Estimated mortality of the highly pathogenic avian influenza pandemic on northern gannets (Morus bassanus) in southwest Ireland.

The 2022 highly pathogenic avian influenza (HPAI) outbreak that occurred in many European countries affected several seabird species. Among them, northern gannets (Morus bassanus) were particularly impacted. We conducted aerial surveys in waters around the two largest gannet colonies in southwest Ireland (Little Skellig and Bull Rock, together representing 87% of the national population) in September 2022. During surveys dead and alive northern gannets were counted on survey effort. A total of 184 dead gannets were recorded on survey effort, representing 3.74% of the total number of gannets recorded. We estimated the abundance of dead gannets in the surveyed area at 1526 (95% confidence intervals (CIs) 1450-1605) individuals. The percentage of dead gannets observed was used to estimate a minimum local population mortality of 3126 (95% CIs 2993-3260) individuals across both colonies. Aerial surveys provided key information on gannet mortality from HPAI at sea. The study provides the first estimate of gannet mortality in the two largest gannetries in Ireland.

Handedness and individual roll-angle specialism when plunge diving in the northern gannet.

Many vertebrates show lateralized behaviour, or handedness, where an individual preferentially uses one side of the body more than the other. This is generally thought to be caused by brain lateralization and allows functional specializations such as sight, locomotion, and decision-making among other things. We deployed accelerometers on 51 northern gannets, Morus bassanus, to test for behavioural lateralization during plunge dives. When plunge diving, gannets 'roll' to one side, and standard indices indicated that 51% of individuals were left-sided, 43% right-sided, and 6% 'non-lateralized'. Lateralization indices provide no measure of error and do not account for environmental covariance, so we conducted two repeatability analyses on individuals' dive roll direction and angle. Dive side lateralization was highly repeatable among individuals over time at the population level (R = 0.878, p < 0.001). Furthermore, roll angle was also highly repeatable in individuals (R = 0.751, p < 0.001) even after controlling for lateralized state. Gannets show individual specializations in two different parts of the plunge diving process when attempting to catch prey. This is the first demonstration of lateralization during prey capture in a foraging seabird. It is also one of the few demonstrations of behavioural lateralization in a mixed model approach, providing a structure for further exploring behavioural lateralization.

A general deep learning model for bird detection in high-resolution airborne imagery.

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it requires large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increases these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.

Meeting Paris agreement objectives will temper seabird winter distribution shifts in the North Atlantic Ocean.

We explored the implications of reaching the Paris Agreement Objective of limiting global warming to <2°C for the future winter distribution of the North Atlantic seabird community. We predicted and quantified current and future winter habitats of five North Atlantic Ocean seabird species (Alle alle, Fratercula arctica, Uria aalge, Uria lomvia and Rissa tridactyla) using tracking data for ~1500 individuals through resource selection functions based on mechanistic modeling of seabird energy requirements, and a dynamic bioclimate envelope model of seabird prey. Future winter distributions were predicted to shift with climate change, especially when global warming exceed 2°C under a "no mitigation" scenario, modifying seabird wintering hotspots in the North Atlantic Ocean. Our findings suggest that meeting Paris agreement objectives will limit changes in seabird selected habitat location and size in the North Atlantic Ocean during the 21st century. We thereby provide key information for the design of adaptive marine-protected areas in a changing ocean.

Tidal drift removes the need for area-restricted search in foraging Atlantic puffins.

Understanding how animals forage is a central objective in ecology. Theory suggests that where food is uniformly distributed, Brownian movement ensures the maximum prey encounter rate, but when prey is patchy, the optimal strategy resembles a Lévy walk where area-restricted search (ARS) is interspersed with commuting between prey patches. Such movement appears ubiquitous in high trophic-level marine predators. Here, we report foraging and diving behaviour in a seabird with a high cost of flight, the Atlantic puffin ( Fratercula arctica), and report a clear lack of Brownian or Levy flight and associated ARS. Instead, puffins foraged using tides to transport them through their feeding grounds. Energetic models suggest the cost of foraging trips using the drift strategy is 28-46% less than flying between patches. We suggest such alternative movement strategies are habitat-specific, but likely to be far more widespread than currently thought.

Seismic Survey Footprints in Irish Waters: A Starting Point for Effective Mitigation.

The noise footprint of a given activity is defined as the area where the noise from the activity spreads into the ocean at levels above the existing statistical ambient noise. The noise footprints of seismic surveys in Irish waters from 2,000 to 2,011 have been estimated using Quonops, a global ocean noise prediction service. Noise footprints are converted into sound exposure levels to evaluate the cumulative risks toward high-, mid-, and low-frequency marine mammals. The results demonstrate large variability in risk areas as a function of existing ambient-noise levels, season, survey location, and characteristics of the survey.

What the F-POD? Comparing the F-POD and C-POD for monitoring of harbor porpoise (Phocoena phocoena).

Passive acoustic monitoring (PAM) is a cost-effective method for monitoring cetacean populations compared with techniques such as aerial and ship-based surveys. The Cetacean POrpoise Detector (C-POD) has become an integral tool in monitoring programs globally for over a decade, providing standardized metrics of occurrence that can be compared across time and space. However, the phasing out of C-PODs following the development of the new Full waveform capture POD (F-POD) with increased sensitivity, improved train detection, and reduced false-positive rates represents an important methodological change in data collection, particularly when being introduced into existing monitoring programs. Here, we compare the performance of the C-POD with that of its successor, the F-POD, co-deployed in a field setting for 15 months, to monitor harbor porpoise (Phocoena phocoena). While similar temporal trends in detections were found for both devices, the C-POD detected only 58% of the detection-positive minutes (DPM), recorded by the F-POD. Differences in detection rates were not consistent through time making it difficult to apply a correction factor or directly compare results obtained from the two PODs. Generalized additive models (GAMs) were used to test whether these differences in detection rates would have an effect on analyses of temporal patterns and environmental drivers of occurrence. No differences were found in seasonal patterns or the environmental correlates of porpoise occurrence (month, diel period, temperature, environmental noise, and tide). However, the C-POD failed to detect sufficient foraging rates to identify temporal patterns in foraging behavior, which were shown by the F-POD. Our results suggest that the switch to F-PODs will have little effect on determining broad-scale seasonal patterns of occurrence but may improve our understanding of fine-scale behaviors such as foraging. We highlight how care must be taken interpreting F-POD results as indicative of increased occurrence when used in time-series analysis.

Decadal increase in vessel interactions by a scavenging pelagic seabird across the North Atlantic.

Fisheries waste is used by many seabirds as a supplementary source of food,1 but interacting with fishing vessels to obtain this resource puts birds at risk of entanglement in fishing gear and mortality.2 As a result, bycatch is one of the leading contributors to seabird decline worldwide,3 and this risk may increase over time as birds increasingly associate fishing vessels with food. Light-level geolocators mounted on seabirds can detect light emitted from vessels at night year-round.4 We used a 16-year time series of geolocator data from 296 northern fulmars (Fulmarus glacialis) breeding at temperate and arctic colonies to investigate trends of nocturnal vessel interactions in this scavenging pelagic seabird. Vessel attendance has progressively increased over the study period despite no corresponding increase in the number of vessels or availability of discards over the same time frame. Fulmars are highly mobile generalist surface feeders,5 so this may signal a reduction in available prey biomass in the upper water column, leading to increased reliance on anthropogenic food subsidies6 and increased risk of bycatch mortality in already threatened seabird populations. Individuals were consistent in the extent to which they interacted with vessels, as shown in other species,7 suggesting that population-level increases may be due to a higher proportion of fulmars following vessels rather than changes at an individual level. Higher encounter rates were correlated with lower time spent foraging and a geographically restricted overwintering distribution, suggesting an energetic advantage for these scavenging strategists compared with foraging for natural prey.

A bioenergetics approach to understanding sex differences in the foraging behaviour of a sexually monomorphic species.

Many animals show sexually divergent foraging behaviours reflecting different physiological constraints or energetic needs. We used a bioenergetics approach to examine sex differences in foraging behaviour of the sexually monomorphic northern gannet. We derived a relationship between dynamic body acceleration and energy expenditure to quantify the energetic cost of prey capture attempts (plunge dives). Fourteen gannets were tracked using GPS, time depth recorders (TDR) and accelerometers. All plunge dives in a foraging trip represented less than 4% of total energy expenditure, with no significant sex differences in expenditure. Despite females undertaking significantly more dives than males, this low energetic cost resulted in no sex differences in overall energy expenditure across a foraging trip. Bayesian stable isotope mixing models based on blood samples highlighted sex differences in diet; however, calorific intake from successful prey capture was estimated to be similar between sexes. Females experienced 10.28% higher energy demands, primarily due to unequal chick provisioning. Estimates show a minimum of 19% of dives have to be successful for females to meet their daily energy requirements, and 26% for males. Our analyses suggest northern gannets show sex differences in foraging behaviour primarily related to dive rate and success rather than the energetic cost of foraging or energetic content of prey.

A new biologging approach reveals unique flightless molt strategies of Atlantic puffins.

Animal-borne telemetry devices provide essential insights into the life-history strategies of far-ranging species and allow us to understand how they interact with their environment. Many species in the seabird family Alcidae undergo a synchronous molt of all primary flight feathers during the non-breeding season, making them flightless and more susceptible to environmental stressors, including severe storms and prey shortages. However, the timing and location of molt remain largely unknown, with most information coming from studies on birds killed by storms or shot by hunters for food. Using light-level geolocators with saltwater immersion loggers, we develop a method for determining flightless periods in the context of the annual cycle. Four Atlantic puffins (Fratercula arctica) were equipped with geolocator/immersion loggers on each leg to attempt to overcome issues of leg tucking in plumage while sitting on the water, which confounds the interpretation of logger data. Light-level and saltwater immersion time-series data were combined to correct for this issue. This approach was adapted and applied to 40 puffins equipped with the standard practice deployments of geolocators on one leg only. Flightless periods consistent with molt were identified in the dual-equipped birds, whereas molt identification in single-equipped birds was less effective and definitive and should be treated with caution. Within the dual-equipped sample, we present evidence for two flightless molt periods per non-breeding season in two puffins that undertook more extensive migrations (>2000 km) and were flightless for up to 77 days in a single non-breeding season. A biannual flight feather molt is highly unusual among non-passerine birds and may be unique to birds that undergo catastrophic molt, i.e., become flightless when molting. Although our conclusions are based on a small sample, we have established a freely available methodological framework for future investigation of the molt patterns of this and other seabird species.

The role of wingbeat frequency and amplitude in flight power.

Body-mounted accelerometers provide a new prospect for estimating power use in flying birds, as the signal varies with the two major kinematic determinants of aerodynamic power: wingbeat frequency and amplitude. Yet wingbeat frequency is sometimes used as a proxy for power output in isolation. There is, therefore, a need to understand which kinematic parameter birds vary and whether this is predicted by flight mode (e.g. accelerating, ascending/descending flight), speed or morphology. We investigate this using high-frequency acceleration data from (i) 14 species flying in the wild, (ii) two species flying in controlled conditions in a wind tunnel and (iii) a review of experimental and field studies. While wingbeat frequency and amplitude were positively correlated, R2 values were generally low, supporting the idea that parameters can vary independently. Indeed, birds were more likely to modulate wingbeat amplitude for more energy-demanding flight modes, including climbing and take-off. Nonetheless, the striking variability, even within species and flight types, highlights the complexity of describing the kinematic relationships, which appear sensitive to both the biological and physical context. Notwithstanding this, acceleration metrics that incorporate both kinematic parameters should be more robust proxies for power than wingbeat frequency alone.

Fine-scale foraging habitat selection by two diving central place foragers in the Northeast Atlantic.

Habitat selection and spatial usage are important components of animal behavior influencing fitness and population dynamic. Understanding the animal-habitat relationship is crucial in ecology, particularly in developing strategies for wildlife management and conservation. As this relationship is governed by environmental features and intra- and interspecific interactions, habitat selection of a population may vary locally between its core and edges. This is particularly true for central place foragers such as gray and harbor seals, where, in the Northeast Atlantic, the availability of habitat and prey around colonies vary at local scale. Here, we study how foraging habitat selection may vary locally under the influence of physical habitat features. Using GPS/GSM tags deployed at different gray and harbor seals' colonies, we investigated spatial patterns and foraging habitat selection by comparing trip characteristics and home-range similarities and fitting GAMMs to seal foraging locations and environmental data. To highlight the importance of modeling habitat selection at local scale, we fitted individual models to colonies as well as a global model. The global model suffered from issues of homogenization, while colony models showed that foraging habitat selection differed markedly between regions for both species. Despite being capable of undertaking far-ranging trips, both gray and harbor seals selected their foraging habitat depending on local availability, mainly based on distance from the last haul-out and bathymetry. Distance from shore and tidal current also influenced habitat preferences. Results suggest that local conditions have a strong influence on population spatial ecology, highlighting the relevance of processes occurring at fine geographical scale consistent with management within regional units.

North Atlantic winter cyclones starve seabirds.

Each winter, the North Atlantic Ocean is the stage for numerous cyclones, the most severe ones leading to seabird mass-mortality events called "winter wrecks."1-3 During these, thousands of emaciated seabird carcasses are washed ashore along European and North American coasts. Winter cyclones can therefore shape seabird population dynamics4,5 by affecting survival rates as well as the body condition of surviving individuals and thus their future reproduction. However, most often the geographic origins of impacted seabirds and the causes of their deaths remain unclear.6 We performed the first ocean-basin scale assessment of cyclone exposure in a seabird community by coupling winter tracking data for ∼1,500 individuals of five key North Atlantic seabird species (Alle alle, Fratercula arctica, Uria aalge, Uria lomvia, and Rissa tridactyla) and cyclone locations. We then explored the energetic consequences of different cyclonic conditions using a mechanistic bioenergetics model7 and tested the hypothesis that cyclones dramatically increase seabird energy requirements. We demonstrated that cyclones of high intensity impacted birds from all studied species and breeding colonies during winter but especially those aggregating in the Labrador Sea, the Davis Strait, the surroundings of Iceland, and the Barents Sea. Our broad-scale analyses suggested that cyclonic conditions do not increase seabird energy requirements, implying that they die because of the unavailability of their prey and/or their inability to feed during cyclones. Our study provides essential information on seabird cyclone exposure in a context of marked cyclone regime changes due to global warming.8.

Spatial variation in a top marine predator's diet at two regionally distinct sites.

In ecological studies it is often assumed that predator foraging strategies and resource use are geographically and seasonally homogeneous, resulting in relatively static trophic relationships. However, certain centrally placed foragers (e.g. seals) often have terrestrial sites for breeding, resting, and moulting that are geographically distinct, and associated with different habitat types. Therefore, accurate estimations of predator diet at relevant spatial and temporal scales are key to understanding energetic requirements, predator-prey interactions and ecosystem structure. We investigate geographic variation in the diet of grey seals (Halichoerus grypus), a relatively abundant and widely distributed central place forager, to provide insights into geographic variation in resource use. Prey composition was identified using scat samples collected over concurrent timescales and a multivariate approach was used to analyse diet from two contrasting habitats. Regional differences in prey assemblages occurred within all years (2011-2013) and all seasons (ANOSIM, all p<0.05), apart from in winter. Telemetry data were used to identify core foraging areas and habitats most likely associated with scat samples collected at the two haul-out sites. Regional differences in the diet appear to reflect regional differences in the physical habitat features, with seals foraging in deeper waters over sandy substrates showing a higher prevalence of pelagic and bentho-pelagic prey species such as blue whiting and sandeels. Conversely, seals foraging in comparatively shallow waters had a greater contribution of demersal and groundfish species such as cephalopods and flatfish in their diet. We suggest that shallower waters enable seals to spend more time foraging along the benthos while remaining within aerobic dive limits, resulting in more benthic species in the diet. In contrast, the diet of seals hauled-out in areas adjacent to deeper waters indicates that either seals engage in a more pelagic foraging strategy, or that seals can spend less time at the benthos, resulting in comparatively more pelagic prey recovered in the diet. The substantial differences in prey assemblages over a small spatial scale (<300 km) demonstrates the importance of using regionally-specific diet information in ecosystem-based models to better account for different trophic interactions.

Sampling strategies for species with high breeding-site fidelity: A case study in burrow-nesting seabirds.

Sampling approaches used to census and monitor populations of flora and fauna are diverse, ranging from simple random sampling to complex hierarchal stratified designs. Usually the approach taken is determined by the spatial and temporal distribution of the study population, along with other characteristics of the focal species. Long-term monitoring programs used to assess seabird population trends are facilitated by their high site fidelity, but are often hampered by large and difficult to access colonies, with highly variable densities that require intensive survey. We aimed to determine the sampling effort required to (a) estimate population size with a high degree of confidence, and (b) detect different scenarios of population change in a regionally important species in the Atlantic, the Manx shearwater (Puffinus puffinus). Analyses were carried out using data collected from tape-playback surveys on four islands in the North Atlantic. To explore how sampling effort influenced confidence around abundance estimates, we used the heuristic approach of imagining the areas sampled represented the total population, and bootstrapped varying proportions of subsamples. This revealed that abundance estimates vary dramatically when less than half of all plots (n dependent on the size of the site) is randomly subsampled, leading to an unacceptable lack of confidence in population estimates. Confidence is substantially improved using a multi-stage stratified approach based on previous information on distribution in the colonies. In reality, this could lead to reducing the number of plots required by up to 80%. Furthermore, power analyses suggested that random selection of monitoring plots using a matched pairs approach generates little power to detect overall population changes of 10%, and density-dependent changes as large as 50%, because variation in density between plots is so high. Current monitoring programs have a high probability of failing to detect population-level changes due to inappropriate sampling efforts. Focusing sampling in areas of high density with low plot to plot variance dramatically increases the power to detect year to year population change, albeit at the risk of not detecting increases in low density areas, which may be an unavoidable strategy when resources are limited. We discuss how challenging populations with similar features to seabirds might be censused and monitored most effectively.

Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca).

There is worldwide concern about the status of elasmobranchs, primarily as a result of overfishing and bycatch with subsequent ecosystem effects following the removal of top predators. Whilst abundant and wide-ranging, blue sharks (Prionace glauca) are the most heavily exploited shark species having suffered marked declines over the past decades, and there is a call for robust abundance estimates. In this study, we utilized depth data collected from two blue sharks using pop-up satellite archival tags, and modelled the proportion of time the sharks were swimming in the top 1-meter layer and could therefore be detected by observers conducting aerial surveys. The availability models indicated that the tagged sharks preferred surface waters whilst swimming over the continental shelf and during daytime, with a model-predicted average proportion of time spent at the surface of 0.633 (SD = 0.094) for on-shelf, and 0.136 (SD = 0.075) for off-shelf. These predicted values were then used to account for availability bias in abundance estimates for the species over a large area in the Northeast Atlantic, derived through distance sampling using aerial survey data collected in 2015 and 2016 and modelled with density surface models. Further, we compared abundance estimates corrected with model-predicted availability to uncorrected estimates and to estimates that incorporated the average time the sharks were available for detection. The mean abundance (number of individuals) corrected with modelled availability was 15,320 (CV = 0.28) in 2015 and 11,001 (CV = 0.27) in 2016. Depending on the year, these estimates were ~7 times higher compared to estimates without the bias correction, and ~3 times higher compared to the abundances corrected with average availability. When the survey area contains habitat heterogeneity that may affect surfacing patterns of animals, modelling animals' availability provides a robust alternative to correcting for availability bias and highlights the need for caution when applying "average" correction factors.

Search and foraging behaviors from movement data: A comparison of methods.

Search behavior is often used as a proxy for foraging effort within studies of animal movement, despite it being only one part of the foraging process, which also includes prey capture. While methods for validating prey capture exist, many studies rely solely on behavioral annotation of animal movement data to identify search and infer prey capture attempts. However, the degree to which search correlates with prey capture is largely untested. This study applied seven behavioral annotation methods to identify search behavior from GPS tracks of northern gannets (Morus bassanus), and compared outputs to the occurrence of dives recorded by simultaneously deployed time-depth recorders. We tested how behavioral annotation methods vary in their ability to identify search behavior leading to dive events. There was considerable variation in the number of dives occurring within search areas across methods. Hidden Markov models proved to be the most successful, with 81% of all dives occurring within areas identified as search. k-Means clustering and first passage time had the highest rates of dives occurring outside identified search behavior. First passage time and hidden Markov models had the lowest rates of false positives, identifying fewer search areas with no dives. All behavioral annotation methods had advantages and drawbacks in terms of the complexity of analysis and ability to reflect prey capture events while minimizing the number of false positives and false negatives. We used these results, with consideration of analytical difficulty, to provide advice on the most appropriate methods for use where prey capture behavior is not available. This study highlights a need to critically assess and carefully choose a behavioral annotation method suitable for the research question being addressed, or resulting species management frameworks established.

Localised residency and inter-annual fidelity to coastal foraging areas may place sea bass at risk to local depletion.

For many marine migratory fish, comparatively little is known about the movement of individuals rather than the population. Yet, such individual-based movement data is vitally important to understand variability in migratory strategies and fidelity to foraging locations. A case in point is the economically important European sea bass (Dicentrarchus labrax L.) that inhabits coastal waters during the summer months before migrating offshore to spawn and overwinter. Beyond this broad generalisation we have very limited information on the movements of individuals at coastal foraging grounds. We used acoustic telemetry to track the summer movements and seasonal migrations of individual sea bass in a large tidally and estuarine influenced coastal environment. We found that the vast majority of tagged sea bass displayed long-term residency (mean, 167 days) and inter-annual fidelity (93% return rate) to specific areas. We describe individual fish home ranges of 3 km or less, and while fish clearly had core resident areas, there was movement of fish between closely located receivers. The combination of inter-annual fidelity to localised foraging areas makes sea bass very susceptible to local depletion; however, the designation of protected areas for sea bass may go a long way to ensuring the sustainability of this species.

New insights into ocean sunfish (Mola mola) abundance and seasonal distribution in the northeast Atlantic.

The ocean sunfish, Mola mola, is the largest teleost fish in the world. Despite being found in all oceans of the world, little is known about its abundance and factors driving its distribution. In this study we provide the first abundance estimates for sunfish in offshore waters in the northeast Atlantic and the first record of extensive sunfish presence in these waters year-round. Abundance estimates and predictive distributions for sunfish in approximately 300,000 km² of the northeast Atlantic were derived from large scale offshore aerial surveys in 2015-2016 using distance sampling techniques. Generalized additive models of sunfish density were fitted to survey data from 17,360 km of line transect effort resulting in minimum abundance estimates of 12,702 (CI: 9,864-16,357) in the summer (Density = 0.043 ind/km²) and 8,223 individuals (CI: 6,178-10,946) (Density = 0.028 ind/km²) in the winter. Density surface models predicted seasonal shifts in distribution and highlighted the importance of the mixed layer depth, possibly related to thermoregulation following deep foraging dives. The abundance estimate and estimated daily consumption of 2,600 tonnes of jellyfish in the northeast Atlantic highlights the need to re-assess the importance of this species in the pelagic ecosystem, and its role in top-down control of jellyfish blooms.