Dynamics of coupled human-environment systems

在耦合的人类-环境系统（HES）中，自然子系统（例如野生种群）响应人类子系统（例如收获），而人类子系统又受到自然子系统变化的影响，从而形成完全耦合的系统。HES偶联的例子是灰狼（Canis lupus）的长期种群变化。在一个丰富的时间，他们被认为是害虫和猎杀到灭绝的边缘。然而，由此产生的稀有性使狼的保护成为公众的优先事项。这反过来又导致自然种群的部分反弹。因此，犬科动物的种群增长和保护优先事项完全耦合。耦合HESs的研究是生态学研究的一个新兴领域。在拟议的研究中，我将研究更多的案例研究，构建经验验证的数学和计算机模型的目的，高等教育。 我将重点关注生态系统，其中人类行为和自然种群相互关联，以及疾病系统，其中人类行为和传染病传播相互关联。 耦合HES研究的一个限制因素是相对缺乏来自自然实验的长期数据。我将通过使用计算机算法来分析Twitter流来帮助解决这一知识差距。有了这些数据，我将衡量情绪如何通过社交网络传播，意见领袖扮演什么角色，情绪如何应对不断变化的环境状态，以及何时演变的情绪转化为行动。 我将专注于生态变量（例如关注/重要物种的种群大小）和人类感知在可用时间段内发生重大变化的系统，以确保有足够的数据来创建模型。 我将开始我的搜索与以下系统，选择基于他们的潜力产生有用的信息，由于高Twitter的使用，突出的环境/健康问题，和我现有的研究合作和数据来源的组合：（1）沿海北美和南美森林草原镶嵌生态系统;（2）麻疹-腮腺炎-风疹（MMR）疫苗自闭症恐慌中疾病发病率和接种行为的动态;（3）加拿大森林中森林害虫控制的自愿木柴移动限制。这些数据将与传统的人口和生态系统数据源结合使用，以开发研究系统的耦合HES模型。 虽然研究系统是多种多样的，但它们将通过一种共同的方法加入，该方法使用数学和计算模型来探索这些系统如何随时间变化。研究问题将从理论到应用，如：（1）公共保护优先事项和当地利益相关者的经济优先事项如何相互作用，以确定系统的结果，特别是在森林病虫害防治和镶嵌生态系统管理的背景下？(2)根据免疫史和疾病流行率，某些人群是否比其他人群更容易受到儿科疫苗恐慌的影响？(3)以制度形式存在的社会规范的“钙化”在什么时候有利于物种保护，什么时候又会损害物种保护？ 总而言之，我寻求通过帮助建立耦合的人类环境系统的动态的经验知情的理论基础，推进生态研究。 这将提高我们对自然系统如何与人类相互作用的理解，从而进一步努力创造一个可持续的未来。

In a coupled human-environment system (HES), a natural sub-system (e.g. a wild population) responds to a human sub-system (e.g. harvesting), which, in turn, is shaped by changes in the natural sub-system, thus forming a fully coupled system. HES coupling is exemplified by the long-term population changes of the grey wolf, Canis lupus. At one time abundant, they were considered pests and hunted to the brink of extinction. However, the resulting rarity caused wolf conservation to become a public priority. This, in turn, led to a partial rebound in natural populations. Hence, Canis lupus population growth and conservation priorities are fully coupled. Study of coupled HESs is an emerging area in ecological research. In the proposed research I will examine additional case studies of HESs with the intent of constructing empirically validated mathematical and computer models. I will focus both on ecological systems, where human behaviour and natural populations are linked to one another, as well as disease systems, where human behavior and infectious disease spread are linked to one another. A limiting factor in the study of coupled HESs is the relative lack of long-term data from natural experiments. I will help address this knowledge gap by using computer algorithms to analyze the Twitter stream. With these data I will gauge how sentiments spread through social networks, what role opinion leaders play, how sentiments respond to changing environmental states, and when evolving sentiments translate into action. I will focus on systems where there have been significant changes in ecological variables (e.g. population sizes of species of concern/importance) and human perceptions over the available time period, to ensure there is enough data to create the models. I will begin my search with the following systems, chosen based on their potential to yield useful information due to a combination of high Twitter usage, prominent environmental/health issues, and my existing research collaborations and sources of data: (1) coastal North and South American forest-grassland mosaic ecosystems; (2) dynamics of disease incidence and vaccinating behaviour in the measles-mumps-rubella (MMR) vaccine autism scare; (3) voluntary firewood movement restrictions for forest pest control in Canadian forests. These data will be used in combination with traditional population and ecosystem data sources to develop coupled HES models of the study systems. Although the study systems are diverse, they will be joined by a common approach that uses mathematical and computational models to explore how these systems change over time. Research questions will range from theoretical to applied, such as: (1) How do public conservation priorities and local stakeholder economic priorities interact to determine system outcomes, especially in the context of forest pest control and mosaic ecosystem management? (2) Are some populations more susceptible to pediatric vaccine scares than others, based on their history of immunization and disease prevalence? (3) When does ‘calcification’ of social norms in the form of institutions benefit species conservation, and when does it harm it? In all, I seek to advance ecological research by helping to build empirically informed theoretical foundations of the dynamics of coupled human-environment systems. This will improve our understanding of how natural systems interact with human populations, thereby furthering efforts to create a sustainable future.