Herbivorous Fish Feeding Dynamics and Energy Expenditure on a Coral Reef: Insights From Stereo-Video and AI-driven 3D Tracking
Date
Authors
Lilkendey, Julian
Barrelet, Cyril
Zhang, Jingjing
Meares, Michael
Larbi, Houssam
Subsol, Gérard
Chaumont, Marc
Sabetian, Armagan
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Wiley
Abstract
Unveiling the intricate relationships between animal movement ecology, feeding behavior, and internal energy budgeting is crucial for a comprehensive understanding of ecosystem functioning, especially on coral reefs under significant anthropogenic stress. Here, herbivorous fishes play a vital role as mediators between algae growth and coral recruitment. Our research examines the feeding preferences, bite rates, inter-bite distances, and foraging energy expenditure of the Brown surgeonfish (Acanthurus nigrofuscus) and the Yellowtail tang (Zebrasoma xanthurum) within the fish community on a Red Sea coral reef. To this end, we used advanced methods such as remote underwater stereo-video, AI-driven object recognition, species classification, and 3D tracking. Despite their comparatively low biomass, the two surgeonfish species significantly influence grazing pressure on the studied coral reef. A. nigrofuscus exhibits specialized feeding preferences and Z. xanthurum a more generalist approach, highlighting niche differentiation and their importance in maintaining reef ecosystem balance. Despite these differences in their foraging strategies, on a population level, both species achieve a similar level of energy efficiency. This study highlights the transformative potential of cutting-edge technologies in revealing the functional feeding traits and energy utilization of keystone species. It facilitates the detailed mapping of energy seascapes, guiding targeted conservation efforts to enhance ecosystem health and biodiversity.Description
Keywords
artificial intelligence, functional traits, metabolic traits, movement ecology, surgeonfish, 41 Environmental Sciences, 31 Biological Sciences, 3103 Ecology, 4104 Environmental Management, 0602 Ecology, 0603 Evolutionary Biology, 3104 Evolutionary biology, 4102 Ecological applications
Source
Ecology and Evolution, ISSN: 2045-7758 (Print); 2045-7758 (Online), Wiley, 14(3), e11070-. doi: 10.1002/ece3.11070
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© 2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.