During the Spring 2014, a group of Stanford students, led by graduate students, Alexis Mychajliw and Melissa Kemp, and biology professor, Dr. Elizabeth Hadly collected news about the human and scientific dimensions of climate change for California for a biology classes entitled Geographic Impacts of Climate Change: Mapping the news . The results was an online map, created with Esri’s Story Map feature (embedded below, you can visit the full version here).
The class collected news and journal articles and classified them by impact: climate disruption, population change, biodiversity loss, pollutants, and invasive disease. For the climate disruption tab, articles about how changes in California’s climate, particularly the ongoing drought, are categorized by who it affects: farmers, immigrants, businesses, governments, etc. The news and journal articles were geocoded based on that news article or journal article’s subject location.
There is a whole lot of information presented with each tab which can get confusing. Each category has a polygon layer related to the category although there isn’t much explanation as to why each specific layer was chosen. For example, the climate disruption layer has average precipitation from 1990-2009 which doesn’t paint the picture of the current severe drought conditions much of the state is under. It might have made more sense to display a layer showing drought conditions or perhaps one that shows the differential between current year to date precipitation against the two decade precipitation averages in order to show the stress the state is under. The GRACE groundwater maps would also be an appropriate layer. Likewise, the biodiversity loss has a layer for forestation loss which doesn’t paint the picture for habitat loss in large areas of the state where there are few forest areas (e.g. Mojave Desert which is battling the disruptive intrusion of solar farms).
As a geographer, when I see map overlays in conjunction with point data, my mind naturally wants to see if there is a visibly discernible correlation between them. I found the only tab that really provides an underlying GIS data layer that correlates with the point data is the pollutants tab which has a polygon layer showing particulate matter measurements. With this map tab, the user can see a pattern of where point locations of news is more clustered in area where there is a higher particulate measurement.
The map story presentation definitely involved a lot of work by the students and advisors in Stanford’s Biology 128: Geographic Impacts of Climate Change: Mapping the news class. It would be helpful if the summaries provided with each tab linked the underlying thought process for why which articles/news and underlying GIS data were chosen. I am also curious as to why the class decided to categorize the impacts by stakeholder instead of type of impact.