921 resultados para 140200 APPLIED ECONOMICS


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Pasture rest is a possible strategy for improving land condition in the extensive grazing lands of northern Australia. If pastures currently in poor condition could be improved, then overall animal productivity and the sustainability of grazing could be increased. The scientific literature is examined to assess the strength of the experimental information to support and guide the use of pasture rest, and simulation modelling is undertaken to extend this information to a broader range of resting practices, growing conditions and initial pasture condition. From this, guidelines are developed that can be applied in the management of northern Australia’s grazing lands and also serve as hypotheses for further field experiments. The literature on pasture rest is diverse but there is a paucity of data from much of northern Australia as most experiments have been conducted in southern and central parts of Queensland. Despite this, the limited experimental information and the results from modelling were used to formulate the following guidelines. Rest during the growing season gives the most rapid improvement in the proportion of perennial grasses in pastures; rest during the dormant winter period is ineffective in increasing perennial grasses in a pasture but may have other benefits. Appropriate stocking rates are essential to gain the greatest benefit from rest: if stocking rates are too high, then pasture rest will not lead to improvement; if stocking rates are low, pastures will tend to improve without rest. The lower the initial percentage of perennial grasses, the more frequent the rests should be to give a major improvement within a reasonable management timeframe. Conditions during the growing season also have an impact on responses with the greatest improvement likely to be in years of good growing conditions. The duration and frequency of rest periods can be combined into a single value expressed as the proportion of time during which resting occurs; when this is done the modelling suggests the greater the proportion of time that a pasture is rested, the greater is the improvement but this needs to be tested experimentally. These guidelines should assist land managers to use pasture resting but the challenge remains to integrate pasture rest with other pasture and animal management practices at the whole-property scale.

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Ecosystem based management requires the integration of various types of assessment indicators. Understanding stakeholders' information preferences is important, in selecting those indicators that best support management and policy. Both the preferences of decision-makers and the general public may matter, in democratic participatory management institutions. This paper presents a multi-criteria analysis aimed at quantifying the relative importance to these groups of economic, ecological and socio-economic indicators usually considered when managing ecosystem services in a coastal development context. The Analytic Hierarchy Process (AHP) is applied within two nationwide surveys in Australia, and preferences of both the general public and decision-makers for these indicators are elicited and compared. Results show that, on average across both groups, the priority in assessing a generic coastal development project is for the ecological assessment of its impacts on marine biodiversity. Ecological assessment indicators are globally preferred to both economic and socio-economic indicators regardless of the nature of the impacts studied. These results are observed for a significantly larger proportion of decision-maker than general public respondents, questioning the extent to which the general public's preferences are well reflected in decision-making processes.

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The driving force behind this study has been the need to develop and apply methods for investigating the hydrogeochemical processes of significance to water management and artificial groundwater recharge. Isotope partitioning of elements in the course of physicochemical processes produces isotopic variations to their natural reservoirs. Tracer property of the stable isotope abundances of oxygen, hydrogen and carbon has been applied to investigate hydrogeological processes in Finland. The work described here has initiated the use of stable isotope methods to achieve a better understanding of these processes in the shallow glacigenic formations of Finland. In addition, the regional precipitation and groundwater records will supplement the data of global precipitation, but as importantly, provide primary background data for hydrological studies. The isotopic composition of oxygen and hydrogen in Finnish groundwaters and atmospheric precipitation was determined in water samples collected during 1995 2005. Prior to this study, no detailed records existed on the spatial or annual variability of the isotopic composition of precipitation or groundwaters in Finland. Groundwaters and precipitation in Finland display a distinct spatial distribution of the isotopic ratios of oxygen and hydrogen. The depletion of the heavier isotopes as a function of increasing latitude is closely related to the local mean surface temperature. No significant differences were observed between the mean annual isotope ratios of oxygen and hydrogen in precipitation and those in local groundwaters. These results suggest that the link between the spatial variability in the isotopic composition of precipitation and local temperature is preserved in groundwaters. Artificial groundwater recharge to glaciogenic sedimentary formations offers many possibilities to apply the isotopic ratios of oxygen, hydrogen and carbon as natural isotopic tracers. In this study the systematics of dissolved carbon have been investigated in two geochemically different glacigenic groundwater formations: a typical esker aquifer at Tuusula, in southern Finland and a carbonate-bearing aquifer with a complex internal structure at Virttaankangas, in southwest Finland. Reducing the concentration of dissolved organic carbon (DOC) in water is a primary challenge in the process of artificial groundwater recharge. The carbon isotope method was used to as a tool to trace the role of redox processes in the decomposition of DOC. At the Tuusula site, artificial recharge leads to a significant decrease in the organic matter content of the infiltrated water. In total, 81% of the initial DOC present in the infiltrated water was removed in three successive stages of subsurface processes. Three distinct processes in the reduction of the DOC content were traced: The decomposition of dissolved organic carbon in the first stage of subsurface flow appeared to be the most significant part in DOC removal, whereas further decrease in DOC has been attributed to adsorption and finally to dilution with local groundwater. Here, isotope methods were used for the first time to quantify the processes of DOC removal in an artificial groundwater recharge. Groundwaters in the Virttaankangas aquifer are characterized by high pH values exceeding 9, which are exceptional for shallow aquifers on glaciated crystalline bedrock. The Virttaankangas sediments were discovered to contain trace amounts of fine grained, dispersed calcite, which has a high tendency to increase the pH of local groundwaters. Understanding the origin of the unusual geochemistry of the Virttaankangas groundwaters is an important issue for constraining the operation of the future artificial groundwater plant. The isotope ratios of oxygen and carbon in sedimentary carbonate minerals have been successfully applied to constrain the origin of the dispersed calcite in the Virttaankangas sediments. The isotopic and chemical characteristics of the groundwater in the distinct units of aquifer were observed to vary depending on the aquifer mineralogy, groundwater residence time and the openness of the system to soil CO2. The high pH values of > 9 have been related to dissolution of calcite into groundwater under closed or nearly closed system conditions relative to soil CO2, at a low partial pressure of CO2.

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The financial health of beef cattle enterprises in northern Australia has declined markedly over the last decade due to an escalation in production and marketing costs and a real decline in beef prices. Historically, gains in animal productivity have offset the effect of declining terms of trade on farm incomes. This raises the question of whether future productivity improvements can remain a key path for lifting enterprise profitability sufficient to ensure that the industry remains economically viable over the longer term. The key objective of this study was to assess the production and financial implications for north Australian beef enterprises of a range of technology interventions (development scenarios), including genetic gain in cattle, nutrient supplementation, and alteration of the feed base through introduced pastures and forage crops, across a variety of natural environments. To achieve this objective a beef systems model was developed that is capable of simulating livestock production at the enterprise level, including reproduction, growth and mortality, based on energy and protein supply from natural C4 pastures that are subject to high inter-annual climate variability. Comparisons between simulation outputs and enterprise performance data in three case study regions suggested that the simulation model (the Northern Australia Beef Systems Analyser) can adequately represent the performance beef cattle enterprises in northern Australia. Testing of a range of development scenarios suggested that the application of individual technologies can substantially lift productivity and profitability, especially where the entire feedbase was altered through legume augmentation. The simultaneous implementation of multiple technologies that provide benefits to different aspects of animal productivity resulted in the greatest increases in cattle productivity and enterprise profitability, with projected weaning rates increasing by 25%, liveweight gain by 40% and net profit by 150% above current baseline levels, although gains of this magnitude might not necessarily be realised in practice. While there were slight increases in total methane output from these development scenarios, the methane emissions per kg of beef produced were reduced by 20% in scenarios with higher productivity gain. Combinations of technologies or innovative practices applied in a systematic and integrated fashion thus offer scope for providing the productivity and profitability gains necessary to maintain viable beef enterprises in northern Australia into the future.

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AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.