Think of your favorite little furry animal. It burns energy all the time in order to stay alive. In order to get more energy, it must travel to places where it can find something to eat. It will spend time at those places, foraging for food and eating. Either when it is satiated, or when the cost of trying to get more food out of a given source becomes too high, it will move on to another food source.
It will have to scurry a certain distance to get to that food source. If this distance is high, then animal is in trouble for it will have little energy left by the time it gets there. If the distance is low, then the creature can be rightfully said to be “fat, dumb, and happy.”
What I just described is broadly an example of “foraging behavior”, something studied by ecologists. These are scientists out there who track animals and watch how they manage the problem of finding food and staying alive.
It probably does not take too much imagination to see how foraging behavior relates back to soaring. A pilot forages for energy by finding thermals, but instead of metabolizing energy biologically, he simply glides it out to the next thermal source. He forages for sites that are worth his time; thermals that are too far away, too weak or the like are not worth the trouble (usually!).
Even some equations in foraging theory have direct similarity to soaring, such as the prescient Marginal Value Theorem (pMVT). This dictates that given perfect information the time to leave a foraging source is when an alternative future source will provide more energy than in the immediate present state. This sounds a lot like MC theory! Leave the current thermal when your climb rate gets below the average expected climb rate for your next thermal. And interestingly enough, this model does a pretty good job of describing the point at which animals leave to a future foraging site.
So looking at foraging behavior, it provides another good analogy as to how glider pilots manage the optimization of climbing and leaving a thermal. Exploit lift until it gets weaker than a future thermal. Explore for an alternative once you cross a given threshold. Simple enough.
However, things get interesting when you start fiddling with the distance between foraging sites. For instance, suppose that there is no possibility of finding any more food beyond this point. It’s winter and your furry animal is at the last food source available. The conclusion is to tank up as much as possible and hope that this will last the creature through the dry spell. This is a similar deal when you have a distance day on a thermal flight and you’re in the last, weak bubble of the day. Take as much as you get and accept that this the best you will do.
But what happens when you’re not really sure whether there will be food at the next foraging sites or not? You go from place to place and you find one empty and another one too. You might even run out of energy and starve!
Suppose you recognize that there is a reasonable possibility that all possible foraging sites may run out while you’re still at a food source. How would this change your behavior?
My guess is that you would take everything you can get out of current foraging sites, accepting greater costs to do so. Your furry animal will eat every scrap off food here, even if its more work to do so. If you look ahead and see a sky that’s decaying and you suspect that this thermal may be your last, then you will be motivated to stay in it, even if its weak. And you will probably do the same thing in the next and subsequent thermal, should you find them and you still judge the conditions to be tricky.
The point is that when the distance that you traverse from a thermal to another thermal is uncertain and may even exceed the total energy you have available, the decision-making is much less straightforward than when you assume you will find a thermal and your goal is to simply optimize the current glide. For people who have followed my writing, this goes back to “Gear Shifting” and my work with John Bird on Bounded Rationality and Risk Strategy in Thermal Soaring. But I figured that this foraging example may be another way to look at risk management in thermal soaring using perhaps intuitive examples and fiddling with their variables.