Department of Integrative Biology, Michigan State University, East Lansing, Michigan, United States of America.
Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, Michigan, United States of America.
PLoS One. 2022 Jun 10;17(6):e0269522. doi: 10.1371/journal.pone.0269522. eCollection 2022.
Group hunting is common among social carnivores, and mechanisms that promote this behavior are a central topic in evolutionary biology. Increased prey capture success and decreased losses from competitors are often invoked as factors promoting group hunting. However, many animal societies have linear dominance hierarchies where access to critical resources is determined by social rank, and group-hunting rewards are shared unequally. Despite this inequality, animals in such societies cooperate to hunt and defend resources. Game theoretic models predict that rank and relative rewards from group hunting vs. solitary hunting affect which hunting strategies will evolve. These predictions are partially supported by empirical work, but data needed to test these predictions are difficult to obtain in natural systems. We use digital evolution to test how social rank and tolerance by dominants of subordinates feeding while sharing spoils from group hunting influence which hunting strategies evolve in digital organisms. We created a computer-simulated world to reflect social and hunting dynamics of spotted hyenas (Crocuta crocuta). We found that group hunting increased as tolerance increased and as the relative payoff from group hunting increased. Also, top-ranking agents were more likely to group hunt than lower-ranking agents under despotic sharing conditions. These results provide insights into mechanisms that may promote cooperation in animal societies structured by dominance hierarchies.
群体狩猎在社会性捕食者中很常见,促进这种行为的机制是进化生物学中的一个核心话题。增加猎物捕获成功率和减少来自竞争者的损失通常被认为是促进群体狩猎的因素。然而,许多动物社会具有线性的统治等级制度,其中关键资源的获取取决于社会等级,并且群体狩猎的奖励是不平等分配的。尽管存在这种不平等,这些社会中的动物仍然会合作进行狩猎并保护资源。博弈论模型预测,等级和群体狩猎相对于单独狩猎的相对奖励会影响哪些狩猎策略会进化。这些预测在一定程度上得到了实证工作的支持,但在自然系统中获得测试这些预测所需的数据是困难的。我们使用数字进化来测试在共享群体狩猎的战利品时,统治阶层对下属进食的容忍度和统治阶层的容忍度如何影响数字生物中进化出的狩猎策略。我们创建了一个计算机模拟的世界,以反映斑点鬣狗(Crocuta crocuta)的社会和狩猎动态。我们发现,随着容忍度的增加和群体狩猎的相对收益的增加,群体狩猎的比例也增加了。此外,在专制分配条件下,高等级的代理比低等级的代理更有可能进行群体狩猎。这些结果为理解可能促进由统治等级制度构成的动物社会中的合作的机制提供了线索。