Unearthing underground predators: The head morphology of larvae of the moth lacewing genus Ithone Newman (Neuroptera: Ithonidae) and its functional and phylogenetic implications
2022
Li, Di | Friedrich, F. D. | Jandausch, Kenny | Pohl, Hans | Liu, Xingyue | Beutel, Rolf G.
Moth lacewings (Ithonidae) are a rare group of Neuroptera with an unusual subterranean larval life‐style. We examined external and internal head structures of an older‐instar larva of Ithone Newman with a broad spectrum of techniques. Larval autapomorphies, likely correlated with the subterranean habits, are the compact and shovel‐shaped head, unusually massive mandibular‐maxillary stylets, and a C‐shaped postcephalic body. Other cephalic autapomorphies are the massive X‐shaped tentorium, incurved antennae, and a strongly developed M. verticopharyngalis. The visual organs are distinctly simplified but a single functional stemma on each side of head is retained despite of the subterranean habits. In contrast to previous studies, a well‐developed gular sclerite is present in Ithonidae, possibly a secondary acquisition. A cephalic gland complex and poison channel are present, with an unexpected additional lateral accessory gland and an additional lateral channel. The poison glands and dual channels very clearly indicate that the larvae are predators, contradicting the phytophagous habits formerly postulated. Compared with soil‐inhabiting scarabaeoid beetle larvae, striking differences of head structures are due to different feeding habits and phylogenetic constraints. Morphological similarities like a C‐shaped postcephalic body and strongly developed legs suitable for burrowing in soil are evolutionary parallels associated with the subterranean life‐style in the two non‐related groups. Bayesian phylogenetic analysis was carried out with an updated morphological matrix. The results were compared with a phylogeny based on anchored hybrid enrichment data. The evolutionary transformations of selected characters were evaluated using phylogenies estimated from both datasets.
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