Morphological adaptations of cavefish support enhanced hydrodynamic perception for underwater environmental monitoring.

Abstract

Many of Earth's most biodiverse and biogeochemically active aquatic ecosystems-including groundwater karst systems, turbid estuaries and the deep ocean-are perpetually dark and hydraulically complex, making long-term, high-resolution monitoring technologically challenging. Conventional optical and acoustic sensors suffer rapid signal attenuation and high energy demand in these conditions. Cavefishes of the genus <i>Sinocyclocheilus</i>, which inhabit lightless subterranean waters, have evolved distinctive cranial morphologies-a duckbilled head, dorsal horn and hump-hypothesized to enhance hydrodynamic perception. Here we show, by combining vital staining of neuromasts with validated computational fluid dynamics simulations across a morphological series of <i>Sinocyclocheilus</i> species, that these structures dramatically amplify differential pressure signals (by up to 429.8%) and near-wall velocity gradients (by up to 69.2%) while extending perceptual range. Regions of maximal hydrodynamic variation predicted by the models closely match the observed distribution of canal and superficial neuromasts, revealing a clear biomimetic design principle: sensors should be positioned where flow-field gradients are strongest. These findings establish a quantitative, evolution-guided framework for optimizing artificial lateral line (ALL) sensor arrays, enabling autonomous underwater vehicles to perform energy-efficient, high-fidelity monitoring in some of the planet's most sensitive and data-scarce aquatic environments.