Abstract Knowing where to find what kind of food, and when, is essential for survival and reproduction. Studying animals’ foraging strategies thus provides insights into the cognitive processes underlying real-world problem solving. We investigated whether free-ranging Guinea baboons ( Papio papio ) keep track of the spatio-temporal availability of a preferred food resource, the Natal orange ( Strychnos spinosa ). An exceptional wildfire that destroyed most ripe fruits in 2019 provided a quasi-experimental opportunity to assess whether Guinea baboons flexibly adjusted their space use to an unexpected change in resource availability or instead continued to follow habitual routines. The animals’ space use patterns shifted significantly following the wildfire. After one single visit, they stopped going to the area during the period when Natal oranges would normally be available. In the following year, when Natal oranges were available again, the baboons resumed regular space use patterns. We also assessed travel linearity, speed, and departure time from sleeping sites towards the target area with and without ripe fruit. Guinea baboons travelled more linearly, 14% faster, and ca. 40 min earlier toward the target area when S. spinosa was in season than when it was not. In conclusion, Guinea baboons rapidly adjusted their space use patterns in response to changes in the availability of a high-value food resource. These results underscore their capacity for flexible, reward-sensitive decision-making and goal-directed foraging.
We review 58 experiments about "intuitive statistics" in mammals and birds, which investigate the animals' ability to make productive decisions when actions have probabilistic outcomes. We show that a stimulus-response associative model closely mirrors the animals' choices. The model reproduces qualitatively all results, and it accounts for an average 88% of the variance in 10 quantitative fits to data from 37 experiments with birds and mammals. The unexplained variance does not indicate processes more sophisticated than stimulus-response learning, as it either lies within measurement error or derives from animals making more mistakes than the stimulus-response model. These results confirm that associative learning models are a powerful tool in animal cognition research, often capable of unmatched quantitative accuracy. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
ما ۵۸ آزمایش درباره «آمار شهودی» در پستانداران و پرندگان را مرور می‌کنیم که توانایی حیوانات در اتخاذ تصمیمات سازنده زمانی را که اقدامات پیامدهای احتمالی دارند، بررسی می‌کنند. ما نشان می‌دهیم که یک مدل اتّصال محرک-پاسخ به‌خوبی انتخاب‌های حیوانات را بازتولید می‌کند. این مدل به‌طور کیفی تمام نتایج را بازتولید می‌نماید و میانگین ۸۸ درصد از واریانس در ۱۰ برازش کمی به داده‌های حاصل از ۳۷ آزمایش با پرندگان و پستانداران را تبیین می‌کند. واریانس تبیین‌نشده نشان‌دهنده فرآیندهای پیچیده‌تر از یادگیری محرک-پاسخ نیست، زیرا یا درون خطای اندازه‌گیری قرار دارد یا ناشی از آن است که حیوانات خطاهای بیشتری نسبت به مدل محرک-پاسخ مرتکب می‌شوند. این نتایج تأیید می‌کنند که مدل‌های یادگیری اتّصالی ابزار قدرتمندی در پژوهش‌های شناخت حیوانی هستند و اغلب قادر به دقت کمی بی‌نظیری می‌باشند. (ثبت پایگاه داده PsycInfo (c) ۲۰۲۶ APA، تمامی حقوق محفوظ است).
