4 resultados para Complex environment

em eResearch Archive - Queensland Department of Agriculture


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QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.

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Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

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The urban presence of flying-foxes (pteropid bats) in eastern Australia has increased in the last 20 years, putatively reflecting broader landscape change. The influx of large numbers often precipitates community angst, typically stemming from concerns about loss of social amenity, economic loss or negative health impacts from recently emerged bat-mediated zoonotic diseases such as Hendra virus and Australian bat lyssavirus. Local authorities and state wildlife authorities are increasingly asked to approve the dispersal or modification of flying-fox roosts to address expressed concerns, yet the scale of this concern within the community, and the veracity of the basis for concern are often unclear. We conducted an on-line survey to capture community attitudes and opinions on flying-foxes in the urban environment to inform management policy and decision-making. Analysis focused on awareness, concerns, and management options, and primarily compared responses from communities where flying-fox management was and was not topical at the time of the survey. While a majority of respondents indicated a moderate to high level of knowledge of both flying-foxes and Hendra virus, a substantial minority mistakenly believed that flying-foxes pose a direct infection risk to humans, suggesting miscommunication or misinformation, and the need for additional risk communication strategies. Secondly, a minority of community members indicated they were directly impacted by urban roosts, most plausibly those living in close proximity to the roost, suggesting that targeted management options are warranted. Thirdly, neither dispersal nor culling was seen as an appropriate management strategy by the majority of respondents, including those from postcodes where flying-fox management was topical. These findings usefully inform community debate and policy development and demonstrate the value of social analysis in defining the issues and options in this complex human - wildlife interaction. The mobile nature of flying-foxes underlines the need for a management strategy at a regional or larger scale, and independent of state borders.

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Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.