Is what you see what you get? The relationship between field observed and laboratory observed aphid parasitism rates in canola fields.

BACKGROUND: Estimating parasitoid abundance in the field can be difficult, even more so when attempting to quantify parasitism rates and the ecosystem service of biological control that parasitoids can provide. To understand how 'field observed' parasitism rates (in-field mummy counts) of the green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae) translate to 'laboratory observed' parasitism rates (laboratory-reared parasitoid counts), field work was undertaken in Australian canola fields, over the winter growing season. RESULTS: Overall, laboratory observed parasitism was on average 2.4 times higher than field observed parasitism, with rates an average of four-fold higher in fields from South Australia. Total field observed and laboratory observed parasitism rates (OPRs) of M. persicae varied considerably across regions, but less so among fields within regions. As crop growth stage progressed, the incidence of field observed mummies increased. The incidence of total parasitoids reared also increased with crop growth stage, averaging 3.4% during flowering and reaching 14.4% during podding/senescing. Although there was a greater diversity of reared parasitoid species at later crop growth stages, the laboratory OPR was unaffected by parasitoid species. Diaeretiella rapae was the most commonly reared parasitoid, increasing in absolute abundance with crop growth stage. CONCLUSION: These findings indicate that field mummy counts alone do not provide a clear representation of parasitism within canola fields. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Australian Bryobia mites (Trombidiformes: Tetranychidae) form a complex of cryptic taxa with unique climatic niches and insecticide responses.

BACKGROUND: Bryobia (Koch) mites belong to the economically important spider mite family, the Tetranychidae, with >130 species described worldwide. Due to taxonomic difficulties and most species being asexual, species identification relies heavily on genetic markers. Multiple putative Bryobia mite species have been identified attacking pastures and grain crops in Australia. In this study, we collected 79 field populations of Bryobia mites and combined these with 134 populations that were collected previously. We characterised taxonomic variation of mites using 28S rDNA amplicon-based DNA metabarcoding using next-generation sequencing approaches and direct Sanger sequencing. We then undertook species distribution modelling of the main genetic lineages and examined the chemical responses of multiple field populations. RESULTS: We identified 47 unique haplotypes across all mites sampled that grouped into four distinct genetic lineages. These lineages have different distributions, with three of the four putative lineages showing different climatic envelopes, as inferred from species distribution modelling. Bryobia mite populations also showed different responses to a widely used insecticide (the organophosphate, omethoate), but not to another chemical (the pyrethroid, bifenthrin) when examined using laboratory bioassays. CONCLUSION: Our findings indicate that cryptic diversity is likely to complicate the formulation of management strategies for Bryobia mites. Although focussed on Australia, this study demonstrates the challenges of studying Bryobia and highlights the importance of further research into this complex group of mites across the world. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Morphological and Molecular Analysis of Australian Earwigs (Dermaptera) Points to Unique Species and Regional Endemism in the Anisolabididae Family.

Dermaptera (earwigs) from the Anisolabididae family may be important for pest control but their taxonomy and status in Australia is poorly studied. Here we used taxonomic information to assess the diversity of southern Australian Anisolabididae and then applied cox1 barcodes as well as additional gene fragments (mitochondrial and nuclear) to corroborate classification and assess the monophyly of the putative genera. Anisolabididae morphospecies fell into two genera, Anisolabis Fieber and Gonolabis Burr, based on paramere morphology. Combinations of paramere and forceps morphology distinguished seven morphospecies, which were further supported by morphometric analyses. The morphospecies were corroborated by barcode data; all showed within-species genetic distance < 4% and between-species genetic distance > 10%. Molecular phylogenies did not support monophyly of putative genera nor clades based on paramere shape, instead pointing to regional clades distinguishable by forceps morphology. This apparent endemism needs to be further tested by sampling of earwig diversity outside of agricultural production regions but points to a unique regional insect fauna potentially important in pest control.

Spatially-Optimized Sequential Sampling Plan for Cabbage Aphids Brevicoryne brassicae L. (Hemiptera: Aphididae) in Canola Fields.

The cabbage aphid is a significant pest worldwide in brassica crops, including canola. This pest has shown considerable ability to develop resistance to insecticides, so these should only be applied on a "when and where needed" basis. Thus, optimized sampling plans to accurately assess cabbage aphid densities are critically important to determine the potential need for pesticide applications. In this study, we developed a spatially optimized binomial sequential sampling plan for cabbage aphids in canola fields. Based on five sampled canola fields, sampling plans were developed using 0.1, 0.2, and 0.3 proportions of plants infested as action thresholds. Average sample numbers required to make a decision ranged from 10 to 25 plants. Decreasing acceptable error from 10 to 5% was not considered practically feasible, as it substantially increased the number of samples required to reach a decision. We determined the relationship between the proportions of canola plants infested and cabbage aphid densities per plant, and proposed a spatially optimized sequential sampling plan for cabbage aphids in canola fields, in which spatial features (i.e., edge effects) and optimization of sampling effort (i.e., sequential sampling) are combined. Two forms of stratification were performed to reduce spatial variability caused by edge effects and large field sizes. Spatially optimized sampling, starting at the edge of fields, reduced spatial variability and therefore increased the accuracy of infested plant density estimates. The proposed spatially optimized sampling plan may be used to spatially target insecticide applications, resulting in cost savings, insecticide resistance mitigation, conservation of natural enemies, and reduced environmental impact.

Nonrandom Distribution of Cabbage Aphids (Hemiptera: Aphididae) in Dryland Canola (Brassicales: Brassicaceae).

Characterization of spatial distribution patterns of pests in large-scale agricultural fields is important because these patterns affect the sampling effort needed to accurately detect and estimate their population density. In this study, we conducted experimental releases of alate cabbage aphids (Brevicoryne brassicae L.) into centers of small plots of canola (Brassica napus L.), and their gradual spread over a 7-wk period was characterized. The small-plot experiment demonstrated gradient effects from plot centers and a nonrandom vertical distribution, with initial colonization occurring on the abaxial side of lower canopy leaves and, later, highest numbers of cabbage aphids occurring on racemes. We also conducted large-scale distribution analyses of cabbage aphid infestations in two commercial canola fields, using visual inspection and sweep net sampling. We used canola plant phenological and landscape features as explanatory variables of the spatial distribution of cabbage aphid counts. These large-scale experiments showed strong edge effects with negative associations between cabbage aphid counts and distance to crop edges, including tree lines and contour banks. Cabbage aphid distribution was more effectively displayed using logistic regression than ordinary regression, Spatial Analysis by Distance IndicEs, or both. Based on the study findings, a nonrandom or optimized inspection approach is proposed to focus monitoring efforts on canola plants within 20 m from field edges with particular attention to the abaxial side of lower-canopy leaves. Detection of advanced cabbage aphid infestations should target the racemes within 20 m from field edges.

Development of "best practices" for sampling of an important surface-dwelling soil mite in pastoral landscapes.

In this study, we analyzed 1145 vacuum samples of redlegged earth mites (RLEM) [Halotydeus destructor (Tucker) (Acari: Penthaleidae)] from 18 sampling events at six locations in pastoral landscapes of Western Australia during three growing seasons (2012-2014) (total of 228,299 RLEM individuals). The specific objectives were to determine: (1) presence/absence effects of a range of vegetation characteristics, (2) possible factors influencing RLEM sampling performance during the course of the season and day, (3) effects of size of area sampled and duration of sampling, (4) the spatial structure of RLEM counts in uniform pastoral vegetation, and (5) develop "best practices" regarding field-based vacuum sampling of surface dwelling soil mites in pastoral landscapes. We found that sampling of completely bare ground will lead to very low RLEM counts but spots with sparse vegetation (presence of bare ground) probably increases the presence of microhabitats for mites to shelter in and therefore lead to higher RLEM counts. RLEM counts were positively associated with the height of vegetation, at least up to about 15 cm in height. In early season (May-August), highest RLEM counts will be obtained in the afternoon hours (2-4 pm), whereas in late season sampling (August-November), highest RLEM counts will be obtained around noon. Higher RLEM counts should be expected from spots with grazed/mowed vegetation including cape weed and without presence of grasses and stubble. Variogram analyses of high-resolution data sets suggested that considerable range of spatial autocorrelation should be expected from fields with fairly uniform vegetation, especially if RLEM population densities are high. We are therefore recommending that samples are collected at least 30 m apart, if the objective is to obtain independent (spatially non-correlated) counts. The results from this study may be used to develop effective sampling protocols deployed in field ecology studies of soil surface dwelling mesofauna in pastoral landscapes and other ecosystems.