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.

Hydrological and economic effects of oil palm cultivation in Indonesian peatlands

Oil palm has increasingly been established on peatlands throughout Indonesia. One of the concerns is that the drainage required for cultivating oil palm in peatlands leads to soil subsidence, potentially increasing future flood risks. This study analyzes the hydrological and economic effects of oil palm production in a peat landscape in Central Kalimantan. We examine two land use scenarios, one involving conversion of the complete landscape including a large peat area to oil palm plantations, and another involving mixed land use including oil palm plantations, jelutung (jungle rubber; (Dyera spp.) plantations, and natural forest. The hydrological effect was analyzed through flood risk modeling using a high-resolution digital elevation model. For the economic analysis, we analyzed four ecosystem services: oil palm production, jelutung production, carbon sequestration, and orangutan habitat. This study shows that after 100 years, in the oil palm scenario, about 67% of peat in the study area will be subject to regular flooding. The flood-prone area will be unsuitable for oil palm and other crops requiring drained soils. The oil palm scenario is the most profitable only in the short term and when the externalities of oil palm production, i.e., the costs of CO2 emissions, are not considered. In the examined scenarios, the social costs of carbon emissions exceed the private benefits from oil palm plantations in peat. Depending upon the local hydrology, income from jelutung, which can sustainably be grown in undrained conditions and does not lead to soil subsidence, outweighs that from oil palm after several decades. These findings illustrate the trade-offs faced at present in Indonesian peatland management and point to economic advantages of an approach that involves expansion of oil palm on mineral lands while conserving natural peat forests and using degraded peat for crops that do not require drainage.