6 resultados para Relativistic mean-field theories

em eResearch Archive - Queensland Department of Agriculture


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Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

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Farmlets, each of 20 cows, were established to field test five milk production systems and provide a learning platform for farmers and researchers in a subtropical environment. The systems were developed through desktop modelling and industry consultation in response to the need for substantial increases in farm milk production following deregulation of the industry. Four of the systems were based on grazing and the continued use of existing farmland resource bases, whereas the fifth comprised a feedlot and associated forage base developed as a greenfield site. The field evaluation was conducted over 4 years under more adverse environmental conditions than anticipated with below average rainfall and restrictions on irrigation. For the grazed systems, mean annual milk yield per cow ranged from 6330 kg/year (1.9 cows/ha) for a herd based on rain-grown tropical pastures to 7617 kg/year (3.0 cows/ha) where animals were based on temperate and tropical irrigated forages. For the feedlot herd, production of 9460 kg/cow.year (4.3 cows/ha of forage base) was achieved. For all herds, the level of production achieved required annual inputs of concentrates of similar to 3 t DM/animal and purchased conserved fodder from 0.3 to 1.5 t DM/animal. This level of supplementary feeding made a major contribution to total farm nutrient inputs, contributing 50% or more of the nitrogen, phosphorus and potassium entering the farming system, and presents challenges to the management of manure and urine that results from the higher stocking rates enabled. Mean annual milk production for the five systems ranged from 88 to 105% of that predicted by the desktop modelling. This level of agreement for the grazed systems was achieved with minimal overall change in predicted feed inputs; however, the feedlot system required a substantial increase in inputs over those predicted. Reproductive performance for all systems was poorer than anticipated, particularly over the summer mating period. We conclude that the desktop model, developed as a rapid response to assist farmers modify their current farming systems, provided a reasonable prediction of inputs required and milk production. Further model development would need to consider more closely climate variability, the limitations summer temperatures place on reproductive success and the feed requirements of feedlot herds.

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There is a large gap between the refined approaches to characterise genotypes and the common use of location and season as a coarse surrogate for environmental characterisation of breeding trials. As a framework for breeding, the aim of this paper is quantifying the spatial and temporal patterns of thermal and water stress for field pea in Australia. We compiled a dataset for yield of the cv. Kaspa measured in 185 environments, and investigated the associations between yield and seasonal patterns of actual temperature and modelled water stress. Correlations between yield and temperature indicated two distinct stages. In the first stage, during crop establishment and canopy expansion before flowering, yield was positively associated with minimum temperature. Mean minimum temperature below similar to 7 degrees C suggests that crops were under suboptimal temperature for both canopy expansion and radiation-use efficiency during a significant part of this early growth period. In the second stage, during critical reproductive phases, grain yield was negatively associated with maximum temperature over 25 degrees C. Correlations between yield and modelled water supply/demand ratio showed a consistent pattern with three phases: no correlation at early stages of the growth cycle, a progressive increase in the association that peaked as the crop approached the flowering window, and a progressive decline at later reproductive stages. Using long-term weather records (1957-2010) and modelled water stress for 104 locations, we identified three major patterns of water deficit nation wide. Environment type 1 (ET1) represents the most favourable condition, with no stress during most of the pre-flowering phase and gradual development of mild stress after flowering. Type 2 is characterised by increasing water deficit between 400 degree-days before flowering and 200 degree-days after flowering and rainfall that relieves stress late in the season. Type 3 represents the more stressful condition with increasing water deficit between 400 degree-days before flowering and maturity. Across Australia, the frequency of occurrence was 24% for ET1, 32% for ET2 and 43% for ET3, highlighting the dominance of the most stressful condition. Actual yield averaged 2.2 t/ha for ET1, 1.9 t/ha for ET2 and 1.4 t/ha for ET3, and the frequency of each pattern varied substantially among locations. Shifting from a nominal (i.e. location and season) to a quantitative (i.e. stress type) characterisation of environments could help improving breeding efficiency of field pea in Australia.

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Spinosad, diatomaceous earth, and cyfluthrin were assessed on two broiler farms at Gleneagle and Gatton in southeastern Queensland, Australia in 2004-2005 and 2007-2009, respectively to determine their effectiveness in controlling lesser mealworm, Alphitobius diaperinus (Panzer) (Coleoptera: Tenebrionidae). Insecticide treatments were applied mostly to earth or 'hard' cement floors of broiler houses before the placement of new bedding. Efficacy of each agent was assessed by regular sampling of litter and counting of immature stages and adult beetles, and comparing insect counts in treatments to counts in untreated houses. Generally, the lowest numbers of lesser mealworm were recorded in the house with hard floors, these numbers equalling the most effective spinosad applications. The most effective treatment was a strategic application of spinosad under feed supply lines on a hard floor. In compacted earth floor houses, mean numbers of lesser mealworms for two under-feed-line spinosad treatments (i.e., 2-m-wide application at 0.18 g of active insecticide (g [AI]) in 100-ml water/m(2), and 1-m-wide application at 0.11 g ([AI] in 33-ml water/m(2)), and an entire floor spinosad treatment (0.07 g [AI] in 86-ml water/m2) were significantly lower (i.e., better control) than those numbers for cyfluthrin, and no treatment (controls). The 1-m-wide under-feed-line treatment was the most cost-effective dose, providing similar control to the other two most effective spinosad treatments, but using less than half the active component per broiler house. No efficacy was demonstrated when spinosad was applied to the surface of bedding in relatively large volumes of water. All applications of diatomaceous earth, applied with and without spinosad, and cyfluthrin at the label rate of 0.02 g (AI)/100-ml water/m(2) showed no effect, with insect counts not significantly different to untreated controls. Overall, the results of this field assessment indicate that cyfluthrin (the Australian industry standard) and diatomaceous earth were ineffective on these two farms and that spinosad can be a viable alternative for broiler house use.

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Flight directionality of the rust-red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), was investigated under glasshouse and field conditions using sticky traps placed around dense experimental infestations of T. castaneum derived from field-collected samples. Although beetles of this species are known to fly quite readily, information on flight of beetles away from grain resources is limited. Under still glasshouse conditions, T. castaneum does not demonstrate strong horizontal or vertical trajectories in their initial flight behaviour. Flight was significantly directional in half of the replicates, but trapped beetles were only weakly concentrated around the mean direction of flight. In the field, by contrast, emigration of T. castaneum was strongly directional soon after flight initiation. The mean vector lengths were generally >0.5 which indicates that trapped beetles were strongly concentrated around the calculated mean flight direction. A circular-circular regression of mean flight vs. mean downwind direction suggested that flight direction was generally correlated with downwind direction. The mean height at which T. castaneum individuals initially flew was 115.4 ± 7.0 cm, with 58.3% of beetles caught no more than 1 m above the ground. The height at which beetles were trapped did not correlate with wind speed at the time of sampling, but the data do indicate that wind speed significantly affected T. castaneum flight initiation, because no beetles (or very few; no more than three) were trapped in the field when the mean wind speed was above 3 m s−1. This study thus demonstrates that wind speed and direction are both important aspects of flight behaviour of T. castaneum, and therefore of the spatio-temporal dynamics of this species.

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Few data exist on direct greenhouse gas emissions from pen manure at beef feedlots. However, emission inventories attempt to account for these emissions. This study used a large chamber to isolate N2O and CH4 emissions from pen manure at two Australian commercial beef feedlots (stocking densities, 13-27 m(2) head) and related these emissions to a range of potential emission control factors, including masses and concentrations of volatile solids, NO3-, total N, NH4+, and organic C (OC), and additional factors such as total manure mass, cattle numbers, manure pack depth and density, temperature, and moisture content. Mean measured pen N2O emissions were 0.428 kg ha(-1) d(-1) (95% confidence interval [CI], 0.252-0.691) and 0.00405 kg ha(-1) d(-1) (95% CI, 0.00114-0.0110) for the northern and southern feedlots, respectively. Mean measured CH4 emission was 0.236 kg ha(-1) d(-1) (95% CI, 0.163-0.332) for the northern feedlot and 3.93 kg ha(-1) d(-1) (95% CI, 2.58-5.81) for the southern feedlot. Nitrous oxide emission increased with density, pH, temperature, and manure mass, whereas negative relationships were evident with moisture and OC. Strong relationships were not evident between N2O emission and masses or concentrations of NO3- or total N in the manure. This is significant because many standard inventory calculation protocols predict N2O emissions using the mass of N excreted by the animal.