7 resultados para agricultural impacts

em University of Queensland eSpace - Australia


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A population of the grassland earless dragon (Tympanocryptis pinguicolla) on the Darling Downs, Queensland, Australia, had been considered extinct until its recent rediscovery. We determined factors affecting grassland earless dragon abundance and prey availability in 3 habitats. Mean dragon body condition and prey numbers were higher in sorghum than grasslands and grass verges. Poisson regression analyses indicated that the dragon numbers were 10 times higher in sorghum, and that this may result from differences in prey numbers as well as other habitat conditions. Tracking data indicated selection of open versus closed microhabitat. Sorghum planted in rows provided alternating open and closed microhabitats for optimal thermoregulation conditions. Grasslands and grass verges were more uniformly shaded. Of individuals we tracked in the sorghum stubble, 85.7% used litter as overnight refuges. Litter was abundant in sorghum and sparse in grass habitats. The practices of minimum tillage and resting stubble strips possibly mitigate agricultural impacts on dragons and provide continuous access to suitable habitat. Changes in agricultural practices that affect the habitat suitability will potentially have detrimental impacts on the population. Our data suggest that conservation efforts be focused on maintaining suitability of habitats in crop fields. We recommend monitoring dragon abundance at control and trial sites of any new agricultural practices; this will provide opportunity to modify or stop undesirable practices before adoption by farmers. Conservation agencies may use our data as a baseline for monitoring long-term viability of the population.

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A combination of physical and chemical measurements and biological indicators identified nutrient impacts throughout an Australian subtropical river estuary. This was a balance of sewage inputs in the lower river and agricultural inputs in the mid-upper river, the combined influence being greater in the wet season due to greater agricultural surface runoff. Field sampling in the region was conducted at 6 sites within the river, over 5 surveys to encapsulate both wet and dry seasonal effects. Parameters assessed were tissue nitrogen (N) contents and delta(15)N signatures of mangroves and macroalgae, phytoplankton nutrient addition bioassays, and standard physical and chemical variables. Strong spatial (within river) and temporal (seasonal) variability was observed in all parameters. Poorest water quality was detected in the middle (agricultural) region of the river in the wet season, attributable to large diffuse inputs in this region. Water quality towards the river mouth remained constant irrespective of season due to strong oceanic flushing. Mangrove and macroalgal tissue delta(15)N and %N proved a successful combination for discerning sewage and agricultural inputs. Elevated delta(15)N and %N represented sewage inputs, whereas low delta(15)N and elevated %N was indicative of agricultural inputs. Phytoplankton bioassays found the system to be primarily responsive to nutrient additions in the warmer wet season, with negligible responses observed in the cooler dry season. These results indicate that the Tweed River is sensitive to the different anthropogenic activities in its catchment and that each activity has a unique influence on receiving water quality.

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A case study approach within an action research framework incorporating qualitative and quantitative domains was adopted to explore the impact on Queensland farmers of a farm business management extension programme. Three new indices were developed to quantify changes perceived by participants. The first measure, the Bennett Change Index, provided statistically significant evidence that attitudinal and behavioural changes were more frequent in participants with less formal education, but also more frequent in participants who had high urbanisation and self-directed learning index scores. The other 2 new indices, Management Constructs Change and Management Objectives Change, provided evidence of statistically significant changes in participant beliefs about, and attitudes towards, farm business management. Although highly correlated with each other, these changes were unrelated statistically to any of 6 other commonly used biographical or psychometric indices employed; including level of formal education. It is concluded that these new measures, with context-relevant modifications, have potential as aids to programme impact evaluation in a range of agricultural and wider applications. They may provide insights into personal psychological issues that complement direct behavioural measures of change.

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Allocations of research funds across programs are often made for efficiency reasons. Social science research is shown to have small, lagged but significant effects on U.S. agricultural efficiency when public agricultural R&D and extension are simultaneously taken into account. Farm management and marketing research variables are used to explain variations in estimates of allocative and technical efficiency using a Bayesian approach that incorporates stylized facts concerning lagged research impacts in a way that is less restrictive than popular polynomial distributed lags. Results are reported in terms of means and standard deviations of estimated probability distributions of parameters and long-run total multipliers. Extension is estimated to have a greater impact on both allocative and technical efficiency than either R&D or social science research.

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An expanding human population and associated demands for goods and services continues to exert an increasing pressure on ecological systems. Although the rate of expansion of agricultural lands has slowed since 1960, rapid deforestation still occurs in many tropical countries, including Colombia. However, the location and extent of deforestation and associated ecological impacts within tropical countries is often not well known. The primary aim of this study was to obtain an understanding of the spatial patterns of forest conversion for agricultural land uses in Colombia. We modeled native forest conversion in Colombia at regional and national-levels using logistic regression and classification trees. We investigated the impact of ignoring the regional variability of model parameters, and identified biophysical and socioeconomic factors that best explain the current spatial pattern and inter-regional variation in forest cover. We validated our predictions for the Amazon region using MODIS satellite imagery. The regional-level classification tree that accounted for regional heterogeneity had the greatest discrimination ability. Factors related to accessibility (distance to roads and towns) were related to the presence of forest cover, although this relationship varied regionally. In order to identify areas with a high risk of deforestation, we used predictions from the best model, refined by areas with rural population growth rates of > 2%. We ranked forest ecosystem types in terms of levels of threat of conversion. Our results provide useful inputs to planning for biodiversity conservation in Colombia, by identifying areas and ecosystem types that are vulnerable to deforestation. Several of the predicted deforestation hotspots coincide with areas that are outstanding in terms of biodiversity value.

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This paper examines the challenges of water supply in agriculture, with particular emphasis on requirements of field crops, including maize. It places the issue of water supply to agriculture in the context of increasing demands for water from alternatives users, declining quality water, pressure of increasing population, all of which are placing stresses on water availability at local, regional and national levels. The paper also examines existing freshwater resources and the potential impact of climate change on water supply and distribution and consequential impact on water stress incidence in various parts of the globe. It examines competition for water in both industrialized and developing countries, with particular emphasis on the impacts on agriculture and food supplies. The challenge of water use efficiency (WUE) in agriculture is explored with discussion of agronomic, economic and physiological WUE concepts, with specific reference to maize.