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.

Informal communication networks and the diffusion of innovations in UK construction projects: A research design

The UK industry has been criticised for being slow to adopt construction process innovations. Research shows that the idiosyncrasies of participants, their roles in the system and the contextual differences between sections of the industry make this a highly complex problem. There is considerable evidence that informal social networks play a key role in diffusion of innovations. The aim is to identify informal communication networks of project participants and the role these play in the diffusion of construction innovations. The characteristics of this network will be analysed in order to understand how they can be used to accelerate innovation diffusion within and between projects. Social Network Analysis is used to determine informal communication routes. Control and experiment case study projects are used within two different organizations. This allows informal communication routes concerning innovations to be mapped, whilst testing if the informal routes can facilitate diffusion. Analysis will focus upon understanding the combination of informal strong and weak ties, and how these impede or facilitate the diffusion of the innovation. Initial work suggests the presence of an informal communication network. Actors within this informal network, and the organization's management are unaware of its' existence and their informal roles within it. Thus, the network remains an untapped medium regarding innovation diffusion. It is proposed that successful innovation diffusion is dependent upon understanding informal strong and weak ties, at project, organization and industry level.

Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks

The themes of awareness and influence within the innovation diffusion process are addressed. The innovation diffusion process is typically represented as stages, yet awareness and influence are somewhat under-represented in the literature. Awareness and influence are situated within the contextual setting of individual actors but also within the broader institutional forces. Understanding how actors become aware of an innovation and then how their opinion is influenced is important for creating a more innovation-active UK construction sector. Social network analysis is proposed as one technique for mapping how awareness and influence occur and what they look like as a network. Empirical data are gathered using two modes of enquiry. This is done through a pilot study consisting of chartered professionals and then through a case study organization as it attempted to diffuse an innovation. The analysis demonstrates significant variations across actors’ awareness and influence networks. It is argued that social network analysis can complement other research methods in order to present a richer picture of how actors become aware of innovations and where they draw their influences regarding adopting innovations. In summarizing the findings, a framework for understanding awareness and influence associated with innovation within the UK construction sector is presented. Finally, with the UK construction sector continually being encouraged to be innovative, understanding and managing an actor’s awareness and influence network will be beneficial. The overarching conclusion thus describes the need not only to build research capacity in this area but also to push the boundaries related to the research methods employed.

Centrality and spectral radius in dynamic communication networks

We explore the influence of the choice of attenuation factor on Katz centrality indices for evolving communication networks. For given snapshots of a network observed over a period of time, recently developed communicability indices aim to identify best broadcasters and listeners in the network. In this article, we looked into the sensitivity of communicability indices on the attenuation factor constraint, in relation to spectral radius (the largest eigenvalue) of the network at any point in time and its computation in the case of large networks. We proposed relaxed communicability measures where the spectral radius bound on attenuation factor is relaxed and the adjacency matrix is normalised in order to maintain the convergence of the measure. Using a vitality based measure of both standard and relaxed communicability indices we looked at the ways of establishing the most important individuals for broadcasting and receiving of messages related to community bridging roles. We illustrated our findings with two examples of real-life networks, MIT reality mining data set of daily communications between 106 individuals during one year and UK Twitter mentions network, direct messages on Twitter between 12.4k individuals during one week.

Data mining for monitoring and managing systems and networks

Guest Editorial

On the radius of centrality in evolving communication networks

In this article, we investigate how the choice of the attenuation factor in an extended version of Katz centrality influences the centrality of the nodes in evolving communication networks. For given snapshots of a network, observed over a period of time, recently developed communicability indices aim to identify the best broadcasters and listeners (receivers) in the network. Here we explore the attenuation factor constraint, in relation to the spectral radius (the largest eigenvalue) of the network at any point in time and its computation in the case of large networks. We compare three different communicability measures: standard, exponential, and relaxed (where the spectral radius bound on the attenuation factor is relaxed and the adjacency matrix is normalised, in order to maintain the convergence of the measure). Furthermore, using a vitality-based measure of both standard and relaxed communicability indices, we look at the ways of establishing the most important individuals for broadcasting and receiving of messages related to community bridging roles. We compare those measures with the scores produced by an iterative version of the PageRank algorithm and illustrate our findings with two examples of real-life evolving networks: the MIT reality mining data set, consisting of daily communications between 106 individuals over the period of one year, a UK Twitter mentions network, constructed from the direct \emph{tweets} between 12.4k individuals during one week, and a subset the Enron email data set.

New opportunities for secure communication networks using shaped femtosecond laser pulses inducing filamentation processes in the atmosphere

The current study discusses new opportunities for secure ground to satellite communications using shaped femtosecond pulses that induce spatial hole burning in the atmosphere for efficient communications with data encoded within super-continua generated by femtosecond pulses. Refractive index variation across the different layers in the atmosphere may be modelled using assumptions that the upper strata of the atmosphere and troposphere behaving as layered composite amorphous dielectric networks composed of resistors and capacitors with different time constants across each layer. Input-output expressions of the dynamics of the networks in the frequency domain provide the transmission characteristics of the propagation medium. Femtosecond pulse shaping may be used to optimize the pulse phase-front and spectral composition across the different layers in the atmosphere. A generic procedure based on evolutionary algorithms to perform the pulse shaping is proposed. In contrast to alternative procedures that would require ab initio modelling and calculations of the propagation constant for the pulse through the atmosphere, the proposed approach is adaptive, compensating for refractive index variations along the column of air between the transmitter and receiver.

Towards an assessment of multiple ecosystem processes and services via functional traits

Managing ecosystems to ensure the provision of multiple ecosystem services is a key challenge for applied ecology. Functional traits are receiving increasing attention as the main ecological attributes by which different organisms and biological communities influence ecosystem services through their effects on underlying ecosystem processes. Here we synthesize concepts and empirical evidence on linkages between functional traits and ecosystem services across different trophic levels. Most of the 247 studies reviewed considered plants and soil invertebrates, but quantitative trait–service associations have been documented for a range of organisms and ecosystems, illustrating the wide applicability of the trait approach. Within each trophic level, specific processes are affected by a combination of traits while particular key traits are simultaneously involved in the control of multiple processes. These multiple associations between traits and ecosystem processes can help to identify predictable trait–service clusters that depend on several trophic levels, such as clusters of traits of plants and soil organisms that underlie nutrient cycling, herbivory, and fodder and fibre production. We propose that the assessment of trait–service clusters will represent a crucial step in ecosystem service monitoring and in balancing the delivery of multiple, and sometimes conflicting, services in ecosystem management.

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.