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May 17 2025
3In the diverse world of wildlife—where some animals hunt, others flee, and many live cooperatively—behavior may appear endlessly varied. Yet, a groundbreaking new study suggests that a common structure underlies the daily actions of very different mammals, offering fresh insight into how animals operate in the wild.
Researchers from the Max Planck Institute of Animal Behavior, along with an international team of fourteen scientists, have uncovered striking similarities in how three distinct species—meerkats in the Kalahari desert, coatis in Panama’s rainforest, and spotted hyenas in Kenya’s savanna—sequence their daily behaviors. Despite the animals’ differences in size, ecology, and lifestyle, the research reveals that their actions are governed by a consistent behavioral order.
“We expected to see variation,” said Pranav Minasandra, postdoctoral researcher at MPI-AB and lead author of the study published in Proceedings of the National Academy of Sciences. “But instead, we found consistent patterns in how behaviors transition, no matter the species or individual. It’s as though all their actions are based on the same underlying algorithm.
This “hidden algorithm” was detected through data collected from accelerometers—tiny motion sensors like those in smartphones—that were attached to the animals. These sensors recorded minute-by-minute posture and movement, capturing high-resolution data over days and even weeks. The team then used machine learning techniques to categorize behaviors such as lying, foraging, and walking.
The study’s key finding was unexpectedly uniform: the longer an animal remains in a particular behavioral state, the less likely it is to switch to another. This phenomenon, called a decreasing hazard function, was observed across all three species. For example, if a hyena walks continuously for ten minutes, it becomes increasingly likely to keep walking rather than stop—defying the initial assumption that animals would naturally shift behavior more frequently over time.
“This kind of behavioral lock-in surprised us,” Minasandra explained. “We assumed constant change would be more adaptive. But what we found was just the opposite—the longer the behavior lasted, the more it tended to persist.”
Another discovery involved what the researchers termed predictivity decay—a measure of how well an animal’s current behavior predicts its future actions. As time progresses, predictability drops due to random and unpredictable influences. Despite these variations, the shape of this predictivity decay graph remained consistent across all animals studied. This implies that behavioral decisions are guided by a shared internal structure, even among species with vastly different lifestyles.
The researchers suggest two potential explanations for these patterns. One is positive feedback, where staying in the same behavioral state provides ongoing benefits—such as safety or social reinforcement—that make it more likely for the animal to continue in that state. The second is multi-timescale decision-making. Instead of a single internal trigger prompting behavioral changes, animals might be processing multiple cues—such as hunger, threats, or social context—each operating on its own timing. The combination of these influences could naturally result in the observed regularities.
Senior author Ariana Strandburg-Peshkin, group leader at MPI-AB, emphasized the significance of collecting long-term, high-resolution data across different species to reveal such patterns. “This approach allows us to observe the fine-grained structure of behavior that isn't apparent in short-term or single-species studies,” she noted.
Looking ahead, the team plans to investigate whether these behavioral architectures exist in other kinds of animals, including non-social species and individuals at different life stages or in varying ecological conditions. They are also curious whether these long-duration behaviors confer any evolutionary advantages—such as energy conservation, improved coordination, or enhanced focus.
Meg Crofoot, co-author and Director of the Department for the Ecology of Animal Societies, summarized the broader implication: “What this research points to is that even as animals go about vastly different lives—whether hunting, resting, or hiding—they appear to be guided by shared, hidden behavioral structures that resonate across the tree of life.”
Source:https://phys.org/news/2025-05-mammals-behavior-hints-underlying-architecture.html
This is non-financial/medical advice and made using AI so could be wrong.
