132 research outputs found

    Diagnosa Hama Dan Penyakit Pada Tanaman Cabai Menggunakan Metode Variable Centered Intelligent Rule System (Vcirs)

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    This research led to an expert system application that was built by applying the method variable centered intelligent rule system and the certainty factor. Variable Centered Intelligent Rule System (VCIRS) is an intelligent rule-based system that focuses on the variables. VCIRS procedures are able to take over the construction of knowledge, update knowledge as well as advice or inference process. Procedure own certainty factor on the symptoms of pests or diseases taking into account the weighting process used to provide from the weighting process result in the form of pests or diseases to the value of the trust of the system. The location of this research is located in Rote Ndao Regency. Data used in this application testing of 28 case data sourced from an expert or agricultural expert. Accuracy in this study was 100 %. The results showed that the method variable centered intelligent rule system and certainty factor can be applied in the application of expert system for the diagnosis of plant pests and diseases chili

    Process based model sheds light on climate sensitivity of Mediterranean tree-ring width

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    We use the process-based VS (Vaganov-Shashkin) model to investigate whether a regional <i>Pinus halepensis</i> tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959–2004) from a climate station to ring-width variations. We check performance of the model on independent data by a validation exercise in which the model's parameters are tuned using data for 1982–2004 and the model is applied to generate tree-ring indices for 1959–1981. The validation exercise yields a highly significant positive correlation between the residual chronology and estimated growth curve (<i>r</i>=0.76 <i>p</i><0.0001, <i>n</i>=23). The model shows that the average duration of the growing season is 191 days, with considerable variation from year to year. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. Model results depend on chosen values of parameters, in particular a parameter specifying a balance ratio between soil moisture and precipitation. Future work in the Mediterranean region should include multi-year natural experiments to verify patterns of cambial-growth variation suggested by the VS model

    Converging Currents in Climate-Relevant Conservation: Water, Infrastructure, and Institutions

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    Ecologists and economists have long talked past each other, but climate change presents similar threats to both groups. Water may serve as the best means of finding a common cause and building a new vision of ecological and economic sustainability, especially in the developing world

    Scientific merits and analytical challenges of tree-ring densitometry

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    R.W. was supported by NERC grant NE/K003097/1.X-ray microdensitometry on annually-resolved tree-ring samples has gained an exceptional position in last-millennium paleoclimatology through the maximum latewood density parameter (MXD), but also increasingly through other density parameters. For fifty years, X-ray based measurement techniques have been the de facto standard. However, studies report offsets in the mean levels for MXD measurements derived from different laboratories, indicating challenges of accuracy and precision. Moreover, reflected visible light-based techniques are becoming increasingly popular and wood anatomical techniques are emerging as a potentially powerful pathway to extract density information at the highest resolution. Here we review the current understanding and merits of wood density for tree-ring research, associated microdensitometric techniques, and analytical measurement challenges. The review is further complemented with a careful comparison of new measurements derived at 17 laboratories, using several different techniques. The new experiment allowed us to corroborate and refresh ?long-standing wisdom?, but also provide new insights. Key outcomes include; i) a demonstration of the need for mass/volume based re-calibration to accurately estimate average ring density; ii) a substantiation of systematic differences in MXD measurements that cautions for great care when combining density datasets for climate reconstructions; and iii) insights into the relevance of analytical measurement resolution in signals derived from tree-ring density data. Finally, we provide recommendations expected to facilitate future inter-comparability and interpretations for global change research.Publisher PDFPeer reviewe

    Runoff variations in Lake Balkhash Basin, Central Asia, 1779-2015, inferred from tree rings

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    Long highly-resolved proxies for runoff are in high demand for hydrological forecasts and water management in arid Central Asia. An accurate (R2 = 0.53) reconstruction of October-September discharge of the Ili River in Kazakhstan, 1779–2015, is developed from moisture-sensitive tree rings of spruce sampled in the Tian Shan Mountains. The fivefold extension of the gauged discharge record represents the variability of runoff in the Lake Balkhash Basin for the last 235 years. The reconstruction shows a 40 year long interval of low discharge preceded a recent high peak in the first decade of the 2000s followed by a decline to more recent levels of discharge not seen since the start of the gauged record. Most reconstructed flow extremes (± 2σ) occur outside the instrumental record (1936–2015) and predate the start of large dam construction (1969). Decadal variability of the Ili discharge corresponds well with hydrological records of other Eurasian internal drainages modeled with tree rings. Spectral analysis identifies variance peaks (highest near 42 year) consistent with main hemispheric oscillations of the Eurasian climatic system. Seasonal comparison of the Ili discharge with sea-level-pressure and geopotential height data suggests periods of high flow likely result from the increased contribution of snow to runoff associated with the interaction of Arctic air circulation with the Siberian High-Pressure System and North Atlantic Oscillation
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