Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Duration from vine emergence to flowering suggests a long-day or rate of change of photoperiod response in white yam (Dioscorea rotundata Poir.)

The objective of this study was to quantify the effect of photoperiod on the duration from vine (shoot) emergence to flowering in white or Guinea yam (Dioscorea rotundata). The duration from vine emergence to flowering in two clonal varieties of yam (TDr 131 and TDr 99-9) was recorded at 10 different sowing dates/locations in Nigeria. Durations to flowering varied from 40 to > 88 days. Mean daily temperature and photoperiod between vine emergence and flowering varied from 25 to 27 degrees C and 13.1 to 13.4 h day(-1), respectively. Both clones had similar responses to temperature, with base and optimum temperatures of 12 and 25-27 degrees C, respectively. Thermal durations to flowering were strongly related (r(2) > 0.75-0.83) to absolute photoperiod (h) at vine emergence as well as to rate of change of photoperiod (s day(-1)) at vine emergence. The response to absolute photoperiod suggests that white yams are quantitative LDPs, flowering sooner in long than short days. Yams also flowered earlier when the rate of change of photoperiod was positive but small, or was negative. It is suggested that yams may use a combination of photoperiod and rate of change in order to fine tune flowering time. (c) 2006 Elsevier B.V. All rights reserved.

Domestication of plants revisited - Darwin to the present day

Darwin studied domesticated plants and animals to try to understand the causes of variability. He observed that variation is greatest in the part of the plant most used by humans, but explanations of the causes of this variation had to await the discovery of Mendelian genetics and subsequent advances in the understanding of the structure and mode of action of genes, from the one gene, one enzyme hypothesis to the role of transcriptional regulators. Darwin credited his studies on domesticated plants and animals with demonstrating to him the power of selection. He recognized two forms of human-mediated selection, methodical and unconscious, in addition to natural selection. Selection leaves a signature in the form of reduced diversity in genes that have been the targets of selection and in 'hitch-hiking' genomic regions linked to the target genes. These so-called selective sweeps may serve now to identify genes targeted by selection in early stages of domestication and thus provide a possible guide to crop improvement in future. (C) 2009 The Linnean Society of London, Botanical Journal of the Linnean Society, 2009, 161, 203-212.

Assembly and maintenance of the sarcomere night and day

The assembly of sarcomeric proteins into the highly organized structure of the sarcomere is an ordered and complex process involving an array of structural and associated proteins. The sarcomere has shown itself to be considerably more complex than ever envisaged and may be considered one of the most complex macromolecular assemblies in biology. Studies over the last decade have helped to put a new face on the sarcomere, and, as such, the sarcomere is being redefined as a dynamic network of proteins capable of generating force and signalling with other cellular compartments and metabolic enzymes capable of controlling many facets of striated myocyte biology.

Duration from vine emergence to flowering suggests a long-day or rate of change of photoperiod response in white yam (Dioscorea rotundata Poir.)

The objective of this study was to quantify the effect of photoperiod on the duration from vine (shoot) emergence to flowering in white or Guinea yam (Dioscorea rotundata). The duration from vine emergence to flowering in two clonal varieties of yam (TDr 131 and TDr 99-9) was recorded at 10 different sowing dates/locations in Nigeria. Durations to flowering varied from 40 to > 88 days. Mean daily temperature and photoperiod between vine emergence and flowering varied from 25 to 27 degrees C and 13.1 to 13.4 h day(-1), respectively. Both clones had similar responses to temperature, with base and optimum temperatures of 12 and 25-27 degrees C, respectively. Thermal durations to flowering were strongly related (r(2) > 0.75-0.83) to absolute photoperiod (h) at vine emergence as well as to rate of change of photoperiod (s day(-1)) at vine emergence. The response to absolute photoperiod suggests that white yams are quantitative LDPs, flowering sooner in long than short days. Yams also flowered earlier when the rate of change of photoperiod was positive but small, or was negative. It is suggested that yams may use a combination of photoperiod and rate of change in order to fine tune flowering time. (c) 2006 Elsevier B.V. All rights reserved.

Reproducibility of a short semi-quantitative food group questionnaire and its performance in estimating nutrient intake compared with a 7-day diet diary in the Million Women Study

Objectives: To assess the short- and long-term reproducibility of a short food group questionnaire, and to compare its performance for estimating nutrient intakes in comparison with a 7-day diet diary. Design: Participants for the reproducibility study completed the food group questionnaire at two time points, up to 2 years apart. Participants for the performance study completed both the food group questionnaire and a 7-day diet diary a few months apart. Reproducibility was assessed by kappa statistics and percentage change between the two questionnaires; performance was assessed by kappa statistics, rank correlations and percentages of participants classified into the same and opposite thirds of intake. Setting: A random sample of participants in the Million Women Study, a population-based prospective study in the UK. Subjects: In total, 12 221 women aged 50-64 years. Results: in the reproducibility study, 75% of the food group items showed at least moderate agreement for all four time-point comparisons. Items showing fair agreement or worse tended to be those where few respondents reported eating them more than once a week, those consumed in small amounts and those relating to types of fat consumed. Compared with the diet diary, the food group questionnaire showed consistently reasonable performance for the nutrients carbohydrate, saturated fat, cholesterol, total sugars, alcohol, fibre, calcium, riboflavin, folate and vitamin C. Conclusions: The short food group questionnaire used in this study has been shown to be reproducible over time and to perform reasonably well for the assessment of a number of dietary nutrients.

Effect of time of day and rabbit strain on patterns of aortic wall permeability

Lipid deposits occur more frequently downstream of branch points than upstream in immature rabbit and human aortas but the opposite pattern is seen in mature vessels. These distributions correlate spatially with age-related patterns of aortic permeability, observed in rabbits, and may be determined by them. The mature but not the immature pattern of permeability is dependent on endogenous nitric oxide synthesis. Although the transport patterns have hitherto seemed robust, recent studies have given the upstream pattern in some mature rabbits but the downstream pattern in others. Here we show that transport in mature rabbits is significantly skewed to the downstream pattern in the afternoon compared with the morning (P < 0.05), and switches from a downstream to an upstream pattern at around 21 months in rabbits of the Murex strain, but at twice this age in Highgate rabbits (P < 0.001). The effect of time of day was not explained by changes in nitric oxide production, assessed from plasma levels of nitrate and nitrate, nor did it correlate with conduit artery tone, assessed from the shape of the peripheral pulse wave. The effect of strain could not be explained by variation in nitric oxide production nor by differences in wall structure. The effects of time of day and rabbit strain on permeability patterns explain recent discrepancies, provide a useful tool for investigating underlying mechanisms and may have implications for human disease.

A two-locus forensic match probability for subdivided populations

A two-locus match probability is presented that incorporates the effects of within-subpopulation inbreeding (consanguinity) in addition to population subdivision. The usual practice of calculating multi-locus match probabilities as the product of single-locus probabilities assumes independence between loci. There are a number of population genetics phenomena that can violate this assumption: in addition to consanguinity, which increases homozygosity at all loci simultaneously, gametic disequilibrium will introduce dependence into DNA profiles. However, in forensics the latter problem is usually addressed in part by the careful choice of unlinked loci. Hence, as is conventional, we assume gametic equilibrium here, and focus instead on between-locus dependence due to consanguinity. The resulting match probability formulae are an extension of existing methods in the literature, and are shown to be more conservative than these methods in the case of double homozygote matches. For two-locus profiles involving one or more heterozygous genotypes, results are similar to, or smaller than, the existing approaches.

The case of negative day-ahead electricity prices

In recent years, Germany has significantly increased its share of electricity produced from renewable sources, which is mainly due to the Renewable Energy Act (EEG). The EEG substantially impacts the dynamics of intra-day electricity prices by increasing the likelihood of negative prices. In this paper, we present a non-Gaussian process to model German intra-day electricity prices and propose an estimation procedure for this model. Most importantly, our model is able to generate extreme positive and negative spikes. A simulation study demonstrates the ability of our model to capture the characteristics of the data.