Tania Yonow

Potential impact of climate change on plant diseases of economic significance to Australia

Burning of fossil fuel, large scale clearing of forests and other human activities have changed global climate. Atmospheric concentration of radiatively active CO2, methane, nitrous oxide and chlorofluorocarbons has increased to cause global warming. In Australia temperature is projected to rise between 1 and 3°C by 2100. This review is the result of a recent workshop on the potential impact of climate change on plant diseases of economic significance to Australia. It gives an overview of projected changes in Australian climate and the current state of knowledge on the effect of climate change on plant diseases. Based on an assessment of important diseases of wheat and other cereals, sugarcane, deciduous fruits, grapevine, vegetables and forestry species, climate change in Australia may reduce, increase or have no effect on some diseases. Impacts will be felt in altered geographical distribution and crop loss due to changes in the physiology of host-pathogen interaction. Changes will occur in the type, amount and relative importance of pathogens and diseases. Host resistance may be overcome more rapidly due to accelerated pathogen evolution from increased fecundity at high CO2, and/or enhanced UV-B radiation. However, uncertainties about climate change predictions and the paucity of knowledge limit our ability to predict potential impacts on plant diseases. Both experimental and modelling approaches are available for impact assessment research. As the development and implementation of mitigation strategies take a long time, more research is urgently needed and we hope this review will stimulate interest.

Modelling the population dynamics of the Queensland fruit fly, Bactrocera (Dacus) tryoni: a cohort-based approach incorporating the effects of weather

Queensland fruit fly, Bactrocera (Dacus) tryoni (QFF) is arguably the most costly horticultural insect pest in Australia. Despite this, no model is available to describe its population dynamics and aid in its management. This paper describes a cohort-based model of the population dynamics of the Queensland fruit fly. The model is primarily driven by weather variables, and so can be used at any location where appropriate meteorological data are available. In the model, the life cycle is divided into a number of discreet stages to allow physiological processes to be defined as accurately as possible. Eggs develop and hatch into larvae, which develop into pupae, which emerge as either teneral females or males. Both females and males can enter reproductive and over-wintering life stages, and there is a trapped male life stage to allow model predictions to be compared with trap catch data. All development rates are temperature-dependent. Daily mortality rates are temperature-dependent, but may also be influenced by moisture, density of larvae in fruit, fruit suitability, and age. Eggs, larvae and pupae all have constant establishment mortalities, causing a defined proportion of individuals to die upon entering that life stage. Transfer from one immature stage to the next is based on physiological age. In the adult life stages, transfer between stages may require additional and/or alternative functions. Maximum fecundity is 1400 eggs per female per day, and maximum daily oviposition rate is 80 eggs/female per day. The actual number of eggs laid by a female on any given day is restricted by temperature, density of larva in fruit, suitability of fruit for oviposition, and female activity. Activity of reproductive females and males, which affects reproduction and trapping, decreases with rainfall. Trapping of reproductive males is determined by activity, temperature and the proportion of males in the active population. Limitations of the model are discussed. Despite these, the model provides a useful agreement with trap catch data, and allows key areas for future research to be identified. These critical gaps in the current state of knowledge exist despite over 50 years of research on this key pest. By explicitly attempting to model the population dynamics of this pest we have clearly identified the research areas that must be addressed before progress can be made in developing the model into an operational tool for the management of Queensland fruit fly

Research investment implications of shifts in the global geography of wheat stripe rust

Breeding new crop varieties with resistance to the biotic stresses that undermine crop yields is tantamount to increasing the amount and quality of biological capital in agriculture. However, the success of genes that confer resistance to pests induces a co-evolutionary response that depreciates the biological capital embodied in the crop, as pests evolve the capacity to overcome the crops new defences. Thus, simply maintaining this biological capital, and the beneficial production and economic outcomes it bestows, requires continual reinvestment in new crop defences. Here we use observed and modelled data on stripe rust occurrence to gauge changes in the geographic spread of the disease over recent decades. We document a significant increase in the spread of stripe rust since 1960, with 88% of the worlds wheat production now susceptible to infection. Using a probabilistic Monte Carlo simulation model we estimate that 5.47 million tonnes of wheat are lost to the pathogen each year, equivalent to a loss of US

The epidemiology of heartwater: Establishment and maintenance of endemic stability

979 million per year. Comparing the cost of developing stripe-rust-resistant varieties of wheat with the cost of stripe-rust-induced yield losses, we estimate that a sustained annual research investment of at least US

The potential global distribution of Chilo partellus, including consideration of irrigation and cropping patterns

32 million into stripe rust resistance is economically justified.

The life-cycle of Amblyomma variegatum (Acari: Ixodidae): a literature synthesis with a view to modelling

Although heartwater (Cowdria ruminantium infection) is one of the most economically important tick-borne diseases of sub-Saharan Africa, its epidemiology hes remained poorly understood until recently. New data, suggesting that heartwater is present in an endemically stable state in much of sub-Saharan Africa and demonstrating vertical transmission of Cowdria ruminantium in the field, have altered previously accepted views on heartwater epidemiology. In this paper, Sharon Deem and colleagues present an overview of the epidemiology of heartwater based on recent studies, discuss the factors that make endemic stability possible, make recommendations for future directions in research, and provide a foundation for the development of epidemiological models.

Misconstrued risks from citrus black spot in colder climates: a response to Er et al. 2013

Chilo partellus is a major crop pest in Asia and Africa, and has recently spread to the Mediterranean region. Knowledge of its potential distribution can inform biosecurity policies aimed at limiting its further spread and efforts to reduce its impact in areas that are already invaded. Three models of the potential distribution of this insect have been published, each with significant shortcomings. We re-parameterized an existing CLIMEX model to address some parameter inconsistencies and to improve the fit to the known distribution of C. partellus. The resulting model fits the known distribution better than previous models, highlights additional risks in equatorial regions and reduces modelled risks in wet and extremely dry regions. We bring new insights into the role of irrigation in the potential spread of this invasive insect and compare its potential distribution with the present known distribution of its hosts. We also distinguish regions that are suitable for supporting persistent populations from those that may be at risk from ephemeral populations during favourable seasons. We present one of the first demonstrations of a new capability in CLIMEX to automatically estimate parameter sensitivity and model uncertainty. Our CLIMEX model highlights the substantial invasion risk posed by C. partellus to cropping regions in the Americas, Australia, China, Europe, New Zealand and West Africa. Its broad host range and reported impacts suggest that it should be a pest of significant concern to biosecurity agencies in these presently uninvaded regions.

The potential distribution of cassava mealybug (Phenacoccus manihoti), a threat to food security for the poor

All available information on the life-cycle of Amblyomma variegatum is collated. Data for each parameter are analysed to derive mathematical descriptions, which may now be used to construct a model of the life-cycle of this tick. Areas for future research are identified. These include the collection of data for most parameters around threshold conditions to clarify discrepancies reported in the literature and to better quantify the relationships described, examination of the effects of photoperiod and host type on various parameters, and assessment of feeding success of each instar on natural hosts.

Scientific critique of the paper “Climatic distribution of citrus black spot caused by Phyllosticta citricarpa. A historical analysis of disease spread in South Africa” by Martínez-Minaya et al. (2015)

Species niche models play an important role in pest risk assessments, providing estimates of areas of suitability for establishment, persistence and impact, and sometimes the likely costs of biological invasions (FAO 2006). As has been demonstrated in the case of CBS, important and valuable phytosanitary decisions affecting international trade can hinge on pest risk assessments and their underlying niche models tend to come under close scrutiny. In 2005, Paul et al. published a CLIMEX model of CBS. CBS is present in South Africa, which exports citrus to Europe. Because European authorities are keen to protect European citrus trees from perceived invasion threats from these imported citrus products, the European Food Safety Agency critiqued the CBS model of Paul et al. (2005) (EFSA 2008). In response to EFSA (2008), and to better inform the assessment of the threat posed to European citrus production from CBS associated with imports of South African citrus fruits, Yonow et al. (2013) revised the CLIMEXmodel developed by Paul et al. (2005), taking into account more extensive distribution records, using arguably improved modelling methods, and using an improved climatological dataset (Kriticos et al. 2012). The Er et al. (2013) modelling is based on the pathogen parameters defined by Paul et al. (2005). We are unsure why Er et al. (2013) used the outdated Paul et al. (2005) parameters to represent “summer” risks. The Yonow et al. (2013) model indicates a more conservative potential distribution, a reduced tolerance of cold conditions, and accords with the known global distribution of CBS more closely than the model of Paul et al. (2005). Where the Paul et al. (2005) model was criticised for being too liberal, the parameter adjustments introduced by Er et al. (2013) extend the modelled potential distribution even further outside the known distribution than that projected by Paul et al. (2005). To further understand the modelling problems with the Er et al. (2013) paper, it is necessary to briefly review how the CLIMEX model works. The CLIMEX Compare Locations model (Sutherst and Maywald 1985, Sutherst et al. 2007) calculates an annual index of climatic suitability, the Ecoclimatic Index (EI), which reflects the overall potential for population persistence, accounting for growth during favourable periods and survival during stressful periods (Equation 1). The annual Growth Index (GIA) describes the potential for growth of the modelled taxa as a function of average weekly soil moisture (Moisture Index; MI) and temperature (Temperature Index; TI) (Equation 2; Weekly Growth Index, GIW = TI x MI). Stress indices describing cold stress (CS), wet stress (WS), heat stress (HS) and dry stress (DS) and their interactions can be used to describe the species response to climatically unfavourable conditions. The individual components Eur J Plant Pathol (2014) 139:231–236 DOI 10.1007/s10658-014-0427-4

Considering biology when inferring range-limiting stress mechanisms for agricultural pests: a case study of the beet armyworm

The cassava mealybug is a clear and present threat to the food security and livelihoods of some of the worlds most impoverished citizens. Niche models, such as CLIMEX, are useful tools to indicate where and when such threats may extend, and can assist with planning for biosecurity and the management of pest invasions. They can also contribute to bioeconomic analyses that underpin the allocation of resources to alleviate poverty. Because species can invade and establish in areas with climates that are different from those that are found in their native range, it is essential to define robust range-limiting mechanisms in niche models. To avoid spurious results when applied to novel climates, it is necessary to employ cross-validation techniques spanning different knowledge domains (e.g., distribution data, experimental results, phenological observations). We build upon and update a CLIMEX niche model by Parsa et al. (PloS ONE 7: e47675), correcting inconsistent parameters and re-fitting it based on a careful examination of geographical distribution data and relevant literature. Further, we consider the role of irrigation, the known distribution of cassava production and a targeted review of satellite imagery to refine, validate and interpret our model and results. In so doing, we bring new insights into the potential spread of this invasive insect, enabling us to identify potential bio-security threats and biological control opportunities. The fit of the revised model is improved, particularly in relation to the wet and dry limits to establishment, and the parameter values are biologically plausible and accord with published scientific literature.