13 resultados para Exposición Regional Valenciana (1ª. 1909. València)

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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Long-term regional changes in phytoplankton biomass in the Northeast Atlantic and North Sea are investigated using data from the Continuous Plankton Recorder survey. During the last decade there have been large changes in the long-term variation in phytoplankton biomass in the Northeast Atlantic and North Sea. Most regions, particularly in the North Sea, have shown a considerable increase in phytoplankton biomass while the opposite pattern was seen in the northern oceanic region of the Northeast Atlantic. These different spatial responses show similar patterns of change to the decadal variability in sea surface temperature influenced by the North Atlantic Oscillation index. Two rare oceanographic events and their relationship to the interannual changes in phytoplankton biomass are discussed. The results highlight the importance of maintaining long-term biological monitoring programmes to assess the biological responses to slow oceanic/atmospheric processes and to rare or episodic physical events.

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We investigated long-term spatial variability in a number of Harmful Algal Blooms (HABs) in the northeast Atlantic and North Sea using data from the Continuous Plankton Recorder. Over the last four decades, some dinoflagellate taxa showed pronounced variation in the south and east of the North Sea, with the most significant increases being restricted to the adjacent waters off Norway. There was also a general decrease along the eastern coast of the United Kingdom. The most prominent feature in the interannual bloom frequencies over the last four decades was the anomalously high values recorded in the late 1980s in the northern and central North Sea areas. The only mesoscale area in the northeast Atlantic to show a significant increase in bloom formation over the last decade was the Norwegian coastal region. The changing spatial patterns of HAB taxa and the frequency of bloom formation are discussed in relation to regional climate change, in particular, changes in temperature, salinity, and the North Atlantic Oscillation (NAO). Areas highly vulnerable to the effects of regional climate change on HABs are Norwegian coastal waters and the Skagerrak. Other vulnerable areas include Danish coastal waters, and to a lesser extent, the German and Dutch Bight and the northern Irish Sea. Quite apart from eutrophication, our results give a preview of what might happen to certain HAB genera under changing climatic conditions in temperate environments and their responses to variability of climate oscillations such as the NAO.

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Several environmental/physical variables derived from satellite and in situ data sets were used to understand the variability of coccolithophore abundance in the subarctic North Atlantic. The 7-yr (1997â2004) time-series analysis showed that the combined effects of high solar radiation, shallow mixed layer depth (<20 m), and increased temperatures explained >89% of the coccolithophore variation. The June 1998 bloom, which was associated with high light intensity, unusually high sea-surface temperature, and a very shallow mixed layer, was found to be one of the most extensive (>995,000 km2) blooms ever recorded. There was a pronounced sea-surface temperature shift in the mid-1990s with a peak in 1998, suggesting that exceptionally large blooms are caused by pronounced environmental conditions and the variability of the physical environment strongly affects the spatial extent of these blooms. Consequently, if the physical environment varies, the effects of these blooms on the atmospheric and oceanic environment will vary as well.

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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 â˜sublittoral rockâ. 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: â˜macroalgaeâ, â˜temporarily or permanently attached active filter feedersâ, â˜temporarily or permanently attached passive filter feedersâ, â˜bivalves, brachiopods and other encrusting filter feedersâ, â˜tube building faunaâ, â˜scavengers and predatory faunaâ, and â˜non-predatory mobile faunaâ. 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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Regional seas are potentially highly vulnerable to climate change, yet are the most directly societally important regions of the marine environment. The combination of widely varying conditions of mixing, forcing, geography (coastline and bathymetry) and exposure to the open-ocean makes these seas subject to a wide range of physical processes that mediates how large scale climate change impacts on these seasâ ecosystems. In this paper we explore the response of five regional sea areas to potential future climate change, acting via atmospheric, oceanic and terrestrial vectors. These include the Barents Sea, Black Sea, Baltic Sea, North Sea, Celtic Seas, and are contrasted with a region of the Northeast Atlantic. Our aim is to elucidate the controlling dynamical processes and how these vary between and within these seas. We focus on primary production and consider the potential climatic impacts on: long term changes in elemental budgets, seasonal and mesoscale processes that control phytoplanktonâs exposure to light and nutrients, and briefly direct temperature response. We draw examples from the MEECE FP7 project and five regional model systems each using a common global Earth System Model as forcing. We consider a common analysis approach, and additional sensitivity experiments. Comparing projections for the end of the 21st century with mean present day conditions, these simulations generally show an increase in seasonal and permanent stratification (where present). However, the first order (low- and mid-latitude) effect in the open ocean projections of increased permanent stratification leading to reduced nutrient levels, and so to reduced primary production, is largely absent, except in the NE Atlantic. Even in the two highly stratified, deep water seas we consider (Black and Baltic Seas) the increase in stratification is not seen as a first order control on primary production. Instead, results show a highly heterogeneous picture of positive and negative change arising from complex combinations of multiple physical drivers, including changes in mixing, circulation and temperature, which act both locally and non-locally through advection.