Tuesday 6
The Social-ecological systems meta-analysis database (SESMAD) project
Michael Cox
› 11:35 - 12:30 (55min)
› JOFFRE 1-5
Understanding governance of large freshwater systems: a comparative analysis of environmental governance in national and transnational watersheds
Sergio Villamayor-Tomas  1@  , Michael Cox  2@  , Irene Pere Ibarra  3@  , Andreas Thiel  4@  , Frank Van Laerhoven  5@  
1 : Humboldt University  -  Website
2 : Dartmouth College  -  Website
3 : Arizona State University  -  Website
4 : Humboldt University  -  Website
5 : Utrecth University  -  Website

The capacity of common pool resource (CPR) theory to explain resource allocation problems under scarcity conditions in local contexts is well proven. The conceptual and empirical validity of the theory to understand the management of other environmental problems in large-scale contexts is a more open question. This paper addresses this question in three ways. First, the paper includes a thorough conceptualization of the similarities and differences between water scarcity and water pollution problems. Particular attention is paid to the characteristics of the resources and actors involved in the two types of problems and how these characteristics mediate the emergence and governance of externalities, collective action dilemmas and transaction costs. Second, the paper explores the opportunities and challenges of managing the two different types of problems in the context of a set of large-scale fresh water systems. Particular attention is paid to the distinction between national and transnational systems in an attempt to disentangle the effects of physical scale from that of political boundaries on governance. Third, the paper draws some hypotheses about the contribution of resource, social and governance characteristics to resource conservation across types of environmental problems and boundary contexts. Methodologically, the paper relies on the Social-Ecological Systems Meta-Analysis database (SESMAD) and coding protocol and a stratified random sample based on existing world river datasets.


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