A diagnostic procedure for applying the social-ecological systems framework in diverse cases

The framework for analyzing sustainability of social-ecological systems (SES) framework of Elinor Ostrom is a multitier collection of concepts and variables that have proven to be relevant for understanding outcomes in diverse SES. The first tier of this framework includes the concepts resource system (RS) and resource units (RU), which are then further characterized through lower tier variables such as clarity of system boundaries and mobility. The long-term goal of framework development is to derive conclusions about which combinations of variables explain outcomes across diverse types of SES. This will only be possible if the concepts and variables of the framework can be made operational unambiguously for the different types of SES, which, however, remains a challenge. Reasons for this are that case studies examine other types of RS than those for which the framework has been developed or consider RS for which different actors obtain different kinds of RU. We explore these difficulties and relate them to antecedent work on common-pool resources and public goods. We propose a diagnostic procedure which resolves some of these difficulties by establishing a sequence of questions that facilitate the step-wise and unambiguous application of the SES framework to a given case. The questions relate to the actors benefiting from the SES, the collective goods involved in the generation of those benefits, and the action situations in which the collective goods are provided and appropriated. We illustrate the diagnostic procedure for four case studies in the context of irrigated agriculture in New Mexico, common property meadows in the Swiss Alps, recreational fishery in Germany, and energy regions in Austria. We conclude that the current SES framework has limitations when applied to complex, multiuse SES, because it does not sufficiently capture the actor interdependencies introduced through RS and RU characteristics and dynamics

Identification of Antibiotic Resistance Gene Hosts in Treatment Wetlands Using a Single-Cell Based High-Throughput Approach

Determining the prevalence of antimicrobial resistance (AMR) in non-clinical settings is vital for better management of the global AMR crisis. Untreated and even treated wastewaters are important sources that release AMR into the environment. Methodologically, it is difficult to generate a comprehensive in situ profile of antibiotic resistance gene hosts. Here, we used epicPCR (emulsion, paired isolation, and concatenation PCR) as a cultivation-independent method to reveal the host profiles of the AMR indicator genes intI1, sul1, sul2, and dfrA1 in two constructed wetlands treating municipal wastewater. Overall, the epicPCR analysis revealed a profile of AMR indicator gene hosts that is consistent with literature data from cultivation-based approaches. Most carriers of antibiotic resistance (AR) genes and likely of class 1 integrons belonged to the Gammaproteobateria, particularly the Burkholderiaceae and Rhodocyclaceae families, followed by members of the Campylobacterota, Desulfobacterota, and Firmicutes. The analysis also identified several novel hosts for the indicator genes widely distributed in the wetlands, including the genera Legionella and Ralstonia. Therefore, the application of epicPCR has produced an expanded insight into the in situ indicator gene host profile, while highlighting the role of the environment as a reservoir for AMR

Application of the SES framework for model-based analysis of the dynamics of social-ecological systems

Social-ecological systems (SES) are dynamic systems that continuously change in response to internal or external pressures. A better understanding of the interactions of the social and ecological systems that drive those dynamics is crucial for the development of sustainable management strategies. Dynamic models can serve as tools to explore social-ecological interactions; however, the complexity of the studied systems and the need to integrate knowledge, theories, and approaches from different disciplines pose considerable challenges for their development. We assess the potential of Ostrom’s general SES framework (SESF) to guide a systematic and transparent process of model development in light of these difficulties. We develop a stepwise procedure for applying SESF to identify variables and their relationships relevant for an analysis of the SES. In doing so we demonstrate how the hierarchy of concepts in SESF and the identification of social-ecological processes using the newly introduced process relationships can help to unpack the system in a systematic and transparent way. We test the procedure by applying it to develop a dynamic model of decision making in the management of recreational fisheries. The added value of the common framework lies in the guidance it provides for (1) a structured approach to identifying major variables and the level of detail needed, and (2) a procedure that enhances model transparency by making explicit underlying assumptions and choices made when selecting variables and their interactions as well as the theories or empirical evidence on which they are based. Both aspects are of great relevance when dealing with the complexity of SES and integrating conceptual backgrounds from different disciplines. We discuss the advantages and difficulties of the application of SESF for model development, and contribute to its further refinement.Policy Analysi