Wing morphometrics of medically and forensically important muscid flies (Diptera: Muscidae)

Geometry of posterior larval spiracles to identify medically and forensically important calliphorids in Thailand

Fly identification is the primary step of analysis in forensic entomology. Although morphology and molecular techniques are considered satisfactory methods, some constraints may arise from a financial or even human point of view. Over the past decade, the geometric morphometric approach has been increasingly advocated for the classification and identification of arthropods. This study explored the method for species identification of 800 third-instar larvae of eight blow fly species of medical and forensic importance: Chrysomya chani Kurahashi, Chrysomya megacephala (Fabricius), Chrysomya (Ceylonomyia) nigripes Aubertin, Chrysomya pinguis (Walker), Chrysomya (Achoetandrus) rufifacies (Macquart), Hemipyrellia ligurriens (Wiedemann), Lucilia cuprina (Wiedemann), and Lucilia porphyrina (Walker). Based on the posterior spiracles geometry, the cross-validation revealed a relatively high percentage of correct classification in most species, ranking from 86% to 100%. The results of this study confirmed that the geometric morphometric (GM) analysis of posterior spiracles might be utilized as a larva identification tool. Therefore, this GM method represents one way of overcoming difficulties with the identification of blow fly larvae and can support further studies of these flies.

Machine learning analysis of wing venation patterns accurately identifies Sarcophagidae, Calliphoridae and Muscidae fly species

In medical, veterinary and forensic entomology, the ease and affordability of image data acquisition have resulted in whole-image analysis becoming an invaluable approach for species identification. Krawtchouk moment invariants are a classical mathematical transformation that can extract local features from an image, thus allowing subtle species-specific biological variations to be accentuated for subsequent analyses. We extracted Krawtchouk moment invariant features from binarised wing images of 759 male fly specimens from the Calliphoridae, Sarcophagidae and Muscidae families (13 species and a species variant). Subsequently, we trained the Generalized, Unbiased, Interaction Detection and Estimation random forests classifier using linear discriminants derived from these features and inferred the species identity of specimens from the test samples. Fivefold cross-validation results show a 98.56 ± 0.38% (standard error) mean identification accuracy at the family level and a 91.04 ± 1.33% mean identification accuracy at the species level. The mean F1-score of 0.89 ± 0.02 reflects good balance of precision and recall properties of the model. The present study consolidates findings from previous small pilot studies of the usefulness of wing venation patterns for inferring species identities. Thus, the stage is set for the development of a mature data analytic ecosystem for routine computer image-based identification of fly species that are of medical, veterinary and forensic importance.

Wing morphology variations in Culicoides circumscriptus from France

The biting midge Culicoides circumscriptus Kieffer, 1918 is a European widespread vector of avian malaria throughout the continent and is a possible vector of Akabane virus and Bluetongue virus. This species populates a wide range of environments in contrasting ecological settings often exposed to strong seasonal fluctuations. The main goals of this study were to investigate C. circumscriptus phenotypic variation at three departments in France (Corsica Island, Moselle and Var) and to determine if its phenotypes vary with the environment. Culicoides circumscriptus wing phenotypes were analyzed using a geometric morphometric approach based on anatomical landmarks and outlines of the wing. Dendogram trees based on landmarks and the outlines-2 set (cell m4) showed similar topologies and separated populations of C. circumscriptus. In contrast, another set of outlines-1 (covering the r-m cross vein, M, radiale and arculus) presented a different hierarchical clustering tree. The phenotypic variation observed in C. circumscriptus indicated that these populations are exposed to environmental and ecological pressures. Our results suggest the presence of phenotypic plasticity in this species.

Size does matter: intraspecific geometric morphometric analysis of wings of the blowfly Chrysomya albiceps (Diptera: Calliphoridae)

Blowflies have forensic, sanitary and veterinary importance, as well as being pollinators, parasitoids and ecological bioindicators. There is still little work with real data and from experiments assessing the relationship between blowflies' morphologic features and environmental and demographic factors. The present work tests whether the variation, in the shape and size, of Chrysomya albiceps (Wiedemann, 1819) wings is influenced by the following factors: 1) time; 2) temperature; 3) sex and; 4) different types of carcasses (pig, dog/cat and whale). Male and female wings from four different sites collected in six different years were used to obtain wing size and shape of C. albiceps. Analyses between wing shape and the variables tested had low explanatory power, even though they had statistical support. However, it was possible to identify differences in wing shape between males and females, with good returns in sex identification. The comparison between wing size and the variables tested showed that wing size has a negative relationship with temperature, significant differences between sexes, slight variation over time and no influence by carcass types. Furthermore, wing size influenced wing shape. Understanding population-specific characteristics of C. albiceps provide important insights about how the species reacts under specific conditions.

Geometric morphometrics versus DNA barcoding for the identification of malaria vectors Anopheles dirus and An. baimaii in the Thai-Cambodia border

Anopheles (Cellia) dirus Peyton & Harrison and Anopheles baimaii Sallum & Peyton are sibling species within the Dirus complex belonging to the Leucosphyrus group, and have been incriminated as primary vectors of malaria in Thailand. In the present study, DNA barcoding and geometric morphometrics were used to distinguish between An. dirus and An. baimaii in the international border areas, Trat Province, eastern Thailand. Our results revealed that DNA barcoding based on the cytochrome c oxidase subunit I gene could not be used to distinguish An. dirus from An. baimaii. The overlapping values between intra- and interspecific genetic divergence indicated no barcoding gap present for An. dirus and An. baimaii (ranging from 0 to 0.99%). However, the results of the geometric morphometric analysis based on the wing shape clearly distinguished An. dirus and An. baimaii, with 92.42% of specimens assigned to the correct species. We concluded that geometric morphometrics is an effective tool for the correct species identification of these two malaria vectors. Our findings could be used to make entomological surveillance information more accurate, leading to further effective mosquito control planning in Thailand and other countries in Southeast Asia.

Wing morphometrics as a tool for the identification of forensic important Lucilia spp. (Diptera: Calliphoridae)

Blow flies of the genera Lucilia Robineau-Desvoidy (Diptera: Calliphoridae) are considered forensically important species across several regions of the world. Due to the similarity of adults, especially females, the usual methods based on morphology or even molecular techniques can experience some limitations; therefore, alternative or supportive tools are required. Recently, the landmark-based geometric morphometric analysis has been applied to discriminate many insects on genus and species level. Herein, we focus on wing morphometric analysis as a tool in classifying five species of Lucilia; three species from Thailand - L. cuprina (Wiedemann, 1830), L. porphyrina (Walker, 1856) and L. sinensis Aubertin, 1933; and two species from Switzerland - L. caesar (Linnaeus, 1758) and L. illustris (Meigen, 1826). Canonical variate analysis of 233 right wings showed four overlapping clusters of L. cuprina, L. sinensis, L. caesar, and L. illustris with one distinct cluster of L. porphyrina. Eighty-eight to 100 percent of correct classification was achieved, with an UPGMA dendrogram analysis revealing clear-cut branch and sub-branch of five species determined. Results from this study suggested that wing morphometric analysis is a useful tool for the identification of adult Lucilia spp.