Smart Organisms Use Physics to Find Their Food
Photo by W. van Egmond
Li presented a paper on the topic at the 2007 APS March Meeting in Denver. For instance, scientists previously assumed that microbes move in random patterns unless they are specifically hot on the scent of tasty nibbles. Yet Li has found that species of amoeba called Dictyostelium seem to remember its previous “steps” and use that remembered information to explore new ground, thereby increasing their chances of finding food.
How can such a simple organism have any kind of memory at all? Li thinks there may be a clue in the mechanism by which the creature moves: namely, by rearranging its body into protruding shapes known as pseudopods.
Using phase contrast microscopy, Li tracked a teeming sample of Dictyostelium over 100 hours, charting the “runs” and “turns” they made, which formed a zigzag pattern of motion. She specifically looked at how often the creatures made a left turn followed by a right turn, and found they showed a clear bias for that kind of variation.
Li reported that the formation of pseudopods leaves temporary “scars” in the cell’s cytoskeleton, and this makes it far more likely that the next pseudopod the creature forms will point in a new direction. Because it changes direction and doesn’t retrace its steps, it covers more ground and increases its chances of finding food.
More complex, higher organisms, like zooplankton, have also evolved a highly efficient hunting strategy. Ricardo Garcia, with the Center for Neurodynamics at the University of Missouri in St. Louis, talked about his research on the role of specific swimming characteristics in achieving optimal food foraging strategies for zooplankton. The work is the first observation in a living animal of an inherent swimming characteristic–the turning angle–that optimizes the food obtained in a patch of fixed size for an organism foraging for a fixed time.
Garcia and his colleague, Frank Moss, studied the zooplankton Daphnia, more commonly known as water fleas. They looked at the swimming movements of five different Daphnia species of varying sizes, all of which exhibit a distinct hop-pause-turn-hop sequence while swimming. They analyzed the turning angles the creatures made after each hop in the sequence, plotting the number of times a given angle was observed on a histogram.
These turning angles were almost, but not quite, completely random–they found evidence of a preferred turning angle value, based on a mathematical analysis of the underlying random processes, or intensity of the “neural noise” in the water fleas.
Scientists have known for many years that biological systems frequently rely on stochastic resonance as a stimulus to the sensory systems, which in turn can affect the behavior of creatures both great and small–usually in positive, optimizing ways that improve the creatures’ chances or survival. The neural noise of water fleas influences the turning angle in such a way as to enable the creature to explore the most amount of space and gather the most food within a given time frame.
The observed noise intensities correlate with the width of distribution of the turning angles favored by the water fleas, and it turns out that the creatures gather the most amount of food in a single foraging session at a very specific noise intensity. “A small noise intensity means that the animal obtains less than the maximum possible amount of food within its patch during its fixed feeding time,” said Garcia. “Likewise, less food is ingested if the distribution is too broad.” The findings were consistent across all five species of Daphnia studied, regardless of size or age of the organisms.
Garcia suspects that this natural stochastic resonance may have a played a significant role in the evolution of sensory systems, although he is careful to emphasize that his results don’t outright prove this hypothesis; they merely offer strong supporting evidence in favor of that notion. In the case of Daphnia, Garcia believes that the water flea’s distinctive swimming patterns evolved over tens to hundreds of millions of years via Darwinian natural selection.
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