5 resultados para Appropriate Selection Processes Are Available For Choosing Hospitality Texts

em eResearch Archive - Queensland Department of Agriculture


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The prioritisation of potential agents on the basis of likely efficacy is an important step in biological control because it can increase the probability of a successful biocontrol program, and reduce risks and costs. In this introductory paper we define success in biological control, review how agent selection has been approached historically, and outline the approach to agent selection that underpins the structure of this special issue on agent selection. Developing criteria by which to judge the success of a biocontrol agent (or program) provides the basis for agent selection decisions. Criteria will depend on the weed, on the ecological and management context in which that weed occurs, and on the negative impacts that biocontrol is seeking to redress. Predicting which potential agents are most likely to be successful poses enormous scientific challenges. 'Rules of thumb', 'scoring systems' and various conceptual and quantitative modelling approaches have been proposed to aid agent selection. However, most attempts have met with limited success due to the diversity and complexity of the systems in question. This special issue presents a series of papers that deconstruct the question of agent choice with the aim of progressively improving the success rate of biological control. Specifically they ask: (i) what potential agents are available and what should we know about them? (ii) what type, timing and degree of damage is required to achieve success? and (iii) which potential agent will reach the necessary density, at the right time, to exert the required damage in the target environment?

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Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

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Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PARc) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PARc explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PARc, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

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In the subtropics of Australia, irrigated temperate species are the key to reliable cool season feed on dairy farms. Persistence of perennial species is a major limitation to achieving reliable production from irrigated areas and yearly sowings of annual ryegrasses have replaced them as the most productive cool season forage production system in the subtropics. This series of experiments evaluated the yield, and resistance to rust damage, of commercially available cultivars and breeders' lines of annually sown ryegrasses (Lolium multiflorum, L. rigidum, L. x boucheanum and L perenne) in pure, nitrogen-fertilised swards under irrigation in the subtropics over a 22-year period. Barberia and Aristocrat 2 were the most adapted cultivars for subtropical conditions, producing high yields (119 and 114% of mean yield, respectively) and demonstrating the least rust damage. Newer selections from New Zealand, South African, United States of America and European breeding programs are performing better under subtropical conditions than older cultivars, particularly if a component of the selection process has been conducted in that environment. Cultivars such as Passerei Plus, Crusader, Hulk, Status and Warrior are examples of this process, producing between 105 and 115% of mean yield. Yields of annual ryegrass cultivars, which have been available or still are available for sale in Australia, ranged from 14-30 t/ha DM, depending on cultivar, site and seasonal conditions. Yields were lower at the site, which had inferior soil structure and drainage. Up to 50% of yield was produced in the 3 winter months. There was a trend towards improved yields and better tolerance of crown rust from experimental lines in the subtropics, as breeders strive for wider adaptation. Around 70% of the variation in total yield of annual ryegrass and 50 and 60% of the variation in winter and spring yield, respectively, were significantly explained by cultivar, site and climatic variables in autumn, winter and spring. While level of rust damage had no effect on total or seasonal yields, it affected the amount of green leaf available in spring. Under subtropical conditions, winter, spring and overall (autumn to mid-summer) temperatures influenced the- development of rust, which along with cultivar, accounted for 46% of the variation in rust damage. Cultivars showed a range of adaptation, with some performing well only under adverse conditions, some being well adapted to all conditions and some which performed well only under favoured conditions. Cultivars with high winter yields were most suited to subtropical conditions and included Aristocrat 2 (now released as CM 108), Barberia, Warrior, Crusader, Status, Passerei Plus and Hulk. Short growing season types such as Winter Star and T Rex performed well in winter but achieved lower total production, and long season cultivars such as Flanker rarely achieved their potential because of unfavourable conditions in late summer.

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1. Some of the most damaging invasive plants are dispersed by frugivores and this is an area of emerging importance in weed management. It highlights the need for practical information on how frugivores affect weed population dynamics and spread, how frugivore populations are affected by weeds and what management recommendations are available. 2. Fruit traits influence frugivore choice. Fruit size, the presence of an inedible peel, defensive chemistry, crop size and phenology may all be useful traits for consideration in screening and eradication programmes. By considering the effect of these traits on the probability, quality and quantity of seed dispersal, it may be possible to rank invasive species by their desirability to frugivores. Fruit traits can also be manipulated with biocontrol agents. 3. Functional groups of frugivores can be assembled according to broad species groupings, and further refined according to size, gape size, pre- and post-ingestion processing techniques and movement patterns, to predict dispersal and establishment patterns for plant introductions. 4. Landscape fragmentation can increase frugivore dispersal of invasives, as many invasive plants and dispersers readily use disturbed matrix environments and fragment edges. Dispersal to particular landscape features, such as perches and edges, can be manipulated to function as seed sinks if control measures are concentrated in these areas. 5. Where invasive plants comprise part of the diet of native frugivores, there may be a conservation conflict between control of the invasive and maintaining populations of the native frugivore, especially where other threats such as habitat destruction have reduced populations of native fruit species. 6. Synthesis and applications. Development of functional groups of frugivore-dispersed invasive plants and dispersers will enable us to develop predictions for novel dispersal interactions at both population and community scales. Increasingly sophisticated mechanistic seed dispersal models combined with spatially explicit simulations show much promise for providing weed managers with the information they need to develop strategies for surveying, eradicating and managing plant invasions. Possible conservation conflicts mean that understanding the nature of the invasive plant-frugivore interaction is essential for determining appropriate management.