We compiled data from over 30 lakes across the globe to address how storms influence thermal structure
and phytoplankton community dynamics mediated by lake conditions and functional traits. In addition to
(generally) fortnightly phytoplankton samples (mean ± SD temporal coverage across all lakes = 20 ± 13 years),
the dataset includes limnological variables from standard long-term monitoring programs (24 ± 15 years
coverage), daily weather observations (16 ± 10 years coverage) and, when available, high-frequency lake
water temperature and water chemistry profiles (12 ± 7 years coverage). All data have been standardized to
similar formats and include complete metadata. We used the dataset to develop an R-package
(“algaeClassify”), which assigns phytoplankton genus/species information to multiple functional trait groups,
and here we provide a summary of ongoing research using the dataset to investigate: 1) the influence of storm
events on seasonal phytoplankton succession, 2) the impact of storms on lake thermal structure, and 3)
whether lake phytoplankton communities are shaped by long-term patterns in disturbance frequency and
intensity. We give an overview on how to access these data, and we further highlight the opportunities the
dataset provides for asking both basic and applied questions in limnology, ecology, climate change, and lake
management
