20 resultados para Thermal and mechanic cycling

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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Within models, zooplankton grazing is typically defined as being dependent on total prey concentration, with feeding selectivity expressed only as a function of prey size. This behavior ignores taxonomic preferences shown by the preda- tors and the capacity of some zooplankton to actively select or reject individual prey items from mixtures. We carried out two model experiments comparing impacts of zooplankton displaying passive and active selection, which resulted in contrasting dynamics for the pelagic system. Passive selection by the grazer resulted in a top down control on the prey with a fast turn-over of nutrients. Active selection, on the other hand led to a bottom-up control, with slower nutrient turnover constraining primary production by changing the system toward export of particulate matter. Our results suggest that selective feeding behavior is an important trait, and should be considered alongside size and taxonomy when studying the role of zooplankton impact in the ecosystem.

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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.

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Front detection and aggregation techniques were applied to 300m resolution MERIS satellite ocean colour data for the first time, to describe frequently occurring shelf-sea fronts near to the Scottish coast. Medium resolution (1km) thermal and colour data have previously been used to analyse the distribution of surface fronts, though these cannot capture smaller frontal zones or those in close proximity to the coast, particularly where the coastline is convoluted. Seasonal frequent front maps, derived from both chlorophyll and SST data, revealed a number of key frontal zones, a subset of which were based on new insights into the sediment and plankton dynamics provided exclusively by the higher-resolution chlorophyll fronts. The methodology is described for applying colour and thermal front data to the task of identifying zones of ecological importance that could assist the process of defining marine protected areas. Each key frontal zone is analysed to describe its spatial and temporal extent and variability, and possible mechanisms. It is hoped that these tools can provide guidance on the dynamic habitats of marine fauna towards aspects of marine spatial planning and conservation.

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Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

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Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

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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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Front detection and aggregation techniques were applied to 300m resolution MERIS satellite ocean colour data for the first time, to describe frequently occurring shelf-sea fronts near to the Scottish coast. Medium resolution (1km) thermal and colour data have previously been used to analyse the distribution of surface fronts, though these cannot capture smaller frontal zones or those in close proximity to the coast, particularly where the coastline is convoluted. Seasonal frequent front maps, derived from both chlorophyll and SST data, revealed a number of key frontal zones, a subset of which were based on new insights into the sediment and plankton dynamics provided exclusively by the higher-resolution chlorophyll fronts. The methodology is described for applying colour and thermal front data to the task of identifying zones of ecological importance that could assist the process of defining marine protected areas. Each key frontal zone is analysed to describe its spatial and temporal extent and variability, and possible mechanisms. It is hoped that these tools can provide guidance on the dynamic habitats of marine fauna towards aspects of marine spatial planning and conservation.

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Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

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We present over 900 carbonate system observations collected over four years (2007–2010) in the Western English Channel (WEC). We determined CO2 partial pressure (pCO2), Total Alkalinity (TA) and Dissolved Inorganic Carbon (DIC) along a series of 40 km transects, including two oceanographic stations (L4 and E1) within a sustained coastal observatory. Our data follow a seasonal pattern of CO2 undersaturation from January to August, followed by supersaturation in September–October and a return to near-equilibrium thereafter. This pattern is explained by the interplay of thermal and biological sinks in winter and spring–summer, respectively, followed by the breakdown of stratification and mixing with deeper, high-CO2 water in autumn. The drawdown of DIC and inorganic N between March and June with a C:N ratio of 8.7–9.5 was consistent with carbon over-consumption during phytoplankton growth. Monthly mean surface pCO2 was strongly correlated with depth integrated chlorophyll a highlighting the importance of subsurface chlorophyll a maxima in controlling C-fluxes in shelf seas. Mixing of seawater with riverine freshwater in near-shore samples caused a reduction in TA and the saturation state of calcite minerals, particularly in winter. Our data show that the L4 and E1 oceanographic stations were small, net sinks for atmospheric CO2 over an annual cycle (−0.52±0.66 mol C m−2 y−1 and −0.62±0.49 mol C m−2 y−1, respectively).