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Risk-sensitive foraging in a tropical lizard.

Avik Banerjee1, Maria Thaker1

  • 1Centre for Ecological Sciences, Indian Institute of Science, Bengaluru, India.

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Summary

Tropical lizards adjust foraging behavior based on hunger. Starved lizards take risks for potentially larger food rewards, while full lizards prefer predictable meals, demonstrating risk-sensitive foraging in reptiles.

Keywords:
energy budgetoptimal foraging theoryreptilerisk averserisk pronestarvation

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Area of Science:

  • Behavioral Ecology
  • Zoology
  • Physiological Ecology

Background:

  • Foraging decisions are influenced by resource predictability and an animal's physiological state.
  • Risk-sensitive foraging theory suggests animals take greater risks when starving.
  • This theory is less explored in reptiles compared to other animal groups.

Purpose of the Study:

  • To test risk-sensitive foraging theory in the tropical lizard, *Psammophilus dorsalis*.
  • To investigate how energy budgets (satiated vs. starved) affect foraging choices between constant and variable food rewards.

Main Methods:

  • Experimental manipulation of lizard energy budgets (satiated or 48-hour starved).
  • Measurement of foraging preferences between constant (2 mealworms) and variable (0 or 4 mealworms) food options.
  • Analysis of foraging strategies in relation to reward predictability and physiological state.

Main Results:

  • Satiated lizards exhibited risk-averse behavior, preferring the constant food reward.
  • Starved lizards displayed risk-prone behavior, choosing the variable food option more often.
  • Both starved and satiated groups achieved similar net resource gains, indicating adaptive strategies.

Conclusions:

  • The study provides evidence for risk-sensitive foraging in a tropical reptile species (*Psammophilus dorsalis*).
  • Resource uncertainty significantly influences foraging strategies in lizards based on their physiological state.
  • Risk-sensitive foraging may be a crucial strategy for tropical lizards with high energy demands in unpredictable environments.