An estimate of the global impact of multiple scattering by clouds on outgoing long-wave radiation

Although the potential importance of scattering of long-wave radiation by clouds has been recognised, most studies have concentrated on the impact of high clouds and few estimates of the global impact of scattering have been presented. This study shows that scattering in low clouds has a significant impact on outgoing long-wave radiation (OLR) in regions of marine stratocumulus (-3.5 W m(-2) for overcast conditions) where the column water vapour is relatively low. This corresponds to an enhancement of the greenhouse effect of such clouds by 10%. The near-global impact of scattering on OLR is estimated to be -3.0 W m(-2), with low clouds contributing -0.9 W m(-2), mid-level cloud -0.7 W m(-2) and high clouds -1.4 W m(-2). Although this effect appears small compared to the global mean OLR of 240 W m(-2), it indicates that neglect of scattering will lead to an error in cloud long-wave forcing of about 10% and an error in net cloud forcing of about 20%.

When smoke gets in our eyes: The multiple impacts of atmospheric black carbon on climate, air quality and health

With both climate change and air quality on political and social agendas from local to global scale, the links between these hitherto separate fields are becoming more apparent. Black carbon, largely from combustion processes, scatters and absorbs incoming solar radiation, contributes to poor air quality and induces respiratory and cardiovascular problems. Uncertainties in the amount, location, size and shape of atmospheric black carbon cause large uncertainty in both climate change estimates and toxicology studies alike. Increased research has led to new effects and areas of uncertainty being uncovered. Here we draw together recent results and explore the increasing opportunities for synergistic research that will lead to improved confidence in the impact of black carbon on climate change, air quality and human health. Topics of mutual interest include better information on spatial distribution, size, mixing state and measuring and monitoring. (c) 2006 Elsevier Ltd. All rights reserved.

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.

Global hydrology modelling and uncertainty: running multiple ensembles with a campus grid.

Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.

An optical study of multiple NEIAL events driven by low energy electron precipitation

Optical data are compared with EISCAT radar observations of multiple Naturally Enhanced Ion-Acoustic Line (NEIAL) events in the dayside cusp. This study uses narrow field of view cameras to observe small-scale, short-lived auroral features. Using multiple-wavelength optical observations, a direct link between NEIAL occurrences and low energy (about 100 eV) optical emissions is shown. This is consistent with the Langmuir wave decay interpretation of NEIALs being driven by streams of low-energy electrons. Modelling work connected with this study shows that, for the measured ionospheric conditions and precipitation characteristics, growth of unstable Langmuir (electron plasma) waves can occur, which decay into ion-acoustic wave modes. The link with low energy optical emissions shown here, will enable future studies of the shape, extent, lifetime, grouping and motions of NEIALs.

Genetic parameters and evaluations from single- and multiple-trait analysis of dairy cow fertility and milk production

Genetic parameters and breeding values for dairy cow fertility were estimated from 62 443 lactation records. Two-trait analysis of fertility and milk yield was investigated as a method to estimate fertility breeding values when culling or selection based on milk yield in early lactation determines presence or absence of fertility observations in later lactations. Fertility traits were calving interval, intervals from calving to first service, calving to conception and first to last service, conception success to first service and number of services per conception. Milk production traits were 305-day milk, fat and protein yield. For fertility traits, range of estimates of heritability (h(2)) was 0.012 to 0.028 and of permanent environmental variance (c(2)) was 0.016 to 0.032. Genetic correlations (r(g)) among fertility traits were generally high ( > 0.70). Genetic correlations of fertility with milk production traits were unfavourable (range -0.11 to 0.46). Single and two-trait analyses of fertility were compared using the same data set. The estimates of h(2) and c(2) were similar for two types of analyses. However, there were differences between estimated breeding values and rankings for the same trait from single versus multi-trait analyses. The range for rank correlation was 0.69-0.83 for all animals in the pedigree and 0.89-0.96 for sires with more than 25 daughters. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended. (C) 2002 Elsevier Science B.V. All rights reserved.

A structural time series approach to modelling multiple and resurgent meat scares in Italy

This paper exploits a structural time series approach to model the time pattern of multiple and resurgent food scares and their direct and cross-product impacts on consumer response. A structural time series Almost Ideal Demand System (STS-AIDS) is embedded in a vector error correction framework to allow for dynamic effects (VEC-STS-AIDS). Italian aggregate household data on meat demand is used to assess the time-varying impact of a resurgent BSE crisis (1996 and 2000) and the 1999 Dioxin crisis. The VEC-STS-AIDS model monitors the short-run impacts and performs satisfactorily in terms of residuals diagnostics, overcoming the major problems encountered by the customary vector error correction approach.

The use of a multiple criteria decision analysis to evaluate the effectiveness of landscape and habitat enhancement mechanisms: an example from the South Downs

A range of funding schemes and policy instruments exist to effect enhancement of the landscapes and habitats of the UK. While a number of assessments of these mechanisms have been conducted, little research has been undertaken to compare both quantitatively and qualitatively their relative effectiveness across a range of criteria. It is argued that few tools are available for such a multi-faceted evaluation of effectiveness. A form of Multiple Criteria Decision Analysis (MCDA) is justified and utilized as a framework in which to evaluate the effectiveness of nine mechanisms in relation to the protection of existing areas of chalk grassland and the creation of new areas in the South Downs of England. These include established schemes, such as the Countryside Stewardship and Environmentally Sensitive Area Schemes, along with other less common mechanisms, for example, land purchase and tender schemes. The steps involved in applying an MCDA to evaluate such mechanisms are identified and the process is described. Quantitative results from the comparison of the effectiveness of different mechanisms are presented, although the broader aim of the paper is that of demonstrating the performance of MCDA as a tool for measuring the effectiveness of mechanisms aimed at landscape and habitat enhancement.

The effect of selective decontamination of the digestive tract on mortality in multiple trauma patients: a multicenter randomized controlled trial

Objective: Evaluation of selective decontamination of the digestive tract (SDD) on late mortality in ventilated trauma patients in an intensive care unit (ICU). Methods: A multicenter, randomized controlled trial was undertaken in 401 trauma patients with Hospital Trauma Index-Injury Severity Score of 16 or higher. Patients were randomized to control (n = 200) or SDD (n = 201), using polymyxin E, tobramycin, and amphotericin B in throat and gut throughout ICU treatment combined with cefotaxime for 4 days. Primary endpoint was late mortality excluding early death from hemorrhage or craniocerebral injury. Secondary endpoints were infection and organ dysfunction. Results: Mortality was 20.9% with SDD and 22.0% in controls. Overall late mortality was 15.3% (57/372) as 29 patients died from cerebral injury, 16 SDD and 13 control. The odds ratio (95% confidence intervals) of late mortality for SDD relative to control was 0.75 (0.40-1.37), corresponding to estimates of 13.4% SDD and 17.2% control. The overall infection rate was reduced in the test group (48.8% vs. 61.0%). SDD reduced lower airway infections (30.9% vs. 50.0%) and bloodstream infections due to aerobic Gram-negative bacilli (2.5% vs. 7.5%). No difference in organ dysfunction was found. Concluson: This study demonstrates that SDD significantly reduces infection in multiple trauma, although this RCT in 401 patients was underpowered to detect a mortality benefit.