Mapping social values of ecosystem services: What is behind the map?

A growing interest in mapping the social value of ecosystem services (ES) is not yet methodologically aligned with what is actually being mapped. We critically examine aspects of the social value mapping process that might influence map outcomes and limit their practical use in decision making. We rely on an empirical case of participatory mapping, for a single ES (recreation opportunities), which involves diverse stakeholders such as planners, researchers, and community representatives. Value elicitation relied on an individual open-ended interview and a mapping exercise. Interpretation of the narratives and GIS calculations of proximity, centrality, and dispersion helped in exploring the factors driving participants’ answers. Narratives reveal diverse value types. Whereas planners highlighted utilitarian and aesthetic values, the answers from researchers revealed naturalistic values as well. In turn community representatives acknowledged symbolic values. When remitted to the map, these values were constrained to statements toward a much narrower set of features of the physical (e.g., volcanoes) and built landscape (e.g., roads). The results suggest that mapping, as an instrumental approach toward social valuation, may capture only a subset of relevant assigned values. This outcome is the interplay between participants’ characteristics, including their acquaintance with the territory and their ability with maps, and the mapping procedure itself, including the proxies used to represent the ES and the value typology chosen, the elicitation question, the cartographic features displayed on the base map, and the spatial scale.

Exploring social representations of adapting to climate change using topic modeling and Bayesian networks

When something unfamiliar emerges or when something familiar does something unexpected people need to make sense of what is emerging or going on in order to act. Social representations theory suggests how individuals and society make sense of the unfamiliar and hence how the resultant social representations (SRs) cognitively, emotionally, and actively orient people and enable communication. SRs are social constructions that emerge through individual and collective engagement with media and with everyday conversations among people. Recent developments in text analysis techniques, and in particular topic modeling, provide a potentially powerful analytical method to examine the structure and content of SRs using large samples of narrative or text. In this paper I describe the methods and results of applying topic modeling to 660 micronarratives collected from Australian academics / researchers, government employees, and members of the public in 2010-2011. The narrative fragments focused on adaptation to climate change (CC) and hence provide an example of Australian society making sense of an emerging and conflict ridden phenomena. The results of the topic modeling reflect elements of SRs of adaptation to CC that are consistent with findings in the literature as well as being reasonably robust predictors of classes of action in response to CC. Bayesian Network (BN) modeling was used to identify relationships among the topics (SR elements) and in particular to identify relationships among topics, sentiment, and action. Finally the resulting model and topic modeling results are used to highlight differences in the salience of SR elements among social groups. The approach of linking topic modeling and BN modeling offers a new and encouraging approach to analysis for ongoing research on SRs.