Miscanthus is a perennial energy grass predominantly used for combustion but there is increasing interest in fermenting the cell-wall carbohydrates or green-cutting for soluble sugars to produce bioethanol. Our aims were to: (1) quantify non-structural carbohydrates (NSC), (2) observe the timing of seasonal shifts in the stems and rhizome, and (3) identify developmental and/or climatic conditions that promoted carbohydrate remobilization from the stems to the rhizome during senescence. Two genotypes of Miscanthus sinensis, a Miscanthus sacchariflorus and a Miscanthus × giganteus were grown at replicated field sites in Aberystwyth, West Wales and Harpenden, South East England. NSC were quantified from the rhizome and aboveground organs and then correlated with climatic data collected from on-site weather stations. PAR and maximum daily temperatures were higher at Harpenden throughout the year, but daily minimum temperatures were lower. Senescence was accelerated at Harpenden. Carbohydrates were retained within the stems of nonflowering genotypes, at both sites, in winter and were still present after a frost event to −2°C. Rhizome starch concentrations were at least equal to the previous winter's levels (February 2011) by September. Lower daily minimum temperatures accelerate the rate of senescence and warmer daily maximum temperatures cannot counteract this effect. At current yields, M. × giganteus, could produce 0.7 t ha −1 of NSC in addition to ligno-cellulosic biomass in November but with concerted breeding efforts this could be targeted for improvement as has been achieved in other crops. Shifting harvests forward to November would not leave the rhizome depleted of carbohydrates.

The ecosystem services approach endeavours to incorporate the economic value of ecosystems into decision making. This is because many natural resources are subject to market failure. As a result many economic decisions omit the impact that natural resource use has on the earth's resources and the life support system it provides. Hence, one of the objectives of the ecosystem services approach is to employ economic valuation of natural resources in micro-and macro-economic policy design, implementation and evaluation.

Willows (Salix spp.) grown as short rotation coppice (SRC) are viewed as a sustainable source of biomass with a positive greenhouse gas (GHG) balance due to their potential to fix and accumulate carbon (C) below ground. However, exploiting this potential has been limited by the paucity of data available on below ground biomass allocation and the extent to which it varies between genotypes. Furthermore, it is likely that allocation can be altered considerably by environment. To investigate the role of genotype and environment on allocation, four willow genotypes were grown at two replicated field sites in southeast England and west Wales, UK. Above and below ground biomass was intensively measured over two two-year rotations. Significant genotypic differences in biomass allocation were identified, with below ground allocation differing by up to 10% between genotypes. Importantly, the genotype with the highest below ground biomass also had the highest above ground yield. Furthermore, leaf area was found to be a good predictor of below ground biomass. Growth environment significantly impacted allocation; the willow genotypes grown in west Wales had up to 94% more biomass below ground by the end of the second rotation. A single investigation into fine roots showed the same pattern with double the volume of fine roots present. This greater below ground allocation may be attributed primarily to higher wind speeds, plus differences in humidity and soil characteristics. These results demonstrate that the capacity exists to breed plants with both high yields and high potential for C accumulation.

Background and AimsThe bioenergy grass Miscanthus is native to eastern Asia. As Miscanthus uses C4 photosynthesis, the cooler temperatures experienced in much of northern Europe are expected to limit productivity. Identification of genetic diversity in chilling tolerance will enable breeders to generate more productive varieties for these cooler regions. Characterizing the temporal relationships between photosynthesis, carbohydrate and molecular expression of relevant genes is key to understanding genotypic differences in tolerance or sensitivity.MethodsTo characterize chilling responses in four Miscanthus genotypes, plants were exposed to a sudden reduction in temperature. The genotypes studied comprised of two M. sinensis, one M. sacchariflorus and one inter-species hybrid, M. × giganteus. Changes in photosynthesis (Asat), carbohydrate composition and the expression of target transcripts were observed following chilling-shock. After 4 d the decline in leaf elongation rate (LER) in the different genotypes was measured.ResultsFollowing chilling-shock the greatest decline in Asat was observed in M. sacchariflorus and one M. sinensis genotype. Carbohydrate concentrations increased in all genotypes following chilling but to a lesser extent in M. sacchariflorus. Two stress inducible genes were most highly expressed in the genotypes that experienced the greatest declines in Asat and LER. Miscanthus × giganteus retained the highest Asat and was unique in exhibiting no decline in LER following transfer to 12 °C.ConclusionsMiscanthus × giganteus exhibits a superior tolerance to chilling shock than other genotypes of Miscanthus. The absence of sucrose accumulation in M. sacchariflorus during chilling-shock suggests an impairment in enzyme function. A candidate transcription factor, MsCBF3, is most highly expressed in the most sensitive genotypes and may be a suitable molecular marker for predicting chilling sensitivity.

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. 2012 Methane, carbon dioxide and nitrous oxide fluxes from a temperate salt marsh: grazing management does not alter global warming potential.Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.

Improved understanding and prediction of the fundamental environmental controls on ecosystem service supply across the landscape will help to inform decisions made by policy makers and land-water managers. To evaluate this issue for a local catchment case study, we explored metrics and spatial patterns of service supply for water quality regulation, agriculture production, carbon storage, and biodiversity for the Macronutrient Conwy catchment. Methods included using ecosystem models such as LUCI and JULES, integration of national scale field survey datasets, earth observation products and plant trait databases, to produce finely resolved maps of species richness and primary production. Analyses were done with both 1×1km gridded and subcatchment data. A common single gradient characterised catchment scale ecosystem services supply with agricultural production and carbon storage at opposing ends of the gradient as reported for a national-scale assessment. Species diversity was positively related to production due to the below national average productivity levels in the Conwy combined with the unimodal relationship between biodiversity and productivity at the national scale. In contrast to the national scale assessment, a strong reduction in water quality as production increased was observed in these low productive systems. Various soil variables were tested for their predictive power of ecosystem service supply. Soil carbon, nitrogen, their ratio and soil pH all had double the power of rainfall and altitude, each explaining around 45% of variation but soil pH is proposed as a potential metric for ecosystem service supply potential as it is a simple and practical metric which can be carried out in the field with crowd-sourcing technologies now available. The study emphasises the importance of considering multiple ecosystem services together due to the complexity of covariation at local and national scales, and the benefits of exploiting a wide range of metrics for each service to enhance data robustness.