Multi-nutrient, multi-group model of present and future oceanic phytoplankton communities

Abstract

Abstract. Phytoplankton community composition profoundly affects patterns of nutrient cycling and the dynamics of marine food webs; therefore predicting present and future phytoplankton community structure is crucial to understand how ocean ecosystems respond to physical forcing and nutrient limitations. We develop a mechanistic model of phytoplankton communities that includes multiple taxonomic groups (diatoms, coccolithophores and prasinophytes), nutrients (nitrate, ammonium, phosphate, silicate and iron), light, and a generalist zooplankton grazer. Each taxonomic group was parameterized based on an extensive literature survey. We test the model at two contrasting sites in the modern ocean, the North Atlantic (North Atlantic Bloom Experiment, NABE) and subarctic North Pacific (ocean station Papa, OSP). The model successfully predicts general patterns of community composition and succession at both sites: In the North Atlantic, the model predicts a spring diatom bloom, followed by coccolithophore and prasinophyte blooms later in the season. In the North Pacific, the model reproduces the low chlorophyll community dominated by prasinophytes and coccolithophores, with low total biomass variability and high nutrient concentrations throughout the year. Sensitivity analysis revealed that the identity of the most sensitive parameters and the range of acceptable parameters differed between the two sites. We then use the model to predict community reorganization under different global change scenarios: a later onset and extended duration of stratification, with shallower mixed layer depths due to increased greenhouse gas concentrations; increase in deep water nitrogen; decrease in deep water phosphorus and increase or decrease in iron concentration. To estimate uncertainty in our predictions, we used a Monte Carlo sampling of the parameter space where future scenarios were run using parameter combinations that produced acceptable modern day outcomes and the robustCorrespondence to: E. Litchman (litchman@msu.edu) ness of the predictions was determined. Change in the onset and duration of stratification altered the timing and the magnitude of the spring diatom bloom in the North Atlantic and increased total phytoplankton and zooplankton biomass in the North Pacific. Changes in nutrient concentrations in some cases changed dominance patterns of major groups, as well as total chlorophyll and zooplankton biomass. Based on these scenarios, our model suggests that global environmental change will inevitably alter phytoplankton community structure and potentially impact global biogeochemical cycles.

Phytoplankton community structure in relation to vertical stratification along a north‐south gradient in the Northeast Atlantic Ocean

“…Chl a concentrations specific for diatoms and cryptophytes were greatest in these homogeneously mixed waters. The association of these taxa with higher macronutrient concentrations is consistent with their lower half-saturation constants for nutrient uptake and nutrient-limited growth (Litchman et al 2006;Irwin et al 2012).…”

“…The predictions of these models critically depend on questions as to which traits best differentiate phytoplankton functional groups and which environmental variables regulate primary production and community structure (Behrenfeld et al 2006;Irwin et al 2012). In this sense, predictions of how the ocean ecosystem will respond to climate change are still limited by a lack of information regarding which taxonomic groups are essential and what environmental controls determine the distribution and succession of these taxonomic groups (Falkowski et al 2000;Litchman et al 2006;Finkel et al 2010).…”

Influence of light and nutrients on the vertical distribution of marine phytoplankton groups in the deep chlorophyll maximum

“…The studies on which this work is based correspond to the most representative seasonal periods of the NW Mediterranean (Latasa et al 2010), a small but representative area for temperate oceans with deep winter mixing and a typical spring bloom (D'Ortenzio and Ribera d'Alcalà 2009), and to the summer conditions in the NE Atlantic (Cabello 2015), where a typical temperate DCM corresponding to a deep biomass maximum occurs. Models incorporating the traits of phytoplankton groups are usually based on laboratory studies of individual species (Gregg et al 2003, Litchman et al 2006, Schwaderer et al 2011, Edwards et al 2015). Here we have used a procedure different from what is habitually assumed as a traitbased approach.…”

“…Models have taken up the challenge of including plankton and specifically phytoplankton functional groups to resolve the functioning of those cycles (Le Quéré et al 2005, Litchman et al 2006, Follows et al 2007). In some cases, the biogeochemical role of phytoplankton groups is related to their phylogeny, indicating some sort of evolutionary trait (Quigg et al 2003, Falkowski and Oliver 2007, Sal et al 2015.…”

Defining the ecological and physiological traits of phytoplankton across marine ecosystems

“…huxleyi, which is thought to be the most r-selected of the coccolithophores, that thrives and blooms (Litchman et al, 2006). E. huxleyi is known to be well-adapted to such low-nutrient environments, having the ability to alter its metabolism to scavenge nutrients from organic compounds (Palenik and Henson, 1997;Dyhrman and Palenik, 2003;Bruhn et al, 2010;Rouco et al, 2013).…”