5,832 research outputs found

    Integrating remote sensing datasets into ecological modelling: a Bayesian approach

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    Process-based models have been used to simulate 3-dimensional complexities of forest ecosystems and their temporal changes, but their extensive data requirement and complex parameterisation have often limited their use for practical management applications. Increasingly, information retrieved using remote sensing techniques can help in model parameterisation and data collection by providing spatially and temporally resolved forest information. In this paper, we illustrate the potential of Bayesian calibration for integrating such data sources to simulate forest production. As an example, we use the 3-PG model combined with hyperspectral, LiDAR, SAR and field-based data to simulate the growth of UK Corsican pine stands. Hyperspectral, LiDAR and SAR data are used to estimate LAI dynamics, tree height and above ground biomass, respectively, while the Bayesian calibration provides estimates of uncertainties to model parameters and outputs. The Bayesian calibration contrasts with goodness-of-fit approaches, which do not provide uncertainties to parameters and model outputs. Parameters and the data used in the calibration process are presented in the form of probability distributions, reflecting our degree of certainty about them. After the calibration, the distributions are updated. To approximate posterior distributions (of outputs and parameters), a Markov Chain Monte Carlo sampling approach is used (25 000 steps). A sensitivity analysis is also conducted between parameters and outputs. Overall, the results illustrate the potential of a Bayesian framework for truly integrative work, both in the consideration of field-based and remotely sensed datasets available and in estimating parameter and model output uncertainties

    Effect of Pressure on the Activity Coefficients of Au and Other Siderophile Elements in Liquid Fe-Si Alloys

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    Light elements can alloy into the iron cores of terrestrial planetary bodies. It is estimated that the Earths core contains ~10% of a light element, most likely a combination of S, C, Si, and O with Si probably being the most abundant. Si dissolved into Fe metal liquids can have a significant influence on the activity coefficients of siderophile elements, and thus the partitioning behavior of those elements between the core and mantle. Many of these elements have been investigated extensively at ambient pressure, and studies up to 1 GPa are becoming more common, but few have been studied at pressures above this. The formation of the Earths core has been estimated to have formed at pressures between 40-60 GPa, so investigating the effect pressure has on Sis influence on siderophile element partitioning is important for modeling core formation in the Earth and smaller planets. Pressure is well known to influence volumetric properties of metallic and silicate liquids, and oxygen fugacity (e.g., [10,11]), but less is known about its effect on activity coefficients (e.g., [12]). Some activity coefficients depend strongly upon the Si content of Fe liquids, and the concentration of siderophile elements such as P, Sb, and As in the terrestrial mantle is easily influenced by dissolved Si in the core. Thus, isolating the effect of pressure on activity coefficients in general is critical in quantitative analysis of core formation models. In this work, we investigate the effect variable Si content has on the partitioning of Au between Fe metal and silicate melt at 10 GPa and 2373 K, with the intention of comparing the behavior to that already investigated at lower pressures. In addition, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb were also measured and could thus be included in the assessment of potential pressure effects

    Introducing new bean varieties with small seed packs: experience from Malawi

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    Trends in total column ozone measurements

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    It is important to ensure the best available data are used in any determination of possible trends in total ozone in order to have the most accurate estimates of any trends and the associated uncertainties. Accordingly, the existing total ozone records were examined in considerable detail. Once the best data set has been produced, the statistical analysis must examine the data for any effects that might indicate changes in the behavior of global total ozone. The changes at any individual measuring station could be local in nature, and herein, particular attention was paid to the seasonal and latitudinal variations of total ozone, because two dimensional photochemical models indicate that any changes in total ozone would be most pronounced at high latitudes during the winter months. The conclusions derived from this detailed examination of available total ozone can be split into two categories, one concerning the quality and the other the statistical analysis of the total ozone record

    Porcine reproductive and respiratory syndrome: characteristic features of the infected fetus

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    Pregnant gilts were infected at 90 days of gestation with porcine reproductive and respiratory virus (PRRSV) isolate SD-23983. Fetuses recovered between 109 and 112 days of gestation were analyzed for the presence of PRRSV. The results showed that not all fetuses were infected, and that infected fetuses tended to be clustered within the uterine horns, suggesting that virus is spread from fetus to fetus. Even though affected litters exhibited different degrees of gross pathology, the presence of an anatomical abnormality was not an identifier of an infected fetus. Analysis of virus replication in individual tissues identified the thymus as the principal site of PRRSV replication. The results show that PRRSV infection in the developing fetus follows a unique course and that PRRSVinduced alterations may be the result of the effect of PRRSV on maternal tissues. These factors need to be taken into consideration when diagnosing PRRSV infection as the cause for aborted and stillborn fetuses.; Swine Day, 2005, Kansas State University, Manhattan, KS, 200
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