28 research outputs found

    Feasibility Study: Social Protection in South Central Somalia

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    In recent years, there has been a growing recognition by policy makers and the international development community that longer-term social protection programming has the potential to reduce poverty and inequality and serve as a foundation upon which, viable livelihoods can be built. In many countries, specially those that are frequently affected by climatic and conflict hazards, this has led to calls for a shift in approach away from interventions thatsimply address the symptoms of household vulnerability towards those which deal with the causes. For more than two decades Somalia has lurched from one humanitarian crisis to another. This debate around the potential of social protection is therefore particularly acute, as years of humanitarian programming seem to have had little impact on increasing household resilience to shocks. Furthermore, the country still ranks 165 out of the 170 countries included in the UN's Human Development Index, and number one on the US Fund for Peace 'Failed State Index'.A consortium of agencies working in Somalia commissioned this study: Adeso, ACF, DRC and Save the Children. The study is intended to further the discussion on the rationale and practicalities of social protection in South Central Somalia, and to serve as a starting point for the debate around moving away from short-term responses towards longer-term social protection interventions by these agencies, and others.The report comprises six parts: Part 1 describes the political economy in South Central Somalia and highlights some key challengesfor humanitarian actors; Part 2 defines the general concept of social protection and looks at the global evidence of the impact of social protection; Part 3 looks at social protection programs in African countries (particularly those in the Somalia region), and also in fragile states; Part 4 looks at current social protection mechanisms in South Central Somalia; Part 5 describes the actions that are currently needed before humanitarian programming can become predictable, and Part 6 summarizes the way forward, including recommendations and the conclusions from the study

    A simple model to quantify the potential trade-off between water level management for ecological benefit and flood risk

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    Throughout the world, historic drainage of wetlands has resulted in a reduction in the area of wet habitat and corresponding loss of wetland plant and animal species. In an attempt to reverse this trend, water level management in some drained areas is trying to replicate a more natural ‘undrained’ state. The resulting hydrological regime is likely to be more suitable to native wetland species; however the raised water levels also represent a potential reduction in flood water storage capacity. Quantifying this reduction is critical if the arguments for and against wetland restoration are to be discussed in a meaningful way. We present a simple model to quantify the hydrological storage capacity of a drainage ditch network under different water level management scenarios. The model was applied to the Somerset Levels and Moors, UK, comparing areas with and without raised water level management. The raised water level areas occupy 11% of the maximum theoretical storage but when put in the context of the recent severe flooding of winter 2013/2014 occupy only 0.6% of the total flood volume and represent an average increase in flood level of 7 mm. These results indicate that although the raised water level scheme does occupy an appreciable volume of the maximum possible ditch storage, in relation to a large flood event the volume is very small. It therefore seems unlikely that the severity of such large flood events would be significantly reduced if the current water level management for ecological benefit ceased

    Radiometric approach for the detection of picophytoplankton assemblages across oceanic fronts

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    Cell abundances of Prochlorococcus, Synechococcus, and autotrophic picoeukaryotes were estimated in surface waters using principal component analysis (PCA) of hyperspectral and multispectral remote-sensing reflectance data. This involved the development of models that employed multilinear correlations between cell abundances across the Atlantic Ocean and a combination of PCA scores and sea surface temperatures. The models retrieve high Prochlorococcus abundances in the Equatorial Convergence Zone and show their numerical dominance in oceanic gyres, with decreases in Prochlorococcus abundances towards temperate waters where Synechococcus flourishes, and an emergence of picoeukaryotes in temperate waters. Fine-scale in-situ sampling across ocean fronts provided a large dynamic range of measurements for the training dataset, which resulted in the successful detection of fine-scale Synechococcus patches. Satellite implementation of the models showed good performance (R2 > 0.50) when validated against in-situ data from six Atlantic Meridional Transect cruises. The improved relative performance of the hyperspectral models highlights the importance of future high spectral resolution satellite instruments, such as the NASA PACE mission’s Ocean Color Instrument, to extend our spatiotemporal knowledge about ecologically relevant phytoplankton assemblages

    An ocean-colour time series for use in climate studies: the experience of the ocean-colour climate change initiate (OC-CCI)

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    Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea viewingWide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel

    Needs Assessment

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    Matching ICD-11 personality status to clinical management in a community team-The Boston (UK) Personality Project: Study protocol

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    Epidemiological studies show 30% to 50% of all patients in community mental health teams have personality disorders. These are normally comorbid with other psychiatric disorders, often as Galenic syndromes, and are seldom identified. In the Boston (UK) Personality Project all patients under a community health service in Boston in Lincolnshire will be asked to agree to have their personality status assessed using scales recording the new ICD-11 classification, together with clinical ratings, social function and satisfaction. A control group of 100 patients from an adjacent service of similar demographics (Spalding) will also have similar ratings but no personality assessments. Changes in clinical status, social function and service satisfaction will be made after 6 and 12 months in both groups. The patients in the Boston group will be offered matched interventions using a stepped care approach for both the severity of disorder and its domain structure. These interventions will include shorter versions of existing psychological treatments, environmental therapies including nidotherapy, adaptive and acceptance models, drug reduction and social prescribing. Full costs of psychiatric care will be measured in both groups. The main hypothesis is that greater awareness of personality function will lead to better clinical outcomes and satisfaction
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