31 resultados para Regional differences

em eResearch Archive - Queensland Department of Agriculture


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Stakeholder engagement is important for successful management of natural resources, both to make effective decisions and to obtain support. However, in the context of coastal management, questions remain unanswered on how to effectively link decisions made at the catchment level with objectives for marine biodiversity and fisheries productivity. Moreover, there is much uncertainty on how to best elicit community input in a rigorous manner that supports management decisions. A decision support process is described that uses the adaptive management loop as its basis to elicit management objectives, priorities and management options using two case studies in the Great Barrier Reef, Australia. The approach described is then generalised for international interest. A hierarchical engagement model of local stakeholders, regional and senior managers is used. The result is a semi-quantitative generic elicitation framework that ultimately provides a prioritised list of management options in the context of clearly articulated management objectives that has widespread application for coastal communities worldwide. The case studies show that demand for local input and regional management is high, but local influences affect the relative success of both engagement processes and uptake by managers. Differences between case study outcomes highlight the importance of discussing objectives prior to suggesting management actions, and avoiding or minimising conflicts at the early stages of the process. Strong contributors to success are a) the provision of local information to the community group, and b) the early inclusion of senior managers and influencers in the group to ensure the intellectual and time investment is not compromised at the final stages of the process. The project has uncovered a conundrum in the significant gap between the way managers perceive their management actions and outcomes, and community's perception of the effectiveness (and wisdom) of these same management actions.

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Reforestation of agricultural land with mixed-species environmental plantings (native trees and shrubs) can contribute to mitigation of climate change through sequestration of carbon. Although soil carbon sequestration following reforestation has been investigated at site- and regional-scales, there are few studies across regions where the impact of a broad range of site conditions and management practices can be assessed. We collated new and existing data on soil organic carbon (SOC, 0–30 cm depth, N = 117 sites) and litter (N = 106 sites) under mixed-species plantings and an agricultural pair or baseline across southern and eastern Australia. Sites covered a range of previous land uses, initial SOC stocks, climatic conditions and management types. Differences in total SOC stocks following reforestation were significant at 52% of sites, with a mean rate of increase of 0.57 ± 0.06 Mg C ha−1 y−1. Increases were largely in the particulate fraction, which increased significantly at 46% of sites compared with increases at 27% of sites for the humus fraction. Although relative increase was highest in the particulate fraction, the humus fraction was the largest proportion of total SOC and so absolute differences in both fractions were similar. Accumulation rates of carbon in litter were 0.39 ± 0.02 Mg C ha−1 y−1, increasing the total (soil + litter) annual rate of carbon sequestration by 68%. Previously-cropped sites accumulated more SOC than previously-grazed sites. The explained variance differed widely among empirical models of differences in SOC stocks following reforestation according to SOC fraction and depth for previously-grazed (R2 = 0.18–0.51) and previously-cropped (R2 = 0.14–0.60) sites. For previously-grazed sites, differences in SOC following reforestation were negatively related to total SOC in the pasture. By comparison, for previously-cropped sites, differences in SOC were positively related to mean annual rainfall. This improved broad-scale understanding of the magnitude and predictors of changes in stocks of soil and litter C following reforestation is valuable for the development of policy on carbon markets and the establishment of future mixed-species environmental plantings.

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Stakeholder engagement is important for successful management of natural resources, both to make effective decisions and to obtain support. However, in the context of coastal management, questions remain unanswered on how to effectively link decisions made at the catchment level with objectives for marine biodiversity and fisheries productivity. Moreover, there is much uncertainty on how to best elicit community input in a rigorous manner that supports management decisions. A decision support process is described that uses the adaptive management loop as its basis to elicit management objectives, priorities and management options using two case studies in the Great Barrier Reef, Australia. The approach described is then generalised for international interest. A hierarchical engagement model of local stakeholders, regional and senior managers is used. The result is a semi-quantitative generic elicitation framework that ultimately provides a prioritised list of management options in the context of clearly articulated management objectives that has widespread application for coastal communities worldwide. The case studies show that demand for local input and regional management is high, but local influences affect the relative success of both engagement processes and uptake by managers. Differences between case study outcomes highlight the importance of discussing objectives prior to suggesting management actions, and avoiding or minimising conflicts at the early stages of the process. Strong contributors to success are a) the provision of local information to the community group, and b) the early inclusion of senior managers and influencers in the group to ensure the intellectual and time investment is not compromised at the final stages of the process. The project has uncovered a conundrum in the significant gap between the way managers perceive their management actions and outcomes, and community's perception of the effectiveness (and wisdom) of these same management actions.

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This paper explores the effect of using regional data for livestock attributes on estimation of greenhouse gas (GHG) emissions for the northern beef industry in Australia, compared with using state/territory-wide values, as currently used in Australia’s national GHG inventory report. Regional GHG emissions associated with beef production are reported for 21 defined agricultural statistical regions within state/territory jurisdictions. A management scenario for reduced emissions that could qualify as an Emissions Reduction Fund (ERF) project was used to illustrate the effect of regional level model parameters on estimated abatement levels. Using regional parameters, instead of state level parameters, for liveweight (LW), LW gain and proportion of cows lactating and an expanded number of livestock classes, gives a 5.2% reduction in estimated emissions (range +12% to –34% across regions). Estimated GHG emissions intensity (emissions per kilogram of LW sold) varied across the regions by up to 2.5-fold, ranging from 10.5 kg CO2-e kg–1 LW sold for Darling Downs, Queensland, through to 25.8 kg CO2-e kg–1 LW sold for the Pindan and North Kimberley, Western Australia. This range was driven by differences in production efficiency, reproduction rate, growth rate and survival. This suggests that some regions in northern Australia are likely to have substantial opportunities for GHG abatement and higher livestock income. However, this must be coupled with the availability of management activities that can be implemented to improve production efficiency; wet season phosphorus (P) supplementation being one such practice. An ERF case study comparison showed that P supplementation of a typical-sized herd produced an estimated reduction of 622 t CO2-e year–1, or 7%, compared with a non-P supplemented herd. However, the different model parameters used by the National Inventory Report and ERF project means that there was an anomaly between the herd emissions for project cattle excised from the national accounts (13 479 t CO2-e year–1) and the baseline herd emissions estimated for the ERF project (8 896 t CO2-e year–1) before P supplementation was implemented. Regionalising livestock model parameters in both ERF projects and the national accounts offers the attraction of being able to more easily and accurately reflect emissions savings from this type of emissions reduction project in Australia’s national GHG accounts.

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The Gascoyne-Murchison region of Western Australia experiences an arid to semi-arid climate with a highly variable temporal and spatial rainfall distribution. The region has around 39.2 million hectares available for pastoral lease and supports predominantly catle and sheep grazing leases. In recent years a number of climate forecasting systems have been available offering rainfall probabilities with different lead times and a forecast period; however, the extent to which these systems are capable of fulfilling the requirements of the local pastoralists is still ambiguous. Issues can range from ensuring forecasts are issued with sufficient lead time to enable key planning or decisions to be revoked or altered, to ensuring forecast language is simple and clear, to negate possible misunderstandings in interpretation. A climate research project sought to provide an objective method to determine which available forecasting systems had the greatest forecasting skill at times of the year relevant to local property management. To aid this climate research project, the study reported here was undertaken with an overall objective of exploring local pastoralists' climate information needs. We also explored how well they understand common climate forecast terms such as 'mean', median' and 'probability', and how they interpret and apply forecast information to decisions. A stratified, proportional random sampling was used for the purpose of deriving the representative sample based on rainfall-enterprise combinations. In order to provide more time for decision-making than existing operational forecasts that are issued with zero lead time, pastoralists requested that forecasts be issued for May-July and January-March with lead times counting down from 4 to 0 months. We found forecasts of between 20 and 50 mm break-of-season or follow-up rainfall were likely to influence decisions. Eighty percent of pastoralists demonstrated in a test question that they had a poor technical understanding of how to interpret the standard wording of a probabilistic median rainfall forecast. this is worthy of further research to investigate whether inappropriate management decisions are being made because the forecasts are being misunderstood. We found more than half the respondents regularly access and use weather and climate forecasts or outlook information from a range of sources and almost three-quarters considered climate information or tools useful, with preferred methods for accessing this information by email, faxback service, internet and the Department of Agriculture Western Australia's Pastoral Memo. Despite differences in enterprise types and rainfall seasonality across the region we found seasonal climate forecasting needs were relatively consistent. It became clear that providing basic training and working with pastoralists to help them understand regional climatic drivers, climate terminology and jargon, and the best ways to apply the forecasts to enhance decision-making are important to improve their use of information. Consideration could also be given to engaging a range of producers to write the climate forecasts themselves in the language they use and understand, in consultation with the scientists who prepare the forecasts.

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Representational Difference Analysis (RDA) is an established technique used for isolation of specific genetic differences between or within bacterial species. This method was used to investigate the genetic basis of serovar-specificity and the relationship between serovar and virulence in Haemophilus parasuis. An RDA clone library of 96 isolates was constructed using H. parasuis strains H425(P) (serovar 12) and HS1967 (serovar 4). To screen such a large clone library to determine which clones are strain-specific would typically involved separately labelling each clone for use in Southern hybridisation against genomic DNA from each of the strains. In this study, a novel application of reverse Southern hybridisation was used to screen the RDA library: genomic DNA from each strain was labelled and used to probe the library to identify strain-specific clones. This novel approach represents a significant improvement in methodology that is rapid and efficient.

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In coastal waters and estuaries, seagrass meadows are often subject to light deprivation over short time scales (days to weeks) in response to increased turbidity from anthropogenic disturbances. Seagrasses may exhibit negative physiological responses to light deprivation and suffer stress, or tolerate such stresses through photo-adaptation of physiological processes allowing more efficient use of low light. Pulse Amplitude Modulated (PAM) fluorometery has been used to rapidly assess changes in photosynthetic responses along in situ gradients in light. In this study, however, light is experimentally manipulated in the field to examine the photosynthesis of Halophila ovalis and Zostera capricorni. We aimed to evaluate the tolerance of these seagrasses to short-term light reductions. The seagrasses were subject to four light treatments, 0, 5, 60, and 90% shading, for a period of 14 days. In both species, as shading increased the photosynthetic variables significantly (P < 0.05) decreased by up to 40% for maximum electron transport rates (ETRmax) and 70% for saturating irradiances (Ek). Photosynthetic efficiencies (a) and effective quantum yields (ΔF/Fm′ ) increased significantly (P < 0.05), in both species, for 90% shaded plants compared with 0% shaded plants. H. ovalis was more sensitive to 90% shading than Z. capricorni, showing greater reductions in ETR max, indicative of a reduced photosynthetic capacity. An increase in Ek, Fm′ and ΔF/Fm′ for H. ovalis and Z. capricorni under 90% shading suggested an increase in photochemical efficiency and a more efficient use of low-photon flux, consistent with photo-acclimation to shading. Similar responses were found along a depth gradient from 0 to10 m, where depth related changes in ETRmax and Ek in H. ovalis implied a strong difference of irradiance history between depths of 0 and 5-10 m. The results suggest that H. ovalis is more vulnerable to light deprivation than Z. capricorni and that H. ovalis, at depths of 5-10 m, would be more vulnerable to light deprivation than intertidal populations. Both species showed a strong degree of photo-adaptation to light manipulation that may enable them to tolerate and adapt to short-term reductions in light. These consistent responses to changes in light suggest that photosynthetic variables can be used to rapidly assess the status of seagrasses when subjected to sudden and prolonged periods of reduced light

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The accurate assessment of trends in the woody structure of savannas has important implications for greenhouse accounting and land-use industries such as pastoralism. Two recent assessments of live woody biomass change from north-east Australian eucalypt woodland between the 1980s and 1990s present divergent results. The first estimate is derived from a network of permanent monitoring plots and the second from woody cover assessments from aerial photography. The differences between the studies are reviewed and include sample density, spatial scale and design. Further analyses targeting potential biases in the indirect aerial photography technique are conducted including a comparison of basal area estimates derived from 28 permanent monitoring sites with basal area estimates derived by the aerial photography technique. It is concluded that the effect of photo-scale; or the failure to include appropriate back-transformation of biomass estimates in the aerial photography study are not likely to have contributed significantly to the discrepancy. However, temporal changes in the structure of woodlands, for example, woodlands maturing from many smaller trees to fewer larger trees or seasonal changes, which affect the relationship between cover and basal area could impact on the detection of trends using the aerial photography technique. It is also possible that issues concerning photo-quality may bias assessments through time, and that the limited sample of the permanent monitoring network may inadequately represent change at regional scales

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Wheat is one of the major food crops in the world. It is Australia's largest crop and most important agricultural commodity. In Australia the crop is grown under rainfed conditions with inherently important regional environmental differences; wheat growing areas are characterized by winter dominant rainfall in southern and western Australia and summer rainfall in northern Australia. Maximizing yield potential across these diverse regions is dependent upon managing, either genetically or agronomically, those factors in the environment that limit yield. The potential of synthetic backcross lines (SBLs) to increase yield in the diverse agroecological zones of Australia was investigated. Significant yield advantages were found for many of the SBLs across diverse environments. Depending on the environment, the yield of the SBLs ranged from 8% to 30% higher than the best local check in Australia. Apart from adaptation to semiarid water stressed conditions, some SBLs were also found to be significantly higher yielding under more optimal (irrigated) conditions. The four testing environments were classified into two groups, with the northern and southern environments being in separate groups. An elite group of SBLs was identified that exhibited broad adaptation across all diverse Australian environments included in this study. Other SBLs showed specific adaptation to either northern or southern Australia. This study showed that SBLs are likely to provide breeders with the opportunity to significantly improve wheat yield beyond what was previously possible in a number of diverse production environments.

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Quantitative trait loci (QTL) detection was carried out for adventitious rooting and associated propagation traits in a second-generation outbred Corymbia torelliana x Corymbia citriodora subspecies variegata hybrid family (n=186). The parental species of this cross are divergent in their capacity to develop roots adventitiously on stem cuttings and their propensity to form lignotubers. For the ten traits studied, there was one or two QTL detected, with some QTL explaining large amounts of phenotypic variation (e.g. 66% for one QTL for percentage rooting), suggesting that major effects influence rooting in this cross. Collocation of QTL for many strongly genetically correlated rooting traits to a single region on linkage group 12 suggested pleiotropy. A three locus model was most parsimonious for linkage group 12, however, as differences in QTL position and lower genetic correlations suggested separate loci for each of the traits of shoot production and root initiation. Species differences were thought to be the major source of phenotypic variation for some rooting rate and root quality traits because of the major QTL effects and up to 59-fold larger homospecific deviations (attributed to species differences) relative to heterospecific deviations (attributed to standing variation within species) evident at some QTL for these traits. A large homospecific/heterospecific ratio at major QTL suggested that the gene action evident in one cross may be indicative of gene action more broadly in hybrids between these species for some traits.

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To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

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Kernel weight is an important factor determining grain yield and nutritional quality in sorghum, yet the developmental processes underlying the genotypic differences in potential kernel weight remain unclear. The aim of this study was to determine the stage in development at which genetic effects on potential kernel weight were realized, and to investigate the developmental mechanisms by which potential kernel weight is controlled in sorghum. Kernel development was studied in two field experiments with five genotypes known to differ in kernel weight at maturity. Pre-fertilization floret and ovary development was examined and post-fertilization kernel-filling characteristics were analysed. Large kernels had a higher rate of kernel filling and contained more endosperm cells and starch granules than normal-sized kernels. Genotypic differences in kernel development appeared before stamen primordia initiation in the developing florets, with sessile spikelets of large-seeded genotypes having larger floret apical meristems than normal-seeded genotypes. At anthesis, the ovaries for large-sized kernels were larger in volume, with more cells per layer and more vascular bundles in the ovary wall. Across experiments and genotypes, there was a significant positive correlation between kernel dry weight at maturity and ovary volume at anthesis. Genotypic effects on meristem size, ovary volume, and kernel weight were all consistent with additive genetic control, suggesting that they were causally related. The pre-fertilization genetic control of kernel weight probably operated through the developing pericarp, which is derived from the ovary wall and potentially constrains kernel expansion.

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Grazing is a major land use in Australia's rangelands. The 'safe' livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the 'best estimates' of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as 'known uncertainties' and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands ( including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the 'best estimate' projections, in combination with appropriate responses to short-term (1-5 years) climate variability, would reduce the risk of resource degradation. Climate change projections - including changes in rainfall, temperature, carbon dioxide and other climatic variables - if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of. re, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3 degrees C) was likely to result in a decrease in forage production for most rangeland locations (e. g. -21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (-33% or -9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3 degrees C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the 'best estimate' of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

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In a study that included C-4 tropical grasses, C-3 temperate grasses and C-3 pasture legumes, in vitro dry matter digestibility of extrusa, measured as in vitro dry matter loss (IVDML) during incubation, compared with that of the forage consumed, was greater for grass extrusa but not for legume extrusa. The increase in digestibility was not caused by mastication or by the freezing of extrusa samples during storage but by the action of saliva. Comparable increases in IVDML were achieved merely by mixing bovine saliva with ground forage samples. Differences were greater than could be explained by increases due to completely digestible salivary DM. There was no significant difference between animals in relation to the saliva effect on IVDML and, except for some minor differences, similar saliva effects on IVDML were measured using either the pepsin-cellulase or rumen fluid-pepsin in vitro techniques. For both C-4 and C-3 grasses the magnitude of the differences were inversely related to IVDML of the feed and there was little or no difference between extrusa and feed at high digestibilities (>70%) whereas differences of more than 10 percentage units were measured on low quality grass forages. The data did not suggest that the extrusa or saliva effect on digestibility was different for C-3 grasses than for C-4 grasses but data on C-3 grasses were limited to few species and to high digestibility samples. For legume forages there was no saliva effect when the pepsin-cellulase method was used but there was a small but significant positive effect using the rumen fluid-pepsin method. It was concluded that when samples of extrusa are analysed using in vitro techniques, predicted in vivo digestibility of the feed consumed will often be overestimated, especially for low quality grass diets. The implications of overestimating in vivo digestibility and suggestions for overcoming such errors are discussed.

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Large geographic areas can have numerous incipient invasive plant populations that necessitate eradication. However, resources are often deficient to address every infestation. Within the United States, weed lists (either state-level or smaller unit) generally guide the prioritization of eradication of each listed species uniformly across the focus region. This strategy has several limitations that can compromise overall effectiveness, which include spending limited resources on 1) low impact populations, 2) difficult to access populations, or 3) missing high impact populations of low priority species. Therefore, we developed a novel science-based, transparent, analytical ranking tool to prioritize weed populations, instead of species, for eradication and tested it on a group of noxious weeds in California. For outreach purposes, we named the tool WHIPPET (Weed Heuristics: Invasive Population Prioritization for Eradication Tool). Using the Analytic Hierarchy Process that included expert opinion, we developed three major criteria, four sub-criteria, and four sub-sub-criteria, taking into account both species and population characteristics. Subject matter experts weighted and scored these criteria to assess the relative impact, potential spread, and feasibility of eradication (major criteria) for 100 total populations of 19 species. Species-wide population scores indicated that conspecific populations do not necessarily group together in the final ranked output. Thus, priority lists based solely on species-level characteristics are less effective compared to a blended prioritization based on both species attributes and individual population and site parameters. WHIPPET should facilitate a more efficacious decision-making process allocating limited resources to target invasive plant infestations with the greatest predicted impacts to the region under consideration.