Leatherbacks swimming in silico: modeling and verifying their momentum and heat balance using computational fluid dynamics.

Peter N Dudley,Riccardo Bonazza,Warren P Porter,T Todd Jones,Jeanette Wyneken,Ulrike G Munderloh

doi:10.1371/journal.pone.0110701

Peter N Dudley, Riccardo Bonazza + Show 4 more

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https://doi.org/10.1371/journal.pone.0110701

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Abstract

As global temperatures increase throughout the coming decades, species ranges will shift. New combinations of abiotic conditions will make predicting these range shifts difficult. Biophysical mechanistic niche modeling places bounds on an animal’s niche through analyzing the animal’s physical interactions with the environment. Biophysical mechanistic niche modeling is flexible enough to accommodate these new combinations of abiotic conditions. However, this approach is difficult to implement for aquatic species because of complex interactions among thrust, metabolic rate and heat transfer. We use contemporary computational fluid dynamic techniques to overcome these difficulties. We model the complex 3D motion of a swimming neonate and juvenile leatherback sea turtle to find power and heat transfer rates during the stroke. We combine the results from these simulations and a numerical model to accurately predict the core temperature of a swimming leatherback. These results are the first steps in developing a highly accurate mechanistic niche model, which can assists paleontologist in understanding biogeographic shifts as well as aid contemporary species managers about potential range shifts over the coming decades.

Highlights

Ecological niche modeling analyzes a set of environmental conditions in a location to determine the likelihood or possibility of a species’ persistence
We see that the up and down phases provide the forward force to the turtle while the top and bottom phases are a necessity to setup the other phases and provide mostly reverse thrust
We see large pressures at the top and bottom turning points most likely owing to added mass Our simulated average force (0.00488 N) was within a quarter of the standard deviation with the experimental force measurements (0.00460.003 N) (Figure 6)

Summary

Introduction

Ecological niche modeling analyzes a set of environmental conditions in a location to determine the likelihood or possibility of a species’ persistence. In addition to causing these range shifts, climate change makes predicting species future ranges difficult because it introduces regionally novel sets of abiotic conditions. With these novel circumstances, forming an empirical niche map (based on species presence/absence data and a statistical model) requires complex statistical methods and may still be inappropriate or inaccurate [2,3]. A more appropriate niche mapping approach may be mapping the fundamental niche [4] using a biophysical mechanistic niche model. A biophysical model permits any combination of abiotic conditions, novel or otherwise, provided the model can accurately represent how they affect the organism [5]

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