A baseline appraisal of water-dependant ecosystem services, the roles they play within desakota livelihood systems and their potential sensitivity to climate change

This report forms part of a larger research programme on 'Reinterpreting the Urban-Rural Continuum', which conceptualises and investigates current knowledge and research gaps concerning 'the role that ecosystems services play in the livelihoods of the poor in regions undergoing rapid change'. The report aims to conduct a baseline appraisal of water-dependant ecosystem services, the roles they play within desakota livelihood systems and their potential sensitivity to climate change. The appraisal is conducted at three spatial scales: global, regional (four consortia areas), and meso scale (case studies within the four regions). At all three scales of analysis water resources form the interweaving theme because water provides a vital provisioning service for people, supports all other ecosystem processes and because water resources are forecast to be severely affected under climate change scenarios. This report, combined with an Endnote library of over 1100 scientific papers, provides an annotated bibliography of water-dependant ecosystem services, the roles they play within desakota livelihood systems and their potential sensitivity to climate change. After an introductory, section, Section 2 of the report defines water-related ecosystem services and how these are affected by human activities. Current knowledge and research gaps are then explored in relation to global scale climate and related hydrological changes (e.g. floods, droughts, flow regimes) (section 3). The report then discusses the impacts of climate changes on the ESPA regions, emphasising potential responses of biomes to the combined effects of climate change and human activities (particularly land use and management), and how these effects coupled with water store and flow regime manipulation by humans may affect the functioning of catchments and their ecosystem services (section 4). Finally, at the meso-scale, case studies are presented from within the ESPA regions to illustrate the close coupling of human activities and catchment performance in the context of environmental change (section 5). At the end of each section, research needs are identified and justified. These research needs are then amalgamated in section 6.

Data assimilation for marine monitoring and prediction: The MERCATOR operational assimilation systems and the MERSEA developments

During the past 15 years, a number of initiatives have been undertaken at national level to develop ocean forecasting systems operating at regional and/or global scales. The co-ordination between these efforts has been organized internationally through the Global Ocean Data Assimilation Experiment (GODAE). The French MERCATOR project is one of the leading participants in GODAE. The MERCATOR systems routinely assimilate a variety of observations such as multi-satellite altimeter data, sea-surface temperature and in situ temperature and salinity profiles, focusing on high-resolution scales of the ocean dynamics. The assimilation strategy in MERCATOR is based on a hierarchy of methods of increasing sophistication including optimal interpolation, Kalman filtering and variational methods, which are progressively deployed through the Syst`eme d’Assimilation MERCATOR (SAM) series. SAM-1 is based on a reduced-order optimal interpolation which can be operated using ‘altimetry-only’ or ‘multi-data’ set-ups; it relies on the concept of separability, assuming that the correlations can be separated into a product of horizontal and vertical contributions. The second release, SAM-2, is being developed to include new features from the singular evolutive extended Kalman (SEEK) filter, such as three-dimensional, multivariate error modes and adaptivity schemes. The third one, SAM-3, considers variational methods such as the incremental four-dimensional variational algorithm. Most operational forecasting systems evaluated during GODAE are based on least-squares statistical estimation assuming Gaussian errors. In the framework of the EU MERSEA (Marine EnviRonment and Security for the European Area) project, research is being conducted to prepare the next-generation operational ocean monitoring and forecasting systems. The research effort will explore nonlinear assimilation formulations to overcome limitations of the current systems. This paper provides an overview of the developments conducted in MERSEA with the SEEK filter, the Ensemble Kalman filter and the sequential importance re-sampling filter.

Singular vector ensemble forecasting systems and the prediction of flow dependent uncertainty

The ECMWF ensemble weather forecasts are generated by perturbing the initial conditions of the forecast using a subset of the singular vectors of the linearised propagator. Previous results show that when creating probabilistic forecasts from this ensemble better forecasts are obtained if the mean of the spread and the variability of the spread are calibrated separately. We show results from a simple linear model that suggest that this may be a generic property for all singular vector based ensemble forecasting systems based on only a subset of the full set of singular vectors.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

Adaptation and yield of pigeonpea in different environments in Tanzania

Pigeonpea is grown in wide range of cropping systems and environments, both in East Africa and internationally. An important feature of adaptation to these diverse systems and environments is the timing of flowering and maturity. Most traditional cultivars grown in Tanzania are medium to late flowering types (> 150 days), although extra-early flowering cultivars are now available. The aim of the present investigation was to measure biomass (BY) and seed (SY) yield of a set of phenologically diverse cultivars to determine their adaptation to contrasting environments in Tanzania. Ten cultivars, from extra-early (60 days) to late (> 180 days) flowering, were planted at six locations varying in mean temperature, photoperiod and rainfall. Days to flowering (DTF) and maturity, and above-ground BY and SY at maturity, were measured. A stress index (ETr:ETm ratio, 100 = no stress) was computed for each site. Rainfall and the stress index at the different sites varied from 322 to 1297 mm and 57 to 89, respectively. Among cultivars, DTF varied from 55 to 320 days, the stress index from 3 to 98, BY from 700 to 25,000 kg ha(-1), and SY from 0 to 4000 kg ha(-1). The highest yielding environment was at Selian, where mean temperatures were favourable (19 degrees C) and no stress occurred. At all sites there was an optimum DTF, which for SY varied from < 100 to 150 days. The best adapted cultivars were ICP 7035, ICPL 90094, Kat 50 and QP37, which were all medium flowering (c. 150 day) types. Extra-early cultivars such as ICPL 86005 also showed considerable potential, especially in short-season environments. (c) 2004 Elsevier B.V. All rights reserved.

Interaction of sulphur-containing aroma compounds with proteins in both model systems and real food systems

Irreversible binding of key flavour disulphides to ovalbumin has been shown previously to occur in model systems. The extent of binding is determined by the availability of the sulphydryl groups to participate in disulphide exchange, influenced either by pH, or the state of the protein (native or heat-denatured). In this study, two further proteins, one with sulphydryl groups available in the native state (beta-lactoglobulin) and one with no sulphydryl groups in the native state (lysozyme) were used to confirm this hypothesis. When the investigation was extended to real food systems, a similar effect was shown when a commercial meat flavouring containing disulphides was added to heat-denatured ovalbumin. Furthermore, comparison of the volatiles generated from onions, cooked either alone, or in the presence of meat, showed a significant reduction of key onion-derived disulphides when cooked in the presence of meat, and an even greater reduction of trisulphides. These findings may have implications for consumer acceptance of food products; where these compounds are used as flavourings or where they occur naturally.

On rank, underdetermined systems and consistency

The concepts of rank, underdetermined systems and consistency in linear algebra are discussed in the context of a puzzle. The article begins with a specific example, moving on to a generalization of the example and then to the general n x n case. As well as providing a solution of the puzzle, the article aims to provide students with a greater understanding of these abstract ideas in linear algebra through the study of the puzzle.