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运用社会网络分析来理解人为环境中野生动物共存和与人类共同相互作用的社会生态学。

Implementing social network analysis to understand the socioecology of wildlife co-occurrence and joint interactions with humans in anthropogenic environments.

机构信息

Department of Population Health & Reproduction, School of Veterinary Medicine (SVM), University of California at Davis, Davis, CA, USA.

Department of Biomedical Science and Physiology, Faculty of Science and Engineering, University of Wolverhampton, Wolverhampton, UK.

出版信息

J Anim Ecol. 2021 Dec;90(12):2819-2833. doi: 10.1111/1365-2656.13584. Epub 2021 Sep 6.

DOI:10.1111/1365-2656.13584
PMID:34453852
Abstract

Human population expansion into wildlife habitats has increased interest in the behavioural ecology of human-wildlife interactions. To date, however, the socioecological factors that determine whether, when or where wild animals take risks by interacting with humans and anthropogenic factors still remains unclear. We adopt a comparative approach to address this gap, using social network analysis (SNA). SNA, increasingly implemented to determine human impact on wildlife ecology, can be a powerful tool to understand how animal socioecology influences the spatiotemporal distribution of human-wildlife interactions. For 10 groups of rhesus, long-tailed and bonnet macaques (Macaca spp.) living in anthropogenically impacted environments in Asia, we collected data on human-macaque interactions, animal demographics, and macaque-macaque agonistic and affiliative social interactions. We constructed 'human co-interaction networks' based on associations between macaques that interacted with humans within the same time and spatial locations, and social networks based on macaque-macaque allogrooming behaviour, affiliative behaviours of short duration (agonistic support, lip-smacking, silent bare-teeth displays and non-sexual mounting) and proximity. Pre-network permutation tests revealed that, within all macaque groups, specific individuals jointly took risks by repeatedly, consistently co-interacting with humans within and across time and space. GLMMs revealed that macaques' tendencies to co-interact with humans was positively predicted by their tendencies to engage in short-duration affiliative interactions and tolerance of conspecifics, although the latter varied across species (bonnets>rhesus>long-tailed). Male macaques were more likely to co-interact with humans than females. Neither macaques' grooming relationships nor their dominance ranks predicted their tendencies to co-interact with humans. Our findings suggest that, in challenging anthropogenic environments, less (compared to more) time-consuming forms of affiliation, and additionally greater social tolerance in less ecologically flexible species with a shorter history of exposure to humans, may be key to animals' joint propensities to take risks to gain access to resources. For males, greater exploratory tendencies and less energetically demanding long-term life-history strategies (compared to females) may also influence such joint risk-taking. From conservation and public health perspectives, wildlife connectedness within such co-interaction networks may inform interventions to mitigate zoonosis, and move human-wildlife interactions from conflict towards coexistence.

摘要

人类向野生动物栖息地扩张,增加了人们对人类与野生动物相互作用的行为生态学的兴趣。然而,迄今为止,决定野生动物是否、何时或何地通过与人类互动以及人为因素来冒险的社会生态因素仍不清楚。我们采用比较方法来解决这一差距,使用社会网络分析(SNA)。SNA 越来越多地用于确定人类对野生动物生态学的影响,它可以成为一种强大的工具,用于了解动物社会生态学如何影响人类与野生动物相互作用的时空分布。对于生活在亚洲人为影响环境中的 10 组猕猴、长尾猕猴和食蟹猕猴(Macaca spp.),我们收集了关于人类与猕猴相互作用、动物人口统计学以及猕猴与猕猴之间的攻击和亲和社会相互作用的数据。我们根据在同一时间和空间位置与人类相互作用的猕猴之间的关联,构建了“人类共同相互作用网络”,并根据猕猴之间的亲和行为、短时间的亲和行为(攻击支持、咂嘴、无声裸齿展示和非性骑乘)以及接近程度构建了社会网络。网络预排列检验显示,在所有猕猴群体中,特定个体通过反复、一致地在同一时间和空间内与人类共同互动,共同承担风险。GLMM 表明,猕猴与人类共同互动的趋势与它们进行短时间的亲和互动以及容忍同种动物的倾向呈正相关,尽管后者因物种而异(食蟹猕猴>猕猴>长尾猕猴)。雄性猕猴比雌性猕猴更有可能与人类共同互动。猕猴的梳理关系或其优势等级都不能预测它们与人类共同互动的倾向。我们的研究结果表明,在具有挑战性的人为环境中,与人类建立联系所需的时间较少(相比之下,时间较长),在与人类接触历史较短、生态灵活性较低的物种中,社会容忍度更高,这可能是动物共同冒险获取资源的关键。对于雄性猕猴而言,探索倾向更大,长期生活史策略的能量需求更低(与雌性猕猴相比),这也可能影响这种共同冒险行为。从保护和公共卫生的角度来看,这种共同相互作用网络中的野生动物联系,可以为缓解人畜共患病的干预措施提供信息,并使人类与野生动物的相互作用从冲突转向共存。

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