TY - JOUR
T1 - A decision-making framework for evaluating environmental tradeoffs in enhancing ecosystem services across complex agricultural landscapes
AU - Acero Triana, Juan S.
AU - Chu, Maria L.
AU - Shipley, Nathan J.
AU - Van Riper, Carena J.
AU - Stewart, William P.
AU - Suski, Cory D.
N1 - Funding Information:
This work was supported by the U.S. Department of Agriculture (USDA) - National Institute of Food and Agriculture (NIFA) [Award No. 2018-68002-27918; Project No. ILLU-741-612 ].
PY - 2022/7/15
Y1 - 2022/7/15
N2 - Decision-making processes to ensure sustainability of complex agro-ecosystems must simultaneously accommodate production goals, environmental soundness, and social relevancy. This means that besides environmental indicators and human activities, stakeholders' perceptions need to be considered in the decision-making process to enable the adoption of mitigation practices. Thus, the decision-making process equates to a multi-criteria and multi-objective problem, requiring additional tools and methods to analyze the possible tradeoffs among decision alternatives based on social acceptability. This study was aimed at establishing a decision support system that integrates hydro-ecologic models and socio-cultural perspectives to identify and assess feasible land management alternatives that can enhance the Kaskaskia River Watershed (KRW) ecosystem services in Illinois (USA). The Soil and Water Assessment Tool (SWAT) was used to simulate the spatio-temporal response of nine environmental predictors to four major management alternatives (crop rotation, cover cropping, reduced tillage, modified fertilizer application) based on stakeholder acceptability and environmental soundness, under 32 distinct climate projections. The stochastic multicriteria acceptability analysis (SMAA) was then applied to classify the management alternatives from the least to the most efficient based on three preference schemes: no preference, expert stakeholders’ preference, and non-expert stakeholders’ preference. Results showed that preference information on watershed ecosystem services is crucial to guide the decision-making process when a broad spectrum of criteria is considered to assess the management alternatives' systemic response. The disparity between expert and non-expert stakeholders' preferences showed different rankings of alternatives across several subcatchments, where the two-year corn one-year soybean rotation scheme was expected to offer the best management alternative to ensure a sustainable agro-production system in the highly cultivated subcatchments of the KRW. In contrast, non-conventional tillage practices were expected to contravene agricultural production, and therefore should be discarded unless combined with complementary measures. This study will enable stakeholders to identify the most suitable management practices to adapt to natural and anthropogenic changes and encourage engagement between government institutions and local communities (multi-stakeholder consensus) to provide a better platform for decision-making.
AB - Decision-making processes to ensure sustainability of complex agro-ecosystems must simultaneously accommodate production goals, environmental soundness, and social relevancy. This means that besides environmental indicators and human activities, stakeholders' perceptions need to be considered in the decision-making process to enable the adoption of mitigation practices. Thus, the decision-making process equates to a multi-criteria and multi-objective problem, requiring additional tools and methods to analyze the possible tradeoffs among decision alternatives based on social acceptability. This study was aimed at establishing a decision support system that integrates hydro-ecologic models and socio-cultural perspectives to identify and assess feasible land management alternatives that can enhance the Kaskaskia River Watershed (KRW) ecosystem services in Illinois (USA). The Soil and Water Assessment Tool (SWAT) was used to simulate the spatio-temporal response of nine environmental predictors to four major management alternatives (crop rotation, cover cropping, reduced tillage, modified fertilizer application) based on stakeholder acceptability and environmental soundness, under 32 distinct climate projections. The stochastic multicriteria acceptability analysis (SMAA) was then applied to classify the management alternatives from the least to the most efficient based on three preference schemes: no preference, expert stakeholders’ preference, and non-expert stakeholders’ preference. Results showed that preference information on watershed ecosystem services is crucial to guide the decision-making process when a broad spectrum of criteria is considered to assess the management alternatives' systemic response. The disparity between expert and non-expert stakeholders' preferences showed different rankings of alternatives across several subcatchments, where the two-year corn one-year soybean rotation scheme was expected to offer the best management alternative to ensure a sustainable agro-production system in the highly cultivated subcatchments of the KRW. In contrast, non-conventional tillage practices were expected to contravene agricultural production, and therefore should be discarded unless combined with complementary measures. This study will enable stakeholders to identify the most suitable management practices to adapt to natural and anthropogenic changes and encourage engagement between government institutions and local communities (multi-stakeholder consensus) to provide a better platform for decision-making.
KW - Agro-ecosystems
KW - Climate change
KW - Decision-making
KW - Environmental tradeoffs
KW - SMAA
KW - Social acceptability
UR - http://www.scopus.com/inward/record.url?scp=85130638760&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85130638760&partnerID=8YFLogxK
U2 - 10.1016/j.jenvman.2022.115077
DO - 10.1016/j.jenvman.2022.115077
M3 - Article
C2 - 35472836
SN - 0301-4797
VL - 314
JO - Journal of Environmental Management
JF - Journal of Environmental Management
M1 - 115077
ER -