Dipteran flight diversity is shaped by aerodynamic constraints, scaling, and evolutionary trade-offs

Abstract

Flight has been a key innovation in insect evolution, yet the selective and mechanistic pressures shaping their flight motor systems remain poorly understood. Here, we present a comprehensive comparative analysis of flight in Diptera (true flies), integrating morphology, wingbeat kinematics, and aerodynamics within a phylogenetic framework. We quantified morphology in 133 species spanning the Dipteran phylogenetic and size range, and for a subset of 46 species, we combined high-speed stereoscopic videography with computational fluid dynamics (CFD) to characterize wingbeat kinematics and aerodynamic performance, respectively

Introduction

Insects are the most species-rich class of animals, comprising an estimated 5 million species—about 80% of all known animal species. Their remarkable radiation may be partly attributed to their flight ability, which has led to a striking diversity of aerial lifestyles. Despite the pivotal role that flight has played in the evolution and ecological importance of insects, our understanding of the evolutionary processes that generate the diversity of their flight kinematics, morphology, and associated aerodynamics remains limited.

Materials and methods

Insect sampling

We quantified diversity in dipteran flight motor systems by sampling 133 species across 43 families spanning both Diptera’s phylogeny and body size range . Most species (n = 94) were collected near Wageningen University, the Netherlands (  N,   E; altitude ca. 10 m) during the summers of 2021 and 2022. Additional sampling in the Amazonian rainforest of French Guiana (  N,   W; altitude ca. 300 m) in July 2021 yielded 36 species.

Assessing the influence of phylogeny on morphological and flight traits

We tested whether evolutionary relatedness among Diptera influences variation in morphology and wingbeat kinematics by quantifying phylogenetic signal using Blomberg’s K for each parameter and its multivariate extension. Analyses were performed in phytools using the Diptera phylogeny of Wiegmann and colleagues, pruned to the species in our datasets 

Computational fluid dynamics simulations

We quantified aerodynamic forces and torques using full-DNS CFD simulations of a rigid, flat wing executing species-specific wingbeat kinematics. Each simulation used the measured wing outline and imposed the recorded wingbeat time series. 

Results

Morphological and kinematic diversity in Diptera

To evaluate our three primary objectives, (i) the effect of aerodynamic constraints on kinematic diversity, (ii) the scaling of morphology, kinematics and aerodynamics with size, and (iii) the trade-off between flight cost minimization and acoustic signaling, we first quantified the range of phenotypic variation in Diptera.We investigated morphological diversity across 133 Diptera species and flight kinematic diversity in a subset of 46 species

Article information

Citation: Le Roy C, Bharathi I, Engels T, Muijres FT (2026) Dipteran flight diversity is shaped by aerodynamic constraints, scaling, and evolutionary trade-offs. PLoS Biol 24(7): e3003473. https://doi.org/10.1371/journal.pbio.3003473

Academic Editor: Abderrahman Khila, Centre National de la Recherche Scientifique, FRANCE

Received: October 1, 2025; Accepted: May 26, 2026; Published: July 9, 2026

Copyright: © 2026 Le Roy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data underlying the findings of this study are fully available without restriction. The complete datasets used in the analyses are deposited in the Dryad Digital Repository under https://doi.org/10.5061/dryad.gxd25480s. The repository includes wing morphology, wingbeat kinematics, and CFD-derived aerodynamic forces and power for all studied species. It also contains all custom code used to generate the study figures from the deposited data, as well as CFD parameter files, microscope images, and representative high-speed videos for our studied species. In addition, the repository provides an interactive tool that allows users to filter, visualize, and export the processed data or selected subsets. This tool is also accessible via an online interface at https://insectflight.eu. DNA barcode data for all analyzed specimens are publicly available through the BOLD System under project DIPTR via https://portal.boldsystems.org/result?query=DIPTR. The version of the WABBIT code used for the numerical simulations is archived on Zenodo and available via https://doi.org/10.5281/zenodo.20234346. No ethical or legal restrictions apply to the sharing of these data.

Funding: This work was supported by an NWO Vidi research grant to F.T.M. (I/VI.Vidi.193.054; www.nwo.nl). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.
Abbreviations: CFD, computational fluid dynamics; PGLS, phylogenetic generalized least squares; Re, Reynolds number.