Feeding interaction network analyses enhance management of NHP breeding groups

喂养相互作用网络分析增强 NHP 育种群体的管理

• 批准号: 10652496
• 负责人: Kelly F Ethun
• 金额: $ 85.99万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10652496
• 关键词: Adult; Affect; Aggressive behavior; Animal Feed; Animals; Behavior; Behavioral; Birth; Breeding; Case Study; Communities; Complex; Consumption; Contracts; Data; Deposition; Detection; Disease Outbreaks; Eating; Ensure; Estradiol; Exhibits; Family; Female; Frequencies; Funding; Goals; Health; Injury; Intake; Lactation; Macaca mulatta; Machine Learning; Methodology; Mission; Modeling; Monitor; Monkeys; Ovulation; Pathway Analysis; Pattern; Phase; Populations at Risk; Practice Management; Primates; Progesterone; Publishing; Reporting; Research; Research Subjects; Risk; Seasons; Signal Transduction; Social Dominance; Social Network; Social support; Structure; Subgroup; Testing; Time; Trauma; United States National Institutes of Health; affiliative behavior; animal resource; behavior observation; cohesion; data-driven model; feeding; fighting; improved; machine learning algorithm; machine learning model; member; model building; network models; pregnant; reproductive; season of birth; social; social attachment; social relationships; social unrest; wound

Abstract A primary mission of Animal Resources Divisions at National Primate Research Centers (NPRC) is to maintain the overall social health of Indian-origin rhesus macaques (Macaca mulatta) living in large multi-generational breeding groups in order to ensure the availability of high-quality research subjects for NIH-funded research. The social dynamics of these breeding groups, however, are complex and disturbances in their dominance hierarchy and kinship structures can lead to increased aggression and fighting that may result in significant wounding. Thus, a common challenge in their management is the utilization of effective social heath surveillance methodology to identify groups at risk for social instability before the onset of significant fighting. These captive groups are routinely monitored for changes in dominance ranks and rates of trauma to detect social instability at the family- and group-level; however, the precise timing of severe outbreaks of aggression is largely considered unpredictable. Further, the frequency of interactions that define dominance and affiliative relationships in these groups are sparse; thus, the gathering of enough behavioral data to unequivocally detect social instability is time- consuming. We recently published a report that indicated automated feeding data can provide critical real-time data and assist management with monitoring social stability in rhesus macaque breeding groups, by possibly predicting the timing of intense aggression. The purpose of this proposal is to expand upon these observations by establishing data-driven models that help management identify groups at risk for social instability. Because automated feeding data include precise timestamps and the order in which animals feed, network analyses can be used to construct Feeding Interaction Networks (FINs), allowing us to examine patterns of temporal proximity feeding among kin and non-kin. Because reproductive status also influences food intake in female monkeys, we will study six outdoor breeding groups at the Yerkes NPRC across the breeding and birthing seasons, and integrate social and reproductive data, with the overarching aim to develop comprehensive data-driven FIN models that will enhance colony management practices of NIH-supported rhesus macaque breeding colonies. Aim 1 will characterize the community structures within static FINs of rhesus macaque breeding groups, varying in size and composition. Aim 2 will determine whether the directionality and strength of connections between adult females within a static FIN can be used to predict patterns of affiliative and dominance relationships among kin and non-kin. Aim 3 will quantify and model the temporal changes of community structures within dynamic FINs of rhesus macaque groups across the breeding and birthing season with respect to female reproductive phase. Finally, Aim 4 will detect changes in the community structures of dynamic FINs, not associated with reproductive seasonality, that are precursor to increased aggression and other signs of social instability. These FIN models will be used to supplement behavioral and trauma data, allowing management to identify groups at risk for social instability and develop strategies to intervene prior to the escalation of additional aggression.

抽象的 国家灵长类动物研究中心（NPRC）的动物资源部门的主要任务是维护 印度 - 奥林恒河猕猴（Macaca Mulatta）的整体社会健康生活在大型多代 为了确保NIH资助研究的高质量研究对象的可用性。 然而，这些繁殖群体的社会动态是复杂的，并且在其主导地位上有干扰 层次结构和亲属关系结构可能会导致侵略和战斗增加，这可能会导致重大 受伤。因此，他们管理中的一个普遍挑战是利用有效的社会荒地监视 在重大战斗发作之前，可以识别有社会不稳定风险的群体的方法。这些俘虏 定期监控群体的统治等级和创伤率的变化，以检测社会不稳定 家庭和团体级别；但是，严重侵略爆发的确切时机在很大程度上被认为 不可预测。此外，这些互动的频率定义了这些互动的频率 组很少；因此，收集足够的行为数据以明确检测社会不稳定是时间 - 消费。我们最近发布了一份报告，该报告表明自动喂食数据可以提供关键的实时 数据并协助管理层监视恒河猕猴育种组中的社会稳定性 预测强烈侵略的时机。该提议的目的是扩大这些观察结果 通过建立数据驱动的模型，以帮助管理层识别有社会不稳定风险的群体。因为 自动进食数据包括精确的时间戳和动物饲料的顺序，网络分析可以 用于构建进食交互网络（FIN），使我们能够检查时间邻近模式 在亲属和非金属之间进食。因为生殖状态也会影响雌猴的食物摄​​入量，所以我们 将在整个繁殖季节研究Yerkes NPRC的六个户外育种组，以及 将社会和生殖数据整合在一起，并旨在开发全面的数据驱动鳍片 将增强NIH支持的恒河猕猴繁殖殖民地的殖民地管理实践的模型。 AIM 1将表征恒河猕猴繁殖群静态鳍中的社区结构，不同 大小和组成。 AIM 2将确定连接之间的方向性和强度是否 静态鳍中的成年女性可用于预测隶属关系和优势关系的模式 亲属和非金属。 AIM 3将量化和建模动态中社区结构的时间变化 在整个繁殖和生育季节的恒河猕猴的鳍片相对于女性生殖 阶段。最后，AIM 4将检测到动态鳍的社区结构的变化，而与 生殖季节性是增加侵略性和其他社会不稳定迹象的先驱。这些 鳍模型将用于补充行为和创伤数据，使管理层可以识别群体 社会不稳定的风险，并制定策略以在额外侵略升级之前进行干预。