The extent of population genetic subdivision differs among four co-distributed shark species in the Indo-Australian archipelago

Background: The territorial fishing zones of Australia and Indonesia are contiguous to the north of Australia in the Timor and Arafura Seas and in the Indian Ocean to the north of Christmas Island. The area surrounding the shared boundary consists of a variety of bio-diverse marine habitats including shallow continental shelf waters, oceanic trenches and numerous offshore islands. Both countries exploit a variety of fisheries species, including whaler (Carcharhinus spp.) and hammerhead sharks (Sphyrna spp.). Despite their differences in social and financial arrangements, the two countries are motivated to develop complementary co-management practices to achieve resource sustainability. An essential starting point is knowledge of the degree of population subdivision, and hence fisheries stock status, in exploited species. Results: Populations of four commercially harvested shark species (Carcharhinus obscurus, Carcharhinus sorrah, Prionace glauca, Sphyrna lewini) were sampled from northern Australia and central Indonesia. Neutral genetic markers (mitochondrial DNA control region sequence and allelic variation at co-dominant microsatellite loci) revealed genetic subdivision between Australian and Indonesian populations of C. sorrah. Further research is needed to address the possibility of genetic subdivision among C. obscurus populations. There was no evidence of genetic subdivision for P. glauca and S. lewini populations, but the sampling represented a relatively small part of their distributional range. For these species, more detailed analyses of population genetic structure is recommended in the future. Conclusion: Cooperative management between Australia and Indonesia is the best option at present for P. glauca and S. lewini, while C. sorrah and C. obscurus should be managed independently. On-going research on these and other exploited shark and ray species is strongly recommended. Biological and ecological similarity between species may not be a predictor of population genetic structure, so species-specific studies are recommended to provide new data to assist with sustainable fisheries management.

Significant features of the epidemiology of equine influenza in Queensland, Australia, 2007.

An outbreak of equine influenza (EI) caused by influenza A H3N8 subtype virus occurred in the Australian states of Queensland and New South Wales in August 2007. Infection in the Australian horse population was associated with the introduction of infection by horses from overseas. The first case of EI in Queensland was detected on 25 August 2007 at an equestrian sporting event. Infection subsequently spread locally and to other clusters through horse movements prior to the implementation of an official standstill. There were five main clusters of infected properties during this outbreak and several outliers, which were investigated to find the potential mechanism of disease spread. To contain the outbreak, Queensland was divided into infection status zones, with different movement controls applied to each zone. Vaccination was implemented strategically in infected areas and within horse subpopulations. Control and eventual eradication of EI from Queensland was achieved through a combination of quarantine, biosecurity measures, movement control, rapid diagnostic testing and vaccination.

Evaluation of wood characteristics of tropical post-mid rotation plantation Eucalyptus cloeziana and E. pellita: Part (c) Wood quality and structural properties.

This study provides information about wood quality, structural properties, processing characterists and product suitability of wood harvested from fast-grown hardwood plantations. Wood quality attributes tested included density, extractive content, unit shrinkage, heartwood proportion and sapwood width. Structural properties tested included small clear and full section strength and stiffness, hardness, joint group, visual grade assessment and natural vibration-based grade assessment. The variation between the inner, intermediate and outer heartwood zones and the variation between provenances was also tested. Overall, the wood qualtiy attributes measured for 19 year-old E. cloeziana and 15 year-old E. pellita plantation material fall between those expected from the wood of mature, native forest trees and those found in younger plantation material of the same species.

Driving better vegetable irrigation through profitable practice change

The availability and quality of irrigation water has become an issue limiting productivity in many Australian vegetable regions. Production is also under competitive pressure from supply chain forces. Producers look to new technologies, including changing irrigation infrastructure, exploring new water sources, and more complex irrigation management, to survive these stresses. Often there is little objective information investigating which improvements could improve outcomes for vegetable producers, and external communities (e.g. meeting NRM targets). This has led to investment in inappropriate technologies, and costly repetition of errors, as business independently discover the worth of technologies by personal experience. In our project, we investigated technology improvements for vegetable irrigation. Through engagement with industry and other researchers, we identified technologies most applicable to growers, particularly those that addressed priority issues. We developed analytical tools for ‘what if’ scenario testing of technologies. We conducted nine detailed experiments in the Lockyer Valley and Riverina vegetable growing districts, as well as case studies on grower properties in southern Queensland. We investigated root zone monitoring tools (FullStop™ wetting front detectors and Soil Solution Extraction Tubes - SSET), drip system layout, fertigation equipment, and altering planting arrangements. Our project team developed and validated models for broccoli, sweet corn, green beans and lettuce, and spreadsheets for evaluating economic risks associated with new technologies. We presented project outcomes at over 100 extension events, including irrigation showcases, conferences, field days, farm walks and workshops. The FullStops™ were excellent for monitoring root zone conditions (EC, nitrate levels), and managing irrigation with poor quality water. They were easier to interpret than the SSET. The SSET were simpler to install, but required wet soil to be reliable. SSET were an option for monitoring deeper soil zones, unsuitable for FullStop™ installations. Because these root zone tools require expertise, and are labour intensive, we recommend they be used to address specific problems, or as a periodic auditing strategy, not for routine monitoring. In our research, we routinely found high residual N in horticultural soils, with subsequently little crop yield response to additional nitrogen fertiliser. With improved irrigation efficiency (and less leaching), it may be timely to re-examine nitrogen budgets and recommendations for vegetable crops. Where the drip irrigation tube was located close to the crop row (i.e. within 5-8 cm), management of irrigation was easier. It improved nitrogen uptake, water use efficiency, and reduced the risk of poor crop performance through moisture stress, particularly in the early crop establishment phases. Close proximity of the drip tube to the crop row gives the producer more options for managing salty water, and more flexibility in taking risks with forecast rain. In many vegetable crops, proximate drip systems may not be cost-effective. The next best alternative is to push crop rows closer to the drip tube (leading to an asymmetric row structure). The vegetable crop models are good at predicting crop phenology (development stages, time to harvest), input use (water, fertiliser), environmental impacts (nutrient, salt movement) and total yields. The two immediate applications for the models are understanding/predicting/manipulating harvest dates and nitrogen movements in vegetable cropping systems. From the economic tools, the major influences on accumulated profit are price and yield. In doing ‘what if’ analyses, it is very important to be as accurate as possible in ascertaining what the assumed yield and price ranges are. In most vegetable production systems, lowering the required inputs (e.g. irrigation requirement, fertiliser requirement) is unlikely to have a major influence on accumulated profit. However, if a resource is constraining (e.g. available irrigation water), it is usually most profitable to maximise return per unit of that resource.

Construction timbers in Queensland. Book 1 and Book 2: Properties and specifications for satisfactory performance of construction timbers in Queensland. Class 1 and Class 10 buildings (houses, carports, garages, greenhouses and sheds). 2013 edition.

This publication lists the more important wood properties of commercial timbers used for construction in Queensland. It also provides requirements and conditions of use for these timbers to provide appropriate design service life in various construction applications. The correct specification of timber considers a range of timber properties including, but not limited to, stress grade; durability class; moisture content and insect resistance. For the specification of timber sizes and spans, relevant Australian Standards and design manuals should be consulted—e.g. Australian Standard AS 1684 series Residential timber—framed construction parts 2 and 3 (Standards Australia 2006a;b.) Book 1 explains the terms used; with reference to nomenclature; origin and timber properties presented under specific column headings in the schedules (Book 2). It also explains target design life; applications and decay hazard zones; presented in the Book 2 Schedules. Book 2 consists of reference tables; presented as schedules A; B and C: • Schedule A contains commercial mixtures of unidentified timbers and of some Australian and imported softwoods. Index numbers 1–10 • Schedule B contains Australian-grown timber species; including both natural forests and plantations. Index numbers 11–493 • Schedule C contains timbers imported into Australia from overseas. Index numbers 494–606 Each schedule has two parts presenting data in tables. • Part 1: Nomenclature, origin and properties of imported timber species • Part 2: Approved uses for commercial mixtures of imported timber species The recommendations made in this publication assume that good building practice will be carried out.

Rabbit haemorrhagic disease: are Australian rabbits (Oryctolagus cuniculus) evolving resistance to infection with Czech CAPM 351 RHDV?

Rabbit haemorrhagic disease is a major tool for the management of introduced, wild rabbits in Australia. However, new evidence suggests that rabbits may be developing resistance to the disease. Rabbits sourced from wild populations in central and southeastern Australia, and domestic rabbits for comparison, were experimentally challenged with a low 60 ID50 oral dose of commercially available Czech CAPM 351 virus - the original strain released in Australia. Levels of resistance to infection were generally higher than for unselected domestic rabbits and also differed (0-73% infection rates) between wild populations. Resistance was lower in populations from cooler, wetter regions and also low in arid regions with the highest resistance seen within zones of moderate rainfall. These findings suggest the external influences of non-pathogenic calicivirus in cooler, wetter areas and poor recruitment in arid populations may influence the development rate of resistance in Australia.

Comparative growth and biomass allocation of two varieties of cat's claw creeper, Dolichandra unguis-cati (Bignoniaceae) in Australia

Introduced as an ornamental vine, cat's claw creeper Dolichandra unguis-cati (syn. Macfadyena unguis-cati) has invaded coastal and subcoastal areas of subtropical eastern Australia. Two varieties have been indentified, one of which ('short-pod') is found throughout south-eastern Australia, while the other ('long-pod') appears to be restricted to several sites in south-eastern Queensland. We compared the growth and biomass allocation patterns of the two varieties in the field over a 22-month period to determine if a higher growth rate and/or more efficient allocation of biomass may contribute to this disparity in distribution. The long-pod variety produced greater aboveground and total biomass than the short-pod variety in both riparian and non-riparian zones. Belowground the two varieties produced a similar number of tubers and overall biomass, though the long-pod variety allocated a smaller portion of its carbon belowground. High growth rates and greater biomass allocation aboveground are characteristic of invasive species, allowing them to outcompete and crowd out existing vegetation. There was no significant site by variety interaction, an indication of consistency in variety performance across riparian and non-riparian sites. Results from our study suggest that differences in growth and biomass allocations are unlikely to have contributed to the disparity in distribution of the two varieties. Despite currently occupying a relatively small range, the long-pod variety may be a more adept invader than the short-pod variety, and could become more prevalent in the future. © 2012 CSIRO.

Drought stress characterization of post-rainy season (rabi) sorghum in India

During the post-rainy (rabi) season in India around 3 million tonnes of sorghum grain is produced from 5.7 million ha of cropping. This underpins the livelihood of about 5 million households. Severe drought is common as the crop grown in these areas relies largely on soil moisture stored during the preceding rainy season. Improvement of rabi sorghum cultivars through breeding has been slow but could be accelerated if drought scenarios in the production regions were better understood. The sorghum crop model within the APSIM (Agricultural Production Systems sIMulator) platform was used to simulate crop growth and yield and the pattern of crop water status through each season using available historical weather data. The current model reproduced credibly the observed yield variation across the production region (R2=0.73). The simulated trajectories of drought stress through each crop season were clustered into five different drought stress patterns. A majority of trajectories indicated terminal drought (43%) with various timings of onset during the crop cycle. The most severe droughts (25% of seasons) were when stress began before flowering and resulted in failure of grain production in most cases, although biomass production was not affected so severely. The frequencies of drought stress types were analyzed for selected locations throughout the rabi tract and showed different zones had different predominating stress patterns. This knowledge can help better focus the search for adaptive traits and management practices to specific stress situations and thus accelerate improvement of rabi sorghum via targeted specific adaptation. The case study presented here is applicable to other sorghum growing environments. © 2012 Elsevier B.V.

Influence of dingoes on sheep distribution in Australia

Objective To describe the influence of the dingo (Canis lupus dingo) on the past, present and future distributions of sheep in Australia. Design The role of the dingo in the rise and fall of sheep numbers is reviewed, revised data are provided on the present distribution and density of sheep and dingoes, and historical patterns of sheep distribution are used to explore the future of rangeland sheep grazing. Results Dingoes are a critical causal factor in the distribution of sheep at the national, regional and local levels. Dingo predation contributed substantially to the historical contraction of the sheep industry to its present-day distribution, which is almost exclusively confined to areas within fenced dingo exclusion zones. Dingo populations and/or their influence are now present and increasing in all sheep production zones of Australia, inclusive of areas that were once dingo free'. Conclusions Rangeland production of wool and sheep meat is predicted to disappear within 30-40 years if the present rate of contraction of the industry continues unabated. Understanding the influence of dingoes on sheep production may help refine disease response strategies and help predict the future distribution of sheep and their diseases.

Stock assessment of the Queensland east coast common coral trout (Plectropomus leopardus) fishery

Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.

Overcoming barriers to the successful implementation of a classical biological control strategy for the exotic invasive weed Mikania micrantha in the Asia-Pacific region

Mikania micrantha (Asteraceae) commonly known as mikania, is a major invasive alien plant (IAP) in the tropical humid agricultural and forest zones of the Asia-Pacific region. This fast-growing Neotropical vine is able to smother plants in agricultural ecosystems, agroforestry and natural habitats, reducing productivity and biodiversity. Fungal pathogens were first investigated for the classical biological control of this weed in 1996. This resulted in the selection and screening of the highly host-specific and damaging rust pathogen, Puccinia spegazzinii (Pucciniales). It was first released in India and China in 2005/6, although it is not believed to have established. Since then, it has been released successfully in Taiwan, Papua New Guinea (PNG), Fiji and most recently Vanuatu. The rust has established and is spreading rapidly after applying lessons learned from the first releases on the best rust pathotype and release strategy. In PNG, direct monitoring of vegetation change has demonstrated that the rust is having a significant impact on M. micrantha, with no unpredicted non-target impacts. Despite this, the authorities in many countries where mikania is a problem remain cautious about releasing the rust. In Western Samoa, introduction of the rust was not pursued because of a conflict of interest, and the perception that mikania suppresses even worse weeds. For some, ‘pathophobia’ is still a major obstacle. In Indonesia, where insects for weed CBC have been introduced, pathogens will currently not be considered. In other countries such as Bhutan and Myanmar, there are no baseline data on the presence and impact of IAPs and, with no history of CBC, no institutional framework for implementing this approach. Malaysia has a well-developed framework, but capacity needs to be built in the country. Overall, it remains critical to have champions at decision making levels. Hence, even with an effective ‘off-the-shelf’ agent available, implementation of mikania CBC still requires significant inputs tailored to the countries’ specific needs.

Biological control of bellyache bush (Jatropha gossypiifolia) in Australia: South America as a possible source of natural enemies

Bellyache bush (Jatropha gossypiifolia, Euphorbiaceae), a deciduous shrub introduced as an ornamental from tropical America, is a major and expanding weed of rangelands and riparian zones in northern Australia. Biological control is the most economically viable and long-term management solution for this weed. Surveys for potential biological control agents for J gossypiifolia in Mexico,Central America and the Caribbean resulted in release of the seed-feeding jewel bug Agonosoma trilineatum (Hemiptera: Scutelleridae), which failed to establish, and prioritisation of a leaf-rust Phakopsora arthuriana (Puccineales: Phakopsoraceae) for host-specificity testing, which is ongoing. With poor prospects for new agents from Mexico and Central America and the Caribbean, the search for candidate agents on J gossypiifolia shifted to localities south of the equator. Surveys were conducted on the purple-leaf form of J gossypiifolia, Jatropha excisa, Jatropha clavuligera and Jatropha curcas in Peru, Bolivia and Paraguay in 2012 and 2013. A total of 11 insect species, one mite species and the leaf-rust (P. arthuriana) were observed. These include a yet to be described leafmining moth (Stomphastis sp.) (Lepidoptera: Gracillaridae), a shoot and leaf-galling midge Prodiplosis longifila, and leaf-feeding midge Prodiplosis sp. near longifila (both Diptera:Cecidomyiidae) and an unidentified leaf-feeding moth larva (Lepidoptera: Notodontidae). The leafminer is widespread and damaging and has a field host range restricted to the genus Jatropha in Peru and Bolivia, holds the greatest promise as a biological control agent in Australia. Phakopsora arthuriana was recorded for the first time ever from Bolivia and Peru. Further exploration will be conducted in Peru and Bolivia during the wet season to confirm the field host range of collected agents,and to look for more new agents. Promising agents with field host-range restricted to Jatropha spp. will be imported into a quarantine facility in Australia for host-specificity testing.

"Description of blue tongue and other arboviruses in Northern Australia"

A serological survey of cattle from throughout Queensland and sheep from cattle/sheep interface areas was conducted to determine the distribution and prevalence of antibodies to Bluetongue virus serotypes. This information allowed preliminary designation of arbovirusfree zones and identification of livestock populations at greatest risk to introduction of exotic Bluetongue viruses. Throughout the state antibodies were detected to only serotypes I and 21. In cattle prevalence decreased with increasing distance from the coast ringing from 73% in the far north to less than I% in the southwest. In sheep, prevalence of bluetongue antibodies in the major cattle/sheep interface areas in the north-west and central Queensland ranged from O% to 5%. A system of strategically placed sentinel herds of 10 young serologically negative cattle was established across northern Australia to monitor the distribution and seasonality of bluetongue viruses. Initially 23 herds were located in Queensland, 4 in Northern Territory and 2 in Western Australia but by the completion of the project the number of herds in Queensland had been reduced to 12. No bluetongue virus activity was detected in Western Australia or Northern Territory herds throughout the project although testing of one herd in Northern Territory with a history of bluetongue activity was not done after June 1991. In Queensland, activity to bluetongue serotypes I and 21 was detected in all years of the project. Transmissions occurred predominantly in the period April to September and were more widespread in wetter years' The pathogenic bluetongue setotypes previously isolated from the Northern Territory have not spread to adjoining States.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.