Surveying the welfare of farmed fish species on a global scale through the fair-fish database.

Fish welfare is a critical issue that needs to be addressed by the rapidly growing aquaculture industry. Scientific knowledge regarding the natural behaviors of species and the conditions in which they are kept in farms is essential for improving their welfare in aquaculture. To provide a consistent overview of the welfare of farmed fish, the organization fair-fish has created the online platform fair-fish database, which gathers ethological knowledge categorized into profiles of farmed aquatic species. The WelfareChecks on this platform are profiles based on criteria that are rated based on the likelihood and potential of the species to experience a high level of welfare in aquaculture systems, together with the certainty about the findings. A score (WelfareScore) is calculated from these ratings, serving as a reference to identify knowledge gaps, assess welfare, and suggest ways to improve it. Here, we performed an in-depth analysis of the species with WelfareChecks already published in the fair-fish database based on their respective WelfareScores. In general, although just a small percentage of farmed aquatic species (~5%) have at least a 20% chance of experiencing a good level of welfare under minimal aquaculture conditions, 60% of them have at least some potential to achieve good welfare under high-standard conditions, with more than a third of the species (~37%) having at least a 20% potential. Despite that, several species exhibit a very high frequency of low chances and potential for experiencing good welfare levels under aquaculture conditions, besides a low degree of certainty based on literature reviews. Furthermore, many others show a very frequent occurrence of unclear or nonexistent knowledge in their profiles. The current welfare state is therefore poor for the majority of farmed aquatic species; yet, there is considerable potential for improvement. However, many species are very unlikely to achieve good welfare, even under high-standard conditions. Importantly, large knowledge gaps remain for an accurate assessment of the welfare of several farmed species.

The good, the bad, and the rare: memory for partners in social interactions.

For cooperation to evolve via direct reciprocity, individuals must track their partners' behavior to avoid exploitation. With increasing size of the interaction group, however, memory becomes error prone. To decrease memory effort, people could categorize partners into types, distinguishing cooperators and cheaters. We explored two ways in which people might preferentially track one partner type: remember cheaters or remember the rare type in the population. We assigned participants to one of three interaction groups which differed in the proportion of computer partners' types (defectors rare, equal proportion, or cooperators rare). We extended research on both hypotheses in two ways. First, participants experienced their partners repeatedly by interacting in Prisoner's Dilemma games. Second, we tested categorization of partners as cooperators or defectors in memory tests after a short and long retention interval (10 min and 1 week). Participants remembered rare partner types better than they remembered common ones at both retention intervals. We propose that the flexibility of responding to the environment suggests an ecologically rational memory strategy in social interactions.

Forgetting constrains the emergence of cooperative decision strategies.

Theoretical studies of cooperative behavior have focused on decision strategies that depend on a partner's last choices. The findings from this work assume that players accurately remember past actions. The kind of memory that these strategies employ, however, does not reflect what we know about memory. Here, we show that human memory may not meet the requirements needed to use these strategies. When asked to recall the previous behavior of simulated partners in a cooperative memory task, participants performed poorly, making errors in 10-24% of the trials. Participants made more errors when required to track more partners. We conducted agent-based simulations to evaluate how well cooperative strategies cope with error. These simulations suggest that, even with few errors, cooperation could not be maintained at the error rates demonstrated by our participants. Our results indicate that the strategies typically used in the study of cooperation likely do not reflect the underlying cognitive capacities used by humans and other animals in social interactions. By including unrealistic assumptions about cognition, theoretical models may have overestimated the robustness of the existing cooperative strategies. To remedy this, future models should incorporate what we know about cognition.