People, Institutions, and Pixels:Linking Remote Sensing and Social Science to Understand Social Adaptation to Environmental Change.

Social Adaptation;Environmental Change;Social-ecological Systems;Sustainability;Remote Sensing;Social Science;Natural Resources and Environment;Science;Natural Resources and Environment

Wang, JunAgrawal, Arun ;

University of Michigan

关键词: Social Adaptation;    Environmental Change;    Social-ecological Systems;    Sustainability;    Remote Sensing;    Social Science;    Natural Resources and Environment;    Science;    Natural Resources and Environment;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/97961/junw_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

This research presents an interdisciplinary approach, which links theories from grassland ecology and institutional economics and methods from remote sensing, field ecological measurements, household survey, statistical modeling, and agent-based computational modeling, to study the dynamics of grassland social-ecological systems on the Mongolian plateau, including Mongolia and Inner Mongolia Autonomous Region, China, and social adaptation to climate change and ecosystem degradation. A range of research questions in the fields of remote sensing of vegetation, drivers and mechanisms of resource dynamics, and societal adaptation to environmental change were addressed at regional and local scales. Using a remote sensing based light-use efficiency model, I estimated annual grassland net primary productivity on the Mongolian plateau over the past three decades and analyzed the spatial-temporal dynamics of annual grassland net primary productivity in response to climate variability and change. In order to account for the insufficiency of using multispectral images to map grassland communities and monitor grassland dynamics, especially grassland degradation, I analyzed the potential for using hyperspectral remote sensing to detect the quantity and quality of dominant grassland communities across ecological gradients of the Inner Mongolian grasslands, based on field data collected across a large geographic area. The dynamics of grassland productivity on the Mongolian plateau over the past decades was interpreted both qualitatively and quantitatively. I used spatial panel data models to identify the biophysical and socioeconomic factors driving the interannual dynamics of grassland net primary productivity across agro-ecological zones on the Mongolian plateau over the past three decades. Social adaptations to climate change and grassland degradation on the Mongolian plateau was studied at both household and community levels. A household survey was designed and implemented across ecological gradients of Mongolia (210 households) and Inner Mongolia, China (540 households), to study livelihood adaptation practices of herders to environmental change. Informed by the empirical studies, I built an agent-based computational model to explore social-ecological outcomes of pasture use under alternative institutional (i.e., grazing sedentarization, pasture rental markets, and reciprocal use of pastures) and climatic (i.e., frequencies of climate hazards) scenarios.