Harnessing Insights from Social-Ecological Systems Research for Monitoring Sustainable Development

被引:21
|
作者
Selomane, Odirilwe [1 ,2 ,3 ]
Reyers, Belinda [1 ,3 ]
Biggs, Reinette [1 ,4 ]
Hamann, Maike [5 ]
机构
[1] Stockholm Univ, Stockholm Resilience Ctr, SE-10691 Stockholm, Sweden
[2] CSIR, Nat Resources & Environm, POB 320, Stellenbosch, South Africa
[3] Stellenbosch Univ, Dept Conservat Ecol & Entomol, ZA-7602 Matieland, South Africa
[4] Stellenbosch Univ, Ctr Complex Syst Transit, ZA-7602 Matieland, South Africa
[5] Univ Minnesota, Humphrey Sch Publ Affairs, Minneapolis, MN 55455 USA
基金
新加坡国家研究基金会;
关键词
human wellbeing; sustainability; equity; complex adaptive systems; indicators; ECOSYSTEM SERVICES; DEVELOPMENT GOALS; ENVIRONMENTALISTS PARADOX; BIODIVERSITY INDICATORS; POVERTY ALLEVIATION; CLIMATE-CHANGE; REGIME SHIFTS; TRADE-OFFS; RESILIENCE; SCALE;
D O I
10.3390/su11041190
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The United Nations' Agenda 2030 marks significant progress towards sustainable development by making explicit the intention to integrate previously separate social, economic and environmental agendas. Despite this intention, the Sustainable Development Goals (SDGs) which were adopted to implement the agenda, are fragmented in their formulation and largely sectoral. We contend that while the design of the SDG monitoring is based on a systems approach, it still misses most of the dynamics and complexity relevant to sustainability outcomes. We propose that insights from the study of social-ecological systems offer a more integrated approach to the implementation of Agenda 2030, particularly the monitoring of progress towards sustainable development outcomes. Using five key features highlighted by the study of social-ecological systems (SESs) relevant to sustainable development: (1) social-ecological feedbacks, (2) resilience, (3) heterogeneity, (4) nonlinearity, and (5) cross-scale dynamics. We analyze the current set of SDG indicators based on these features to explore current progress in making them operational. Our analysis finds that 59% of the indicators account for heterogeneity, 33% for cross-scale dynamics, 23% for nonlinearities, and 18% and 17%, respectively, for social-ecological feedbacks and resilience. Our findings suggest limited use of complex SES science in the current design of SDG monitoring, but combining our findings with recent studies of methods to operationalize SES features suggests future directions for sustainable development monitoring for the current as well as post 2030 set of indicators.
引用
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页数:36
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