University of Vermont

Insu Koh

Insu Koh Postdoctoral Research Associate, RSENR

PhD, Environmental/City Planning, Seoul National University

MS, Environmental/City Planning, Seoul National University

BS, Biology, Yonsei University

 

 

Advisor: Taylor Ricketts
Email: Insu.Koh@uvm.edu
CV


Insu is broadly interested in how landscape structure and composition influence biodiversity, organism dispersal and ecosystem services. This interest began when he first considered the role of traditional Korean landscape configuration in mitigating weather conditions. These interests in landscape ecology have led him to investigate how various landscapes differently influence the delivery of ecosystem service. Using statistical and modeling techniques, he has studied the effects of habitat connectivity on the movements of life organisms that provide seed dispersal and biological control ecosystem services. Insu's current research focuses on the development of a spatially-explicit statistical model of crop pollination services, which can account for ecological and economic factors.

He received his Ph.D. in environmental/city planning from the Graduate School of Environmental Studies at Seoul National University and previously conducted post-doctoral research on graph and circuit-theory connectivity models of conservation biological control agents at Purdue University. He is currently a post-doctoral associate at the Gund Institute for Ecological Economics at the University of Vermont.

I am currently a postdoctoral associate advised by Dr. Taylor Ricketts at the Gund Institute for Ecological Economics and co-advised by Dr. Eric Lonsdorf, Research Scientist at the Chicago Botanic Garden. My research goal is to develop a spatially-explicit statistical model of pollination services and apply this model to several agricultural landscapes and crops within the US. I am particularly interested in: (1) understanding how habitat management and surrounding landscape influence the abundance and diversity of bees in crops, (2) developing a spatially-explicit statistical model of pollination service prediction in different crops, and (3) predicting impacts of habitat enhancements on pollinator communities and crop productivity. To address these issues, my current research uses ArcGIS and R to conduct spatial and statistical analyses and to develop a pollination model.

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At the Gund Institute:
As a post-doc research associate Insu is currently working on sustainable pollination strategies for U.S. specialty crops.

Last modified August 08 2013 11:56 AM

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