Experiments with humans indicate that decision accuracy drives the evolution of niche width

Area of Science:

• Behavioral Ecology
• Cognitive Ecology
• Evolutionary Biology

Background:

• Niche specialization is common in animals, potentially due to reduced attentional load during resource seeking.
• A neural network model suggests specialists have a cognitive advantage when errors in resource selection have moderate positive fitness consequences.

Purpose of the Study:

• To empirically test the predictions of a cognitive model regarding niche specialization.
• To investigate whether decision accuracy differs between specialists and generalists under varying error-consequence conditions.

Main Methods:

• Utilized a human-computer interactive task to simulate resource-seeking behavior.
• Compared decision-making accuracy of human specialists and generalists under conditions where mistakes were rewarded versus punished.

Main Results:

• Specialist decision-makers were significantly more accurate than generalists when errors were rewarded.
• No significant difference in accuracy was observed between specialists and generalists when errors were punished.

Conclusions:

• The study empirically supports the model's prediction that cognitive advantages drive niche specialization.
• Increased decision accuracy, particularly when errors have positive fitness consequences, may be a significant factor promoting niche specialization in animals.