The fishery and reproductive biology of Barking crayfish, Linuparus trigonus (Von Siebold, 1824) along Queenslands east coast

This paper describes the fishery and reproductive biology for Linuparus trigonus obtained from trawl fishermen operating off Queensland’s east coast, Australia. The smallest mature female lobster measured 59.8 mm CL, however, 50% maturity was reached between 80 and 85 mm CL. Brood fecundity (BF) was size dependent and ranged between 19,287 and 100,671 eggs in 32 females from 59.8 to 104.3 mm CL. The relationship was best described by the power equation BF = 0.1107*CL to the power of 2.9241 (r to the power of 2 = 0:74). Egg size ranged from 0.96 to 1.12 mm in diameter (mean = 1:02 (+or-) 0:01 mm). Egg weight and size were independent of lobster size. Length frequencies displayed multi-modal distributions.The percentage of female to male lobsters was relatively stable for small size classes (30 to 70 mm CL; 50.0 to 63.6% females), but female proportions rose markedly between 75 and 90 mm (72.2 to 85.4%) suggesting that at the onset of sexual maturity female growth rates are reduced. In size classes greater than 95 mm, males were numerically dominant. A description of the L. trigonus fishery in Queensland is also detailed.

Genetic population structure of red snappers (Lutjanus malabaricus Bloch & Schneider, 1801 and Lutjanus erythropterus Bloch, 1790) in central and eastern Indonesia and northern Australia

The genetic population structure of red snapper Lutjanus malabaricus and Lutjanus erythropterus in eastern Indonesia and northern Australia was investigated by allozyme electrophoresis and sequence variation in the control region of mtDNA. Samples were collected from eight sites in Indonesia and four sites in northern Australia for both species. A total of 13 allozyme loci were scored. More variable loci were observed in L. malabaricus than in L. erythropterus. Sequence variation in the control region (left domain) of the mitochondrial genome was assessed by RFLP and direct sequencing. MtDNA haplotype diversity was high (L. erythropterus, 0.95 and L. malabaricus, 0.97), as was intraspecific sequence divergence, (L. erythropterus, 0.0-12.5% and L. malabaricus, 0.0-9.5%). The pattern of mtDNA haplotype frequencies grouped both species into two broad fisheries stocks with a genetic boundary either between Kupang and Sape (L. malabaricus) or between Kupang and Australian Timor Sea (L. erythropertus). The allozyme analyses revealed similar boundaries for L. erythropterus. Seven allozymes stocks compared to two mtDNA stocks of L. malabaricus including Ambon, which was not sampled with mtDNA, however, were reported. Possible reasons for differences in discrimination between the methods include: i) increased power of multiple allozyme loci over the single mtDNA locus, ii) insufficient gene sampling in the mtDNA control region and iii) relative evolutionary dynamics of nuclear (allozyme loci) and mitochondrial DNA in these taxa. Allozyme and haplotype data did not distinguish separate stocks among the four Australian locations nor the central Indonesian (Bali and Sape locations) for both L. malabaricus and L. erythropterus.

Factors influencing the release and establishment of weed biological control agents

Mike Day and colleagues recently published their paper 'Factors influencing the release and establishment of weed biocontrol agents' in Proceedings of the 16th Australian Weeds Conference. The CRC for Australian Weed Management facilitated an investigation into the factors influencing the release and establishment of weed biological control agents on a wide variety of Australian weeds. The investigation improved the understanding of post-release ecology of biocontrol agents and generated recommendations for best practice. Factors affecting successful establishment on the weed include host plant characteristics, size of releases, dispersal power of the agent, predation and parasitism, and climate. A best practice guide was produced by the CRC to assist practitioners in designing robust release strategies to increase rates of establishment.

Harvest strategy evaluation to optimise the sustainability and value of the Queensland scallop fishery. Queensland scallop fishery - FRDC Project No 2006/024 Final Report

Objective 1. Measure spatial and temporal trawl frequency of scallop grounds using VMS data. This will provide a relative measure of how often individual undersized scallops are caught and put through a tumbler 2. Estimate discard mortality and growth rates for saucer scallops using cage experiments. 3. Evaluate the current management measures, in particular the seasonal closure, rotational closure and seasonally varying minimum legal sizes using stock assessment and management modeling models. Recommend optimal range of management measures to ensure long-term viability and value of the Scallop fishery based on a formal management strategy evaluation. Outcomes acheived to date: 1. Improved understanding of the survival rates of discarded sub-legal scallops; 2. Preliminary von Bertalanffy growth parameters using data from tagged-and-released scallops; 3. Changing trends in vessels and fishing gear used in the Queensland scallop fishery and their effect on scallop catch rates over time using standardised catch rates quantified; 4. Increases in fishing power of vessels operating in the Queensland scallop fishery quantified; 5. Trawl intensity mapped and quantified for all Scallop Replenishment Areas; 6. Harvest Strategy Evaluations completed.

Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time

Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.

Are high-impact species predictable? An analysis of naturalised grasses in northern Australia

Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species.

The effect of pasture utilization rate on stocks of soil organic carbon and total nitrogen in a semi-arid tropical grassland

The influence of grazing management on total soil organic carbon (SOC) and soil total nitrogen (TN) in tropical grasslands is an issue of considerable ecological and economic interest. Here we have used linear mixed models to investigate the effect of grazing management on stocks of SOC and TN in the top 0.5 m of the soil profile. The study site was a long-term pasture utilization experiment, 26 years after the experiment was established for sheep grazing on native Mitchell grass (Astrebla spp.) pasture in northern Australia. The pasture utilization rates were between 0% (exclosure) and 80%, assessed visually. We found that a significant amount of TN had been lost from the top 0.1 m of the soil profile as a result of grazing, with 80% pasture utilization resulting in a loss of 84 kg ha−1 over the 26-year period. There was no significant effect of pasture utilization rate on TN when greater soil depths were considered. There was no significant effect of pasture utilization rate on stocks of SOC and soil particulate organic carbon (POC), or the C:N ratio at any depth; however, visual trends in the data suggested some agreement with the literature, whereby increased grazing pressure appeared to: (i) decrease SOC and POC stocks; and, (ii) increase the C:N ratio. Overall, the statistical power of the study was limited, and future research would benefit from a more comprehensive sampling scheme. Previous studies at the site have found that a pasture utilization rate of 30% is sustainable for grazing production on Mitchell grass; however, given our results, we conclude that N inputs (possibly through management of native N2-fixing pasture legumes) should be made for long-term maintenance of soil health, and pasture productivity, within this ecosystem.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.