9 resultados para PRECISE DETERMINATION

em eResearch Archive - Queensland Department of Agriculture


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The reliable assessment of macrophyte biomass is fundamental for ecological research and management of freshwater ecosystems. While dry mass is routinely used to determine aquatic plant biomass, wet (fresh) mass can be more practical. We tested the accuracy and precision of wet mass measurements by using a salad spinner to remove surface water from four macrophyte species differing in growth form and architectural complexity. The salad spinner aided in making precise and accurate wet mass with less than 3% error. There was also little difference between operators, with a user bias estimated to be below 5%. To achieve this level of precision, only 10–20 turns of the salad spinner are needed. Therefore, wet mass of a sample can be determined in less than 1 min. We demonstrated that a salad spinner is a rapid and economical technique to enable precise and accurate macrophyte wet mass measurements and is particularly suitable for experimental work. The method will also be useful for fieldwork in situations when sample sizes are not overly large.

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Variability of specific leaf area (SLA) across taxa, sites and crown zones was determined for four sub-tropical hardwood species, Eucalyptus grandis, E. cloeziana, E. argophloia and Corymbia citriodora ssp. variegata, growing in south-eastern Queensland. Mean SLA values were stable amongst those taxa sampled on dry sites but varied markedly between provenances of E. grandis on a moist site. Mean SLA did not vary significantly with crown zone in any of these four sub-tropical eucalypts, which is in contrast to that observed in temperate species, both in Australia and overseas. A provenance of E. cloeziana from a moist coastal site exhibited the largest SLA of all taxa studied.

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The amount of space provided to animals governs important elements of their behaviour and, hence, is critical for their health and welfare. We review the use of allometric principles and equations to estimate the static space requirements of animals when standing and lying, and the space required for animals to feed, drink, stand-up and lie-down. We use the research literature relating to transportation and intensive housing of sheep and cattle to assess the validity of allometric equations for estimating space allowances. We investigated these areas because transportation and intensive housing provide points along a continuum in terms of the duration of confinement, (from hours to months) and spatial requirements are likely to increase with increasing duration of confinement, as animals will need to perform a greater behavioural repertoire for long-term survival, health and welfare. We find that, although there are theoretical reasons why allometric relationships to space allowances may vary slightly for different classes of stock, space allowances that have been demonstrated to have adverse effects on animal welfare during transportation correlated well with an inability to accommodate standing animals, as estimated from allometry. For intensive housing, we were able to detect a space allowance below which there were adverse effects on welfare. For short duration transportation during which animals remain standing, a space allowance per animal described by the allometric equation: area (m^2) = 0.020W^0.66, where W = liveweight (kg), would appear to be appropriate. Where it is desirable for all animals to lie simultaneously, then a minimum space allowance per animal described by the allometric equation: area (m^2) = 0.027W^0.66 appears to permit this, given that animals in a group time-share space. However, there are insufficient data to determine whether this allowance onboard a vehicle/vessel would enable animals to move and access food and water with ease. In intensive housing systems, a minimum space allowance per animal described by the allometric equation: area (m^2) = 0.033W^0.66 appears to be the threshold below which there are adverse effects on welfare. These suggested space allowances require verification with a range of species under different thermal conditions and, for transportation, under different conditions of vehicular/vessel stability. The minimum length of trough per animal (L in m) required for feeding and drinking can be determined from L = 0.064W^0.33, with the number of animals required to feed/drink simultaneously taken into account, together with any requirement to minimise competition. This also requires verification with a range of species. We conclude that allometric relationships are an appropriate basis for the formulation of space allowances for livestock.

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Sandalwood oil is widely used in the medicinal, cosmetic and aromatherapy industries. The oil is distilled from the heartwood of the sandalwood tree Santalum - a genus of hemi-parasitic tree species occurring throughout South and Southeast Asia, Australia and the Pacific. With international concern on the sustainability Sandalwood oil (Fox, 2000), the quality of oil entering the market is being compromised either through extraction from underdeveloped heartwoods or through adulteration with lower grade Sandalwood oils or synthetic substitutes (Howes et al. 2004). Although no standard method exists to assess the quality of Sandalwood oil, the International Organisation for Standardisation recommends GCMS analysis of santalol oil content. NIR spectroscopy has had a demonstrated success for other essential oils (Schulz et al. 2004, Steur et al. 2001). In addition, NIR spectroscopy has also been applied as both a qualitative and quantitative analytical tool in the forestry industry (Steur et al. 2001). This project aimed to assess the ability of NIR spectroscopy as a non-invasive, rapid and cheap analytical alternative to GCMS for Santalol determination.

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Sexing wild marine mammals that show little to no sexual dimorphism is challenging. For sirenians that are difficult to catch or approach closely, molecular sexing from tissue biopsies offers an alternative method to visual discrimination. This paper reports the results of a field study to validate the use of two sexing methods: (1) visual discrimination of sex vs (2) molecular sexing based on a multiplex PCR assay which amplifies the male-specific SRY gene and differentiates ZFX and ZFY gametologues. Skin samples from 628 dugongs (Dugong dugon) and 100 Florida manatees (Trichechus manatus latirostris) were analysed and assigned as male or female based on molecular sex. These individuals were also assigned a sex based on either direct observation of the genitalia and/or the association of the individual with a calf. Individuals of both species showed 93 to 96% congruence between visual and molecular sexing. For the remaining 4 to 7%, the discrepancies could be explained by human error. To mitigate this error rate, we recommend using both of these robust techniques, with routine inclusion of sex primers into microsatellite panels employed for identity, along with trained field observers and stringent sample handling.

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The requirement for Queensland, Northern Territory and Western Australian jurisdictions to ensure sustainable harvest of fish resources and their optimal use relies on robust information on the resource status. For grey mackerel (Scomberomorus semifasciatus) fisheries, each of these jurisdictions has their own management regime in their corresponding waters. The lack of information on stock structure of grey mackerel, however, means that the appropriate spatial scale of management is not known. As well, fishers require assurance of future sustainability to encourage investment and long-term involvement in a fishery that supplies lucrative overseas markets. These management and fisher-unfriendly circumstances must be viewed in the context of recent 3-fold increases in catches of grey mackerel along the Queensland east coast, combined with significant and increasing catches in other parts of the species' northern Australian range. Establishing the stock structure of grey mackerel would also immensely improve the relevance of resource assessments for fishery management of grey mackerel across northern Australia. This highlighted the urgent need for stock structure information for this species. The impetus for this project came from the strategic recommendations of the FRDC review by Ward and Rogers (2003), "Northern mackerel (Scombridae: Scomberomorus): current and future research needs" (Project No. 2002/096), which promoted the urgency for information on the stock structure of grey mackerel. In following these recommendations this project adopted a multi-technique and phased sampling approach as carried out by Buckworth et al (2007), who examined the stock structure of Spanish mackerel, Scomberomorus commerson, across northern Australia. The project objectives were to determine the stock structure of grey mackerel across their northern Australian range, and use this information to define management units and their appropriate spatial scales. We used multiple techniques concurrently to determine the stock structure of grey mackerel. These techniques were: genetic analyses (mitochondrial DNA and microsatellite DNA), otolith (ear bones) isotope ratios, parasite abundances, and growth parameters. The advantage of using this type of multi-technique approach was that each of the different methods is informative about the fish’s life history at different spatial and temporal scales. Genetics can inform about the evolutionary patterns as well as rates of mixing of fish from adjacent areas, while parasites and otolith microchemistry are directly influenced by the environment and so will inform about the patterns of movement during the fishes lifetime. Growth patterns are influenced by both genetic and environmental factors. Due to these differences the use of these techniques concurrently increases the likelihood of detecting different stocks where they exist. We adopted a phased sampling approach whereby sampling was carried out at broad spatial scales in the first year: east coast, eastern Gulf of Carpentaria (GoC), western GoC, and the NW Northern Territory (NW NT). By comparing the fish samples from each of these locations, and using each of the techniques, we tested the null hypothesis that grey mackerel were comprised of a single homogeneous population across northern Australia. Having rejected the null hypothesis we re-sampled the 1st year locations to test for temporal stability in stock structure, and to assess stock structure at finer spatial scales. This included increased spatial coverage on the east coast, the GoC, and WA. From genetic approaches we determined that there at least four genetic stocks of grey mackerel across northern Australia: WA, NW NT (Timor/Arafura), the GoC and the east Grey mackerel management units in northern Australia ix coast. All markers revealed concordant patterns showing WA and NW NT to be clearly divergent stocks. The mtDNA D-loop fragment appeared to have more power to resolve stock boundaries because it was able to show that the GoC and east coast QLD stocks were genetically differentiated. Patterns of stock structure on a finer scale, or where stock boundaries are located, were less clear. From otolith stable isotope analyses four major groups of S. semifasciatus were identified: WA, NT/GoC, northern east coast and central east coast. Differences in the isotopic composition of whole otoliths indicate that these groups must have spent their life history in different locations. The magnitude of the difference between the groups suggests a prolonged separation period at least equal to the fish’s life span. The parasite abundance analyses, although did not include samples from WA, suggest the existence of at least four stocks of grey mackerel in northern Australia: NW NT, the GoC, northern east coast and central east coast. Grey mackerel parasite fauna on the east coast suggests a separation somewhere between Townsville and Mackay. The NW NT region also appears to comprise a separate stock while within the GoC there exists a high degree of variability in parasite faunas among the regions sampled. This may be due to 1. natural variation within the GoC and there is one grey mackerel stock, or 2. the existence of multiple localised adult sub-stocks (metapopulations) within the GoC. Growth parameter comparisons were only possible from four major locations and identified the NW NT, the GoC, and the east coast as having different population growth characteristics. Through the use of multiple techniques, and by integrating the results from each, we were able to determine that there exist at least five stocks of grey mackerel across northern Australia, with some likelihood of additional stock structuring within the GoC. The major management units determined from this study therefore were Western Australia, NW Northern Territory (Timor/Arafura), the Gulf of Carpentaria, northern east Queensland coast and central east Queensland coast. The management implications of these results indicate the possible need for management of grey mackerel fisheries in Australia to be carried out on regional scales finer than are currently in place. In some regions the spatial scales of management might continue as is currently (e.g. WA), while in other regions, such as the GoC and the east coast, managers should at least monitor fisheries on a more local scale dictated by fishing effort and assess accordingly. Stock assessments should also consider the stock divisions identified, particularly on the east coast and for the GoC, and use life history parameters particular to each stock. We also emphasise that where we have not identified different stocks does not preclude the possibility of the occurrence of further stock division. Further, this study did not, nor did it set out to, assess the status of each of the stocks identified. This we identify as a high priority action for research and development of grey mackerel fisheries, as well as a management strategy evaluation that incorporates the conclusions of this work. Until such time that these priorities are addressed, management of grey mackerel fisheries should be cognisant of these uncertainties, particularly for the GoC and the Queensland east coast.

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On-going, high-profile public debate about climate change has focussed attention on how to monitor the soil organic carbon stock (C(s)) of rangelands (savannas). Unfortunately, optimal sampling of the rangelands for baseline C(s) - the critical first step towards efficient monitoring - has received relatively little attention to date. Moreover, in the rangelands of tropical Australia relatively little is known about how C(s) is influenced by the practice of cattle grazing. To address these issues we used linear mixed models to: (i) unravel how grazing pressure (over a 12-year period) and soil type have affected C(s) and the stable carbon isotope ratio of soil organic carbon (delta(13)C) (a measure of the relative contributions of C(3) and C(4) vegetation to C(s)); (ii) examine the spatial covariation of C(s) and delta(13)C; and, (iii) explore the amount of soil sampling required to adequately determine baseline C(s). Modelling was done in the context of the material coordinate system for the soil profile, therefore the depths reported, while conventional, are only nominal. Linear mixed models revealed that soil type and grazing pressure interacted to influence C(s) to a depth of 0.3 m in the profile. At a depth of 0.5 m there was no effect of grazing on C(s), but the soil type effect on C(s) was significant. Soil type influenced delta(13)C to a soil depth of 0.5 m but there was no effect of grazing at any depth examined. The linear mixed model also revealed the strong negative correlation of C(s) with delta(13)C, particularly to a depth of 0.1 m in the soil profile. This suggested that increased C(s) at the study site was associated with increased input of C from C(3) trees and shrubs relative to the C(4) perennial grasses; as the latter form the bulk of the cattle diet, we contend that C sequestration may be negatively correlated with forage production. Our baseline C(s) sampling recommendation for cattle-grazing properties of the tropical rangelands of Australia is to: (i) divide the property into units of apparently uniform soil type and grazing management; (ii) use stratified simple random sampling to spread at least 25 soil sampling locations about each unit, with at least two samples collected per stratum. This will be adequate to accurately estimate baseline mean C(s) to within 20% of the true mean, to a nominal depth of 0.3 m in the profile.

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In Maize, as with most cereals, grain yield is mostly determined by the total grain number per unit area, which is highly related to the rate of crop growth during the critical period around silking. Management practices such as plant density or nitrogen fertilization can affect the growth of the crop during this period, and consequently the final grain yield. Across the Northern Region maize is grown under a large range of plant populations under high year-to-year rainfall variability. Clear guidelines on how to match hybrids and management across environments and expected seasonal condition, would allow growers to increase yields and profits while managing risks. The objective of this research was to screen the response of commercial maize hybrids differing in maturity and prolificity (i.e. multi or single cobbing) types for their efficiency in the allocation of biomass into grain.