Soybean Stem Fly, Melanagromyza sojae (Diptera: Agromyzidae), in the New World: detection of high genetic diversity from soybean fields in Brazil

Soybean Stem Fly (SSF), Melanagromyza sojae (Zehntner), belongs to the family Agromyzidae and is highly polyphagous, attacking many plant species of the family Fabaceae, including soybean and other beans. SSF is regarded as one of the most important pests in soybean fields of Asia (e.g., China, India), North East Africa (e.g., Egypt), parts of Russia, and South East Asia. Despite reports of Agromyzidae flies infesting soybean fields in Rio Grande do Sul State (Brazil) in 1983 and 2009 and periodic interceptions of SSF since the 1940s by the USA quarantine authorities, SSF has not been officially reported to have successfully established in the North and South Americas. In South America, M. sojae was recently confirmed using morphology and its complete mitochondrial DNA (mtDNA) was characterized. In the present study, we surveyed the genetic diversity of M. sojae, collected directly from soybean host plants, using partial mtDNA cytochrome oxidase I (COI) gene, and provide evidence of multiple (>10) maternal lineages in SSF populations in South America, potentially representing multiple incursion events. However, a single incursion involving multiple-female founders could not be ruled out. We identified a haplotype that was common in the fields of two Brazilian states and the individuals collected from Australia in 2013. The implications of SSF incursions in southern Brazil are discussed in relation to the current soybean agricultural practices, highlighting an urgent need for better understanding of SSF population movements in the New World, which is necessary for developing effective management options for this significant soybean pest. © FUNPEC-RP.

Sustainable native forest management. Case studies in managing private native forest in southeast Queensland.

The introduction describes productive forest in Queensland and summaries the principles of native forest management that achieve optimum productivity. Case study 1 deals with thinning an even-aged regrowth forest. It shows how thinning the stand actively manages the future composition and structure to improve productivity in the best stems and increase the commercial value of the next harvest. Case study 2 describes restoring productivity in a high-graded spotted gum - ironbark forest. It shows that defective and non-saleable trees should be removed so they do not repress the future stand; and that regeneration should be thinned, retaining the best trees in adequate growing space. Case study 3 discusses on-farm value adding for hardwood forests. It shows how long-term viability and maximum productivity and returns depend on the best management practices and knowing how to obtain the best returns from a range of forest products. Case study 4 examines integrated harvesting in a eucalypt forest. It shows how integrating the harvest enables the full range of timber products are harvested and sold for their maximum value while reducing the amount of waste.

Sustainable management for rangelands in a variable climate: evidence and insights from northern Australia

Inter-annual rainfall variability is a major challenge to sustainable and productive grazing management on rangelands. In Australia, rainfall variability is particularly pronounced and failure to manage appropriately leads to major economic loss and environmental degradation. Recommended strategies to manage sustainably include stocking at long-term carrying capacity (LTCC) or varying stock numbers with forage availability. These strategies are conceptually simple but difficult to implement, given the scale and spatial heterogeneity of grazing properties and the uncertainty of the climate. This paper presents learnings and insights from northern Australia gained from research and modelling on managing for rainfall variability. A method to objectively estimate LTCC in large, heterogeneous paddocks is discussed, and guidelines and tools to tactically adjust stocking rates are presented. The possible use of seasonal climate forecasts (SCF) in management is also considered. Results from a 13-year grazing trial in Queensland show that constant stocking at LTCC was far more profitable and largely maintained land condition compared with heavy stocking (HSR). Variable stocking (VAR) with or without the use of SCF was marginally more profitable, but income variability was greater and land condition poorer than constant stocking at LTCC. Two commercial scale trials in the Northern Territory with breeder cows highlighted the practical difficulties of variable stocking and provided evidence that heavier pasture utilisation rates depress reproductive performance. Simulation modelling across a range of regions in northern Australia also showed a decline in resource condition and profitability under heavy stocking rates. Modelling further suggested that the relative value of variable v. constant stocking depends on stocking rate and land condition. Importantly, variable stocking may possibly allow slightly higher stocking rates without pasture degradation. Enterprise-level simulations run for breeder herds nevertheless show that poor economic performance can occur under constant stocking and even under variable stocking in some circumstances. Modelling and research results both suggest that a form of constrained flexible stocking should be applied to manage for climate variability. Active adaptive management and research will be required as future climate changes make managing for rainfall variability increasingly challenging.

Improving the effectiveness of age-abundance indicators in the management of fisheries in Queensland, Australia

The development of fishery indicators is a crucial undertaking as it ultimately provides evidence to stakeholders about the status of fished species such as population size and survival rates. In Queensland, as in many other parts of the world, age-abundance indicators (e.g. fish catch rate and/or age composition data) are traditionally used as the evidence basis because they provide information on species life history traits as well as on changes in fishing pressures and population sizes. Often, however, the accuracy of the information from age-abundance indicators can be limited due to missing or biased data. Consequently, improved statistical methods are required to enhance the accuracy, precision and decision-support value of age-abundance indicators.