71 resultados para Shrimps - Geographical distribution - Australia


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Beef cattle grazing is the dominant land use in the extensive tropical and sub-tropical rangelands of northern Australia. Despite the considerable knowledge on land and herd management gained from both research and practical experience, the adoption of improved management is limited by an inability to predict how changes in practices and combinations of practices will affect cattle production, economic returns and resource condition. To address these issues, past Australian and international research relating to four management factors that affect productivity and resource condition was reviewed in order to identify key management principles. The four management factors considered were stocking rates, pasture resting, prescribed fire, and fencing and water point development for managing grazing distribution. Four management principles for sound grazing management in northern Australia were formulated as follows: (1) manage stocking rates to meet goals for livestock production and land condition; (2) rest pastures to maintain them in good condition or to restore them from poor condition to increase pasture productivity; (3) devise and apply fire regimes that enhance the condition of grazing land and livestock productivity while minimising undesirable impacts; and (4) use fencing and water points to manipulate grazing distribution. Each principle is supported by several more specific guidelines. These principles and guidelines, and the supporting research on which they are based, are presented.

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This is the first report of the genetic diversity within ilarvirus subgroup 1 from eastern Australia. It supports the separation of tobacco streak virus (TSV) strains from parthenium (Parthenium hysterophorus) and crownbeard (Verbescina encelioides) based on serology and host specificity. It has confirmed one previously described strain of TSV as a member of the species Strawberry necrotic shock virus and another as a new subgroup 1 ilarvirus, ageratum latent virus (AgLV), from Ageratum houstonianum. A multiplex RT-PCR showed that the genetically distinct strains of TSV and AgLV were commonly found in symptomless infections in virus-specific alternative weed hosts growing over a wide geographical range in eastern Australia. TSV has been one of the most damaging viruses in Australian oilseed and pulse crops in recent years, and this study has provided the taxonomic knowledge essential for the development of control programs for these viruses. © 2013 Springer-Verlag Wien.

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Deriving an estimate of optimal fishing effort or even an approximate estimate is very valuable for managing fisheries with multiple target species. The most challenging task associated with this is allocating effort to individual species when only the total effort is recorded. Spatial information on the distribution of each species within a fishery can be used to justify the allocations, but often such information is not available. To determine the long-term overall effort required to achieve maximum sustainable yield (MSY) and maximum economic yield (MEY), we consider three methods for allocating effort: (i) optimal allocation, which optimally allocates effort among target species; (ii) fixed proportions, which chooses proportions based on past catch data; and (iii) economic allocation, which splits effort based on the expected catch value of each species. Determining the overall fishing effort required to achieve these management objectives is a maximizing problem subject to constraints due to economic and social considerations. We illustrated the approaches using a case study of the Moreton Bay Prawn Trawl Fishery in Queensland (Australia). The results were consistent across the three methods. Importantly, our analysis demonstrated the optimal total effort was very sensitive to daily fishing costs—the effort ranged from 9500–11 500 to 6000–7000, 4000 and 2500 boat-days, using daily cost estimates of $0, $500, $750, and $950, respectively. The zero daily cost corresponds to the MSY, while a daily cost of $750 most closely represents the actual present fishing cost. Given the recent debate on which costs should be factored into the analyses for deriving MEY, our findings highlight the importance of including an appropriate cost function for practical management advice. The approaches developed here could be applied to other multispecies fisheries where only aggregated fishing effort data are recorded, as the literature on this type of modelling is sparse.

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This study aimed to determine if pathotypic diversity of the sorghum rust pathogen, P. purpurea, exists in eastern Australia. A differential set of 10 Sorghum bicolor genotypes was used to identify four putative pathotypes from the 28 P. purpurea isolates that were tested. Pathotypes 1 and 3 were the most common, together comprising 85.7 % of the isolates tested, while pathotype 2 comprised 10.7 % of isolates, and pathotype 4 the remainder. Based on the limited number of isolates that were tested, there was evidence of geographic specialization amongst the pathotypes, with pathotype 1 not being found in north Queensland. This work has provided conclusive evidence that pathotypes of P. purpurea exist in the sorghum growing regions of Australia and has resulted in the development of a protocol for identifying pathotypes and screening breeding and experimental lines for resistance to these pathotypes. However, further investigations on the pathotypic diversity of P. purpurea and on the temporal and geographic distribution of these four as well as any additional undiscovered pathotypes are needed.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Bactrocera frauenfeldi (Schiner), the ‘mango fruit fly’, is a horticultural pest originating from the Papua New Guinea region. It was first detected in Australia on Cape York Peninsula in north Queensland in 1974 and had spread to Cairns by 1994 and Townsville by 1997. Bactrocera frauenfeldi has not been recorded further south since then despite its invasive potential, an absence of any controls and an abundance of hosts in southern areas. Analysis of cue-lure trapping data from 1997 to 2012 in relation to environmental variables shows that the distribution of B. frauenfeldi in Queensland correlates to locations with a minimum temperature for the coldest month >13.2°C, annual temperature range <19.3°C, mean temperature of the driest quarter >20.2°C, precipitation of the wettest month >268 mm, precipitation of the wettest quarter >697 mm, temperature seasonality <30.9°C (i.e. lower temperature variability) and areas with higher human population per square kilometre. Annual temperature range was the most important variable in predicting this species' distribution. Predictive distribution maps based on an uncorrelated subset of these variables reasonably reflected the current distribution of this species in northern Australia and predicted other areas in the world potentially at risk from invasion by this species. This analysis shows that the distribution of B. frauenfeldi in Australia is correlated to certain environmental variables that have most likely limited this species' spread southward in Queensland. This is of importance to Australian horticulture in demonstrating that B. frauenfeldi is unlikely to establish in horticultural production areas further south than Townsville.

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Coccidiosis is a costly enteric disease of chickens caused by protozoan parasites of the genus Eimeria. Disease diagnosis and management is complicated since there are multiple Eimeria species infecting chickens and mixed species infections are common. Current control measures are only partially effective and this, combined with concerns over vaccine efficacy and increasing drug resistance, demonstrates a need for improved coccidiosis diagnosis and control. Before improvements can be made, it is important to understand the species commonly infecting poultry flocks in both backyard and commercial enterprises. The aim of this project was to conduct a survey and assessment of poultry Eimeria across Australia using genetic markers, and create a collection of isolates for each Eimeria species. A total of 260 samples (faecal or caecal) was obtained, and survey results showed that Eimeria taxa were present in 98% of commercial and 81% of backyard flocks. The distribution of each Eimeria species was widespread across Australia, with representatives of all species being found in every state and territory, and the Eimeria species predominating in commercial flocks differed from those in backyard flocks. Three operational taxonomic units also occurred frequently in commercial flocks highlighting the need to understand the impact of these uncharacterised species on poultry production. As Eimeria infections were also frequent in backyard flocks, there is a potential for backyard flocks to act as reservoirs for disease, especially as the industry moves towards free range production systems. This Eimeria collection will be an important genetic resource which is the crucial first step in the development of more sophisticated diagnostic tools and the development of new live vaccines which ultimately will provide savings to the industry in terms of more efficient coccidiosis management.

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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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The project aimed to detect exotic C"11coides species recently established in northern Australia and to map the distribution of Cullcoid"' bi'e\, nth'sis and C. 1.1-, oddiill Western Australia and NT. Between February 1990 and June 1992, collections were Inade throughout Cape York Peninsula, Nortlierii Territory and northern and central Western Australia. Six previously unreported species were collected. These species an'e considered unlikely to be recent jininigrants and seein to pose little threat as potential arboviiT. Is vectors. C. woddi was restricted to coastal 1101tlierii Qld, the northernmost areas of NT and the northern Kiinberley region in WA. 111 NT C. bi'evitai'sis was collected as far soutli as Katlierine. In WA it was collected throughout the Kiinberley and in the Pilbara region ill all area bounded by Nullagine, KanTatha and 300km nortli of Carnalvon. C. bi'evilcii'sis reinains tlie only Guncoide. s species of known 11npoitance as a vector of livestock an'boviruses to extend into Inajor sheep-grazing areas. Generally, CUIicoides distributions in northern Australia between 1990 and 1992 were coinparable but not identical to those defined ill surveys conducted ill tlie 1970's and 1980's. Species distributions were not static and will continue to fluctuate witli variation ill rainfall. . .

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A serological survey of cattle from throughout Queensland and sheep from cattle/sheep interface areas was conducted to determine the distribution and prevalence of antibodies to Bluetongue virus serotypes. This information allowed preliminary designation of arbovirusfree zones and identification of livestock populations at greatest risk to introduction of exotic Bluetongue viruses. Throughout the state antibodies were detected to only serotypes I and 21. In cattle prevalence decreased with increasing distance from the coast ringing from 73% in the far north to less than I% in the southwest. In sheep, prevalence of bluetongue antibodies in the major cattle/sheep interface areas in the north-west and central Queensland ranged from O% to 5%. A system of strategically placed sentinel herds of 10 young serologically negative cattle was established across northern Australia to monitor the distribution and seasonality of bluetongue viruses. Initially 23 herds were located in Queensland, 4 in Northern Territory and 2 in Western Australia but by the completion of the project the number of herds in Queensland had been reduced to 12. No bluetongue virus activity was detected in Western Australia or Northern Territory herds throughout the project although testing of one herd in Northern Territory with a history of bluetongue activity was not done after June 1991. In Queensland, activity to bluetongue serotypes I and 21 was detected in all years of the project. Transmissions occurred predominantly in the period April to September and were more widespread in wetter years' The pathogenic bluetongue setotypes previously isolated from the Northern Territory have not spread to adjoining States.