网络分析法在动物声音通讯及生物声学研究中的应用与前景

动物社会网络分析法(animal social network analysis,ASNA)是一套用于研究动物社会性、量化个体间各种社会关系、揭示个体行为与社会结构动态之间联系的工具,被广泛应用于多种动物类群的行为学研究。该分析方法所提供的一系列指标也非常适用于探究动物的声音交流及鸣声结构。在此,本文首先简要介绍了网络分析法的基本概念及一些常用的指标;然后基于野外和室内研究实例,阐述了如何利用ASNA建立声音通讯网络、量化声音交流,以及将ASNA与被动声学监测技术相结合的应用前景;随后探讨了ASNA在分析鸣声相似性及鸣声地理变异中的优势;最后概述了ASNA在解析鸣声结构和句法规则中的应用。ASNA为研究动物通讯网络以及声音信号的适应性进化提供了新的视角和新的思路。     

社会关系网络分析在行为生态学中的跨学科应用

社会关系网络分析(social network analysis,SNA)是综合运用图论、数学模型,来研究个体与个体、个体与其所处社会网络、以及一个社会网络与另一社会网络之间关系的研究方法。SNA不仅仅是一套技术、而是一种关于关系网的方法论。该方法论认为每一个个体都不是独立的,而是通过信息、行为、空间分布、生态因素等连结共生。这让我们以全局视野理解一个动物群体,从两方关系、三方关系、个体与群体间关系、到动态网络模型等角度进行研究,为验证性行为与性选择理论、互惠与合作理论、信息流动与疾病传播理论、个体策略与种群选择理论、界定一个群、预测社会关系网络稳定性等行为生态学领域提供可靠的量化数据,极大地推动了行为生态学的发展。相对于国外的快速发展,SNA在国内动物学研究中的应用仍十分有限。为此,该文结合作者对川金丝猴的研究结果,介绍了SNA的理论背景、概念、测量方法和应用领域,旨在推广SNA在我国行为生态学研究中的跨学科应用。     

笼养川金丝猴社会偏侧行为的初步研究

社会环境中动物个体之间在互动行为过程中所表现出的行为偏侧称为社会偏侧.社会偏侧对于物种个体和群体的适应性生存均有重要意义.本研究基于生物系统发生关系,应用定量多维方法和The Observer 11.0动物行为观察分析系统初步研究笼养川金丝猴社会偏侧(社会互动过程中的位置偏侧)的基本特征.研究结果显示:(1)笼养川金丝...     

乌干达野生动物研究中心外来黑猩猩融入笼养群体的过程

1967至1997的30年间,生活在非洲热带地区自然栖息地的野生黑猩猩数量由60万降至不足20万,至今这个数字仍在减少,因此引起了全球的关注并急需要开展迁地保护。笼养黑猩猩与野外种群一样营群居生活,为了有效进行野生黑猩猩的迁地保护,将野外捕获的野生黑猩猩个体成功引入已在动物园的黑猩猩群体中十分必要。2004年10月至2005年3月,乌干达野生动物研究中心首先开展了这一实验。同时为更好地了解外来黑猩猩融入笼养群体的过程,2006年9月至2007年1月间收集其活动数据。选取5只黑猩猩个体并记录它们的食性、行为、体重变化及身体健康状况。除直接观察和记录外,与兽医和研究中心管理人员进行合作,以获取较多笼养个体的信息。我们发现,野生个体比笼养个体多病,因此影响了它们的取食、社会行为及活动水平。尽管笼养黑猩猩有人照料,但仍具备野生个体的行为,所以,理解外来黑猩猩融入笼养群体的过程对于黑猩猩的迁地保护和就地保护是非常重要的。     

繁殖期高原鼠兔的攻击行为

通过室内配对实验对高原鼠兔（Ｏｃｈｏｔｏｎａ ｃｕｒｚｏｎｉａｅ）繁殖期的攻击行为进行了研究。结果表明,雌雄动物的攻击水平相同,同性个体间的攻击性明显高于异性个体间。雌雄动物具有不同的攻击模式。雌性个体遇到陌生个体首先以攻击中的进攻和追逐为主,然后通过相互接触确定个体的性别,若为同性个体,以防御为主,若为异性个体,则有防御和亲昵两种选择;雄性动物遇到陌生个体同样首先以攻击为主,相互接触后,若为异性     

非人灵长类的个性研究进展

个性的研究能够加深对群居动物个体间差异和群体的社会组织模式的了解,这使其成为非人灵长类学者关注的一个热点话题,并为社会心理学和行为生态学交叉融合发展提供新的方法与思路。本文简要总结了目前灵长类个性的分类定义、评定方法与研究内容,并详细介绍了研究进展中的突出成果：从激素变化、特定基因位点差异和环境条件3个角度解释个性形成机制;将个性在个体健康和认知中的功能应用到灵长类的饲养管理中,有效提升动物福利。为了更好地回答行为生态学理论问题,今后需进一步拓展对野生环境中非人灵长类个体的个性以及行为模式的探索,建议从性选择、社群结构以及空间动态深入研究,切实为濒危物种保护提出新的思路。     

拖延的大尺度脑网络效用连接模式:基于多态格兰杰因果模型分析

拖延(procrastination)是全球所热议的最重要的行为问题之一,它是指个体尽管能够预见不利后果,但仍然不理性推迟或延后执行任务的行为.已有研究提示,作为一种有害的行为倾向,拖延不仅影响个体的情绪体验及主观幸福感,还在一定程度上损害个体的生理健康.新近的一项基于大尺度脑网络的分析在功能连接水平上揭示了拖延的网络连接模式,为理解拖延行为的核心过程提供了一定的证据,但却很难解释拖延的核心加工过程的工作机制.因此,本研究通过多态联合的格兰杰因果模型(Granger causality model, GCM)基于效用连接水平来解释和预测拖延神经相关网络的因果连接模式.首先,采用群体独立成分分析法(group independent component analysis,g ICA),基于Infomax算法提取并识别出脑功能扣带执行控制网络(cingulate executive control network, CON)、突显网络(salience network, SAN)及皮层下网络(subcortical network, SCN)的空间独立成分作为感兴趣大尺度脑网络(network of interests, NOI).其次,在增广迪基-富勒检验后利用皮尔逊积差相关分别检验三个网络间的格兰杰因果效用连接与拖延间的关系.最后,利用基于高斯径向基底核函数(radial basis function, RBF)的支持向量回归算法(support vector regression, SVR)在独立样本上进行机器学习,随后用于预测个体的拖延行为.结果发现,扣带执行控制网络向皮层下网络的效用连接与拖延行为存在显著负相关,扣带执行控制网络是格兰杰因,而皮层下网络是格兰杰果.同时,结果还发现了扣带执行控制网络向突显网络的效用连接和拖延之间呈负相关关系.最后,机器学习的结果显示,这些格兰杰因果效用连接能够显著预测个体拖延症状(R2=0.66, MSE=0.120).结果揭示,扣带执行控制网络对与皮层下网络及突显网络的自上而下调控可能是拖延的脑网络效用连接模式,并提供了可靠的证据表明,参与冲动控制的扣带执行控制网络对于参与价值表征加工的皮层下网络及参与情绪编码的突显网络的调控.     

鸟类惊飞距离及其影响因素

惊飞距离(FID)是指捕食者(包括人类)接近目标个体并导致其逃避时,捕食者与目标个体之间的距离。惊飞距离能很好地衡量动物个体在特定环境下的恐惧反应和风险权衡,是研究动物逃避行为的常用指标,并为物种保护提供科学依据。鸟类是研究逃避行为的理想对象,本文综述了影响鸟类惊飞距离的各种因素,可分为3类:栖息地因素(距隐蔽处的距离和生境开阔度等)、鸟类自身因素(生活史、体型和群体大小等)以及与捕食者相关的因素(捕食者的接近方向和速度等)。城市化也会影响鸟类的惊飞距离,导致城市中的鸟类通常比乡村生境的同种鸟类拥有更短的惊飞距离。习惯化、适应和生境选择是解释惊飞距离城乡差异的3种假说。研究鸟类的惊飞距离及其影响因素,有助于理解鸟类的逃避行为及其风险权衡机制,为物种保护中设立合理的缓冲区域及制定有效的保护管理措施提供科学依据。目前国内有关鸟类惊飞距离的研究多为行为观察和单一因素的影响,有待从不同因素的交互作用角度探讨鸟类的逃避行为并用于物种保护。     

个体亲近程度对藏酋猴攻击行为的影响

友好和冲突行为决定了群居动物的社会结构及其表现形式,表现为个体间近距差异。但目前尚不清楚藏酋猴个体间亲近关系的差异性是否会影响冲突和攻击的强度。本研究于2020年9月至2021年5月对栖息于安徽黄山的藏酋猴鱼鳞坑YA1群进行跟踪观察,采用目标动物取样法采集行为数据,全事件记录法用于攻击行为数据的补充,分析个体间近距、理毛和攻击行为矩阵的关系,并采用GLMM模型探讨攻击行为的影响因素。结果显示：藏酋猴个体间近距指数越大,理毛时间越长;个体间近距指数矩阵与攻击总次数、轻度攻击和重度攻击次数矩阵均呈显著正相关;个体间亲近关系越紧密,攻击次数和强度越大,但相较雄性间和异性间,雌性间攻击次数和强度最小。这些结果表明,个体间近距持续时间会增加理毛和攻击行为的可能性,雌性个体间社会关系更稳定,但并未发现藏酋猴根据个体间亲近关系调整攻击强度。本研究为进一步了解多雌多雄的藏酋猴群体的社会关系和社会结构提供了数据支持。     

在缺乏繁殖能力的食蟹猴群体中探究指长比与社会等级以及行为的关系

为了探究笼养食蟹猴Macaca fascicularis指长比与社会等级、行为之间的关系,2016年1月,在江苏省苏州西山中科实验动物有限公司猴场内筛选12只健康雌性食蟹猴,组建新的群体前测量实验个体的食指和无名指指长比率(指长比)。利用人为观察记录法和视频采集法记录群体进食顺序和个体行为,分析群体等级秩序和相应个体的行为表现。研究发现,在食蟹猴抑郁样(低头、蜷缩)、独处、运动、社交、自我护理、攻击等行为中,高、低指长比组的食蟹猴在抑郁样、独处、攻击行为上的差异有统计学意义(P0.05)。研究表明,社会等级强度较高的食蟹猴个体具有较低的指长比比值,在社会活动中具有更强的攻击性;具有较高指长比比值的食蟹猴个体在社会环境下更容易出现抑郁倾向。     

Infectious disease transmission and contact networks in wildlife and livestock

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.     

Multiscale complexity in the mammalian circadian clock

The field of systems biology studies how the interactions among individual components (e.g. genes and proteins) yield interesting and complex behavior. The circadian (daily) timekeeping system in mammals is an ideal system to study complexity because of its many biological scales (from genes to animal behavior). A wealth of data at each of these scales has recently been discovered. Within each scale, modeling can advance our understanding of challenging problems that arise in studying mammalian timekeeping. However, future work must focus on bridging the multiple spatial and temporal scales in the modeling of SCN network. Here we review recent advances, and then delve into a few areas that are promising research directions. We also discuss the flavor of modeling needed (simple or detailed) as well as new techniques that are needed to meet the challenges in modeling data across scales.     

Automated proximity sensing in small vertebrates: design of miniaturized sensor nodes and first field tests in bats

Social evolution has led to a stunning diversity of complex social behavior, in particular in vertebrate taxa. Thorough documentation of social interactions is crucial to study the causes and consequences of sociality in gregarious animals. Wireless digital transceivers represent a promising tool to revolutionize data collection for the study of social interactions in terms of the degree of automation, data quantity, and quality. Unfortunately, devices for automated proximity sensing via direct communication among animal‐borne sensors are usually heavy and do not allow for the investigation of small animal species, which represent the majority of avian and mammalian taxa. We present a lightweight animal‐borne sensor node that is built from commercially available components and uses a sophisticated scheme for energy‐efficient communication, with high sampling rates at relatively low power consumption. We demonstrate the basic functionality of the sensor node under laboratory conditions and its applicability for the study of social interactions among free‐ranging animals. The first field tests were performed on two species of bats in temperate and tropical ecosystems. At <2 g, this sensor node is light enough to observe a broad spectrum of taxa including small vertebrates. Given our specifications, the system was especially sensitive to changes in distance within the short range (up to a distance of 4 m between tags). High spatial resolution at short distances enables the evaluation of interactions among individuals at a fine scale and the investigation of close contacts. This technology opens new avenues of research, allowing detailed investigation of events associated with social contact, such as mating behavior, pathogen transmission, social learning, and resource sharing. Social behavior that is not easily observed becomes observable, for example, in animals living in burrows or in nocturnal animals. A switch from traditional methods to the application of digital transceiver chips in proximity sensing offers numerous advantages in addition to an enormous increase in data quality and quantity. For future applications, the platform allows for the integration of additional sensors that may collect physiological or environmental data. Such information complements social network studies and may allow for a deeper understanding of animal ecology and social behavior.     

Connecting the dots in ethology: applying network theory to understand neural and animal collectives

A major goal shared by neuroscience and collective behavior is to understand how dynamic interactions between individual elements give rise to behaviors in populations of neurons and animals, respectively. This goal has recently become within reach, thanks to techniques providing access to the connectivity and activity of neuronal ensembles as well as to behaviors among animal collectives. The next challenge using these datasets is to unravel network mechanisms generating population behaviors. This is aided by network theory, a field that studies structure–function relationships in interconnected systems. Here we review studies that have taken a network view on modern datasets to provide unique insights into individual and collective animal behaviors. Specifically, we focus on how analyzing signal propagation, controllability, symmetry, and geometry of networks can tame the complexity of collective system dynamics. These studies illustrate the potential of network theory to accelerate our understanding of behavior across ethological scales.     

Personality in the context of social networks

There is great interest in environmental effects on the development and evolution of animal personality traits. An important component of an individual's environment is its social environment. However, few studies look beyond dyadic relationships and try to place the personality of individuals in the context of a social network. Social network analysis provides us with many new metrics to characterize the social fine-structure of populations and, therefore, with an opportunity to gain an understanding of the role that different personalities play in groups, communities and populations regarding information or disease transmission or in terms of cooperation and policing of social conflicts. The network position of an individual is largely a consequence of its interactive strategies. However, the network position can also shape an individual's experiences (especially in the case of juveniles) and therefore can influence the way in which it interacts with others in future. Finally, over evolutionary time, the social fine-structure of animal populations (as quantified by social network analysis) can have important consequences for the evolution of personalities-an approach that goes beyond the conventional game-theoretic analyses that assumed random mixing of individuals in populations.     

Personality and Affinities Play a Key Role in the Organisation of Collective Movements in a Group of Domestic Horses

Understanding how groups of individuals with different motives come to daily decisions about the exploitation of their environment is a key question in animal behaviour. While interindividual differences are often seen only as a threat to group cohesion, growing evidence shows that they may to some extent facilitate effective collective action. Recent studies suggest that personality differences influence how individuals are attracted to conspecifics and affect their behaviour as an initiator or a follower. However, most of the existing studies are limited to a few taxa, mainly social fish and arthropods. Horses are social herbivores that live in long‐lasting groups and show identifiable personality differences between individuals. We studied a group of 38 individuals living in a 30‐ha hilly pasture. Over 200 h, we sought to identify how far individual differences such as personality and affinity distribution affect the dynamic of their collective movements. First, we report that individuals distribute their relationships according to similar personality and hierarchical rank. This is the first study that demonstrates a positive assortment between unrelated individuals according to personality in a mammal species. Second, we measured individual propensity to initiate and found that bold individuals initiated more often than shy individuals. However, their success in terms of number of followers and joining duration did not depend on their individual characteristics. Moreover, joining process is influenced by social network, with preferred partners following each other and bolder individuals being located more often at the front of the movement. Our results illustrate the importance of taking into account interindividual behavioural differences in studies of social behaviours.     

The Effect of Disease-Induced Mortality on Structural Network Properties

As the understanding of the importance of social contact networks in the spread of infectious diseases has increased, so has the interest in understanding the feedback process of the disease altering the social network. While many studies have explored the influence of individual epidemiological parameters and/or underlying network topologies on the resulting disease dynamics, we here provide a systematic overview of the interactions between these two influences on population-level disease outcomes. We show that the sensitivity of the population-level disease outcomes to the combination of epidemiological parameters that describe the disease are critically dependent on the topological structure of the population’s contact network. We introduce a new metric for assessing disease-driven structural damage to a network as a population-level outcome. Lastly, we discuss how the expected individual-level disease burden is influenced by the complete suite of epidemiological characteristics for the circulating disease and the ongoing process of network compromise. Our results have broad implications for prediction and mitigation of outbreaks in both natural and human populations.     

Universal behaviors as candidate traditions in wild spider monkeys

Candidate traditions were documented across three communities of wild spider monkeys (Ateles geoffroyi) using an a priori approach to identify behavioral variants and a statistical approach to examine differences in their proportional use. This methodology differs from previous studies of animal traditions, which used retrospective data and relied on the 'exclusion method' to identify candidate traditions. Our a priori approach increased the likelihood that behavior variants with equivalent functions were considered and our statistical approach enabled the proportional use of 'universal' behaviors, i.e., used across all communities, to be examined for the first time in any animal species as candidate traditions. Among universal behaviors we found 14 'community preferred' variants. After considering the extent to which community preferred variants were due to ecological and, to a lesser degree, genetic differences, we concluded that at least six were likely maintained through social learning. Our findings have two main implications: (i) tradition repertoires could be larger than assumed from previous studies using the exclusion method; (ii) the relative use of universal behavior variants can reinforce community membership.