(WOOD) – With the changing trees and tumbling temperatures, many look to nature for hints about the winter to come. But how reliable are these old wives’ tales?
Many have been noticing abnormalities this year, especially with tree nuts.
However, experts with Mass Audubon say nut production by oak trees has nothing to do with the incoming winter; the yield is cyclical.
Every two to five years, a tree will produce a bumper crop of nuts. Trees want to produce young trees, which can only happen if scavengers don’t eat all their nuts. An abundant drop of acorns or walnuts ensures new trees will be planted every few years.
One of the most widespread tales pertains to the big furry coat of the woolly bear caterpillar.
The old tale goes like this: the thickness of the brown stripe on the caterpillar will tell you how harsh the upcoming winter will be. If there is a lot of brown, the winter will be mild; If there is only a narrow strip of brown on their backs, expect a harsh winter.
There has actually been some research pertaining to this old wives’ tale. Dr. C.H. Curran, former curator of insects at the American Museum of Natural History in New York City, surveyed the bugs back in the 1950s. His studies showed that the woolly bear caterpillars had an 80 percent accuracy rate. However, today’s entomologists say no one has been able to replicate the study.
Current insect experts agree that woolly bear caterpillars are not accurate predictors of winter weather. Many variables may contribute to changes in the caterpillar’s coloration, including larval stage, food availability, the temperature or moisture during their development, age, and even species.
And don’t be fooled: all-black fuzzy caterpillars aren’t woolly bear caterpillars at all. They are a slightly different species that transforms into the giant leopard moth.
The old wives’ tales related to winter don’t stop there. Some so-called predictors are the thickness of animals’ fur, the height of wasp nests in trees, and the early migration of birds.
However, these stories aren’t studied as heavily, so it’s difficult to know how accurate they are.
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