Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing

This paper describes the development of a model, based on Bayesian networks, to estimate the likelihood that sheep flocks are infested with lice at shearing and to assist farm managers or advisers to assess whether or not to apply a lousicide treatment. The risk of lice comes from three main sources: (i) lice may have been present at the previous shearing and not eradicated; (ii) lice may have been introduced with purchased sheep; and (iii) lice may have entered with strays. A Bayesian network is used to assess the probability of each of these events independently and combine them for an overall assessment. Rubbing is a common indicator of lice but there are other causes too. If rubbing has been observed, an additional Bayesian network is used to assess the probability that lice are the cause. The presence or absence of rubbing and its possible cause are combined with these networks to improve the overall risk assessment.

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

Specific detection of the Old World screwworm fly, Chrysomya bezziana, in bulk fly trap catches using real-time PCR.

The Old World screwworm fly (OWS), Chrysomya bezziana Villeneuve (Diptera: Calliphoridae), is a myiasis-causing blowfly of major concern for both animals and humans. Surveillance traps are used in several countries for early detection of incursions and to monitor control strategies. Examination of surveillance trap catches is time-consuming and is complicated by the presence of morphologically similar flies that are difficult to differentiate from Ch. bezziana, especially when the condition of specimens is poor. A molecular-based method to confirm or refute the presence of Ch. bezziana in trap catches would greatly simplify monitoring programmes. A species-specific real-time polymerase chain reaction (PCR) assay was designed to target the ribosomal DNA internal transcribed spacer 1 (rDNA ITS1) of Ch. bezziana. The assay uses both species-specific primers and an OWS-specific Taqman MGB probe. Specificity was confirmed against morphologically similar and related Chrysomya and Cochliomyia species. An optimal extraction protocol was developed to process trap catches of up to 1000 flies and the assay is sensitive enough to detect one Ch. bezziana in a sample of 1000 non-target species. Blind testing of 29 trap catches from Australia and Malaysia detected Ch. bezziana with 100% accuracy. The probability of detecting OWS in a trap catch of 50 000 flies when the OWS population prevalence is low (one in 1000 flies) is 63.6% for one extraction. For three extractions (3000 flies), the probability of detection increases to 95.5%. The real-time PCR assay, used in conjunction with morphology, will greatly increase screening capabilities in surveillance areas where OWS prevalence is low.

Optimizing sowing management for short duration dry seeded aman rice on the High Ganges River Floodplain of Bangladesh

Dry seeding of aman rice can facilitate timely crop establishment and early harvest and thus help to alleviate the monga (hunger) period in the High Ganges Flood Plain of Bangladesh. Dry seeding also offers many other potential benefits, including reduced cost of crop establishment and improved soil structure for crops grown in rotation with rice. However, the optimum time for seeding in areas where farmers have access to water for supplementary irrigation has not been determined. We hypothesized that earlier sowing is safer, and that increasing seed rate mitigates the adverse effects of significant rain after sowing on establishment and crop performance. To test these hypotheses, we analyzed long term rainfall data, and conducted field experiments on the effects of sowing date (target dates of 25 May, 10 June, 25 June, and 10 July) and seed rate (20, 40, and 60 kg ha−1) on crop establishment, growth, and yield of dry seeded Binadhan-7 (short duration, 110–120 d) during the 2012 and 2013 rainy seasons. Wet soil as a result of untimely rainfall usually prevented sowing on the last two target dates in both years, but not on the first two dates. Rainfall analysis also suggested a high probability of being able to dry seed in late May/early June, and a low probability of being able to dry seed in late June/early July. Delaying sowing from 25 May/10 June to late June/early July usually resulted in 20–25% lower plant density and lower uniformity of the plant stand as a result of rain shortly after sowing. Delaying sowing also reduced crop duration, and tillering or biomass production when using a low seed rate. For the late June/early July sowings, there was a strong positive relationship between plant density and yield, but this was not the case for earlier sowings. Thus, increasing seed rate compensated for the adverse effect of untimely rains after sowing on plant density and the shorter growth duration of the late sown crops. The results indicate that in this region, the optimum date for sowing dry seeded rice is late May to early June with a seed rate of 40 kg ha−1. Planting can be delayed to late June/early July with no yield loss using a seed rate of 60 kg ha−1, but in many years, the soil is simply too wet to be able to dry seed at this time due to rainfall.

Modelling Mortality and Reproduction Rates for Management of Sheep Flocks in Northern Australia

By quantifying the effects of climatic variability in the sheep grazing lands of north western and western Queensland, the key biological rates of mortality and reproduction can be predicted for sheep. These rates are essential components of a decision support package which can prove a useful management tool for producers, especially if they can easily obtain the necessary predictors. When the sub-models of the GRAZPLAN ruminant biology process model were re-parameterised from Queensland data along with an empirical equation predicting the probability of ewes mating added, the process model predicted the probability of pregnancy well (86% variation explained). Predicting mortality from GRAZPLAN was less successful but an empirical equation based on relative condition of the animal (a measure based on liveweight), pregnancy status and age explained 78% of the variation in mortalities. A crucial predictor in these models was liveweight which is not often recorded on producer properties. Empirical models based on climatic and pasture conditions estimated from the pasture production model GRASP, predicted marking and mortality rates for Mitchell grass (Astrebla sp.) pastures (81% and 63% of the variation explained). These prediction equations were tested against independent data from producer properties and the model successfully validated for Mitchell grass communities.

Modelling climatic risks of aflatoxin contamination in maize

Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM's maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.

Productivity and health effects of anaplasmosis and babesiosis on Bos indicus cattle and their crosses, and the effects of differing intensity of tick control in Australia

Tick fever is an important disease of cattle where Rhipicephalus (Boophilus) microplus acts as a vector for the three causal organisms Babesia bovis, Babesia bigemina and Anaplasma marginale. Bos indicus cattle and their crosses are more resistant to the clinical effects of infection with B. bovis and B. bigemina than are Bos taurus cattle. Resistance is not complete, however, and herds of B. indicus-cross cattle are still at risk of babesiosis in environments where exposure to B. bovis is light in most years but occasionally high. The susceptibility of B. indicus cattle and their crosses to infection with A. marginale is similar to that of B. taurus cattle. In herds of B. indicus cattle and their crosses the infection rate of Babesia spp. and A. marginale is lowered because fewer ticks are likely to attach per day due to reduced numbers of ticks in the field (long-term effect on population, arising from high host resistance) and because a smaller proportion of ticks that do develop to feed on infected cattle will in turn be infected (due to lower parasitaemia). As a consequence, herds of B. indicus cattle are less likely than herds of B. taurus cattle to have high levels of population immunity to babesiosis or anaplasmosis. The effects of acaricide application on the probability of clinical disease due to anaplasmosis and babesiosis are unpredictable and dependent on the prevalence of infection in ticks and in cattle at the time of application. Attempting to manipulate population immunity through the toleration of specific threshold numbers of ticks with the aim of controlling tick fever is not reliable and the justification for acaricide application should be for the control of ticks rather than for tick fever. Vaccination of B. indicus cattle and their crosses is advisable in all areas where ticks exist, although vaccination against B. bigemina is probably not essential in pure B. indicus animals.

Agonosoma trilineatum (Heteroptera: Scutelleridae) a biological control agent of the weed bellyache bush, Jatropha gossypiifolia (Euphorbiaceae)

Bellyache bush, Jatropha gossypiifolia L., is a serious weed of northern Australia. Agonosoma trilineatum (F.) is an insect from tropical America released in Australia in 2003 as a biological control agent against bellyache bush. It feeds on seeds and has the potential to reduce seed production, thereby potentially reducing the rate of spread and recruitment. To test the host specificity of A. trilineatum, four biological responses to host plant species were determined: development of nymphs, oviposition preferences, adult feeding and frequency of mating. Development of nymphs to adults and adult feeding only occurred on three Jatropha spp. These species also supported mating and oogenesis but only J. gossypiifolia was accepted for oviposition. Mating did not occur in the presence of other plant species. The evidence indicates that there is little risk associated with the release of this insect species in Australia and probably other countries where this weed is a problem. The probability of this insect expanding its host range is low because multiple aspects of the biology would need to change simultaneously. A. trilineatum was released in Australia between 2003 and 2007. A Climex model indicated that coastal areas of Queensland and the Northern Territory would be climatically most suitable for this insect.

Defining and predicting the 'break of the season' for north-east Queensland grazing areas

For pasture growth in the semi-arid tropics of north-east Australia, where up to 80% of annual rainfall occurs between December and March, the timing and distribution of rainfall events is often more important than the total amount. In particular, the timing of the 'green break of the season' (GBOS) at the end of the dry season, when new pasture growth becomes available as forage and a live-weight gain is measured in cattle, affects several important management decisions that prevent overgrazing and pasture degradation. Currently, beef producers in the region use a GBOS rule based on rainfall (e. g. 40mm of rain over three days by 1 December) to define the event and make their management decisions. A survey of 16 beef producers in north-east Queensland shows three quarters of respondents use a rainfall amount that occurs in only half or less than half of all years at their location. In addition, only half the producers expect the GBOS to occur within two weeks of the median date calculated by the CSIRO plant growth days model GRIM. This result suggests that in the producer rules, either the rainfall quantity or the period of time over which the rain is expected, is unrealistic. Despite only 37% of beef producers indicating that they use a southern oscillation index (SOI) forecast in their decisions, cross validated LEPS (linear error in probability space) analyses showed both the average 3 month July-September SOI and the 2 month August-September SOI have significant forecast skill in predicting the probability of both the amount of wet season rainfall and the timing of the GBOS. The communication and implementation of a rigorous and realistic definition of the GBOS, and the likely impacts of anthropogenic climate change on the region are discussed in the context of the sustainable management of northern Australian rangelands.

Cassowary dispersal of the invasive pond apple in a tropical rainforest: the contribution of subordinate dispersal modes in invasion.

Dispersal is a significant determinant of the pattern and process of invasions; however, weed dispersal distances are rarely described and descriptions of dispersal kernels are completely lacking for vertebrate-dispersed weeds. Here, we describe dispersal kernels generated by a native disperser, the endangered southern cassowary (Casuarius casuarius, L.) for an invasive, tropical rainforest plant, pond apple (Annona glabra, L.). Pond apple is primarily water-dispersed and is managed as such. We consider whether cassowary dispersal, as a numerically subordinate dispersal mode, provides an additional dispersal service that may modify the invasion process. In infested areas, pond apple seed was common in cassowary dung. Gut passage had no effect on the probability of single seed germination but deposition in clumps or as whole fruits reduced the probability of germination below that of single seeds. Gut passage times ranged from 65 to 1675 min. Combined with cassowary movement data, this resulted in estimated dispersal distances of 12.5-5212 m, with a median distance of 387 m (quartile range 112-787 m). Native frugivores can be effective dispersers of weeds in rainforest and even terrestrial dispersers can provide long-distance dispersal. Importantly, though pond apple might be expected to be almost entirely dispersed downstream and along the margins of aquatic and marine habitats, cassowaries provide dispersal upstream and between drainages, leading to novel dispersal outcomes. Even through the provision of small quantities of novel dispersal outcomes, subordinate dispersal modes can play a significant role in determining invasion pattern and influence the ultimate success of control programs by providing dispersal to locations unattainable via the primary mode.

Predicting risk and benefit a priori in biological control of invasive plant species: a systems modelling approach

While the method using specialist herbivores in managing invasive plants (classical biological control) is regarded as relatively safe and cost-effective in comparison to other methods of management, the rarity of strict monophagy among insect herbivores illustrates that, like any management option, biological control is not risk-free. The challenge for classical biological control is therefore to predict risks and benefits a priori. In this study we develop a simulation model that may aid in this process. We use this model to predict the risks and benefits of introducing the chrysomelid beetle Charidotis auroguttata to manage the invasive liana Macfadyena unguis-cati in Australia. Preliminary host-specificity testing of this herbivore indicated that there was limited feeding on a non-target plant, although the non-target was only able to sustain some transitions of the life cycle of the herbivore. The model includes herbivore, target and non-target life history and incorporates spillover dynamics of populations of this herbivore from the target to the non-target under a variety of scenarios. Data from studies of this herbivore in the native range and under quarantine were used to parameterize the model and predict the relative risks and benefits of this herbivore when the target and non-target plants co-occur. Key model outputs include population dynamics on target (apparent benefit) and non-target (apparent risk) and fitness consequences to the target (actual benefit) and non-target plant (actual risk) of herbivore damage. The model predicted that risk to the non-target became unacceptable (i.e. significant negative effects on fitness) when the ratio of target to non-target in a given patch ranged from 1:1 to 3:2. By comparing the current known distribution of the non-target and the predicted distribution of the target we were able to identify regions in Australia where the agent may be pose an unacceptable risk. By considering risk and benefit simultaneously, we highlight how such a simulation modelling approach can assist scientists and regulators in making more objective decisions a priori, on the value of releasing specialist herbivores as biological control agents.

A scientific approach to agent selection

The prioritisation of potential agents on the basis of likely efficacy is an important step in biological control because it can increase the probability of a successful biocontrol program, and reduce risks and costs. In this introductory paper we define success in biological control, review how agent selection has been approached historically, and outline the approach to agent selection that underpins the structure of this special issue on agent selection. Developing criteria by which to judge the success of a biocontrol agent (or program) provides the basis for agent selection decisions. Criteria will depend on the weed, on the ecological and management context in which that weed occurs, and on the negative impacts that biocontrol is seeking to redress. Predicting which potential agents are most likely to be successful poses enormous scientific challenges. 'Rules of thumb', 'scoring systems' and various conceptual and quantitative modelling approaches have been proposed to aid agent selection. However, most attempts have met with limited success due to the diversity and complexity of the systems in question. This special issue presents a series of papers that deconstruct the question of agent choice with the aim of progressively improving the success rate of biological control. Specifically they ask: (i) what potential agents are available and what should we know about them? (ii) what type, timing and degree of damage is required to achieve success? and (iii) which potential agent will reach the necessary density, at the right time, to exert the required damage in the target environment?

Towards Ecologically Sustainable Management of the Torres Strait Prawn Fishery. CRC Torres Strait Task T1.5 – Final Report

This publication, which is the final report to the Torres Strait Cooperative Research Centre, provides an overview of all the research that was conducted as part of the Torres Strait CRC Task 1.5 - Towards Ecologically Sustainable Management of the Torres Strait Prawn Fishery The objectives of the task were: To develop cost-effective protocols to monitor and quantify the bycatch and environmental impacts of commercial prawn trawling. To monitor the status of target species using both fishery dependent and fishery independent data. To develop biological reference points for target species and undertake management strategy evaluation, in particular a risk assessment of fishing at various levels of fishing mortality. This report focuses on the second component of objective 1 and details a comparative analysis of bycatch samples collected from areas of the Torres Strait that were both closed and open to prawn trawl fishing. The report also reviews the research conducted in relation to objectives 2 and 3 which are detailed in a separate report, Stock Assessment of the Torres Strait Tiger Prawn Fishery (Penaeus esculentus).

Modelling the distribution and relative abundance of feral camels in the Northern Territory using count data

The objectives of this study were to predict the potential distribution, relative abundance and probability of habitat use by feral camels in southern Northern Territory. Aerial survey data were used to model habitat association. The characteristics of ‘used’ (where camels were observed) v. ‘unused’ (pseudo-absence) sites were compared. Habitat association and abundance were modelled using generalised additive model (GAM) methods. The models predicted habitat suitability and the relative abundance of camels in southern Northern Territory. The habitat suitability maps derived in the present study indicate that camels have suitable habitat in most areas of southern Northern Territory. The index of abundance model identified areas of relatively high camel abundance. Identifying preferred habitats and areas of high abundance can help focus control efforts.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.