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Brisbane, Australia

Taylor S.M.,Australian Department of Primary Industries and Fisheries | Webley J.A.C.,Australian Department of Primary Industries and Fisheries | Mayer D.G.,AgriScience Queensland
Fisheries Research | Year: 2011

As recreational fishing continues to expand, the need to obtain precise harvest estimates is becoming increasingly important for the sustainable management of fisheries. Recreational fishing data are frequently zero-inflated which can present problems for commonly used analyses that assume a normal distribution. In this study, we analysed zero-inflated recreational fishing data collected from a bus-route access point survey in southeastern Queensland, Australia. Using the Time Interval Count method, we compared estimates of the proportion of boats fishing, fishing effort, harvest per unit effort (HPUE) and harvest using sample mean values and mean values derived from a two-part conditional general linear model (CGLM). The CGLM gave more precise estimates of the proportion of boats fishing, fishing effort and HPUE, which formed the basis of the harvest calculations. Differences in harvest estimates using the two methods ranged from 3 to 28% for the five recreational species examined. Relative standard errors for harvest estimated by the CGLM were 65-84% smaller. The results suggest that CGLMs may deliver more precise outputs in other types of recreational fishing surveys that derive effort and catch from zero-inflated data. © 2011 Elsevier B.V.

Etebari K.,University of Queensland | Palfreyman R.W.,University of Queensland | Schlipalius D.,AgriScience Queensland | Nielsen L.K.,University of Queensland | And 2 more authors.
BMC Genomics | Year: 2011

Background: Parasitoid insects manipulate their hosts' physiology by injecting various factors into their host upon parasitization. Transcriptomic approaches provide a powerful approach to study insect host-parasitoid interactions at the molecular level. In order to investigate the effects of parasitization by an ichneumonid wasp (Diadegma semiclausum) on the host (Plutella xylostella), the larval transcriptome profile was analyzed using a short-read deep sequencing method (Illumina). Symbiotic polydnaviruses (PDVs) associated with ichneumonid parasitoids, known as ichnoviruses, play significant roles in host immune suppression and developmental regulation. In the current study, D. semiclausum ichnovirus (DsIV) genes expressed in P. xylostella were identified and their sequences compared with other reported PDVs. Five of these genes encode proteins of unknown identity, that have not previously been reported.Results: De novo assembly of cDNA sequence data generated 172,660 contigs between 100 and 10000 bp in length; with 35% of > 200 bp in length. Parasitization had significant impacts on expression levels of 928 identified insect host transcripts. Gene ontology data illustrated that the majority of the differentially expressed genes are involved in binding, catalytic activity, and metabolic and cellular processes. In addition, the results show that transcription levels of antimicrobial peptides, such as gloverin, cecropin E and lysozyme, were up-regulated after parasitism. Expression of ichnovirus genes were detected in parasitized larvae with 19 unique sequences identified from five PDV gene families including vankyrin, viral innexin, repeat elements, a cysteine-rich motif, and polar residue rich protein. Vankyrin 1 and repeat element 1 genes showed the highest transcription levels among the DsIV genes.Conclusion: This study provides detailed information on differential expression of P. xylostella larval genes following parasitization, DsIV genes expressed in the host and also improves our current understanding of this host-parasitoid interaction. © 2011 Etebari et al; licensee BioMed Central Ltd.

Taylor S.,Australian Department of Primary Industries and Fisheries | Sumpton W.,AgriScience Queensland | Ham T.,Australian Department of Primary Industries and Fisheries
Marine and Freshwater Research | Year: 2011

Our understanding of the ecological role of larger elasmobranchs is limited by a lack of information on their spatial and seasonal abundance. Analysis of 14 years of gill-net catch data in south-eastern Queensland, Australia, revealed that the species composition of large sharks and other elasmobranchs significantly differed among beaches and seasons. Spinner sharks (Carcharhinus brevipinna) and hammerhead sharks (Sphyrna spp.) comprised nearly half the catch of all elasmobranchs. Although the distribution of these sharks overlapped, spatial variation existed in their abundance. Spinner sharks characterised the catch at Sunshine Coast beaches, whereas the catch at Gold Coast beaches was dominated by hammerhead sharks. Seasonal differences in elasmobranch community structure were also apparent, driven largely by a lower abundance of many species during the winter and the predominance of species such as spinner sharks and hammerheads in spring and summer. The present study provides the first quantitative data for numerous species of Carcharhiniformes in south-eastern Queensland and demonstrates that analysis of catch-rate data can improve our understanding of how larger sharks partition resources. © CSIRO 2011.

Redding M.R.,AgriScience Queensland
Applied Clay Science | Year: 2011

Manure by-products of intensive livestock industries, such as spent poultry litter are a considerable nutrient resource. This study sought to improve the environmental characteristics of spent poultry litter, through the addition of hydrotalcite and bentonite, to decrease likely nutrient losses to the environment. Three experiments were conducted. An incubation trial sought to identify the effect of bentonite addition (0 to 158%. m/m of dry spent-litter mass) on exchangeable retention of ammonium-N in poultry litter. A column leaching trial (33 pore volumes over 11. days) sought to determine the effect of varied hydrotalcite additions (0 to 50%. m/m) and a fixed rate of bentonite (127%. m/m) on phosphorus release. Rainfall simulations were conducted on turf-applied spent poultry litter to determine the effect of alum (0 to 11%. m/m), bentonite (0 to 158%. m/m), and hydrotalcite (0 to 50%. m/m) addition on overland losses of phosphorus. The addition of bentonite (0 to 158%) increased the proportion of mineral N retained in exchangeable form from 19% to as much as 54%. The additions of hydrotalcite at 30% of the mass of dried litter resulted in 90% decreases in the quantity of phosphorus leached. However, under rainfall simulation, the 10% hydrotalcite addition combined with bentonite (127%) was sufficient to effectively eliminate run-off phosphorus losses that occurred with untreated spent litter. The combination of hydrotalcite (10%) and bentonite appeared to exceed the performance of conventional rates (2 to 11%. m/m) of alum addition. Only a small proportion of the decrease in phosphorus losses was attributable to bentonite addition. © 2011.

Webley J.A.C.,Australian Department of Primary Industries and Fisheries | Mayer D.G.,AgriScience Queensland | Taylor S.M.,Australian Department of Primary Industries and Fisheries
Fisheries Research | Year: 2011

Many decisions and assessments made by fisheries managers and researchers use estimates. The confidence stakeholders have in these decisions is greater when those estimates are accurate and precise. Complex statistical models are often used in fisheries management and research to improve these estimates. The models usually assume the underlying data are distributed according to some theoretical distribution (e.g. Poisson, gamma) but in reality fishery data usually only approximate theoretical distributions, breaching them to varying degrees. If the models are not sufficiently robust, these breaches can produce biased and/or imprecise estimates leading to excessive Type I and Type II errors, both of which can lead to poor decisions. We examined the robustness of seven models used in fisheries research to varying degrees of breaches in their distribution assumptions. Using six different zero-inflated gamma and Poisson distributions and three different sample sizes we examined the mean bias, confidence interval width and actual Type I error rate (as opposed to the modeled α of 0.05) of these models by comparing the estimates to the known population parameters. We found that the more complex models tended to be less robust to breaches of their distribution assumptions than the simpler normal model (sample mean). We recommend that the robustness of a chosen statistical model be assessed a priori to provide stakeholders with some confidence in the accuracy and precision of the estimates and we present a simple iterative method to do this. © 2011.

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