58 resultados para Environmental adaptation


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The project uses participatory methods to engage primary producers and advisers in central Queensland, southern Queensland, and north east New South Wales on-farm trials and demonstrations to adapt mixed farming systems to changed climate conditions. The focus is adaptation to climate change but will support abatement of greenhouse gas emissions by building soil carbon, better managing soil nitrogen and soil organic carbon. Data will be collected and integrated with data from Round 1 of the Climate Change Research Program to extend industry understanding beyond a general awareness of ‘climate change’. Nitrous oxide and soil carbon data will help farmers/advisers understand the implications of climate change and develop adaptation strategies for a more sustainable, climate sensitive future.

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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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Nodal root angle in sorghum influences vertical and horizontal root distribution in the soil profile and is thus relevant to drought adaptation. In this study, we report for the first time on the mapping of four QTL for nodal root angle (qRA) in sorghum, in addition to three QTL for root dry weight, two for shoot dry weight, and three for plant leaf area. Phenotyping was done at the six leaf stage for a mapping population (n = 141) developed by crossing two inbred sorghum lines with contrasting root angle. Nodal root angle QTL explained 58.2% of the phenotypic variance and were validated across a range of diverse inbred lines. Three of the four nodal root angle QTL showed homology to previously identified root angle QTL in rice and maize, whereas all four QTL co-located with previously identified QTL for stay-green in sorghum. A putative association between nodal root angle QTL and grain yield was identified through single marker analysis on field testing data from a subset of the mapping population grown in hybrid combination with three different tester lines. Furthermore, a putative association between nodal root angle QTL and stay-green was identified using data sets from selected sorghum nested association mapping populations segregating for root angle. The identification of nodal root angle QTL presents new opportunities for improving drought adaptation mechanisms via molecular breeding to manipulate a trait for which selection has previously been very difficult.

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Development of new agricultural industries in northern Australia is often perceived as a solution to changes in water availability that have occurred within southern Australia as a result of changes to government policy in response to and exacerbated by climate change. This report examines the likely private, social and community costs and benefits associated with the establishment of a cotton industry in the Burdekin. The research undertaken covers three spatial scales by modelling the response of cotton and to climate change at the crop and farm scale and linking this to regional scale modelling of the economy. Modelling crop growth as either a standalone crop or as part of a farm enterprise provides the clearest picture of how yields and water use will be affected under climate change. The alternative to this is to undertake very costly trials in environmental chambers. For this reason it is critical that funding for model development especially for crops being crop in novel environments be seen as a high priority for climate change and adaptation studies. Crop level simulations not only provide information on how the crop responds to climate change, they also illustrate that that these responses are the result of complex interactions and cannot necessarily be derived from the climate information alone. These simulations showed that climate change would lead to decreased cotton yields in 2030 and 2050 without the affect of CO2 fertilisation. Without CO2 fertilisation, yields would be decreased by 3.2% and 17.8%. Including CO2 fertilisation increased yields initially by 5.9%, but these were reduced by 3.6% in 2050. This still represents a major offset and at least ameliorates the impact of climate change on yield. To cope with the decreased in-crop rainfall (4.5% by 2030 and 15.8% in 2050) and an initial increase in evapotranspiration of 2% in 2030 and

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Root architecture traits in wheat are important in deep soil moisture acquisition and may be used to improve adaptation to water-limited environments. The genetic architecture of two root traits, seminal root angle and seminal root number, were investigated using a doubled haploid population derived from SeriM82 and Hartog. Multiple novel quantitative trait loci (QTL) were identified, each one having a modest effect. For seminal root angle, four QTL (-log10(P) >3) were identified on 2A, 3D, 6A and 6B, and two suggestive QTL (-log10(P) >2) on 5D and 6B. For root number, two QTL were identified on 4A and 6A with four suggestive QTL on 1B, 3A, 3B and 4A. QTL for root angle and root number did not co-locate. Transgressive segregation was found for both traits. Known major height and phenology loci appear to have little effect on root angle and number. Presence or absence of the T1BL.1RS translocation did not significantly influence root angle. Broad sense heritability (h 2) was estimated as 50 % for root angle and 31 % for root number. Root angle QTL were found to be segregating between wheat cultivars adapted to the target production region indicating potential to select for root angle in breeding programs. © 2013 Springer-Verlag Berlin Heidelberg.

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Cereal crops can suffer substantial damage if frosts occur at heading. Identification of post-head-emergence frost (PHEF) resistance in cereals poses a number of unique and difficult challenges. Many decades of research have failed to identify genotypes with PHEF resistance that could offer economically significant benefit to growers. Research and breeding gains have been limited by the available screening systems. Using traditional frost screening systems, genotypes that escape frost injury in trials due to spatial temperature differences and/or small differences in phenology can be misidentified as resistant. We believe that by improving techniques to minimize frost escapes, such ofalse-positive' results can be confidently identified and eliminated. Artificial freezing chambers or manipulated natural frost treatments offer many potential advantages but are not yet at the stage where they can be reliably used for frost screening in breeding programmes. Here we describe the development of a novel photoperiod gradient method (PGM) that facilitates screening of genotypes of different phenology under natural field frosts at matched developmental stages. By identifying frost escapes and increasing the efficiency of field screening, the PGM ensures that research effort can be focused on finding genotypes with improved PHEF resistance. To maximize the likelihood of identifying PHEF resistance, we propose that the PGM form part of an integrated strategy to (i) source germplasm;(ii) facilitate high throughput screening; and (iii) permit detailed validation. PGM may also be useful in other studies where either a range of developmental stages and/or synchronized development are desired.

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Mango is an important horticultural fruit crop and breeding is a key strategy to improve ongoing sustainability. Knowledge of breeding values of potential parents is important for maximising progress from breeding. This study successfully employed a mixed linear model methods incorporating a pedigree to predict breeding values for average fruit weight from highly unbalanced data for genotypes planted over three field trials and assessed over several harvest seasons. Average fruit weight was found to be under strong additive genetic control. There was high correlation between hybrids propagated as seedlings and hybrids propagated as scions grafted onto rootstocks. Estimates of additive genetic correlation among trials ranged from 0.69 to 0.88 with correlations among harvest seasons within trials greater than 0.96. These results suggest that progress from selection for broad adaptation can be achieved, particularly as no repeatable environmental factor that could be used to predict G x E could be identified. Predicted breeding values for 35 known cultivars are presented for use in ongoing breeding programs.

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This analysis of the variations of brown tiger prawn (Penaeus esculentus) catch in Moreton Bay multispecies trawl fishery estimated catchability using a delay difference model. It integrated several factors responsible for variations in catchability: targeting of fishing effort, increasing fishing power and changing availability. An analysis of covariance was used to define fishing events targeted at brown tiger prawns. A general linear model estimated inter-annual variations of fishing power. Temperature-induced changes in prawn behaviour played an important role on the dynamics of this fishery. Maximum likelihood estimates of targeted catchability (4.09 ± 0.42 × 10−4 boat-day−1) were twice as large as non-targeted catchability (1.86 ± 0.25 × 10−4 boat-day−1). The causes of recent declines in fishing effort in this fishery were discussed.

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Calotropis procera (Apocynaceae), a native of tropical Africa, the Middle East and the Indian subcontinent, is a serious environmental and rangeland weed of Australia and Brazil. It is also a weed in Hawaii in USA, the Caribbean Islands, the Seychelles, Mexico, Thailand, Vietnam and many Pacific Islands. In the native range C. procera has many natural enemies, thus classical biological control could be the most cost-effective option for its long-term management. Based on field surveys in India and a literature search, some 65 species of insects and five species of mites have been documented on C. procera and another congeneric-invador C. gigantea in the native range. All the leaf-feeding and stem-boring agents recorded on Calotropis spp. have wide host range. Three pre-dispersal seed predators,the Aak weevil Paramecops farinosus and the Aak fruit fly Dacuspersicus in the Indian subcontinent, and the Sodom apple fruit fly Dacus longistylus in the Middle East have been identified as prospective biological control agents based on their field host range. In Australia and Brazil, where C. procera has the potential to spread across vast areas, pre-dispersal seed predators would help to limit the spread of the weed. While the fruits of C. procera vary in size and shape across its range, those from India are similar to the ones in Australia and Brazil. Hence, seed-feeding insects from India are more likely to be suitable due to adaptation to fruit size and morphology. Future survey efforts for potential biological control agents should focus on North Africa.

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To quantify the impact that planting indigenous trees and shrubs in mixed communities (environmental plantings) have on net sequestration of carbon and other environmental or commercial benefits, precise and non-biased estimates of biomass are required. Because these plantings consist of several species, estimation of their biomass through allometric relationships is a challenging task. We explored methods to accurately estimate biomass through harvesting 3139 trees and shrubs from 22 plantings, and collating similar datasets from earlier studies, in non-arid (>300mm rainfallyear-1) regions of southern and eastern Australia. Site-and-species specific allometric equations were developed, as were three types of generalised, multi-site, allometric equations based on categories of species and growth-habits: (i) species-specific, (ii) genus and growth-habit, and (iii) universal growth-habit irrespective of genus. Biomass was measured at plot level at eight contrasting sites to test the accuracy of prediction of tonnes dry matter of above-ground biomass per hectare using different classes of allometric equations. A finer-scale analysis tested performance of these at an individual-tree level across a wider range of sites. Although the percentage error in prediction could be high at a given site (up to 45%), it was relatively low (<11%) when generalised allometry-predictions of biomass was used to make regional- or estate-level estimates across a range of sites. Precision, and thus accuracy, increased slightly with the level of specificity of allometry. Inclusion of site-specific factors in generic equations increased efficiency of prediction of above-ground biomass by as much as 8%. Site-and-species-specific equations are the most accurate for site-based predictions. Generic allometric equations developed here, particularly the generic species-specific equations, can be confidently applied to provide regional- or estate-level estimates of above-ground biomass and carbon. © 2013 Elsevier B.V.

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Tillering determines the plant size of sorghum (Sorghum bicolor) and an understanding of its regulation is important to match genotypes to prevalent growing conditions in target production environments. The aim of this study was to determine the physiological and environmental regulation of variability in tillering among sorghum genotypes, and to develop a framework for this regulation. * Diverse sorghum genotypes were grown in three experiments with contrasting temperature, radiation and plant density to create variation in tillering. Data on phenology, tillering, and leaf and plant size were collected. A carbohydrate supply/demand (S/D) index that incorporated environmental and genotypic parameters was developed to represent the effects of assimilate availability on tillering. Genotypic differences in tillering not explained by this index were defined as propensity to tiller (PTT) and probably represented hormonal effects. * Genotypic variation in tillering was associated with differences in leaf width, stem diameter and PTT. The S/D index captured most of the environmental effects on tillering and PTT most of the genotypic effects. * A framework that captures genetic and environmental regulation of tillering through assimilate availability and PTT was developed, and provides a basis for the development of a model that connects genetic control of tillering to its phenotypic consequences.

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Stay-green sorghum plants exhibit greener leaves and stems during the grain-filling period under water-limited conditions compared with their senescent counterparts, resulting in increased grain yield, grain mass, and lodging resistance. Stay-green has been mapped to a number of key chromosomal regions, including Stg1, Stg2, Stg3, and Stg4, but the functions of these individual quantitative trait loci (QTLs) remain unclear. The objective of this study was to show how positive effects of Stg QTLs on grain yield under drought can be explained as emergent consequences of their effects on temporal and spatial water-use patterns that result from changes in leaf-area dynamics. A set of four Stg near-isogenic lines (NILs) and their recurrent parent were grown in a range of field and semicontrolled experiments in southeast Queensland, Australia. These studies showed that the four Stg QTLs regulate canopy size by: (1) reducing tillering via increased size of lower leaves, (2) constraining the size of the upper leaves; and (3) in some cases, decreasing the number of leaves per culm. In addition, they variously affect leaf anatomy and root growth. The multiple pathways by which Stg QTLs modulate canopy development can result in considerable developmental plasticity. The reduction in canopy size associated with Stg QTLs reduced pre-flowering water demand, thereby increasing water availability during grain filling and, ultimately, grain yield. The generic physiological mechanisms underlying the stay-green trait suggest that similar Stg QTLs could enhance post-anthesis drought adaptation in other major cereals such as maize, wheat, and rice.

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Q fever is a vaccine-preventable disease; despite this, high annual notification numbers are still recorded in Australia. We have previously shown seroprevalence in Queensland metropolitan regions is approaching that of rural areas. This study investigated the presence of nucleic acid from Coxiella burnetii, the agent responsible for Q fever, in a number of animal and environmental samples collected throughout Queensland, to identify potential sources of human infection. Samples were collected from 129 geographical locations and included urine, faeces and whole blood from 22 different animal species; 45 ticks were removed from two species, canines and possums; 151 soil samples; 72 atmospheric dust samples collected from two locations and 50 dust swabs collected from domestic vacuum cleaners. PCR testing was performed targeting the IS1111 and COM1 genes for the specific detection of C.burnetii DNA. There were 85 detections from 1318 animal samples, giving a detection rate for each sample type ranging from 2.1 to 6.8%. Equine samples produced a detection rate of 11.9%, whilst feline and canine samples showed detection rates of 7.8% and 5.2%, respectively. Native animals had varying detection rates: pooled urines from flying foxes had 7.8%, whilst koalas had 5.1%, and 6.7% of ticks screened were positive. The soil and dust samples showed the presence of C.burnetii DNA ranging from 2.0 to 6.9%, respectively. These data show that specimens from a variety of animal species and the general environment provide a number of potential sources for C.burnetii infections of humans living in Queensland. These previously unrecognized sources may account for the high seroprevalence rates seen in putative low-risk communities, including Q fever patients with no direct animal contact and those subjects living in a low-risk urban environment.