Corrigendum to: The acute physiological status of white sharks (Carcharodon carcharias) exhibits minimal variation after capture on SMART drumlines.

[This corrects the article DOI: 10.1093/conphys/coz042.].

The acute physiological status of white sharks (Carcharodon carcharias) exhibits minimal variation after capture on SMART drumlines.

Drumlines incorporating SMART (Shark-Management-Alert-in-Real-Time) technology are a new tool used in several bather protection programmes globally. In New South Wales (NSW), Australia, the white shark (Carcharodon carcharias) is a target species for SMART drumlines because they are often involved in attacks on humans. To understand white shark sensitivity to capture and to establish protocols around acceptable timeframes for responding to alerts, 47 juvenile and subadult white sharks were caught on SMART drumlines at five locations off the east coast of Australia. There was no at-vessel mortality during the sampling period. After capture, blood was sampled from each shark to assess its acute physiological status. Of the 18 metabolites investigated, only lactate and aspartate aminotransferase exhibited significant positive relationships with the capture duration on SMART drumlines. These results indicate that the capture process is relatively benign and that the current response times used here are appropriate to minimize long-term negative impacts on released white sharks. Where white sharks are likely to interact negatively with beachgoers, SMART drumlines can therefore be a useful addition to bather protection programmes that also aim to minimize harm to captured animals. Other shark species captured on SMART drumlines should also be investigated to gain broader understanding of potential physiological consequences of using this new technology.

Resilience of inshore, juvenile snapper Pagrus auratus to angling and release.

This study assessed the mortality of 157 snapper Pagrus auratus (9-29 cm, total length, L(T) ) after being conventionally angled and then released into cages (along with 48 controls) for 4 days off south-eastern Australia. Fatalities were restricted to 12 angled fish (7·6%) and mostly attributed to the ingestion of hooks and especially their subsequent removal, which caused substantial blood loss and immediate death. Hook ingestion was significantly biased towards smaller fish (<21 cm L(T)) and attributed to a lower chance of anglers initially detecting these individuals on the line (allowing them to consume more of the baits). While mortalities might be reduced in future via (1) choosing terminal rigs that promote mouth hooking and (2) cutting the line on any-hook ingested fish, the results nevertheless validate releasing unwanted angled inshore juvenile P. auratus as a means for managing their exploitation.

Analysis of yield and oil from a series of canola breeding trials. Part I. Fitting factor analytic mixed models with pedigree information.

In this paper multiplicative mixed models have been used for the analysis of multi-environment trial (MET) data for canola oil and grain yield. Information on pedigrees has been included to allow for the modelling of additive and nonadditive genetic effects. The MET data set included a total of 19 trials (synonymous with sites or environments), which were sown across southern Australia in 2007 and 2008. Each trial was designed as a p-rep design using DiGGeR with the default prespecified spatial model. Lines in their first year of testing were unreplicated, whereas there were two or three replications of advanced lines or varieties. Pedigree information on a total of 578 entries was available, and there were 69 entries that had unknown pedigrees. The degree of inbreeding varied from 0 (55 entries) to nearly fully inbred (337 entries). Subsamples of 2 g harvested grain were taken from each plot for determination of seed oil percentage by near infrared reflectance spectroscopy. The MET analysis for both yield and oil modelled genetic effects in different trials using factor analytic models and the residual plot effects for each trial were modelled using spatial techniques. Models in which pedigree information was included provided significantly better fits to both yield and oil data.

Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis.

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.

The analysis of the NSW wheat variety database. I. Modelling trial error variance.

The retrospective analysis of a large database on wheat variety testing in New South Wales (NSW) is considered. This analysis involved three key steps. Initially error variance heterogeneity is modelled, indicating significant differences in error variance due to trial location, year of trialling, sowing date and trial mean yield. The implication of this modelling for the estimaion of variance components is discussed.

The analysis of the NSW wheat variety database. II. Variance component estimation.

The efficiency of various trialling systems for wheat variety evaluation in New South Wales (NSW) is considered. This involved the estimation of the variance components due to genotype, genotype-by-year, genotype-by-location and genotype-by-year-by-location. It is shown that there is a significant reduction in the magnitude of these variance components by the inclusion of the interaction of genotype maturity, winter habit and aluminium tolerance with environment.

The effect of footrot on body weight and wool growth of sheep.

Body weight and traits associated with production of wool were measured over a 2-year period between 1985 and 1987 in south-western New South Wales in a flock of Merino wethers experimentally infected with footrot. The disease was allowed to spread freely amongst 150 of the flock but kept at very low prevalence in the remaining 50 by preventive footbathing during transmission periods. Severe, underrunning footrot had a significant adverse effect on body weight, for each year of the trial. Body weight was most severely reduced at times of the year when footrot was spreading among animals and lesions were severe. The mean body weight of the infected group at the end of the 2 years of observation was 7.3 kg (11.6%) below that of the control group. Footrot also depressed wool growth, with the mean clean fleece weight of the infected group being 0.4 kg (8%) lighter than that of the controls at each of the 2 annual shearings. There were no consistent differences between the groups for the other wool characteristics measured.

A model for the analysis of growth data from designed experiments.

A model for growth data from designed experiments is presented which extends the stochastic differential equation of Sandland and McGilchrist (1979, Biometrics 35, 255-272). Residual maximum likelihood (REML) is used to estimate the parameters of the model. The model is easily extended to incomplete data and is shown to overcome some of the practical difficulties encountered with the profile model. The procedure is applied to data from experiments on pigs and sheep.