Understanding and predicting the diffusion of innovations in animal populations

这项研究的目的是增加我们对新知识和技能通过复制（“社会学习”）在动物（包括人类）之间转移的过程的理解。对于人类来说，模仿和教学被认为是信息从知识渊博的个体传递到幼稚个体的最重要的过程。然而，在其他动物中，几乎没有证据表明教学发生，但尽管如此，缺乏经验的年轻个体从更有知识的其他人那里获得线索，例如，捕食者的身份或如何最好地处理食物。这种社会学习可以产生执行特定行为模式的“传统”，例如，吃特定的食物，或采取特定的路径。因此，动物的行为可能会因种群而异，这不仅是因为它们拥有不同的基因或暴露于不同的环境资源，而且还因为它们从更有经验的种群成员那里学到了不同的习惯。研究动物行为的研究人员面临的一个挑战是识别这些“传统”，并找出新的行为和技能（“创新”）如何在种群中传播。目前，研究人员很难判断动物是否在实验室环境之外相互复制，也很难确定创新传播背后的心理和社会过程。这项研究计划将使用实验室的椋鸟种群生成有用的数据，然后使用数学来开发统计软件包，指定动物何时通过社会学习获得其行为，新的行为如何通过动物种群的社会学习传播，以及部署了什么学习规则。这些统计工具的有用性将在新喀里多尼亚乌鸦、猫鼬、黑猩猩和卷尾猴的自然或自然种群中进行测试-这些动物以其传统行为而闻名-与来自牛津大学、剑桥大学和达勒姆大学的专家合作。这些统计工具将作为免费软件提供给各种研究人员（生物学家、心理学家、人类学家、考古学家、经济学家），他们有兴趣发现和理解社会学习并预测创新的传播，包括人类的技术创新。由于信息的传播与某些可通过人口传播的疾病之间存在一些相似之处，该项目还包括一项试点研究，以调查所开发的统计工具是否有可能使用古比模型系统来预测疾病流动。该项目涉及与普林斯顿大学、牛津大学、剑桥大学、达勒姆大学和埃克塞特大学以及莱比锡MPI的杰出研究人员合作。

The aim of this research is to increase our understanding of the processes by which new knowledge and skills is transferred between animals, including humans, through copying ('social learning'). For human beings, imitation and teaching are thought to be the most important processes by which information is transferred from knowledgeable to naive individuals. However, in other animals there is little evidence that teaching occurs but nonetheless inexperienced and young individuals pick up clues from more knowledgeable others concerning, for instance, the identity of predators or how best to process foods. This social learning can generate 'traditions' for performing particular behaviour patterns, for instance, eating specific foods, or taking particular pathways. As a consequence, the behaviour of animals may vary from one population to the next, not just because they possess different genes, or are exposed to different environmental resources, but also because they have learned different habits from more experienced members of their population. A challenge for researchers studying animal behaviour is to identify these 'traditions' and to work out how novel behaviour and skills ('innovations') spread through populations. Currently it is very difficult for researchers to tell if animals are copying each other outside of the laboratory context, or to specify the psychological and social processes that underlie the spread of innovations. This research programme will generate useful data using laboratory populations of starlings and then use mathematics to develop statistical packages that specify when animals acquire their behaviour through social learning, how novel behaviours spread through social learning in animal populations, and what learning rules are deployed. The usefulness of these statistical tools will then be tested in natural or naturalistic populations of New Caledonian crows, meerkats, chimpanzees and capuchin monkeys - animals renowned for their traditional behaviour - working with expert collaborators from Oxford, Cambridge and Durham universities. These statistical tools will be made available as freeware to a variety of researchers (biologists, psychologists, anthropologists, archaeologists, economists) interested in detecting and understanding social learning and predicting the diffusion of innovations, including technological innovations in humans. As there are some parallels between the spread of information and certain transmittable diseases through populations, the project also contains a pilot study to investigate whether the developed statistical tools potentially can be applied to predict disease flow, using a guppy model system. This project involves collaborations with outstanding researchers at Princeton, Oxford, Cambridge, Durham and Exeter Universities and the MPI Leipzig.