Herbivorous fish feeding dynamics and energy expenditure on a coral reef: Insights from stereo-video and AI-driven 3D tracking

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.

Keywords: artificial intelligence; functional traits; metabolic traits; movement ecology; surgeonfish.

FIGURE 1

Detection of the checkboard pattern on the back of the calibration frame in Matlab.

FIGURE 2

The calibration frame in a stereorectified frame pair in OpenCV.

FIGURE 3

Performance of automatic object detection (a) before and (b) after background subtraction.

FIGURE 4

Percentage of total bites and mean (±Standard Error) feeding rate, biomass, and feeding pressure for all fish species recorded in 45 min of video per stereo‐video rack placement. Footage was obtained on a coral reef in Eilat, Gulf of Aqaba, Red Sea.

FIGURE 5

Feeding preferences of the two study surgeonfish species on a coral reef in Eilat, Gulf of Aqaba, Red Sea. EAT, epilithic algae turf.

FIGURE 6

Violin plots of manually determined bite distances and bite rates of the two study surgeonfish species on a coral reef in Eilat, Gulf of Aqaba, Red Sea. The asterisk indicates a significant difference.

FIGURE 7

Violin plots showcasing mean velocities and rates of energy expenditures during foraging, based on artificial intelligence‐generated three‐dimensional fish trajectories for Acanthurus nigrofuscus and Zebrasoma xanthurum. Stereo‐video footage was captured in Eilat, Red Sea, Israel.

FIGURE A1

Relative benthic cover of substrates ± Standard Error across all 9 1 × 1 m study quadrats.

FIGURE A2

Total length frequencies of the focal species on a coral reef in Eilat, Gulf of Aqaba, measured manually using VidSync (a) and measured by object recognition driven by artificial intelligence in individuals used for this study (b).