In a particular case of secondary succession, three species of wild grass all invaded a field. By the second season, a single species dominated the field and the other two species had a lower relative abundance. A possible factor contributing to the abundances of these species in this example of secondary succession is inhibition
<h3>What is
inhibition ?</h3>
In psychology, inhibition is the conscious or unconscious restraint or restriction of a process or behavior, particularly of urges or wants. The ability to inhibit oneself from acting on some impulses, such as the desire to hit someone in a fit of rage, and the ability to postpone the enjoyment of enjoyable activities, all serve important social functions. Conscious inhibition occurs frequently in daily life and appears whenever two opposing urges are felt (e.g., the desire to eat a rich dessert versus the desire to lose weight).
According to psychoanalytic theory, inhibition serves as a mediator between the superego (the conscience) and the id (primitive desires). Taboos are socially imposed inhibitions that are raised to the level of prohibition, such as those against incest or murder.
To learn more about inhibition from the given link:
brainly.com/question/13661646
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Snakes might eat grains but it also eats grasshoppers that makes it a consumer.
Frogs eat grasshoppers also and similarly it is also a consumer.
A person might say that from this the answer surely is "both eat grasshoppers"
But the answer is "both are consumers" since eating of grasshoppers is a feature of consumers.
Please mark me as brainliest.
"The Feynman Technique is a mental model that was coined by Nobel-prize winning physicist Richard Feynman. Known as the "Great Explainer," Feynman was revered for his ability to clearly illustrate dense topics like quantum physics for virtually anybody."
Answer:
Recurrent Neural Network (RNN)
Explanation:
Recurrent Neural Network (RNN) is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. This makes them applicable to tasks such as unsegmented connected handwriting recognition or speech recognition.
