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Influence of phytoplankton size structure on ocean carbon cycling and on ocean colour Bob Brewin 1,2,3, Shubha Sathyendranath 1,3, with contributions from.

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Presentation on theme: "Influence of phytoplankton size structure on ocean carbon cycling and on ocean colour Bob Brewin 1,2,3, Shubha Sathyendranath 1,3, with contributions from."— Presentation transcript:

1 Influence of phytoplankton size structure on ocean carbon cycling and on ocean colour Bob Brewin 1,2,3, Shubha Sathyendranath 1,3, with contributions from Giorgio Dall’Olmo 1,3, Icarus Allen 1,3, Lee De Mora 1, Momme Butenschon 1 1 Plymouth Marine Laboratory (PML), Prospect Place, The Hoe, Plymouth PL1 3DH, UK 2 ESA Changing Earth Science Network post-doctoral fellowship of the STSE program 3 National Centre for Earth Observation, PML, Plymouth PL1 3DH, UK

2 Earth system modelling is used for predicting and determining how the ocean and land sinks may respond in the future. These models are constrained / improved by comparison and verification with observations. Importance of Phytoplankton The ocean contributes to ~1/4 of anthropogenic CO 2 (Le Quéré et al. 2009) ~1/2 of net global primary production (Longhurst et al. 1995) Evidence of declining ocean CO 2 sink (Canadell et al. 2007) Future changes are highly uncertain!

3 Source ESA: Phytoplankton biomass and climate see also papers by Behrenfeld et al. (2006) Nature and Martinez et al. (2009) Science

4 A number of biogeochemical models use a size class partitioning Cell size Nutrient uptake Light absorption Sinking rate Exported production Phytoplankton physiology Metabolic rates Marine food-web An integrative approach to describing phytoplankton function and structure in relation to marine bio-geochemical cycling (Marañón 2009). Influence of size structure on carbon cycle

5 Phytoplankton size structure Brewin et al. (2010) Ecol. Model. Brewin et al. (2011) Appl. Optics Brewin et al. (2012a) Opt. Express Brewin et al. (2012b) Deep Sea Res. II Brotas et al. (2013) Rem. Sens. Environ. Brewin et al. (2014a) Deep Sea Res. I Brewin et al. (2014b) J Geophys. Res. Lin et al. (2014) Mar. Pollut. Bull.

6 Influence of size structure on ocean colour PICO <2 μm

7 Influence of size structure on ocean colour NANO 2-20 μm

8 Influence of size structure on ocean colour MICRO >20 μm

9 Influence of size structure on ocean colour

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13 Satellite estimates of size structure Brewin et al. (2010) Ecol. Model.

14 .html Phytoplankton size and climate Brewin et al. (2012) Deep-Sea Res. II

15 .html Phytoplankton size and climate Brewin et al. (2012) Deep-Sea Res. II

16 .html Model comparison EURO-BASIN Programme Holt et al. (2014) Progress in Oceanography MEDUSA PISCES ERSEM

17 .html Model comparison EURO-BASIN Programme Holt et al. (2014) Progress in Oceanography

18 .html Model data assimilation Xiao and Friedrichs (2014) J Geophys. Res Before assimilation After assimilation When implementing assimilative models with more than one phytoplankton size class, the assimilation of size- fractionated chlorophyll provides an advantage over the assimilation of total chlorophyll.

19 -Phytoplankton size structure is an importance component of the ocean carbon cycle and other biogeochemical cycles. -Phytoplankton size structure has a direct influence on variations in reflected light within the visible electromagnetic spectrum. -These variations are implicitly build into standard empirical algorithms designed to estimate the total chlorophyll concentration as a function of reflected light. -These variations can be revealed through simple empirical relationships between total chlorophyll and size structure. -Satellite estimates of size structure can improve our understanding of the relationship between physical variables and size structure, and are useful for validation of, and assimilation into, multi-phytoplankton biogeochemical models. -This will ultimately improve our predictions and understanding of how the ocean ecosystem is responding to changes in climate. Summary

20 We thank contributors, crew and staff involved with the collection of all in situ data, particularly for AMT and NOMAD. We thank all data contributors without whom this work would not be possible. In particular, Ray Barlow, Vanda Brotas and Jeremy Werdell. We thank the ESA Changing Earth Science Network of the STSE program, NCEO and ESA OC-CCI project for financial support. Acknowledgements


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