State-dependent risky choices in primates: Variation in energy budget does not affect tufted capuchin monkeys' (Sapajus spp.) risky choices.

Economic models predict that rational decision makers' choices between a constant, "safe" option and a variable, "risky" option leading, on average, to the same payoff, should be random. However, a wealth of research has revealed that, when faced with risky decisions, both human and nonhuman animals deviate from economic rationality. According to the risk-sensitivity theory, individuals should prefer a safe option when they are in a positive energy state and a risky option when they are in a negative energy state. The abundance/risk hypothesis proposes that individuals should prefer risky options when diet quality exceeds their nutritional requirements. We tested how energy budget affects decision making under risk by presenting 22 capuchins belonging to two colonies (IT: N = 12, US: N = 10) with a risky choice task. Capuchins had to choose between a constant option (always four food items) and a variable option (one or seven food items with a 50% probability) in two conditions. In the Low-energy condition capuchins were tested before their main meal, whereas in the High-energy condition they were tested following a high-caloric meal. In neither colony did we find a significant difference between conditions, suggesting that the energy budget did not affect risk preferences. However, we found differences between colonies in their general response to risky choices: US capuchins were more risk-prone after selecting a safe option than a risky option and after selecting a bad (one food item) than a good (seven food items) risky option, whereas this did not hold true in IT capuchins. Furthermore, in the IT colony, males were more risk-prone under the High-energy condition compared to the Low-energy condition. Subtle differences in individual characteristics, management conditions, or stochastic founder effects may be implied, with relevant consequences for the outcomes of research on risky decision-making across laboratories.