Temporal changes in total and size-fractioned chlorophyll-a in surface waters of three provinces in the Atlantic Ocean (September to November) between 2003 and 2010

Phytoplankton total chlorophyll concentration (TCHLa) and phytoplankton size structure are two important ecological indicators in biological oceanography. Using high performance liquid chromatography (HPLC) pigment data, collected from surface waters along the Atlantic Meridional Transect (AMT), we examine temporal changes in TCHLa and phytoplankton size class (PSC: micro-, nano- and pico-phytoplankton) between 2003 and 2010 (September to November cruises only), in three ecological provinces of the Atlantic Ocean. The HPLC data indicate no significant change in TCHLa in northern and equatorial provinces, and an increase in the southern province. These changes were not significantly different to changes in TCHLa derived using satellite ocean-colour data over the same study period. Despite no change in AMT TCHLa in northern and equatorial provinces, significant differences in PSC were observed, related to changes in key diagnostic pigments (fucoxanthin, peridinin, 19′-hexanoyloxyfucoxanthin and zeaxanthin), with an increase in small cells (nano- and pico-phytoplankton) and a decrease in larger cells (micro-phytoplankton). When fitting a three-component model of phytoplankton size structure — designed to quantify the relationship between PSC and TCHLa to each AMT cruise, model parameters varied over the study period. Changes in the relationship between PSC and TCHLa have wide implications in ecology and marine biogeochemistry, and provide key information for the development and use of empirical ocean-colour algorithms. Results illustrate the importance of maintaining a time-series of in-situ observations in remote regions of the ocean, such as that acquired in the AMT programme.

On the Potential of Surfers to Monitor Environmental Indicators in the Coastal Zone

The social and economic benefits of the coastal zone make it one of the most treasured environments on our planet. Yet it is vulnerable to increasing anthropogenic pressure and climate change. Coastal management aims to mitigate these pressures while augmenting the socio-economic benefits the coastal region has to offer. However, coastal management is challenged by inadequate sampling of key environmental indicators, partly due to issues relating to cost of data collection. Here, we investigate the use of recreational surfers as platforms to improve sampling coverage of environmental indicators in the coastal zone. We equipped a recreational surfer, based in the south west United Kingdom (UK), with a temperature sensor and Global Positioning System (GPS) device that they used when surfing for a period of one year (85 surfing sessions). The temperature sensor was used to derive estimates of sea-surface temperature (SST), an important environmental indicator, and the GPS device used to provide sample location and to extract information on surfer performance. SST data acquired by the surfer were compared with data from an oceanographic station in the south west UK and with satellite observations. Our results demonstrate: (i) high-quality SST data can be acquired by surfers using low cost sensors; and (ii) GPS data can provide information on surfing performance that may help motivate data collection by surfers. Using recent estimates of the UK surfing population, and frequency of surfer participation, we speculate around 40 million measurements on environmental indicators per year could be acquired at the UK coastline by surfers. This quantity of data is likely to enhance coastal monitoring and aid UK coastal management. Considering surfing is a world-wide sport, our results have global implications and the approach could be expanded to other popular marine recreational activities for coastal monitoring of environmental indicators.

Can benthic community structure be used to predict the process of bioturbation in real ecosystems

Disentangling the roles of environmental change and natural environmental variability on biologically mediated ecosystem processes is paramount to predict future marine ecosystem functioning. Bioturbation, the biogenic mixing of sediments, has a regulating role in marine biogeochemical processes. However, our understanding of bioturbation as a community level process and of its environmental drivers is still limited by loose use of terminology, and a lack of consensus about what bioturbation is. To help resolve these challenges, this empirical study investigated the links between four different attributes of bioturbation (bioturbation depth, activity and distance, and biodiffusive transport); the ability of an index of bioturbation (BPc) to predict each of them; and their relation to seasonality, in a shallow coastal system – the Western Channel Observatory, UK. Bioturbation distance depended on changes in benthic community structure, while the other three attributes were more directly influenced by seasonality in food availability. In parallel, BPc successfully predicted bioturbation distance but not the other attributes of bioturbation. This study therefore highlights that community bioturbation results from this combination of processes responding to environmental variability at different time-scales. However, community level measurements of bioturbation across environmental variability are still scarce, and BPc is calculated using commonly available data on benthic community structure and the functional classification of invertebrates. Therefore, BPc could be used to support the growth of landscape scale bioturbation research, but future uses of the index need to consider which bioturbation attributes the index actually predicts. As BPc predicts bioturbation distance, estimated here using a random-walk model applicable to community settings, studies using either of the metrics should be directly comparable and contribute to a more integrated future for bioturbation research.

Influence of light in the mixed-layer on the parameters of a three-component model of phytoplankton size class

Phytoplankton size structure is an important indicator of the state of the pelagic ecosystem. Stimulated by the paucity of in situ observations on size structure, and by the sampling advantages of autonomous remote platforms, new efforts are being made to infer the size-structure of the phytoplankton from oceanographic variables that may be measured at high temporal and spatial resolution, such as total chlorophyll concentration. Large-scale analysis of in situ data has revealed coherent relationships between size-fractionated chlorophyll and total chlorophyll that can be quantified using the three-component model of Brewin et al. (2010). However, there are variations surrounding these general relationships. In this paper, we first revise the three-component model using a global dataset of surface phytoplankton pigment measurements. Then, using estimates of the average irradiance in the mixed-layer, we investigate the influence of ambient light on the parameters of the three-component model. We observe significant relationships between model parameters and the average irradiance in the mixed-layer, consistent with ecological knowledge. These relationships are incorporated explicitly into the three-component model to illustrate variations in the relationship between size-structure and total chlorophyll, ensuing from variations in light availability. The new model may be used as a tool to investigate modifications in size-structure in the context of a changing climate.

The effect of the North Atlantic Subpolar Front as a boundary in pelagic biogeography decreases with increasing depth and organism size

Broad-scale patterns in the distribution of deep-sea pelagic species and communities are poorly known. An important question is whether biogeographic boundaries identified from surface features are important in the deep mesopelagic and bathypelagic. We present community analyses of discrete-depth samples of mesozooplankton and micronekton to full-ocean depth collected in the area where the Mid-Atlantic Ridge is crossed by the Subpolar Front. The results show that the distributional discontinuity associated with the front, which is strong near the surface, decreases with increasing depth. Both the frontal separation near the surface and the community convergence at increasing depths were clearer for mesozooplankton than for micronekton.

Drivers and effects of Karenia mikimotoi blooms in the western English Channel

Naturally occurring red tides and harmful algal blooms (HABs) are of increasing importance in the coastal environment and can have dramatic effects on coastal benthic and epipelagic communities worldwide. Such blooms are often unpredictable, irregular or of short duration, and thus determining the underlying driving factors is problematic. The dinoflagellate Karenia mikimotoi is an HAB, commonly found in the western English Channel and thought to be responsible for occasional mass finfish and benthic mortalities. We analysed a 19-year coastal time series of phytoplankton biomass to examine the seasonality and interannual variability of K. mikimotoi in the western English Channel and determine both the primary environmental drivers of these blooms as well as the effects on phytoplankton productivity and oxygen conditions. We observed high variability in timing and magnitude of K. mikimotoi blooms, with abundances reaching >1000 cells mL�1 at 10 m depth, inducing up to a 12-fold increase in the phytoplankton carbon content of the water column. No long-term trends in the timing or magnitude of K. mikimotoi abundance were evident from the data. Key driving factors were identified as persistent summertime rainfall and the resultant input of low-salinity high-nutrient river water. The largest bloom in 2009 was associated with highest annual primary production and led to considerable oxygen depletion at depth, most likely as a result of enhanced biological breakdown of bloom material; however, this oxygen depletion may not affect zooplankton. Our data suggests that K. mikimotoi blooms are not only a key and consistent feature of western English Channel productivity, but importantly can potentially be predicted from knowledge of rainfall or river discharge.

Temporal variability in total, micro- and nano-phytoplankton primary production at a coastal site in the Western English Channel

Primary productivity and subsequent carbon cycling in the coastal zone have a significant impact on the global carbon budget. It is currently unclear how anthropogenic activity could alter these budgets but long term coastal time series of hydrological, biogeochemical and biological measurements represent a key means to better understand past drivers, and hence to predicting future seasonal and inter-annual variability in carbon fixation in coastal ecosystems. An 8-year time series of primary production from 2003 to 2010, estimated using a recently developed absorption-based algorithm, was used to determine the nature and extent of change in primary production at a coastal station (L4) in the Western English Channel (WEC). Analysis of the seasonal and inter-annual variability in production demonstrated that on average, nano- and pico-phytoplankton account for 48% of the total carbon fixation and micro-phytoplankton for 52%. A recent decline in the primary production of nano- and pico-phytoplankton from 2005 to 2010 was observed, corresponding with a decrease in winter nutrient concentrations and a decrease in the biomass of Phaeocystis sp. Micro-phytoplankton primary production (PPM) remained relatively constant over the time series and was enhanced in summer during periods of high precipitation. Increases in sea surface temperature, and decreases in wind speeds and salinity were associated with later spring maxima in PPM. Together these trends indicate that predicted increases in temperature and decrease in wind speeds in future would drive later spring production whilst predicted increases in precipitation would also continue these blooms throughout the summer at this site.

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.

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.

Surface Salinity in the North Atlantic Subtropical Gyre During the STRASSE/SPURS Summer 2012 Cruise

We investigated a 100 × 100 km high-salinity region of the North Atlantic subtropical gyre during the Sub-Tropical Atlantic Surface Salinity Experiment/Salinity Processes in the Upper-ocean Regional Study (STRASSE/SPURS) cruise from August 21, 2012, to September 9, 2012. Results showed great variability in sea surface salinity (SSS; over 0.3 psu) in the mesoscale, over 7 cm of total evaporation, and little diapycnal mixing below 36 m depth, the deepest mixed layers encountered. Strong currents in the southwestern part of the domain, and the penetration of freshwater, suggest that advection contributed greatly to salinity evolution. However, it was further observed that a smaller cyclonic structure tucked between the high SSS band and the strongest currents contributed to the transport of high SSS water along a narrow front. Cross-frontal transport by mixing is also a possible cause of summertime reduction of SSS. The observed structure was also responsible for significant southward salt transport over more than 200 km.

Lateral diffusivity coefficients from the dynamics of a SF6 patch in a coastal environment

The dispersion of a patch of the tracer sulfur hexafluoride (SF6) is used to assess the lateral diffusivity in the coastal waters of the western part of the Gulf of Lion (GoL), northwestern Mediterranean Sea, during the Latex10 experiment (September 2010). Immediately after the release, the spreading of the patch is associated with a strong decrease of the SF6 concentrations due to the gas exchange from the ocean to the atmosphere. This has been accurately quantified, evidencing the impact of the strong wind conditions during the first days of this campaign. Few days after the release, as the atmospheric loss of SF6 decreased, lateral diffusivity coefficient at spatial scales of 10 km has been computed using two approaches. First, the evolution of the patch with time was combined with a diffusion-strain model to obtain estimates of the strain rate (γ = 2.5 10- 6 s- 1) and of the lateral diffusivity coefficient (Kh = 23.2 m2s− 1). Second, a steady state model was applied, showing Kh values similar to the previous method after a period of adjustment between 2 and 4.5 days. This implies that after such period, our computation of Kh becomes insensitive to the inclusion of further straining of the patch. Analysis of sea surface temperature satellite imagery shows the presence of a strong front in the study area. The front clearly affected the dynamics within the region and thus the temporal evolution of the patch. Our results are consistent with previous studies in open ocean and demonstrate the success and feasibility of those methods also under small-scale, rapidly-evolving dynamics typical of coastal environments.

20 Years of the Atlantic Meridional Transect — AMT

The AMT (www.amt-uk.org) is a multidisciplinary programme which undertakes biological, chemical, and physical oceanographic research during an annual voyage between the UK and a destination in the South Atlantic such as the Falkland Islands,South Africa, or Chile. This transect of >12,000 km crosses a range of ecosystems from subpolar to tropical, from euphotic shelf seas and upwelling systems, to oligotrophic mid-ocean gyres. The year 2015 has seen two milestones in the history of the AMT: the achievement of 20 years of this unique ocean going programme and the departure of the 25th cruise on the 15th of September. Both of these events were celebrated in June this year with an open science conference hosted by the Plymouth Marine Laboratory (PML) and will be further documented in a special issue of Progress in Oceanography which is planned for publication in 2016. Since 1995, the 25 research cruises have involved 242 sea-going scientists from 66 institutes representing 22 countries.

Initial Examination of AltiKa's Individual Echoes

The AltiKa altimeter records the reflection of Ka-band radar pulses from the Earth’s surface, with the commonly used waveform product involving the summation of 96 returns to provide average echoes at 40 Hz. Occasionally there are one-second recordings of the complex individual echoes (IEs), which facilitate the evaluation of on-board processing and offer the potential for new processing strategies. Our investigation of these IEs over the ocean confirms the on-board operations, whilst noting that data quantization limits the accuracy in the thermal noise region. By constructing average waveforms from 32 IEs at a time, and applying an innovative subwaveform retracker, we demonstrate that accurate height and wave height information can be retrieved from very short sections of data. Early exploration of the complex echoes reveals structure in the phase information similar to that noted for Envisat’s IEs.

Metocean Comparisons of Jason-2 and AltiKa—A Method to Develop a New Wind Speed Algorithm

As well as range, the AltiKa altimeter provides estimates of wave height, Hs and normalized backscatter, s0, that need to be assessed prior to statistics based on them being included in climate databases. An analysis of crossovers with the Jason-2 altimeter shows AltiKa Hs values to be biased high by only »0.05m, with a standard deviation (s.d.) of »0.1m for seven-point averages. AltiKa’s s 0 values are 2.5–3 dB less than those from Jason-2, with a s.d. of »0.3 dB, with these relatively large mismatches to be expected as AltiKa measures a different part of the spectrum of sea surface roughness. A new wind speed algorithm is developed through matchinghistogram of s0 values to that for Jason-2 wind speeds. The algorithm is robust to the use of short durations of data, with a consistency at roughly the 0.1 m/s level. Incorporation of Hs as a secondary input reduces the assessed error at crossovers from 0.82 m/s to 0.71 m/s. A comparison across all altimeter frequencies used to date demonstrates that the lowest wind speeds preferentially develop the shortest scales of roughness.

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.