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Research Area 8 - Analyzing spatial and temporal change of urban plant communities in Shanghai


Shanghai has experienced extensive urban expansion over the past three decades (Zhao et al. 2006). The results of Shanghai’s increasing urbanization are emergence of urban heat island (higher ambient temperature in urban areas relative to the surrounding area), water, air, and soil pollution (Zhao et al. 2006). Also, urbanization has resulted in residential and commercial landscape with planted homogeneous vegetation communities. The spatial variation in vegetation communities has been attributed to heterogeneity in resources availability reflecting social, economic and cultural influences (Chesson 2000). The long term studies will quantify gradients of resource availability and disturbances, and study the integrate land use, legacy effects, socioeconomic status, and cultural differences because these factors mediate the human-environment interactions and result in varied ecological condition (Chen et al. 2010).  Such effects are extensively studied, and models have been developed in the West, mainly in US (e.g., Grimm et al. 2000, Pickett et al. 2001, Hope et al. 2003). Due to the difference in social systems, green space in Shanghai is mainly managed by local government agency, such as the Shanghai Research Institute of Landscape and Gardening (SRILG). To date, however, long-term and spatially explicit monitoring of the urbanization and plant communities at the entire Shanghai area has not been conducted. 

The objectives of this project include: (i) analyzing spatial and temporal variations of plant communities at different locations across Shanghai; (ii) identifying the relationships between changes in plant communities and surrounding environmental and social condition; and (iii) analyzing the observed patterns and providing implications for green space management in Shanghai. The data will be collected through site surveys and supplemented by previous records. Each site will be mapped to delineate the surface cover and surrounding physical condition. Spatial statistical techniques will be applied to data specific to Shanghai. Our expected results include (i) describing patterns of spatial and temporal distribution of plant communities in Shanghai; (ii) understanding the driving forces related to changes in plant communities; and (iii) comparing and further developing models that predict the relationships between urbanization driving forces and plant community changes in US and China. REU students will be involved with data acquisition, GIS processing, and model development and testing. The REU students will also have opportunities to interact with personnel from city government and local people to better understand the issues that are unique to China.