The Ecology and Evolution of Cooperative Breeding

合作养殖的生态与演化

• 批准号: 355854-2013
• 负责人: Wild, Geoffrey
• 金额: $ 3.64万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=632039
• 关键词: Ecology; Evolution; Cooperative; Breeding

My research group applies modern computational methods to study theoretical problems in evolutionary ecology. Work from my group appears in top journals like Nature, the American Naturalist, Evolution, and Proceedings B. Furthermore, our discoveries have driven our discipline forward, as evidenced by numerous invitations to attend conferences and join international scientific working groups. The long-term objective of my research is to understand why social behaviours like cooperation are adaptive. At first glance, cooperation in a "dog-eat-dog world" is puzzling, and solving this puzzle is a major challenge in evolutionary biology. In the short-term, I am proposing to study the cooperative breeding systems found in mammals, birds, insects, and even some micro-organisms. My research group will use mathematical and computer models to understand how the ecology of a species can promote (or inhibit) the emergence of cooperative breeding. Unlike previous work in other groups, we will apply models that pay careful attention to the dynamic processes that feed into species' ecology. Our work will address connections between the occurrence of cooperative breeding, and (i) dispersal, (ii) mating systems, (iii) patterns of parental investment in offspring, and (iv) the division of reproductive success within social groups. Answers to the questions we ask are crucial to anyone who wishes to accurately study cooperation (or social behaviour in general) in the wild. The proposed work will involve at least twelve trainees. Each will learn how to conduct research in evolutionary ecology using computational approaches valued by academia, government, and industry. Trainees, therefore, will be highly qualified to make contributions to any one of these three sectors.

我的研究小组应用现代计算方法来研究进化生态学的理论问题。我的团队的工作发表在《自然》、《美国博物学家》、《进化论》和《Proceedings B》等顶级期刊上。此外，我们的发现推动了我们的学科向前发展，无数邀请参加会议和加入国际科学工作组就证明了这一点。我研究的长期目标是了解为什么合作等社会行为具有适应性。乍一看，“狗咬狗的世界”中的合作令人费解，而解决这个难题是进化生物学的一个重大挑战。短期内，我建议研究哺乳动物、鸟类、昆虫甚至一些微生物中的合作繁殖系统。我的研究小组将使用数学和计算机模型来了解一个物种的生态如何促进（或抑制）合作育种的出现。与其他小组之前的工作不同，我们将应用模型，仔细关注物种生态的动态过程。我们的工作将解决合作繁殖的发生与（i）传播，（ii）交配系统，（iii）父母对后代的投资模式，以及（iv）社会群体内繁殖成功的划分之间的联系。对于任何希望准确研究野外合作（或一般社会行为）的人来说，我们提出的问题的答案至关重要。拟议的工作将涉及至少十二名学员。每个人都将学习如何使用学术界、政府和工业界重视的计算方法进行进化生态学研究。因此，学员将非常有资格为这三个部门中的任何一个做出贡献。