30 resultados para TEMPORAL ASPECTS

em eResearch Archive - Queensland Department of Agriculture


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Hendra virus (HeV) causes highly lethal disease in horses and humans in the eastern Australian states of Queensland (QLD) and New South Wales (NSW), with multiple equine cases now reported on an annual basis. Infection and excretion dynamics in pteropid bats (flying-foxes), the recognised natural reservoir, are incompletely understood. We sought to identify key spatial and temporal factors associated with excretion in flying-foxes over a 2300 km latitudinal gradient from northern QLD to southern NSW which encompassed all known equine case locations. The aim was to strengthen knowledge of Hendra virus ecology in flying-foxes to improve spillover risk prediction and exposure risk mitigation strategies, and thus better protect horses and humans. Monthly pooled urine samples were collected from under roosting flying-foxes over a three-year period and screened for HeV RNA by quantitative RT-PCR. A generalised linear model was employed to investigate spatiotemporal associations with HeV detection in 13,968 samples from 27 roosts. There was a non-linear relationship between mean HeV excretion prevalence and five latitudinal regions, with excretion moderate in northern and central QLD, highest in southern QLD/northern NSW, moderate in central NSW, and negligible in southern NSW. Highest HeV positivity occurred where black or spectacled flying-foxes were present; nil or very low positivity rates occurred in exclusive grey-headed flying-fox roosts. Similarly, little red flying-foxes are evidently not a significant source of virus, as their periodic extreme increase in numbers at some roosts was not associated with any concurrent increase in HeV detection. There was a consistent, strong winter seasonality to excretion in the southern QLD/northern NSW and central NSW regions. This new information allows risk management strategies to be refined and targeted, mindful of the potential for spatial risk profiles to shift over time with changes in flying-fox species distribution.

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Plantings of mixed native species (termed 'environmental plantings') are increasingly being established for carbon sequestration whilst providing additional environmental benefits such as biodiversity and water quality. In Australia, they are currently one of the most common forms of reforestation. Investment in establishing and maintaining such plantings relies on having a cost-effective modelling approach to providing unbiased estimates of biomass production and carbon sequestration rates. In Australia, the Full Carbon Accounting Model (FullCAM) is used for both national greenhouse gas accounting and project-scale sequestration activities. Prior to undertaking the work presented here, the FullCAM tree growth curve was not calibrated specifically for environmental plantings and generally under-estimated their biomass. Here we collected and analysed above-ground biomass data from 605 mixed-species environmental plantings, and tested the effects of several planting characteristics on growth rates. Plantings were then categorised based on significant differences in growth rates. Growth of plantings differed between temperate and tropical regions. Tropical plantings were relatively uniform in terms of planting methods and their growth was largely related to stand age, consistent with the un-calibrated growth curve. However, in temperate regions where plantings were more variable, key factors influencing growth were planting width, stand density and species-mix (proportion of individuals that were trees). These categories provided the basis for FullCAM calibration. Although the overall model efficiency was only 39-46%, there was nonetheless no significant bias when the model was applied to the various planting categories. Thus, modelled estimates of biomass accumulation will be reliable on average, but estimates at any particular location will be uncertain, with either under- or over-prediction possible. When compared with the un-calibrated yield curves, predictions using the new calibrations show that early growth is likely to be more rapid and total above-ground biomass may be higher for many plantings at maturity. This study has considerably improved understanding of the patterns of growth in different types of environmental plantings, and in modelling biomass accumulation in young (<25. years old) plantings. However, significant challenges remain to understand longer-term stand dynamics, particularly with temporal changes in stand density and species composition. © 2014.

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The size at recruitment, temporal and spatial distribution, and abiotic factors influencing abundance of three commercially important species of penaeid prawns in the sublittoral trawl grounds of Moreton Bay (Queensland, Australia) were compared. Metapenaeus bennettae and Penaeus plebejus recruit to the trawl grounds at sizes which are relatively small (14-15 mm carapace length, CL) and below that at which prawns are selected for, and retained, in the fleet's cod-ends. In contrast, Penaeus esculenlus recruit at the relatively large size of 27 mm CL from February to May, well above the size ranges selected for. Recruitment of M. bennettae extends over several months, September-October and February March, and was thus likely to be bi-annual, while the recruitment period of P. plebejus was distinct, peaking in October-November each year. Size classes of M . bennettae were the most spatially stratified of the three species. Catch rates of recruits were negatively correlated with depth for all three species, and were also negatively correlated with salinity for M. bennettae.

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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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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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The G-protein-coupled receptor 54 (muGPR54) cDNA was cloned from the brain of the grey mullet, and its expression level, as well as those of the gonadotropin-releasing hormones (GnRH1, GnRH2, GnRH3) and dopamine receptor D2 (drd2), in the brain, pituitary and ovary of pubertal fish (early, intermediate, advanced) were determined by real-time quantitative RT-PCR (QPCR). The muGPR54 cDNA has an open reading frame of 1140 bp with a predicted 380 amino acid peptide, containing seven putative transmembrane domains and putative N-glycosylation and protein kinase C phosphorylation sites. QPCR results showed that the early stage of puberty in grey mullet is characterized by significantly high levels of expression of GPR54, GnRH and drd2 in the brain relative to the intermediate and advanced stages, except for GnRH1 that increased at the advanced stage of puberty. In the pituitary, drd2 expression declined significantly at the advanced stage relative to levels at the intermediate stage. Ovarian expression of GPR54 significantly increased from the intermediate stage of puberty relative to the early stage while that of GnRH1 acutely increased at the advanced stage of puberty. The ovarian expression of drd2 decreased as puberty progressed, but the changes were not significant. The results suggest the possible role of GPR54 and GnRH in positively regulating pubertal development in grey mullet and the dopaminergic inhibition of reproductive function mediated by drd2.

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The Australian endemic skate Dipturus polyommata collected from by-catch of a benthic prawn fishery off southern Queensland was examined to provide information on reproduction and diet. Morphological relationships of total length (LT) to disc width and LT to mass were estimated. Size at birth was estimated at c. 100-110 mm and size at first feeding at c. 105-110 mm LT. Size at 50% maturity (LT50 and 95% CI) was 321 (305-332) and 300 (285-306) mm LT for females and males, respectively. Size at first maturity corresponded to 87.7% of observed maximum size in females (366 mm LT) and 87.5% in males (343 mm L T). Two females, representing 18.2% of mature females sampled in the austral winter were each carrying two egg cases. Descriptions of egg cases are given. Diet described by the index of relative importance as a percentage (%IRI) was predominantly crustacean based with carid shrimps (53.64%) and penaeoid prawns (23.30%) the most significant prey groups. Teleosts (11.72%), gammarid amphipods (5.31%) and mysids (4.72%) were also important to the diet of the species, while a further six prey groups made only a minor contribution to diet (1.31%). An ontogenetic change was evident between the diets of immature and mature skates. Immature animals fed more extensively on carids and amphipods and mature animals on penaeoids, teleosts and mysids.

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Knowledge of the temporal and spatial characteristics of chokka squid (Loligo vulgaris reynaudii) biology in South African waters is limited, so the possibility of there being a geographically fragmented stock was examined by investigating the distribution of maturity patterns for the species, covering all known spawning areas and using both historical and recent data. Gonadosomatic indices (GSI) varied between year-round consistency and apparent seasonal peaks in both summer and winter; there was no clear spatial pattern. Monthly percentage maturity provided further evidence for two peak reproductive periods each year, although mature squid were present throughout. Sex ratios demonstrated great variability between different areas and life history stages. Male-biased sex ratios were only apparent on the inshore spawning grounds and ranged between 1.118:1 and 4.267:1. Size at sexual maturity was also seasonal, squid maturing smaller in winter/spring than in summer/autumn. Also, squid in the east matured smaller than squid in the west. Although the results from the present study do not provide conclusive evidence of distinct geographic populations, squid likely spawn over a significantly larger area of the Agulhas Bank than previously estimated, and squid on the west coast of South Africa may return to spawn on the western portion of the Agulhas Bank. It remains likely, however, that the east and west coast populations are a single stock and that migration of juveniles to the west coast and their subsequent return as sub-adults is an integral but non-essential and variable part of the life history.

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Predatory insects and spiders are key elements of integrated pest management (IPM) programmes in agricultural crops such as cotton. Management decisions in IPM programmes should to be based on a reliable and efficient method for counting both predators and pests. Knowledge of the temporal constraints that influence sampling is required because arthropod abundance estimates are likely to vary over a growing season and within a day. Few studies have adequately quantified this effect using the beat sheet, a potentially important sampling method. We compared the commonly used methods of suction and visual sampling to the beat sheet, with reference to an absolute cage clamp method for determining the abundance of various arthropod taxa over 5 weeks. There were significantly more entomophagous arthropods recorded using the beat sheet and cage clamp methods than by using suction or visual sampling, and these differences were more pronounced as the plants grew. In a second trial, relative estimates of entomophagous and phytophagous arthropod abundance were made using beat sheet samples collected over a day. Beat sheet estimates of the abundance of only eight of the 43 taxa examined were found to vary significantly over a day. Beat sheet sampling is recommended in further studies of arthropod abundance in cotton, but researchers and pest management advisors should bear in mind the time of season and time of day effects.

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Discarding in commercially exploited fisheries has received considerable attention in the last decade, though only more recently in Australia. The Reef Line fishery (RLF) of the Great Barrier Reef (GBR) in Australia is a large-scale multi-sector, multi-species, highly regulated hook and line fishery with the potential for high levels of discarding. We used a range of data sources to estimate discard rates and discard quantities for the two main target groups of the RLF, the coral trout, Plectropomus spp, and the red throat emperor, Lethrinus miniatus, and investigated possible effects on discarding of recent changes in management of the fishery. Fleet-wide estimates of total annual quantities discarded from 1989 to 2003 were 292-622 t and 33-95 t for coral trout and red throat emperor, respectively. Hypothetical scenarios of high-grading after the introduction of a total allowable commercial catch for coral trout resulted in increases in discard quantities up to 3895 t, while no high-grading still meant 421 t were discarded. Increasing the minimum size limit of red throat emperor from 35 to 38 cm also increased discards to an estimated 103 t. We provide spatially and temporally explicit estimates of discarding for the two most important species in the GBR RLF of Australia to demonstrate the importance of accounting for regional variation in quantification of discarding. Effects of management changes on discarding are also highlighted. This study provides a template for exploring discarding levels for other species in the RLF and elsewhere.

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Feral pigs (Sus scrofa) are believed to have a severe negative impact on the ecological values of tropical rainforests in north Queensland, Australia. Most perceptions of the environmental impacts of feral pigs focus on their disturbance of the soil or surface material (diggings). Spatial and temporal patterns of feral pig diggings were identified in this study: most diggings occurred in the early dry season and predominantly in moist soil (swamp and creek) microhabitats, with only minimal pig diggings found elsewhere through the general forest floor. The overall mean daily pig diggings were 0.09% of the rainforest floor. Most diggings occurred 3-4 months after the month of maximum rainfall. Most pig diggings were recorded in highland swamps, with over 80% of the swamp areas dug by pigs at some time during the 18-month study period. These results suggest that management of feral pig impacts should focus on protecting swamp and creek microhabitats in the rainforest, which are preferred by pigs for digging and which have a high environmental significance.

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The membracid Aconophora compressa Walker, a biological control agent released in 1995 to control Lantana camara (Verbenaceae) in Australia, has since been collected on several nontarget plant species. Our survey suggests that sustained populations of A. compressa are found only on the introduced nontarget ornamental Citharexylum spinosum (Verbenaceae) and the target weed L. camara. It is found on other nontarget plant species only when populations on C. spinosum and L. camara are high, suggesting that the presence of populations on nontarget species may be a spill-over effect. Some of the incidence and abundance on nontarget plants could have been anticipated from host specificity studies done on this agent before release, whereas others could not. This raises important issues about predicting risks posed by weed biological control agents and the need for long-term postintroduction monitoring on nontarget species.

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Management of the commercial harvest of kangaroos relies on quotas set annually as a proportion of regular estimates of population size. Surveys to generate these estimates are expensive and, in the larger states, logistically difficult; a cheaper alternative is desirable. Rainfall is a disappointingly poor predictor of kangaroo rate of increase in many areas, but harvest statistics (sex ratio, carcass weight, skin size and animals shot per unit time) potentially offer cost-effective indirect monitoring of population abundance (and therefore trend) and status (i.e. under-or overharvest). Furthermore, because harvest data are collected continuously and throughout the harvested areas, they offer the promise of more intensive and more representative coverage of harvest areas than aerial surveys do. To be useful, harvest statistics would need to have a close and known relationship with either population size or harvest rate. We assessed this using longterm (11-22 years) data for three kangaroo species (Macropus rufus, M. giganteus and M. fuliginosus) and common wallaroos (M. robustus) across South Australia, New South Wales and Queensland. Regional variation in kangaroo body size, population composition, shooter efficiency and selectivity required separate analyses in different regions. Two approaches were taken. First, monthly harvest statistics were modelled as a function of a number of explanatory variables, including kangaroo density, harvest rate and rainfall. Second, density and harvest rate were modelled as a function of harvest statistics. Both approaches incorporated a correlated error structure. Many but not all regions had relationships with sufficient precision to be useful for indirect monitoring. However, there was no single relationship that could be applied across an entire state or across species. Combined with rainfall-driven population models and applied at a regional level, these relationships could be used to reduce the frequency of aerial surveys without compromising decisions about harvest management.

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Long-running datasets from aerial surveys of kangaroos (Macropus giganteus, Macropus [uliginosus, Macropus robustus and Macropus rufus) across Queensland, New South Wales and South Australia have been analysed, seeking better predictors of rates of increase which would allow aerial surveys to be undertaken less frequently than annually. Early models of changes in kangaroo numbers in response to rainfall had shown great promise, but much variability. We used normalised difference vegetation index (NDVI) instead, reasoning that changes in pasture condition would provide a better predictor than rainfall. However, except at a fine scale, NDVI proved no better; although two linked periods of rainfall proved useful predictors of rates of increase, this was only in some areas for some species. The good correlations reported in earlier studies were a consequence of data dominated by large droughtinduced adult mortality, whereas over a longer time frame and where changes between years are less dramatic, juvenile survival has the strongest influence on dynamics. Further, harvesting, density dependence and competition with domestic stock are additional and important influences and it is now clear that kangaroo movement has a greater influence on population dynamics than had been assumed. Accordingly, previous conclusions about kangaroo populations as simple systems driven by rainfall need to be reassessed. Examination of this large dataset has permitted descriptions of shifts in distribution of three species across eastern Australia, changes in dispersion in response to rainfall, and an evaluation of using harvest statistics as an index of density and harvest rate. These results have been combined into a risk assessment and decision theory framework to identify optimal monitoring strategies.

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In order to investigate the effect of long term recurrent selection on the pattern of gene diversity, thirty randomly-selected individuals from the progenitors (p) and four selection cycles (C0, C3, C6 and C11) were sampled for DNA analysis from the tropical maize (Zea mays L.) breeding populations, Atherton 1 (AT1) and Atherton 2 (AT2). Fifteen polymorphic Simple Sequence Repeat markers amplified a total of 284 and 257 alleles in AT1 and AT2 populations, respectively. Reductions in the number of alleles were observed at advanced selection cycles. About 11 and 12% of the alleles in AT1 and AT2 populations respectively, were near to fixation. However, a higher number of alleles (37% in AT1 and 33% in AT2) were close to extinction. Fisher's exact test and analysis of molecular variance (AMOVA) showed significant population differentiations. Gene diversity estimates and AMOVA revealed increased genetic differentiations at the expense of loss of heterozygosity. Population differentiations were mainly due to fixation of complementary alleles at a locus in the two breeding populations. The estimates of effective population at an advanced selection cycle were close to the population size predicted by the breeding method.