Hazel Parry

Connecting scales: achieving in-field pest control from areawide and landscape ecology studies.

Areawide management has a long history of achieving solutions that target pests, however, there has been little focus on the areawide management of arthropod natural enemies. Landscape ecology studies that show a positive relationship between natural enemy abundance and habitat diversity demonstrate landscape‐dependent pest suppression, but have not yet clearly linked their findings to pest management or to the suite of pests associated with crops that require control. Instead the focus has often been on model systems of single pest species and their natural enemies. We suggest that management actions to capture pest control from natural enemies may be forth coming if: (i) the suite of response and predictor variables focus on pest complexes and specific management actions; (ii) the contribution of “the landscape” is identified by assessing the timing and numbers of natural enemies immigrating and emigrating to and from the target crop, as well as pests; and (iii) pest control thresholds aligned with crop development stages are the benchmark to measure impact of natural enemies on pests, in turn allowing for comparison between study regions, and generalizations. To achieve pest control we will need to incorporate what has been learned from an ecological understanding of model pest and natural enemy systems and integrate areawide landscape management with in‐field pest management.

Large Scale Agent-Based Modelling: A Review and Guidelines for Model Scaling

This chapter provides a review and examples of approaches to model scaling when constructing large agent-based models. A comparison is made between an aggregate ‘super-individual’ approach, as run on a single processor machine, and two different approaches to parallelisation of agent models run on multi-core hardware. Super-individuals provide a straightforward solution without much alteration of the model formulation and result in large improvements in model efficiency (speed and memory use). However, there are significant challenges to using a super-individual approach when relating super-individuals to individuals in time and space. Parallel computing approaches accept the requirement for large amounts of memory or CPU and attempt to solve the problem by distributing the calculation over many computational units. This requires some modification of the model software and algorithms to distribute the model components across multiple computational cores. This can be achieved in a number of different ways, two of which we illustrate further for the case of spatial models, an ‘agent-parallel’ and an ‘environment-parallel’ approach. However, the success of such approaches may also be affected by the complexity of the model (such as multiple agent types and agent interactions), as we illustrate by adding a predator to our example simulation. Between these two parallelisation approaches to the case study, the environment-parallel version of the model, written in C++ instead of Java, proved more efficient and successful at handling parallel processing of complex agent interactions. In conclusion, we use our experiences of creating large agent-based simulations to provide some general guidelines for best practice in agent-based model scaling.

A perspective on management of Helicoverpa armigera: transgenic Bt cotton, IPM, and landscapes

Helicoverpa armigera is a major pest of agriculture, horticulture and floriculture throughout the Old World and recently invaded parts of the New World. We overview of the evolution in thinking about the application of area-wide approaches to assist with its control by the Australian Cotton Industry to highlight important lessons and future challenges to achieving the same in the New World. An over-reliance of broad-spectrum insecticides led to Helicoverpa spp. in Australian cotton rapidly became resistant to DDT, synthetic pyrethroids, organophosphates, carbamates and endosulfan. Voluntary strategies were developed to slow the development of insecticide resistance, which included rotating chemistries and basing spray decisions on thresholds. Despite adoption of these practices, insecticide resistance continued to develop until the introduction of genetically modified cotton provided a platform for augmenting Integrated Pest Management in the Australian cotton industry. Compliance with mandatory resistance management plans for Bt cotton necessitated a shift from pest control at the level of individual fields or farms towards a coordinated area-wide landscape approach. Our take-home message for control of H. armigera is that resistance management is essential in genetically modified crops and must be season long and area-wide to be effective.

Monarchs in decline: A collateral landscape level effect of modern agriculture.

We review the postulated threatening processes that may have affected the decline in the eastern population of the monarch butterfly, Danaus plexippus L. (Lepidoptera: Nymphalidae), in North America. Although there are likely multiple contributing factors, such as climate and resource‐related effects on breeding, migrating, and overwintering populations, the key landscape‐level change appears to be associated with the widespread use of genetically modified herbicide resistant crops that have rapidly come to dominate the extensive core summer breeding range. We dismiss misinterpretations of the apparent lack of population change in summer adult count data as logically flawed. Glyphosate‐tolerant soybean and maize have enabled the extensive use of this herbicide, generating widespread losses of milkweed (Asclepias spp.), the only host plants for monarch larvae. Modeling studies that simulate lifetime realized fecundity at a landscape scale, direct counts of milkweeds, and extensive citizen science data across the breeding range suggest that a herbicide‐induced, landscape‐level reduction in milkweed has precipitated the decline in monarchs. A recovery will likely require a monumental effort for the re‐establishment of milkweed resources at a commensurate landscape scale.

Optimal Lévy-flight foraging in a finite landscape

We present a simple model to study Lévy-flight foraging with a power-law step-size distribution in a finite landscape with countable targets. We find that different optimal foraging strategies characterized by a wide range of power-law exponent μopt, from ballistic motion (μopt → 1) to Lévy flight (1 < μopt < 3) to Brownian motion (μopt ≥ 3), may arise in adaptation to the interplay between the termination of foraging, which is regulated by the number of foraging steps, and the environmental context of the landscape, namely the landscape size and number of targets. We further demonstrate that stochastic returning can be another significant factor that affects the foraging efficiency and optimality of foraging strategy. Our study provides a new perspective on Lévy-flight foraging, opens new avenues for investigating the interaction between foraging dynamics and the environment and offers a realistic framework for analysing animal movement patterns from empirical data.

Cereal aphid movement: general principles and simulation modelling

Cereal aphids continue to be an important agricultural pest, with complex lifecycle and dispersal behaviours. Spatially-explicit models that are able to simulate flight initiation, movement direction, distance and timing of arrival of key aphid species can be highly valuable to area-wide pest management programmes. Here I present an overview of how knowledge about cereal aphid flight and migration can be utilized by mechanistic simulation models. This article identifies specific gaps in knowledge for researchers who may wish to further scientific understanding of aphid flight behaviour, whilst at the same time provides a synopsis of the knowledge requirements for a mechanistic approach applicable to the simulation of a wide range of insect species.Although they are one of the most comprehensively studied insect groups in entomology, it is only recently that our understanding of cereal aphid flight and migration has been translated effectively into spatially-explicit simulation models. There are now a multitude of examples available in the literature for modelling methods that address each of the four phases of the aerial transportation process (uplift, transport in the atmosphere, initial distribution, and subsequent movement). I believe it should now be possible to draw together this knowledgebase and the range of modelling methods available to simulate the entire process: integrating mechanistic simulations that estimate the initiation of migration events, with the large scale migration modelling of cereal aphids and their subsequent local movement.

Temporal change in vegetation productivity in grain production landscapes: linking landscape complexity with pest and natural enemy communities

1. Strategies to enhance the ecosystem service of pest control in agricultural landscapes often rely on manipulating the structure of the landscape to reduce pest population build‐up or facilitate natural enemy activity. For highly mobile and polyphagous invertebrate pest species the agricultural landscape represents a continually changing mosaic of resources and habitats that at certain points in time may be conducive to high population productivity and therefore pest outbreaks. Deciding which features of the landscape we need to measure and monitor to understand this process is the first step in developing intervention strategies. Previous studies have focused on static measures of landscape composition and have generally ignored landscape configuration and change across time.

The geographical distribution of Yellow dwarf viruses and their aphid vectors in Australian grasslands and wheat

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.

Pigeon pea refuge crops are likely to provide patchy delivery of Helicoverpa (Lepidoptera: Noctuidae) within Bt cotton production regions in eastern Australia

Refuge crops, in particular pigeon pea and conventional (non‐Bt) cotton, are mandatory components within the Bt resistance management strategy for Helicoverpa pests in Bt cotton production systems in eastern Australia. These refuge crops are expected to produce large numbers of Bt‐susceptible moths, some of which will mate with the relatively few resistant moths emerging from Bt cotton, thus reducing the likelihood of Bt resistance developing. The spatial and temporal variability in Helicoverpa production in pigeon pea refuge crops within the St George Irrigation Area in southern Queensland was measured in this study, and the likely dispersal of moths produced in such refuges to Bt cotton crops throughout the local landscape was modelled. The attractiveness of pigeon pea for Helicoverpa oviposition and the resultant abundance of eggs on plants and pupae in the soil were highly variable between refuge crops within and between seasons. A simulation model was developed to explore the effects of random and wind‐biased assumptions on moth movements within the landscape. The model was initialised using data on the abundance of either live pupae or remains of pupal cases in the soil as surrogates for moth production within refuges. The results of the model suggested that delivery of moths from refuges to Bt cotton crops throughout the St George landscape would be patchy, with some areas thus more likely to be exposed to the threat of Bt resistance development than others. A reduction in refuge area requirements, such as recently proposed as a change to the Bt resistance management guidelines, appears likely to exacerbate such risk.

Movement Ecology of Pest Helicoverpa: Implications for Ongoing Spread

The recent introduction and spread of Helicoverpa armigera throughout South America highlight the invasiveness and adaptability of moths in the Helicoverpa genus. Long-range movement in three key members, H. armigera, H. zea, and H. punctigera, occurs by migration and international trade. These movements facilitate high population admixture and genetic diversity, with important economic, biosecurity, and control implications in todays agricultural landscape. This is particularly true for the spread of resistance alleles to transgenic crops expressing Bacillus thuringiensis (Bt) toxins that are planted over vast areas to suppress Helicoverpa spp. The ability to track long-distance movement through radar technology, population genetic markers, and/or long-distance dispersal modeling has advanced in recent years, yet we still know relatively little about the population trajectories or migratory routes in Helicoverpa spp. Here, we consider how experimental and theoretical approaches can be integrated to fill key knowledge gaps and assist management practices.