How do foragers decide when to leave a patch? A test of alternative models under natural and experimental conditions

1. A forager’s optimal patch-departure time can be predicted by the prescient marginal value theorem (pMVT), which assumes they have perfect knowledge of the environment, or by approaches such as Bayesian-updating and learning rules, which avoid this assumption by allowing foragers to use recent experiences to inform their decisions. 2. In understanding and predicting broader scale ecological patterns, individual-level mechanisms, such as patch-departure decisions, need to be fully elucidated. Unfortunately, there are few empirical studies that compare the performance of patch-departure models that assume perfect knowledge with those that do not, resulting in a limited understanding of how foragers decide when to leave a patch. 3. We tested the patch-departure rules predicted by fixed-rule, pMVT, Bayesian-updating and learning models against one another, using patch residency times recorded from 54 chacma baboons (Papio ursinus) across two groups in natural (n = 6,594 patch visits) and ...

1. 觅食者的最优斑块离开时间，可通过预知性边际价值定理（prescient marginal value theorem, pMVT）进行预测——该定理假设觅食者完全知晓环境信息；亦可通过贝叶斯更新、学习规则等方法实现预测，这类方法无需假设觅食者掌握完美环境知识，而是允许其借助近期经验辅助决策。
2. 在理解和预测大尺度生态格局的过程中，诸如斑块离开决策这类个体层面的行为机制需要得到充分阐明。然而，目前鲜有实证研究对比假设完美环境知识的斑块离开模型与无需该假设的模型的性能表现，这导致学界对觅食者如何决策离开斑块的机制仍缺乏深入认知。
3. 本研究以自然生境中两个种群的54只南非大狒狒（*Papio ursinus*）的斑块停留时长记录（共计6594次斑块到访）为数据基础，对比检验了固定规则模型、pMVT模型、贝叶斯更新模型以及学习模型所预测的斑块离开规则，相关数据涵盖……