Megan E. Bishop, Maria R. Servedio, Brian A. Lerch
{"title":"The evolution of fear-acquisition strategies under predation","authors":"Megan E. Bishop, Maria R. Servedio, Brian A. Lerch","doi":"10.1016/j.jtbi.2024.111949","DOIUrl":null,"url":null,"abstract":"<div><div>Fear is a taxonomically widespread behavioral response that functions to keep individuals out of danger. Empirical research has demonstrated that a diverse set of strategies are used in order to acquire a fear response across animals. Animals often use a mixed strategy: fear is acquired both innately and through learning. Despite the ubiquity of the fear response, and its established importance for shaping predator–prey interactions, little is known about why different fear acquisition strategies evolve or why mixed strategies appear common. Here, we model the evolution of fear acquisition (learning versus innate) under predation. We assume a tradeoff where individuals that learn fear are at higher risk from predators initially, but eventually obtain a lower risk as they survive predation attempts. We find that frequent predator encounters, predators that are not very dangerous, and effective learning favor the evolution of learned fear. Only pure strategies of fear acquisition evolve unless individuals suffer from either a cost to fear or, especially, a cost to learning, either of which can lead to the evolution of mixed strategies. Our results thus shed light onto the evolution of mixed fear acquisition strategies and open the door to further research on the evolution of fear acquisition.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"595 ","pages":"Article 111949"},"PeriodicalIF":1.9000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Theoretical Biology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022519324002340","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Fear is a taxonomically widespread behavioral response that functions to keep individuals out of danger. Empirical research has demonstrated that a diverse set of strategies are used in order to acquire a fear response across animals. Animals often use a mixed strategy: fear is acquired both innately and through learning. Despite the ubiquity of the fear response, and its established importance for shaping predator–prey interactions, little is known about why different fear acquisition strategies evolve or why mixed strategies appear common. Here, we model the evolution of fear acquisition (learning versus innate) under predation. We assume a tradeoff where individuals that learn fear are at higher risk from predators initially, but eventually obtain a lower risk as they survive predation attempts. We find that frequent predator encounters, predators that are not very dangerous, and effective learning favor the evolution of learned fear. Only pure strategies of fear acquisition evolve unless individuals suffer from either a cost to fear or, especially, a cost to learning, either of which can lead to the evolution of mixed strategies. Our results thus shed light onto the evolution of mixed fear acquisition strategies and open the door to further research on the evolution of fear acquisition.
期刊介绍:
The Journal of Theoretical Biology is the leading forum for theoretical perspectives that give insight into biological processes. It covers a very wide range of topics and is of interest to biologists in many areas of research, including:
• Brain and Neuroscience
• Cancer Growth and Treatment
• Cell Biology
• Developmental Biology
• Ecology
• Evolution
• Immunology,
• Infectious and non-infectious Diseases,
• Mathematical, Computational, Biophysical and Statistical Modeling
• Microbiology, Molecular Biology, and Biochemistry
• Networks and Complex Systems
• Physiology
• Pharmacodynamics
• Animal Behavior and Game Theory
Acceptable papers are those that bear significant importance on the biology per se being presented, and not on the mathematical analysis. Papers that include some data or experimental material bearing on theory will be considered, including those that contain comparative study, statistical data analysis, mathematical proof, computer simulations, experiments, field observations, or even philosophical arguments, which are all methods to support or reject theoretical ideas. However, there should be a concerted effort to make papers intelligible to biologists in the chosen field.