Development of a new control rule for managing anthropogenic removals of protected, endangered or threatened species in marine ecosystems.

Human activities in the oceans are increasing and can result in additional mortality on many marine Protected, Endangered or Threatened Species (PETS). It is necessary to implement ambitious measures that aim to restore biodiversity at all nodes of marine food webs and to manage removals resulting from anthropogenic activities. We developed a stochastic surplus production model (SPM) linking abundance and removal processes under the assumption that variations in removals reflect variations in abundance. We then consider several 'harvest' control rules, included two candidate ones derived from this SPM (which we called 'Anthropogenic Removals Threshold', or ART), to manage removals of PETS. The two candidate rules hinge on the estimation of a stationary removal rate. We compared these candidate rules to other existing control rules (e.g. potential biological removal or a fixed percentage rule) in three scenarios: (i) a base scenario whereby unbiased but noisy data are available, (ii) scenario whereby abundance estimates are overestimated and (iii) scenario whereby abundance estimates are underestimated. The different rules were tested on a simulated set of data with life-history parameters close to a small-sized cetacean species of conservation interest in the North-East Atlantic, the harbour porpoise (Phocoena phocoena), and in a management strategy evaluation framework. The effectiveness of the rules were assessed by looking at performance metrics, such as time to reach the conservation objectives, the removal limits obtained with the rules or temporal autocorrelation in removal limits. Most control rules were robust against biases in data and allowed to reach conservation objectives with removal limits of similar magnitude when averaged over time. However, one of the candidate rule (ART) displayed greater alignment with policy requirements for PETS such as minimizing removals over time.

Composition of cetacean communities worldwide shapes their contribution to ocean nutrient cycling.

Defecation by large whales is known to fertilise oceans with nutrients, stimulating phytoplankton and ecosystem productivity. However, our current understanding of these processes is limited to a few species, nutrients and ecosystems. Here, we investigate the role of cetacean communities in the worldwide biological cycling of two major nutrients and six trace nutrients. We show that cetaceans release more nutrients in mesotrophic to eutrophic temperate waters than in oligotrophic tropical waters, mirroring patterns of ecosystem productivity. The released nutrient cocktails also vary geographically, driven by the composition of cetacean communities. The roles of small cetaceans, deep diving cetaceans and baleen whales differ quantitatively and functionally, with contributions of small cetaceans and deep divers exceeding those of large whales in some areas. The functional diversity of cetacean communities expands beyond their role as top predators to include their role as active nutrient vectors, which might be equally important to local ecosystem dynamics.

Temporal correlations among demographic parameters are ubiquitous but highly variable across species.

Temporal correlations among demographic parameters can strongly influence population dynamics. Our empirical knowledge, however, is very limited regarding the direction and the magnitude of these correlations and how they vary among demographic parameters and species' life histories. Here, we use long-term demographic data from 15 bird and mammal species with contrasting pace of life to quantify correlation patterns among five key demographic parameters: juvenile and adult survival, reproductive probability, reproductive success and productivity. Correlations among demographic parameters were ubiquitous, more frequently positive than negative, but strongly differed across species. Correlations did not markedly change along the slow-fast continuum of life histories, suggesting that they were more strongly driven by ecological than evolutionary factors. As positive temporal demographic correlations decrease the mean of the long-run population growth rate, the common practice of ignoring temporal correlations in population models could lead to the underestimation of extinction risks in most species.

Accounting for detection probability with overestimation by integrating double monitoring programs over 40 years.

In the context of wildlife population declines, increasing computer power over the last 20 years allowed wildlife managers to apply advanced statistical techniques that has improved population size estimates. However, respecting the assumptions of the models that consider the probability of detection, such as N-mixture models, requires the implementation of a rigorous monitoring protocol with several replicate survey occasions and no double counting that are hardly adaptable to field conditions. When the logistical, economic and ecological constraints are too strong to meet model assumptions, it may be possible to combine data from independent surveys into the modelling framework in order to understand population dynamics more reliably. Here, we present a state-space model with an error process modelled on the log scale to evaluate wintering waterfowl numbers in the Camargue, southern France, while taking a conditional probability of detection into consideration. Conditional probability of detection corresponds to estimation of a detection probability index, which is not a true probability of detection, but rather conditional on the difference to a particular baseline. The large number of sites (wetlands within the Camargue delta) and years monitored (44) provide significant information to combine both terrestrial and aerial surveys (which constituted spatially and temporally replicated counts) to estimate a conditional probability of detection, while accounting for false-positive counting errors and changes in observers over the study period. The model estimates abundance indices of wintering Common Teal, Mallard and Common Coot, all species abundant in the area. We found that raw counts were underestimated compared to the predicted population size. The model-based data integration approach as described here seems like a promising solution that takes advantage of as much as possible of the data collected from several methods when the logistic constraints do not allow the implementation of a permanent monitoring and analysis protocol that takes into account the detectability of individuals.

Two cetacean species reveal different long-term trends for toxic trace elements in European Atlantic French waters.

Cetaceans have been naturally exposed to toxic trace elements (TEs) on an evolutionary time scale. Hence, they have developed mechanisms to control and/or mitigate their toxic effects. These long-lived species located at high trophic positions and bioaccumulating toxic elements are assumed to be good biomonitoring organisms. However, anthropogenic emissions have strongly increased environmental levels of toxic TEs in the last decades, questioning the efficiency of the detoxication mechanisms in cetaceans. In this context, temporal trends of mercury (Hg), cadmium (Cd) and lead (Pb) concentrations were studied through the analysis of 264 individuals from two cetacean species the common dolphin (Delphinus delphis) and the harbour porpoise (Phocoena phocoena) and belonging to two different Management Units (MUs) for the latter. These individuals stranded along the French Atlantic coasts from 2000s to 2017. All the trends presented were age- and sex-corrected and stable isotope ratios of carbon (δ13C) and nitrogen (δ15N) were measured as proxies of their feeding ecology. Results showed that Pb concentrations clearly decreased over time in both species and MUs. This decrease agrees with the lead petrol regulation after 2000s, supporting the use of these species as valuable bioindicators of changes for TE levels in the marine environment. A significant long-term increase of total Hg concentrations was only observed in common dolphins. Cadmium concentrations also revealed different trends over the period in both species. The different Hg and Cd trends observed in the two species, probably reflected a contrasted contamination of habitat and prey species than a global increase of the contamination in the environment. These results highlight the necessity and gain of using different species to monitor changes in marine environments, each of them informing on the contamination of its own ecological niche. Lastly, the Se:Hg molar ratios of species suggested a low risk for Hg toxicity over time.

Using single visits into integrated occupancy models to make the most of existing monitoring programs.

A major challenge in statistical ecology consists of integrating knowledge from different data sets to produce robust ecological indicators. To estimate species distribution, occupancy models are a flexible framework that can accommodate several data sets obtained from different sampling methods. However, repeating visits at sampling sites is a prerequisite for using standard occupancy models. Occupancy models were recently developed to analyze detection/non-detection data collected during a single visit. To date, single-visit occupancy models have never been used to integrate several different data sets. Here, we showcase an approach that combines two data sets into an integrated single-visit occupancy model. As a case study, we estimated the distribution of common bottlenose dolphin (Tursiops truncatus) over the northwestern Mediterranean Sea by combining 24,624 km of aerial surveys and 21,464 km of at-sea monitoring. We compared the outputs of single- vs. repeated-visit occupancy models into integrated occupancy models. Integrated models allowed a better sampling coverage of the targeted population, which provided a better precision for occupancy estimates than occupancy models using data sets in isolation. Overall, single- and repeated-visit integrated occupancy models produced similar inference about the distribution of bottlenose dolphins. We suggest that single-visit occupancy models open promising perspectives for the use of existing ecological data sets.

Trophic niche overlap between sympatric harbour seals (Phoca vitulina) and grey seals (Halichoerus grypus) at the southern limit of their European range (Eastern English Channel).

Sympatric harbour (Phoca vitulina) and grey seals (Halichoerus grypus) are increasingly considered potential competitors, especially since recent local declines in harbour seal numbers while grey seal numbers remained stable or increased at their European core distributions. A better understanding of the interactions between these species is critical for conservation efforts. This study aimed to identify the trophic niche overlap between harbour and grey seals at the southern limit of their European range, in the Baie de Somme (BDS, Eastern English Channel, France), where numbers of resident harbour seals and visiting grey seals are increasing exponentially. Dietary overlap was identified from scat contents using hierarchical clustering. Isotopic niche overlap was quantified using δ13C and δ15N isotopic values from whiskers of 18 individuals, by estimating isotopic standard ellipses with a novel hierarchical model developed in a Bayesian framework to consider both intraindividual variability and interindividual variability. Foraging areas of these individuals were identified from telemetry data. The three independent approaches provided converging results, revealing a high trophic niche overlap due to consumption of benthic flatfish. Two diet clusters were dominated by either small or large benthic flatfish; these comprised 85.5% [CI95%: 80.3%-90.2%] of harbour seal scats and 46.8% [35.1%-58.4%] of grey seal scats. The narrower isotopic niche of harbour seals was nested within that of grey seals (58.2% [22.7%-100%] overlap). Grey seals with isotopic values similar to harbour seals foraged in coastal waters close to the BDS alike harbour seals did, suggesting the niche overlap may be due to individual grey seal strategies. Our findings therefore provide the basis for potential competition between both species (foraging on benthic flatfish close to the BDS). We suggest that a continued increase in seal numbers and/or a decrease in flatfish supply in this area could cause/amplify competitive interactions and have deleterious effects on harbour seal colonies.

Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?

In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deep-diver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans.

Of power and despair in cetacean conservation: estimation and detection of trend in abundance with noisy and short time-series.

Many conservation instruments rely on detecting and estimating a population decline in a target species to take action. Trend estimation is difficult because of small sample size and relatively large uncertainty in abundance/density estimates of many wild populations of animals. Focusing on cetaceans, we performed a prospective analysis to estimate power, type-I, sign (type-S) and magnitude (type-M) error rates of detecting a decline in short time-series of abundance estimates with different signal-to-noise ratio. We contrasted results from both unregularized (classical) and regularized approaches. The latter allows to incorporate prior information when estimating a trend. Power to detect a statistically significant estimates was in general lower than 80%, except for large declines. The unregularized approach (status quo) had inflated type-I error rates and gave biased (either over- or under-) estimates of a trend. The regularized approach with a weakly-informative prior offered the best trade-off in terms of bias, statistical power, type-I, type-S and type-M error rates and confidence interval coverage. To facilitate timely conservation decisions, we recommend to use the regularized approach with a weakly-informative prior in the detection and estimation of trend with short and noisy time-series of abundance estimates.

Decadal changes in blood δ13C values, at-sea distribution, and weaning mass of southern elephant seals from Kerguelen Islands.

Changes in the foraging environment and at-sea distribution of southern elephant seals from Kerguelen Islands were investigated over a decade (2004-2018) using tracking, weaning mass, and blood δ13C values. Females showed either a sub-Antarctic or an Antarctic foraging strategy, and no significant shift in their at-sea distribution was detected between 2004 and 2017. The proportion of females foraging in sub-Antarctic versus Antarctic habitats did not change over the 2006-2018 period. Pup weaning mass varied according to the foraging habitat of their mothers. The weaning mass of sub-Antarctic foraging mothers' pups decreased by 11.7 kg over the study period, but they were on average 5.8 kg heavier than pups from Antarctic foraging mothers. Pup blood δ13C values decreased by 1.1‰ over the study period regardless of their sex and the presumed foraging habitat of their mothers. Together, these results suggest an ecological change is occurring within the Indian sector of the Southern Ocean with possible consequences on the foraging performance of southern elephant seals. We hypothesize that this shift in δ13C is related to a change in primary production and/or in the composition of phytoplankton communities, but this requires further multidisciplinary investigations.

High mortality rates in a juvenile free-ranging marine predator and links to dive and forage ability.

High juvenile mortality rates are typical of many long-lived marine vertebrate predators. Insufficient development in dive and forage ability is considered a key driver of this. However, direct links to survival outcome are sparse, particularly in free-ranging marine animals that may not return to land.In this study, we conduct exploratory investigations toward early mortality in juvenile southern elephant seals Mirounga leonina. Twenty postweaning pups were equipped with (a) a new-generation satellite relay data tag, capable of remotely transmitting fine-scale behavioral movements from accelerometers, and (b) a location transmitting only tag (so that mortality events could be distinguished from device failures). Individuals were followed during their first trip at sea (until mortality or return to land). Two analyses were conducted. First, the behavioral movements and encountered environmental conditions of nonsurviving pups were individually compared to temporally concurrent observations from grouped survivors. Second, common causes of mortality were investigated using Cox's proportional hazard regression and penalized shrinkage techniques.Nine individuals died (two females and seven males) and 11 survived (eight females and three males). All but one individual died before the return phase of their first trip at sea, and all but one were negatively buoyant. Causes of death were variable, although common factors included increased horizontal travel speeds and distances, decreased development in dive and forage ability, and habitat type visited (lower sea surface temperatures and decreased total [eddy] kinetic energy).For long-lived marine vertebrate predators, such as the southern elephant seal, the first few months of life following independence represent a critical period, when small deviations in behavior from the norm appear sufficient to increase mortality risk. Survival rates may subsequently be particularly vulnerable to changes in climate and environment, which will have concomitant consequences on the demography and dynamics of populations.

Role of sociality in the response of killer whales to an additive mortality event.

In highly social top predators, group living is an ecological strategy that enhances individual fitness, primarily through increased foraging success. Additive mortality events across multiple social groups in populations may affect the social structure, and therefore the fitness, of surviving individuals. This hypothesis was examined in a killer whale (Orcinus orca) population that experienced a 7-y period of severe additive mortality due to lethal interactions with illegal fishing vessels. Using both social and demographic analyses conducted on a unique long-term dataset encompassing periods before, during, and after this event, results indicated a decrease in both the number and the mean strength of associations of surviving individuals during the additive mortality period. A positive significant correlation between association strength and apparent survival suggested that the fitness of surviving individuals was impacted by the additive mortality event. After this event, individuals responded to the loss of relatives in their social groups by associating with a greater number of other social groups, likely to maintain a functional group size that maximized their foraging success. However, these associations were loose; individuals did not reassociate in highly stable social groups, and their survival remained low years after the mortality event. These findings demonstrate how the disruption of social structure in killer whales may lead to prolonged negative effects of demographic stress beyond an additive mortality event. More importantly, this study shows that sociality has a key role in the resilience of populations to human-induced mortality; this has major implications for the conservation of highly social and long-lived species.

Population response of an apex Antarctic consumer to its prey and climate fluctuations.

A fundamental endeavor in population ecology is to identify the drivers of population dynamics. A few empirical studies included the effect of prey abundance when investigating simultaneously the effects of density-dependence and climate factors on marine top-predator population dynamics. Our aim was to unravel the mechanisms forcing population dynamics of an apex consumer seabird, the south polar skua, using long-term climatic and population time series of the consumer and its prey in Terre Adélie, Antarctica. Influences of density-dependence, climatic factors, and prey abundance with lag effects were tested on the breeding population dynamics with a Bayesian multi-model inference approach. We evidenced a negative trend in breeding population growth rate when density increased. Lagged effects of sea-ice concentration and air temperature in spring and a contemporary effect of prey resources were supported. Remarkably, results outline a reverse response of the south polar skua and one of its main preys to the same environmental factor (sea-ice concentration), suggesting a strong link between skua and penguin dynamics. The causal mechanisms may involve competition for food and space through territorial behavior as well as local climate and prey availability, which probably operate on breeding parameters (breeding propensity, breeding success, or recruitment) rather than on adult survival. Our results provide new insights on the relative importance of factors forcing the population dynamics of an apex consumer including density-dependence, local climate conditions, and direct and indirect effects of prey abundance.

How many sightings to model rare marine species distributions.

Despite large efforts, datasets with few sightings are often available for rare species of marine megafauna that typically live at low densities. This paucity of data makes modelling the habitat of these taxa particularly challenging. We tested the predictive performance of different types of species distribution models fitted to decreasing numbers of sightings. Generalised additive models (GAMs) with three different residual distributions and the presence only model MaxEnt were tested on two megafauna case studies differing in both the number of sightings and ecological niches. From a dolphin (277 sightings) and an auk (1,455 sightings) datasets, we simulated rarity with a sighting thinning protocol by random sampling (without replacement) of a decreasing fraction of sightings. Better prediction of the distribution of a rarely sighted species occupying a narrow habitat (auk dataset) was expected compared to the distribution of a rarely sighted species occupying a broad habitat (dolphin dataset). We used the original datasets to set up a baseline model and fitted additional models on fewer sightings but keeping effort constant. Model predictive performance was assessed with mean squared error and area under the curve. Predictions provided by the models fitted to the thinned-out datasets were better than a homogeneous spatial distribution down to a threshold of approximately 30 sightings for a GAM with a Tweedie distribution and approximately 130 sightings for the other models. Thinning the sighting data for the taxon with narrower habitats seemed to be less detrimental to model predictive performance than for the broader habitat taxon. To generate reliable habitat modelling predictions for rarely sighted marine predators, our results suggest (1) using GAMs with a Tweedie distribution with presence-absence data and (2) implementing, as a conservative empirical measure, at least 50 sightings in the models.

Assessing cetacean surveys throughout the Mediterranean Sea: a gap analysis in environmental space.

Heterogeneous data collection in the marine environment has led to large gaps in our knowledge of marine species distributions. To fill these gaps, models calibrated on existing data may be used to predict species distributions in unsampled areas, given that available data are sufficiently representative. Our objective was to evaluate the feasibility of mapping cetacean densities across the entire Mediterranean Sea using models calibrated on available survey data and various environmental covariates. We aggregated 302,481 km of line transect survey effort conducted in the Mediterranean Sea within the past 20 years by many organisations. Survey coverage was highly heterogeneous geographically and seasonally: large data gaps were present in the eastern and southern Mediterranean and in non-summer months. We mapped the extent of interpolation versus extrapolation and the proportion of data nearby in environmental space when models calibrated on existing survey data were used for prediction across the entire Mediterranean Sea. Using model predictions to map cetacean densities in the eastern and southern Mediterranean, characterised by warmer, less productive waters, and more intense eddy activity, would lead to potentially unreliable extrapolations. We stress the need for systematic surveys of cetaceans in these environmentally unique Mediterranean waters, particularly in non-summer months.

Ocean sunfish as indicators for the 'rise of slime'.

Overfishing and ocean warming are drastically altering the community composition and size structure of marine ecosystems, eliminating large bodied species [1]. Against a backdrop of such environmental change, the heaviest of all bony fish, the ocean sunfish (Mola mola), seems an improbable survivor. Indeed this indolent giant is killed globally as bycatch, and is listed as 'Vulnerable'[2]. We undertook the most extensive aerial surveys of sunfish ever conducted and found surprisingly high abundances off the Atlantic and Mediterranean coasts of Western Europe. With up to 475 individuals per 100 km2, these figures are one order of magnitude higher than abundance estimates for other areas [3-5]. Using bioenergetic modelling, we estimate that each sunfish requires 71 kg day-1 of jellyfish, a biomass intake more than an order of magnitude greater than predicted for a similarly sized teleost. Scaled up to the population level, this equates to a remarkable 20,774 tonnes day-1 of predated jellyfish across our study area in summer. Sunfish abundance may be facilitated by overfishing and ocean warming, which together cause reduced predation of sunfish by sharks and elevated jellyfish biomass. Our combined survey and bioenergetic data provide the first-ever estimate of spatialized ocean sunfish daily food requirements, and stress the importance of this species as a global indicator for the 'rise of slime'. This hypothesis posits that, in an overfished world ocean exposed to global warming, gelatinous zooplankton should flourish, to the detriment of other mesotrophic species such as small pelagic fish, causing irreversible trophic cascades as well as a series of other environmental and economic issues.

Wolf in sheep's clothing: Model misspecification undermines tests of the neutral theory for life histories.

Understanding the processes behind change in reproductive state along life-history trajectories is a salient research program in evolutionary ecology. Two processes, state dependence and heterogeneity, can drive the dynamics of change among states. Both processes can operate simultaneously, begging the difficult question of how to tease them apart in practice. The Neutral Theory for Life Histories (NTLH) holds that the bulk of variations in life-history trajectories is due to state dependence and is hence neutral: Once previous (breeding) state is taken into account, variations are mostly random. Lifetime reproductive success (LRS), the number of descendants produced over an individual's reproductive life span, has been used to infer support for NTLH in natura. Support stemmed from accurate prediction of the population-level distribution of LRS with parameters estimated from a state dependence model. We show with Monte Carlo simulations that the current reliance of NTLH on LRS prediction in a null hypothesis framework easily leads to selecting a misspecified model, biased estimates and flawed inferences. Support for the NTLH can be spurious because of a systematic positive bias in estimated state dependence when heterogeneity is present in the data but ignored in the analysis. This bias can lead to spurious positive covariance between fitness components when there is in fact an underlying trade-off. Furthermore, neutrality implied by NTLH needs a clarification because of a probable disjunction between its common understanding by evolutionary ecologists and its translation into statistical models of life-history trajectories. Irrespective of what neutrality entails, testing hypotheses about the dynamics of change among states in life histories requires a multimodel framework because state dependence and heterogeneity can easily be mistaken for each other.

Variability in sea ice cover and climate elicit sex specific responses in an Antarctic predator.

Contrasting regional changes in Southern Ocean sea ice have occurred over the last 30 years with distinct regional effects on ecosystem structure and function. Quantifying how Antarctic predators respond to such changes provides the context for predicting how climate variability/change will affect these assemblages into the future. Over an 11-year time-series, we examine how inter-annual variability in sea ice concentration and advance affect the foraging behaviour of a top Antarctic predator, the southern elephant seal. Females foraged longer in pack ice in years with greatest sea ice concentration and earliest sea ice advance, while males foraged longer in polynyas in years of lowest sea ice concentration. There was a positive relationship between near-surface meridional wind anomalies and female foraging effort, but not for males. This study reveals the complexities of foraging responses to climate forcing by a poleward migratory predator through varying sea ice property and dynamic anomalies.

The Conundrum of Heterogeneities in Life History Studies.

What causes interindividual variation in fitness? Evidence of heritability of latent individual fitness traits has resparked a debate about the causes of variation in life histories in populations: neutralism versus empirical adaptationism. This debate about the processes underlying observed variation pits neutral stochastic demographic processes against evolutionarily relevant differences among individual fitness traits. Advancing this debate requires careful consideration of differences among inference approaches used by proponents of each hypothesis. Here we draw parallels between several disciplines focusing on processes generating variation in individuals' life-course, and we contrast methodologies to disentangle these processes. We draw on other disciplines to clarify terminology, risks of flawed inference, and expand the panel of hypotheses and formalizations of processes generating variation in life histories.

Windscape and tortuosity shape the flight costs of northern gannets.

When animals move across a landscape, they alternate between active searching phases in areas with high prey density and commuting phases towards and in-between profitable feeding patches. Such active searching movements are more sinuous than travelling movements, and supposedly more costly in energy. Here we provide an empirical validation of this long-lasting assumption. To this end, we evaluated simultaneously energy expenditure and trajectory in northern gannets (Morus bassanus) using GPS loggers, dive recorders and three-dimensional accelerometers. Three behavioural states were determined from GPS data: foraging, when birds actively searched for prey (high tortuosity, medium speed); travelling, when birds were commuting (straight trajectory, high speed); and resting (straight trajectory, low speed). Overall dynamic body acceleration, calculated from acceleration data, was used as a proxy for energy expenditure during flight. The impact of windscape characteristics (wind force and direction) upon flight costs was also tested. Energy expenditure of northern gannets was higher during sinuous foraging flight than during more rectilinear travelling flight, demonstrating that turns are indeed costly. Yet wind force and direction also strongly shaped flight energy expenditure; within any behavioural state it was less costly to fly with the wind than against it, and less costly to fly with strong winds. Despite the major flight costs of wind action, birds did not fully optimize their flight track relative to wind direction, probably because of prey distributions relative to the coastline and wind predictability. Our study illustrates how both tortuosity and windscape shape the foraging costs of marine predators such as northern gannets.