The waters rising, but do we notice?…. Research shows that we kind of do.
Social science hey, who needs it? This was my stance on the field up until 2 years ago when I began this project. The majority of my experience prior to this was really management focused, and my mentors at the time were all ecologists. 21-year-old Carla’s take home message with regard to social science was that the “fluffy nature” of social science questions and the resulting conclusions were seen not as a hard science, therefore weren’t useful or as valuable (wow, I sounded like a real jerk… also, I would argue that ecology probably isn’t a hard science either but that’s another story). Anyway, this mentality means that some ecologist don’t account for the social aspect of systems, which can end up jeopardizing the management or conservation outcome’s success and sustainability.
This project was something really different for me. People – water – social science!?… I am sure I was allergic to one (or more) of these things. However, a group of really great scientists, lead by Dr. Morena Mills, was conducting this project, so I applied and (somehow) got the job (I am sure it was through a coin toss).
The guts of this project were exploring whether peoples’ perceived risk of being flooded in their homes (now, in 20 years and in 100 years) is correlated with their actual (objective) risk of being flooded calculated using climate models. I was working with the questionnaire data, which opened up my world to the wonders of non-parametric data. As an ecologist of sorts, all my work up until this point was working with ‘real’ numbers. I saw one bird, which equaled a 1 in my data set, two birds = 2, and these numbers had an ordered value – higher numbers mean more birds (or things in general). Questionnaire data is a whole different breed. The Likert Scale approach is a style of surveying which allows respondents to rank how much they agree or disagree with a statement, most commonly on a 7 or 5-point scale. These numbers are ordered, but the order doesn’t mean the same as the order of parametric numbers. We collected information on worldview, past experience, general demographic and risk perception to explore the interaction (if any) between these factors and risk perception and objective risk.
We found that perceived risk only partially reflected objective risk. Other factors that influenced risk perception of respondents were the previous experience of flooding events, belief in climate change, risk aversion, age, and gender. Factors driving risk perception varied with the type of flooding event (permanently flooded or temporarily flooded) and the frequency of flooding event (now, in 20 years and in 100 years). Respondents with previous experience with extreme weather events and belief in climate change influenced how they perceived their risk in the future. We also looked at how respondents adapted to flooding events. Only 58% of the respondents that experienced extreme weather events chose to adopt some mitigation intervention. We found that personal as well as environmental factors influence the likelihood of this adaptation.
This project was the beginning of my ‘social science’ quest (whatever that means) and I came out of the project with a PhD supervisor, some new mentors and a new perspective to which I can explore questions.
The paper can be found here and I will upload a pdf once I check if its ok to do so. Lastly, thank you to all of the lovely authors and co-authors that made this project possible:
Morena Mills, Konar Mutafoglu, Vanessa M. Adams, Justine Bell, Javier X. Leon
Climatic Change DOI 10.1007/s10584-016-1644-y
Photo credit to my sister Brooke, who is a fantastic photographer x traveler.