4 resultados para [JEL:E4] Macroeconomics and Monetary Economics - Money and Interest Rates

em eResearch Archive - Queensland Department of Agriculture


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By quantifying the effects of climatic variability in the sheep grazing lands of north western and western Queensland, the key biological rates of mortality and reproduction can be predicted for sheep. These rates are essential components of a decision support package which can prove a useful management tool for producers, especially if they can easily obtain the necessary predictors. When the sub-models of the GRAZPLAN ruminant biology process model were re-parameterised from Queensland data along with an empirical equation predicting the probability of ewes mating added, the process model predicted the probability of pregnancy well (86% variation explained). Predicting mortality from GRAZPLAN was less successful but an empirical equation based on relative condition of the animal (a measure based on liveweight), pregnancy status and age explained 78% of the variation in mortalities. A crucial predictor in these models was liveweight which is not often recorded on producer properties. Empirical models based on climatic and pasture conditions estimated from the pasture production model GRASP, predicted marking and mortality rates for Mitchell grass (Astrebla sp.) pastures (81% and 63% of the variation explained). These prediction equations were tested against independent data from producer properties and the model successfully validated for Mitchell grass communities.

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Tick infestation occurs over 1.3 x 106 km2 in northern Australia. It has been difficult to estimate the economic effects of ticks due to a lack of information on their effects on growth and reproduction (Anon 1975). 12th Biennial Conference. February 1978. Melbourne, Victoria

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In current simulation packages for the management of extensive beef-cattle enterprises, the relationships for the key biological rates (namely conception and mortality) are quite rudimentary. To better estimate these relationships, cohort-level data covering 17 100 cow-years from six sites across northern Australia were collated and analysed. Further validation data, from 7200 cow-years, were then used to test these relationships. Analytical problems included incomplete and non-standardised data, considerable levels of correlation among the 'independent' variables, and the close similarity of alternate possible models. In addition to formal statistical analyses of these data, the theoretical equations for predicting mortality and conception rates in the current simulation models were reviewed, and then reparameterised and recalibrated where appropriate. The final models explained up to 80% of the variation in the data. These are now proposed as more accurate and useful models to be used in the prediction of biological rates in simulation studies for northern Australia. © The State of Queensland (through the Department of Agriculture, Fisheries and Forestry) 2012. © CSIRO.

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Current understanding is that high planting density has the potential to suppress weeds and crop-weed interactions can be exploited by adjusting fertilizer rates. We hypothesized that (a) high planting density can be used to suppress Rottboellia cochinchinensis growth and (b) rice competitiveness against this weed can be enhanced by increasing nitrogen (N) rates. We tested these hypotheses by growing R. cochinchinensis alone and in competition with four rice planting densities (0, 100, 200, and 400 plants m-2) at four N rates (0, 50, 100, and 150 kg ha-1). At 56 days after sowing (DAS), R. cochinchinensis plant height decreased by 27-50 %, tiller number by 55-76 %, leaf number by 68-84 %, leaf area by 70-83 %, leaf biomass by 26-90 %, and inflorescence biomass by 60-84 %, with rice densities ranging from 100 to 400 plants m-2. All these parameters increased with an increase in N rate. Without the addition of N, R. cochinchinensis plants were 174 % taller than rice; whereas, with added N, they were 233 % taller. Added N favored more weed biomass production relative to rice. R. cochinchinensis grew taller than rice (at all N rates) to avoid shade, which suggests that it is a "shade-avoiding" plant. R. cochinchinensis showed this ability to reduce the effect of rice interference through increased leaf weight ratio, specific stem length, and decreased root-shoot weight ratio. This weed is more responsive to N fertilizer than rice. Therefore, farmers should give special consideration to the application timing of N fertilizer when more N-responsive weeds are present in their field. Results suggest that the growth and seed production of R. cochinchinensis can be decreased considerably by increasing rice density to 400 plants m-2. There is a need to integrate different weed control measures to achieve complete control of this noxious weed.