Clusters of landscape, cultural ecosystem services and demographics associated with Instagram images in Chen et al 2020

Clusters of landscape, cultural ecosystem services and demographics associated with Instagram images in Chen et al 2020

As decision-makers tackle the challenge of adapting Bay of Fundy dykelands to climate change, they need to understand who uses and values dykelands and salt marshes, and for what. This new paper in Ocean and Coastal ManagementComparing cultural ecosystem service delivery in dykelands and marshes using Instagram: A case of the Cornwallis (Jijuktu’kwejk) River, Nova Scotia, Canada, used four months of geocoded Instagram data to understand the cultural ecosystem service (CES) tradeoffs that might result from removing/realigning dykes and restoring salt marshes where dykelands can’t be sustained.  Dykelands provide a much wider set of CES for a wider demographic than do marshes for this set of social media users. However, a big surprise is that while salt marshes were present in many photos they were not named as such; users spoke only about the dykes and dykelands behind those marshes. As such, the marsh CES in the dataset came from visitors to an impounded freshwater wetland trail which is a local attraction walkable from the downtown centre of Kentville. Many of the messages triangulate well with the 2016 online Q survey I ran with Nova Scotians about the same topic and the paper provides another nice case study as to the utility of social media data for social impact assessment.  One of the really great things about this paper is that it is a real ‘lab’ output. The work was initiated as a follow-up to that 2016 study and to inform the new ResNet work when I knew Camille was going to be joining as an intern from AgroCampus Ouest. PhD student Yan collected a few months of Instagram posts for Camille to analyze with her help, postdoc Tuihedur helped with statistics, and then Yan picked it up again to write up after Camille went back to France. I’m proud of this paper and this collaborative team.