Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales

Abstract

Predictions of chlorophyll a (Chl-a) in lentic waterbodies (lakes and reservoirs) are valuable to researchers and resource managers alike but have been rarely conducted at the global scale. With the development of remote sensing technologies, it is now feasible to gather large amounts of data across the world, including understudied and remote regions. To determine which factors were most important in explaining the variation of Chl-ain waterbodies at global and regional scales, we first developed a database of 227 globally distributed waterbodies and watersheds with corresponding Chl-a, nutrient, hydrogeomorphic, and climate data. Then we used a generalized additive modeling approach and selected models that most parsimoniously related Chl-ato predictor variables for all 227 waterbodies and for a subset of 51 within the Laurentian Great Lakes region. Our best global model contained 3 hydrogeomorphic variables (waterbody area, shoreline development index, and watershed to waterbody area ratio) and a climate variable (mean temperature in the warmest quarter) that explained about 30% of variation in Chl-a. Our regional model contained one hydrogeomorphic variable (watershed area), the same climate variable, and a nutrient variable (percent of watershed area cover by waterbodies) that explained 58% of variation in Chl-a. Our results indicate that a regional approach to watershed modeling may be more informative to predicting Chl-athan a global approach and that nearly a third of global variation in Chl-amay be explained using hydrogeomorphic and climate variables.