Adaptive Sex‐Specific Cognitive Bias in Predation Behaviours of Japanese Pygmy Squid

Abstract

Errors in decision-making in animals can be partially explained by adaptive evolution, and error management theory explains that cognitive biases result from the asymmetric costs of false-positive and false-negative errors. Error rates that result from the cognitive bias may differ between sexes. In addition, females are expected to have higher feeding rates than males because of the high energy requirements of gamete production. Thus, females may suffer relatively larger costs from false-negative errors (i.e. non-feeding) than males, and female decisions would be biased to reduce these costs if the costs of false-positive errors are not as high.Females would consequently overestimate their capacity in relation to the probability of predation success. We tested this hypothesis using the Japanese pygmy squid Idiosepius paradoxus. Our results show that size differences between the squid and prey shrimp affected predatory attacks, and that predatory attacks succeeded more often when the predator was relatively larger than the prey. Nevertheless, compared to male predatory attacks, female squid frequently attacked even if their size was relatively small compared to the prey, suggesting that the females overestimated their probability of success. However, if the females failed in the first attack, they subsequently adjusted their attack threshold: squid did not attack again if the prey size was relatively larger. These results suggest a sex-specific cognitive bias, that is females skewed judgment in decisionmaking for the first predation attack, but they also show that squid can modify their threshold to determine whether they should attack in subsequent encounters.

Optimistic and realistic perspectives on cognitive biases

“…For instance, Haselton et al 18 identify overperception of sexual interest (typically by males) as a cognitive bias, which can be explained simply by signal detection theory, as they recognise. (Similar examples abound in the animal kingdom 21,22 , including the possibility that some traits evolve to exploit existing cognitive biases in others 23,24 .) Although an interesting topic, and one that falls under a wide definition of cognitive bias 2** , this is not an explanation of sub-optimal behaviours (as identified by the authors 25 and others 26 ).…”

Pair-bonding influences affective state in a monogamous fish species

“…We used the cognitive judgement bias paradigm to objectively measure the change in the affective state of the female in the presence of her preferred or non-preferred male [5,44,48]. The rationale behind the judgement bias test is that the behavioural response to an ambiguous signal (intermediate between a positive signal and a negative signal) is a direct indicator of the positive/negative affective states of the individual [8,11,21,45]. We transposed this test to fish by training them to open boxes (figure 1b,c).…”

“…When opening the positive box, the fish were able to collect a food reward (one chironomid larva). Following recent studies [18,21,49,50], we used a box without a reward as a negative signal. Despite the absence of active punishment, opening this box is potentially associated with frustration when opening an empty box [49] and with several costs (energetic costs, time costs or exposure to predation threats) when the individual leaves its nest to approach the rear end of the tank.…”

“…An experimental session consisted of the sequential presentation of six boxes (one box at time, with 5 min between two consecutive presentations) in the following order: P, N, A, P, N and P. The judgement bias of the focal fish was estimated from the third, fourth and fifth boxes (A, P and N). The first two boxes (P and N) were reminder trials [21], and the last box (P) was used to keep the fish motivated for the next session.…”

“…Affective states are influenced by internal factors such as hunger state or hormonal level [5,23] and environmental factors such as food quality or quantity [8,21], habitat quality [7], presence of predators [21] or conspecifics [17,24]. In turn, these affective states bias decision-making [25][26][27][28].…”