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Projected climate changes are thought to promote emerging infectious diseases, though to date, evidence linking climate changes and such diseases in plants has not been available. Cassava is perhaps the most important crop in Africa for smallholder farmers. Since the late 1990’s there have been reports from East and Central Africa of pandemics of begomoviruses in cassava linked to high abundances of whitefly species within the Bemisia tabaci complex. We used CLIMEX, a process-oriented climatic niche model, to explore if this pandemic was linked to recent historical climatic changes. The climatic niche model was corroborated with independent observed field abundance of B. tabaci in Uganda over a 13-year time-series, and with the probability of occurrence of B. tabaci over 2 years across the African study area. Throughout a 39-year climate time-series spanning the period during which the pandemics emerged, the modelled climatic conditions for B. tabaci improved significantly in the areas where the pandemics had been reported and were constant or decreased elsewhere. This is the first reported case where observed historical climate changes have been attributed to the increase in abundance of an insect pest, contributing to a crop disease pandemic.

Aedes aegypti (Linnaeus) was once highly prevalent across eastern Australia, resulting in epidemics of dengue fever. Drought conditions have led to a rapid rise in semi-permanent, urban water storage containers called rainwater tanks known to be critical larval habitat for the species. The presence of these larval habitats has increased the risk of establishment of highly urbanised, invasive mosquito vectors such as Ae. aegypti. Here we use a spatially explicit network model to examine the role that unsealed rainwater tanks may play in population connectivity of an Ae. aegypti invasion in suburbs of Brisbane, a major Australian city. We characterise movement between rainwater tanks as a diffusion-like process, limited by a maximum distance of movement, average life expectancy, and a probability that Ae. aegypti will cross wide open spaces such as roads. The simulation model was run against a number of scenarios that examined population spread through the rainwater tank network based on non-compliance rates of tanks (unsealed or sealed) and road grids. We show that Ae. aegypti tank infestation and population spread was greatest in areas of high tank density and road lengths were shortest e.g. cul-de-sacs. Rainwater tank non-compliance rates of over 30% show increased connectivity when compared to less than 10%, suggesting rainwater tanks non-compliance should be maintained under this level to minimize the spread of an invading Ae. aegypti population. These results presented as risk maps of Ae. aegypti spread across Brisbane, can assist health and government authorities on where to optimally target rainwater tank surveillance and educational activities.

This article reviews and analyzes the literature on Yellow dwarf viruses (YDVs) in Australia, examining the range of environmental and climatic factors that explain the observed geographical distribution of the virus and its vectors. BYDV-PAV, vectored mainly by the aphid Rhopalosiphum padi , is the most prevalent YDV species in wheat and grasslands across all states, except Queensland. BYDV-RMV, vectored mainly by Rhopalosiphum maidis , dominates in Queensland grasslands, with very low incidence in wheat. Queensland experiences higher rainfall and warmer temperatures than southern Australia. Across Australia disease incidence in wheat is generally low (around 10 %) and varies from year to year, with the highest incidence found on occasion in Western Australia (up to 52 %) and the lowest in Queensland (<1 %). Across Australia there is a much higher virus incidence and more variation in YDV species present in grasslands than in wheat, although in general BYDV-PAV still dominates. An overview of the differences between the YDV species in terms of symptoms, impacts, frequency, transmission rates and geographical distribution is necessary to appreciate the implications of virus spread across Australia, as well as the risks from the interaction of YDV with more recently introduced wheat pathogens. This overview is set in the context of a changing climate, with a discussion of the possible implications of anthropogenic climate change for future epidemics. For example, increasing temperatures in the future may result in more rapid transmission of the virus in the cooler months than at present, with implications for winter crops such as wheat, where YDV currently does most damage. Also, there is potential for the spread of BYDV-RMV further south, as changes in climatic conditions alter both the transmission potential of the virus as well as the vectoring potential by the aphids R. padi and R. maidis . Finally, critical knowledge gaps are identified, highlighting a need for ongoing seasonal monitoring of the virus and vectors to support the use of simulation models to predict the incidence of YDVs in near real-time.

In this article we review a variety of methods to enable understanding and modelling the spread of a pest or pathogen post-entry. Building upon our experience of multidisciplinary research in this area, we propose practical guidelines and a framework for model development, to help with the application of mathematical modelling in the field of invasion ecology for post-entry spread. We evaluate the pros and cons of a range of methods, including references to examples of the methods in practice. We also show how issues of data deficiency and uncertainty can be addressed. The aim is to provide guidance to the reader on the most suitable elements to include in a model of post-entry dispersal in a risk assessment, under differing circumstances. We identify both the strengths and weaknesses of different methods and their application as part of a holistic, multidisciplinary approach to biosecurity research.

In the Australian subtropics, flying-foxes (family Pteropididae) play a fundamental ecological role as forest pollinators. Flying-foxes are also reservoirs of the fatal zoonosis, Hendra virus. Understanding flying fox foraging ecology, particularly in agricultural areas during winter, is critical to determine their role in transmitting Hendra virus to horses and humans. We developed a spatiotemporal model of flying-fox foraging intensity based on foraging patterns of 37 grey-headed flying-foxes ( Pteropus poliocephalus ) using GPS tracking devices and boosted regression trees. We validated the model with independent population counts and summarized temporal patterns in terms of spatial resource concentration. We found that spatial resource concentration was highest in late-summer and lowest in winter, with lowest values in winter 2011, the same year an unprecedented cluster of spillover events occurred in Queensland and New South Wales. Spatial resource concentration was positively correlated with El Niño Southern Oscillation at 3–8 month time lags. Based on shared foraging traits with the primary reservoir of Hendra virus ( Pteropus alecto ), we used our results to develop hypotheses on how regional climatic history, eucalypt phenology, and foraging behaviour may contribute to the predominance of winter spillovers, and how these phenomena connote foraging habitat conservation as a public health intervention.

Despite the known benefits of integrated pest management, adoption in Australian broadacre crops has been slow, in part due to the lack of understanding about how pests and natural enemies interact. We use a previously developed process-based model to predict seasonal patterns in the population dynamics of a canola pest, the green peach aphid (Myzus persicae), and an associated common primary parasitic wasp (Diaeretiella rapae), found in this cropping landscape. The model predicted aphid population outbreaks in autumn and spring. Diaeretiella rapae was able to suppress these outbreaks, but only in scenarios with a sufficiently high number of female wasps in the field (a simulated aphid:wasp density ratio of at least 5:1 was required). Model simulations of aphid-specific foliar pesticide applications facilitated biological control. However, a broad-spectrum pesticide negated the control provided by D. rapae, in one case leading to a predicted 15% increase in aphid densities compared to simulations in which no pesticide was applied. Biological and chemical control could therefore be used in combination for the successful management of the aphid while conserving the wasp. This modelling framework provides a versatile tool for further exploring how chemical applications can impact pests and candidate species for biological control.