DOI of Published Version
Studies that assess the distribution of benefits provided by ecosystem services across urban areas are increasingly common. Nevertheless, current knowledge of both the supply and demand sides of ecosystem services remains limited, leaving a gap in our understanding of balance between ecosystem service supply and demand that restricts our ability to assess and manage these services. The present study seeks to fill this gap by developing and applying an integrated approach to quantifying the supply and demand of a key ecosystem service, carbon storage and sequestration, at the local level. This approach follows three basic steps: (1) quantifying and mapping service supply based upon Light Detection and Ranging (LiDAR) processing and allometric models, (2) quantifying and mapping demand for carbon sequestration using an indicator based on local anthropogenic CO2 emissions, and (3) mapping a supply-to-demand ratio. We illustrate this approach using a portion of the Twin Cities Metropolitan Area of Minnesota, USA. Our results indicate that 1735.69 million kg carbon are stored by urban trees in our study area. Annually, 33.43 million kg carbon are sequestered by trees, whereas 3087.60 million kg carbon are emitted by human sources. Thus, carbon sequestration service provided by urban trees in the study location play a minor role in combating climate change, offsetting approximately 1% of local anthropogenic carbon emissions per year, although avoided emissions via storage in trees are substantial. Our supply-to-demand ratio map provides insight into the balance between carbon sequestration supply in urban trees and demand for such sequestration at the local level, pinpointing critical locations where higher levels of supply and demand exist. Such a ratio map could help planners and policy makers to assess and manage the supply of and demand for carbon sequestration.
Journal Article Version
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Published Article/Book Citation
PLoS ONE 10(8): e0136392. https://doi.org/10.1371/ journal.pone.0136392
© 2015 Zhao, Sander
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This work is licensed under a Creative Commons Attribution 4.0 License.