16 resultados para COX

em eResearch Archive - Queensland Department of Agriculture


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Grass and broad-leaved weeds can reduce both yields and product marketability of desmanthus (Desmanthus virgatus) seed crops, even when cultural control strategies are used. Selective herbicides might economically control these weeds, but, prior to this study, the few herbicides tolerated by desmanthus did not control key weed contaminants of desmanthus seed crops. In this study, the tolerance of desmanthus cv. Marc to 55 herbicides used for selective weed control in other leguminous crops was assessed in 1 pot trial and 3 Queensland field trials. One field trial assessed the tolerance of desmanthus seedlings to combinations of the most promising pre-emergent and post emergent herbicides. The pre-emergent herbicides, imazaquin, imazethapyr, pendimethalin, oryzalin and trifluralin, gave useful weed control with very little crop damage. The post-emergent herbicides, haloxyfop, clethodim, propyzamide, carbetamide and dalapon, were safe for controlling grass weeds in desmanthus. Selective post-emergence control of broad-leaved weeds was achieved using bentazone, bromoxynil and imazethapyr. One trial investigated salvaging second-year desmanthus crops from mature perennial weeds, and atrazine, terbacil and hexazinone showed some potential in this role. Overall, our results show that desmanthus tolerates herbicides which collectively control a wide range of weeds encountered in Queensland. These, in combination with cultural weed control strategies, should control most weeds in desmanthus seed crops.

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Runoff and sediment loss from forest roads were monitored for a two-year period in a Pinus plantation in southeast Queensland. Two classes of road were investigated: a gravelled road, which is used as a primary daily haulage route for the logging area, and an ungravelled road, which provides the main access route for individual logging compartments and is intensively used as a haulage route only during the harvest of these areas (approximately every 30 years). Both roads were subjected to routine traffic loads and maintenance during the study. Surface runoff in response to natural rainfall was measured and samples taken for the determination of sediment and nutrient (total nitrogen, total phosphorus, dissolved organic carbon and total iron) loads from each road. Results revealed that the mean runoff coefficient (runoff depth/rainfall depth) was consistently higher from the gravelled road plot with 0.57, as compared to the ungravelled road with 0.38. Total sediment loss over the two-year period was greatest from the gravelled road plot at 5.7 t km−1 compared to the ungravelled road plot with 3.9 t km−1. Suspended solids contributed 86% of the total sediment loss from the gravelled road, and 72% from the ungravelled road over the two years. Nitrogen loads from the two roads were both relatively constant throughout the study, and averaged 5.2 and 2.9 kg km−1 from the gravelled and ungravelled road, respectively. Mean annual phosphorus loads were 0.6 kg km−1 from the gravelled road and 0.2 kg km−1 from the ungravelled road. Organic carbon and total iron loads increased in the second year of the study, which was a much wetter year, and are thought to reflect the breakdown of organic matter in roadside drains and increased sediment generation, respectively. When road and drain maintenance (grading) was performed runoff and sediment loss were increased from both road types. Additionally, the breakdown of the gravel road base due to high traffic intensity during wet conditions resulted in the formation of deep (10 cm) ruts which increased erosion. The Water Erosion Prediction Project (WEPP):Road model was used to compare predicted to observed runoff and sediment loss from the two road classes investigated. For individual rainfall events, WEPP:Road predicted output showed strong agreement with observed values of runoff and sediment loss. WEPP:Road predictions for annual sediment loss from the entire forestry road network in the study area also showed reasonable agreement with the extrapolated observed values.

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Rainfall simulation experiments were carried out to measure runoff and soil water fluxes of suspended solids, total nitrogen, total phosphorus, dissolved organic carbon and total iron from sites in Pinus plantations on the coastal lowlands of south-eastern Queensland subjected to various operations (treatments). The operations investigated were cultivated and nil-cultivated site preparation, fertilised site preparation, clearfall harvesting and prescribed burning; these treatments were compared with an 8-y-old established plantation. Flow-weighted mean concentrations of total nitrogen and total phosphorus in surface runoff from the cultivated and nil-cultivated site-preparation, clearfall harvest, prescribed burning and 8-y-old established plantation treatments were very similar. However, both the soil water and the runoff from the fertilised site preparation treatment contained more nitrogen (N) and phosphorus (P) than the other treatments - with 3.10 mg N L-1 and 4.32 mg P L-1 (4 and 20 times more) in the runoff. Dissolved organic carbon concentrations in runoff from the nil-cultivated site-preparation and prescribed burn treatments were elevated. Iron concentrations were highest in runoff from the nil-cultivated site-preparation and 8-y-old established plantation treatments. Concentrations of suspended solids in runoff were higher from cultivated site preparation and prescribed burn treatments, and reflect the great disturbance of surface soil at these sites. The concentrations of all analytes were highest in initial runoff from plots, and generally decreased with time. Total nitrogen (mean 7.28, range 0.11-13.27 mg L-1) and total phosphorus (mean 11.60, range 0.06-83.99 mg L-1) concentrations in soil water were between 2 and 10 times greater than in surface runoff, which highlights the potential for nutrient fluxes in interflow (i.e. in the soil above the water table) through the general plantation area. Implications in regard to forest management are discussed, along with results of larger catchment-scale studies.

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Lipopolysaccharide (LPS) is a critical virulence determinant in Pasteurella multocida and a major antigen responsible for host protective immunity. In other mucosal pathogens, variation in LPS or lipooligosaccharide structure typically occurs in the outer core oligosaccharide regions due to phase variation. P. multocida elaborates a conserved oligosaccharide extension attached to two different, simultaneously expressed inner core structures, one containing a single phosphorylated 3-deoxy-D-manno-octulosonic acid (Kdo) residue and the other containing two Kdo residues. We demonstrate that two heptosyltransferases, HptA and HptB, add the first heptose molecule to the Kdo1 residue and that each exclusively recognizes different acceptor molecules. HptA is specific for the glycoform containing a single, phosphorylated Kdo residue (glycoform A), while HptB is specific for the glycoform containing two Kdo residues (glycoform B). In addition, KdkA was identified as a Kdo kinase, required for phosphorylation of the first Kdo molecule. Importantly, virulence data obtained from infected chickens showed that while wild-type P. multocida expresses both LPS glycoforms in vivo, bacterial mutants that produced only glycoform B were fully virulent, demonstrating for the first time that expression of a single LPS form is sufficient for P. multocida survival in vivo. We conclude that the ability of P. multocida to elaborate alternative inner core LPS structures is due to the simultaneous expression of two different heptosyltransferases that add the first heptose residue to the nascent LPS molecule and to the expression of both a bifunctional Kdo transferase and a Kdo kinase, which results in the initial assembly of two inner core structures.

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Two examples of GIS-based multiple-criteria evaluations of plantation forests are presented. These desktop assessments use available topographical, geological and pedological information to establish the risk of occurrence of certain environmentally detrimental processes. The first case study is concerned with the risk that chemical additives (i.e. simazine) applied within the forestry landscape may reach the drainage system. The second case study assesses the vulnerability of forested areas to landslides. The subject of the first multiple-criteria evaluation (MCE) was a 4 km2 logging area, which had been recently site-prepared for a Pinus plantation. The criteria considered relevant to the assessment were proximity to creeks, slope, soil depth to the restrictive layer (i.e. potential depth to a perched water table) and soil erodability (based on clay content). The output of the MCE was in accordance with field observations, showing that this approach has the potential to provide management support by highlighting areas vulnerable to waterlogging, which in turn can trigger overland flow and export of pollutants to the local stream network. The subject of the second evaluation was an Araucaria plantation which is prone to landslips during heavy rain. The parameters included in the assessment were drainage system, the slope of the terrain and geological features such as rocks and structures. A good correlation between the MCE results and field observations was found, suggesting that this GIS approach is useful for the assessment of natural hazards. Multiple-criteria evaluations are highly flexible as they can be designed in either vector or raster format, depending on the type of available data. Although tested on specific areas, the MCEs presented here can be easily used elsewhere and assist both management intervention and the protection of the adjacent environment by assessing the vulnerability of the forest landscape to either introduced chemicals or natural hazards.

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Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

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Phosphocholine (PCho) is an important substituent of surface structures expressed by a number of bacterial pathogens. Its role in virulence has been investigated in several species, in which it has been shown to play a role in bacterial adhesion to mucosal surfaces, in resistance to antimicrobial peptides, or in sensitivity to complement-mediated killing. The lipopolysaccharide (LPS) structure of Pasteurella multocida strain Pm70, whose genome sequence is known, has recently been determined and does not contain PCho. However, LPS structures from the closely related, virulent P. multocida strains VP161 and X-73 were shown to contain PCho on their terminal galactose sugar residues. To determine if PCho was involved in the virulence of P. multocida, we used subtractive hybridization of the VP161 genome against the Pm70 genome to identify a four-gene locus (designated pcgDABC) which we show is required for the addition of the PCho residues to LPS. The proteins predicted to be encoded by pcgABC showed identity to proteins involved in choline uptake, phosphorylation, and nucleotide sugar activation of PCho. We constructed a P. multocida VP161 pcgC mutant and demonstrated that this strain produces LPS that lacks PCho on the terminal galactose residues. This pcgC mutant displayed reduced in vivo growth in a chicken infection model and was more sensitive to the chicken antimicrobial peptide fowlicidin-1 than the wild-type P. multocida strain

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Because of the variable and changing environment, advisors and farmers are seeking systems that provide risk management support at a number of time scales. The Agricultural Production Systems Research Unit, Toowoomba, Australia has developed a suite of tools to assist advisors and farmers to better manage risk in cropping. These tools range from simple rainfall analysis tools (Rainman, HowWet, HowOften) through crop simulation tools (WhopperCropper and YieldProphet) to the most complex, APSFarm, a whole-farm analysis tool. Most are derivatives of the APSIM crop model. These tools encompass a range of complexity and potential benefit to both the farming community and for government policy. This paper describes, the development and usage of two specific products; WhopperCropper and APSFarm. WhopperCropper facilitates simulation-aided discussion of growers' exposure to risk when comparing alternative crop input options. The user can readily generate 'what-if' scenarios that separate the major influences whilst holding other factors constant. Interactions of the major inputs can also be tested. A manager can examine the effects of input levels (and Southern Oscillation Index phase) to broadly determine input levels that match their attitude to risk. APSFarm has been used to demonstrate that management changes can have different effects in short and long time periods. It can be used to test local advisors and farmers' knowledge and experience of their desired rotation system. This study has shown that crop type has a larger influence than more conservative minimum soil water triggers in the long term. However, in short term dry periods, minimum soil water triggers and maximum area of the various crops can give significant financial gains.

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This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.

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Effective and targeted conservation action requires detailed information about species, their distribution, systematics and ecology as well as the distribution of threat processes which affect them. Knowledge of reptilian diversity remains surprisingly disparate, and innovative means of gaining rapid insight into the status of reptiles are needed in order to highlight urgent conservation cases and inform environmental policy with appropriate biodiversity information in a timely manner. We present the first ever global analysis of extinction risk in reptiles, based on a random representative sample of 1500 species (16% of all currently known species). To our knowledge, our results provide the first analysis of the global conservation status and distribution patterns of reptiles and the threats affecting them, highlighting conservation priorities and knowledge gaps which need to be addressed urgently to ensure the continued survival of the world’s reptiles. Nearly one in five reptilian species are threatened with extinction, with another one in five species classed as Data Deficient. The proportion of threatened reptile species is highest in freshwater environments, tropical regions and on oceanic islands, while data deficiency was highest in tropical areas, such as Central Africa and Southeast Asia, and among fossorial reptiles. Our results emphasise the need for research attention to be focussed on tropical areas which are experiencing the most dramatic rates of habitat loss, on fossorial reptiles for which there is a chronic lack of data, and on certain taxa such as snakes for which extinction risk may currently be underestimated due to lack of population information. Conservation actions specifically need to mitigate the effects of human-induced habitat loss and harvesting, which are the predominant threats to reptiles.

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This study presents the use of a whole farm model in a participatory modelling research approach to examine the sensitivity of four contrasting case study farms to a likely climate change scenario. The newly generated information was used to support discussions with the participating farmers in the search for options to design more profitable and sustainable farming systems in Queensland Australia. The four case studies contrasted in key systems characteristics: opportunism in decision making, i.e. flexible versus rigid crop rotations; function, i.e. production of livestock or crops; and level of intensification, i.e. dryland versus irrigated agriculture. Tested tactical and strategic changes under a baseline and climate change scenario (CCS) involved changes in the allocation of land between cropping and grazing enterprises, alternative allocations of limited irrigation water across cropping enterprises, and different management rules for planting wheat and sorghum in rainfed cropping. The results show that expected impacts from a likely climate change scenario were evident in the following increasing order: the irrigated cropping farm case study, the cropping and grazing farm, the more opportunistic rainfed cropping farm and the least opportunistic rainfed cropping farm. We concluded that in most cases the participating farmers were operating close to the efficiency frontier (i.e. in the relationship between profits and risks). This indicated that options to adapt to climate change might need to evolve from investments in the development of more innovative cropping and grazing systems and/or transformational changes on existing farming systems. We expect that even though assimilating expected changes in climate seems to be rather intangible and premature for these farmers, as innovations are developed, adaptation is likely to follow quickly. The multiple interactions among farm management components in complex and dynamic farm businesses operating in a variable and changing climate, make the use of whole farm participatory modelling approaches valuable tools to quantify benefits and trade-offs from alternative farming systems designs in the search for improved profitability and resilience.

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Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.

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Pasteurella multocida is a Gram-negative bacterial pathogen that is the causative agent of a wide range of diseases in many animal species, including humans. A widely used method for differentiation of P. multocida strains involves the Heddleston serotyping scheme. This scheme was developed in the early 1970s and classifies P. multocida strains into 16 somatic or lipopolysaccharide (LPS) serovars using an agar gel diffusion precipitin test. However, this gel diffusion assay is problematic, with difficulties reported in accuracy, reproducibility, and the sourcing of quality serovar-specific antisera. Using our knowledge of the genetics of LPS biosynthesis in P. multocida, we have developed a multiplex PCR (mPCR) that is able to differentiate strains based on the genetic organization of the LPS outer core biosynthesis loci. The accuracy of the LPS-mPCR was compared with classical Heddleston serotyping using LPS compositional data as the "gold standard." The LPS-mPCR correctly typed 57 of 58 isolates; Heddleston serotyping was able to correctly and unambiguously type only 20 of the 58 isolates. We conclude that our LPS-mPCR is a highly accurate LPS genotyping method that should replace the Heddleston serotyping scheme for the classification of P. multocida strains.