【来访单位 Institution】：University of South Florida，美国
Macroalgae blooms have been reported in many places around the world. These blooms provide important ecological functions in the ocean, but can cause many problems when large quantities of macroalgae are washed ashore. Using satellite data, spectroscopy, and novel algorithms, we show long-term bloom patterns of the green macroalgae Ulva prolifera and brown macroalgae Sargassum spp. in several oceans. Both show clear seasonality and long-term trends, but the mechanisms driving such trends are yet to be determined. In the absence of process-driven models, statistics-based models may be used to predict bloom probability, thus providing an early-warning means to help make management decisions.