Winds and tides might not be the only ocean-mixing factors affecting climate change; two scientists from the California Institute of Technology say marine-dwelling creatures could also have a significant impact as they swim through the seas.

Researchers Kakani Katija and John Dabiri at the California Institute of Technology have developed a way to estimate the extent of “biogenic” mixing by marine animals. After conducting field measurements on swimming jellyfish, they built models of how animals mix the waters ocean-wide and concluded that the effect may be extensive.

“Swimming animals may contribute to ocean mixing on the same level as winds and tides,” Katija said. “This necessitates the inclusion of biogenic mixing sources in ocean circulation and global climate models.”

Katija will present those findings at this week’s annual meeting of the American Physical Society’s (APS) Division of Fluid Dynamics in Minneapolis.

Most of biogenic mixing is due to the displacement created by the movement of animal bodies through the water, rather than by the turbulence stirred up by fish as they swim. This displacement is found to depend primarily on the shape of the animal rather than the dynamics of the animal’s swimming motion.

Moreover, Katija said only a small part of the mixing comes from the mighty creatures that inhabit the deep. Most of it is due to meeker, but much more plentiful, animals — the tiny krill, copepods and other small critters that make up the vast majority of organisms swimming in the ocean.

Understanding ocean mixing is of fundamental importance to modeling climate change or predicting the effects of an El Niño on our weather. Modern ocean models primarily incorporate the effects of winds and tides. However, they have not generally taken into account the mixing generated by swimming animals.

Oceanographers first predicted more than 60 years ago that the effect of swimming animals could be profound. Accounting for this effort has proven difficult, though, so it has not yet entered into today’s climate models.

Tags: climate models