Development and testing of a risk indexing framework to determine field-scale critical source areas of faecal bacteria on grassland.

This paper draws on lessons from a UK case study in the management of diffuse microbial pollution from grassland farm systems in the Taw catchment, south west England. We report on the development and preliminary testing of a field-scale faecal indicator organism risk indexing tool (FIORIT). This tool aims to prioritise those fields most vulnerable in terms of their risk of contributing FIOs to water. FIORIT risk indices were related to recorded microbial water quality parameters (faecal coliforms [FC] and intestinal enterococci [IE]) to provide a concurrent on-farm evaluation of the tool. There was a significant upward trend in Log[FC] and Log[IE] values with FIORIT risk score classification (r2 =0.87 and 0.70, respectively and P<0.01 for both FIOs). The FIORIT was then applied to 162 representative grassland fields through different seasons for ten farms in the case study catchment to determine the distribution of on-farm spatial and temporal risk. The high risk fields made up only a small proportion (1%, 2%, 2% and 3% for winter, spring, summer and autumn, respectively) of the total number of fields assessed (and less than 10% of the total area), but the likelihood of the hydrological connection of high FIO source areas to receiving watercourses makes them a priority for mitigation efforts. The FIORIT provides a preliminary and evolving mechanism through which we can combine risk assessment with risk communication to end-users and provides a framework for prioritising future empirical research. Continued testing of FIORIT across different geographical areas under both low and high flow conditions is now needed to initiate its long term development into a robust indexing tool

An analysis of the likely success of policy actions under uncertainty: recovery from acidification across Great Britain

In the context of wider debates about the role of uncertainty in environmental science and the development of environmental policy, we use a Generalised Likelihood Uncertainty Estimate (GLUE) approach to address the uncertainty in both acid deposition model predictions and in the sensitivity of the soils to assess the likely success of policy actions to reduce acid deposition damage across Great Britain. A subset of 11,699 acid deposition model runs that adequately represented observed deposition data were used to provide acid deposition distributions for 2005 and 2020, following a substantial reduction in SO2 and NOx emissions. Uncertain critical loads data for soils were then combined with these deposition data to derive estimates of the accumulated exceedance (AE) of critical loads for 2005 and 2020. For the more sensitive soils, the differences in accumulated exceedance between 2005 and 2020 were such that we could be sure that they were significant and a meaningful environmental improvement would result. For the least sensitive soils, critical loads were largely met by 2020, hence uncertainties in the differences in accumulated exceedance were of little policy relevance. Our approach of combining estimates of uncertainty in both a pollution model and an effects model, shows that even taking these combined uncertainties into account, policy-makers can be sure that the substantial planned reduction in acidic emissions will reduce critical loads exceedances. The use of accumulated exceedance as a relative measure of environmental protection provides additional information to policy makers in tackling this ‘wicked problem’

Strategies for Testing the Impact of Natural Flood Risk Management Measures

Natural Flood Management (NFM) is an approach that seeks to work with natural processes to enhance the flood regulating capacity of a catchment, whilst delivering a wide range of ecosystem services, from pollution assimilation to habitat creation and carbon storage. This chapter describes a tiered approach to NFM, commencing with strategic modelling to identify a range of NFM opportunities (tree-planting, distributed runoff attenuation features, and soil structure improvements), and their potential benefits, before engagement with catchment partners, and prioritisation of areas for more detailed hydrological modelling and uncertainty analysis. NFM measures pose some fundamental challenges in modelling their contribution to flood risk management because they are often highly distributed, can influence multiple catchment processes, and evidence for their effectiveness at the large scale is uncertain. This demands we model the ‘upstream’ in more detail so that we can assess the effectiveness of many small-scale changes at the large-scale. We demonstrate an approach to address these challenges employing the fast, high resolution, fully-distributed inundation model JFLOW, and visualisation of potential benefits in map form. These are used to engage catchment managers who can prioritise areas for potential deployment of NFM measures, where more detailed modelling may be targeted. We then demonstrate a framework applying the semi-distributed Dynamic TOPMODEL in which uncertainty plays an integral role in the decision-making process

Floating photovoltaics could mitigate climate change impacts on water body temperature and stratification

Floating solar photovoltaics, or floatovoltaics (FPV), are a relatively new form of renewable energy, currently experiencing rapid growth in deployment. FPV decarbonises the energy supply while reducing land-use pressures, offers higher electricity generating efficiencies compared to ground-based systems and reduces water body evaporation. However, the effects on lake temperature and stratification of FPV both sheltering the water’s surface from the wind and limiting the solar radiation reaching the water column are unresolved, despite temperature and stratification being key drivers of the ecosystem response to FPV deployment. These unresolved impacts present a barrier to further deployment, with water body managers concerned of any deleterious effects. To overcome this knowledge gap, here the effects of FPV-induced changes in wind speed and solar radiation on lake thermal structure were modelled utilising the one-dimensional process-based MyLake model. To resolve the effect of FPV arrays of different sizes and designs, observed wind speed and solar radiation were scaled using a factorial approach from 0% to 100% in 1% intervals. The simulations returned a highly non-linear response, dependent on system design and coverage. The responses could be either positive or negative, and were often highly variable, although, most commonly, water temperatures reduce, stratification shortens and mixed depths shallow. Modifications to the thermal dynamics of the water body may subsequently drastically alter biogeochemical processes, with fundamental implications for ecosystem service provision and water treatment costs. The extreme nature of response for particular wind speed and solar radiation combinations results in impacts that could be comparable to, or more significant than, climate change. As such, depending on how they are used, FPV have the potential to mitigate some of the impacts of climate change on water bodies and could be a useful tool for water body managers in dealing with changes to water quality, or, conversely, they could induce deleterious impacts on standing water ecosystems. These simulations provide a starting point to inform the design of future systems that maximise ecosystem service and environmental co-benefits from this growing water body change of use

Adaptive forecasting of phytoplankton communities

The global proliferation of harmful algal blooms poses an increasing threat to water resources, recreation and ecosystems. Predicting the occurrence of these blooms is therefore needed to assist water managers in making management decisions to mitigate their impact. Evaluation of the potential for forecasting of algal blooms using the phytoplankton community model PROTECH was undertaken in pseudo-real-time. This was achieved within a data assimilation scheme using the Ensemble Kalman Filter to allow uncertainties and model nonlinearities to be propagated to forecast outputs. Tests were made on two mesotrophic lakes in the English Lake District, which differ in depth and nutrient regime. Some forecasting success was shown for chlorophyll a, but not all forecasts were able to perform better than a persistence forecast. There was a general reduction in forecast skill with increasing forecasting period but forecasts for up to four or five days showed noticeably greater promise than those for longer periods. Associated forecasts of phytoplankton community structure were broadly consistent with observations but their translation to cyanobacteria forecasts was challenging owing to the interchangeability of simulated functional species

Engineering Temperature‐Dependent Carrier Concentration in Bulk Composite Materials via Temperature‐Dependent Fermi Level Offset

Precise control of carrier concentration in both bulk and thin‐film materials is crucial for many solid‐state devices, including photovoltaic cells, superconductors, and high mobility transistors. For applications that span a wide temperature range (thermoelectric power generation being a prime example) the optimal carrier concentration varies as a function of temperature. This work presents a modified modulation doping method to engineer the temperature dependence of the carrier concentration by incorporating a nanosize secondary phase that controls the temperature‐dependent doping in the bulk matrix. This study demonstrates this technique by de‐doping the heavily defect‐doped degenerate semiconductor GeTe, thereby enhancing its average power factor by 100% at low temperatures, with no deterioration at high temperatures. This can be a general method to improve the average thermoelectric performance of many other materials.Temperature‐dependent modulation doping is demonstrated in a GeTe–CuInTe2 composite material. Temperature‐dependent carrier concentration is achieved by controlling the temperature‐dependent Fermi level offset between the GeTe matrix and CuInTe2 inclusions. An enhanced average power factor over a wide temperature range is demonstrated.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141881/1/aenm201701623.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141881/2/aenm201701623-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141881/3/aenm201701623_am.pd

Phylogenetic Analysis of Klebsiella pneumoniae from Hospitalized Children, Pakistan.

Klebsiella pneumoniae shows increasing emergence of multidrug-resistant lineages, including strains resistant to all available antimicrobial drugs. We conducted whole-genome sequencing of 178 highly drug-resistant isolates from a tertiary hospital in Lahore, Pakistan. Phylogenetic analyses to place these isolates into global context demonstrate the expansion of multiple independent lineages, including K. quasipneumoniae.This work was supported by National Health and Medical Research Council program grants (0606788 to R.A.S. and T. L.; 1092262 to R.A.S., G.D., and T.L.); the Wellcome Trust (206194); and the Higher Education Commission of Pakistan and The Children’s Hospital & The Institute of Child Health, Lahore, Pakistan. H.E. was supported by a scholarship from Higher Education Commission Pakistan under the International Research Support Initiative Program

Do Child Soldiers Influence UN Peacekeeping?

The use of child soldiers in conflicts has received increasing academic attention in recent years. This article examines post-conflict periods to see whether the use of child soldiers mobilizes United Nations peacekeeping operations (UN PKO) in the aftermath of a conflict. Taking into consideration how child soldiers affect conflict and how important their reintegration is to sustainable peace and post-conflict development, we analyse whether the presence of child soldiers in a civil war increases the likelihood of the presence of a PKO. We argue that the UN deems a conflict with child soldiers as a difficult case for conflict resolution, necessitating a response from the international community. This is in line with our empirical results confirming that the use of child soldiers significantly increases the likelihood of peacekeeping

Re-shaping models of E.coli population dynamics in livestock faeces: Increased bacterial risk to humans?

Dung-pats excreted directly on pasture from grazing animals can contribute a significant burden of faecal microbes to agricultural land. The aim of this study was to use a combined field and modelling approach to determine the importance of Escherichia coli growth in dung-pats when predicting faecal bacteria accumulation on grazed grassland. To do this an empirical model was developed to predict the dynamics of an E. coli reservoir within 1 ha plots each grazed by four beef steers for six months. Published first-order die-off coefficients were used within the model to describe the expected decline of E. coli in dung-pats. Modelled estimates using first-order kinetics led to an underestimation of the observed E. coli land reservoir, when using site-specific die-off coefficients. A simultaneous experiment determined the die-off profiles of E. coli within fresh faeces of beef cattle under field relevant conditions and suggested that faecal bacteria may experience growth and re-growth in the period post defecation when exposed to a complex interaction of environmental drivers such as variable temperature, UV radiation and moisture levels. This growth phase in dung-pats is not accounted for in models based on first-order die-off coefficients. When the model was amended to incorporate the growth of E. coli, equivalent to that observed in the field study, the prediction of the E. coli reservoir was improved with respect to the observed data and produced a previously unquantified step-change improvement in model predictions of the accumulation of these faecal bacteria on grasslands. Results from this study suggest that the use of first-order kinetic equations for determining land-based reservoirs of faecal bacteria should be approached with caution and greater emphasis placed on accounting for actual survival patterns observed under field relevant conditions