Spatio-temporal distribution of Gymnocypris przewalskii during migration with UAV-based photogrammetry and deep neural network

Abstract The naked carp (Gymnocypris przewalskii) plays a central role in the ecosystem of the Qinghai Lake, the largest saline-alkaline lake in China. The adult naked carp migrates in large groups with high population density annually from the Qinghai Lake to the upstream freshwater rivers to spawn. Nevertheless, the responsiveness of the fish to local abiotic cues in the form of distribution patterns during migration across the riverine-lacustrine network of the Qinghai Lake region remains unknown. This knowledge gap has reduced efficiency in fish conservation and management efforts in the region. To address this issue, we carried out two field surveys from June to August, 2018, with the aid of unmanned aerial vehicles to a 200-m long back channel characterizing diverse morphological and hydraulic features on the migration route. Combined structure from motion photogrammetry and deep neural network techniques were used to establish a new workflow for detecting and extracting the profiles of fish individuals in large schools. The spatio-temporal distribution pattern of the fish demonstrated that the naked carp was attracted by hydraulic environments with high flow velocity or deep-water during migration. The diurnal variation of temperature and light could alter the preference for hydraulic environments of the fish. Our results highlight the crucial role of the interactions between river morphology and hydraulics, water temperature and light on the migration behaviours of the naked carp.