DOI
doi.org/10.1126/science.1172133

Summary
A major problem worldwide is the potential loss of fisheries, forests, and water resources. Understanding of the processes that lead to improvements in or deterioration of natural resources is limited, because scientific disciplines use different concepts and languages to describe and explain complex social-ecological systems (SESs). Without a common framework to organize findings, isolated knowledge does not cumulate. Until recently, accepted theory has assumed that resource users will never self-organize to maintain their resources and that governments must impose solutions. Research in multiple disciplines, however, has found that some government policies accelerate resource destruction, whereas some resource users have invested their time and energy to achieve sustainability. A general framework is used to identify 10 subsystem variables that affect the likelihood of self-organization in efforts to achieve a sustainable SES.

Relevance for Complex Systems Knowledge
The point of departure for this article is that researchers on complex socio-ecoogical systems in lack of a common framework use different languages which prehibit a true accumulation of knowledge. Elinor Ostrom then sets out to provide such a framework. In the framework she identifies 10 subsystem variables that affect the likelihood of self-organization in efforts to achieve a sustainable SES.

In a complex SES, subsystems such as a resource system (e.g., a coastal fishery), resource units (lobsters), users (fishers), and governance systems (organizations and rules that govern fishing on that coast) are relatively separable but interact to produce outcomes at the SES level, which in turn feed back to affect these subsystems and their components, as well other larger or smaller SESs.

Scholars have tended to develop simple theoretical models to analyze aspects of resource problems and to prescribe universal solutions.A core challenge in diagnosing why some SESs are sustainable whereas others collapse is the identification and analysis of relationships among multiple levels of these complex systems at different spatial and temporal scales.

Understanding a complex whole requires knowledge about specific variables and how their component parts are related. This process is complicated, however, because entirely different frameworks, theories, and models are used by different disciplines to analyze their parts of the complex multilevel whole. A common, classificatory framework is needed to facilitate multidisciplinary efforts toward a better understanding of complex SESs.

Ostrom present an updated version of a multilevel, nested framework for analyzing outcomes achieved in SESs. Consist of four first-level core subsystems of an SES that affect each other as well as linked social, economic, and political settings and related ecosystems.
The subsystems are:

(i) resource systems;
(ii) resource units ;
(iii) governance systems and
(iv) users 

Each core subsystem is made up of multiple second-level variables  which are further composed of deeper-level variables  depending the system in focus.A set of generalized second level varibales are specified in the article. Besides components to the subsystems it also contain a list of typical interactions and outcomes.

Point of Strength
A framework like the one proposed is useful in providing a common set of potentially relevant variables and their subcomponents to use in the design of data collection instruments, the conduct of fieldwork, and the analysis of findings about the sustainability of complex SESs. It can also be used in teaching of possible ways of modelling and understanding complex SES.

There are other frameworks that could be used in comparison  to discuss what overlaås and differences signify int terms of paradigms as well as for operationalization. 8Ontological and epistemological discussions)