Dynamics of coupled human-environment systems

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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.