The Wheal Jane wetlands model for bioremediation of acid mine drainage

Acid mine drainage (AMD) is a widespread environmental problem associated with both working and abandoned mining operations. As part of an overall strategy to determine a long-term treatment option for AMD, a pilot passive treatment plant was constructed in 1994 at Wheal Jane Mine in Cornwall, UK. The plant consists of three separate systems, each containing aerobic reed beds, anaerobic cell and rock filters, and represents the largest European experimental facility of its kind. The systems only differ by the type of pretreatment utilised to increase the pH of the influent minewater (pH <4): lime dosed (LD), anoxic limestone drain (ALD) and lime free (LF), which receives no form of pretreatment. Historical data (1994-1997) indicate median Fe reduction between 55% and 92%, sulphate removal in the range of 3-38% and removal of target metals (cadmium, copper and zinc) below detection limits, depending on pretreatment and flow rates through the system. A new model to simulate the processes and dynamics of the wetlands systems is described, as well as the application of the model to experimental data collected at the pilot plant. The model is process based, and utilises reaction kinetic approaches based on experimental microbial techniques rather than an equilibrium approach to metal precipitation. The model is dynamic and utilises numerical integration routines to solve a set of differential equations that describe the behaviour of 20 variables over the 17 pilot plant cells on a daily basis. The model outputs at each cell boundary are evaluated and compared with the measured data, and the model is demonstrated to provide a good representation of the complex behaviour of the wetland system for a wide range of variables. (C) 2004 Elsevier B.V/ All rights reserved.

A model for the evolution of pathogen-induced leaf shedding

A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

A model for the evolution of pathogen-induced leaf shedding

A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

Modeling the plant uptake of organic chemicals, including the soil-air-plant pathway

The soil−air−plant pathway is potentially important in the vegetative accumulation of organic pollutants from contaminated soils. While a number of qualitative frameworks exist for the prediction of plant accumulation of organic chemicals by this pathway, there are few quantitative models that incorporate this pathway. The aim of the present study was to produce a model that included this pathway and could quantify its contribution to the total plant contamination for a range of organic pollutants. A new model was developed from three submodels for the processes controlling plant contamination via this pathway: aerial deposition, soil volatilization, and systemic translocation. Using the combined model, the soil−air−plant pathway was predicted to account for a significant proportion of the total shoot contamination for those compounds with log KOA > 9 and log KAW < −3. For those pollutants with log KOA < 9 and log KAW > −3 there was a higher deposition of pollutant via the soil−air−plant pathway than for those chemicals with log KOA > 9 and log KAW < −3, but this was an insignificant proportion of the total shoot contamination because of the higher mobility of these compounds via the soil−root−shoot pathway. The incorporation of the soil−air−plant pathway into the plant uptake model did not significantly improve the prediction of the contamination of vegetation from polluted soils when compared across a range of studies. This was a result of the high variability between the experimental studies where the bioconcentration factors varied by 2 orders of magnitude at an equivalent log KOA. One potential reason for this is the background air concentration of the pollutants under study. It was found background air concentrations would dominate those from soil volatilization in many situations unless there was a soil hot spot of contamination, i.e., >100 mg kg−1.

A combined engineering and statistical model of UK domestic appliance electrical load profiles

The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.

Tackling drought stress: RECEPTOR-LIKE KINASES present new approaches

Global climate change and a growing population require tackling the reduction in arable land and improving biomass production and seed yield per area under varying conditions. One of these conditions is suboptimal water availability. Here, we review some of the classical approaches to dealing with plant response to drought stress and we evaluate how research on RECEPTOR-LIKE KINASES (RLKs) can contribute to improving plant performance under drought stress. RLKs are considered as key regulators of plant architecture and growth behavior, but they also function in defense and stress responses. The available literature and analyses of available transcript profiling data indeed suggest that RLKs can play an important role in optimizing plant responses to drought stress. In addition, RLK pathways are ideal targets for nontransgenic approaches, such as synthetic molecules, providing a novel strategy to manipulate their activity and supporting translational studies from model species, such as Arabidopsis thaliana, to economically useful crops.

The importance of sward architectural complexity in structuring predatory and phytophagous invertebrate assemblages

1. Although the importance of plant community assemblages in structuring invertebrate assemblages is well known, the role that architectural complexity plays is less well understood. In particular, direct empirical data for a range of invertebrate taxa showing how functional groups respond to plant architecture is largely absent from the literature. 2. The significance of sward architectural complexity in determining the species richness of predatory and phytophagous functional groups of spiders, beetles, and true bugs, sampled from 135 field margin plots over 2 years was tested. The present study compares the relative importance of sward architectural complexity to that of plant community assemblage. 3. Sward architectural complexity was found to be a determinant of species richness for all phytophagous and predatory functional groups. When individual species responses were investigated, 62.5% of the spider and beetle species, and 50.0% of the true bugs responded to sward architectural complexity. 4. Interactions between sward architectural complexity and plant community assemblage indicate that the number of invertebrate species supported by the plant community alone could be increased by modification of sward architecture. Management practices could therefore play a key role in diversifying the architectural structure of existing floral assemblages for the benefit of invertebrate assemblages. 5. The contrasting effects of sward architecture on invertebrate functional groups characterised by either direct (phytophagous species) or indirect (predatory species) dependence on plant communities is discussed. It is suggested that for phytophagous taxa, plant community assemblage alone is likely to be insufficient to ensure successful species colonisation or persistence without appropriate development of sward architecture.

Photoperiod sensitivity affects flowering duration in wheat

Flowering and successful pollination in wheat are key determinants of both quantity and quality of grain. Bread wheat line ‘Paragon’, introgressed with single or multiple day length insensitivity alleles was used to dissect the effects on the timing and duration of flowering within a hierarchical plant architecture. Flowering of wheat plants was observed in a series of pot-based and field experiments. Ppd-D1a was the most potent known allele affecting the timing of flowering, requiring the least thermal time to flowering across all experiments. The duration of flowering for individual lines was dominated by the shift in the start of flowering in later tillers and the number of tillers per plant, rather than variation in flowering duration of individual spikes. There was a strong relationship between flowering duration and the start of flowering with the earliest lines flowering for the longest. The greatest flowering overlap between tillers was recorded for the Ppd-1b. Across all lines, a warmer environment significantly reduced the duration of flowering and the influence of Ppd-1a alleles on the start of flowering. These findings provide evidence of pleiotropic effects of the Ppd-1a alleles, and have direct implications for breeding for increased stress resilient wheat varieties.

Suitability of Arabidopsis thaliana as a model for host plant-Plutella xylostella-Cotesia plutellae interactions

Successful pest management is often hindered by the inherent complexity of the interactions of a pest with its environment. The use of genetically characterized model plants can allow investigation of chosen aspects of these interactions by limiting the number of variables during experimentation. However, it is important to study the generic nature of these model systems if the data generated are to be assessed in a wider context, for instance, with those systems of commercial significance. This study assesses the suitability of Arabidopsis thaliana (L.) Heynh. (Brassicaceae) as a model host plant to investigate plant-herbivore-natural enemy interactions, with Plutella xylostella (L.) (Lepidoptera: Plutellidae), the diamondback moth, and Cotesia plutellae (Kurdjumov) (Hymenoptera: Braconidae), a parasitoid of P. xylostella. The growth and development of P. xylostella and C. plutellae on an A. thaliana host plant (Columbia type) were compared to that on Brassica rapa var. pekinensis (L.) (Brassicaceae), a host crop that is widely cultivated and also commonly used as a laboratory host for P. xylostella rearing. The second part of the study investigated the potential effect of the different A. thaliana background lines, Columbia and Landsberg (used in wider scientific studies), on growth and development of P. xylostella and C. plutellae. Plutella xylostella life history parameters were found generally to be similar between the host plants investigated. However, C. plutellae were more affected by the differences in host plant. Fewer adult parasitoids resulted from development on A. thaliana compared to B. rapa, and those that did emerge were significantly smaller. Adult male C. plutellae developing on Columbia were also significantly smaller than those on Landsberg A. thaliana.

A novel method for assessing risks to pollinators from plant protection products using honeybees as a model species

Pollination is one of the most important ecosystem services in agroecosystems and supports food production. Pollinators are potentially at risk being exposed to pesticides and the main route of exposure is direct contact, in some cases ingestion, of contaminated materials such as pollen, nectar, flowers and foliage. To date there are no suitable methods for predicting pesticide exposure for pollinators, therefore official procedures to assess pesticide risk are based on a Hazard Quotient. Here we develop a procedure to assess exposure and risk for pollinators based on the foraging behaviour of honeybees (Apis mellifera) and using this species as indicator representative of pollinating insects. The method was applied in 13 European field sites with different climatic, landscape and land use characteristics. The level of risk during the crop growing season was evaluated as a function of the active ingredients used and application regime. Risk levels were primarily determined by the agronomic practices employed (i.e. crop type, pest control method, pesticide use), and there was a clear temporal partitioning of risks through time. Generally the risk was higher in sites cultivated with permanent crops, such as vineyard and olive, than in annual crops, such as cereals and oil seed rape. The greatest level of risk is generally found at the beginning of the growing season for annual crops and later in June–July for permanent crops.

Measuring Enterprise Architecture success: a tentative model for measuring success

Interest towards Enterprise Architecture (EA) has been increasing during the last few years. EA has been found to be a crucial aspect of business survival, and thus the importance of EA implementation success is also crucial. Current literature does not have a tool to be used to measure the success of EA implementation. In this paper, a tentative model for measuring success is presented and empirically validated in EA context. Results show that the success of EA implementation can be measured indirectly by measuring the achievement of the objectives set for the implementation. Results also imply that achieving individual's objectives do not necessarily mean that organisation's objectives are achieved. The presented Success Measurement Model can be used as basis for developing measurement metrics.