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Overview of the SES Framework

The SES framework explicitly aims to bridge disciplinary and methodological boundaries while facilitating the synthesis of disparate studies by providing a common classificatory framework containing potentially important SES attributes and relationships. Derived from the IAD framework, the SES framework retains the action situation (Fig. 6.1), a general game-theoretic model of interdependent choice, and carries with it much of the intellectual history of the Bloomington School (Kiser and Ostrom 1982; Ostrom et al. 1994; Crawford and Ostrom 1995; Ostrom 2005). In general, outcomes are understood to be the aggregate result of individual interactions and decisions in action situations structured by attributes of four core components: resources (RU), resource systems (RS), governance systems (GS), and actors (A). Although this simple model is thought to encompass and explain diverse outcomes in SESs, analytical complexity emerges from the wide range of attributes that collectively define each component and their interactions within action situations. The most recent elaboration of the SES framework (Epstein et al. 2013) includes more than 30 potentially influential attributes pertaining to the 4 core components of SESs (Table 6.1). Since the SES framework is structured as a multitiered classificatory system, each of these attributes can be further unpacked into types and subtypes such that the full suite of potentially relevant conditions is effectively unknown (Ostrom and Cox 2010).

Fig. 6.1 Analytical structure of the social-ecological system framework (Source: Based on McGinnis and Ostrom forthcoming)

To date, the SES framework has been used to study a wide range of systems, including forests, fisheries, irrigation systems, and nature-based tourism (Fleischman et al. 2010; Blanco 2011; Gutierrez et al. 2011; Basurto and Nenadovic 2012; Cinner et al. 2012; Basurto et al. 2013). In adopting a common framework, these studies may advance knowledge more rapidly by generating observations on a common set of attributes that can be readily compared or integrated for large-n analysis. Alternatively, individual case studies may be used to add diagnostic pieces to the overall puzzle of sustainability (Basurto and Ostrom 2009).

The structure of the framework is somewhat flexible, allowing for the integration of additional concepts and attributes to improve the study of SESs. Although we know of no studies of power that have derived from engagement with the SES framework, we do not rush to add attributes here. Given the wide range of conceptualizations of power from different fields and strands of literature, adding a single attribute, “power,” would likely create considerable confusion regarding how such an attribute could be operationalized or measured, working contrary to the goal of providing a common classificatory system for SES research. Instead, close examination of various conceptualizations of power reveals that many indicators thereof are already included among the existing attributes of the framework. Thus, our analysis focuses on the extent to which the existing attributes of the SES framework, whether individually or in combination, can be used to operationalize and measure power. We then apply these measures to conduct an illustrative analysis of the

Table 6.1 The social-ecological system framework

Ecological Rules (ER)

ER1 – Physical rules. ER2 – Chemical rules. ER3 – Biological rules

Social, economic, and political settings (S)

S1 – Economic development. S2 – Demographic trends. S3 – Political stability

S4 – Other governance systems. S5 – Markets. S6 – Media organizations. S7 – Technology

Resource Systems (RS)

Governance Systems (GS)

RS1 – Sector (e.g., water, forests, pasture) RS2 – Clarity of system boundaries

RS3 – Size of resource system

RS4 – Human-constructed facilities RS5 – Productivity of system

RS6 – Equilibrium properties

RS7 – Predictability of system dynamics RS8 – Storage characteristics

RS9 – Location

GS1 – Government organizations GS2 – Nongovernment organizations GS3 – Network structure

GS4 – Property-rights systems GS5 – Operational-choice rules GS6 – Collective-choice rules GS7 – Constitutional-choice rules

GS8 – Monitoring and sanctioning rules

Resource Units (RU)

Actors (A)

RU1 – Resource unit mobility RU2 – Growth or replacement rate

RU3 – Interaction among resource units RU4 – Economic value

RU5 – Number of units

RU6 – Distinctive characteristics

RU7 – Spatial and temporal distribution

A1 – Number of relevant actors A2 – Socioeconomic attributes A3 – History or past experiences A4 – Location

A5 – Leadership/entrepreneurship A6 – Norms (trust-reciprocity)/social

capital

A7 – Knowledge of SES/mental models A8 – Importance of resource

(dependence)

A9 – Technologies available

Action situations: Interactions (I) → Outcomes (O)

Activities and processes

Outcome criteria

I1 – Harvesting

I2 – Information sharing

I3 – Deliberation processes I4 – Conflicts

I5 – Investment activities I6 – Lobbying activities

I7 – Self-organizing activities I8 – Networking activities

I9 – Monitoring activities I10 – Evaluative activities

O1 – Social performance measures (e.g., efficiency, equity, accountability, sustainability)

O2 – Ecological performance measures (e.g., overharvested, resilience, biodiversity, sustainability)

O3 – Externalities to other SESs

Related Ecosystems (ECO)

ECO1 – Climate patterns. ECO2 – Pollution patterns. ECO3 – Flows into and out of focal SES

Source: Adapted from McGinnis and Ostrom (forthcoming)

general hypothesis that “power matters” with regard to SES outcomes. Our application is demonstrative in the sense that its primary purpose is to illustrate how such an analysis may be conducted; the results then are not intended to be interpreted in any conclusive sense.

 
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