The effect of data sources and quality on the predictive capacity of CLIMEX models: an assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia

Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.

Responses of tribolium castaneum to olfactory cues from cotton seeds, the fungi associated with cotton seeds, and cereals

We tested, in an olfactometer, whether or not Tribolium castaneum Herbst (Coleoptera: Tenebrionidae) responds preferentially to the volatiles that emanate from the fungi associated with cotton [Gossypium hirsutum L. (Malvaceae)] seed over those that emanate from cereals, because cereals are usually portrayed as the primary resources of these beetles. Pairwise comparisons were conducted between cotton seed, wheat (Triticum aestivum L.), and sorghum [Sorghum bicolor (L.) Moench] (both Poaceae); volatiles were tested from intact seeds and from both water and ethanol extracts. The results demonstrate that T. castaneum is attracted more strongly to cotton seeds with its lint contaminated with fungi, than to the conventional resources of this species (i.e., wheat and sorghum). Further tests prove that it is the fungus on the lint that produces the active volatiles, because the beetles did not respond to sterilized cotton lint (i.e., without the fungi typically associated with it when cotton seed is stored). Tests with five fungal cultures (each representing an unidentified species that was isolated from the field-collected cotton lint) were variable across the cultures, with only one of them being significantly attractive to the beetles. The others were not attractive and one may even have repulsed the beetles. The results are consistent with the beetles having a strong ecological association with fungi and suggest it would be worth investigating the ecology of T. castaneum from this perspective. © 2012 The Netherlands Entomological Society.

An inordinate fondness for Fusarium: Phylogenetic diversity of fusaria cultivated by ambrosia beetles in the genus Euwallacea on avocado and other plant hosts

Ambrosia beetle fungiculture represents one of the most ecologically and evolutionarily successful symbioses, as evidenced by the 11 independent origins and 3500 species of ambrosia beetles. Here we document the evolution of a clade within Fusarium associated with ambrosia beetles in the genus Euwallacea (Coleoptera: Scolytinae). Ambrosia Fusarium Clade (AFC) symbionts are unusual in that some are plant pathogens that cause significant damage in naive natural and cultivated ecosystems, and currently threaten avocado production in the United States, Israel and Australia. Most AFC fusaria produce unusual clavate macroconidia that serve as a putative food source for their insect mutualists. AFC symbionts were abundant in the heads of four Euwallacea spp., which suggests that they are transported within and from the natal gallery in mandibular mycangia. In a four-locus phylogenetic analysis, the AFC was resolved in a strongly supported monophyletic group within the previously described Cade 3 of the Fusarium solani species complex (FSSC). Divergence-time estimates place the origin of the AFC in the early Miocene similar to 21.2 Mya, which coincides with the hypothesized adaptive radiation of the Xyleborini. Two strongly supported clades within the AFC (Clades A and B) were identified that include nine species lineages associated with ambrosia beetles, eight with Euwallacea spp. and one reportedly with Xyleborus ferrugineus, and two lineages with no known beetle association. More derived lineages within the AFC showed fixation of the clavate (club-shaped) macroconidial trait, while basal lineages showed a mix of clavate and more typical fusiform macroconidia. AFC lineages consisted mostly of genetically identical individuals associated with specific insect hosts in defined geographic locations, with at least three interspecific hybridization events inferred based on discordant placement in individual gene genealogies and detection of recombinant loci. Overall, these data are consistent with a strong evolutionary trend toward obligate symbiosis coupled with secondary contact and interspecific hybridization. (C) 2013 Elsevier Inc. All rights reserved.

Gut-inhabiting yeasts from the gut of Australian passalid beetles

Passalidae (Polyphaga, Coleoptera) is a family of beetles with approximately 960 species that are distributed worldwide. Preliminary studies that characterized ascomycete and basidiomycete yeasts in the gut of these wood-eating beetles from the USA, Guatemala, and Thailand, demonstrated associations between certain yeast taxa and passalids. We extended the study to include yeasts and beetles from tropical forests near Cairns and Brisbane, Queensland, Australia. We isolated more than 1000 yeast strains from about 150 beetles belonging to 10 species. LSU and ITS rRNA markers were used to identify a subset of 250 yeast strains, which revealed that the gut of Australian passalids contained undescribed ascomycetes in the Debaryomyces, Dipodascus, Kazachstania, Ogataea, Scheffersomyces, Sugiyamaella, Spathaspora, Torulaspora, and Zygowilliopsis clades, as well as basidiomycetes in the genera Cryptococcus and Trichosporon. A close relative of Candida subhashii (Spathaspora clade) and the xylose-fermenting yeast Scheffersomyces stipitis were the most common species isolated in Queensland. These results agree with those of previous studies that showed a common association of xylose-fermenting yeasts in the gut of lignicolous insects. Species and higher taxa of yeasts, however, vary between Queensland passalids and those previously collected in distant regions.

Biological control of prickly acacia: Current research and future prospects

Prickly acacia, Vachellia nilotica subsp. indica (syn. Acacia nilotica subsp. indica) (Fabaceae), a major weed in the natural grasslands of western Queensland, has been a target of biological control since the 1980s with limited success to date. Surveys in India, based on genetic and climate matching, identified five insects and two rust pathogens as potential agents. Host-specificity tests were conducted for the insects in India and under quarantine conditions in Australia, and for the rust pathogens under quarantine conditions at CABI in the UK. In no-choice tests, the brown leaf-webber, Phycita sp. A, (Lepidoptera: Pyralidae) completed development on 17 non-target plant species. Though the moth showed a clear preference for prickly acacia in oviposition choice trials screening of additional test-plant species was terminated in view of the potential non-target risk. The scale insect Anomalococcus indicus (Hemiptera: Lecanodiaspididae) developed into mature gravid females on 13 out of 58 non-target plant species tested. In the majority of cases very few female scales matured but development was comparable to that on prickly acacia on four of the non-target species. In multiple choice tests, the scale insect showed a significant preference for the target weed over non-target species tested. In a paired-choice trial under field conditions in India, crawler establishment occurred only on prickly acacia and not on the non-target species tested. Further choice trials are to be conducted under natural field conditions in India. A colony of the green leaf-webber Phycita sp. B has been established in quarantine facilities in Australia and host-specificity testing has commenced. The gall-rust Ravenelia acaciae-arabicae and the leaf-rust Ravenelia evansii (Puccineales: Raveneliaceae) both infected and produced viable urediniospores on Vachellia sutherlandii (Fabaceae), a non-target Australian native plant species. Hence, no further testing with the two rust species was pursued. Inoculation trials using the gall mite Aceria liopeltus (Acari: Eriophyidae) from V. nilotica subsp. kraussiana in South Africa resulted in no gall induction on V. nilotica subsp. indica. Future research will focus on the leaf-weevil Dereodus denticollis (Coleoptera: Curculionidae) and the leaf-beetle Pachnephorus sp. (Coleoptera: Chrysomelidae) under quarantine conditions in Australia. Native range surveys for additional potential biological control agents will also be pursued in northern and western Africa.

Increased attractiveness of honeybee hive product volatiles to adult small hive beetle, Aethina tumida, resulting from small hive beetle larval infestation

The small hive beetle, Aethina tumida Murray (Coleoptera: Nitidulidae), is a recent but significant pest of honeybee Apis mellifera L. (Hymenoptera: Apidae) hives in various regions throughout the world, including Eastern Australia. The larval stage of this beetle damages hives when they feed on brood, pollen, and honeycomb, leaving behind fermented wastes. In cases of extreme damage, hives collapse and are turned to an odorous mass of larvae in fermenting hive products. The yeast Kodamaea ohmeri (Etchells & Bell) Yamada et al. (Ascomycota) has been consistently isolated from the fermenting material as well as each life stage of this beetle. Various studies have noted that the small hive beetle is attracted to volatiles from hive products and those of the yeast K. ohmeri, although earlier studies have not used naturally occurring hive products as their source of fermentation. This study investigated changes through time in the attractiveness of natural honeybee hive products to the small hive beetle as the hive products were altered by the action of beetle larvae and fermentation by K. ohmeri. We used gas chromatography-mass spectrometry and choice-test behavioural assays to investigate these changes using products sampled from three apiaries. Attractiveness of the fermenting hive products (‘slime’) increased as fermentation progressed, and volatile profiles became more complex. Fermenting hive products remained extremely attractive for more than 30 days, significantly longer than previous reports. These results have strong implications for the development of an external attractant trap to assist in the management of this invasive pest.

Flight directionality of Tribolium castaneum soon after take-off under glasshouse and field conditions

Flight directionality of the rust-red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), was investigated under glasshouse and field conditions using sticky traps placed around dense experimental infestations of T. castaneum derived from field-collected samples. Although beetles of this species are known to fly quite readily, information on flight of beetles away from grain resources is limited. Under still glasshouse conditions, T. castaneum does not demonstrate strong horizontal or vertical trajectories in their initial flight behaviour. Flight was significantly directional in half of the replicates, but trapped beetles were only weakly concentrated around the mean direction of flight. In the field, by contrast, emigration of T. castaneum was strongly directional soon after flight initiation. The mean vector lengths were generally >0.5 which indicates that trapped beetles were strongly concentrated around the calculated mean flight direction. A circular-circular regression of mean flight vs. mean downwind direction suggested that flight direction was generally correlated with downwind direction. The mean height at which T. castaneum individuals initially flew was 115.4 ± 7.0 cm, with 58.3% of beetles caught no more than 1 m above the ground. The height at which beetles were trapped did not correlate with wind speed at the time of sampling, but the data do indicate that wind speed significantly affected T. castaneum flight initiation, because no beetles (or very few; no more than three) were trapped in the field when the mean wind speed was above 3 m s−1. This study thus demonstrates that wind speed and direction are both important aspects of flight behaviour of T. castaneum, and therefore of the spatio-temporal dynamics of this species.

Native Phloem and Wood Borers in Australian Mediterranean Forest Trees

Native Mediterranean forests in Australia are dominated by two tree genera, Eucalyptus and Acacia, while Pinus and Eucalyptus dominate plantation forestry. In native forests, there is a high diversity of phloem and wood borers across several families in the Coleoptera and Lepidoptera. In the Coleoptera, cerambycid beetles (Cerambycidae), jewel beetles (Buprestidae), bark, ambrosia and pinhole beetles (Curculionidae) and pinworms (Lymexelidae) are some of the most commonly found beetles attacking eucalypts and acacias. In the Lepidoptera, wood moths (Cossidae), ghost moths (Hepialidae) and borers in the Xyloryctidae (subfamily Xyloryctinae) are most common. In contrast to native forests, there is a much more limited range of native insects present in Australian plantations, particularly in exotic Pinus spp. plantations, although eucalypt plantations do share some borers in common with native forests. This chapter reviews the importance of these borers in Australian forests primarily from an economic perspective (i.e. those species that cause damage to commercial tree species) and highlights a paucity of native forest species that commonly kill trees relative to the large scales regularly seen in North America and Europe.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

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 methodology 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 this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling 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 clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.