Award: OCE-0928819

Intellectual merit: The goal of the project was to compile the information on functional traits (characteristics that affect species growth and survival) of phytoplankton, microscopic algae in aquatic ecosystems, and use them to explain and predict how phytoplankton communities are organized at present and in the future. Understanding what drives the composition and dynamics of phytoplankton communities is important because phytoplankton composition affects food webs and global biogeochemical cycles, including the carbon cycle. We found that phytoplankton species and groups differ in the values of their important traits and these differences determine different ecological strategies that allow different species to dominate under contrasting conditions. Many of these traits can be predicted based on fundamental scaling laws, which is helpful for characterizing species with unmeasured traits and for parameterizing mathematical models. We show that traits measured in the lab can be good predictors of species dynamics in natural conditions. This confirms the value of laboratory studies and combining them with ecosystem observations. Our compilation of temperature traits of phytoplankton demonstrated that local environmental temperature regimes select species best adapted to those temperatures. We also predict that future increases in temperature may reduce phytoplankton species diversity in the tropics, because tropical species, somewhat counter-intuitively, are especially vulnerable to rising temperatures. We also show that species traits change depending on environmental conditions, for example, traits that determine phytoplankton response to light depend on temperature. In an experimental study, we also show that phytoplankton traits evolve in response to stressful conditions. A marine diatom subjected to high temperatures evolved higher temperature tolerances after 300 hundred generations (1 year). This suggests that phytoplankton can adapt to changing conditions but we need to learn more about the rate of adaptation, whether it would be fast enough. Our modeling study within this project suggests that ecological communities respond to changing climate through both ecological and evolutionary processes and that the relative importance of these processes depends on trait diversity and species dispersal, among other factors. Our study also suggests that changes in ecological communities, such as species loss, can persist even after the stressor is removed. In summary, the project compiled and synthesized comprehensive data on phytoplankton traits that are made freely available and should be useful for aquatic ecologists, oceanographers, climate scientists and modelers. The results were published in 20+ peer-reviewed publications, including several high profile journals such as Science, Ecology Letters and Nature Climate Change. The results demonstrate that the composition of phytoplankton communities can be explained and predicted based on the characteristics of species but these characteristics do change on short-term and longer time scales. The project increased our mechanistic understanding of how phytoplankton communities are organized and may reorganize in the future. Broader Impacts: The results of the project are disseminated widely through publications, presentations and freely available data. Data are also deposited to the open Biological and Chemical Oceanography Data Management Office (http://www.bco-dmo.org/project/543188). Three graduate students, three undergraduate students and a postdoc were trained on this project. The results of the project were also incorporated into a course the PIs teach and numerous talks to lay audiences were delivered on the subject of the project (global change, aquatic ecology and oceanography). Last Modified: 01/28/2016 Submitted by: Elena G Litchman