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The Hemiptera is the largest non-endopterygote insect order comprising approximately 98,000 recent species. All species of the suborders Cicadomorpha (leafhoppers, spittlebugs, treehoppers and cicadas) and Fulgoromorpha (planthoppers) feed by sucking sap from plant tissues and are thus often vectors for economically important phytopathogens. Except for the cicadas (Cicadomorpha: Cicadoidea: Cicadidae) which produce air-borne sounds, all species of the suborders Cicadomorpha and Fulgoromorpha communicate by vibrational (substrate-borne) signals. While the generation of these signals has been extensively investigated, the mechanisms of perception are poorly understood. This study provides a full description and 3D reconstruction of a large and complex array of six paired chordotonal organs in the first abdominal segments of the Rhododendron leafhopper Graphocephala fennahi (Cicadomorpha: Membracoidea: Cicadellidae). Further we were able to identify homologous organs in the closely related spittlebug Philaenus spumarius (Cicadomorpha: Cercopoidea: Aphrophoridae) and the planthopper Issus coleoptratus (Fulgoromorpha: Fulgoroidea: Issidae). The configuration is congruent with the abdominal chordotonal organs in cicadas, where one of them is an elaborate tympanal organ. This indicates that these organs, together with the tymbal organ constitute a synapomorphy of the Tymbalia (Hemiptera excl. Sternorrhyncha). Our results contribute to the understanding of the evolution from substrate-borne to airborne communication in insects.
Shark populations that are distributed alongside a latitudinal gradient often display body size differences at sexual maturity and vicariance patterns related to their number of tooth files. Previous works have demonstrated that Scyliorhinus canicula exhibits distinct genetic structures, life history traits, and body size differences between populations inhabiting the North Atlantic Ocean and the Mediterranean Sea. In this work, we sample more than 3,000 S. canicula teeth from 56 specimens and provide and use a dataset containing their shape coordinates. We investigate tooth shape and form differences between a Mediterranean and an Atlantic S. canicula population using two approaches. Classification results show that the classical geometric morphometric framework is outperformed by an original Random Forests-based framework. Visually, both S. canicula populations share similar ontogenetic trends and timing of gynandric heterodonty emergence but the Atlantic population has bigger, blunter teeth, and less numerous accessory cusps than the Mediterranean population. According to the models, the populations are best differentiated based on their lateral tooth edges, which bear accessory cusps, and the tooth centroid sizes significantly improve classification performances. The differences observed are discussed in light of dietary and behavioural habits of the populations considered. The method proposed in this study could be further adapted to complement DNA analyses to identify shark species or populations based on tooth morphologies. This process would be of particular interest for fisheries management and identification of shark fossils.
The present dataset contains the 3D models analyzed in Berio, F., Bayle, Y., Baum, D., Goudemand, N., and Debiais-Thibaud, M. 2022. Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula. It contains the head surfaces of 56 North Atlantic and Mediterranean small-spotted catsharks Scyliorhinus canicula, from which tooth surfaces were further extracted to perform geometric morphometrics and machine learning.
Grasping, in both biological and engineered mechanisms, can be highly sensitive to the gripper and object morphology, as well as perception and motion planning. Here we circumvent the need for feedback or precise planning by using an array of fluidically-actuated slender hollow elastomeric filaments to actively entangle with objects that vary in geometric and topological complexity. The resulting stochastic interactions enable a unique soft and conformable grasping strategy across a range of target objects that vary in size, weight, and shape. We experimentally evaluate the grasping performance of our strategy, and use a computational framework for the collective mechanics of flexible filaments in contact with complex objects to explain our findings. Overall, our study highlights how active collective entanglement of a filament array via an uncontrolled, spatially distributed scheme provides new options for soft, adaptable grasping.