932 resultados para Marine sciences


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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.

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Sea ice in the western Antarctic Peninsula (WAP) region is both highly variable and rapidly changing. In the Palmer Station region, the ice season duration has decreased by 92 d since 1978. The sea-ice changes affect ocean stratification and freshwater balance and in turn impact every component of the polar marine ecosystem. Long-term observations from the WAP nearshore and offshore regions show a pattern of chlorophyll (Chl) variability with three to five years of negative Chl anomalies interrupted by one or two years of positive anomalies (high and low Chl regimes). Both field observations and results from an inverse food-web model show that these high and low Chl regimes differed significantly from each other, with high primary productivity and net community production (NCP) and other rates associated with the high Chl years and low rates with low Chl years. Gross primary production rates (GPP) averaged 30 mmolC.m-2.d-1 in the low Chl years and 100 mmolC.m-2.d-1 in the high Chl years. Both large and small phytoplankton were more abundant and more productive in high Chl years than in low Chl years. Similarly, krill were more important as grazers in high Chl years, but did not differ from microzooplankton in high or low Chl years. Microzooplankton did not differ between high and low Chl years. Net community production differed significantly between high and low Chl years, but mobilized a similar proportion of GPP in both high and low Chl years. The composition of the NCP was uniform in high and low Chl years. These results mphasize the importance of microbial components in the WAP plankton system and suggest that food webs dominated by small phytoplankton can have pathways that funnel production into NCP, and likely, export.

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The Joint Nature Conservation Committee (JNCC) commissioned this project to generate an improved understanding of the sensitivities of blue mussel (Mytilus edulis) beds, found in UK waters, to pressures associated with human activities in the marine environment. The work will provide an evidence base that will facilitate and support management advice for Marine Protected Areas, development of UK marine monitoring and assessment, and conservation advice to offshore marine industries. Blue mussel beds are identified as a Habitat of Principle Importance (HPI) under the Natural Environment and Rural Communities (NERC) Act 2006, as a Priority Marine Feature (PMF) under the Marine (Scotland) Act 2010, and included on the OSPAR (Annex V) list of threatened and declining species and habitats. The purpose of this project was to produce sensitivity assessments for the blue mussel biotopes included within the HPI, PMF and OSPAR habitat definitions, and clearly document the supporting evidence behind the assessments and any differences between them. A total of 20 pressures falling in five categories - biological, hydrological, physical damage, physical loss, and pollution and other chemical changes - were assessed in this report. The review examined seven blue mussel bed biotopes found on littoral sediment and sublittoral rock and sediment. The assessments were based on the sensitivity of M. edulis rather than associated species, as M. edulis was considered the most important characteristic species in blue mussel beds. To develop each sensitivity assessment, the resistance and resilience of the key elements are assessed against the pressure benchmark using the available evidence gathered in this review. The benchmarks were designed to provide a ‘standard’ level of pressure against which to assess sensitivity. Blue mussel beds were highly sensitive to a few human activities: • introduction or spread of non-indigenous species (NIS); • habitat structure changes - removal of substratum (extraction); and • physical loss (to land or freshwater habitat). Physical loss of habitat and removal of substratum are particularly damaging pressures, while the sensitivity of blue mussel beds to non-indigenous species depended on the species assessed. Crepidula fornicata and Crassostrea gigas both had the potential to outcompete and replace mussel beds, so resulted in a high sensitivity assessment. Mytilus spp. populations are considered to have a strong ability to recover from environmental disturbance. A good annual recruitment may allow a bed to recovery rapidly, though this cannot always be expected due to the sporadic nature of M. edulis recruitment. Therefore, blue mussel beds were considered to have a 'Medium' resilience (recovery within 2-10 years). As a result, even where the removal or loss of proportion of a mussel bed was expected due to a pressure, a sensitivity of 'Medium' was reported. Hence, most of the sensitivities reported were 'Medium'. It was noted, however, that the recovery rates of blue mussel beds were reported to be anywhere between two years to several decades. In addition, M. edulis is considered very tolerant of a range of physical and chemical conditions. As a result, blue mussel beds were considered to be 'Not sensitive' to changes in temperature, salinity, de-oxygenation, nutrient and organic enrichment, and substratum type, at the benchmark level of pressure. The report found that no distinct differences in overall sensitivity exist between the HPI, PMF and OSPAR definitions. Individual biotopes do however have different sensitivities to pressures, and the OSPAR definition only includes blue mussel beds on sediment. These differences were determined by the position of the habitat on the shore and the sediment type. For example, the infralittoral rock biotope (A3.361) was unlikely to be exposed to pressures that affect sediments. However in the case of increased water flow, mixed sediment biotopes were considered more stable and ‘Not sensitive’ (at the benchmark level) while the remaining biotopes were likely to be affected.

Using a clearly documented, evidence-based approach to create sensitivity assessments allows the assessment basis and any subsequent decision making or management plans to be readily communicated, transparent and justifiable. The assessments can be replicated and updated where new evidence becomes available ensuring the longevity of the sensitivity assessment tool. For every pressure where sensitivity was previously assessed as a range of scores in MB0102, the assessments made by the evidence review have supported one of the MB0102 assessments. The evidence review has reduced the uncertainty around assessments previously undertaken in the MB0102 project (Tillin et al., 2010) by assigning a single sensitivity score to the pressures as opposed to a range. Finally, as blue mussel bed habitats also contribute to ecosystem function and the delivery of ecosystem services, understanding the sensitivity of these biotopes may also support assessment and management in regard to these. Whatever objective measures are applied to data to assess sensitivity, the final sensitivity assessment is indicative. The evidence, the benchmarks, the confidence in the assessments and the limitations of the process, require a sense-check by experienced marine ecologists before the outcome is used in management decisions.

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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.

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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.

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For the first time, bacterial symbiosis is recognized in the bivalve family Montacutidae of the superfamily Galeommatoidea. The ctenidial filaments of Syssitomya pourtalesiana Oliver, 2012 are extended abfrontally and a dense layer of bacteriocyte cells cover the entire surface behind a narrow ciliated frontal zone. The bacteria are extracellular and held within a matrix of epithelial extensions and microvilli. There is no cuticular layer (glycocalyx) covering the bacteria as in many thyasirid symbioses. The bacteriocytes hold more than one morphotype of bacteria, but bacilli, 1–3 μm in length, dominate. Scanning electron microscopy observations show a surface mat of filamentous bacteria over the extreme abfrontal surfaces. Filter feeding was confirmed by the presence of food particles in the stomach and the bivalve is presumed to be mixotrophic. Syssitomya is commensal and lives attached to the anal spines of the deep-sea echinoid Pourtalesia. In this position, echinoid feeding currents and echinoid faecal material may supply the bacteria with a variety of nutrient materials including dissolved organic matter.

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Mediterranean demersal fisheries are highly multispecific and many of their target stocks are overexploited. In addition, rocketing fuel costs and low market prices of traditionally high-value species are challenging the viability of fisheries. Here, based on the numeric results of a simulation model, we conclude that this situation can be remedied by reducing both fishing mortality and fishing costs. According to our model results, fishing effort reductions of 48-71% would improve the health of fish stocks while increasing the economic profits of Mallorca islands bottom trawl fishery to as much as 1.9 M(sic) (146% higher than current profits). If all fish stocks were exploited at their MSY (or below) level, the reduction in fishing effort would have to be of 71% from current values. If equilibrium profits from the fishery were to be maximized (MEY), fishing effort would need to be reduced by 48%. These results must be taken with caution due the many sources of uncertainty of our analysis. The modeling tools used to estimate these values are conditional to the adequate treatment of two sources of uncertainty that are particularly problematic in Mediterranean fisheries: insufficiently known recruitment variability and lack of periodic evaluations of the state of many species. Our results show that fishing effort reductions would produce economic yield gains after a period of transition. Further studies on the benefits of changing the size-selection pattern of fisheries, on better estimation of stock recruitment relationships and on better quantifications of the contribution of secondary species to these fisheries, are expected to improve the scientific recommendations for Mediterranean demersal fisheries toward sustainability principles.

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Vestimentiferan tube worms living at deep-sea hydrothermal vents and cold seeps have been considered as a clade with a long and continuing evolutionary history in these ecosystems. Whereas the fossil record appears to support this view, molecular age estimates do not. The two main features that are used to identify vestimentiferan tubes in the fossil record are longitudinal ridges on the tube's surface and a tube wall constructed of multiple layers. It is shown here that chaetopterid tubes from modern vents and seeps—as well as a number of fossil tubes from shallow-water environments—also show these two features. This calls for a more cautious interpretation of tubular fossils from ancient vent and seep deposits. We suggest that: current estimates for a relatively young evolutionary age based on molecular clock methods may be more reliable than the inferences of ancient “vestimentiferans” based on putative fossils of these worms; not all of these putative fossils actually belong to this group; and that tubes from fossil seeps should be investigated for chitinous remains to substantiate claims of their potential siboglinid affinities.

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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.

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Despite its importance to ocean–climate interactions, the metabolic state of the oligotrophic ocean has remained controversial for 415 years. Positions in the debate are that it is either hetero- or autotrophic, which suggests either substantial unaccounted for organic matter inputs, or that all available photosynthesis (P) estimations (including 14C) are biased. Here we show the existence of systematic differences in the metabolic state of the North (heterotrophic) and South (autotrophic) Atlantic oligotrophic gyres, resulting from differences in both P and respiration (R). The oligotrophic ocean is neither auto- nor heterotrophic, but functionally diverse. Our results show that the scaling of plankton metabolism by generalized P:R relationships that has sustained the debate is biased, and indicate that the variability of R, and not only of P, needs to be considered in regional estimations of the ocean’s metabolic state.

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The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO2 (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO2 values) and extended data coverage (from 1968–2007 to 1968–2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications ofSOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longer term variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models.

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The nano- and picoplankton community at Station L4 in the Western English Channel was studied between 2007 and 2013 by flow cytometry to quantify abundance and investigate seasonal cycles within these communities. Nanoplankton included both photosynthetic and heterotrophic eukaryotic single-celled organisms while the picoplankton included picoeukaryote phytoplankton, Synechococcus sp. cyanobacteria and heterotrophic bacteria. A Box–Jenkins Transfer Function climatology analysis of surface data revealed that Synechococcus sp., cryptophytes, and heterotrophic flagellates had bimodal annual cycles. Nanoeukaryotes and both high and low nucleic acid-containing bacteria (HNA and LNA, respectively) groups exhibited unimodal annual cycles. Phaeocystis sp., whilst having clearly defined abundance maxima in spring was not detectable the rest of the year. Coccolithophores exhibited a weak seasonal cycle, with abundance peaks in spring and autumn. Picoeukaryotes did not exhibit a discernable seasonal cycle at the surface. Timings of maximum group abundance varied through the year. Phaeocystis sp. and heterotrophic flagellates peaked in April/May. Nanoeukaryotes and HNA bacteria peaked in June/July and had relatively high abundance throughout the summer. Synechococcus sp., cryptophytes and LNA bacteria all peaked from mid to late September. The transfer function model techniques used represent a useful means of identifying repeating annual cycles in time series data with the added ability to detect trends and harmonic terms at different time scales from months to decades.

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Information on non-native species (NNS) is often scattered among a multitude of sources, such as regional and national databases, peer-reviewed and grey literature, unpublished research projects, institutional datasets and with taxonomic experts. Here we report on the development of a database designed for the collation of information in Britain. The project involved working with volunteer experts to populate a database of NNS (hereafter called “the species register”). Each species occupies a row within the database with information on aspects of the species’ biology such as environment (marine, freshwater, terrestrial etc.), functional type (predator, parasite etc.), habitats occupied in the invaded range (using EUNIS classification), invasion pathways, establishment status in Britain and impacts. The information is delivered through the Great Britain Non-Native Species Information Portal hosted by the Non-Native Species Secretariat. By the end of 2011 there were 1958 established NNS in Britain. There has been a dramatic increase over time in the rate of NNS arriving in Britain and those becoming established. The majority of established NNS are higher plants (1,376 species). Insects are the next most numerous group (344 species) followed by non-insect invertebrates (158 species), vertebrates (50 species), algae (24 species) and lower plants (6 species). Inventories of NNS are seen as an essential tool in the management of biological invasions. The use of such lists is diverse and far-reaching. However, the increasing number of new arrivals highlights both the dynamic nature of invasions and the importance of updating NNS inventories.