Camille M Montalcini, Charles C Driver, Michael T Mendl
{"title":"Relevance of state-behaviour feedbacks for animal welfare.","authors":"Camille M Montalcini, Charles C Driver, Michael T Mendl","doi":"10.1111/brv.70016","DOIUrl":null,"url":null,"abstract":"<p><p>An animal's behaviour and its state, including its health and affective state, are dynamic and tightly coupled, influencing each other over time. Although both are relevant to the animal's welfare, there has been limited research on their dynamics in welfare studies. Here we aim to: (i) review evidence for feedbacks between state and behaviour that could have beneficial or detrimental consequences for farm animal welfare; (ii) propose ways in which an understanding of such feedbacks could be used to enhance welfare; and (iii) provide practical guidance. We include as state variables any features that could influence the costs and benefits of an animal's behavioural actions, including individual characteristics and aspects of its social environment. We find evidence supporting positive state-behaviour feedback loops in various livestock species, suggesting that these loops could be common in farm settings and have significant welfare implications, such as leading to abnormal behaviours and persistent negative affective states. We suggest (i) estimating within-individual feedback loops to extract individual characteristics for studying differences in welfare; (ii) identifying scenarios where change accelerated by positive feedbacks pushes an animal (or a group of animals) to a new state, also called tipping points; and (iii) generating positive feedback loops to elicit and maintain positive affective states. We end by encouraging use of dynamic models that integrate longitudinal data on animals' behaviour and state to enable exploration of their dynamics, and we provide a practical guide with annotated R code for support. Since the principles and ideas discussed here are relevant to any animals under human care, this approach could foster new perspectives for improving the welfare of all captive animals.</p>","PeriodicalId":133,"journal":{"name":"Biological Reviews","volume":" ","pages":""},"PeriodicalIF":11.0000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological Reviews","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1111/brv.70016","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
An animal's behaviour and its state, including its health and affective state, are dynamic and tightly coupled, influencing each other over time. Although both are relevant to the animal's welfare, there has been limited research on their dynamics in welfare studies. Here we aim to: (i) review evidence for feedbacks between state and behaviour that could have beneficial or detrimental consequences for farm animal welfare; (ii) propose ways in which an understanding of such feedbacks could be used to enhance welfare; and (iii) provide practical guidance. We include as state variables any features that could influence the costs and benefits of an animal's behavioural actions, including individual characteristics and aspects of its social environment. We find evidence supporting positive state-behaviour feedback loops in various livestock species, suggesting that these loops could be common in farm settings and have significant welfare implications, such as leading to abnormal behaviours and persistent negative affective states. We suggest (i) estimating within-individual feedback loops to extract individual characteristics for studying differences in welfare; (ii) identifying scenarios where change accelerated by positive feedbacks pushes an animal (or a group of animals) to a new state, also called tipping points; and (iii) generating positive feedback loops to elicit and maintain positive affective states. We end by encouraging use of dynamic models that integrate longitudinal data on animals' behaviour and state to enable exploration of their dynamics, and we provide a practical guide with annotated R code for support. Since the principles and ideas discussed here are relevant to any animals under human care, this approach could foster new perspectives for improving the welfare of all captive animals.
期刊介绍:
Biological Reviews is a scientific journal that covers a wide range of topics in the biological sciences. It publishes several review articles per issue, which are aimed at both non-specialist biologists and researchers in the field. The articles are scholarly and include extensive bibliographies. Authors are instructed to be aware of the diverse readership and write their articles accordingly.
The reviews in Biological Reviews serve as comprehensive introductions to specific fields, presenting the current state of the art and highlighting gaps in knowledge. Each article can be up to 20,000 words long and includes an abstract, a thorough introduction, and a statement of conclusions.
The journal focuses on publishing synthetic reviews, which are based on existing literature and address important biological questions. These reviews are interesting to a broad readership and are timely, often related to fast-moving fields or new discoveries. A key aspect of a synthetic review is that it goes beyond simply compiling information and instead analyzes the collected data to create a new theoretical or conceptual framework that can significantly impact the field.
Biological Reviews is abstracted and indexed in various databases, including Abstracts on Hygiene & Communicable Diseases, Academic Search, AgBiotech News & Information, AgBiotechNet, AGRICOLA Database, GeoRef, Global Health, SCOPUS, Weed Abstracts, and Reaction Citation Index, among others.