Date of Original Version
Aim: This study examined phytoplankton blooms on a global scale, with the intention of describing patterns of bloom timing and size, the effect of bloom timing on the size of blooms, and time series trends in bloom characteristics.
Methods: We used a change‐point statistics algorithm to detect phytoplankton blooms in time series (1998–2015) of chlorophyll concentration data over a global grid. At each study location, the bloom statistics for the dominant bloom, based on the search time period that resulted in the most blooms detected, were used to describe the spatial distribution of bloom characteristics over the globe. Time series of bloom characteristics were also subjected to trend analysis to describe regional and global changes in bloom timing and size.
Results: The characteristics of the dominant bloom were found to vary with latitude and in localized patterns associated with specific oceanographic features. Bloom timing had the most profound effect on bloom duration, with early blooms tending to last longer than later‐starting blooms. Time series of bloom timing and duration were trended, suggesting that blooms have been starting earlier and lasting longer, respectively, on a global scale. Blooms have also increased in size at high latitudes and decreased in equatorial areas based on multiple size metrics.
Main conclusions: Phytoplankton blooms have changed on both regional and global scales, which has ramifications for the function of food webs providing ecosystem services. A tendency for blooms to start earlier and last longer will have an impact on energy flow pathways in ecosystems, differentially favouring the productivity of different species groups. These changes may also affect the sequestration of carbon in ocean ecosystems. A shift to earlier bloom timing is consistent with the expected effect of warming ocean climate conditions observed in recent decades.
Friedland, KD, Mouw, CB, Asch, RG, et al. Phenology and time series trends of the dominant seasonal phytoplankton bloom across global scales. Global Ecol Biogeogr. 2018; 27: 551– 569. https://doi.org/10.1111/geb.12717 Available at: https://doi.org/10.1111/geb.12717