Back

Collective movement of schooling fish reduces locomotor cost in turbulence

zhang, y.; Ko, H.; Calicchia, M. A.; Ni, R.; Lauder, G.

2024-01-22 physiology
10.1101/2024.01.18.576168 bioRxiv
Show abstract

The ecological and evolutionary benefits of collective behaviours are rooted in the physical principles and physiological mechanisms underpinning animal locomotion. We propose a turbulence sheltering hypothesis that collective movements of fish schools in turbulent flow can reduce the total energetic cost of locomotion by shielding individuals from the perturbation of chaotic turbulent eddies. We test this hypothesis by quantifying energetics and kinematics in schools of giant danio (Devario aequipinnatus) compared to solitary individuals swimming under control and turbulent conditions over a wide speed range. We discovered that, when swimming at high speeds and high turbulence levels, fish schools reduced their total energy expenditure (TEE, both aerobic and anaerobic energy) by 63-79% compared to solitary fish. Solitary individuals spend [~]25% more kinematic effort (tail beat amplitude*frequency) to swim in turbulence at higher speeds than in control conditions. However, fish schools swimming in turbulence reduced their three-dimensional group volume by 41-68% (at higher speeds) and did not alter their kinematic effort compared to control conditions. This substantial energy saving highlighted a [~]261% higher TEE when fish swimming alone in turbulence are compared to swimming in a school. Schooling behaviour could mitigate turbulent disturbances by sheltering fish within schools from the eddies of sufficient kinetic energy that can disrupt the locomotor gaits. Providing a more desirable internal hydrodynamic environment could be one of the ecological drivers underlying collective behaviours in a dense fluid environment. One-Sentence SummaryThe collective movement of fish schools substantially reduces the energetic cost of locomotion in turbulence compared to that of swimming alone.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Journal of The Royal Society Interface
189 papers in training set
Top 0.1%
41.2%
2
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 0.6%
8.8%
50% of probability mass above
3
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 10%
6.7%
4
eLife
5422 papers in training set
Top 12%
6.7%
5
Mathematical Biosciences
42 papers in training set
Top 0.2%
4.5%
6
Scientific Reports
3102 papers in training set
Top 30%
4.0%
7
Biological Cybernetics
12 papers in training set
Top 0.1%
2.2%
8
Current Biology
596 papers in training set
Top 7%
2.2%
9
Royal Society Open Science
193 papers in training set
Top 1%
2.2%
10
PLOS Computational Biology
1633 papers in training set
Top 17%
1.6%
11
Journal of Experimental Biology
249 papers in training set
Top 2%
1.6%
12
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 0.6%
1.2%
13
Physical Review Research
46 papers in training set
Top 0.6%
1.0%
14
PNAS Nexus
147 papers in training set
Top 0.8%
1.0%
15
Nature Communications
4913 papers in training set
Top 58%
1.0%
16
PLOS ONE
4510 papers in training set
Top 65%
0.8%
17
Physical Review E
95 papers in training set
Top 1%
0.8%
18
Cell Reports
1338 papers in training set
Top 32%
0.8%
19
Bulletin of Mathematical Biology
84 papers in training set
Top 2%
0.8%
20
Biophysical Journal
545 papers in training set
Top 5%
0.8%
21
iScience
1063 papers in training set
Top 39%
0.5%
22
Frontiers in Physiology
93 papers in training set
Top 7%
0.5%