I was recently catching up with a friend that lives out in Jamaica and she mentioned that the neighborhood was named after beavers since New York was once home to a diverse ecosystem of wildlife before the settlers landed. She mentioned that Queens was once all swamp and marshes and that the word “Jamaica” derived from the word “Jameco” which is the word for beaver among the Lenape people. Hearing this brought back memories of the early settlers that I would learn about in my elementary class when I was about eight and remembered that New York was once home to wild animals that did not include rats, pigeons, squirrels, and the occasional raccoons. With this in mind, I wanted to visualize the decline of New York City’s natural wildlife. The goal I set myself is to show that pollution is one of the driving forces for the removal of these wild animals and that we should be placing the necessary resources to conserve sanctuary spaces and parks.
Not too long ago more and more residents have reported coyotes roaming around central park and even around the Bronx. These sightings were becoming so frequent that New York City’s official Parks website posted a “Living With Coyotes in New York City” blog post on their webpage. As I took off to find the appropriate data, I realized that I was dealing with too ambitious set of data points that included too many variables with missing dates which play an important role in my visualization. I then went on the search again for what else I can possibly visualize. The colder nights and the fact that the days are getting shorter made me miss summer and the lakes and beaches. This helped me settle on reports of harmful algal blooms that affect most large bodies of water, especially lakes where the water can remain stagnant for weeks on end. The dataset I downloaded contained the reports on the condition of the body of water. “S” being a suspicious bloom, “HT” meaning it contains high toxins, and “C” reporting a confirmed bloom. Adding the definitions to the abbreviations in the visualization proved to be difficult without first changing it on the source. I therefore went ahead and left it as is on the dashboard of Tableau and pressed forward.
I set off with the goal to visualize which county in New York had the greatest amount of reports of harmful algal blooms, my guess being counties in upstate since that is where all the lakes and rivers are. But as I placed my necessary pills into the correct columns and row sections, something very surprising came up. It is actually Suffolk county that came in with the most reports and Westchester coming in second. After seeing the bar graphs, it did make sense that Long Island would have the most reports seeing as they are surrounded by water all around where some leaks my seep through to the nearby lakes and reservoirs. What I wish I could do more research on however, is finding a way to standardize the data by population since I am fairly certain that some parts of Upstate are more densely populated than others. Westchester is also easily accessible by New York City residents so that may also play a role on the county placing second.
Hopefully this entices people to be more careful with what they leave behind by the body of water since most residents look forward to spending their time in lakes during the hot summer days. These algal blooms, if exposed to high enough concentrations, could be detrimental to someone’s health, especially those that enjoy eating shellfish where the toxins can easily transfer between the animal and person. And with the right resources we can have the right department take the necessary steps to make sure that these algal blooms are within a reasonable count where the rest of the ecosystem faces little to no harm and pose no threat to people.