Theorizing benefits and constraints in collaborative environmental governance: a transdisciplinary social-ecological network approach for empirical investigations

被引:124
|
作者
Bodin, Orjan [1 ,2 ]
Robins, Garry [3 ]
McAllister, Ryan R. J. [4 ]
Guerrero, Angela M. [5 ,6 ]
Crona, Beatrice [1 ,7 ]
Tengo, Maria [1 ]
Lubell, Mark [8 ]
机构
[1] Stockholm Univ, Stockholm Resilience Ctr, Stockholm, Sweden
[2] Duke Univ, Marine Lab, Nicholas Sch Environm, Durham, NC 27706 USA
[3] Univ Melbourne, Melbourne Sch Psychol Sci, Melbourne, Vic 3010, Australia
[4] CSIRO, Stockholm, Sweden
[5] Univ Queensland, Australian Res Council, Ctr Excellence Environm Decis, Brisbane, Qld 4072, Australia
[6] Univ Queensland, Sch Biol Sci, Brisbane, Qld 4072, Australia
[7] Royal Swedish Acad Sci, Global Econ Dynam & Biosphere, Stockholm, Sweden
[8] Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA
来源
ECOLOGY AND SOCIETY | 2016年 / 21卷 / 01期
基金
澳大利亚研究理事会;
关键词
collaborative governance; connectivity; exponential random graph models (ERGM); interdisciplinary; networks; social-ecological fit; social-ecological networks; social-ecological systems; SCALE MISMATCHES; INSTITUTIONS; CONNECTIVITY; ECOSYSTEMS; MANAGEMENT; SYSTEMS; FOREST; FIT;
D O I
10.5751/ES-08368-210140
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
When environmental processes cut across socioeconomic boundaries, traditional top-down government approaches struggle to effectively manage and conserve ecosystems. In such cases, governance arrangements that foster multiactor collaboration are needed. The effectiveness of such arrangements, however, depends on how well any ecological interdependencies across governed ecosystems are aligned with patterns of collaboration. This inherent interdisciplinary and complex problem has impeded progress in developing a better understanding of how to govern ecosystems for conservation in an increasingly interconnected world. We argue for the development of empirically informed theories, which are not only able to transcend disciplinary boundaries, but are also explicit in taking these complex social-ecological interdependences into account. We show how this emerging research frontier can be significantly improved by incorporating recent advances in stochastic modeling of multilevel social networks. An empirical case study from an agricultural landscape in Madagascar is reanalyzed to demonstrate these improvements.
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收藏
页数:14
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