Every second breath you take is courtesy of the phytoplankton — the tiny single-celled photosynthesizers in the ocean. The oxygen the phytoplankton produce has allowed the proliferation of life on earth, while the carbon dioxide they fix into organic carbon helps to regulate the planet’s climate, and forms the base of nearly all ocean food webs. So it is clearly important to know how fast the phytoplankton are growing and photosynthesizing. Unfortunately, these are difficult measurements to make, and scientists only measure the phytoplankton growth at a few discrete points in the ocean on infrequent research cruises.
Models are a convenient tool for interpolating between those discrete measurements in time and space. If phytoplankton growth rates can be related to properties of their environment that are easy to measure from ships — or can be measured remotely from space — then the gaps between the measurements can be filled in, much the way weather maps give local forecasts from widely spaced meteorological data. The CCE scientists developed a model of phytoplankton growth that is based on a few easily measured properties: nutrient concentrations, temperature, and light in the ocean. What enabled the scientists to so accurately build their model was the large numbers of phytoplankton growth-rate measurements acquired during the CCE-LTER research cruises. Having so many data helped to reduce the error bars on the predicted growth rates, leading to accurate maps of the vertical and horizontal variations in growth rate in the California Current System.
The phytoplankton growth model breaks the phytoplankton community down into two groups: one group requires silicic acid to grow (the diatoms), while the other does not. The model accurately reproduces patterns seen in the measurements: diatoms are very important near the coast, but the other smaller phytoplankton dominate in offshore waters. The composition of the phytoplankton community directly influences fish production, because some fish such as sardines can eat diatoms, while others require larger prey.
One particularly exciting prospect of having such a well-tested model is that it can now be applied to historical measurements of nutrients, temperature, and light from the CalCOFI program. These measurements will allow scientists to create maps of phytoplankton growth rates dating back to 1949 along the west coast of North America. The relatively continuous data coverage will allow researchers to explore the ways in which climate change has affected phytoplankton growth, and thus the food for zooplankton and fish, the organic carbon sequestered into the ocean’s sediments, and the oxygen available for metabolism.
The CCE scientists who developed the phytoplankton growth model are now working on a model predicting the grazing rates of the zooplankton that eat the phytoplankton. The coupling of the two models will allow scientists to predict the ecosystem dynamics of the plankton in response to variable environmental forcing.