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Seasonal to Interannual Variability in Phytoplankton Biomass and Diversity on the New England Shelf Heidi M. Sosik Hui Feng In Situ Time Series for Validation.

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Presentation on theme: "Seasonal to Interannual Variability in Phytoplankton Biomass and Diversity on the New England Shelf Heidi M. Sosik Hui Feng In Situ Time Series for Validation."— Presentation transcript:

1 Seasonal to Interannual Variability in Phytoplankton Biomass and Diversity on the New England Shelf Heidi M. Sosik Hui Feng In Situ Time Series for Validation and Exploration of Remote Sensing Algorithms Woods Hole Oceanographic Institution University of New Hampshire

2 Project Overview Goal: Use unique time series to evaluate algorithms that extend MODIS ocean color data beyond chlorophyll to functional type or size-class- dependent phytoplankton retrievals Approach: End-to-end time series observations, with step-by-step algorithm evaluation and error analysis single cells  phytoplankton community  bulk water optical properties  sea surface optical properties (air and water)  MODIS optical properties Martha’s Vineyard Coastal Observatory Tower mounted AERONET-OC MODIS products Submersible Imaging Flow Cytometry

3 Approach Phytoplankton Observations Single cells to communities Biomass, size- and taxon-resolved Phytoplankton Algorithms Absorption spectral shape  size structure Diagnostic pigments  size structure Diagnostic pigments  taxonomic structure

4     Variability in community structure Diatoms Cyano- bacteria.    

5 Pigment-based retrieval of taxonomic groups Diatoms “CHEMTAX” In situ FCM Total Chl a = diatom Chl a + dinoflagellate Chl a + cyanobacteria Chl a + … with partitioning according to accessory pigment ratios Mackey et al. 1996

6 Pigment-based retrieval of taxonomic groups Diatoms Diatoms (mg m 3 )

7 Pigment-based retrieval of taxonomic groups Diatoms 10  m DinoflagellatesCyanobacteria ~1  m cells

8 Pigment-based retrieval of taxonomic groups Diatoms 10  m DinoflagellatesCyanobacteria ~1  m cells Chl or Carbon (mg m 3 )

9 Diagnostic pigment retrieval from Rrs Pan et al. 2010 band ratio algorithms AERONET-OC SeaPRISM, R rs ( ) Discrete samples HPLC pigment analysis Chl a Fucoxanthin Peridinin Zeaxanthin

10 Pigment-based retrieval of taxonomic groups Diatoms 10  m DinoflagellatesCyanobacteria ~1  m cells Chl or Carbon (mg m 3 )

11 Remote sensing retrieval of taxonomic groups DiatomsDinoflagellatesCyanobacteria AERONET-OC SeaPRISM, R rs ( ) Following: Pan et al. 2010 band ratio algorithms Pan et al. 2011 CHEMTAX application  Loss of seasonal resolution Chl or Carbon (mg m 3 )

12 Remote sensing retrieval of taxonomic groups DiatomsDinoflagellatesCyanobacteria Fraction of Chl a AERONET-OC SeaPRISM, R rs ( ) Relative contribution to total Chl a  Loss of seasonal resolution Following: Pan et al. 2010 band ratio algorithms Pan et al. 2011 CHEMTAX application

13 Remote sensing retrieval of taxonomic groups DiatomsDinoflagellatesCyanobacteria Fraction of Chl a

14 Ecosystem characterization Decadal increase in pico-cyanobacteria at MVCO.

15 Ecosystem characterization Peacock et al. 2014. 50  m

16 Ecosystem characterization Interannual fluctuations in diatoms  related to parasite infection  linked to temperature. Peacock et al. 2014

17 Looking forward on PFT characterization Time series observations single cells  phytoplankton community  bulk water optical properties  sea surface optical properties (air and water)  MODIS optical properties Martha’s Vineyard Coastal Observatory Tower mounted AERONET-OC MODIS products Submersible Imaging Flow Cytometry Local detail  Trends and patterns of change  Regional to basin scales Combined in situ & satellite observations

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19 http://ifcb-data.whoi.edu/ Open data access Standard formats Processing pipelines End-to-end provenance

20 Ecosystem characterization Taxa with positive response to warmer winters Taxa with negative response to warmer winters Interannual variability – taxon specific Seasonally adjusted Biomass anomalies vs Temperature anomalies Cyanobacterium Diatoms

21 FlowCytobot Imaging FlowCytobot Observing Phytoplankton at MVCO Martha’s Vineyard Coastal Observatory (MVCO) Cabled site with power and two-way communications MicroplanktonPicoplankton Laser-based flow cytometry Fluorescence and light scattering Flow cytometry with video imaging Automated features for extended deployment (>6 months) Enumeration, identification, and cell sizing Thousands of individual cells every hour Olson et al. 2003 Olson & Sosik 2007

22 Single Cells to Biomass FlowCytobot Picoplankton Imaging FlowCytobot Microplankton Light scattering Cell volume (  m 3 ) Sosik and Olson 2007 Moberg & Sosik 2012 Olson et al. 2003 Volume from laser scattering Volume from image analysis new “distance map” approach Menden-Deuer and Lessard 2000


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