Population genetic structure of the brown tiger prawn, Penaeus esculentus, in tropical northern Australia

Eight polymorphic microsatellite loci were analysed in six population samples from four locations of the Australian endemic brown tiger prawn, Penaeus esculentus. Tests of Hardy-Weinberg equilibrium were generally in accord with expectations, with only one locus, in two samples, showing significant deviations. Three samples were taken in different years from the Exmouth Gulf. These showed no significant heterogeneity, and it was concluded that they were from a single panmictic population. A sample from Shark Bay, also on the west coast of Australia, showed barely detectable differentiation from Exmouth Gulf (F (ST) = 0 to 0.0014). A northeast sample from the Gulf of Carpentaria showed low (F (ST) = 0.008) but significant differentiation from Moreton Bay, on the east coast. However, Exmouth Gulf/Shark Bay samples were well differentiated from the Gulf of Carpentaria/Moreton Bay (F (ST) = 0.047-0.063). The data do not fit a simple isolation by distance model. It is postulated that the east-west differentiation largely reflects the isolation of east and west coast populations that occurred at the last glacial maximum when there was a land bridge between north-eastern Australia and New Guinea.

Scalloped Hammerhead microsatellite genotypes (eight loci) representing five regions on Australia's east coast and one location in central Indonesia.

Biodiversity of sharks in the tropical Indo-Pacific is high, but species-specific information to assist sustainable resource exploitation is scarce. The null hypothesis of population genetic homogeneity was tested for scalloped hammerhead shark (Sphyrna lewini, n=244) and the milkshark (Rhizoprionodon acutus, n=209) from northern and eastern Australia, using nuclear (S. lewini, eight microsatellite loci; R. acutus, six loci) and mitochondrial gene markers (873 base pairs of NADH dehydrogenase subunit 4). We were unable to reject genetic homogeneity for S. lewini, which was as expected based on previous studies of this species. Less expected were similar results for R. acutus, which is more benthic and less vagile than S. lewini. These features are probably driving the genetic break found between Australian and central Indonesian R. acutus (F-statistics; mtDNA, 0.751 to 0.903; microsatellite loci, 0.038 to 0.047). Our results support the spatially-homogeneous management plan for shark species in Queensland, but caution is advised for species yet to be studied.

Milkshark (Rhizoprionodon acutus) microsatellite genotype data (six loci) from samples collected from five locations in eastern Australia and central Indonesia.

Biodiversity of sharks in the tropical Indo-Pacific is high, but species-specific information to assist sustainable resource exploitation is scarce. The null hypothesis of population genetic homogeneity was tested for scalloped hammerhead shark (Sphyrna lewini, n=244) and the milkshark (Rhizoprionodon acutus, n=209) from northern and eastern Australia, using nuclear (S. lewini, eight microsatellite loci; R. acutus, six loci) and mitochondrial gene markers (873 base pairs of NADH dehydrogenase subunit 4). We were unable to reject genetic homogeneity for S. lewini, which was as expected based on previous studies of this species. Less expected were similar results for R. acutus, which is more benthic and less vagile than S. lewini. These features are probably driving the genetic break found between Australian and central Indonesian R. acutus (F-statistics; mtDNA, 0.751 to 0.903; microsatellite loci, 0.038 to 0.047). Our results support the spatially-homogeneous management plan for shark species in Queensland, but caution is advised for species yet to be studied.

Negligible evidence for regional genetic population structure for two shark species Rhizoprionodon acutus (Rüppell, 1837) and Sphyrna lewini (Griffith & Smith, 1834) with contrasting biology

Biodiversity of sharks in the tropical Indo-Pacific is high, but species-specific information to assist sustainable resource exploitation is scarce. The null hypothesis of population genetic homogeneity was tested for scalloped hammerhead shark (Sphyrna lewini, n = 237) and the milk shark (Rhizoprionodon acutus, n = 207) from northern and eastern Australia, using nuclear (S. lewini, eight microsatellite loci; R. acutus, six loci) and mitochondrial gene markers (873 base pairs of NADH dehydrogenase subunit 4). We were unable to reject genetic homogeneity for S. lewini, which was as expected based on previous studies of this species. Less expected were similar results for R. acutus, which is more benthic and less vagile than S. lewini. These features are probably driving the genetic break found between Australian and central Indonesian R. acutus (F-statistics; mtDNA, 0.751–0.903, respectively; microsatellite loci, 0.038–0.047 respectively). Our results support the spatially homogeneous monitoring and management plan for shark species in Queensland, Australia.

Estimating Hydrogen Cyanide in Forage Sorghum (Sorghum bicolor) by Near-Infrared Spectroscopy

Hydrogen cyanide (HCN) is a toxic chemical that can potentially cause mild to severe reactions in animals when grazing forage sorghum. Developing technologies to monitor the level of HCN in the growing crop would benefit graziers, so that they can move cattle into paddocks with acceptable levels of HCN. In this study, we developed near-infrared spectroscopy (MRS) calibrations to estimate HCN in forage sorghum and hay. The full spectral NIRS range (400-2498 nm) was used as well as specific spectral ranges within the full spectral range, i.e., visible (400-750 nm), shortwave (800-1100 nm) and near-infrared (NIR) (1100-2498 nm). Using the full spectrum approach and partial least-squares (PLS), the calibration produced a coefficient of determination (R-2) = 0.838 and standard error of cross-validation (SECV) = 0.040%, while the validation set had a R-2 = 0.824 with a low standard error of prediction (SEP = 0.047%). When using a multiple linear regression (MLR) approach, the best model (NIR spectra) produced a R-2 = 0.847 and standard error of calibration (SEC) = 0.050% and a R-2 = 0.829 and SEP = 0.057% for the validation set. The MLR models built from these spectral regions all used nine wavelengths. Two specific wavelengths 2034 and 2458 nm were of interest, with the former associated with C=O carbonyl stretch and the latter associated with C-N-C stretching. The most accurate PLS and MLR models produced a ratio of standard error of prediction to standard deviation of 3.4 and 3.0, respectively, suggesting that the calibrations could be used for screening breeding material. The results indicated that it should be feasible to develop calibrations using PLS or MLR models for a number of users, including breeding programs to screen for genotypes with low HCN, as well as graziers to monitor crop status to help with grazing efficiency.