Temporal expression of G-protein-coupled receptor 54 (GPR54), gonadotropin-releasing hormones (GnRH), and dopamine receptor D2 (drd2) in pubertal female grey mullet, Mugil cephalus.

The G-protein-coupled receptor 54 (muGPR54) cDNA was cloned from the brain of the grey mullet, and its expression level, as well as those of the gonadotropin-releasing hormones (GnRH1, GnRH2, GnRH3) and dopamine receptor D2 (drd2), in the brain, pituitary and ovary of pubertal fish (early, intermediate, advanced) were determined by real-time quantitative RT-PCR (QPCR). The muGPR54 cDNA has an open reading frame of 1140 bp with a predicted 380 amino acid peptide, containing seven putative transmembrane domains and putative N-glycosylation and protein kinase C phosphorylation sites. QPCR results showed that the early stage of puberty in grey mullet is characterized by significantly high levels of expression of GPR54, GnRH and drd2 in the brain relative to the intermediate and advanced stages, except for GnRH1 that increased at the advanced stage of puberty. In the pituitary, drd2 expression declined significantly at the advanced stage relative to levels at the intermediate stage. Ovarian expression of GPR54 significantly increased from the intermediate stage of puberty relative to the early stage while that of GnRH1 acutely increased at the advanced stage of puberty. The ovarian expression of drd2 decreased as puberty progressed, but the changes were not significant. The results suggest the possible role of GPR54 and GnRH in positively regulating pubertal development in grey mullet and the dopaminergic inhibition of reproductive function mediated by drd2.

Can feral pig harvesting and co-ordinated control reduce damage to grain crops?

Commercial and recreational harvesting of pigs is often encouraged by pest managers because it is essentially a ‘free’ reduction in pest density. However, the reduction in numbers may provide minimal damage mitigation and may be inappropriately allocated in space and time. Additionally, more effective control (e.g. baiting) may not occur because of the incorrect perception that harvesting is effective or because pigs are valued for recreational use.

Risk-based surveillance for avian influenza control along poultry market chains in South China: The value of social network analysis.

Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5 years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.

Round scallops and square meshes: a comparison of four codend types on the catch rates of target species and by-catch in the Queensland (Australia) saucer scallop (Amusium balloti) trawl fishery

Concern over the amount of by-catch from benthic trawl fisheries and research into the problem have increased in recent years. The present paper demonstrated that by-catch rates in the Queensland (Australia) saucer scallop (Amusium balloti) trawl fishery can be reduced by 77% (by weight) using nets fitted with a turtle excluder device (TED) and a square-mesh codend, compared with a standard diamond-mesh codend with no TED. This large reduction was achieved with no significant effect on the legal size scallop catch rate and 39% fewer undersize scallops were caught. In total, 382 taxa were recorded in the by-catch, which was dominated by sponges, portunid crabs, small demersal and benthic fish (e.g. leatherjackets, stingerfish, bearded ghouls, nemipterids, longspine emperors, lizard fish, triggerfish, flounders and rabbitfish), elasmobranchs (e.g. mainly rays) and invertebrates (e.g. sea stars, sea urchins, sea cucumbers and bivalve molluscs). Extremely high reductions in catch rate (i.e. ≥85%) were demonstrated for several by-catch species owing to the square-mesh codend. Square-mesh codends show potential as a means of greatly reducing by-catch and lowering the incidental capture and mortality of undersize scallops and Moreton Bay bugs (Thenus australiensis) in this fishery

Plot size matters: interference from intergenotypic competition in plant phenotyping studies

Genetic and physiological studies often comprise genotypes diverse in vigour, size and flowering time. This can make the phenotyping of complex traits challenging, particularly those associated with canopy development, biomass and yield, as the environment of one genotype can be influenced by a neighbouring genotype. Limited seed and space may encourage field assessment in single, spaced rows or in small, unbordered plots, whereas the convenience of a controlled environment or greenhouse makes pot studies tempting. However, the relevance of such growing conditions to commercial field-grown crops is unclear and often doubtful. Competition for water, light and nutrients necessary for canopy growth will be variable where immediate neighbours are genetically different, particularly under stress conditions, where competition for resources and influence on productivity is greatest. Small hills and rod-rows maximise the potential for intergenotypic competition that is not relevant to a crop’s performance in monocultures. Response to resource availability will typically vary among diverse genotypes to alter genotype ranking and reduce heritability for all growth-related traits, with the possible exception of harvest index. Validation of pot experiments to performance in canopies in the field is essential, whereas the planting of multirow plots and the simple exclusion of plot borders at harvest will increase experimental precision and confidence in genotype performance in target environments.

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.