Nutrient regimes control phytoplankton ecophysiology in the South Atlantic

Fast Repetition Rate fluorometry (FRRf) measurements of phytoplankton photophysiology from an across-basin South Atlantic cruise (as part of the GEOTRACES programme) characterised two dominant ecophysiological regimes which were interpreted on the basis of nutrient limitation. South of the South Subtropical Convergence (SSTC) in the northern sub-Antarctic sector of the Antarctic Circumpolar Current (ACC) in the Eastern Atlantic Basin, waters are characterised by elevated chlorophyll concentrations, a dominance by larger phytoplankton cells, and low apparent photochemical efficiency (F-v/F-m). Shipboard 24 h iron (Fe) addition incubation experiments confirmed that Fe stress was primarily responsible for the low F-v/F-m, with Fe addition to these waters, either within the artificial bottle additions or naturally occurring downstream enrichment from Gough Island, significantly increasing F-v/F-m values. To the north of the SSTC at the southern boundary of the South Atlantic Gyre, phytoplankton are characterised by high values of F-v/F-m which, coupled with the low macronutrient concentrations and increased presence of picocyanobacteria, are interpreted as conditions of Fe replete, balanced macronutrient-limited growth. Spatial correlation was found between F-v/F-m and Fe: nitrate ratios, supporting the suggestion that the relative supply ratios of these two nutrients can control patterns of limitation and consequently the ecophysiology of phytoplankton in subtropical gyre and ACC regimes.

Fine-scale nutrient and carbonate system dynamics around cold-water coral reefs in the northeast Atlantic.

Ocean acidification has been suggested as a serious threat to the future existence of cold-water corals (CWC). However, there are few fine-scale temporal and spatial datasets of carbonate and nutrients conditions available for these reefs, which can provide a baseline definition of extant conditions. Here we provide observational data from four different sites in the northeast Atlantic that are known habitats for CWC. These habitats differ by depth and by the nature of the coral habitat. At depths where CWC are known to occur across these sites the dissolved inorganic carbon ranged from 2088 to 2186 μmol kg−1, alkalinity ranged from 2299 to 2346 μmol kg−1, and aragonite Ω ranged from 1.35 to 2.44. At two sites fine-scale hydrodynamics caused increased variability in the carbonate and nutrient conditions over daily time-scales. The observed high level of variability must be taken into account when assessing CWC sensitivities to future environmental change.

Response of an Arctic Sediment Nitrogen Cycling Community to Increased CO2

Ocean acidification influences sediment/water nitrogen fluxes, possibly by impacting on the microbial process of ammonia oxidation. To investigate this further, undisturbed sediment cores collected from Ny Alesund harbour (Svalbard) were incubated with seawater adjusted to CO2 concentrations of 380, 540, 760, 1,120 and 3,000 μatm. DNA and RNA were extracted from the sediment surface after 14 days' exposure and the abundance of bacterial and archaeal ammonia oxidising (amoA) genes and transcripts quantified using quantitative polymerase chain reaction. While there was no change to the abundance of bacterial amoA genes, an increase to 760 μatm pCO2 reduced the abundance of bacterial amoA transcripts by 65 %, and this was accompanied by a shift in the composition of the active community. In contrast, archaeal amoA gene and transcript abundance both doubled at 3,000 μatm, with an increase in species richness also apparent. This suggests that ammonia oxidising bacteria and archaea in marine sediments have different pH optima, and the impact of elevated CO2 on N cycling may be dependent on the relative abundances of these two major microbial groups. Further evidence of a shift in the balance of key N cycling groups was also evident: the abundance of nirS-type denitrifier transcripts decreased alongside bacterial amoA transcripts, indicating that NO3 − produced by bacterial nitrification fuelled denitrification. An increase in the abundance of Planctomycete-specific 16S rRNA, the vastmajority of which grouped with known anammox bacteria, was also apparent at 3,000 μatm pCO2. This could indicate a possible shift from coupled nitrification–denitrification to anammox activity at elevated CO2.

Impacts of bioturbation on temporal variation in bacterial and archaeal nitrogen-cycling gene abundance in coastal sediments

In marine environments, macrofauna living in or on the sediment surface may alter the structure, diversity and function of benthic microbial communities. In particular, microbial nitrogen (N)-cycling processes may be enhanced by the activity of large bioturbating organisms. Here, we study the effect of the burrowing mud shrimp Upogebia deltaura upon temporal variation in the abundance of genes representing key N-cycling functional guilds. The abundance of bacterial genes representing different N-cycling guilds displayed different temporal patterns in burrow sediments in comparison with surface sediments, suggesting that the burrow provides a unique environment where bacterial gene abundances are influenced directly by macrofaunal activity. In contrast, the abundances of archaeal ammonia oxidizers varied temporally but were not affected by bioturbation, indicating differential responses between bacterial and archaeal ammonia oxidizers to environmental physicochemical controls. This study highlights the importance of bioturbation as a control over the temporal variation in nitrogen-cycling microbial community dynamics within coastal sediments.

Variation in elemental stoichiometry of the marine diatomThalassiosira weissflogii(Bacillariophyceae) in response to combined nutrient stress and changes in carbonate chemistry

The combined consequences of the multi-stressors of pH and nutrient availability upon the growth of a marine diatom were investigated. Thalassiosira weissflogii was grown in N- or P-limited batch culture in sealed systems, with pH commencing at 8.2 (extant conditions) or 7.6 (ocean acidification [OA] conditions), and then pH was allowed to either drift with growth, or was held fixed. Results indicated that within the pH range tested, the stability of environmental pH rather than its value (i.e., OA vs. extant) fundamentally influenced biomass accumul-ation and C:N:P stoichiometry. Despite large changes in total alkalinity in the fixed pH systems, final biomass production was consistently greater in these systems than that in drifting pH systems. In drift systems, pH increased to exceed pH 9.5, a level of alkalinity that was inhibitory to growth. No statis-tically significant differences between pH treatments were measured for N:C, P:C or N:P ratios during nutrient-replete growth, although the diatom expre-ssed greater plasticity in P:C and N:P ratios than in N:C during this growth phase. During nutrient-deplete conditions, the capacity for uncoupled carbon fixa-tion at fixed pH was considerably greater than that measured in drift pH systems, leading to strong contrasts in C:N:P stoichiometry between these treatments. Whether environmental pH was stable or drifted directly influenced the extent of physiological stress. In contrast, few distinctions could be drawn between extant versus OA conditions for cell physiology.

Interaction Effects of Light, Temperature and Nutrient Limitations (N, P and Si) on Growth, Stoichiometry and Photosynthetic Parameters of the Cold-Water Diatom Chaetoceros wighamii

Light (20-450 μmol photons m^-2 s^-1), temperature (3-11°C) and inorganic nutrient composition (nutrient replete and N, P and Si limitation) were manipulated to study their combined influence on growth, stoichiometry (C:N:P:Chl a) and primary production of the cold water diatom Chaetoceros wighamii. During exponential growth, the maximum growth rate (~0.8 d^-1) was observed at high temperture and light; at 3°C the growth rate was ~30% lower under similar light conditions. The interaction effect of light and temperature were clearly visible from growth and cellular stoichiometry. The average C:N:P molar ratio was 80:13:1 during exponential growth, but the range, due to different light acclimation, was widest at the lowest temperature, reaching very low C:P (~50) and N:P ratios (~8) at low light and temperature. The C:Chl a ratio had also a wider range at the lowest temperature during exponential growth, ranging 16-48 (weight ratio) at 3°C compared with 17-33 at 11°C. During exponential growth, there was no clear trend in the Chl a normalized, initial slope (α*) of the photosynthesis-irradiance (PE) curve, but the maximum photosynthetic production (P_m) was highest for cultures acclimated to the highest light and temperature. During the stationary growth phase, the stoichiometric relationship depended on the limiting nutrient, but with generally increasing C:N:P ratio. The average photosynthetic quotient (PQ) during exponential growth was 1.26 but decreased to <1 under nutrient and light limitation, probably due to photorespiration. The results clearly demonstrate that there are interaction effects between light, temperature and nutrient limitation, and the data suggests greater variability of key parameters at low temperature. Understanding these dynamics will be important for improving models of aquatic primary production and biogeochemical cycles in a warming climate.

Conceptual Ecological Modelling of Sublittoral Rock Habitats to Inform Indicator Selection

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 1 Report: Rationale and proposed ecological groupings for Level 5 biotopes against which sensitivity assessments would be best undertaken.

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Ocean acidification with (de)eutrophication will alter future phytoplankton growth and succession.

Human activity causes ocean acidification (OA) though the dissolution of anthropogenically generated CO2 into seawater, and eutrophication through the addition of inorganic nutrients. Eutrophication increases the phytoplankton biomass that can be supported during a bloom, and the resultant uptake of dissolved inorganic carbon during photosynthesis increases water-column pH (bloom-induced basification). This increased pH can adversely affect plankton growth. With OA, basification commences at a lower pH. Using experimental analyses of the growth of three contrasting phytoplankton under different pH scenarios, coupled with mathematical models describing growth and death as functions of pH and nutrient status, we show how different conditions of pH modify the scope for competitive interactions between phytoplankton species. We then use the models previously configured against experimental data to explore how the commencement of bloom-induced basification at lower pH with OA, and operating against a background of changing patterns in nutrient loads, may modify phytoplankton growth and competition. We conclude that OA and changed nutrient supply into shelf seas with eutrophication or de-eutrophication (the latter owing to pollution control) has clear scope to alter phytoplankton succession, thus affecting future trophic dynamics and impacting both biogeochemical cycling and fisheries.

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.

Report from an International Nutrient Workshop focusing on Phosphate Analysis

A practical analytical workshop at NIOZ (Royal Netherlands Institute for Sea Research), The Netherlands, was held on 12-15 November 2012. The aim of the workshop was to gain information from the global nutrient analytical community about general problems which arise when measuring nutrients, and then to attempt to investigate these problems in the laboratory, with a small select representative group of International nutrient analysts conducting the lab work. 18 experts were participated and worked simultaneously on four different PO4 gas segmented CFA systems. This report documents the finding of the workshop and describes recommendations based on group consensus which can hopefully assist the larger community of labs worldwide participating in the Inter-Laboratory Comparison RMNS 2012 studies organized by MRI in Japan.

Vertical fluxes and atmospheric cycling of methanol, acetaldehyde, and acetone in a coastal environment

We present here vertical fluxes of methanol, acetaldehyde, and acetone measured directly with eddy covariance (EC) during March to July 2012 near the southwest coast of the UK. The performance of the proton-transfer reaction mass spectrometer (PTR-MS) for flux measurement is characterized, with additional considerations given to the homogeneity and stationarity assumptions required by EC. Concentrations and fluxes of these compounds vary significantly with time of day and wind direction. Higher values of acetaldehyde and acetone are usually observed in the daytime and from the direction of a forested park, most likely due to light-driven emissions from terrestrial plants. Methanol concentration and flux do not demonstrate clear diel variability, suggesting sources in addition to plants. We estimate air–sea exchange and photochemical rates of these compounds, which are compared to measured vertical fluxes. For acetaldehyde, the mean (1�) concentration of 0.13 (0.02) ppb at night may be maintained by oceanic emission, while photochemical destruction outpaces production during the day. Air-sea exchange and photochemistry are probably net sinks of methanol and acetone in this region. Their nighttime concentrations of 0.46 (0.20) and 0.39 (0.08) ppb appear to be affected more by terrestrial emissions and long distance transport, respectively.

Mercury presence and speciation in the South Atlantic Ocean along the 40°S transect

Mercury (Hg) natural biogeochemical cycle is complex and a significant portion of biological and chemical transformation occurs in the marine environment. To better understand the presence and abundance of Hg species in the remote ocean regions, waters of South Atlantic Ocean along 40°S parallel were investigated during UK-GEOTRACES cruise GA10. Total mercury (THg), methylated mercury (MeHg), and dissolved gaseous mercury (DGM) concentrations were determined. The concentrations were very low in the range of pg/L (femtomolar). All Hg species had higher concentration in western than in eastern basin. THg did not appear to be a useful geotracer. Elevated methylated Hg species were commonly associated with low-oxygen water masses and occasionally with peaks of chlorophyll a, both involved with carbon (re)cycling. The overall highest MeHg concentrations were observed in themixed layer (500m) and in the vicinity of the Gough Island. Conversely, DGM concentrations showed distinct layering and differed between the water masses in a nutrient-like manner. DGM was lowest at surface, indicating degassing to the atmosphere, and was highest in the Upper Circumpolar Deep Water, where the oxygen concentration was lowest. DGM increased also in Antarctic Bottom Water. At one station, dimethylmercury was determined and showed increase in region with lowest oxygen saturation. Altogether, our data indicate that the South Atlantic Ocean could be a source of Hg to the atmosphere and that its biogeochemical transformations depend primarily upon carbon cycling and are thereby additionally prone to global ocean change.