887 resultados para Picomolar Sensitivity


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The ocean plays an important role in regulating the climate, acting as a sink for carbon dioxide, perturbing the carbonate system and resulting in a slow decrease of seawater pH. Understanding the dynamics of the carbonate system in shelf sea regions is necessary to evaluate the impact of Ocean Acidification (OA) in these societally important ecosystems. Complex hydrodynamic and ecosystem coupled models provide a method of capturing the significant heterogeneity of these areas. However rigorous validation is essential to properly assess the reliability of such models. The coupled model POLCOMS–ERSEM has been implemented in the North Western European shelf with a new parameterization for alkalinity explicitly accounting for riverine inputs and the influence of biological processes. The model has been validated in a like with like comparison with North Sea data from the CANOBA dataset. The model shows good to reasonable agreement for the principal variables, physical (temperature and salinity), biogeochemical (nutrients) and carbonate system (dissolved inorganic carbon and total alkalinity), but simulation of the derived variables, pH and pCO2, are not yet fully satisfactory. This high uncertainty is attributed mostly to riverine forcing and primary production. This study suggests that the model is a useful tool to provide information on Ocean Acidification scenarios, but uncertainty on pH and pCO2 needs to be reduced, particularly when impacts of OA on ecosystem functions are included in the model systems.

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We applied coincident Earth observation data collected during 2008 and 2009 from multiple sensors (RA2, AATSR and MERIS, mounted on the European Space Agency satellite Envisat) to characterise environmental conditions and integrated sea-air fluxes of CO2 in three Arctic seas (Greenland, Barents, Kara). We assessed net CO2 sink sensitivity due to changes in temperature, salinity and sea ice duration arising from future climate scenarios. During the study period the Greenland and Barents seas were net sinks for atmospheric CO2, with integrated sea-air fluxes of -36 +/- 14 and -11 +/- 5 Tg C yr(-1), respectively, and the Kara Sea was a weak net CO2 source with an integrated sea-air flux of +2.2 +/- 1.4 TgC yr(-1). The combined integrated CO2 sea-air flux from all three was -45 +/- 18 TgC yr(-1). In a sensitivity analysis we varied temperature, salinity and sea ice duration. Variations in temperature and salinity led to modification of the transfer velocity, solubility and partial pressure of CO2 taking into account the resultant variations in alkalinity and dissolved organic carbon (DOC). Our results showed that warming had a strong positive effect on the annual integrated sea-air flux of CO2 (i.e. reducing the sink), freshening had a strong negative effect and reduced sea ice duration had a small but measurable positive effect. In the climate change scenario examined, the effects of warming in just over a decade of climate change up to 2020 outweighed the combined effects of freshening and reduced sea ice duration. Collectively these effects gave an integrated sea-air flux change of +4.0 TgC in the Greenland Sea, +6.0 Tg C in the Barents Sea and +1.7 Tg C in the Kara Sea, reducing the Greenland and Barents sinks by 11% and 53 %, respectively, and increasing the weak Kara Sea source by 81 %. Overall, the regional integrated flux changed by +11.7 Tg C, which is a 26% reduction in the regional sink. In terms of CO2 sink strength, we conclude that the Barents Sea is the most susceptible of the three regions to the climate changes examined. Our results imply that the region will cease to be a net CO2 sink in the 2050s.

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Recent strategies to sustain fish stocks have suggested a move towards an ecosystem based fisheries management (EBFM) approach. While EBFM considers the effect of fishing at the ecosystem level, it generally struggles with climate-driven environmental variability. In this study we show that the position of a fish stock within its distributional range or thermal niche (we use Icelandic and North Sea cod as examples of stocks at the centre and edge of their niche, respectively) will influence the relative importance of fishing and climate on abundance. At the warmer edge of the thermal niche of cod in the North Sea, we show a prominent influence of climate on the cod stock that is mediated through temperature effects on the plankton. In contrast, the influence of climate through its effects on plankton appears much less important at the present centre of the niche around Iceland. Recognising the potentially strong effect of climate on fish stocks, at a time of rapid global climate change, is probably an important prerequisite towards the synthesis of a cod management strategy.

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Coccolithophores are the largest source of calcium carbonate in the oceans and are considered to play an important role in oceanic carbon cycles. Current methods to detect the presence of coccolithophore blooms from Earth observation data often produce high numbers of false positives in shelf seas and coastal zones due to the spectral similarity between coccolithophores and other suspended particulates. Current methods are therefore unable to characterise the bloom events in shelf seas and coastal zones, despite the importance of these phytoplankton in the global carbon cycle. A novel approach to detect the presence of coccolithophore blooms from Earth observation data is presented. The method builds upon previous optical work and uses a statistical framework to combine spectral, spatial and temporal information to produce maps of coccolithophore bloom extent. Validation and verification results for an area of the north east Atlantic are presented using an in situ database (N = 432) and all available SeaWiFS data for 2003 and 2004. Verification results show that the approach produces a temporal seasonal signal consistent with biological studies of these phytoplankton. Validation using the in situ coccolithophore cell count database shows a high correct recognition rate of 80% and a low false-positive rate of 0.14 (in comparison to 63% and 0.34 respectively for the established, purely spectral approach). To guide its broader use, a full sensitivity analysis for the algorithm parameters is presented.

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We used coincident Envisat RA2 and AATSR temperature and wind speed data from 2008/2009 to calculate the global net sea-air flux of dimethyl sulfide (DMS), which we estimate to be 19.6 Tg S a21. Our monthly flux calculations are compared to open ocean eddy correlation measurements of DMS flux from 10 recent cruises, with a root mean square difference of 3.1 lmol m22 day21. In a sensitivity analysis, we varied temperature, salinity, surface wind speed, and aqueous DMS concentration, using fixed global changes as well as CMIP5 model output. The range of DMS flux in future climate scenarios is discussed. The CMIP5 model predicts a reduction in surface wind speed and we estimate that this will decrease the global annual sea-air flux of DMS by 22% over 25 years. Concurrent changes in temperature, salinity, and DMS concentration increase the global flux by much smaller amounts. The net effect of all CMIP5 modelled 25 year predictions was a 19% reduction in global DMS flux. 25 year DMS concentration changes had significant regional effects, some positive (Southern Ocean, North Atlantic, Northwest Pacific) and some negative (isolated regions along the Equator and in the Indian Ocean). Using satellite-detected coverage of coccolithophore blooms, our estimate of their contribution to North Atlantic DMS emissions suggests that the coccolithophores contribute only a small percentage of the North Atlantic annual flux estimate, but may be more important in the summertime and in the northeast Atlantic.

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This project was commissioned to generate an improved understanding of the sensitivities of seagrass habitats to pressures associated with human activities in the marine environment - to provide an evidence base to facilitate and support management advice for Marine Protected Areas; development of UK marine monitoring and assessment, and conservation advice to offshore marine industries. Seagrass bed habitats are identified as a Priority Marine Feature (PMF) under the Marine (Scotland) Act 2010, they are also included on the OSPAR list of threatened and declining species and habitats, and are a Habitat of Principle Importance (HPI) under the Natural Environment and Rural Communities (NERC) Act 2006, in England and Wales. The purpose of this project was to produce sensitivity assessments with supporting evidence for the HPI, OSPAR and PMF seagrass/Zostera bed habitat definitions, clearly documenting the evidence behind the assessments and any differences between assessments. Nineteen pressures, falling in five categories - biological, hydrological, physical damage, physical loss, and pollution and other chemical changes - were assessed in this report. Assessments were based on the three British seagrasses Zostera marina, Z. noltei and Ruppia maritima. Z. marina var. angustifolia was considered to be a subspecies of Z. marina but it was specified where studies had considered it as a species in its own rights. Where possible other components of the community were investigated but the basis of the assessment focused on seagrass species. To develop each sensitivity assessment, the resistance and resilience of the key elements were assessed against the pressure benchmark using the available evidence. The benchmarks were designed to provide a ‘standard’ level of pressure against which to assess sensitivity. Overall, seagrass beds were highly sensitive to a number of human activities: • penetration or disturbance of the substratum below the surface; • habitat structure changes – removal of substratum; • physical change to another sediment type; • physical loss of habitat; • siltation rate changes including and smothering; and • changes in suspended solids. High sensitivity was recorded for pressures which directly impacted the factors that limit seagrass growth and health such as light availability. Physical pressures that caused mechanical modification of the sediment, and hence damage to roots and leaves, also resulted in high sensitivity. Seagrass beds were assessed as ‘not sensitive’ to microbial pathogens or ‘removal of target species’. These assessments were based on the benchmarks used. Z. marina is known to be sensitive to Labyrinthula zosterae but this was not included in the benchmark used. Similarly, ‘removal of target species’ addresses only the biological effects of removal and not the physical effects of the process used. For example, seagrass beds are probably not sensitive to the removal of scallops found within the bed but are highly sensitive to the effects of dredging for scallops, as assessed under the pressure penetration or disturbance of the substratum below the surface‘. This is also an example of a synergistic effect Assessing the sensitivity of seagrass bed biotopes to pressures associated with marine activities between pressures. Where possible, synergistic effects were highlighted but synergistic and cumulative effects are outside the scope off this study. The report found that no distinct differences in sensitivity exist between the HPI, PMF and OSPAR definitions. Individual biotopes do however have different sensitivities to pressures. These differences were determined by the species affected, the position of the habitat on the shore and the sediment type. For instance evidence showed that beds growing in soft and muddy sand were more vulnerable to physical damage than beds on harder, more compact substratum. Temporal effects can also influence the sensitivity of seagrass beds. On a seasonal time frame, physical damage to roots and leaves occurring in the reproductive season (summer months) will have a greater impact than damage in winter. On a daily basis, the tidal regime could accentuate or attenuate the effects of pressures depending on high and low tide. A variety of factors must therefore be taken into account in order to assess the sensitivity of a particular seagrass habitat at any location. No clear difference in resilience was established across the three seagrass definitions assessed in this report. The resilience of seagrass beds and the ability to recover from human induced pressures is a combination of the environmental conditions of the site, growth rates of the seagrass, the frequency and the intensity of the disturbance. This highlights the importance of considering the species affected as well as the ecology of the seagrass bed, the environmental conditions and the types and nature of activities giving rise to the pressure and the effects of that pressure. For example, pressures that result in sediment modification (e.g. pitting or erosion), sediment change or removal, prolong recovery. Therefore, the resilience of each biotope and habitat definitions is discussed for each pressure. Using a clearly documented, evidence based approach to create sensitivity assessments allows the assessment 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. 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 seagrass habitats may 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 Joint Nature Conservation Committee (JNCC) commissioned this project to generate an improved understanding of the sensitivities of Sabellaria spinulosa reefs based on the OSPAR habitat definition. This work aimed to provide an evidence base to facilitate and support management advice for Marine Protected Areas, development of UK marine monitoring and assessment, and conservation advice to offshore marine industries. The OSPAR list of threatened and declining species and habitats refers to subtidal S. spinulosa reefs on hard or mixed substratum. S. spinulosa may also occur as thin crusts or individual worms but these are not the focus of conservation. The purpose of this project was to produce sensitivity assessments with supporting evidence for S. spinulosa reefs, clearly documenting the evidence behind the assessments and the confidence in these assessments. Sixteen pressures, falling in five categories - biological, hydrological, physical damage, physical loss, and pollution and other chemical changes - were assessed in this report. To develop each sensitivity assessment, the resistance and resilience of the key elements of the habitat were assessed against the pressure benchmark using the available evidence. The benchmarks were designed to provide a ‘standard’ level of pressure against which to assess sensitivity. The highest sensitivity (‘medium’) was recorded for physical pressures which directly impact the reefs including: • habitat structure changes – removal of substratum; • abrasion and penetration and sub-surface disturbance; • physical loss of habitat and change to habitat; and • siltation rate changes including and smothering. The report found that no evidence for differences in the sensitivity of the three EUNIS S. spinulosa biotopes that comprise the OSPAR definition. However, this evidence review has identified significant information gaps regarding sensitivity, ecological interactions with other species and resilience. No clear difference in resilience was established across the OSPAR S. spinulosa biotopes that were assessed in this report. Using a clearly documented, evidence based approach to create sensitivity assessments allows the assessment 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. Finally, as S. spinulosa habitats may 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 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.