ABSTRACT Offshore wind farms are growing worldwide and increase the source of renewable energy. However, as the extent and density of offshore wind farms increase, there is growing importance to understand the interactions with physical systems and the marine environment, in particular, the sea state. This study presents an analysis of airborne data from the flight projects WIPAFF and X‐Wakes which took place in the German Bight, examining the effects of wind farm wakes on the sea surface and the possible interaction between atmospheric and sea surface wakes. By clustering the data, this study identifies patterns for the sea surface wake. For stable atmospheric stratification, the sea surface wake extends up to several tens of kilometers, while during unstable conditions, the sea surface wake is very short or absent. In all analyzed cases, the length of the atmospheric wake was longer than the length of the sea surface wake.

Accurate characterization of light backscattering in natural waters is critical for interpreting remote sensing reflectance and retrieving marine biogeochemical properties. While light absorption has been extensively measured, resolving fine-scale spectral variability in particulate light backscattering has remained challenging due to instrumental limitations. Here, we present hyperspectral backscattering measurements from the newly developed HyFi-bb instrument during field campaigns in the Baltic Sea and German Bight. The high spectral resolution (∼2 nm, 350-850 nm) reveals distinct bio-optical features, including pigment-specific signatures and anomalous dispersion near the pigment absorption bands, which are not resolved in multispectral measurements. Comparisons across regions show that backscattering ratios are higher in the minerogenic particle-dominated German Bight than in phytoplankton-rich Baltic waters, with spectral slopes of the backscattering ratios reflecting underlying particle composition. Contributions from particles <0.2 µm were found to be minor, suggesting their limited role in total backscattering in coastal waters. Our results demonstrate that hyperspectral backscattering provides new insights into the biogeochemical drivers of optical variability.

We describe for the first time the occurrence of the smallest extant brachiopod, Gwynia capsula (Jeffreys, 1859), from the island of Helgoland. A single living specimen was found in dredged shell gravel from the Helgoland trench ("Tiefe Rinne") mainly consisting of large dead shells of the bivalves Ostrea edulis and Modiolus modiolus. G. capsula was identified through its minute size and its characteristic submarginal ridges on the inside of the dorsal valve supporting the trocholophous lophophore of the animal. Among other localities, populations of G. capsula are known from British waters as well as the continental coasts of, e.g., France, Belgium and the Netherlands. However, the reproductive biology of the species makes it rather unlikely that larvae of G. capsula have reached Helgoland by natural drift. It is briefly discussed whether ship-based trading throughout the 19th century may have had an influence here.

Abstract. We assess the evolution of Northeast Atlantic and German Bight storm activity using both model simulations and observational data. Our analysis includes the CMIP6 multi-model ensemble and the Max Planck Institute Grand Ensemble (MPI-GE) under CMIP6 forcing, evaluated across historical forcing and three future emission scenarios. Storm activity is quantified via upper percentiles of geostrophic wind speeds, derived from horizontal gradients of mean sea-level pressure. Observational datasets are employed to benchmark and validate the modeled storm characteristics, enhancing the robustness of our assessment. We detect robust downward trends for Northeast Atlantic storm activity in all scenarios, and weaker but still downward trends for German Bight storm activity. In both the multi-model ensemble and the MPI-GE, we find a projected increase in the frequency of westerly winds over the Northeast Atlantic and northwestesrly winds over the German Bight, and a decrease in the frequency of easterly and southerly winds over the respective regions. We also show that despite the projected increase in the frequency of wind directions associated with increased cyclonic activity, the 95th percentiles of wind speeds from these directions decrease, leading to lower overall storm activity. Lastly, we detect that the change in wind speeds strongly depends on the region and percentile considered, and that the most extreme storms (&gt;99th percentile) may become stronger or more likely in the German Bight in a future climate despite reduced overall storm activity.

In this study, a hybrid architecture combining convolutional neural networks for spatial reconstruction and long short-term memory networks for temporal forecasting is used to predict sea-level variations in the German Bight. This new framework is applied to a series of sea level data ranging from academic to realistic data. Experiments with monochromatic waves demonstrate the model’s ability to deliver accurate short-term forecasts with minimal errors. Forecasts of real tidal constituents, including M2 and the sum of M2 and M4 tides, confirm robust model performance over lead times up to 48 h. A key result is that deep learning can reconstruct basin-wide sea level from a limited number of coastal gauge stations. Therefore, in the forecast experiments, adding data from coastal observations (mimicking data assimilation) significantly improves prediction accuracy. The study highlights the potential of deep learning to supplement traditional numerical models, particularly in regions with dense observational coverage. Key factors influencing model performance are identified, among them spatial signal complexity and steepness of gradients. An overall result is that deep learning can complement numerical models in operational ocean forecasting and provide a valuable tool for evidence-based coastal management in data-rich regions.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-31670-2.

Marine protected area (MPA) networks are important for supporting biodiversity, enhancing ecosystem resilience, and facilitating species recovery. For the effectiveness of conservation and restoration, functional connectivity plays a vital role. The dispersal, movement, and successful establishment of organisms between suitable habitats and MPAs ensure long‐term sustainability of the populations. Despite its importance, functional connectivity is rarely integrated into restoration planning, which limits the effectiveness of species reintroductions, habitat connectivity, and adaptation to environmental changes. In this study, we applied an integrative approach combining molecular detections (environmental DNA [eDNA] and meroplankton metabarcoding) with biophysical modeling to explore the functional connectivity between two Natura 2000 MPAs in the North Sea: Borkum Reef Ground (BRG) and Sylt Outer Reef (SOR). We focused on the European flat oyster (Ostrea edulis), a reef‐building species that once provided vast reef habitats but is now functionally extinct in the German Bight and is therefore the subject of recent restoration measures at BRG. Our results showed partial but informative correspondence between molecular detections of oyster genetic traces and the modeled larval pathways during the June–July 2022 sampling period. We further explored larval dispersal across entire spawning seasons in 2022 and 2023. Connectivity between BRG and SOR was highly dependent on larval drift depth. Surface‐drifting larvae showed strong interannual variability, with 3% reaching SOR in 2022 when northwesterly winds dominated, increasing to 22% in 2023 under westerly and southwesterly winds. Larvae drifting at depth, however, exhibited near‐zero connectivity, leading to high self‐recruitment rates, with over 25% settling near the original restoration sites. Our results demonstrate that wind‐driven currents are a key driver of interannual variability in larval retention and dispersal. Additionally, they highlight the role of biological traits, such as vertical positioning and pelagic larval duration, in shaping connectivity between MPAs and oyster restoration sites. These findings emphasize the need to integrate connectivity assessments into MPA management and the restoration planning of reef‐building benthic species. The interdisciplinary approach presented here provides a quantitative framework for assessing connectivity under species‐ and site‐specific conditions, offering a transferable tool to evaluate the restoration potential of other species and enhance the functional network between MPAs.

Abstract Anthropogenically driven nutrient shifts and warming are key stressors affecting phytoplankton in marine coastal environments. The German Bight, a coastal region in the North Sea, has undergone substantial nutrient reductions and rising sea surface temperature (SST) over recent decades. Despite extensive research, the combined long-term effects of nutrient shifts and warming, particularly in the river-influenced coastal area, remain unclear. Here, we aimed to evaluate trends and explore the partial and interactive effects of winter nutrient alterations and seasonal warming on spring chlorophyll- a (Chl- a ) levels. For this purpose, we compiled a comprehensive spatiotemporal dataset (1980–2019) and applied generalized linear mixed models. Results showed that spring Chl- a concentrations peaked in the 1980s and 1990s, with values surpassing 30 µg L −1 in the Elbe estuary. Concentrations declined to &lt; 15 µg L −1 in the following decades, although values &gt; 15 µg L −1 persisted in the southern inner coastal waters. Decreasing winter dissolved inorganic nitrogen (DIN) emerged as the primary driver of declining spring Chl- a in coastal waters (estimate = 0.40, p &lt; 0.01), while winter phosphorus and nitrogen-to-phosphorus ratios were not significant predictors. Spring SST had a weak positive effect on Chl- a (estimate = 0.09, p = 0.03), suggesting that warming during spring may enhance phytoplankton growth. Together, winter DIN and spring SST explained 30% of the variance in spring Chl- a . Additional factors, such as light availability and grazing, likely contribute to unexplained variability. This study provides evidence that nutrient reductions have successfully lowered chlorophyll levels, but persistent hotspots in the inner coastal waters highlight the need for targeted management under continued warming.

The brown shrimp ( Crangon crangon ) stock of the Wadden Sea supports one of the most important fisheries in the region due to its high productivity and market price. Given the species' short life history and seasonal dynamics, fisheries-based indicators (i.e., landings per unit effort, LPUE) are used to monitor stock biomass; however, these indicators may be biased by fishing behavior and thus require further evaluation. Using survey data from the German Bight area of the Wadden Sea, this study presents a novel species distribution model to estimate annual stock biomass changes for different size fractions (‘small’, <50 mm; ‘large’, >50 mm; and ‘combined’, all sizes), which are compared to LPUE and catch per unit effort (CPUE, with modelled discards) to evaluate their use as indicators of biomass. The results indicate that changes in LPUE are well correlated with biomass changes, although CPUE is shown to have an even stronger relationship to the combined biomass index, representative of exploitable biomass. This relationship is used to reconstruct monthly historical stock dynamics and estimate fishing exploitation rates (monthly harvest rate and annual fishing mortality). Estimated fishing rates reflect changes in fishing effort, which varies seasonally, in response to recruitment and subsequent exploitable biomass dynamics, and interannually, relating to reductions in fleet size and shorter-term pauses in effort. The resulting time series serve as a basis for further stock assessment models that can provide more biologically-based advice for the stock. The methodology’s combination of survey and fisheries-dependent data should be of interest to other data-limited applications; particularly, short-lived species where seasonal dynamics of the stock and fishery are of importance. • Species distribution model is used to derive biomass estimates of brown shrimp from fisheries-independent survey data. • Evaluation of fisheries-dependent indices of brown shrimp density (landings or catch per unit effort) as proxies for biomass. • Reconstruction of monthly exploitable biomass and estimation of historical fishing mortality changes.

Extreme physical-oceanographic events, such as marine heatwaves, fluvial floods, droughts and storm surges, have major impacts on local communities, economic sectors and ecosystems, and their frequency, intensity and duration increase due to climate change. There is a lack of understanding of the systemic drivers of extreme events as well as of their interconnected impacts on estuarine and coastal ecosystems. This knowledge is essential for assessing future impacts on ecosystem services and the local communities that depend on them, and to inform robust risk assessments and develop comprehensive risk management and adaptation strategies including early warning systems. Considering this, the German Alliance for Marine Research (DAM)-funded programme “ElbeXtreme” focuses on an integrated approach utilizing stakeholder engagement, data mining, experimental and field observations to develop novel observational and modelling approaches for assessing and monitoring risks in the Elbe estuary. The programme will deliver new insights into risks and impacts of extreme events in the estuarine system of the Elbe and the adjacent region of the North Sea (German Bight) to build a systemic risk understanding and support adaptation planning for local communities and ecosystems. Here we outline the rationale of the ElbeXtreme project and its planned activities, with the aim of stimulating national and international collaboration in tackling the urgent issue of marine and coastal risks.

Ocean warming and metal pollution pose a threat to coastal ecosystems worldwide. In the German Bight, efforts to restore biogenic reefs using the native European flat oyster (Ostrea edulis) face challenges due to environmental conditions and potential pollutants of the North Sea. Besides O. edulis, the non-native Pacific oyster (Crassostrea gigas) inhabits the North Sea. Larval stages of bivalves are known to be sensitive to pollution. In this study, we investigate the effect of the trace metals copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb) in combination with water temperatures of 18° and 24°C on the embryo-larval development of C. gigas and acute mortality of C. gigas and O. edulis D-larvae. This multi-stressor approach revealed that Cu was the most toxic metal, regardless of temperature, species or life stage. While elevated temperatures mitigated the negative effects of metal exposure on embryo-larval development, larval mortality was species- and metal-dependent at the tested temperatures. O. edulis D-larvae demonstrated a greater absolute tolerance to metal exposure at both temperatures, but a species comparison showed that O. edulis D-larvae had lower relative tolerance to the combined stress of warming and metal exposure than C. gigas. Based on the resulting toxicity thresholds, an environmental risk assessment for Cu was conducted to identify potentially hazardous areas for O. edulis restoration to be included in future habitat suitability studies and site selection for restoration. The identified areas may also indicate problematic environmental conditions for larval stages of other invertebrate species or fish.

Abstract The concentration and size of particles in coastal oceans is of great ecological importance, for example for light penetration and thus primary production. A common tool to determine particle sizes and concentrations is the Laser In Situ Scattering and Transmissometry (LISST). Previous studies with LISST instruments have found large variations in particle sizes and a possible influence on the measurement by current shear. To determine the strength of this influence, we conducted a cruise in the German Bight. We determined particle sizes and concentrations using a Sequoia LISST‐200X, as well as the encounter velocity and the direction with which the water hits the instrument frame using an Acoustic Doppler Velocimeter. The encounter velocity was modulated by drifting and steering of the ship, leading to minimal velocities of 0.1 m s−1 during drift and maximum velocities of 0.6 m s−1 during steering. We found that the determined particle size is strongly dependent on the encounter velocity and the orientation of the instrument. The determined particle size decreased by 17–56 μm per increase in 0.1 m s−1 encounter velocity. Identifying and exploring two hypotheses, we assume that large particles are destroyed by the current shear at high velocities. We propose that for future LISST measurements, the encounter velocity with which the water hits the instrument be taken into account and reduced as far as possible. In addition, we propose measurements under controlled conditions that can accurately determine the extent of the influence of encounter velocity on particle size determination.

Flood events caused by high rainfall can have profound biogeochemical impacts on riverine systems but also on the receiving coastal waters. The winter flood in Germany in December 2023/January 2024 affected the Elbe and Weser River systems. We obtained unique data during the peak of the flood and compared these with the monthly means from previous years (2018-2023). Hydrographic parameters and nutrients were determined by standard methods. Low salinity values were observed in the Elbe estuary and the adjacent German Bight (part of North Sea). At Helgoland the lowest average salinity was observed in January 2024 with 31.3 ± 0.5 compared to an average salinity of 32.7 ± 0.7 for the years 2016 to 2023. Nutrient loads (nitrate, phosphate) in the rivers showed a six- to 11-fold increase in the Elbe and Weser rivers compared to years without flood events. Enhanced concentrations of nitrate and silicate were found in the German Bight in January. Nutrients were diluted with North Sea waters, indicating a conservative behavior of nutrients in winter. Atypical prevailing meteorological conditions in January 2024, with predominantly easterly winds, potentially affect the dispersal of the river plume and the nutrients in the North Sea. In March 2024 the chlorophyll-a concentration strongly increased to 2.9 ± 1.8 µmol/L and was twice as high compared to only 1.5 ± 0.7 µmol/L observed in previous years. The observed intensified spring bloom in March in the German Bight near the island of Helgoland indicates the impacts of the flood-derived nutrient inputs three months after the flood event, as the timing of light and nutrient availability was optimal. It is assumed that seasonality and magnitude of flooding in the Elbe estuary and adjacent coastal region will change in future due to climate warming. Thus, the timing of light and nutrient availability will also change, with unconstrained impacts on primary producers and higher trophic levels.

Abstract. Storm surges pose significant threats to coastal regions, including the German Bight, where strong winds from the northwesterly direction drive water levels to extreme heights. In this study, we present a simple, effective storm surge model for the German Bight, utilizing a multiple linear regression approach based solely on 10 m effective wind speed as the predictor variable. We train and evaluate the model using historical skew surge data from 1959 to 2022, incorporating regularization techniques to improve prediction accuracy while maintaining simplicity. The model consists of only five terms, the effective wind at various locations with different lead times within the North Sea region, and an intercept. It demonstrates high predictive skill, achieving a correlation of 0.88. This indicates that, despite its extreme simplicity, the model performs just as well as more complex models. The storm surge model provides robust predictions for both moderate and extreme storm surge events. Moreover, due to its simplicity, the model can be effectively used in climate simulations, making it a valuable tool for assessing future storm surge risks under changing climate conditions, independent of the ongoing and continuous sea-level rise.

Driven by the demands of climate change mitigation, many countries have begun large-scale electricity production from variable renewables, such as solar PV and wind power. Electricity production from wind turbines, in particular, strongly depends on local weather conditions and their changes caused by climate change. Thus, for many countries with a high share of wind power generation, such as Germany, two essential questions arise: how will climate change affect electricity production, and how strong will be this impact for different RCPs? To better assess the impact on existing onshore wind turbines, spatially and temporally resolved data on their power generation are required. In order to create such disaggregated data, this study uses a physical simulation model and climate data modified for the RCP 2.6, RCP 4.5, and RCP 8.5 scenarios. To investigate the effects on a significant region with very high wind power generation in Germany, the numerical simulations were carried out on an ensemble of 22 onshore wind turbines with an installed capacity of 65.5 MW in the German Bight. After model validation, the power generation from this turbine ensemble was simulated for the high-wind year 2008 and the low-wind year 2010. The simulation results are presented with a high temporal resolution, and the observed changes are discussed for the applied RCPs. In summary, the resulting wind power generation of the entire plant ensemble decreases with increasing RCP to values of up to nearly 3 GWh for both years.

Scenarios of energy transition in Germany project large wind capacity deployment in the German Bight by 2050. They use models that estimate technical potential or annual generation by fixing energy loss from atmosphere-turbine interactions to 10% to manage computational cost. This approach, which we call Fixed, underestimates losses as it discounts impacts of wind resource depletion that manifest as reduced wind speeds and lowered turbine yields. We explore the influence of kinetic energy (KE) removal by wind turbines and stability conditions on wind resource depletion and turbine yield. Using wind speeds, turbine yields and capacity factor estimates from three approaches that include the Fixed approach, a simplified representation of atmospheric KE budgets and their depletion (KEBA), and mesoscale simulations from the Weather Research and Forecasting (WRF) model with a wind farm parameterisation we investigate the predominant influence on the Bight’s potential that is relevant for energy scenarios. WRF, the most physically comprehensive model among the three, reveals that reductions in these estimates are highest during stable conditions. KEBA, which incorporates only KE removal effects, aligns closely with WRF. Under highly unstable conditions KEBA’s wind speed and capacity factors estimates are within 10% and 20% of WRF, respectively. Under stable conditions they are within 20 and 45%. As unstable conditions dominate the German Bight, KEBA estimates of technical potential are within 35% of WRF, suggesting that KE removal primarily shapes depletion effects and technical potential. Disregarding it leads to an overestimation of almost 90%. Despite depletion effects, the Bight’s potential remains substantial, generating about 200–250 TWh yr−1 or 3000–3400 full load hours yr−1 from a 72 GW deployment. We conclude that using a simplified yet physical model of KE budgets provides more representative technical potential estimates for energy scenarios compared to the Fixed approach.

Abstract. The burial of organic matter (OM) within fine-grained continental shelf sediments represents one of the major long-term sinks of carbon. We investigated the key factors controlling organic carbon burial in sediments of the North Sea by using the Helgoland Mud Area (HMA) as a natural test field. The HMA represents the most significant depocentre of fine-grained and organic-rich sediments in the German Bight (SE North Sea). We examined factors including sedimentation and accumulation rate, sediment-mixing rate, grain size, total organic carbon (TOC) content, and aerobic remineralisation rate. Highest sedimentation rates (SRs) of up to ∼ 4.5 mm yr−1 and average TOC contents of 2 wt % were found in the southern part of the HMA, which is under the influence of the Elbe River outflow, reaching organic carbon burial efficiencies of &gt;65 %. Sedimentation rates 4 times lower and the lowest TOC contents (0.7 wt %–1.0 wt %) were found in the shallow eastern part of the research area, with the lowest organic carbon burial efficiencies being 30 %. High sedimentation rates are known to limit oxygen exposure time, thereby enhancing OM preservation. Our data support this finding, demonstrating and confirming that sedimentation rate is the key factor determining organic carbon burial efficiency (OC BE) and long-term sedimentary carbon storage. In the southern part of the HMA, close to the outflow of the Elbe River, the OM being degraded is primarily of terrigenous origin, while, in the central and northern parts of the HMA, a mixture of marine and terrigenous OM is remineralised. At the sites dominated by the degradation of marine organic matter, as found in the western and northwestern HMA, the organic carbon burial efficiency is lower and fluctuates around 55 %. The burial efficiency of OM is highest in sedimentary habitats characterised by high sedimentation rates and OM of terrigenous sources. Sediment-mixing rates were highest in the northwestern HMA, where the highest bottom-trawling activity is also reported. The comparison of sites similar in depositional characteristics but different in bottom-trawling intensity suggests that, in the area of intense bottom trawling in the northwestern HMA, the sequestration of OM is reduced by around 30 %. The annual burial flux of organic carbon in the HMA amounts to an average of 22.5 g C m−2 yr−1. Considering the strong tidal currents in the shallow HMA, the burial flux is exceptionally high and even compares with those reported for the deeper Skagerrak and Norwegian Trough (∼ 10 to 66 g C m−2 yr−1), which are the main depocentres for fine-grained and organic-rich sediments in the North Sea. For the entire HMA, the total annual organic carbon accumulation amounts to 0.011 Tg C yr−1. These findings highlight the importance of depocentres for fine-grained sediments as important carbon sinks: while the area of the HMA represents only 0.09 % of the North Sea, it stores 0.76 % of the total annual accumulated organic carbon in this shelf sea area.

The study focused on the seamless integration of the land–ocean continuum, establishing a connection between the estuarine and coastal model and the regional ocean model. The integration of models that cover the land–ocean connection remains a significant challenge, as it is essential to provide a more realistic representation of estuarine flows. Such flows facilitate the transport of freshwater and salinity from the land into the coastal ocean through estuaries, where they mix with seawater flows. These mixed water masses exert a discernible influence on local dynamics, particularly regarding water stratification and circulation patterns. The interplay of wave-induced processes and estuarine influences in the coastal German Bight was quantified through comprehensive sensitivity experiments. The incorporation of high-resolution estuarine salinity data into land–ocean continuum models enhances their accuracy, enabling a more precise representation of estuarine flows and their impact on coastal simulations. The realistic representation of estuarine fluxes has a significant impact on ocean dynamics, as demonstrated by alterations to water stratification and salinity fronts along the German Bight coast. Our findings underscore the pivotal role of high-frequency freshwater discharges in modulating coastal salinity and water levels, especially during extreme flood events. The study emphasizes the necessity of incorporating wave effects and estuarine dynamics to achieve an accurate simulation of oceanographic processes in the German Bight. The integration of these processes into the regional ocean framework enhances the representation of estuarine inflows, offering a more realistic simulation of coastal environments. This is critical for effective management of coastal systems and for developing resilient strategies. These findings have significant implications for enhancing coastal forecasting systems, understanding the influence of extreme events, and guiding future research into long-term coastal dynamics under different climatic conditions.Graphical abstract

Offshore production of hydrogen powered by offshore wind energy offers a promising alternative to fossil fuels. However, current technologies return waste heat and brine into the sea, raising questions of potential effects on local and regional hydrography. This study evaluates the hydrographic footprint of offshore hydrogen in the context of anthropogenic pressures from offshore energy production, focusing on a scenario for the German Bight. Cross-scale modeling shows that waste heat emerges as the primary influence, causing temperature changes of up to 2 °C within 10’s of meters around a 500 MW hydrogen plant. While tides prove to be decisive for the dilution of density plumes, we demonstrate that production capacity and discharge method determine the hydrographic footprint. Large-scale effects are minor and negligible compared to the impact of offshore wind farm wakes, however, waste heat can raise annual mean sea surface temperature by up to 0.2 °C near production sites.

Connectivity and larval drift across marine protected areas in the German bight, North Sea: Necessity of stepping stones

Moulting and overwintering Common Scoter Melanitta nigra aggregate in largely undisturbed, shallow‐water marine areas, preying upon sessile benthic organisms (mainly bivalves), which do not reproduce during this period of exploitation. Assuming even prey distribution, we predict that Common Scoters would aggregate to moult in shallowest waters with most accessible prey in July, where diving costs were minimal, but would disperse to deeper (i.e. comparatively less profitable) waters through the season as Common Scoter numbers increase and (potentially) as their prey are depleted in winter. To test these hypotheses, we used multiple aerial survey count data to study Common Scoter distribution patterns in Aalborg Bugt, Denmark (in relatively sheltered areas subject to restricted tidal influence), and along the more exposed, highly tidal Schleswig‐Holstein North Sea coast in the German Bight. Despite these physical differences, Common Scoters displayed similar distribution patterns in both areas, showing significant increases in mean water depth (from 6.3 m in July to 9.8 m in March in Denmark, 6.5–10.3 m in Germany), number of flock units (432 to 1614; 48 to 581) and the percentage of 3 × 3 km grid squares occupied by birds as the season progressed (15% to 44% of 628 grid cells; 1% to 39% of 408 grid cells). The results support our hypotheses that these consumers distribute themselves to maximize their nutritional and energetic intake, while minimizing costs of gaining food in two contrasting marine environments, but we require sequential sampling of their food supply at differing water depths to confirm the causes of these observed patterns.