Project Funding: 2013 - 2015

NRA: 2012 NASA: Ocean Biology and Biogeochemistry   

Funded by NASA

Abstract:
The size structure of algal communities determines ecosystem structure and function, and pathways of biogeochemical cycling. Size structure is related to phytoplankton functional types (PFTs), groups of phytoplankton with similar biogeochemical roles. Understanding the spatio-temporal dynamics of the PFTs in the World Ocean on various time scales is crucial for building realistic dynamic green ocean models capable of predicting the future role of ocean biota in climate. Spatio-temporal distributions of PFTs are expected to change with climate, with potentially significant impacts on ocean carbon cycling. Global  retrievals of chlorophyll from ocean color satellite data reveal expansions of oligotrophic gyres [Polovina et al., 2008], which may favor small phytoplankton and influence the biological pump [e.g., Finkel et al., 2010]. Yet, satellite observations of size structure do not show as clear a trend as those of chlorophyll [Kostadinov et al., 2010], emphasizing the need for further detailed study of the spatio-temporal trends in an improved and extended satellite PFTs data set. Moreover, our preliminary analysis suggests that the IPCC AR5 climate models show widely different responses of large- and small-cell phytoplankton biomass both at present and for the rest of the 21st century. Here, we propose to address these issues through the following activities: 1. Extending, evaluating and improving satellite PFT estimates Recent advances in ocean color remote sensing allow phytoplankton size structure retrieval via several different algorithms [e.g. Alvain et al., 2008; Kostadinov et al., 2010; Mouw and Yoder, 2010; Uitz et al., 2006; Bricaud et al., 2012]. The Co-I, Dr. Kostadinov, is the leading author of the only published backscattering-based PFT algorithm [Kostadinov et al., 2009, 2010]. We will participate in an internationally coordinated satellite PFT Intercomparison Project, the results of which are expected to provide new insights into PFT dynamics and guide algorithm improvements. We also propose to improve and temporally extend the existing satellite PFT data set [Kostadinov et al., 2009; 2010] and use it in spatio- temporal trend and bloom dynamics analyses. Importantly, we will improve uncertainty estimates by using Monte Carlo simulations to incorporate additional sources of uncertainty in the PFT algorithm products. Improvements to phytoplankton carbon retrievals from space will be attempted using particle volume retrievals and allometric relationships [Kostadinov, 2009] and introducing dynamic relative scaling to the algorithm of Behrenfeld et al. [2005]. The PFTs will be recast in terms of percent carbon biomass. 2. Analysis of bottom-up controls on changes in algal community size structure The new satellite PFT dataset in combination with output from a hindcast ocean simulation will allow us to evaluate ecological biome separation methods, as well as the seasonality and succession of PFTs across the satellite era. Informed by this analysis and resulting statistical tools, we will compare 21st century trends and variability in biome extent, productivity and community composition across the IPCC AR5 models; as well as analyze the underlying physical and biogeochemical drivers. Our recent theoretical work [Marinov et al., 2010] suggests the existence of a critical nutrient isoline that separates ocean biomes where large-cell algae vary more than smallcell ones from biomes where the opposite occurs. We plan further development of this theory and a novel suite of coupled model runs in order to separate and predict the responses of PFT biomass, productivity and ecosystem composition to changes in nutrients, light and temperature. Informed by this analysis, we will next evaluate and compare responses of small/large phytoplankton to 21st century changes in nutrients, light and temperature across the IPCC AR5 models, and explore consequences for community composition on interannual to interdecadal timescales.

Publications:

Cabre, A., Shields, D., Marinov, I., Kostadinov, T. S. 2016. Phenology of Size-Partitioned Phytoplankton Carbon-Biomass from Ocean Color Remote Sensing and CMIP5 Models. Frontiers in Marine Science. 3. DOI: 10.3389/fmars.2016.00039

Kostadinov, T. S., Cabre, A., Vedantham, H., Marinov, I., Bracher, A., Brewin, R. J., Bricaud, A., Hirata, T., Hirawake, T., Hardman-Mountford, N. J., Mouw, C., Roy, S., Uitz, J. 2017. Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models. Remote Sensing of Environment. 190, 162-177. DOI: 10.1016/j.rse.2016.11.014

Leung, S., Cabre, A., Marinov, I. 2015. A latitudinally banded phytoplankton response to 21st century climate change in the Southern Ocean across the CMIP5 model suite. Biogeosciences. 12(19), 5715-5734. DOI: 10.5194/bg-12-5715-2015

Sharma, P., Marinov, I., Cabre, A., Kostadinov, T., Singh, A. 2019. Increasing Biomass in the Warm Oceans: Unexpected New Insights From SeaWiFS. Geophysical Research Letters. 46(7), 3900-3910. DOI: 10.1029/2018GL079684

Sharma, P., Singh, A., Marinov, I., Kostadinov, T. 2019. Contrasting ENSO Types With Satellite-Derived Ocean Phytoplankton Biomass in the Tropical Pacific. Geophysical Research Letters. 46(11), 5987-5996. DOI: 10.1029/2018GL080689

More details may be found in the following project profile(s):

• NASA Ocean Biology & Biogeochemistry (OBB) Project Profile