Dynamics of air–sea CO2 fluxes in the northwestern European shelf based on voluntary observing ship and satellite observations

From January 2011 to December 2013, we constructed a comprehensive pCO2 data set based on voluntary observing ship (VOS) measurements in the western English Channel (WEC). We subsequently estimated surface pCO2 and air–sea CO2 fluxes in northwestern European continental shelf waters using multiple linear regressions (MLRs) from remotely sensed sea surface temperature (SST), chlorophyll a concentration (Chl a), wind speed (WND), photosynthetically active radiation (PAR) and modeled mixed layer depth (MLD). We developed specific MLRs for the seasonally stratified northern WEC (nWEC) and the permanently well-mixed southern WEC (sWEC) and calculated surface pCO2 with uncertainties of 17 and 16 μatm, respectively. We extrapolated the relationships obtained for the WEC based on the 2011–2013 data set (1) temporally over a decade and (2) spatially in the adjacent Celtic and Irish seas (CS and IS), two regions which exhibit hydrographical and biogeochemical characteristics similar to those of WEC waters. We validated these extrapolations with pCO2 data from the SOCAT and LDEO databases and obtained good agreement between modeled and observed data. On an annual scale, seasonally stratified systems acted as a sink of CO2 from the atmosphere of −0.6 ± 0.3, −0.9 ± 0.3 and −0.5 ± 0.3 mol C m−2 yr−1 in the northern Celtic Sea, southern Celtic sea and nWEC, respectively, whereas permanently well-mixed systems acted as source of CO2 to the atmosphere of 0.2 ± 0.2 and 0.3 ± 0.2 mol C m−2 yr−1 in the sWEC and IS, respectively. Air–sea CO2 fluxes showed important inter-annual variability resulting in significant differences in the intensity and/or direction of annual fluxes. We scaled the mean annual fluxes over these provinces for the last decade and obtained the first annual average uptake of −1.11 ± 0.32 Tg C yr−1 for this part of the northwestern European continental shelf. Our study showed that combining VOS data with satellite observations can be a powerful tool to estimate and extrapolate air–sea CO2 fluxes in sparsely sampled area.

Attribution of Atmospheric Sulfur Dioxide over the English Channel to Dimethylsulfide and Changing Ship Emissions

Atmospheric sulfur dioxide (SO2) was measured continuously from the Penlee Point Atmospheric Observatory(PPAO) near Plymouth, United Kingdom between May 2014 and November 2015. This coastal site is exposed to marine air across a wide wind sector. The predominant southwesterly winds carry relatively clean background Atlantic air. In contrast, air from the southeast is heavily influenced by exhaust plumes from ships in the English Channel as well as near the Plymouth Sound. New International Maritime Organization (IMO) regulation came into force in January 2015 to reduce sulfur emissions tenfold in Sulfur Emission Control Areas such as the English Channel. Our observations suggest a three-fold reduction from 2014 to 2015 in ship-emitted SO2 from that direction. Apparent fuel sulfur content calculated from coincidental SO2 and carbon dioxide (CO2) peaks from local ship plum es show a high level of compliance to the IMO regulation (> 95 %) in both years. Dimethylsulfide (DMS) is an important source of atmospheric SO2 even in this semi-polluted region. The relative contribution of DMS oxidation to the SO2 burden over the English Channel increased from ~ 1/3 in 2014 to ~ 1/2 in 2015 due to the reduction in ship sulfur emissions. Our diel analysis suggests that SO2 is removed from the marine atmospheric boundary layer in about half a day, with dry deposition to the ocean accounting for a quarter of the total loss.

Wave height analysis from 10 years of observations in the Norwegian Sea

Large waves pose risks to ships, offshore structures, coastal infrastructure and ecosystems. This paper analyses 10 years of in-situ measurements of significant wave height (Hs) and maximum wave height (Hmax) from the ocean weather ship Polarfront in the Norwegian Sea. During the period 2000 to 2009, surface elevation was recorded every 0.59 s during sampling periods of 30 min. The Hmax observations scale linearly with Hs on average. A widely-used empirical Weibull distribution is found to estimate average values of Hmax/H s and Hmax better than a Rayleigh distribution, but tends to underestimate both for all but the smallest waves. In this paper we propose a modified Rayleigh distribution which compensates for the heterogeneity of the observed dataset: the distribution is fitted to the whole dataset and improves the estimate of the largest waves. Over the 10-year period, the Weibull distribution approximates the observed Hs and Hmax well, and an exponential function can be used to predict the probability distribution function of the ratio Hmax/Hs. However, the Weibull distribution tends to underestimate the occurrence of extremely large values of Hs and Hmax. The persistence of Hs and Hmax in winter is also examined. Wave fields with Hs > 12 m and Hmax > 16 m do not last longer than 3 h. Low-to-moderate wave heights that persist for more than 12 h dominate the relationship of the wave field with the winter NAO index over 2000–2009. In contrast, the inter-annual variability of wave fields with Hs > 5.5 m or Hmax > 8.5 m and wave fields persisting over ~2.5 days is not associated with the winter NAO index.

Changes in significant and maximum wave heights in the Norwegian Sea

This paper analyses 10 years of in-situ measurements of significant wave height (Hs) and maximum wave height (Hmax) from the ocean weather ship Polarfront in the Norwegian Sea. The 30-minute Ship-Borne Wave Recorder measurements of Hmax and Hs are shown to be consistent with theoretical wave distributions. The linear regression between Hmax and Hs has a slope of 1.53. Neither Hs nor Hmax show a significant trend in the period 2000–2009. These data are combined with earlier observations. The long-term trend over the period 1980–2009 in annual Hs is 2.72 ± 0.88 cm/year. Mean Hs and Hmax are both correlated with the North Atlantic Oscillation (NAO) index during winter. The correlation with the NAO index is highest for the more frequently encountered (75th percentile) wave heights. The wave field variability associated with the NAO index is reconstructed using a 500-year NAO index record. Hs and H max are found to vary by up to 1.42 m and 3.10 m respectively over the 500-year period. Trends in all 30-year segments of the reconstructed wave field are lower than the trend in the observations during 1980–2009. The NAO index does not change significantly in 21st century projections from CMIP5 climate models under scenario RCP85, and thus no NAO-related changes are expected in the mean and extreme wave fields of the Norwegian Sea.

Plankton populations at the bifurcation of the North Pacific Current

As the eastward-flowing North Pacific Current approaches the North American continent it bifurcates into the southward-flowing California Current and the northward-flowing Alaska Current. This bifurcation occurs in the south-eastern Gulf of Alaska and can vary in position. Dynamic height data from Project Argo floats have recently enabled the creation of surface circulation maps which show the likely position of the bifurcation; during 2002 it was relatively far north at 53 degrees N then, during early 2003, it moved southwards to a more normal position at 45 degrees N. Two ship-of-opportunity transects collecting plankton samples with a Continuous Plankton Recorder across the Gulf of Alaska were sampled seasonally during 2002 and 2003. Their position was dependent on the commercial ship's operations; however, most transects sampled across the bifurcation. We show that the oceanic plankton differed in community composition according to the current system they occurred in during spring and fall of 2002 and 2003, although winter populations were more mixed. Displacement of the plankton communities could have impacts on the plankton's reproduction and development if they use cues such as day length, and also on foraging of higher trophic-level organisms that use particular regions of the ocean if the nutritional value of the communities is different. Although we identify some indicator taxa for the Alaska and California currents, functional differences in the plankton communities on either side of the bifurcation need to be better established to determine the impacts of bifurcation movement on the ecosystems of the north-east Pacific.

Volcanic ash fuels anomalous plankton bloom in subarctic northeast Pacific

Using multiple lines of evidence, we demonstrate that volcanic ash deposition in August 2008 initiated one of the largest phytoplankton blooms observed in the subarctic North Pacific. Unusually widespread transport from a volcanic eruption in the Aleutian Islands, Alaska deposited ash over much of the subarctic NE Pacific, followed by large increases in satellite chlorophyll. Surface ocean pCO2, pH, and fluorescence reveal that the bloom started a few days after ashfall. Ship-based measurements showed increased dominance by diatoms. This evidence points toward fertilization of this normally iron-limited region by ash, a relatively new mechanism proposed for iron supply to the ocean. The observations do not support other possible mechanisms. Extrapolation of the pCO2 data to the area of the bloom suggests a modest ∼0.01 Pg carbon export from this event, implying that even large-scale iron fertilization at an optimum time of year is not very efficient at sequestering atmospheric CO2.

Development and validation of a shipboard system for measuring high-resolution vertical profiles of aqueous dimethylsulfide concentrations using chemical ionization mass spectrometry

A sampling and analytical system has been developed for shipboard measurements of high-resolution vertical profiles of the marine trace gas dimethylsulfide (DMS). The system consists of a tube attached to a CTD with a peristaltic pump on deck that delivers seawater to a membrane equilibrator and atmospheric pressure chemical ionization mass spectrometer (Eq-APCIMS). This allows profiling DMS concentrations to a depth of 50 m, with a depth resolution of 1.3-2 m and a detection limit of nearly 0.1 nmol L-1. The seawater is also plumbed to allow parallel operation of additional continuous instruments, and simultaneous collection of discrete samples for complementary analyses. A valve alternates delivery of seawater from the vertical profiler and the ship�s underway intake, thereby providing high-resolution measurements in both the vertical and horizontal dimensions. Tests conducted on various cruises in the Mediterranean Sea, Atlantic, Indian, and Pacific Oceans show good agreement between the Eq-APCIMS measurements and purge and trap gas chromatography with flame photometric detection (GC-FPD) and demonstrate that the delivery of seawater from the underway pump did not significantly affect endogenous DMS concentrations. Combination of the continuous flow DMS analysis with high-frequency hydrographic, optical, biological and meteorological measurements will greatly improve the spatial/temporal resolution of seagoing measurements and improve our understanding of DMS cycling.

Space-based lidar measurements of global ocean carbon stocks

Global ocean phytoplankton biomass (C-phyto) and total particulate organic carbon (POC) stocks have largely been characterized from space using passive ocean color measurements. A space-based light detection and ranging (lidar) system can provide valuable complementary observations for C-phyto and POC assessments, with benefits including day-night sampling, observations through absorbing aerosols and thin cloud layers, and capabilities for vertical profiling through the water column. Here we use measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to quantify global C-phyto and POC from retrievals of subsurface particulate backscatter coefficients (b(bp)). CALIOP b(bp) data compare favorably with airborne, ship-based, and passive ocean data and yield global average mixed-layer standing stocks of 0.44 Pg C for C-phyto and 1.9 Pg for POC. CALIOP-based C-phyto and POC data exhibit global distributions and seasonal variations consistent with ocean plankton ecology. Our findings support the use of spaceborne lidar measurements for advancing understanding of global plankton systems.

Foraging success of biological Levy flights recorded in situ

It is an open question how animals find food in dynamic natural environments where they possess little or no knowledge of where resources are located. Foraging theory predicts that in environments with sparsely distributed target resources, where forager knowledge about resources’ locations is incomplete, Lévy flight movements optimize the success of random searches. However, the putative success of Lévy foraging has been demonstrated only in model simulations. Here, we use high-temporal-resolution Global Positioning System (GPS) tracking of wandering (Diomedea exulans) and black-browed albatrosses (Thalassarche melanophrys) with simultaneous recording of prey captures, to show that both species exhibit Lévy and Brownian movement patterns. We find that total prey masses captured by wandering albatrosses during Lévy movements exceed daily energy requirements by nearly fourfold, and approached yields by Brownian movements in other habitats. These results, together with our reanalysis of previously published albatross data, overturn the notion that albatrosses do not exhibit Lévy patterns during foraging, and demonstrate that Lévy flights of predators in dynamic natural environments present a beneficial alternative strategy to simple, spatially intensive behaviors. Our findings add support to the possibility that biological Lévy flight may have naturally evolved as a search strategy in response to sparse resources and scant information.

A new approach for objective identification of turns and steps in organism movement data relevant to random walk modelling

1. A first step in the analysis of complex movement data often involves discretisation of the path into a series of step-lengths and turns, for example in the analysis of specialised random walks, such as Lévy flights. However, the identification of turning points, and therefore step-lengths, in a tortuous path is dependent on ad-hoc parameter choices. Consequently, studies testing for movement patterns in these data, such as Lévy flights, have generated debate. However, studies focusing on one-dimensional (1D) data, as in the vertical displacements of marine pelagic predators, where turning points can be identified unambiguously have provided strong support for Lévy flight movement patterns. 2. Here, we investigate how step-length distributions in 3D movement patterns would be interpreted by tags recording in 1D (i.e. depth) and demonstrate the dimensional symmetry previously shown mathematically for Lévy-flight movements. We test the veracity of this symmetry by simulating several measurement errors common in empirical datasets and find Lévy patterns and exponents to be robust to low-quality movement data. 3. We then consider exponential and composite Brownian random walks and show that these also project into 1D with sufficient symmetry to be clearly identifiable as such. 4. By extending the symmetry paradigm, we propose a new methodology for step-length identification in 2D or 3D movement data. The methodology is successfully demonstrated in a re-analysis of wandering albatross Global Positioning System (GPS) location data previously analysed using a complex methodology to determine bird-landing locations as turning points in a Lévy walk. For this high-resolution GPS data, we show that there is strong evidence for albatross foraging patterns approximated by truncated Lévy flights spanning over 3·5 orders of magnitude. 5. Our simple methodology and freely available software can be used with any 2D or 3D movement data at any scale or resolution and are robust to common empirical measurement errors. The method should find wide applicability in the field of movement ecology spanning the study of motile cells to humans.

The biogeochemical structuring role of horizontal stirring: Lagrangian perspectives on iron delivery downstream of the Kerguelen Plateau

Field campaigns are instrumental in providing ground truth for understanding and modeling global ocean biogeochemical budgets. A survey however can only inspect a fraction of the global oceans, typically a region hundreds of kilometers wide for a temporal window of the order of (at most) several weeks. This spatiotemporal domain is also the one in which the mesoscale activity induces through horizontal stirring a strong variability in the biogeochemical tracers, with ephemeral, local contrasts which can easily mask the regional and seasonal gradients. Therefore, whenever local in situ measures are used to infer larger-scale budgets, one faces the challenge of identifying the mesoscale structuring effect, if not simply to filter it out. In the case of the KEOPS2 investigation of biogeochemical responses to natural iron fertilization, this problem was tackled by designing an adaptive sampling strategy based on regionally optimized multisatellite products analyzed in real time by specifically designed Lagrangian diagnostics. This strategy identified the different mesoscale and stirring structures present in the region and tracked the dynamical frontiers among them. It also enabled back trajectories for the ship-sampled stations to be estimated, providing important insights into the timing and pathways of iron supply, which were explored further using a model based on first-order iron removal. This context was essential for the interpretation of the field results. The mesoscale circulation-based strategy was also validated post-cruise by comparing the Lagrangian maps derived from satellites with the patterns of more than one hundred drifters, including some adaptively released during KEOPS2 and a subsequent research voyage. The KEOPS2 strategy was adapted to the specific biogeochemical characteristics of the region, but its principles are general and will be useful for future in situ biogeochemical surveys.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Could benzalkonium chloride be a suitable alternative to mercuric chloride for preservation of seawater samples?

Instrumental equipment unsuitable or unavailable for fieldwork as well as lack of ship space can necessitate the preservation of seawater samples prior to analysis in a shore-based laboratory. Mercuric chloride (HgCl2/ is routinely used for such preservation, but its handling and subsequent disposal incur environmental risks and significant expense. There is therefore a strong motivation to find less hazardous alternatives. Benzalkonium chloride (BAC) has been used previously as microbial inhibitor for freshwater samples. Here, we assess the use of BAC for marine samples prior to the measurement of oxygen-to-argon (O2 = Ar) ratios, as used for the determination of biological net community production. BAC at a concentration of 50 mg dm-3 inhibited microbial activity for at least 3 days in samples tested with chlorophyll a (Chl a) concentrations up to 1 mgm-3. BAC concentrations of 100 and 200 mg dm

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.