# Explaining and Measuring Social-Ecological Pathways: The Case of Global Changes and Water Security
## 3 SES Evolution and Measurement: Insights from the Case of Water Security
The persistent diversity in perspectives and applications of water security suggests that scholars adapt the concept to the contexts of the cases they are studying. In the same sample of studies, 60% of the studies using a definition of water security offer a new definition, and thus are case-based [60]. While this can suggest the need for a more community-context view to understand and realize water security, it might also suggest a limited generalizability of water security and hinder our knowledge of water security. Finally, the third limitation of knowledge accumulation around water security focuses are static, or measuring cross-sectional, meaning that samples cover only one period of time (mostly a year). It prevents the study of water security evolution, and of SESs more generally. As an illustration, a significant strength of water security in comparison to Integrated Water Resource Management (IWRM) and nexus--competing concepts--is that water security is thought as a lever of development and transitions [2,4]. Integrated Water Resource Management and nexus consist mostly of refining an existing situation without any systemic change in most cases [62,63]. Integrated Water Resource Management and nexus-based governance concepts are prone to institutionalizing the saturation of the SES. Regarding our institutional and cognitive model of change, we could assume that they frame integrative and entrepreneurial synchronous regimes mainly. Existing datasets prevent testing this core assumption, which impedes analyzing the impact of social reforms on the ecological outcome of an SES. Dealing with Measurement Disparity and Evolution: Recommendations to Reinforce External and Internal Validity  
To overcome methodological heterogeneity and case-specificity that constrain external validity of studies, we recommend: (i) enlarging the number of observations; (ii) carrying out a replicable empirical strategy; and (iii) including a time dimension. First, increasing the number of observations and cases automatically increase the external validity as it reduces the case-dependency of results. In addition, it makes it easier to identify the strategy and delineate impacts of contextual variables(climate, economic activity, etc.) from effects of explanatory variables (learning processes, institutional setting, resource uses, etc.). Seven prominent databases that contain SES or commons related datasets exist. Recommendations have been formulated to favor their use in a replicable and consistent manner [11]. These datasets cover about 2000 cases, and coding strategies are all based on the SES or IAD framework, which limits inconsistency among studies. (Two important meta-database initiatives include: (1) SESMAD, 2014. Social-Ecological Systems Meta-Analysis Database: Background and Research Methods. Available from: [[http://sesmad.dartmouth.edu/](http://sesmad.dartmouth.edu/)]([http://sesmad.dartmouth.edu/](http://sesmad.dartmouth.edu/)); and (2) Resilience Alliance and Santa Fe Institute. 2004. Thresholds and alternate states in ecological and social-ecological systems. Resilience Alliance. (Online.) [[http://www.resilliance.org/index.php/thresholds_database](http://www.resilliance.org/index.php/thresholds_database)]([http://www.resilliance.org/index.php/thresholds_database](http://www.resilliance.org/index.php/thresholds_database))). The literature on water security should gain in developing this kind of common research practice and data sharing. Second, replicable research design is a necessary condition for expending datasets over time, by adding new observations or variables and by facilitating merging dataset. The choice of raw data and coding strategy are critical. We recommend using data that are reliable, free and \"protected\" to ensure their accessibility over space and time. Coding strategy contributes to reach this goal. It should be clear, not case-dependent and easy to replicate over many observations. In this regard, automated-coding looks necessary.