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In the mammalian model of sex determination, embryos are considered to be sexually indifferent until the transient action of a sex-determining gene initiates gonadal differentiation. Although this model is thought to apply to all vertebrates, this has yet to be established. Here we have examined three lateral gynandromorph chickens (a rare, naturally occurring phenomenon in which one side of the animal appears male and the other female) to investigate the sex-determining mechanism in birds. These studies demonstrated that gynandromorph birds are genuine male:female chimaeras, and indicated that male and female avian somatic cells may have an inherent sex identity. To test this hypothesis, we transplanted presumptive mesoderm between embryos of reciprocal sexes to generate embryos containing male:female chimaeric gonads. In contrast to the outcome for mammalian mixed-sex chimaeras, in chicken mixed-sex chimaeras the donor cells were excluded from the functional structures of the host gonad. In an example where female tissue was transplanted into a male host, donor cells contributing to the developing testis retained a female identity and expressed a marker of female function. Our study demonstrates that avian somatic cells possess an inherent sex identity and that, in birds, sexual differentiation is substantively cell autonomous.

Assessing the vulnerability of low-lying coral reef islands is a global concern due to predictions that climate and environmental change will increase reef island instability and cause reef island populations to be among the first environmental refugees. Reef islands in the Pacific and Indian Oceans are highly dynamic environments that morphologically adjust to changing environmental conditions over annual-decadal timescales. However, there is a paucity of reef island shoreline change data from the Caribbean where sea-level rise, ecological and environmental disturbance and hydrodynamic regimes are considerably different than in other oceans globally. Here we present shoreline change analysis of 16 reef islands in northern Honduras, at the southern end of the Mesoamerican Barrier Reef. Satellite imagery from a maximum period of 12.4 years from Utila (2006–2019), and 2.4 years from Cayos Cochinos (2018–2021) was analysed to quantify island shoreline change and planform morphological adjustments. We identified accretion as the dominant island behaviour in Utila, where 5 of 7 islands increased in area and 61.7% of shorelines accreted, contributing to an overall net area increase of 9.4%. Island behaviour was more variable in Cayos Cochinos, where 55.7% of shorelines eroded, 5 of 9 islands remained stable, and net island area change was insignificant (2%). Conversely, the 4 smallest Cayos Cochinos islands (all <1500 m2) experienced significant shoreline change, potentially highlighting a new size threshold for considering reef island evolution. Across both sites, reef islands demonstrated a range of modes of planform change, including lateral accretion and erosion, and migration. Consequently, we provide the first empirical evidence of the dynamic nature of Caribbean reef islands during a period coincident with sea-level rise and highlight the heterogeneous nature of reef island evolution between and within two neighbouring sites at timescales relevant for island adaptation efforts.

Constructing activity budgets for marine animals when they are at sea and cannot be directly observed is challenging, but recent advances in bio-logging technology offer solutions to this problem. Accelerometers can potentially identify a wide range of behaviours for animals based on unique patterns of acceleration. However, when analysing data derived from accelerometers, there are many statistical techniques available which when applied to different data sets produce different classification accuracies. We investigated a selection of supervised machine learning methods for interpreting behavioural data from captive otariids (fur seals and sea lions). We conducted controlled experiments with 12 seals, where their behaviours were filmed while they were wearing 3-axis accelerometers. From video we identified 26 behaviours that could be grouped into one of four categories (foraging, resting, travelling and grooming) representing key behaviour states for wild seals. We used data from 10 seals to train four predictive classification models: stochastic gradient boosting (GBM), random forests, support vector machine using four different kernels and a baseline model: penalised logistic regression. We then took the best parameters from each model and cross-validated the results on the two seals unseen so far. We also investigated the influence of feature statistics (describing some characteristic of the seal), testing the models both with and without these. Cross-validation accuracies were lower than training accuracy, but the SVM with a polynomial kernel was still able to classify seal behaviour with high accuracy (>70%). Adding feature statistics improved accuracies across all models tested. Most categories of behaviour -resting, grooming and feeding-were all predicted with reasonable accuracy (52-81%) by the SVM while travelling was poorly categorised (31-41%). These results show that model selection is important when classifying behaviour and that by using animal characteristics we can strengthen the overall accuracy.

During wild foraging, Australian fur seals (Arctocephalus pusillus doriferus) encounter many different types of prey in a wide range of scenarios, yet in captive environments they are typically provided with a narrower range of opportunities to display their full repertoire of behaviours. This study aimed to quantitatively explore the effect of foraging-based enrichment on the behaviour and activity patterns displayed by two captive Australian fur seals at Melbourne Zoo, Australia. Food was presented as a scatter in open water, in a free-floating ball device, or in a static box device, with each treatment separated by control trials with no enrichment. Both subjects spent more time interacting with the ball and static box devices than the scatter feed. The total time spent pattern swimming was reduced in the enrichment treatments compared to the controls, while the time spent performing random swimming behaviours increased. There was also a significant increase in the total number of bouts of behaviour performed in all three enrichment treatments compared to controls. Each enrichment method also promoted a different suit of foraging behaviours. Hence, rather than choosing one method, the most effective way to increase the diversity of foraging behaviours, while also increasing variation in general activity patterns, is to provide seals with a wide range of foraging scenarios where food is encountered in different ways.

Teeth are the primary tool used by most mammals to capture and process food. Over the lifetime of an individual, they progressively wear through contact with each other (attrition) and with food (abrasion), creating distinctive patterns that reflect function and diet. Unlike their terrestrial cousins, many marine mammals capture prey via suction, which so far has not been associated with a specific wear pattern. Here, we describe two new types of tooth wear across 18 species of modern marine mammal (beaked whales, belugas, killer whales, globicephalines, and various seals) that likely stem from this behaviour: “glossowear”, which primarily affects the lingual side of the crown and plausibly records piston-like tongue movements during suction feeding; and “hydrowear”, which wraps around the sides of the crown and occurs as water is expelled from the mouth. Both wear types differ from attrition and biting-related abrasion in their surface characteristics and location on the crown. Horizontal scratches suggest a physical wear process, rather than dental erosion (acid corrosion) and tooth abfraction (microfracture). Since suction specifically exploits the liquid properties of water, physical evidence of this behaviour may help to elucidate marine mammal feeding ecology and evolution. For example, glossowear is found in the toothed ancestors of baleen whales (mammalodontids, at least one aetiocetid, and likely Mystacodon ), where it suggests an important role for suction in the emergence of filter feeding. By contrast, it is absent in most long-snouted toothed whales and dolphins, indicating that these animals mostly bite, rather than suck in, their prey.

Changes in penguin populations on the Antarctic Peninsula have been linked to several environmental factors, but the potentially devastating impact of volcanic activity has not been considered. Here we use detailed biogeochemical analyses to track past penguin colony change over the last 8,500 years on Ardley Island, home to one of the Antarctic Peninsula’s largest breeding populations of gentoo penguins. The first sustained penguin colony was established on Ardley Island c. 6,700 years ago, pre-dating sub-fossil evidence of Peninsula-wide occupation by c. 1,000 years. The colony experienced five population maxima during the Holocene. Overall, we find no consistent relationships with local-regional atmospheric and ocean temperatures or sea-ice conditions, although the colony population maximum, c. 4,000–3,000 years ago, corresponds with regionally elevated temperatures. Instead, at least three of the five phases of penguin colony expansion were abruptly ended by large eruptions from the Deception Island volcano, resulting in near-complete local extinction of the colony, with, on average, 400–800 years required for sustainable recovery. Changes in penguin populations on the Antarctic Peninsula in recent decades have been linked to environmental factors such as sea ice. Here, the authors show that penguin colony change on Ardley Island, NW Antarctic Peninsula during the last 8,500 years was primarily driven by volcanic activity.

Drones have become popular with the general public for viewing and filming marine life. One amateur enthusiast platform, DroneSharkApp, films marine life in the waters off Sydney, Australia year-round and posts their observations on social media. The drone observations include the behaviours of a variety of coastal marine wildlife species, including sharks, rays, fur seals, dolphins and fish, as well as migratory species such as migrating humpback whales. Given the extensive effort and multiple recordings of the presence, behaviour and interactions of various species with humans provided by DroneSharkApp, we explored its utility for providing biologically meaningful observations of marine wildlife. Using social media posts from the DroneSharkApp Instagram page, a total of 678 wildlife videos were assessed from 432 days of observation collected by a single observer. This included 94 feeding behaviours or events for fur seals (n = 58) and dolphins (n = 33), two feeding events for white sharks and one feeding event for a humpback whale. DroneSharkApp documented 101 interactions with sharks and humans (swimmers and surfers), demonstrating the frequent, mainly innocuous human–shark overlap off some of Australia’s busiest beaches. Finally, DroneSharkApp provided multiple observations of humpback and dwarf minke whales with calves travelling north, indicating calving occurring well south of traditional northern Queensland breeding waters. Collaboration between scientists and citizen scientists such as those involved with DroneSharkApp can greatly and quantitatively increase the biological understanding of marine wildlife data.

Background Campylobacter is the leading cause of foodborne diarrhoeal illness in humans and is mostly acquired from consumption or handling of contaminated poultry meat. In the absence of effective licensed vaccines and inhibitors, selection for chickens with increased resistance to Campylobacter could potentially reduce its subsequent entry into the food chain. Campylobacter intestinal colonisation levels are influenced by the host genetics of the chicken. In the present study, two chicken populations were used to investigate the genetic architecture of avian resistance to colonisation: (i) a back-cross of two White Leghorn derived inbred lines [(6 1 x N) x N] known to differ in resistance to Campylobacter colonisation and (ii) a 9 th generation advanced intercross (6 1 x N) line. Results The level of colonisation with Campylobacter jejuni following experimental infection was found to be a quantitative trait. A back-cross experiment using 1,243 fully informative single nucleotide polymorphism (SNP) markers revealed quantitative trait loci (QTL) on chromosomes 7, 11 and 14. In the advanced intercross line study, the location of the QTL on chromosome 14 was confirmed and refined and two new QTLs were identified located on chromosomes 4 and 16. Pathway and re-sequencing data analysis of the genes located in the QTL candidate regions identified potential pathways, networks and candidate resistance genes. Finally, gene expression analyses were performed for some of the candidate resistance genes to support the results. Conclusion Campylobacter resistance in chickens is a complex trait, possibly involving the Major Histocompatibility Complex, innate and adaptive immune responses, cadherins and other factors. Two of the QTLs for Campylobacter resistance are co-located with Salmonella resistance loci, indicating that it may be possible to breed simultaneously for enhanced resistance to both zoonoses.

Background A major goal of evolutionary developmental biology is to discover general models and mechanisms that create the phenotypes of organisms. However, universal models of such fundamental growth and form are rare, presumably due to the limited number of physical laws and biological processes that influence growth. One such model is the logarithmic spiral, which has been purported to explain the growth of biological structures such as teeth, claws, horns, and beaks. However, the logarithmic spiral only describes the path of the structure through space, and cannot generate these shapes. Results Here we show a new universal model based on a power law between the radius of the structure and its length, which generates a shape called a ‘power cone’. We describe the underlying ‘power cascade’ model that explains the extreme diversity of tooth shapes in vertebrates, including humans, mammoths, sabre-toothed cats, tyrannosaurs and giant megalodon sharks. This model can be used to predict the age of mammals with ever-growing teeth, including elephants and rodents. We view this as the third general model of tooth development, along with the patterning cascade model for cusp number and spacing, and the inhibitory cascade model that predicts relative tooth size. Beyond the dentition, this new model also describes the growth of claws, horns, antlers and beaks of vertebrates, as well as the fangs and shells of invertebrates, and thorns and prickles of plants. Conclusions The power cone is generated when the radial power growth rate is unequal to the length power growth rate. The power cascade model operates independently of the logarithmic spiral and is present throughout diverse biological systems. The power cascade provides a mechanistic basis for the generation of these pointed structures across the tree of life.

Foraging behaviours used by two female Australian fur seals (Arctocephalus pusillus doriferus) were documented during controlled feeding trials. During these trials the seals were presented with prey either free-floating in open water or concealed within a mobile ball or a static box feeding device. When targeting free-floating prey both subjects primarily used raptorial biting in combination with suction, which was used to draw prey to within range of the teeth. When targeting prey concealed within either the mobile or static feeding device, the seals were able to use suction to draw out prey items that could not be reached by biting. Suction was followed by lateral water expulsion, where water drawn into the mouth along with the prey item was purged via the sides of the mouth. Vibrissae were used to explore the surface of the feeding devices, especially when locating the openings in which the prey items had been hidden. The mobile ball device was also manipulated by pushing it with the muzzle to knock out concealed prey, which was not possible when using the static feeding device. To knock prey out of this static device one seal used targeted bubble blowing, where a focused stream of bubbles was blown out of the nose into the openings in the device. Once captured in the jaws, prey items were manipulated and re-oriented using further mouth movements or chews so that they could be swallowed head first. While most items were swallowed whole underwater, some were instead taken to the surface and held in the teeth, while being vigorously shaken to break them into smaller pieces before swallowing. The behavioural flexibility displayed by Australian fur seals likely assists in capturing and consuming the extremely wide range of prey types that are targeted in the wild, during both benthic and epipelagic foraging.