TY - JOUR
T1 - Network analysis as a tool for quantifying the dynamics of metacoupled systems
T2 - An example using global soybean trade
AU - Schaffer-Smith, Danica
AU - Tomscha, Stephanie A.
AU - Jarvis, Karl J.
AU - Maguire, Dorothy Y.
AU - Treglia, Michael L.
AU - Liu, Jianguo
N1 - Funding Information:
DS was supported by a NASA Earth and Space Science Fellowship (NNX13AQ15H) and a P.E.O. Scholar Award. SAT was funded by the Canadian Network for Aquatic Ecosystem Services and the Holdsworth Foundation. KJJ was supported in part by the U.S. Department of Defense through the Strategic Environmental Research and Development Program (SERDP; project RC-1722). DYM was supported by a USDA-ARS Area Wide Project Grant. MLT was partially supported by the NSF-EPSCoR Program (OIA-1301789). JL was supported by U.S. National Science Foundation and Michigan AgBioResearch. This research built on initial discussions among a group of junior researchers at the 2014 Annual Meeting of the US Regional Association of the International Association for Landscape Ecology, which also included Marufa Akther, Caroline Curtis, Whalen Dillon, Lisa Green, Binbin Li, Alexis Maldonado, Katherine Renwick, Eric Taber, Hui Xu, Hongbo Yang. Funding to support attendance at the US-IALE meeting was provided by the NASA-MSU Professional Enhancement Awards Program. We thank Amanda Schwantes and four anonymous reviewers for providing thoughtful comments, which greatly improved the quality of the manuscript.
Publisher Copyright:
© 2018 by the author(s).
PY - 2018/12
Y1 - 2018/12
N2 - The metacoupling framework provides grounds for characterizing interactions within and between coupled human and natural systems, yet few studies quantify the nuances of these systems. Network analysis is a powerful and flexible tool that has been used to quantify social, economic, and ecological systems. Our objective was to evaluate the utility of network analysis for quantifying metacoupled systems by assessing global soybean trade among 217 countries from 1986 to 2013. We identified and quantified sending and receiving systems, subnetworks and flow pathways, changes over time and across scales, feedbacks, and associations between trade and tropical deforestation. Although a total of 165 distinct cliques were identified within the network, a few key players were disproportionately influential in the 2872 partnerships, including Brazil (37.5%), China (48.6%), and the USA (72.3%). Total network density increased five-fold over the study period with an increasingly smaller set of countries heavily engaged in trade, posing sustainability and food security concerns. We found evidence of a positive feedback where countries with established trade partnerships were more likely to expand trade relationships over the study period. Trade patterns were not explained by regional or continental geography, highlighting limitations of neighborhood analyses commonly used in ecology. We also found evidence of a link between soybean trade and tropical deforestation; in pantropical countries participating in soybean trade, cumulative soybean exports for the period 2000–2012 were strongly associated with remotely sensed estimates of forest loss by country (Rsq = 0.35, p < 0.0001). We demonstrated that network analyses can be used to quantitatively assess relationships between metacoupled social-ecological systems. Increased data access and platforms for integrating diverse data sources using multidisciplinary tools will be key to pushing the boundaries of quantitative metacoupled systems research.
AB - The metacoupling framework provides grounds for characterizing interactions within and between coupled human and natural systems, yet few studies quantify the nuances of these systems. Network analysis is a powerful and flexible tool that has been used to quantify social, economic, and ecological systems. Our objective was to evaluate the utility of network analysis for quantifying metacoupled systems by assessing global soybean trade among 217 countries from 1986 to 2013. We identified and quantified sending and receiving systems, subnetworks and flow pathways, changes over time and across scales, feedbacks, and associations between trade and tropical deforestation. Although a total of 165 distinct cliques were identified within the network, a few key players were disproportionately influential in the 2872 partnerships, including Brazil (37.5%), China (48.6%), and the USA (72.3%). Total network density increased five-fold over the study period with an increasingly smaller set of countries heavily engaged in trade, posing sustainability and food security concerns. We found evidence of a positive feedback where countries with established trade partnerships were more likely to expand trade relationships over the study period. Trade patterns were not explained by regional or continental geography, highlighting limitations of neighborhood analyses commonly used in ecology. We also found evidence of a link between soybean trade and tropical deforestation; in pantropical countries participating in soybean trade, cumulative soybean exports for the period 2000–2012 were strongly associated with remotely sensed estimates of forest loss by country (Rsq = 0.35, p < 0.0001). We demonstrated that network analyses can be used to quantitatively assess relationships between metacoupled social-ecological systems. Increased data access and platforms for integrating diverse data sources using multidisciplinary tools will be key to pushing the boundaries of quantitative metacoupled systems research.
KW - Agriculture
KW - Brazil
KW - China
KW - Connectivity
KW - Coupled human and natural systems
KW - Export
KW - Graph theory
KW - Import
KW - Social-ecological systems
KW - Telecoupling
KW - USA
UR - http://www.scopus.com/inward/record.url?scp=85059535747&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059535747&partnerID=8YFLogxK
U2 - 10.5751/ES-10460-230403
DO - 10.5751/ES-10460-230403
M3 - Article
AN - SCOPUS:85059535747
SN - 1708-3087
VL - 23
JO - Conservation Ecology
JF - Conservation Ecology
IS - 4
M1 - 3
ER -