It's the people that have the great ideas and make the research happen! Some information about my past and present students, postdocs and research assistants can be found here, to give you an idea of the range of things we do.
*Note that there are still a few important people missing.
My name is Stan, I am from Perth W.A. and am a Ph.D. candidate at the school of plant biology, University of Western Australia. I am developing and researching methods for Australian forest management practices that will best conserve endemic species and eco-system services. I have a background in remote sensing, GIS analysis, and spatial statistics and have previous experience working with species distribution and habitat models as well as renewable energy implementation. During my time here I will assess the ecological, structural and hydrological indices of the South West Eucalypt forest using the latest satellite imagery and use this information to inform landscape management strategies. Additionally, I will be modelling the distribution and range shifts of the Forest Red-tailed Black-cockatoo as a response to a changing environment and how offsets may improve management strategies for this vulnerable species.
I am visiting Michael’s lab for 6 months (or maybe longer!). While here, I am supporting Katarina's project especially in case of programming and parameter estimation for her Functional-Structural Plant Model.After my studies of Biology I decided to specialise in modelling and programming, because I find it fascinating to transform nature into computer models and to be able to simulate complex relations. Therefore I started a master's programme of Forest Science and Forest Ecology in Germany, where I chose the specification Data Analysis and Modelling.
With Michael's and Katarina's help I am working here on two sub models.
One of it simulates the spread of spores of fungal diseases in wheat in a 3D environment. The other one estimates the most likely day when spores get released the first time in season. I work with GroImp and R and additionally mostly with Java and Python. I love doing sports and spend lots of my free time outdoors. I am interested in politics and mainly the world and I am very interested in the topics of the fourth industrial revolution.
I received my Diploma degree in Mathematics and Biology (teacher education), and my PhD in Applied Informatics (looking at new approaches to create virtual vegetation for park reconstructions and in the area of computer graphics), both from the Comenius University in Bratislava, Slovakia. Already during my PhD, and later as post-doc, I worked at the University of Göttingen, Germany and CentraleSupélec, France on model development and analysis in the area of functional-structural plant modelling. In 2017, I started my post-doc with Michael on a Grain Research & Development Corporation project on pathogen management modelling. Our main focus will be on developing a simulation model of progression of fungal diseases, e.g. yellow spot and septoria nodorum blotch, in wheat crop canopies. By coupling a functional-structural model of wheat with an epidemiological model of a fungal pathogen, we want to virtually explore various plant x pathogen x environment x management interactions and their effect on crop yield. The overall aim of our project is to help farmers predict disease risk and manage their crops based on weather conditions. The model will be tested for different locations and weather conditions across Western Australia.
I previously graduated from the University of Tasmania with a Bachelor of Science (Applied Mathematics and Zoology) and Honours in Marine Science. I am one year into my PhD within the Marine Ecology Group at the UWA Oceans Institute and the School of Biological Sciences, together with the CSIRO. My interest is in quantifying the resilience of coral reef communities and considering how acute climatic disturbances shape these complex ecosystems. I am determined to pursue a career that will allow me to help conserve and enhance our understandings of marine environments at a time of rapid global change. Currently, I am working with Michael to develop a functional structural model of different coral morphologies to investigate how the structure of coral reef systems may change in the future. We will test our model with data from Ningaloo Reef. I enjoy photography, surfing and diving.
I am interested in the dynamics of plant communities, i.e. how they change over time and how they achieve resilience. I also have a passion for understanding how plant form influences plant function. Most of my previous work in this area has involved looking into the role of leaf anatomy, morphology and hydraulic architecture in determining overall plant water use/ requirements. I have recently begun my PhD which is aimed at developing well-defined methods to quantify and predict plant community resilience based on patterns of structural and functional change throughout natural succession and assisted restoration. To accomplish this, I will compile and conduct analyses on a range of plant communities that have undergone census over several decades and that have experienced disturbance/ succession events during the census period. I will use these datasets to parameterize models derived from maximum entropy theory. This will inform whether energetic- or information-based emergent properties are stable through time, or whether systematic shifts occur in the chosen properties consistent with expectations following disturbance events. I will primarily focus on the Kwongan vegetation system, a highly diverse and resilient system that contains areas undergoing natural and assisted succession. Complementary to this analysis, I will also analyse datasets from numerous national and international, as well as datasets held privately by other researchers. Ultimately the results from these studies promise to significantly advance our understanding of resilience in natural communities. This will add to efforts to develop robust, definable measures of resilience that can be applied and compared across multiple systems to assist in the rehabilitation decision-making processes.
My research has been looking at the effect of crop rotation on temporal measures of soil mineral N under long-term no-tillage. I have a particular emphasis on the importance of the crop residue (which is retained under no-tillage each year) as both a source and sink of available N. By measuring annual crop growth, crop residue decomposition, and in-situ soil N mineralisation, I hope to provide greater insight into the cumulative effects of crop rotation on organic matter cycling and nitrogen mineralisation in long-term no-tillage systems. The outcomes from this study will increase the awareness of the role that crop residue plays in N cycling under no-tillage, and allow farmers and consultants to better value the role of crop residue when assessing the potential adoption of alternative tillage practices. This will lead to a more sustainable food production system in Western Australia and contribute on a global scale to feeding the growing world population in the long term.
In 2012 I completed a Bachelor of Science in Conservation & Wildlife Biology and was awarded most outstanding student completing a Science degree at Edith Cowan University. After completing a Bachelor of Science (Honours) in Botany at The University of Western Australia in 2013 I was offered and accepted a PhD candidature which is allowing the pursuit of my passion for community ecology through research. My research addresses community assembly using plant functional traits, which inform about challenges facing rehabilitation of Kwongan shrublands. I will test the hypothesis that habitat heterogeneity determines and modifies biotic interactions, and drives functional trait variability at multiple scales. The project aims at enhancing the theory of trait response to ecological gradients and its influence on the assembly processes with knowledge to be applied to assist rehabilitation.
I have been looking at describing temporal vegetation patterns from a functional trait perspective rather than from a floristic viewpoint, in the hope that a greater insight into understanding ecological function in the restoration of land after mining can be achieved. The basis of my research has been two datasets of floristic data for areas subject to different restoration practices and fire regimes. I have been making comparisons between floristic and functional trait patterns derived from these datasets as well as to post-disturbance recovery patterns from the literature. The collection of plant functional traits for species within the databases will also contribute towards the creation of the first comprehensive functional trait database in Western Australia.
My PhD project is investigating the effects of dredging on marine sponges, sedentary filter feeding animals. I am focusing on species common to Northwest Australia where there is a lot of dredging occurring. I have been conducting aquarium-based experiments that look at various dredging-related stressors in isolation. These stressors include high levels of suspended solids, light attenuation and sediment deposition. I have been developing and optimizing three methodologies for identifying and quantifying stress responses in sponges. These methods comprise: 1) micro computed tomography (Micro CT) scanning to visualize sponge tissue and potential sediment clogging; 2) a microthermistor flowmeter to determine changes in sponge pumping (i.e. filtering) rates; and 3) transcriptome sequencing (RNA-seq) to determine what changes in gene expression are associated with dredging-related stress. I will then combine these methods in an experiment to test the effects of all three dredging-related stressors. It is hypothesized that dredging-related pressures will affect feeding structures, pumping rates, and gene expression of different test species to varying degrees under different conditions. My PhD project forms part of the Western Australian Marine Science Institution’s (WAMSI) interdisciplinary Dredging Science Node. I have focused on the effects of dredging on sponges because sponges are very ecologically important. They ameliorate water quality, form substrates, and foster bentho-pelagic coupling in carbon and nitrogen cycles. Furthermore, Northwest Australia contains many sponge biodiversity hotspots. Understanding lethal thresholds and stress responses in sponges will help managers and stakeholders set guidelines for dredging operations in the future.
The goal of my project is to develop a forecasting model for Pea seed-borne mosaic virus (PSbMV) epidemics in field pea crops. This model would be used to inform a Decision Support System (DSS) for growers and advisors to enable effective integrated disease management in a Mediterranean-type environment. To do this we need to achieve a greater understanding of the driving factors behind PSbMV epidemiology. I have been busy collecting numerous pea samples and PSbMV isolates from the field and have presented some of my work at the 2015 Australasian Plant Virology Workshop in Fremantle and at the Australasian Plant Pathology Student Symposium, where I was awarded ‘Best Presentation’. Further work for the year includes completing the forecasting model and extend it to growers through SMS delivery with Blackspot forecasts, as well as access to recommendations on control measures and further information. Upon completion, we aim to organise focus groups in field pea growing areas to promote use of the DSS and explain its outputs. Application and acceptance of the DSS is crucially important in improving PSbMV management as currently there is little awareness of its proliferation into most commercial seed-lots and its impact on yield and seed quality.
I am currently doing my first post doc after having recently competed my PhD. The project that I primarily work on aims to develop general methods for designing and evaluating statistically-based surveillance systems for high priority horticulture threats, focusing specifically on three case studies including two arthropod pests, grape phylloxera (Daktulosphaira vitifoliae Fitch) and Mediterranean fruit fly (Ceratitis capitate; Medfly) and one nematode pest, potato cyst nematode (Globodera rostochiensis; PCN). One challenge we face in all of our case studies is how to use the available resources in the best way to maximise the chance of detecting a new biosecurity threat as quickly as possible. This is particularly important as our methods are also relevant to surveillance to help prove area-freedom or for monitoring. Our research Methods for each organism integrate outputs from dynamic models simulating dispersal and spread of the organism in realistic landscapes, with systems that represent both static and dynamic surveillance systems, thus obtaining statistically-validated evaluation of the ability of surveillance strategies to meet detection goals.
I get to do some interstate travel and fieldwork for my job, which involves testing the efficacy of the number and location of traps or samples, and the frequency with which they are conducted or checked. The methods employed in this project will be applicable to evaluating both existing and new surveillance technologies for a range of industries and organisms. Our recommendations will be provided to government regulators, property owners and horticulture managers to guide their surveillance efforts, improve time to detection and/or reduce costs, and thus restrict the spread of our case studies as efficiently as possible.
I’m doing my PhD with Michael, using simulation modelling in weed populations to help understand, predict and manage the evolution of herbicide resistance. The vast majority of herbicide resistance modelling studies have not been spatially-explicit, and thus implicitly assumed that weed populations are spatially-homogenous with fully random mating. However, in reality weed populations are usually very spatially heterogeneous and structured in terms of density (i.e. patchy), genetics and mating. My project aims to investigate whether more realistic spatially-explicit modelling leads to different predictions, novel management recommendations, and new insights. Along with others from Michael’s research group, I have participated in and presented at a focussed workshop on modelling resistance evolution at Rothamsted Research UK, and the Mathematical Modelling in Ecology and Evolution conference in Paris. I have also presented a paper on some of my results at the MODSIM 2015 conference, Gold Coast, and have had a paper published in the proceedings.
Not so current:
I completed my undergraduate at the University of Western Australia in Conservation and Land Management with Honours and was fortunate enough to have Michael as lecturer during some of my undergraduate courses. When I was deciding on an Honours project he was willing to work with me to put together a project modelling bat activity against climatic variables. The project focused on correlating White-Stripe Free-Tail bat activity, measured as call frequency using ultrasonic recording devices, with climatic data obtained from a weather station at the same site. White-Stripe Free-Tail bat's are somewhat unique in Australia as they are migratory, and along with some recent research that had revealed some unique physical features potentially related to thermoregulation, we hypothesised that there was a temperature threshold to their activity - further research was required after the project though to completely understand the potential relationships between the bat's behaviour and climate. After my undergraduate I completed a Masters in Applied Statistics at Macquarie University. My Master's thesis was supervised by Dr David Bulger and explored sexual selection in female Australian brush-turkeys and the implications for findings based on different missing-data imputation and variable reduction techniques. During my Masters I also moved to the US and worked for about a year consulting mostly PhD students in statistics for their dissertations. Currently, I work in program evaluation for a US nutrition and cooking non-profit based in Austin, Texas. Nationally we provide programming to 70,000 students and conduct outcome and process evaluations internally and in collaboration with external groups. I really enjoy the new challenges working with people as subjects has had, but I hope to one day go back to working in the environmental space, and maybe even thinking about a PhD!
I have finished my post doc with Michael. I looked at phoma stem canker (Blackleg) a fungal disease that effects Canola (oilseed rape). This disease is of major economic importance, causing yield losses of between 5% and 20% of production in some places, and even up to 100% in exceptional situations. Control strategies rely on fungicides, deep tillage of the crop residues, use of resistant cultivars, and crop management (specific sowing period, crop rotations). However, rotation or stacking of resistance genes can potentially cause a super-virulent strain to arise because pathogens with a lot of virulence genes are likely to be selected. Strategies to maximize durability of resistance genes in cultivars should therefore both limit the selection of the more virulent variants of the pathogen and reduce pathogen population sizes. Results so far have highlighted the importance of using cultivar rotation strategies while pathogen virulence gene frequencies are still low. Models used in previous work did not represent spatial variability in terms of cultivars grown. In effect, this meant it represented an isolated homogenous area (a field, set of fields, or landscape), and ignored the possibility of spatial heterogeneity within the area, or interactions with other fields outside the area. My work therefore, will extend this model in a spatially explicit manner (taking care of distances between fields) at a regional scale to investigate how different rotation strategies, degrees of co-ordination across a landscape, and levels of use of non-host crops influence evolutionary dynamics, population levels and the selection of super-virulent strains at the regional scale, and how this may be influenced by initial levels of pathogen, different proportions and different locations between the strains. This model is still under development, and will be used in the future for estimation purposes.
I completed my Honours on 'redefining flammability' (paper in progress) at Curtin University, Western Australia, but decided to jump ship and move to The University of Western Australia for my PhD. What initially drew me to UWA and this project was the work Michael Renton had been doing in ecological modelling. As we had not touched on modelling in my undergraduate degree, this concept was rather new and exciting to me thanks to my background in computers, programming and a love for statistics. After teaming up with Erik Veneklaas and Pieter Poot, we managed to develop a PhD which not only incorporated some ecological modelling but three of myother interests as well: plant traits, ecophysiology and angiosperm taxonomy.The overall objective of my PhD research was to assess the long-term vulnerability of Eucalypt species’ in the south-west of Western Australia to a changing climate. This was achieved through a combination of field work (to quantify how Eucalypts are using changes to morphological and physiological traits to survive drought), a glasshouse study (measuring juvenile root architecture to see if roots are adapted to soil and climate conditions) and species distribution modelling (to visualise areas at risk of health decline, and areas of potential refuge).
I now work for The University of Western Australia as a data analyst in the Office of Strategy, Planning and Performance.
My PhD focused on the ecology, tolerances, and habitat requirements of ephemeral plants inhabiting small freshwater rock pools in the remote North Kimberley. My work was the first time these tiny but incredibly unique habitats have been studied, and I worked with Michael to model their hydrology under different rainfall scenarios. Our data showed these often small and rather nondescript plants were actually exquisitely tuned to the unpredictable seasonal conditions of the monsoonal north, produce one of the largest seed banks in the known universe, and in terms of ecological resilience could be placed in the category of 'hard as nails'. We've since continued to work on these rock pool ecosystems, examining their equally unique invertebrate and microbial communities, and each study continues to highlight their biodiversity value further.
The focus of my PhD was the sandalwood tree and looking at ways to improve its marketability through improved trees selection and silviculture strategies. I looked specifically at enhancing our knowledge of heartwood oil composition and yield variation, as well as the genetic diversity of natural populations, with the ultimate aim of elucidating the oil biosynthetic pathway and developing genetic markers for the assistance in the selection of germplasm, so as to further understand the physiological factors involved in essential oil biosynthesis. My results can be applied to the development of genetic markers to assist in selection programs and improved management of current genetic resources. These selection programs will also reduce the pressure off natural populations and ensure a sustainable supply of sandalwood in the future.
For my PhD I examined a 19 year-old, post-mining Banksia woodland restoration chronosequence so as to further our current understanding of how ecosystems develop in restored sites. I looked at this in terms of three major ecosystem attributes; 1) plant community composition (species richness and abundance); 2) ecosystem function, and; 3) vegetation structure. The development of plant community composition through time, and the effects thereon of environmental drivers (rainfall regimes during the establishment phase, site aspect, slope) and management intervention techniques (substrate ripping and properties of reconstruction materials) were assessed in terms of four commonly employed restoration criteria; species richness, plant density, vegetation cover, and similarity to reference sites. I found that irrespective of environmental drivers or management intervention techniques, vegetation cover increased through time, while plant density and species richness declined. I also found that the compositional similarity to reference communities remained relatively unchanged. Within the confines of these trends, rainfall and ripping treatments interacted to significantly affect restoration criteria; species richness and plant density were greatest when rainfall in the first winter immediately following site restoration was low, and then followed by a high summer rainfall. From my research I determined that the most effective ripping depth was dependent on rainfall, with deep-ripped sites performing best when rainfall was high, and shallow ripped sites performing best under low-mean rainfall conditions.
Originally a pure Mathematics student from the big state of Texas in the USA, I came to Western Australia to get a Masters degree that pushed my Mathematics into the ecological realm. I worked with Michael, Richard Hobbs, and Michael Perring on the challenging topic of native invasion. Human-induced changes in environmental conditions can sometimes cause higher establishment and survivorship or increased per-capita impact by native species. This presents a unique management question in that the solution is rarely direct population control, but more likely management of the environmental change to restore the population to prior levels.I worked on the native invasive Allocasuarina huegeliana in the heath of the Western Australian wheatbelt. My study was guided by previous work and management concerns that the invasion, thought to be caused by shifting fire regimes, is decreasing heathland diversity. I quantified the strength of the relationships
between the invasion, shifted fire regimes, and biodiversity through observational study of A. huegeliana densities, time since last fire, and species loss. I then used simulation modelling to examine the effect of fire and other management tactics on A. huegeliana population spread. I created a spatially-explicit stochastic model parameterized using empirical field data and found that fire-based management is potentially a viable control method, though current return intervals are inadequate. I also got to check out amateur pole-dancing and test my mountain climbing abilities in far-north Queensland.
My research focusesd on the use of spatially explicit models to simulate dispersal processes and invasive spread. I like to develop simple, general models that have a wide applicability and can be used to study more theoretical ecological concepts as well as practical problems. In my PhD, I looked at wind-assisted dispersal of fungal pathogen spores. In my postdoc, I worked on models to simulate the wind-assisted dispersal of Conyza cadiensis (fleabane) and on a general model of biological invasion, which can be used to rapidly assess how exotic pests will most likely spread over a given landscape. I am interested in the computational issues associated with model development and simulation studies, and esoteric programming languages that nobody uses. But I've learned my lesson about shooters in backpacker bars after MODSIM conference dinners.
The aim of my PhD was to use individual-based two-locus simulation modelling to predict population dynamics and the evolution of resistance to phosphine (PH3) fumigation in the lesser grain borer, Rhyzopertha dominica, and thus significantly contribute to evaluating resistance management strategy options. Individual-based modelling is a cutting-edge approach that explicitly represents the fact that R. dominica populations consist of individual beetles, each of a particular genotype and a particular life stage. In my Phd, I developed new numerical algorithms for generating or estimating key parameters within individual-based models, particularly for estimating mortality of different genotypes at different doses and durations of fumigation. By comparing the differences between the predictions of one- and two-locus individual-based models, I showed the importance of basing resistance evolution models on realistic genetics and that using over-simplified one-locus models to develop pest control strategies runs the risk of not correctly identifying tactics to minimise the incidence of pest infestation. Further results from the more realistic model indicate that extending exposure duration is a much more efficient control tactic than increasing the phosphine concentration. Finally, I used the individual-based two-locus model to investigate the impact of two important issues; the consistency of pesticide dosage through the storage facility; and the immigration rate of the adult pest, on overall population control and avoidance of evolution of resistance to phosphine in lesser grain borer. The results indicate that achieving a consistent fumigant dosage is a key factor in avoiding evolution of resistance to phosphine and maintaining control of populations of stored grain pests.
While isolated in the desert from my two true loves - my partner and surfing - I needed a project to keep me from excessive navel-gazing. My MSc project investigated seasonal changes in growth of the seagrass Halophila stipulacea in the highly stressful marine environment of the Western Arabian Gulf, where water temperature ranges from 10 degrees in winter to 37 degrees in summer and salinity is always higher than 40 rsu. These stressful conditions result in seasonal cycles of net growth and dieback, with net growth in spring and summer followed by net dieback in autumn and winter. I collected detailed information about how the seagrass grew so that I could use this information with a computer simulated growth model, which Michael developed using R. The model predicted the rate of seagrass growth and dieback, which helps to predict the outcomes of seagrass transplantation projects. The transplantation of seagrass has become the default method of mitigating against the environmental impacts of coastal developments in Qatar. It has been fascinating to watch the seasonal cycles unfold in the Gulf. The populations of macro-algae, pesky blue swimmer crabs, some fish and (to an extent) seagrass, all wax and wane with the seasons.
I worked as a programmer for Michael Renton. The projects I worked on included models of the evolution of herbicide/pesticide resistance and the Weed Seed Wizard, a decision support tool that uses paddock management information to predict weed emergence and crop yield. My job involved helping with the development of models, developing user-friendly interfaces for models, and verifying models. I also flew around the country helping to run workshops. More info on the Weed Seed Wizard can be found here: http://grains.agric.wa.gov.au/weed-seed-wizard
For my honours I examined the role that habitus, an individual’s or group’s dispositions, has played in the retention of traditional ecological knowledge among the Noongar people of south-western Australia. With my supervisors, I sought to determine if current plant knowledge reflects Noongar habitus or, alternatively, the use of fall-back species that were important due to the intermittency of agricultural employment and the social exclusion of Aboriginal people up until at least the 1960s in Western Australia. I compared the seasonal availability of Noongar food plant resources currently known by Noongar Elders to those described at the time of European settlement, and used non-metric Multidimensional Scaling (nMDS) and multivariate statistics to compare the seasonal availability of plant resources with the seasonal availability of work prior to the introduction of civil rights for Aboriginal Australians in the 1960s. I showed that the seasonal pattern of plant knowledge has changed little since settlement and that there was no significant relationship between the seasonal availability of work and plant knowledge. This result suggests that prior to 1960 Noongars maintained a reasonably traditional round of seasonal activities involving traditional plant use, and that Noongar habitus guided their response to the colonising culture and helped preserve traditional ecological knowledge.
I am an agronomist. I like to study the agronomy and physiology of plants, and more importantly incorporate the temporal dynamics of those characteristics to look at how plants grow in a resource limited environment in a quantitative manner. Therefore, I selected to do my PhD on ‘estimating the growth of Cullen australasicum under moisture and phosphorus limited growth conditions in Western Australasian landscapes’. I developed a mechanistic model to simulate the growth of C. australasicum in R software. My project period was from 2008-2011. After completing the PhD studies, I am back at the University of Peradeniya, Sri Lanka and working as a lecturer in Agronomy and Crop Modelling.
As part of its climate change policy the Australian government introduced a Carbon Pollution Reduction Scheme in 2010. After 2015 it is possible that agriculture may also be covered by this scheme. In my Honours project I examined how different broadacre farming systems in the south-west of Australia may be affected by the policy settings of this scheme. Using the bio-economic farming systems model MIDAS (Model of an Integrated Dryland Agricultural System), I investigated the impacts of the Carbon Pollution Reduction Scheme on the profitability of different farming systems that characterise the region. My results showed a range of profit and enterprise impacts across the various farm types. In a scenario where agriculture is not covered by the scheme, reductions in profit are significant, and farmers reduce their use of expensive energy inputs such as chemicals and fertilisers. I found that in a covered scenario profit reductions are even greater and results indicate that a combination of reducing livestock numbers, introducing permanent wood plantations on marginal lands and other changes to the farm enterprise mixes are the key components of the least-cost strategy for reducing emissions. What’s more, I got to go on a great trip to Toowoomba to learn about APSIM with Lalith, Padmaja and Michael! Since finishing my Honours, I’ve spent a bit of time helping Michael with his Land Use Sequence Optimiser (LUSO) and a few other things, but mostly just enjoyed myself.
I did my PhD studying the impact of low rates of herbicides on the evolution of herbicide resistance in annual ryegrass. My study included a combination of experimental studies and simulation modelling. I showed that low herbicide rates can potentially increase the speed at which weed populations increase or evolve to be more resistant, but it depends on the underlying genetics. We published four papers from the thesis, so it was quite a productive association! After finishing my PhD at UWA, I now work as a postdoc in UWA in greenhouse gas emission and its mitigation. Besides simulation of herbicide resistance evolution, I share with Michael an interest in books on Yoga, Buddha, Krishna, Jesus and interpretations on Quran that inculcate a feeling to see good in everything rather than confinement.
My PhD work developed new procedures for developing simple statistical models for accurately predicting agricultural production or yield, such as for crops, fruits, or pastures, based on relatively simple inputs. These were based on creating simple statistical models or emulators utilising extensive data obtained from an existing comprehensive mechanistic simulation model of agricultural production. The biomass production of the perennial pasture species lucerne (Medicago sativa) was used as a case study in developing and testing the emulators, while the simulation model used was APSIM (the Agricultural Production Systems sIMulator). My studies showed that simple emulator models can be constructed to predict agricultural production or yield, based on relatively simple inputs, with a degree of accuracy similar to that of the mechanistic model on which they are based. These emulators can be extended relatively easily to predict in new locations, environments, or for new species, and their accuracy can be improved by incorporating new data as it becomes available. Because they provide quick and accurate estimates of productivity under a range of different conditions, these emulators can be efficiently incorporated into more complex farming systems models, thus providing researchers, plant breeders and farmers with an invaluable tool for assessing the potential role of the species within the overall system. Because they don’t require extensive empirical data, they can be used to assess the potential role of new species, cultivars or management approaches in new soils, climatic conditions or farming systems, and thus have the potential to be an invaluable asset in the agricultural industry.
I worked with Michael as a postdoc. Australia faces a significant challenge in order to minimise the entry, establishment and spread of harmful plant pests and diseases which could affect agriculture production, market access and our environment. A plant pest or disease outbreak could have serious economic and environmental impact. To protect Australia from a potentially devastating pests and diseases a tool to predict how they were established, how far they spread and the speed at which they spread is required. During my time at UWA, I worked on a system to rapidly characterise new invading organisms and thus provide timely information about the pest’s biology and spread potential, as well as guide the appropriate response in the event of an incursion. I now work at RMIT in Canberra on space-age stuff - it's damn cold here compared to Perth, but at least it's closer to the home of VB.
In my Honours thesis, entitled “Unearthing the economic value of crop sequencing for soil-borne disease management in the case study region of Wickepin, Western Australia”, I used the bio-economic modelling and optimisation framework LUSO (Land Use Sequence Optimiser) to investigate the economic value of crop sequencing for the management of soil-borne disease in a farming system. Wheat is the most common crop grown in Western Australia. The familiarity and profitability of wheat often influences farmer’s decisions to grow continuous wheat. However, many yield-limiting factors take effect with consecutive crops of like species. Soil-borne diseases such as take-all (Gaeumannomyces graminis var. tritici), crown and root rot (Fusarium pseudograminearum and Pythium spp.), bare patch (Rhizoctonia solani) and root lesion nematodes (particularly Pratylenchus neglectus, thornei and teres) damage the roots and, crowns, thereby inhibiting plant growth and limiting cereal crop yield. In the absence of a suitable host the disease life-cycle can be interrupted and yield losses reduced. The challenge comes from determining the ideal crop sequences given the choices available, and that’s where LUSO came in! In my study LUSO demonstrated its potential as a tool for evaluating a comprehensive combination of scenarios used to unearth the economic value of crop sequencing for soil-borne disease management. I also got to spend some quality and enlightening time with my CSIRO co-supervisor Roger on trips out to the wheat-belt trial sites.
Weeds competing with crops and pastures for sunlight, water and nutrients are a major constraint to agricultural production, costing farmers billions of dollars each year in lost production and management costs. Therefore, for my Honours project I investigated use of karrikinolide, a germination stimulant isolated from smoke. The idea is to stimulate weed seed germination so more of the weed population is available for control and consequently there are less seeds remaining in the seed bank within the soil. With the declining effectiveness of some herbicides, there is an increasing need for alternative weed control strategies. Understanding the dormancy release characteristics of weed species is essential for predicting when applying karrikinolide to cropping paddocks would be most beneficial, as it can't force dormant deep seeds to germinate. Wild radish, wild oat and wild turnip successfully germinated when seed was exposed to karrikinolide, but the challenge will be translating this to broad acre field conditions.
In my Honours, I looked at biserrula (Biserrula pelecinus L.), a recently domesticated annual pasture legume developed for ley farming systems that have traditionally relied upon subterranean clover (Trifolium subterraneum L.). My study examined competitive interactions between biserrula and subterranean clover and the common broad-leaf weed capeweed (Arctotheca calendula L.) during seedling establishment and vegetative growth, in order to develop guidelines for successful legume pasture management. Two glasshouse experiments were conducted to investigate the allocation of biomass to roots and shoots in biserrula, capeweed, and subterranean clover and its relationship with competitive ability in the first 100 days after sowing. In Experiment 1, capeweed had a higher relative growth rate of shoots and roots than the two legumes and developed a more extensive root system. Experiment 2 consisted of growing binary mixtures of the three species at different densities. The effect of competition on the biomass of biserrula, capeweed, and subterranean clover was best modelled by a power–exponential model. Increasing capeweed densities suppressed the biomass production of both biserrula and subterranean clover, whereas capeweed biomass increased with increasing densities of subterranean clover. This study suggests that the competitive advantage of capeweed is mainly conferred during the seedling stage. It also suggests that biserrula and subterranean clover germinating at the same time can co-exist as a mixed sward, at least up until flowering, if biserrula density is high relative to subterranean clover. During my Honours, I also learned that soils ain’t soils... but survived to publish a paper nonetheless.
Rhizoctonia bare-patch is a soil-borne root disease of cereals in southern and western Australian wheat-belts that costs the region up to $100 million per annum. The pathogen responsible, R. solani (AG-8) interacts with the host and the environment to express disease. Environmental factors such as soil moisture, organic matter and available mineral N affect the expression of the disease via a number of relationships. In my Honours project, I ran glasshouse experiments with my CSIRO co-supervisor Roger to assess the effect of differing rainfall frequencies and stubble management practices on R. solani inoculum levels in the soil and resulting disease expression in the plants. I found that disease severity, plant height and dry matter were all affected. This supports previous results that an increase in soil moisture leads to an increase in soil microbial activity which places competitive pressure on the pathogen thus minimising its virulence. ‘Soil suppression’ is seen to be the key driver in this experiment and developing natural soil suppression in affected regions could potentially be the key. Hopefully the results from my project, once refined by future research, can be used in the bio-economic LUSO framework to better enable it to predict and account for disease risk.
Grain producers, particularly in marginal rainfall areas, tend to sow as early as possible to extend the growing season and therefore maximise yield potential. However, this often means seed is sown into soil that has limited moisture or is dry, which is often associated with uneven emergence and poor establishment. Soil moisture and temperature are the predominant factors affecting how long the crop will take to emerge, the spread of emergence, and how long the crop can survive before the next rainfall event. Initial seedling vigour and good early establishment are vital for the healthy development and competitiveness required of a grain crop. Growth before flowering sets the potential yield and number of grains that fill from dry matter produced after flowering. Planting dry results in a simultaneous crop and weed emergence when the rains start, limiting the weed management options of farmers and increasing the reliance on selective herbicides. Therefore, in my Honours project I looked at crops such as wheat (Triticum aestivum L.) canola (Brassica napus) and narrow- leafed lupin (Lupinus angustifolius L.) respond to moisture stress conditions during germination and early growth. My results will assist producers in making decisions concerning seeding time and in understanding how these decisions may affect their weed management strategies in the future.
Effective weed management is a key agronomic practice determining agricultural success. My resource economics project assessed how tactical ungrazed pasture, or ley phases in intensive crop only farms, could address declining soil fertility and increasing levels of herbicide resistance in WA's wheatbelt. Depressed livestock prices, ongoing rural labour scarcity and elevated cereal prices mean that intensive cereal production and crop only farming systems are becoming increasingly common features of WA's grainbelt. A complex simulation model assessed alternative integrated weed management strategies, using tactical ungrazed pasture phases and showed that tactical use of a single year, ungrazed pasture phase was more profitable than using break crops in intensive cereal production systems. And in contrast to previous analyses and general practice, I found alternating short periods of cropping and pasture is more profitable than extended crop and pasture phases. Flexible land use sequences had a 10 per cent economic premium compared to fixed land rotations. And as the supply of effective selective herbicides becomes more limited, using ungrazed pasture fallows to opportunistically control weeds and improve soil fertility will become increasingly profitable.