999 resultados para 12930-015


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Mussels tolerant to seawater pH's that are projected to occur by 2300 due to ocean acidification.•Exposure to pH 6.50 reduced mussel immune response, yet in the absence of a pathogen.•Subsequent pathogenic challenge led to a reversal of immune suppression at pH 6.50.•Study highlights the importance of undertaking multiple stressor exposures.•Shows a need to consider physiological trade-offs and measure responses functionally

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Fish provides more than 4.5 billion people with at least 15 % of their average per capita intake of animal protein. Fish's unique nutritional properties make it also essential to the health of billions of consumers in both developed and developing countries. Fish is one of the most efficient converters of feed into high quality food and its carbon footprint is lower compared to other animal production systems. Through fish-related activities (fisheries and aquaculture but also processing and trading), fish contribute substantially to the income and therefore to the indirect food security of more than 10 % of the world population, essentially in developing and emergent countries. Yet, limited attention has been given so far to fish as a key element in food security and nutrition strategies at national level and in wider development discussions and interventions. As a result, the tremendous potential for improving food security and nutrition embodied in the strengthening of the fishery and aquaculture sectors is missed. The purpose of this paper is to make a case for a closer integration of fish into the overall debate and future policy about food security and nutrition. For this, we review the evidence from the contemporary and emerging debates and controversies around fisheries and aquaculture and we discuss them in the light of the issues debated in the wider agriculture/farming literature. The overarching question that underlies this paper is: how and to what extent will fish be able to contribute to feeding 9 billion people in 2050 and beyond?

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Scepticism over stated preference surveys conducted online revolves around the concerns over “professional respondents” who might rush through the questionnaire without sufficiently considering the information provided. To gain insight on the validity of this phenomenon and test the effect of response time on choice randomness, this study makes use of a recently conducted choice experiment survey on ecological and amenity effects of an offshore windfarm in the UK. The positive relationship between self-rated and inferred attribute attendance and response time is taken as evidence for a link between response time and cognitive effort. Subsequently, the generalised multinomial logit model is employed to test the effect of response time on scale, which indicates the weight of the deterministic relative to the error component in the random utility model. Results show that longer response time increases scale, i.e. decreases choice randomness. This positive scale effect of response time is further found to be non-linear and wear off at some point beyond which extreme response time decreases scale. While response time does not systematically affect welfare estimates, higher response time increases the precision of such estimates. These effects persist when self-reported choice certainty is controlled for. Implications of the results for online stated preference surveys and further research are discussed.

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Marine ecosystems provide many ecosystem goods and services. However, these ecosystems and the benefits they create for humans are subject to competing uses and increasing pressures. As a consequence of the increasing threats to the marine environment, several regulations require applying an ecosystem-based approach for managing the marine environment. Within the Mediterranean Sea, in 2008, the Contracting Parties of the Mediterranean Action Plan decided to progressively apply the Ecosystem Approach (EcAp) with the objective of achieving Good Environmental Status (GES) for 2018. To assess the Environmental Status, the EcAp proposes 11 Ecological Objectives, each of which requires a set of relevant indicators to be integrated. Progress towards the EcAp entails a gradual and important challenge for North-African countries, and efforts have to be initiated to propose and discuss methods. Accordingly, to enhance the capacity of North-African countries to implement EcAp and particularly to propose and discuss indicators and methods to assess GES, the aim of this manuscript is to identify the practical problems and gaps found at each stage of the Environmental Status assessment process. For this purpose, a stepwise method has been proposed to assess the Environmental Status using Ecologic Objective 5-Eutrophication as example.

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Macroalgae (seaweeds) are a promising feedstock for the production of third generation bioethanol, since they have high carbohydrate contents, contain little or no lignin and are available in abundance. However, seaweeds typically contain a more diverse array of monomeric sugars than are commonly present in feedstocks derived from lignocellulosic material which are currently used for bioethanol production. Hence, identification of a suitable fermentative microorganism that can utilise the principal sugars released from the hydrolysis of macroalgae remains a major objective. The present study used a phenotypic microarray technique to screen 24 different yeast strains for their ability to metabolise individual monosaccharides commonly found in seaweeds, as well as hydrolysates following an acid pre-treatment of five native UK seaweed species (Laminaria digitata, Fucus serratus, Chondrus crispus, Palmaria palmata and Ulva lactuca). Five strains of yeast (three Saccharomyces spp, one Pichia sp and one Candida sp) were selected and subsequently evaluated for bioethanol production during fermentation of the hydrolysates. Four out of the five selected strains converted these monomeric sugars into bioethanol, with the highest ethanol yield (13 g L−1) resulting from a fermentation using C. crispus hydrolysate with Saccharomyces cerevisiae YPS128. This study demonstrated the novel application of a phenotypic microarray technique to screen for yeast capable of metabolising sugars present in seaweed hydrolysates; however, metabolic activity did not always imply fermentative production of ethanol.

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Due to the impacts of natural processes and anthropogenic activities, different coastal wetlands are faced with variable patterns of heavy metal contamination. It is important to quantify the contributions of pollutant sources, in order to adopt appropriate protection measures for local ecosystems. The aim of this research was to compare the heavy metal contamination patterns of two contrasting coastal wetlands in eastern China. In addition, the contributions from various metal sources were identified and quantified, and influencing factors, such as the role of the plant Spartina alterniflora, were evaluated. Materials and methods Sediment samples were taken from two coastal wetlands (plain-type tidal flat at the Rudong (RD) wetland vs embayment-type tidal flat at Luoyuan Bay (LY)) to measure the content of Al, Fe, Co, Cr, Cu, Mn, Mo, Ni, Sr, Zn, Pb, Cd, and As. Inductively coupled plasma atomic emission spectrometry, flame atomic absorption spectrometry, and atomic fluorescence spectrometry methods were used for metal detection. Meanwhile, the enrichment factor and geoaccumulation index were applied to assess the pollution level. Principle component analysis and receptor modeling were used to quantify the sources of heavy metals. Results and discussion Marked differences in metal distribution patterns between the two systems were present. Metal contents in LY were higher than those in RD, except for Sr and Mo. The growth status of S. alterniflora influenced metal accumulations in RD, i.e., heavy metals were more easily adsorbed in the sediment in the following sequence: Cu > Cd > Zn > Cr > Al > Pb ≥ Ni ≥ Co > Fe > Sr ≥ Mn > As > Mo as a result of the presence and size of the vegetation. However, this phenomenon was not observed in LY. A higher potential ecological risk was associated with LY, compared with RD, except for Mo. Based on a receptor model output, sedimentary heavy metal contents at RD were jointly influenced by natural sedimentary processes and anthropogenic activities, whereas they were dominated by anthropogenic activities at LY. Conclusions A combination of geochemical analysis and modeling approaches was used to quantify the different types of natural and anthropogenic contributions to heavy metal contamination, which is useful for pollution assessments. The application of this approach reveals that natural and anthropogenic processes have different influences on the delivery and retention of metals at the two contrasting coastal wetlands. In addition, the presence and size of S. alterniflora can influence the level of metal contamination in sedimentary environments.

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Sediment contaminants were monitored in Milford Haven Waterway (MHW) since 1978 (hydrocarbons) and 1982 (metals), with the aim of providing surveillance of environmental quality in one of the UK’s busiest oil and gas ports. This aim is particularly important during and after large-scale investment in liquefied natural gas (LNG) facilities. However, methods inevitably have changed over the years, compounding the difficulties of coordinating sampling and analytical programmes. After a review by the MHW Environmental Surveillance Group (MHWESG), sediment hydrocarbon chemistry was investigated in detail in 2010. Natural Resources Wales (NRW) contributed their MHW data for 2007 and 2012, collected to assess the condition of the Special Area of Conservation (SAC) designated under the European Union Habitats Directive. Datasets during 2007-2012 have thus been more comparable. The results showed conclusively that a MHW-wide peak in concentrations of sediment polycyclic aromatic hydrocarbons (PAHs), metals and other contaminants occurred in late 2007. This was corroborated by independent annual monitoring at one centrally-located station with peaks in early 2008 and 2011. The spatial and temporal patterns of recovery from the 2007 peak, shown by MHW-wide surveys in 2010 and 2012, indicate several probable causes of contaminant trends, as follows: atmospheric deposition, catchment runoff, sediment resuspension from dredging, and construction of two LNG terminals and a power station. Adverse biological effects predictable in 2007 using international sediment quality guidelines, were independently tested by data from monitoring schemes of more than a decade duration in MHW (starfish, limpets), and in the wider SAC (grey seals). Although not proving cause and effect, many of these potential biological receptors showed a simultaneous negative response to the elevated 2007 contamination following intense dredging activity in 2006. Wetland bird counts were typically at a peak in the winter of 2005-2006 previous to peak dredging. In the following winter 2006-2007, shelduck in Pembroke River showed their lowest winter count, and spring 2007 was the largest ever drop in numbers of broods across MHW between successive breeding seasons. Wigeon counts in Pembroke River were again low in late 2012 after further dredging nearby. These results are strongly supported by PAH data reported previously from invertebrate bioaccumulation studies in MHW 2007-2010, themselves closely reflecting sediment

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Maritime transport and shipping are impacted negatively by biofouling, which can result in increased fuel consumption. Thus, costs for fouling reduction can be considered an investment to reduce fuel consumption. Anti-fouling measures also reduce the rate of introduction of non-indigenous species (NIS). Further mitigation measures to reduce the transport of NIS within ballast water and sediments impose additional costs. The estimated operational cost of NIS mitigation measures may represent between 1.6% and 4% of the annual operational cost for a ship operating on European seas, with the higher proportional costs in small ships. However, fouling by NIS may affect fuel consumption more than fouling by native species due to differences in species’ life-history traits and their resistance to antifouling coatings and pollution. Therefore, it is possible that the cost of NIS mitigation measures could be smaller than the cost from higher fuel consumption arising from fouling by NIS.

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Marine legislation is becoming more complex and marine ecosystem-based management is specified in national and regional legislative frameworks. Shelf-seas community and ecosystem models (hereafter termed ecosystem models) are central to the delivery of ecosystem-based management, but there is limited uptake and use of model products by decision makers in Europe and the UK in comparison with other countries. In this study, the challenges to the uptake and use of ecosystem models in support of marine environmental management are assessed using the UK capability as an example. The UK has a broad capability in marine ecosystem modelling, with at least 14 different models that support management, but few examples exist of ecosystem modelling that underpin policy or management decisions. To improve understanding of policy and management issues that can be addressed using ecosystem models, a workshop was convened that brought together advisors, assessors, biologists, social scientists, economists, modellers, statisticians, policy makers, and funders. Some policy requirements were identified that can be addressed without further model development including: attribution of environmental change to underlying drivers, integration of models and observations to develop more efficient monitoring programmes, assessment of indicator performance for different management goals, and the costs and benefit of legislation. Multi-model ensembles are being developed in cases where many models exist, but model structures are very diverse making a standardised approach of combining outputs a significant challenge, and there is a need for new methodologies for describing, analysing, and visualising uncertainties. A stronger link to social and economic systems is needed to increase the range of policy-related questions that can be addressed. It is also important to improve communication between policy and modelling communities so that there is a shared understanding of the strengths and limitations of ecosystem models.