A review of the biology, ecology, distribution and control of Mozambique tilapia, Oreochromis mossambicus (Peters 1852) (Pisces: Cichlidae) with particular emphasis on invasive Australian populations

Oreochromis mossambicus (Peters 1852) are native to the eastward flowing rivers of central and southern Africa but from the early 1930s they have been widely distributed around the world for aquaculture and for biological control of weeds and insects. While O. mossambicus are now not commonly used as an aquaculture species, the biological traits that made them a popular culture species including tolerance to wide ranging ecological conditions, generalist dietary requirements and rapid reproduction with maternal care have also made them a 'model' invader. Self-sustaining populations now exist in almost every region to which they have been imported. In Australia, since their introduction in the 1970s, O. mossambicus have become established in catchments along the east and west coasts and have the potential to colonise other adjacent drainages. It is thought that intentional translocations are likely to be the most significant factor in their spread in Australia. The ecological and physical tolerances and preferences, reproductive behaviour, hybridization and the high degree of plasticity in the life history traits of O. mossambicus are reviewed. Impacts of O. mossambicus on natural ecosystems including competitive displacement of native species, habitat alteration, predation and as a vector in the spread of diseases are discussed. Potential methods for eradicating or controlling invasive populations of O. mossambicus including physical removal, piscicides, screens, environmental management and genetic technologies are outlined.

The Distribution of Henipaviruses in Southeast Asia and Australasia: Is Wallace's Line a Barrier to Nipah Virus?

Nipah virus (NiV) (Genus Henipavirus) is a recently emerged zoonotic virus that causes severe disease in humans and has been found in bats of the genus Pteropus. Whilst NiV has not been detected in Australia, evidence for NiV-infection has been found in pteropid bats in some of Australia's closest neighbours. The aim of this study was to determine the occurrence of henipaviruses in fruit bat (Family Pteropodidae) populations to the north of Australia. In particular we tested the hypothesis that Nipah virus is restricted to west of Wallace's Line. Fruit bats from Australia, Papua New Guinea, East Timor and Indonesia were tested for the presence of antibodies to Hendra virus (HeV) and Nipah virus, and tested for the presence of HeV, NiV or henipavirus RNA by PCR. Evidence was found for the presence of Nipah virus in both Pteropus vampyrus and Rousettus amplexicaudatus populations from East Timor. Serology and PCR also suggested the presence of a henipavirus that was neither HeV nor NiV in Pteropus alecto and Acerodon celebensis. The results demonstrate the presence of NiV in the fruit bat populations on the eastern side of Wallace's Line and within 500 km of Australia. They indicate the presence of non-NiV, non-HeV henipaviruses in fruit bat populations of Sulawesi and Sumba and possibly in Papua New Guinea. It appears that NiV is present where P. vampyrus occurs, such as in the fruit bat populations of Timor, but where this bat species is absent other henipaviruses may be present, as on Sulawesi and Sumba. Evidence was obtained for the presence henipaviruses in the non-Pteropid species R. amplexicaudatus and in A. celebensis. The findings of this work fill some gaps in knowledge in geographical and species distribution of henipaviruses in Australasia which will contribute to planning of risk management and surveillance activities.

Potential Distribution and Risk Assessment of an Invasive Plant Species: A Case Study of Hymenachne amplexicaulis in Australia

Given the limited resources available for weed management, a strategic approach is required to give the best bang for your buck. The current study incorporates: (1) a model ensemble approach to identify areas of uncertainty and commonality regarding a species invasive potential, (2) current distribution of the invaded species, and (3) connectivity of systems to identify target regions and focus efforts for more effective management. Uncertainty in the prediction of suitable habitat for H. amplexicaulis (study species) in Australia was addressed in an ensemble-forecasting approach to compare distributional scenarios from four models (CLIMATCH; CLIMEX; boosted regression trees [BRT]; maximum entropy [Maxent]). Models were built using subsets of occurrence and environmental data. Catchment risk was determined through incorporating habitat suitability, the current abundance and distribution of H. amplexicaulis, and catchment connectivity. Our results indicate geographic differences between predictions of different approaches. Despite these differences a number of catchments in northern, central, and southern Australia were identified as high risk of invasion or further spread by all models suggesting they should be given priority for the management of H. amplexicaulis. The study also highlighted the utility of ensemble approaches in indentifying areas of uncertainty and commonality regarding the species invasive potential.

Determining changes in the distribution and abundance of a Rhyzopertha dominica phosphine resistance allele in farm grain storages using a DNA marker

BACKGROUND: The lesser grain borer, Rhyzopertha dominica (F.), is a highly destructive pest of stored grain that is strongly resistant to the fumigant phosphine (PH3). Phosphine resistance is due to genetic variants at the rph2 locus that alter the function of the dihydrolipoamide dehydrogenase (DLD) gene. This discovery now enables direct detection of resistance variants at the rph2 locus in field populations. RESULTS: A genotype assay was developed for direct detection of changes in distribution and frequency of a phosphine resistance allele in field populations of R. dominica. Beetles were collected from ten farms in south-east Queensland in 2006 and resampled in 2011. Resistance allele frequency increased in the period from 2006 to 2011 on organic farms with no history of phosphine use, implying that migration of phosphine-resistant R. dominica had occurred from nearby storages. CONCLUSION: Increasing resistance allele frequencies on organic farms suggest local movement of beetles and dispersal of insects from areas where phosphine has been used. This research also highlighted for the first time the utility of a genetic DNA marker in accurate and rapid determination of the distribution of phosphine-resistant insects in the grain value chain. Extending this research over larger landscapes would help in identifying resistance problems and enable timely pest management decisions. © 2013 Society of Chemical Industry © 2013 Society of Chemical Industry 69 6 June 2013 10.1002/ps.3514 Rapid Report Rapid Report © 2013 Society of Chemical Industry.

Strong resistance to phosphine in the rusty grain beetle, Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae): its characterisation, a rapid assay for diagnosis and its distribution in Australia

BACKGROUND: The recent development of very high resistance to phosphine in rusty grain beetle, Cryptolestes ferrugineus (Stephens), seriously threatens stored-grain biosecurity. The aim was to characterise this resistance, to develop a rapid bioassay for its diagnosis to support pest management and to document the distribution of resistance in Australia in 20072011. RESULTS: Bioassays of purified laboratory reference strains and field-collected samples revealed three phenotypes: susceptible, weakly resistant and strongly resistant. With resistance factors of > 1000 x , resistance to phosphine expressed by the strong resistance phenotype was higher than reported for any stored-product insect species. The new time-to-knockdown assay rapidly and accurately diagnosed each resistance phenotype within 6 h. Although less frequent in western Australia, weak resistance was detected throughout all grain production regions. Strong resistance occurred predominantly in central storages in eastern Australia. CONCLUSION: Resistance to phosphine in the rusty grain beetle is expressed through two identifiable phenotypes: weak and strong. Strong resistance requires urgent changes to current fumigation dosages. The development of a rapid assay for diagnosis of resistance enables the provision of same-day advice to expedite resistance management decisions. (c) 2012 Commonwealth of Australia. Published by John Wiley & Sons, Ltd.

Biology and Management of Psocids Infesting Stored Products

Previously regarded as minor nuisance pests, psocids belonging to the genus Liposcelis now pose a major problem for the effective protection of stored products worldwide. Here we examine the apparent biological and operational reasons behind this phenomenon and why conventional pest management seems to be failing. We investigate what is known about the biology, behavior, and population dynamics of major pest species to ascertain their strengths, and perhaps find weaknesses, as a basis for a rational pest management strategy. We outline the contribution of molecular techniques to clarifying species identification and understanding genetic diversity. We discuss progress in sampling and trapping and our comprehension of spatial distribution of these pests as a foundation for developing management strategies. The effectiveness of various chemical treatments and the availability and potential of nonchemical control methods are critically examined. Finally, we identify research gaps and suggest future directions for research.

Predictive modelling to aid the regional-scale management of a vertebrate pest

Extensive resources are allocated to managing vertebrate pests, yet spatial understanding of pest threats, and how they respond to management, is limited at the regional scale where much decision-making is undertaken. We provide regional-scale spatial models and management guidance for European rabbits (Oryctolagus cuniculus) in a 260,791 km(2) region in Australia by determining habitat suitability, habitat susceptibility and the effects of the primary rabbit management options (barrier fence, shooting and baiting and warren ripping) or changing predation or disease control levels. A participatory modelling approach was used to develop a Bayesian network which captured the main drivers of suitability and spread, which in turn was linked spatially to develop high resolution risk maps. Policy-makers, rabbit managers and technical experts were responsible for defining the questions the model needed to address, and for subsequently developing and parameterising the model. Habitat suitability was determined by conditions required for warren-building and by above-ground requirements, such as food and harbour, and habitat susceptibility by the distance from current distributions, habitat suitability, and the costs of traversing habitats of different quality. At least one-third of the region had a high probability of being highly suitable (support high rabbit densities), with the model supported by validation. Habitat susceptibility was largely restricted by the current known rabbit distribution. Warren ripping was the most effective control option as warrens were considered essential for rabbit persistence. The anticipated increase in disease resistance was predicted to increase the probability of moderately suitable habitat becoming highly suitable, but not increase the at-risk area. We demonstrate that it is possible to build spatial models to guide regional-level management of vertebrate pests which use the best available knowledge and capture fine spatial-scale processes.

Early recovery signs of an Australian grassland following the management of Parthenium hysterophorus L

Parthenium weed (Parthenium hysterophorus L.) is believed to reduce the above- and below-ground plant species diversity and the above-ground productivity in several ecosystems. We quantified the impact of this invasive weed upon species diversity in an Australian grassland and assessed the resulting shifts in plant community composition following management using two traditional approaches. A baseline plant community survey, prior to management, showed that the above-ground community was dominated by P. hysterophorus, stoloniferous grasses, with a further high frequency of species from Malvaceae, Chenopodiaceae and Amaranthaceae. In heavily invaded areas, P. hysterophorus abundance and biomass was found to negatively correlate with species diversity and native species abundance. Digitaria didactyla Willd. was present in high abundance when P. hysterophorus was not, with these two species, contributing most to the dissimilarity seen between areas. The application of selective broad leaf weed herbicides significantly reduced P. hysterophorus biomass under ungrazed conditions, but this management did not yet result in an increase in species diversity. In the above-ground community, P. hysterophorus was partly replaced by the introduced grass species Cynodon dactylon L. (Pers.) 1 year after management began, increasing the above-ground forage biomass production, while D. didactyla replaced P. hysterophorus in the below-ground community. This improvement in forage availability continued to strengthen over the time of the study resulting in a total increase of 80% after 2 years in the ungrazed treatment, demonstrating the stress that grazing was imposing upon this grassland-based agro-ecosystem and showing that it is necessary to remove grazing to obtain the best results from the chemical management approach.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

Effects of trawling on sessile megabenthos in the Great Barrier Reef and evaluation of the efficacy of management strategies

A series of related research studies over 15 years assessed the effects of prawn trawling on sessile megabenthos in the Great Barrier Reef, to support management for sustainable use in the World Heritage Area. These large-scale studies estimated impacts on benthos (particularly removal rates per trawl pass), monitored subsequent recovery rates, measured natural dynamics of tagged megabenthos, mapped the regional distribution of seabed habitats and benthic species, and integrated these results in a dynamic modelling framework together with spatio-temporal fishery effort data and simulated management. Typical impact rates were between 5 and 25% per trawl, recovery times ranged from several years to several decades, and most sessile megabenthos were naturally distributed in areas where little or no trawling occurred and so had low exposure to trawling. The model simulated trawl impact and recovery on the mapped species distributions, and estimated the regional scale cumulative changes due to trawling as a time series of status for megabenthos species. The regional status of these taxa at time of greatest depletion ranged from ∼77% relative to pre-trawl abundance for the worst case species, having slow recovery with moderate exposure to trawling, to ∼97% for the least affected taxon. The model also evaluated the expected outcomes for sessile megabenthos in response to major management interventions implemented between 1999 and 2006, including closures, effort reductions, and protected areas. As a result of these interventions, all taxa were predicted to recover (by 2-14% at 2025); the most affected species having relatively greater recovery. Effort reductions made the biggest positive contributions to benthos status for all taxa, with closures making smaller contributions for some taxa. The results demonstrated that management actions have arrested and reversed previous unsustainable trends for all taxa assessed, and have led to a prawn trawl fishery with improved environmental sustainability. © 2015 International Council for the Exploration of the Sea 2015. All rights reserved. For Permissions, please email: journals.permissions@oup.com.