Evolution of wing shape in hornets: why is the wing venation efficient for species identification?

Wing geometric morphometrics and COI barcoding of Culex pipiens subgroup in the Republic of Korea

Two members of the Culex pipiens subgroup, Culex pallens and Culex pipiens f. molestus, are known to occur in the Republic of Korea (ROK). These species exhibit morphologically similar features and are challenging to distinguish below the species level. Therefore, this study utilized wing geometric morphometrics (GM) on the right wing of the Culex pipiens subgroup, alongside sequencing of the cytochrome c oxidase subunit I (COI) region. Mosquitoes were collected from 11 locations between June and October (2020-2022) to minimize regional and seasonal variations. Additionally, Culex pipiens f. pipiens, which is not native to the ROK, was included in the analysis. Culex tritaeniorhynchus, Aedes albopictus, and Anopheles sinensis, the primary vectors in the ROK, were used as outgroups for comparison. All three taxa in the Culex pipiens subgroup could be identified with an 82.4%-97.0% accuracy using GM. However, a comparison of the COI regions of the Culex pipiens subgroup revealed no clear differences between the taxa. These data can be used for accurate identification, contributing to effective mosquito control, in addition to providing a foundation for evolutionary and ecological studies on wing shape differences.

Analysis of geometric morphometrics and molecular phylogeny for Anopheles species in the Republic of Korea

Human malaria, transmitted by Anopheles mosquitoes, is the most predominant mosquito-borne disease that is responsible for hundreds of thousands of deaths worldwide each year. In the Republic of Korea (ROK), there are currently several hundred malaria cases annually, mostly near the demilitarized zone (DMZ). Eight species of Anopheles mosquitoes are currently known to be present in the ROK. Similar to other major malaria vectors in Africa and India, it is very challenging to morphologically differentiate Anopheles mosquitoes in the ROK due to their extremely similar morphology. In this study, wing geometric morphometrics (WGM) were used to differentiate the eight Anopheles species collected at six locations near the DMZ, Seoul and Pyeongtaek from April-October 2021. Phylogenetic analysis was also performed using cytochrome c oxidase subunit 1 (COI), internal transcribed spacer 2 (ITS2), and tyrosine hydroxylase (TH) genes for comparison with WGM analysis and to infer evolutionary relationships. The results of cross-validation (overall accuracy = 74.8%) demonstrated that species identification using WGM alone was not possible with a high accuracy for all eight species. While phylogenetic analyses based on the COI region could not clearly distinguish some species, the analysis based on ITS2 and TH was more useful for resolving the phylogenetic correlation of the eight species. Our results may improve Anopheles species identification strategies for effective identification and control of malaria vectors in the ROK.

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.

Disparification and extinction trade-offs shaped the evolution of Permian to Jurassic Odonata

Owing to their prevalence in nowadays terrestrial ecosystems, insects are a relevant group to assess the impact of mass extinctions on emerged land. However, limitations of the insect fossil record make it difficult to assess the impact of such events based on taxonomic diversity alone. Therefore, we documented trends in morphological diversity, i.e., disparity, using wings of Permian to Jurassic Odonata as model. Our results show a decreasing trend in disparity while species richness increased. Both the Permian-Triassic and Triassic-Jurassic transitions are revealed as important events, associated with strong morphospace restructuring due to selective extinction. In each case, a recovery was assured by the diversification of new forms compensating the loss of others. Early representatives of Odonata continuously evolved new shapes, a pattern contrasting with the classical assertion of a morphospace fulfilled early and followed by selective extinctions and specialization within it.

Classifying high-dimensional phenotypes with ensemble learning

Classification is a fundamental task in biology used to assign members to a class. While linear discriminant functions have long been effective, advances in phenotypic data collection are yielding increasingly high-dimensional datasets with more classes, unequal class covariances, and non-linear distributions. Numerous studies have deployed machine learning techniques to classify such distributions, but they are often restricted to a particular organism, a limited set of algorithms, and/or a specific classification task. In addition, the utility of ensemble learning or the strategic combination of models has not been fully explored.We performed a meta-analysis of 33 algorithms across 20 datasets containing over 20,000 high-dimensional shape phenotypes using an ensemble learning framework. Both binary (e.g., sex, environment) and multi-class (e.g., species, genotype, population) classification tasks were considered. The ensemble workflow contains functions for preprocessing, training individual learners and ensembles, and model evaluation. We evaluated algorithm performance within and among datasets. Furthermore, we quantified the extent to which various dataset and phenotypic properties impact performance.We found that discriminant analysis variants and neural networks were the most accurate base learners on average. However, their performance varied substantially between datasets. Ensemble models achieved the highest performance on average, both within and among datasets, increasing average accuracy by up to 3% over the top base learner. Higher class R2 values, mean class shape distances, and between- vs. within-class variances were positively associated with performance, whereas higher class covariance distances were negatively associated. Class balance and total sample size were not predictive.Learning-based classification is a complex task driven by many hyperparameters. We demonstrate that selecting and optimizing an algorithm based on the results of another study is a flawed strategy. Ensemble models instead offer a flexible approach that is data agnostic and exceptionally accurate. By assessing the impact of various dataset and phenotypic properties on classification performance, we also offer potential explanations for variation in performance. Researchers interested in maximizing performance stand to benefit from the simplicity and effectiveness of our approach made accessible via the R package pheble.

Phenotypic divergence in an island bee population: Applying geometric morphometrics to discriminate population-level variation in wing venation

Phenotypic divergence is an important consequence of restricted gene flow in insular populations. This divergence can be challenging to detect when it occurs through subtle shifts in morphological traits, particularly in traits with complex geometries, like insect wing venation. Here, we employed geometric morphometrics to assess the extent of variation in wing venation patterns across reproductively isolated populations of the social sweat bee, Halictus tripartitus. We examined wing morphology of specimens sampled from a reproductively isolated population of H. tripartitus on Santa Cruz Island (Channel Islands, Southern California). Our analysis revealed significant differentiation in wing venation in this island population relative to conspecific mainland populations. We additionally found that this population-level variation was less pronounced than the species-level variation in wing venation among three sympatric congeners native to the region, Halictus tripartitus, Halictus ligatus, and Halictus farinosus. Together, these results provide evidence for subtle phenotypic divergence in an island bee population. More broadly, these results emphasize the utility and potential of wing morphometrics for large-scale assessment of insect population structure.

Species morphospace boundary revisited through wing phenotypic variations of Antodynerus species (Hymenoptera: Vespidae: Eumeninae) from the Indian subcontinent

The main objective of this study was to investigate the taxonomic significance of wing phenotypic variations (size and shape) for classifying potter wasps. This is the first study investigating the wing size and shape variations, as well as wing asymmetry, sexual dimorphism, wing integration, and phylogenetic signal analysis of all known Antodynerus species from the Indian subcontinent: A. flavescens, A. limbatus, and A. punctatipennis. We used forewings and hindwings for geometric morphometric analysis, and we proved that each species’ wing had unique size and shape variations, as well as significant right–left wing asymmetry and sexual dimorphism across the Antodynerus species, as verified by discriminant function analysis. Wings of Vespidae are longitudinally folded; based on that, we tested two alternative wing modular hypotheses for evaluating the wing integration, using two subsets organization, such as anterior–posterior (AP) and proximal-distal (PD) wing modular organization. We proved that Antodynerus species wings are highly integrated units (RV > 0.5), and we rejected our hypothesis at p < 0.05. The morphospace distribution analysis revealed that each species has its unique morphospace boundary, although they share some level of homoplasy, which suggests to us that we can use wing morphometric traits for Antodynerus species delimitation. In addition, we revealed the phylogenetic signal of Antodynerus species. Surprisingly, we found a shape-related phylogenetic signal in the forewing, and there is no significant (p > 0.05) phylogenetic signal in forewing size, hindwing shape, and size. We observed that the Antodynerus species’ forewing shape is evolutionarily more highly constrained than the hindwing. We found that A. limbatus and A. flavescens with distinct geographical distribution share a similar evolutionary history, while A. punctatipennis evolved independently.

Classifying fossil Darwin wasps (Hymenoptera: Ichneumonidae) with geometric morphometrics of fore wings

Linking fossil species to the extant diversity is often a difficult task, and the correct interpretation of character evidence is crucial for assessing their taxonomic placement. Here, we make use of geometric morphometrics of fore wings to help classify five fossil Darwin wasps from the Early Eocene Fur Formation in Denmark into subfamilies and often tribes. We compile a reference dataset with 342 fore wings of nine extant subfamilies and nine relevant fossil species. Since geometric morphometrics was mostly ignored in the past in Darwin wasp classification, the dataset is first used to examine differences and similarities in wing venation among subfamilies. In a next step, we used the reference dataset to inform the classification of the fossil species, which resulted in the description of one new genus and five new species, Crusopimpla weltii sp. nov., Ebriosa flava gen. et sp. nov., Entypoma? duergari sp. nov., Lathrolestes? zlatorog sp. nov., and Triclistus bibori sp. nov., in four different subfamilies. Carefully assessing data quality, we show that the fore wing venation of fossil Darwin wasps is surprisingly suitable to assign them to a subfamily or even lower taxonomic level, especially when used in conjunction with characters from other parts of the body to narrow down a candidate set of potential subfamilies and tribes. Our results not only demonstrate a fast and useful approach to inform fossil classification but provide a basis for future investigations into evolutionary changes in fore wings of ichneumonids. The high informativeness of wing venation for classification furthermore could be harvested for phylogenetic analyses, which are otherwise often hampered by homoplasy in this parasitoid wasp family.

Leveraging machine learning tools and algorithms for analysis of fruit fly morphometrics

Analysis of landmark-based morphometric measurements taken on body parts of insects have been a useful taxonomic approach alongside DNA barcoding in insect identification. Statistical analysis of morphometrics have largely been dominated by traditional methods and approaches such as principal component analysis (PCA), canonical variate analysis (CVA) and discriminant analysis (DA). However, advancement in computing power creates a paradigm shift to apply modern tools such as machine learning. Herein, we assess the predictive performance of four machine learning classifiers; K-nearest neighbor (KNN), random forest (RF), support vector machine (the linear, polynomial and radial kernel SVMs) and artificial neural network (ANNs) on fruit fly morphometrics that were previously analysed using PCA and CVA. KNN and RF performed poorly with overall model accuracy lower than "no-information rate" (NIR) (p value > 0.1). The SVM models had a predictive accuracy of > 95%, significantly higher than NIR (p < 0.001), Kappa > 0.78 and area under curve (AUC) of the receiver operating characteristics was > 0.91; while ANN model had a predictive accuracy of 96%, significantly higher than NIR, Kappa of 0.83 and AUC was 0.98. Wing veins 2, 3, 8, 10, 14 and tibia length were of higher importance than other variables based on both SVM and ANN models. We conclude that SVM and ANN models could be used to discriminate fruit fly species based on wing vein and tibia length measurements or any other morphologically similar pest taxa. These algorithms could be used as candidates for developing an integrated and smart application software for insect discrimination and identification. Variable importance analysis results in this study would be useful for future studies for deciding what must be measured.

On the classification of simple and complex biological images using Krawtchouk moments and Generalized pseudo-Zernike moments: a case study with fly wing images and breast cancer mammograms

In image analysis, orthogonal moments are useful mathematical transformations for creating new features from digital images. Moreover, orthogonal moment invariants produce image features that are resistant to translation, rotation, and scaling operations. Here, we show the result of a case study in biological image analysis to help researchers judge the potential efficacy of image features derived from orthogonal moments in a machine learning context. In taxonomic classification of forensically important flies from the Sarcophagidae and the Calliphoridae family (n = 74), we found the GUIDE random forests model was able to completely classify samples from 15 different species correctly based on Krawtchouk moment invariant features generated from fly wing images, with zero out-of-bag error probability. For the more challenging problem of classifying breast masses based solely on digital mammograms from the CBIS-DDSM database (n = 1,151), we found that image features generated from the Generalized pseudo-Zernike moments and the Krawtchouk moments only enabled the GUIDE kernel model to achieve modest classification performance. However, using the predicted probability of malignancy from GUIDE as a feature together with five expert features resulted in a reasonably good model that has mean sensitivity of 85%, mean specificity of 61%, and mean accuracy of 70%. We conclude that orthogonal moments have high potential as informative image features in taxonomic classification problems where the patterns of biological variations are not overly complex. For more complicated and heterogeneous patterns of biological variations such as those present in medical images, relying on orthogonal moments alone to reach strong classification performance is unrealistic, but integrating prediction result using them with carefully selected expert features may still produce reasonably good prediction models.

The Unequal Taxonomic Signal of Mosquito Wing Cells

Simple Summary

Mosquitoes of the genus Aedes include important vectors of human disease viruses, including dengue, chikungunya and Zika. Surveillance programs used to detect and control these pests need accurate, fast and low-cost techniques to track the primary target and monitor possible re-infestations. Geometric morphometrics of mosquito wings is a convenient tool in mosquito species identification, but this method requires a complete wing in good condition for maximum accuracy. In this study, we investigate the amount of taxonomic signal provided by shape analysis of the internal cells of the wing. We show that (i) the internal cells of the wing provide differing amounts of taxonomic information, and (ii) the taxonomic signal of a given cell depends on the species under comparison. Since some of these cells are very informative, our study suggests that even damaged wings may provide key taxonomic information to differentiate among species found in mixed species surveillance collections.

Abstract

Accurate identification of mosquito species is critically important for monitoring and controlling the impact of human diseases they transmit. Here, we investigate four mosquito species: Aedes aegypti, Ae. albopictus, Ae. scutellaris and Verrallina dux that co-occur in tropical and subtropical regions, and whose morphological similarity challenges their accurate identification, a crucial requirement in entomological surveillance programs. Previous publications reveal a clear taxonomic signal embedded in wing cell landmark configuration, as well as in the external contour of the wings. We explored this signal for internal cells of the wings as well, to determine whether internal cells could uniformly provide the same taxonomic information. For each cell to be tentatively assigned to its respective species, i.e., to measure the amount of its taxonomic information, we used the shape of its contour, rather than its size. We show that (i) the taxonomic signal of wing shape is not uniformly spread among internal cells of the wing, and (ii) the amount of taxonomic information of a given cell depends on the species under comparison. This unequal taxonomic signal of internal cells is not related to size, nor to apparent shape complexity. The strong taxonomic signal of some cells ensures that even partly damaged wings can be used to improve species recognition.

Shape relatedness between geographic populations of Culex tritaeniorhynchus, the primary vector of Japanese encephalitis virus: A landmark study

BACKGROUND

Japanese encephalitis is a severe disease of acute encephalitis, with children and the elderly primarily affected, and with mortality rates reaching over 25%. The virus is transmitted mainly by species of the Culex (Culex) vishnui subgroup, primarily the widely spread Cx. tritaeniorhynchus Giles. The latter is known as a highly migratory mosquito which moves with airflow over large distances. We explored the geometric variation of the wing venation among distant areas of its geographic distribution. Our working hypothesis was that shape variation across geography could reveal known past and present migratory routes.

MATERIALS METHODS

We compared the wing venation geometry of 236 female Culex tritaeniorhynchus from different locations in the Madagascan (La Reunion), Oriental (Thailand, Vietnam) and Paleartic (Japan) regions. To ascertain the taxonomic signal of the wing venation we also used two species as relative outgroups, Cx. whitmorei and Cx. brevipalpis.

RESULTS

In spite of an increasing morphometric variation as expected with larger geographic dispersion, our Cx. tritaeniorhynchus samples were clustered as a single species when considered relative to other Culex species. The relationships between geographic sites of Cx. tritaeniorhynchus globally conformed with an isolation by distance model. The shape homogeneity of our Palearctic samples (Japan) contrasted with some heterogeneity observed in the Oriental region (Thailand, Vietnam), and could be related to the different regimes of wind trajectories in these regions.

CONCLUSION

The average shape variation of Culex tritaeniorhynchus disclosed a separation between Madagascan, Oriental and Palearctic regions in accordance with geography. The wing venation not only could reflect geography, it also contained a clear taxonomic signal separating three Culex species. Within Cx. tritaeniorhynchus, a contrasting pattern of shape variation between the Palearctic and the Oriental regions is tentatively explained by the influence of wind trajectories.

Random forests for predicting species identity of forensically important blow flies (Diptera: Calliphoridae) and flesh flies (Diptera: Sarcophagidae) using geometric morphometric data: Proof of concept

Wing shape variation has been shown to be useful for delineating forensically important fly species in two Diptera families: Calliphoridae and Sarcophagidae. Compared to DNA-based identification, the cost of geometric morphometric data acquisition and analysis is relatively much lower because the tools required are basic, and stable softwares are available. However, to date, an explicit demonstration of using wing geometric morphometric data for species identity prediction in these two families remains lacking. Here, geometric morphometric data from 19 homologous landmarks on the left wing of males from seven species of Calliphoridae (n = 55), and eight species of Sarcophagidae (n = 40) were obtained and processed using Generalized Procrustes Analysis. Allometric effect was removed by regressing centroid size (in log₁₀ ) against the Procrustes coordinates. Subsequently, principal component analysis of the allometry-adjusted Procrustes variables was done, with the first 15 principal components used to train a random forests model for species prediction. Using a real test sample consisting of 33 male fly specimens collected around a human corpse at a crime scene, the estimated percentage of concordance between species identities predicted using the random forests model and those inferred using DNA-based identification was about 80.6% (approximate 95% confidence interval = [68.9%, 92.2%]). In contrast, baseline concordance using naive majority class prediction was 36.4%. The results provide proof of concept that geometric morphometric data has good potential to complement morphological and DNA-based identification of blow flies and flesh flies in forensic work.

Molecular and morphometric divergence of four species of butterflies (Nymphalidae and Pieridae) from the Western Himalaya, India

Morphometric and molecular divergence among four butterfly species of the families Nymphalidae and Pieridae from the western Himalaya region were investigated using molecular tools, traditional morphometric measures and a truss network system. The considered species were Danaus chrysippus, Vanessa cardui, Pieris brassicae and Pieris canidia. Traditional taxonomy is sometimes unable to discriminate cryptic species or species that have close morphological features. Although taxonomists carefully examine external body features to differentiate the species; however, there is a risk for misidentification during a visual assessment of cryptic species. Therefore, we aimed to use the truss network system of 14 morphological landmarks interconnected to yield 90 variables about molecular taxonomy. Principal component analysis (PCA), discriminant function analysis (DFA) and cluster analysis (CA) were employed to determine morphometric variations. In the traditional analysis, 79, 68, 16 and 5 characters out of 90 were found significant (p < 0.05) for D. chrysippus, V. cardui, P. brassicae and P. canidia, respectively. One to seven principal components were extracted through PCA; they explained 87.5-100% of the total variance in samples. Notably, DFA correctly classified 100% of the original grouped cases and 100% of the cross-validated grouped cases. However, the variations were not the same for the two different methods (truss and traditional) employed for the analysis. We correctly identified all the species; the interspecies sequence divergence was between 0.1034 and 0.1398, and the intra-species sequence divergence range was 0.0001 to 0.0128 using the Cytochrome c oxidase subunit-I (COI) gene. The present study provides useful information about the application and complementary role of traditional with truss morphometric analysis for the precise identification and classification of the selected species.

Dataset of wing venation measurements for Apis mellifera caucasica, A. mellifera carnica and A. mellifera mellifera (Hymenoptera: Apidae), their hybrids and backcrosses

Background

Wing venation is used as a tool in honeybee (Apismellifera L., 1758) subspecies identification. The presented dataset concerns nineteen landmarks located at honeybee worker's forewing vein junctions. Landmarks of Apismelliferacaucasica Pollmann, 1889, A.melliferacarnica Pollmann, 1879 and A.melliferamellifera Linnaeus, 1758, their hybrids and backcrosses were measured. In total, data from 9590 wings were collected. The dataset could be used in geometric morphometric analysis, studies of degree of inheritance of morphological features and, after further development and supplementation with other local subspecies and hybrids, can contribute to in-depth evolutionary research on honeybees.

New information

Baseline dataset for wing venation of hybrids and backcrosses of A.melliferacarnica, A.melliferacaucasica and A.melliferamellifera.

Wasp Waist and Flight: Convergent Evolution in Wasps Reveals a Link between Wings and Body Shapes

Insect flight is made possible by different morphological structures: wings produce the lift, the thorax drives the wings' movements, and the abdomen serves as a secondary control device. As such, the covariation of these structures could reflect functional constraints related to flight performances. This study examines evolutionary convergences in wasp body shapes to provide the first evidence for morphological integration among insect wings, thorax, and abdomen. The shapes of the forewings and hind wings, thorax, and petiole (connecting abdomen and thorax) of 22 Vespidae species were analyzed using computerized tomography and geometric morphometrics. Results show a clear relationship between petiole and wings or thorax shapes but not between wings and thorax. Wasps with elongated bodies have pointed wings, both features thought to improve flight maneuverability. In contrast, stouter species have rounded wings, which may allow for higher flight speeds. These integration patterns suggest that multiple selective regimes on flight performance, some of them biased toward maneuverability or maximal speed, drove the morphological diversity in Vespidae. The results also suggest that wing shapes evolved under constraints related to the body type they have to lift. The abdomen morphology is thus another factor to take into account to understand the flight performance of insects.

Morphometric analysis of fossil bumble bees (Hymenoptera, Apidae, Bombini) reveals their taxonomic affinities

Bumble bees (Bombus spp.) are a widespread corbiculate lineage (Apinae: Corbiculata: Bombini), mostly found among temperate and alpine ecosystems. Approximately 260 species have been recognized and grouped recently into a simplified system of 15 subgenera. Most of the species are nest-building and primitively eusocial. Species of Bombus have been more intensely studied than any other lineages of bees with the exception of the honey bees. However, most bumble bee fossils are poorly described and documented, making their placement relative to other Bombus uncertain. A large portion of the known and presumed bumble bee fossils were re-examined in an attempt to better understand their affinities with extant Bombini. The taxonomic affinities of fossil specimens were re-assessed based on morphological features and previous descriptions, and for 13 specimens based on geometric morphometrics of forewing shape. None of the specimens coming from Eocene and Oligocene deposits were assigned within the contemporary shape space of any subgenus of Bombus. It is shown that Calyptapis florissantensis Cockerell, 1906 (Eocene-Oligocene boundary, Florissant shale, Colorado, USA) and Oligobombus cuspidatus Antropov, 2014 (Late Eocene, Bembridge Marls) likely belong to stem-group Bombini. Bombus anacolus Zhang, 1994, B. dilectus Zhang, 1994, B. luianus Zhang, 1990 (Middle Miocene, Shanwang Formation), as well as B. vetustus Rasnitsyn & Michener, 1991 (Miocene, Botchi Formation) are considered as species inquirenda. In the Miocene, affinities of fossils with derived subgenera of Bombus s. l. increased, and some are included in the shape space of contemporary subgenera: Cullumanobombus (i.e., B. pristinus Unger, 1867, B. randeckensis Wappler & Engel, 2012, and B. trophonius Prokop, Dehon, Michez & Engel, 2017), Melanobombus (i.e., B. cerdanyensis Dehon, De Meulemeester & Engel, 2014), and Mendacibombus (i.e., B. beskonakensis (Nel & Petrulevičius, 2003), new combination), agreeing with previous estimates of diversification.

Hind wing variation in Leptura annularis complex among European and Asiatic populations (Coleoptera, Cerambycidae)

The ability to quantify morphological variation is essential for understanding the processes of species diversification. The geometric morphometrics approach allows reliable description of variation in animals, including insects. Here, this method was used to quantify the morphological variation among European and Asiatic populations of Lepturaannularis Fabricius, 1801 and its closely related species L.mimica Bates, 1884, endemic for Japan and Sakhalin islands. Since the taxonomic status of these two taxa is differently interpreted by taxonomists, they are collectively called “Lepturaannularis complex” in this paper. The analysis was based on the measurements of hind wings of 269 specimens from six populations from Europe and Asia. The level of morphological divergence between most of continental European and Asiatic populations was relatively small and proportional to the geographic distance between them. However, distinct morphotype was detected in Sakhalin Is. and Japan. These data confirm the morphological divergence of the endemic L.mimica species. Obtained results highlight the potential of the geometric morphometric method in studying morphological variation in beetles.

Elytra reduction may affect the evolution of beetle hind wings

Beetles are one of the largest and most diverse groups of animals in the world. Conversion of forewings into hardened shields is perceived as a key adaptation that has greatly supported the evolutionary success of this taxa. Beetle elytra play an essential role: they minimize the influence of unfavorable external factors and protect insects against predators. Therefore, it is particularly interesting why some beetles have reduced their shields. This rare phenomenon is called brachelytry and its evolution and implications remain largely unexplored. In this paper, we focused on rare group of brachelytrous beetles with exposed hind wings. We have investigated whether the elytra loss in different beetle taxa is accompanied with the hind wing shape modification, and whether these changes are similar among unrelated beetle taxa. We found that hind wings shape differ markedly between related brachelytrous and macroelytrous beetles. Moreover, we revealed that modifications of hind wings have followed similar patterns and resulted in homoplasy in this trait among some unrelated groups of wing-exposed brachelytrous beetles. Our results suggest that elytra reduction may affect the evolution of beetle hind wings.

An Early Miocene bumble bee from northern Bohemia (Hymenoptera, Apidae)

A new species of fossil bumble bee (Apinae: Bombini) is described and figured from Early Miocene (Burdigalian) deposits of the Most Basin at the Bílina Mine, Czech Republic. Bombus trophoniussp. n., is placed within the subgenus Cullumanobombus Vogt and distinguished from the several species groups therein. The species is apparently most similar to the Nearctic B. (Cullumanobombus) rufocinctus Cresson, the earliest-diverging species within the clade and the two may be related only by symplesiomorphies. The age of the fossil is in rough accordance with divergence estimations for Cullumanobombus.

Wing morphometrics as a tool in species identification of forensically important blow flies of Thailand

Background

Correct species identification of blow flies is a crucial step for understanding their biology, which can be used not only for designing fly control programs, but also to determine the minimum time since death. Identification techniques are usually based on morphological and molecular characters. However, the use of classical morphology requires experienced entomologists for correct identification; while molecular techniques rely on a sound laboratory expertise and remain ambiguous for certain taxa. Landmark-based geometric morphometric analysis of insect wings has been extensively applied in species identification. However, few wing morphometric analyses of blow fly species have been published.

Methods

We applied a landmark-based geometric morphometric analysis of wings for species identification of 12 medically and forensically important blow fly species of Thailand. Nineteen landmarks of each right wing of 372 specimens were digitised. Variation in wing size and wing shape was analysed and evaluated for allometric effects. The latter confirmed the influence of size on the shape differences between species and sexes. Wing shape variation among genera and species were analysed using canonical variates analysis followed by a cross-validation test.

Results

Wing size was not suitable for species discrimination, whereas wing shape can be a useful tool to separate taxa on both, genus and species level depending on the analysed taxa. It appeared to be highly reliable, especially for classifying Chrysomya species, but less robust for a species discrimination in the genera Lucilia and Hemipyrellia. Allometry did not affect species separation but had an impact on sexual shape dimorphism.

Conclusions

A landmark-based geometric morphometric analysis of wings is a useful additional method for species discrimination. It is a simple, reliable and inexpensive method, but it can be time-consuming locating the landmarks for a large scale study and requires non-damaged wings for analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-017-2163-z) contains supplementary material, which is available to authorized users.

Distribution and predictors of wing shape and size variability in three sister species of solitary bees

Morphological traits can be highly variable over time in a particular geographical area. Different selective pressures shape those traits, which is crucial in evolutionary biology. Among these traits, insect wing morphometry has already been widely used to describe phenotypic variability at the inter-specific level. On the contrary, fewer studies have focused on intra-specific wing morphometric variability. Yet, such investigations are relevant to study potential convergences of variation that could highlight micro-evolutionary processes. The recent sampling and sequencing of three solitary bees of the genus Melitta across their entire species range provides an excellent opportunity to jointly analyse genetic and morphometric variability. In the present study, we first aim to analyse the spatial distribution of the wing shape and centroid size (used as a proxy for body size) variability. Secondly, we aim to test different potential predictors of this variability at both the intra- and inter-population levels, which includes genetic variability, but also geographic locations and distances, elevation, annual mean temperature and precipitation. The comparison of spatial distribution of intra-population morphometric diversity does not reveal any convergent pattern between species, thus undermining the assumption of a potential local and selective adaptation at the population level. Regarding intra-specific wing shape differentiation, our results reveal that some tested predictors, such as geographic and genetic distances, are associated with a significant correlation for some species. However, none of these predictors are systematically identified for the three species as an important factor that could explain the intra-specific morphometric variability. As a conclusion, for the three solitary bee species and at the scale of this study, our results clearly tend to discard the assumption of the existence of a common pattern of intra-specific signal/structure within the intra-specific wing shape and body size variability.

DNA barcoding and wing morphometrics to distinguish three Aedes vectors in Thailand

Aedes aegypti (Diptera: Culicidae) (L.), Ae. albopictus (Skuse), and Ae. scutellaris (Walker) are important mosquito vectors of dengue and chikungunya viruses. They are morphologically similar and sympatric in some parts of their distribution; therefore, there is a risk of incorrect morphological identification. Any confusion could have a negative impact on epidemiological studies or control strategies. Therefore, we explored two modern tools to supplement current morphological identification: DNA barcoding and geometric morphometric analyses. Field larvae were reared to adults and carefully classified based on morphological traits. The genetic analysis was based on the 658bp each of 30COI sequences. Some Culex spp., Mansonia bonneae, were included as outgroups, and inclusion of a few other Aedes spp. facilitated phylogenetic inference of the relationship between Ae. albopictus and Ae. scutellaris. The two species were separated by an average interspecific divergence of 0.123 (0.119-0.127). Morphometric examination included landmark- (392 specimens) and outline-based (317 specimens) techniques. The shape of the wing showed different discriminating power based on sex and digitizing technique. This is the first time that Ae. scutellaris and Ae. albopictus have been compared using these two techniques. We confirm that these morphologically close species are valid, and that geometric morphometrics can considerably increase the reliability of morphological identification.

Within- and Between-Species Variation of Wing Venation in Genus Monochamus (Coleoptera: Cerambycidae)

We have described the morphological variation of five Western Palaearctic species of Monochamus Dejean, 1821. The variation was assessed using wing measurements. Special emphasis was placed on the differences between Monochamus sartor (F., 1787) and Monochamus urussovii (Fischer-Waldheim, 1805). There was an interesting pattern of variation between the two species. Individuals of M. sartor from the Carpathians differed markedly from individuals of M. urussovii from Siberia, but individuals from north-eastern Poland were intermediate between those two populations. The intermediate individuals were more similar to the Siberian M. urussovii than to the Carpathian M. sartor despite the relatively large geographic distance between north-eastern Poland and Siberia. The occurrence of the intermediate individuals in north-eastern Poland may be the effect of hybridization between M. urussovii and M. sartor, which might have occurred after secondary contact between the two species in the Holocene.

Bony labyrinth shape variation in extant Carnivora: a case study of Musteloidea

The bony labyrinth provides a proxy for the morphology of the inner ear, a primary cognitive organ involved in hearing, body perception in space, and balance in vertebrates. Bony labyrinth shape variations often are attributed to phylogenetic and ecological factors. Here we use three-dimensional (3D) geometric morphometrics to examine the phylogenetic and ecological patterns of variation in the bony labyrinth morphology of the most species-rich and ecologically diversified traditionally recognized superfamily of Carnivora, the Musteloidea (e.g. weasels, otters, badgers, red panda, skunks, raccoons, coatis). We scanned the basicrania of specimens belonging to 31 species using high-resolution X-ray computed micro-tomography (μCT) to virtually reconstruct 3D models of the bony labyrinths. Labyrinth morphology is captured by a set of six fixed landmarks on the vestibular and cochlear systems, and 120 sliding semilandmarks, slid at the center of the semicircular canals and the cochlea. We found that the morphology of this sensory structure is not significantly influenced by bony labyrinth size, in comparisons across all musteloids or in any of the individual traditionally recognized families (Mephitidae, Procyonidae, Mustelidae). PCA (principal components analysis) of shape data revealed that bony labyrinth morphology is clearly distinguishable between musteloid families, and permutation tests of the Kmult statistic confirmed that the bony labyrinth shows a phylogenetic signal in musteloids and in most mustelids. Both the vestibular and cochlear regions display morphological differences among the musteloids sampled, associated with the size and curvature of the semicircular canals, angles between canals, presence or absence of a secondary common crus, degree of lateral compression of the vestibule, orientation of the cochlea relative to the semicircular canals, proportions of the cochlea, and degree of curvature of its turns. We detected a significant ecological signal in the bony labyrinth shape of musteloids, differentiating semi-aquatic taxa from non-aquatic ones (the taxa assigned to terrestrial, arboreal, semi-arboreal, and semi-fossorial categories), and a significant signal for mustelids, differentiating the bony labyrinths of terrestrial, semi-arboreal, arboreal, semi-fossorial and semi-aquatic species from each other. Otters and minks are distinguished from non-aquatic musteloids by an oval rather than circular anterior canal, sinuous rather than straight lateral canal, and acute rather than straight angle between the posterior and lateral semicircular canals - each of these morphological characters has been related previously to animal sensitivity for detecting head motion in space.

Patriline Differences Reveal Genetic Influence on Forewing Size and Shape in a Yellowjacket Wasp (Hymenoptera: Vespidae: Vespula flavopilosa Jacobson, 1978)

The wing venation is frequently used as a morphological marker to distinguish biological groups among insects. With geometric morphometrics, minute shape differences can be detected between closely related species or populations, making this technique useful for taxonomy. However, the direct influence of genetic differences on wing morphology has not been explored within colonies of social insects. Here, we show that the father's genotype has a direct effect on wing morphology in colonies of social wasps. Using geometric morphometrics on the venation pattern, we found significant differences in wing size and shape between patrilines of yellowjackets, taking allometry and measurement error into account. The genetic influence on wing size accounted for a small part of the overall size variation, but venation shape was highly structured by the differences between patrilines. Overall, our results showed a strong genetic influence on wing morphology likely acting at multiple levels of venation pattern development. This confirmed the pertinence of this marker for taxonomic purposes and suggests this phenotype as a potentially useful marker for phylogenies. This also raises doubts about the strength of selective pressures on this phenotype, which highlights the need to understand better the role of wing venation shape in insect flight.

An image database of Drosophila melanogaster wings for phenomic and biometric analysis

BACKGROUND

Extracting important descriptors and features from images of biological specimens is an ongoing challenge. Features are often defined using landmarks and semi-landmarks that are determined a priori based on criteria such as homology or some other measure of biological significance. An alternative, widely used strategy uses computational pattern recognition, in which features are acquired from the image de novo. Subsets of these features are then selected based on objective criteria. Computational pattern recognition has been extensively developed primarily for the classification of samples into groups, whereas landmark methods have been broadly applied to biological inference.

RESULTS

To compare these approaches and to provide a general community resource, we have constructed an image database of Drosophila melanogaster wings - individually identifiable and organized by sex, genotype and replicate imaging system - for the development and testing of measurement and classification tools for biological images. We have used this database to evaluate the relative performance of current classification strategies. Several supervised parametric and nonparametric machine learning algorithms were used on principal components extracted from geometric morphometric shape data (landmarks and semi-landmarks). For comparison, we also classified phenotypes based on de novo features extracted from wing images using several computer vision and pattern recognition methods as implemented in the Bioimage Classification and Annotation Tool (BioCAT).

CONCLUSIONS

Because we were able to thoroughly evaluate these strategies using the publicly available Drosophila wing database, we believe that this resource will facilitate the development and testing of new tools for the measurement and classification of complex biological phenotypes.