{"id":4426,"date":"2024-03-07T01:34:04","date_gmt":"2024-03-07T01:34:04","guid":{"rendered":"https:\/\/blogs.lincoln.ac.nz\/gis\/?p=4426"},"modified":"2024-03-07T01:34:05","modified_gmt":"2024-03-07T01:34:05","slug":"global-phosphorus-blooms","status":"publish","type":"post","link":"https:\/\/blogs.lincoln.ac.nz\/gis\/global-phosphorus-blooms\/","title":{"rendered":"Global Phosphorus Blooms"},"content":{"rendered":"\n

Three different ways of mapping some dissolved reactive phosphorus data<\/em> are covered.<\/em><\/p>\n\n\n\n

Some of our recent work in pulling together a set of global datasets<\/a> is beginning to bear fruit. Over the next few posts, I’ll go into excruciating detail on how the datasets were pulled together and the analysis results mapped. <\/p>\n\n\n\n

Along with nitrogen, phosphorus is a key growth nutrient for plants. But like too much of anything being a bad thing, excessive levels of phosphorus in water can promote the growth of algae and plants leading to less oxygen available for fish and a decrease in water quality. Dissolved Reactive Phosphorus<\/a> (DRP), the form of phosphate most available for plant growth, is monitored as a water quality indicator and can be found in both surface and groundwater. With some of the good folk at AgResearch, we’ve been pulling together these global scale datasets to model its spatial distribution in groundwater.<\/p>\n\n\n\n

We’re working with different sets of modelled data that I’ll have to go into another time, but in this post we’ll look at some different strategies for mapping them. To get things started, I’m working with a polygon layer that has two values of DRP from two different modelling efforts. <\/p>\n\n\n\n