TY - JOUR
T1 - A dynamic and spatially explicit modeling approach to identify the ecosystem service implications of complex urban systems interactions
AU - Pan, Haozhi
AU - Zhang, Le
AU - Cong, Cong
AU - Deal, Brian
AU - Wang, Yutao
N1 - Funding Information:
The work used the ROGER supercomputer, which is supported by NSF under grant number: 1429699. We thank Shaowen Wang and Anand Padmanabhan for their assistance with high performance computing jobs, which was made possible through the CyberGIS Center Help Desk. We are also very grateful for the anonymous reviewers and editor for their constructive comments, which helped improve the quality of the paper.
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/7
Y1 - 2019/7
N2 - A comprehensive understanding and modeling of socio-ecological systems can better assess how human-induced urban growth affects ecosystem service. This paper demonstrates a comprehensive socio-ecological system modeling approach to identify ecosystem service impacts that result from human activities within large, complex urban systems. It adds to the existing ecosystem impact assessment approaches by integrating spatiotemporal and socio-ecological process model with dynamic interaction and feedback between models and policies. The approach couples regional economics, urban land-use, and ecosystem interactions in a fine scaled (30 × 30 m) modeling framework with multiple time steps and feedback. The coupled model fuses a regional econometric input-output model with a dynamic land-use allocation model that spatially allocates the residential and commercial lands that are needed to satisfy the identified economic changes on an annual basis. A dynamic and spatially explicit index is constructed to measure the potential impacts of the economic/land use interactions on available ecosystem services. A scenario analysis is performed to test various ecologically oriented policy outcomes against noted ecosystem service impacts. The Chicago metropolitan region constitutes the study area with forecasts to 2040. Analysis results prove that models without inclusion of feedback dynamics and uncertainties could significantly under-estimate resulting ecosystem service impacts without. The scenario simulation shows a significant land-use developmental pattern restructure occurs when preservative policies are reinforced and significant ecosystem service loss reduction can also be achieved.
AB - A comprehensive understanding and modeling of socio-ecological systems can better assess how human-induced urban growth affects ecosystem service. This paper demonstrates a comprehensive socio-ecological system modeling approach to identify ecosystem service impacts that result from human activities within large, complex urban systems. It adds to the existing ecosystem impact assessment approaches by integrating spatiotemporal and socio-ecological process model with dynamic interaction and feedback between models and policies. The approach couples regional economics, urban land-use, and ecosystem interactions in a fine scaled (30 × 30 m) modeling framework with multiple time steps and feedback. The coupled model fuses a regional econometric input-output model with a dynamic land-use allocation model that spatially allocates the residential and commercial lands that are needed to satisfy the identified economic changes on an annual basis. A dynamic and spatially explicit index is constructed to measure the potential impacts of the economic/land use interactions on available ecosystem services. A scenario analysis is performed to test various ecologically oriented policy outcomes against noted ecosystem service impacts. The Chicago metropolitan region constitutes the study area with forecasts to 2040. Analysis results prove that models without inclusion of feedback dynamics and uncertainties could significantly under-estimate resulting ecosystem service impacts without. The scenario simulation shows a significant land-use developmental pattern restructure occurs when preservative policies are reinforced and significant ecosystem service loss reduction can also be achieved.
KW - Coupled human-nature systems
KW - Ecosystem service
KW - Land-use
KW - Planning Support Systems
KW - Scenario planning
KW - Socio-ecological processes
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U2 - 10.1016/j.ecolind.2019.02.059
DO - 10.1016/j.ecolind.2019.02.059
M3 - Article
AN - SCOPUS:85062413607
SN - 1470-160X
VL - 102
SP - 426
EP - 436
JO - Ecological Indicators
JF - Ecological Indicators
ER -