumers. Yet these dimensions are rarely evaluated together in the prey actually selected and delivered by predators under natural foraging conditions. We used little auks ( Alle alle ) as biological samplers of realized chick-provisioning diets and analysed 138 food loads collected across eight colony-by-year domains at six colonies in Greenland and Svalbard during 2022–2023. We quantified methylmercury (MeHg), total mercury (THg), carotenoids, molar carbon-to‑nitrogen (C:N) ratio, stable carbon and nitrogen isotopes, and taxonomic composition. We also combined standardized carotenoid, molar C:N ratio and MeHg measurements into a dataset-relative Nutrition–Toxicity Trade-off (NTT) score describing their joint configuration within individual diets. Diet chemistry differed markedly among the sampled domains, with particularly pronounced differences in MeHg, molar C:N and stable-isotope values. The component profiles showed that nutritional proxies and MeHg exposure did not necessarily covary: similar relative NTT scores could arise from different combinations of carotenoids, molar C:N and MeHg. Taxon-specific composites further showed that THg did not consistently track either MeHg concentration or the MeHg fraction and that these MeHg characteristics varied among locations within the same prey taxon and developmental stage. An exploratory domain-level analysis further showed a negative association between median dietary MeHg and sea-surface salinity. Where corresponding samples were available, variation in adult blood THg and astaxanthin broadly paralleled patterns observed in chick-provisioning diets. These results show substantial variation in the chemical characteristics of predator-selected zooplankton across contemporary Greenland and Svalbard foraging domains and demonstrate the value of jointly considering nutritional proxies and contaminant exposure when characterizing realized trophic conditions.

For millennia, human activities have transformed ecosystems globally. Determining which landscapes are predominantly anthropogenic is crucial to conservation and habitat restoration. Madagascar, a critically-threatened biodiversity hotspot, is a prominent example. Currently 80% of non-cropland habitat is tree-limited savanna falling under the tropical grassy biome (savanna/TGB). Savanna/TGB is particularly prevalent in the Dry Deciduous Forest (DDF) in the north/northwest and below the treeline in the Central Highlands (CH). Relative savanna/TGB cover when agropastoralism arrived <1300 years ago (ya) has been intensely debated. Two competing hypotheses have emerged. The Mixed Mosaic Perspective argues current savanna/TGB is mostly anthropogenic, and differs from endemic, tree-rich savannas, because it has been produced by frequent agropastoralist fires, grazing by 7-10 million zebu cattle, and habitat clearance. These novel disturbances replaced a mosaic of savanna/TGB, comprised of C3 and C4 graminoids (both grasses and sedges), forest, heathland and wetland, with non-endemic fire- and grazing-adapted pantropical C4 grasses. This perspective is founded on multiple lines of evidence: >90% of endemic vertebrates are forest-adapted, Malagasy people named many locations currently in savanna/TGB after forest, and only 1000 ya, abundant tree-adapted fauna with predominantly C3 diets inhabited the CH and DDF. The Vast Grassland Perspective (VGP) contends that late Holocene aridity favoured vast savanna/TGB, and that cattle and human-lit fires maintain savanna/TGB previously grazed by now-extinct megafauna. This view contends that ecological models predict 'treeless grassland' across the CH and DDF, with savanna/TGB woodland naturally limited to <5%, and it questions palaeoecological evidence as spatially-limited. Clarifying which viewpoint is correct is fundamental to conservation; if human-lit fires and cattle grazing are not surrogates for past ecological processes, they may be detrimental to ecosystem function. We address this debate by applying ecological models that predict grassy habitat likelihood based on precipitation, and, for the first time, map these likelihoods across the entire CH and DDF. We review all available literature and apply novel interpolations of palaeo-data to highlight existing spatial coverage and broad spatiotemporal trends. We then assess if predicted habitats from our ecological models concur with reconstructed habitat at the onset of pastoralism. Ecological models align with palaeo-data at >90% of sites but diverge markedly from current conditions. Today, savanna/TGB is three to seventimesmore extensive than predicted, with >183,000 km2 less forest than models suggest should exist, given current precipitation. Multiple lines of evidence indicate widespread anthropogenic transformation started with the arrival of agropastoralism ~1300 ya, and began shifting biomes to tree-limited savanna by ~1100-1000 ya. Charcoal records show increased fire activity preceded decline of forest, tree-rich savanna woodlands, heathland, and populations of large, now-extinct, endemic vertebrates. Paradoxically, this happened when DDF climate was relatively wet, which should have promoted, not reduced, forest, and limited fire. Expansion of savanna/TGB dominated by C4 grasses followed the increase in fire coinciding with the onset of pastoralism. In the context of a biome transition that is still unfolding, we present a critical pre-agropastoralist baseline that can guide ecological restoration efforts to reinstate lost ecological functions and preserve Madagascar's remaining extraordinary endemic biota.

Human activities and their impacts are a major source of mortality for wide-ranging animals, yet conservation efforts often remain reactive because it is difficult to predict where mortality is most likely to occur. Approaches to understand and reduce wildlife mortality typically rely on coarse-scale associations between mortality events and landscape features, limiting their ability to identify spatially concentrated high-risk areas and prioritise effective mitigation. We contend that mortality risk arises from interactions between animal space use and human-modified environments, where movements result in spatial overlap with anthropogenic threats. Here, we outline the Movement–Mortality Framework (MMF), a conceptual framework with practical implications that integrates movement ecology, predictive space-use modelling, and spatial threat mapping to predict where anthropogenic mortality is most likely to occur. The MMF combines predicted space use with spatial threat distributions to estimate exposure, identify mortality hotspots and prioritise targeted conservation interventions. We demonstrate this approach using a worked example for the globally Vulnerable Cape Vulture (Gyps coprotheres) in South Africa. Predicted exposure was highly spatially concentrated: the highest-risk 1% of the landscape contained 41% and 43% of predicted exposure to powerline collision/electrocution and unintentional poisoning, respectively, while the highest-risk 10% contained 78% and 76%. By linking predictive movement models with spatial threat mapping, the MMF provides a transferable framework for identifying mortality hotspots, supporting evidence-based conservation planning and prioritising targeted mitigation for wide-ranging animals facing anthropogenic threats. Practical implication: The MMF provides practitioners with a transferable approach for combining animal space-use predictions with spatial information on anthropogenic threats to identify priority areas for intervention. By targeting locations containing disproportionate levels of predicted exposure, conservation resources can be directed towards areas where mitigation has the greatest potential to reduce anthropogenic mortality.

A new subspecies of Cape Verde Storm Petrel Hydrobates jabejabe, previously considered endemic to the Cape Verde Islands, is described from São Tomé Island, Gulf of Guinea. The formal description is based on evidence gathered from the literature, museums and fieldwork in and around São Tomé; namely, from four specimens collected in 1928, one bird trapped offshore in 1997, six birds captured at a palm oil factory in 2023, and digital images taken of several hundred birds at sea off São Tomé in 2023 and farther out in the Gulf of Guinea in 2011. São Tomé Storm Petrels were found to differ from H. jabejabe by bill shape (relatively long, slender, downcurved), plumage (extremely narrow white rump band in many individuals) and breeding ecology (presumed nesting at high elevation in tropical forest vs flat or sloped rocky areas near the sea). In a phylogenetic analysis using mtDNA control region, São Tomé Storm Petrels clustered within H. jabejabe, with the two not being reciprocally monophyletic. However, the unique haplotypes of the six individuals analysed from São Tomé, not found among 34 haplotypes from 58 individuals of hot- and cool-season breeders from Cape Verde, might indicate a lack of recent maternal gene flow. Integration of these multiple lines of evidence shows that, despite varying degrees of support, the São Tomé Storm Petrel is distinctive enough to be treated as a separate taxon. It is not sufficiently differentiated to warrant species-level status, so we treat it as a subspecies of H. jabejabe. Procellaria lugubris Bonaparte, 1845, a valid and available name whose holotype originates from the South Atlantic, could not be confirmed to refer to the São Tomé Storm Petrel.

The Roseate Tern Sterna dougallii is a locally threatened seabird that breeds in four discrete metapopulations across the Atlantic Ocean Basin: Northwest Atlantic, Caribbean, Azores and Northwest Europe. While this species is well‐monitored and the focus of long‐term management efforts across the breeding distribution, significant knowledge gaps remain for the Northwest Europe and Azores metapopulations with regard to genetic diversity, population structure and connectivity outside the breeding season. Here, we address this gap by leveraging data collected as part of a long‐term mist‐netting programme in Senegal, West Africa. We genotyped 240 individuals sampled during the northward migration in 2021–2023, including 112 ringed or resighted in breeding colonies. We used a panel of 15 microsatellite loci to investigate genetic diversity and population structure for birds of known origin (determined by location of ringing or resighting), and compared them to individuals sampled from a site in the Northwest Atlantic. We found relatively low genetic diversity indices within the Northwest Europe and Azores metapopulations, consistent with previous reports from the Caribbean, Azores and Northwest Atlantic metapopulations. We found no significant genetic differentiation among sites within Northwest Europe, consistent with metapopulation modelling studies. Significant differentiation was detected among the Northwest Europe, Azores and Northwest Atlantic metapopulations. We used discriminant analysis of principal components to assign 79% of individuals of unknown origin to the Azores or Northwest Europe metapopulations with ≥ 80% probability, while no birds were assigned to the Northwest Atlantic metapopulation. These results contribute the first comprehensive documentation of the genetic diversity of Roseate Terns utilizing the East Atlantic Flyway and the Northwest Europe metapopulation, document gene flow within Northwest Europe and demonstrate the value of sampling birds during migration for population genetic studies.

Despite increasing efforts to diversify the field of animal behaviour, systemic barriers continue to limit access and inclusion for researchers from historically underrepresented and underfunded backgrounds. These persistent inequities result in unequal opportunities for participation and advancement. The Animal Behaviour Collective (ABC) is a volunteer-led initiative that works to address the financial and structural barriers faced by students and early-career researchers in the discipline. Since its inception in 2020, ABC has distributed £23 261 in microgrants to 126 recipients to cover essential expenses often overlooked by traditional funding sources and has offered mentorship to 121 students and researchers across the globe. By prioritizing people over projects, ABC fosters inclusive participation and strives for lasting structural change within the field of animal behaviour. In this paper, we outline the motivations behind ABC's founding, chart its development and share key resources and insights gained along the way. In doing so, we hope this paper and these resources can serve as both a practical guide and a source of inspiration for others working to advance equity, diversity and inclusion in science.

Abstract Energy is fundamental for life and accurately predicting animals' energy expenditure under changing environments is central to ecology and global change biology. Energy expenditure in free‐living animals can be directly quantified using the doubly labelled water (DLW) technique or estimated by extrapolating respirometric measurements of metabolic rates or modelled using biophysical principles. However, the accuracy of these latter approaches depends on data quality and model parameterisation. We evaluated respirometry extrapolations and biophysical models for estimating daily energy expenditure (DEE) in a free‐living bird, the Southern Pied Babbler ( Turdoides bicolor ) against DLW measurements. Respirometry extrapolations and biophysical models were parameterised using: (a) assumed animal behaviour and assumed operative temperature ( T e ), (b) assumed animal behaviour and measured T e , (c) fine scale (focal) observations of behaviour under natural conditions and measured T e , or (d) coarse scale (scan) behaviour observations and measured T e . We then quantified the minimum field‐collected data needed to accurately predict measured DEE across a range of daily maximum air temperatures ( T air ). Models parameterised with assumed behaviours and T e failed to predict DEE with 95% confidence across all T air values. Biophysical models using focal observations and measured T e closely matched DLW measurements (within 94.1%–95.3% of measured DEE), while scan observations reduced accuracy (within 81.7%–88.1% of measured DEE). Respirometry extrapolations using focal or scan observations and measured T e predicted DEE within 82.1%–88.9% and 69.0%–87.1% of observed values, respectively. Varying behavioural data inputs showed that improving the accuracy of DEE predictions does not require exhaustive sampling. A targeted approach prioritising behavioural observations and T e measurements across representative T air can minimise effort in the field, while maintaining model accuracy. Biophysical models, increasingly used to predict species interactions, distributions, survival and fitness under environmental change, must be biologically relevant, well‐informed and accurate to reliably inform ecological and conservation research. Read the free Plain Language Summary for this article on the Journal blog.