87 resultados para Tree Database
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The Genomic Threading Database currently contains structural annotations for the genomes of over 100 recently sequenced organisms. Annotations are carried out by using our modified GenTHREADER software and through implementing grid technology.
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A range of physiological parameters (canopy light transmission, canopy shape, leaf size, flowering and flushing intensity) were measured from the International Clone Trial, typically over the course of two years. Data were collected from six locations, these being: Brazil, Ecuador, Trinidad, Venezuela, Côte d’Ivoire and Ghana. Canopy shape varied significantly between clones, although it showed little variation between locations. Genotypic variation in leaf size was differentially affected by the growth location; such differences appeared to underlie a genotype by environment interaction in relation to canopy light transmission. Flushing data were recorded at monthly intervals over the course of a year. Within each location, a significant interaction was observed between genotype and time of year, suggesting that some genotypes respond to a greater extent than others to environmental stimuli. A similar interaction was observed for flowering data, where significant correlations were found between flowering intensity and temperature in Brazil and flowering intensity and rainfall in Côte d’Ivoire. The results demonstrate the need for local evaluation of cocoa clones and also suggest that the management practices for particular planting material may need to be fine-tuned to the location in which they are cultivated.
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Background: The characterization of phytoestrogen intake and cancer risk has been hindered by the absence of accurate dietary phytoestrogen values. Objective: We examined the risk of breast, colorectal, and prostate cancers relative to phytoestrogen intake on the basis of a comprehensive database. Design: Demographic and anthropometric characteristics, a medical history, and 7-d records of diet were collected prospectively from participants (aged 40–79 y) in the European Prospective Investigation into Cancer and Nutrition–Norfolk (EPIC-Norfolk). Five hundred nine food items were analyzed by liquid chromatography–mass spectrometry/mass spectrometry, and 13C3-labeled internal standards were analyzed for isoflavones (genistein, daidzein, glycitein, biochanin A, and formononetin), lignans (secoisolariciresinol and matairesinol), and enterolignans from gut microbial metabolism in animal food sources (equol and enterolactone). From the direct analysis, values for 10,708 foods were calculated. Odds ratios (ORs) for breast (244 cases, 941 controls), colorectal (221 cases, 886 controls), and prostate (204 cases, 812 controls) cancers were calculated relative to phytoestrogen intake. Results: Phytoestrogen intake was not associated with breast cancer among women or colorectal cancer among men. Among women, colorectal cancer risk was inversely associated with enterolactone (OR: 0.33; 95% CI: 0.14, 0.74) and total enterolignans (OR: 0.32; 95% CI: 0.13, 0.79), with a positive trend detected for secoisolariciresinol (OR: 1.60; 95% CI: 0.96, 2.69). A positive trend between enterolignan intake and prostate cancer risk (OR: 1.27; 95% CI: 0.97, 1.66) was attenuated after adjustment for dairy intake (OR: 1.19; 95% CI: 0.77, 1.82). Conclusion: Dietary phytoestrogens may contribute to the risk of colorectal cancer among women and prostate cancer among men.
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Objective: A phytoestrogen-rich diet has been suggested to protect against a variety of common diseases but UK intake data on phytoestrogens or their food sources is sparse. This study aims to estimate the average intake of isoflavones, lignans, enterolignans and coumestrol from 7-day food diaries (7dFD), and to provide data on total isoflavone, lignan and phytoestrogen consumption by food group. Design: Development of a food composition database for twelve phytoestrogens and analysis of soya food and phytoestrogen consumption in a population-based study. Setting: Men and women, aged 40-79 years from the general population participating in EPIC-Norfolk between 1993 and 1997, with nutrient and food data from 7dFD. Subjects: A subset of 20 437 participants. Results: The median daily phytoestrogen intake for men was 1.20mg (interquartile range (IQR) 0.93-1.54 mg; mean 1.50 mg, SD 1.50 mg) and 0.89 mg for women (IQR 0.71-1.14 mg; mean 1.20 mg, SD 1.70 mg). In soya-consumers (SC), median daily intakes were higher: 2.86 mg in men (IQR – 1.30-7.27mg; mean 5.05 mg, SD 5.03 mg) and 3.14 mg in women (IQR – 1.09-7.33mg; mean 5.40 mg, SD 6.09 mg). In both men and women, bread made the greatest contribution to phytoestrogen intake – 40.7% and 35.7% respectively. In SC men and women, vegetable dishes and soya/goat’s/sheep’s milks were the main contributors – 42.6% and 18.9% in men and 38.8% and 29.1% in women, respectively. Conclusions: The ability to estimate phytoestrogen intake in Western populations more accurately will aid investigations into their suggested effects on health.
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As a consequence of land use change and the burning of fossil fuels, atmospheric concentrations of CO2 are increasing and altering the dynamics of the carbon cycle in forest ecosystems. In a number of studies using single tree species, fine root biomass has been shown to be strongly increased by elevated CO2. However, natural forests are often intimate mixtures of a number of co-occurring species. To investigate the interaction between tree mixture and elevated CO2, Alnus glutinosa, Betula pendula and Fagus sylvatica were planted in areas of single species and a three species polyculture in a free-air CO2 enrichment study (BangorFACE). The trees were exposed to ambient or elevated CO2 (580 µmol mol-1) for four years. Fine and coarse root biomass, together with fine root turnover and fine root morphological characteristics were measured. Fine root biomass, and morphology responded differentially to elevated CO2 at different soil depths in the three species when grown in monocultures. In polyculture, a greater response to elevated CO2 was observed in coarse roots to a depth of 20 cm, and fine root area index to a depth of 30 cm. Total fine root biomass was positively affected by elevated CO2 at the end of the experiment, but not by species diversity. Our data suggest that existing biogeochemical cycling models parameterised with data from species grown in monoculture may be underestimating the belowground response to global change.
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Background and Aims Forest trees directly contribute to carbon cycling in forest soils through the turnover of their fine roots. In this study we aimed to calculate root turnover rates of common European forest tree species and to compare them with most frequently published values. Methods We compiled available European data and applied various turnover rate calculation methods to the resulting database. We used Decision Matrix and Maximum-Minimum formula as suggested in the literature. Results Mean turnover rates obtained by the combination of sequential coring and Decision Matrix were 0.86 yr−1 for Fagus sylvatica and 0.88 yr−1 for Picea abies when maximum biomass data were used for the calculation, and 1.11 yr−1 for both species when mean biomass data were used. Using mean biomass rather than maximum resulted in about 30 % higher values of root turnover. Using the Decision Matrix to calculate turnover rate doubled the rates when compared to the Maximum-Minimum formula. The Decision Matrix, however, makes use of more input information than the Maximum-Minimum formula. Conclusions We propose that calculations using the Decision Matrix with mean biomass give the most reliable estimates of root turnover rates in European forests and should preferentially be used in models and C reporting.
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Extratropical cyclone lifecycles have been studied extensively with the aim of understanding the dynamical mechanisms involved in their development. Previous work has often been based on subjective analysis of individual case studies. Such case studies have contributed heavily to the generation of conceptual models of extratropical cyclones that provide a framework for understanding the dynamical evolution of cyclones. These conceptual models are widely used in educational meteorology courses throughout the world to illustrate the basic structure and evolution of extratropical cyclones. This article presents a database of extratropical cyclone composites which highlight the average structure and evolution of 20 years of extratropical cyclones, as opposed to individual case studies. The composite fields are achieved by combining a database containing cyclone tracks from the ERA-Interim reanalysis (1989-2009, 6 hourly) with the full 3D ERA-Interim reanalysis fields. Vertical and horizontal composites of cyclone structure for cyclones generated in the Atlantic and Pacific regions identifying features such as the relative positions of cold, warm and occluded fronts and their associated wind and cloud patterns are shown. In addition the evolution of cyclonic flows such as the warm and cold conveyor belts and dry intrusion are illustrated. A webpage containing an archive of the composited data is freely available for educational purposes.
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This article clarifies what was done with the sub-7-man positions in data-mining Harold van der Heijden's 'HHdbIV' database of chess studies prior to its publication. It emphasises that only positions in the main lines of studies were examined and that the information about uniqueness of move was not incorporated in HHdbIV. There is some reflection on the separate technical and artistic dimensions of study evaluation.
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Four commercially available, biostimulants sold under the trade names ‘Generate’, ‘Crop Set’, ‘Fulcrum’ and ‘Redicrop 2000’ were applied either as a root drench or foliar spray to three transplant-sensitive tree species, red oak(Quercus rubra), birch(Betula pendula) and beech (Fagus sylvatica) post transplanting. The short and long-term efficacy of the biostimulants on growth was quantified by recording root and shoot vigour at week 8 and 20. In addition, improvements in tree vitality were assessed by measurement of a chlorophyll a performance index based on leaf chlorophyll fluorescence emissions. Irrespective of species, no significant effect of mode of application (foliar spray versus root drench) was recorded on growth and vitality. The biostimulants Generate and Fulcrum increased growth of all three tree species. No significant effects on growth and chlorophyll fluorescence of birch and beech were recorded following applications of the biostimulants Crop Set and Redicrop 2000, however, significant increase in growth of red oak was recorded. Only the biostimulant Generate increased chlorophyll fluorescence values of all test species. Results show use of biostimulants can improve root and shoot vigour following transplanting. However, selection of an appropriate biostimulant is critical as effects on growth and vitality can vary widely between tree species possibly as a result of the differing active ingredient used in the formulation of the product.
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A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multimodel mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISSPUCCINI)and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23Wm−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08Wm−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05Wm−2, but which is within the stated range of −0.15 to +0.05Wm−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1Wm−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/).
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Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.
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The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead.
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Version 1 of the Global Charcoal Database is now available for regional fire history reconstructions, data exploration, hypothesis testing, and evaluation of coupled climate–vegetation–fire model simulations. The charcoal database contains over 400 radiocarbon-dated records that document changes in charcoal abundance during the Late Quaternary. The aim of this public database is to stimulate cross-disciplinary research in fire sciences targeted at an increased understanding of the controls and impacts of natural and anthropogenic fire regimes on centennial-to-orbital timescales. We describe here the data standardization techniques for comparing multiple types of sedimentary charcoal records. Version 1 of the Global Charcoal Database has been used to characterize global and regional patterns in fire activity since the last glacial maximum. Recent studies using the charcoal database have explored the relation between climate and fire during periods of rapid climate change, including evidence of fire activity during the Younger Dryas Chronozone, and during the past two millennia.
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This letter has tested the canopy height profile (CHP) methodology as a way of effective leaf area index (LAIe) and vertical vegetation profile retrieval at a single-tree level. Waveform and discrete airborne LiDAR data from six swaths, as well as from the combined data of six swaths, were used to extract the LAIe of a single live Callitris glaucophylla tree. LAIe was extracted from raw waveform as an intermediate step in the CHP methodology, with two different vegetation-ground reflectance ratios. Discrete point LAIe estimates were derived from the gap probability using the following: 1) single ground returns and 2) all ground returns. LiDAR LAIe retrievals were subsequently compared to hemispherical photography estimates, yielding mean values within ±7% of the latter, depending on the method used. The CHP of a single dead Callitris glaucophylla tree, representing the distribution of vegetation material, was verified with a field profile manually reconstructed from convergent photographs taken with a fixed-focal-length camera. A binwise comparison of the two profiles showed very high correlation between the data reaching R2 of 0.86 for the CHP from combined swaths. Using a study-area-adjusted reflectance ratio improved the correlation between the profiles, but only marginally in comparison to using an arbitrary ratio of 0.5 for the laser wavelength of 1550 nm.