Forest health guide: symptoms of insect and fungal damage on trees

The Forest health guide: symptoms of insect and fungal damage on trees is intended to help forestry and quarantine staff undertake tree health assessments, in both forest and urban environments. The guide is designed to be used as a quick reference to common symptoms of damage, not as an identification guide to particular insect pests and pathogens.

CRC50089 Grain Insect Ecology

Resistance to phosphine in target pests threatens market access for Australian grain. While the grains industry is now attempting to develop an effective and sustainable strategy to manage this resistance, action is severely limited by significant gaps in our knowledge of the key ecological factors that influence the development of resistance. There is a need to research this information as a foundation for a rational approach to managing phosphine resistance in the Australian grains industry. Research outcomes: The project has provided critical research methodologies and preliminary data to fill the large gaps in our knowledge of the ecology of two key pests, Rhyzopertha dominica and Tribolium castaneum, and how this may drive the development of phosphine resistance. This information will contribute to the groundwork for future research needed to provide a scientific basis for a rational resistance management strategy.

Using Trichogramma Westwood (Hymenoptera: Trichogrammatidae) for insect pest biological control in cotton crops: an Australian perspective.

Trichogramma Westwood egg parasitoids alone generally fail to suppress heliothine pests when released in established cotton-growing regions. Factors hindering their success include indiscriminate use of detrimental insecticides, compensation for minimal pest larval hatch due to their activity via reduced larval cannibalism or mortality in general, singly laid heliothine eggs avoiding detection and asynchronous development benefiting host over parasitoid. Yet, despite these limitations, relatively large Trichogramma pretiosum Riley populations pervade and effectively suppress Helicoverpa (Hardwick) pests in Australian Bt (Bacillus thuringiensis Berliner)-transgenic cotton, Gossypium hirsutum L., crops, especially in the Ord River Irrigation Area (ORIA) of tropical northern Australia, where their impact on the potentially resistant pest species, Helicoverpa armigera (Hubner), is considered integral to the local insecticide resistance management (IRM) strategy for continued, sustainable Bt-transgenic cotton production. When devoid of conventional insecticides, relatively warm and stable conditions of the early dry season in winter grown ORIA Bt-transgenic cotton crops are conducive to Trichogramma proliferation and biological control appears effective. Further, there is considerable scope to improve Trichogramma's biological control potential, in both the ORIA and established cotton-growing regions, via habitat manipulation. It is proposed that Trichogramma may prove equally effective in developing agricultural regions of monsoonal northern Australia, and that environmental constraints on Trichogramma survival, and those of other natural enemies, require due consideration prior to their successful application in biological control programs.

Insect induced bud fall in cultivated hibiscus and aspects of the biology of Macroura concolor (Macleay) (Coleoptera: Nitidulidae)

The influence of insect attack on bud fall and subsequent poor flowering in cultivated hibiscus (Hibiscus rosa-sinensis) was studied in cages and in the field in southern Queensland. Three species of Hemiptera (most importantly Aulacosternum nigrorubrum but also Nezara viridula and Tectocoris diophthalmus) caused some bud fall in 2 plantations studied. Adults of Macroura concolor suppressed flowering for long periods in spring and summer. Data from white funnel traps and counts in flowers showed that M. concolor was most active in these seasons. Methiocarb (0.75 g a.i./litre) reduced beetle numbers and increased flowering. When 15 or more adults of M. concolor occurred per bud (or flower) most buds fell and few flowers were produced, but when beetles declined to 10 or fewer many buds survived and widespread flowering occurred. Larvae fed in fallen buds and flowers and the mean duration of development of the combined immature stages was 14 days at 26 deg C. The preference of adults of M. concolor for pale coloured flowers was examined. Hibiscus plants produced most buds from December to June with lower numbers in winter and spring (July to November). Bud production in spring and early summer (September-December) varied greatly and probably contributed to poor flowering, however, even when large numbers of buds occurred very few flowers were produced because of the activities of M. concolor.

Evaluation of exclusion netting for insect pest control and fruit quality enhancement in tree crops

This work evaluated the following aspects of the use of exclusion netting in low chill stone fruit: the efficacy of protection from fruit fly for this highly susceptible crop; the effects on environmental factors; and the effects on crop development. Concurrently, an economic viability study on the use of exclusion netting was undertaken. The trial site was a 0.6-ha block of low chill stone fruit at Nambour, south-east Queensland, Australia. In this area, populations of Queensland fruit fly (Bactrocera tryoni) are known to be substantial, particularly in spring and summer. The trial block contained healthy 4-year-old trees as follows: 96 peach trees (Prunus persica cv. Flordaprince) and 80 nectarine trees (40 P. persica var. nucipersica cv. White Satin and 40 P. persica var. nucipersica cv. Sunwright). Exclusion netting was installed over approximately half of the block in february 2001. The net was a UV-stabilized structural knitted fabric made from high-density polyethylene yarn with a 10-year prorated UV degradation warranty. The results demonstrated the efficacy of exclusion netting in the control of fruit flies. Exclusion netting increased maximum temperatures by 4.4 deg C and decreased minimum temperatures by 0.5 deg C. Although exclusion netting reduced irradiance by approximately 20%, it enhanced fruit development by 7-10 days and improved fruit quality by increasing sugar concentration by 20-30% and colour intensity by 20%.

The potential for monitoring and control of insect pests in Southern Hemisphere forestry plantations using semiochemicals

Southern Hemisphere plantation forestry has grown substantially over the past few decades and will play an increasing role in fibre production and carbon sequestration in future. The sustainability of these plantations is, however, increasingly under pressure from introduced pests. This pressure requires an urgent and matching increase in the speed and efficiency at which tools are developed to monitor and control these pests. To consider the potential role of semiochemicals to address the need for more efficient pest control in Southern Hemisphere plantations, particularly by drawing from research in other parts of the world. Semiochemical research in forestry has grown exponentially over the last 40 years but has been almost exclusively focussed on Northern Hemisphere forests. In these forests, semiochemicals have played an important role to enhance the efficiency of integrated pest management programmes. An analysis of semiochemical research from 1970 to 2010 showed a rapid increase over time. It also indicated that pheromones have been the most extensively studied type of semiochemical in forestry, contributing to 92% of the semiochemical literature over this period, compared with research on plant kairomones. This research has led to numerous applications in detection of new invasions, monitoring population levels and spread, in addition to controlling pests by mass trapping or disrupting of aggregation and mating signals. The value of semiochemicals as an environmentally benign and efficient approach to managing forest plantation pests in the Southern Hemisphere seems obvious. There is, however, a lack of research capacity and focus to optimally capture this opportunity. Given the pressure from increasing numbers of pests and reduced opportunities to use pesticides, there is some urgency to develop semiochemical research capacity.

Insect pests in tropical forestry

The layout of this second edition follows that of the first, though the content has been substantially rewritten to reflect 10 years of research and development, as well as the emergence of new pest species. Chapter 1 presents an overview, from a somewhat entomological perspective, of tropical forestry in its many guises. Chapters 2, 3 and 4 then discuss the 'pure' biology and ecology of tropical insects and their co-evolved relationships with the trees and forests in which they live. Chapter 5 is necessarily the largest chapter in the book, looking in detail at a selection of major pest species from all over the tropical world. Chapters 6, 7, 8 and 9 then discuss the theory and practice of insect pest management, starting at the fundamental planning stage, before any seeds hit the soil. Nursery management and stand management were considered in Chapters 7 and 8. Chapter 9 covers the topics of forest health surveillance, quarantine and forest invasive species, topics which again have significance at all stages of forestry but for convenience are presented after nursery and forest management. This, in fact, we attempt to do in the final chapter, Chapter 10, which combines most of the previous nine chapters in examples illustrating the concept of integrated pest management. ©CABI Publishing CABI Publishing

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

A new gall midge of the genus Dentifibula (Diptera: Cecidomyiidae), a predator of the scale insect Aulacaspis australis feeding on mangrove Bruguiera gymnorrhiza

Dentifibula nigroapicalisKolesik sp. nov., a new species of gall midge, is described whose larvae were found preying on the mangrove scale insect Aulacaspis australisBrimblecombe (Hemiptera: Coccoidea: Diaspididae). The mangrove scale was feeding on leaves of the mangrove Bruguiera gymnorrhiza (Rhizophoraceae) in Queensland. The new species is the first DentifibulaFelt known from Australia. © 2013 Australian Entomological Society.

Cytorhabdovirus phosphoprotein shows RNA silencing suppressor activity in plants, but not in insect cells

RNA silencing in plants and insects provides an antiviral defense and as a countermeasure most viruses encode RNA silencing suppressors (RSS). For the family Rhabdoviridae, no detailed functional RSS studies have been reported in plant hosts and insect vectors. In agroinfiltrated Nicotiana benthamiana leaves we show for the first time for a cytorhabdovirus, lettuce necrotic yellows virus (LNYV), that one of the nucleocapsid core proteins, phosphoprotein (P) has relatively weak local RSS activity and delays systemic silencing of a GFP reporter. Analysis of GFP small RNAs indicated that the P protein did not prevent siRNA accumulation. To explore RSS activity in insects, we used a Flock House virus replicon system in Drosophila S2 cells. In contrast to the plant host, LNYV P protein did not exhibit RSS activity in the insect cells. Taken together our results suggest that P protein may target plant-specific components of RNA silencing post siRNA biogenesis.

The insecticidal spider toxin SFI1 is a knottin peptide that blocks the pore of insect voltage-gated sodium channels via a large β-hairpin loop

Spider venoms contain a plethora of insecticidal peptides that act on neuronal ion channels and receptors. Because of their high specificity, potency and stability, these peptides have attracted much attention as potential environmentally friendly insecticides. Although many insecticidal spider venom peptides have been isolated, the molecular target, mode of action and structure of only a small minority have been explored. Sf1a, a 46-residue peptide isolated from the venom of the tube-web spider Segesteria florentina, is insecticidal to a wide range of insects, but nontoxic to vertebrates. In order to investigate its structure and mode of action, we developed an efficient bacterial expression system for the production of Sf1a. We determined a high-resolution solution structure of Sf1a using multidimensional 3D/4D NMR spectroscopy. This revealed that Sf1a is a knottin peptide with an unusually large β-hairpin loop that accounts for a third of the peptide length. This loop is delimited by a fourth disulfide bond that is not commonly found in knottin peptides. We showed, through mutagenesis, that this large loop is functionally critical for insecticidal activity. Sf1a was further shown to be a selective inhibitor of insect voltage-gated sodium channels, consistent with its 'depressant' paralytic phenotype in insects. However, in contrast to the majority of spider-derived sodium channel toxins that function as gating modifiers via interaction with one or more of the voltage-sensor domains, Sf1a appears to act as a pore blocker.

Spatial ecology of a specialist insect herbivore : the leaf-mining moth Tischeria ekebladella on the pedunculate oak Quercus robur

Herbivorous insects comprise a major part of terrestrial biodiversity, and their interactions with their host plants and natural enemies are of vast ecological importance. A large body of research demonstrates that the ecology and evolution of these insects may be affected by trophic interactions, by abiotic influences, and by intraspecific processes, but so far research on these individual aspects has rarely been combined. This thesis uses the leaf-mining moth Tischeria ekebladella and the pedunculate oak (Quercus robur) as a case study to assess how spatial variation in trophic interactions and the physical distribution of host trees jointly affect the distribution, dynamics and evolution of a host-specific herbivore. With respect to habitat quality, Tischeria ekebladella experiences abundant variation at several spatial scales. Most of this variation occurs at small scales notably among leaves and shoots within individual trees. While hypothetically this could cause moths to evolve an ability to select leaves and shoots of high quality, I did not find any coupling between female preference and offspring performance. Based on my studies on temporal variation in resource quality I therefore propose that unpredictable temporal changes in the relative rankings of individual resource units may render it difficult for females to predict the fate of their developing offspring. With respect to intraspecific processes, my results suggest that limited moth dispersal in relation to the spatial distribution of oak trees plays a key role in determining the regional distribution of Tischeria ekebladella. The distribution of the moth is aggregated at the landscape level, where local leaf miner populations are less likely to be present where oaks are scarce. A modelling exercise based on empirical dispersal estimates revealed that the moth population on Wattkast an island in south-western Finland is spatially structured overall, but that the relative importance of local and regional processes on tree-specific moth dynamics varies drastically across the landscape. To conclude, my work in the oak-Tischeria ekebladella system demonstrates that the local abundance and regional distribution of a herbivore may be more strongly influenced by the spatial location of host trees than by their relative quality. Hence, it reveals the importance of considering spatial context in the study of herbivorous insects, and forms a bridge between the classical fields of plant-insect interactions and spatial ecology.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.