Modelling the vertical distribution of eggs of anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus)

Measurements were made of the density and settling velocity of eggs of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus), using a density-gradient column. These results were related to observed vertical distributions of eggs obtained from stratified vertical distribution sampling in the Bay of Biscay. Eggs of both species had slightly positive buoyancy in local seawater throughout most of their development until near hatching, when there was a marked increase in density and they became negatively buoyant. The settling velocity of anchovy eggs, which are shaped as prolate ellipsoids, was close to predictions for spherical particles of equivalent volume. An improved model was developed for prediction of the settling velocity of sardine eggs, which are spherical with a relatively large perivitelline volume; this incorporated permeability of the chorion and adjustment of the density of the perivitelline fluid to ambient seawater. Eggs of both species were located mostly in the top 20 m of the water column, in increasing abundance towards the surface. A sub-surface peak of egg abundance was sometimes observed at the pycnocline, particularly where this was pronounced and associated with a low-salinity surface layer. There was a progressive deepening of the depth distributions for successive stages of egg development. Results from this study can be applied for improved plankton sampling of sardine and anchovy eggs and in modelling studies of their vertical distribution.

Buoyancy measurements and vertical distribution of eggs of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus)

Measurements were made of the density and settling velocity of eggs of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus), using a density-gradient column. These results were related to observed vertical distributions of eggs obtained from stratified vertical distribution sampling in the Bay of Biscay. Eggs of both species had slightly positive buoyancy in local seawater throughout most of their development until near hatching, when there was a marked increase in density and they became negatively buoyant. The settling velocity of anchovy eggs, which are shaped as prolate ellipsoids, was close to predictions for spherical particles of equivalent volume. An improved model was developed for prediction of the settling velocity of sardine eggs, which are spherical with a relatively large perivitelline volume; this incorporated permeability of the chorion and adjustment of the density of the perivitelline fluid to ambient seawater. Eggs of both species were located mostly in the top 20 m of the water column, in increasing abundance towards the surface. A sub-surface peak of egg abundance was sometimes observed at the pycnocline, particularly where this was pronounced and associated with a low-salinity surface layer. There was a progressive deepening of the depth distributions for successive stages of egg development. Results from this study can be applied for improved plankton sampling of sardine and anchovy eggs and in modelling studies of their vertical distribution.

A mechanistic explanation of the Sargasso Sea DMS summer paradox

In the Sargasso Sea, maximum dimethylsulfide (DMS) accumulation occurs in summer, concomitant with the minimum of chlorophyll and 2 months later than its precursor, dimethylsulfoniopropionate (DMSP). This phenomenon is often referred to as the DMS "summer paradox". It has been previously suggested that the main agent triggering this pattern is increasing irradiance leading to light stress-induced DMS release from phytoplankton cells. We have developed a new model describing DMS(P) dynamics in the water column and used it to investigate how and to what extent processes other than light induced DMS exudation from phytoplankton, may contribute to the DMS summer paradox. To do this, we have conceptually divided the DMS "summer paradox" into two components: (1) the temporal decoupling between chlorophyll and DMSP and (2) the temporal decoupling between DMSP and DMS. Our results suggest that it is possible to explain the above cited patterns by means of two different dynamics, respectively: (1) a succession of phytoplankton types in the surface water and (2) the bacterially mediated DMSP(d) to DMS conversion, seasonally varying as a function of nutrient limitation. This work differs from previous modelling studies in that the presented model suggests that phytoplankton light-stress induced processes may only partially explain the summer paradox, not being able to explain the decoupling between DMSP and DMS, which is possibly the more challenging aspect of this phenomenon. Our study, therefore, provides an "alternative" explanation to the summer paradox further underlining the major role that bacteria potentially play in DMS production and fate.

Global sea-to-air flux climatology for bromoform, dibromomethane and methyl iodide

Volatile halogenated organic compounds containing bromine and iodine, which are naturally produced in the ocean, are involved in ozone depletion in both the troposphere and stratosphere. Three prominent compounds transporting large amounts of marine halogens into the atmosphere are bromoform (CHBr3), dibromomethane (CH2Br2) and methyl iodide (CH3I). The input of marine halogens to the stratosphere has been estimated from observations and modelling studies using low-resolution oceanic emission scenarios derived from top-down approaches. In order to improve emission inventory estimates, we calculate data-based high resolution global sea-to-air flux estimates of these compounds from surface observations within the HalOcAt (Halocarbons in the Ocean and Atmosphere) database (https://halocat.geomar.de/). Global maps of marine and atmospheric surface concentrations are derived from the data which are divided into coastal, shelf and open ocean regions. Considering physical and biogeochemical characteristics of ocean and atmosphere, the open ocean water and atmosphere data are classified into 21 regions. The available data are interpolated onto a 1 degrees x 1 degrees grid while missing grid values are interpolated with latitudinal and longitudinal dependent regression techniques reflecting the compounds' distributions. With the generated surface concentration climatologies for the ocean and atmosphere, global sea-to-air concentration gradients and sea-to-air fluxes are calculated. Based on these calculations we estimate a total global flux of 1.5/2.5 Gmol Br yr(-1) for CHBr3, 0.78/0.98 Gmol Br yr(-1) for CH2Br2 and 1.24/1.45 Gmol Br yr(-1) for CH3I (robust fit/ordinary least squares regression techniques). Contrary to recent studies, negative fluxes occur in each sea-to-air flux climatology, mainly in the Arctic and Antarctic regions. "Hot spots" for global polybromomethane emissions are located in the equatorial region, whereas methyl iodide emissions are enhanced in the subtropical gyre regions. Inter-annual and seasonal variation is contained within our flux calculations for all three compounds. Compared to earlier studies, our global fluxes are at the lower end of estimates, especially for bromoform. An under-representation of coastal emissions and of extreme events in our estimate might explain the mismatch between our bottom-up emission estimate and top-down approaches.

Coccolithophore surface distributions in the North Atlantic and their modulation of the air-sea flux of CO2 from 10 years of satellite Earth observation data

Coccolithophores are the primary oceanic phytoplankton responsible for the production of calcium carbonate (CaCO3). These climatically important plankton play a key role in the oceanic carbon cycle as a major contributor of carbon to the open ocean 5 carbonate pump (�50%) and their formation can affect the atmosphere-to-ocean (airsea) uptake of carbon dioxide (CO2) through increasing the seawater partial pressure of CO2 (pCO2). Here we document variations in the areal extent of surface blooms of the globally important coccolithophore, Emiliania huxleyi, in the North Atlantic over a 10-year period (1998–2007), using Earth observation data from the Sea-viewing Wide 10 Field of view Sensor (SeaWiFS).We calculate the annual mean surface areal coverage of E. huxleyi in the North Atlantic to be 474 000±119 000km2 yr−1, which results in a net CaCO3 production of 0.62±0.15 Tg CaCO3 carbon per year. However, this surface coverage and net production can fluctuate by −54/+81% about these mean values and are strongly correlated with the El Ni˜no/Southern Oscillation (ENSO) climate os15 cillation index (r =0.75, p<0.02). Our analysis evaluates the spatial extent over which the E. huxleyi blooms in the North Atlantic can increase the pCO2 and thus decrease the localised sink of atmospheric CO2. In regions where the blooms are prevalent, the average reduction in the monthly CO2 sink can reach 12 %. The maximum reduction of the monthly CO2 sink in the time series is 32 %. This work suggests that the high 20 variability, frequency and distribution of these calcifying plankton and their impact on pCO2 should be considered within modelling studies of the North Atlantic if we are to fully understand the variability of its air-to-sea CO2 flux.

Bridging the gap between marine biogeochemical and fisheries sciences; configuring the zooplankton link

Exploring climate and anthropogenic impacts on marine ecosystems requires an understanding of how trophic components interact. However, integrative end-to-end ecosystem studies (experimental and/or modelling) are rare. Experimental investigations often concentrate on a particular group or individual species within a trophic level, while tropho-dynamic field studies typically employ either a bottom-up approach concentrating on the phytoplankton community or a top-down approach concentrating on the fish community. Likewise the emphasis within modelling studies is usually placed upon phytoplankton-dominated biogeochemistry or on aspects of fisheries regulation. In consequence the roles of zooplankton communities (protists and metazoans) linking phytoplankton and fish communities are typically under-represented if not (especially in fisheries models) ignored. Where represented in ecosystem models, zooplankton are usually incorporated in an extremely simplistic fashion, using empirical descriptions merging various interacting physiological functions governing zooplankton growth and development, and thence ignoring physiological feedback mechanisms. Here we demonstrate, within a modelled plankton food-web system, how trophic dynamics are sensitive to small changes in parameter values describing zooplankton vital rates and thus the importance of using appropriate zooplankton descriptors. Through a comprehensive review, we reveal the mismatch between empirical understanding and modelling activities identifying important issues that warrant further experimental and modelling investigation. These include: food selectivity, kinetics of prey consumption and interactions with assimilation and growth, form of voided material, mortality rates at different age-stages relative to prior nutrient history. In particular there is a need for dynamic data series in which predator and prey of known nutrient history are studied interacting under varied pH and temperature regimes.

Developments since 2005 in understanding potential environmental impacts of CO2 leakage from geological storage

This paper reviews research into the potential environmental impacts of leakage from geological storage of CO2 since the publication of the IPCC Special Report on Carbon Dioxide Capture and Storage in 2005. Possible impacts are considered on onshore (including drinking water aquifers) and offshore ecosystems. The review does not consider direct impacts on man or other land animals from elevated atmospheric CO2 levels. Improvements in our understanding of the potential impacts have come directly from CO2 storage research but have also benefitted from studies of ocean acidification and other impacts on aquifers and onshore near surface ecosystems. Research has included observations at natural CO2 sites, laboratory and field experiments and modelling. Studies to date suggest that the impacts from many lower level fault- or well-related leakage scenarios are likely to be limited spatially and temporarily and recovery may be rapid. The effects are often ameliorated by mixing and dispersion of the leakage and by buffering and other reactions; potentially harmful elements have rarely breached drinking water guidelines. Larger releases, with potentially higher impact, would be possible from open wells or major pipeline leaks but these are of lower probability and should be easier and quicker to detect and remediate.

Biophysical models of larval dispersal in the Benguela Current ecosystem

We synthesise and update results from the suite of biophysical, larval-dispersal models developed in the Benguela Current ecosystem. Biophysical models of larval dispersal use outputs of physical hydrodynamic models as inputs to individual-based models in which biological processes acting during the larval life are included. In the Benguela, such models were first applied to simulate the dispersal of anchovy Engraulis encrasicolus and sardine Sardinops sagax ichthyoplankton, and more recently of the early life stages of chokka-squid Loligo reynaudii and Cape hakes Merluccius spp. We identify how the models have helped advance understanding of key processes for these species. We then discuss which aspects of the early life of marine species in the Benguela Current ecosystem are still not well understood and could benefit from new modelling studies.

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.

Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling

In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine ecosystem model improves the simulation of biogeochemistry in a shelf sea. A localized Ensemble Kalman filter was used to assimilate weekly diffuse light attenuation coefficient data, Kd(443) from SeaWiFs, into an ecosystem model of the western English Channel. The spatial distributions of (unassimilated) surface chlorophyll from satellite, and a multivariate time series of eighteen biogeochemical and optical variables measured in situ at one long-term monitoring site were used to evaluate the system performance for the year 2006. Assimilation reduced the root mean square error and improved the correlation with the assimilated Kd(443) observations, for both the analysis and, to a lesser extent, the forecast estimates, when compared to the reference model simulation. Improvements in the simulation of (unassimilated) ocean colour chlorophyll were less evident, and in some parts of the Channel the simulation of this data deteriorated. The estimation errors for the (unassimilated) in situ data were reduced for most variables with some exceptions, e.g. dissolved nitrogen. Importantly, the assimilation adjusted the balance of ecosystem processes by shifting the simulated food web towards the microbial loop, thus improving the estimation of some properties, e.g. total particulate carbon. Assimilation of Kd(443) outperformed a comparative chlorophyll assimilation experiment, in both the estimation of ocean colour data and in the simulation of independent in situ data. These results are related to relatively low error in Kd(443) data, and because it is a bulk optical property of marine ecosystems. Assimilation of remotely-sensed optical properties is a promising approach to improve the simulation of biogeochemical and optical variables that are relevant for ecosystem functioning and climate change studies.

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.