heidi m. sosik hui feng

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

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 analysissingle cells phytoplankton community bulk water optical properties sea surface optical properties (air and water) MODIS optical properties

Martha’s Vineyard Coastal Observatory

Tower mountedAERONET-OC

MODIS productsSubmersible Imaging

Flow Cytometry

Approach

Phytoplankton ObservationsSingle cells to communitiesBiomass, size- and taxon-resolved

Phytoplankton AlgorithmsAbsorption spectral shape size structure

Diagnostic pigments size structure

Diagnostic pigments taxonomic structure400 500 600 7000

0.5

1

1.5

2

2.5

3

3.5

03-Jul-2007 20:00:00Fraction micro = 0.40

Rel

ativ

e ph

ytop

lank

ton

abso

rptio

n

Wavelength (nm)

pico

micro

MeasuredCiotti fit

400 500 600 7000

0.5

1

1.5

2

2.5

3

3.5

09-Dec-2007 21:15:00Fraction micro = 0.78

Wavelength (nm)

pico

micro

MeasuredCiotti fit

m m m m

m

Variability in community structure

Jan Apr Jul Oct Jan0

10

20

30

40

Dia

tom

s (m

gC m

-3)Diatoms

Cyano-bacteria


2

4

6

8

10

12

Cya

noba

cter

ia (m

gC m

-3)

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20140

20

40

60C

arbo

n ( m

g m

L-1)

SynechococcusGuinardia delicatula

.

m m m m

m

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/9)x0.913

r = 0.630


1

2

3

4

5

6

7

Dia

tom

s

CHEMTAX Chla, HPLCFCM carbon / 11

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

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/9)x0.913

r = 0.630


1

2

3

4

5

6

7

Dia

tom

s



Diatoms

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20140

2

4

6

8

Dia

tom

s


Dia

tom

s (m

g m

3 )

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/161)x0.694

r = 0.375


0.02

0.04

0.06

0.08

Cya

noba

cter

ia


10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/9)x0.913

r = 0.630


1

2

3

4

5

6

7

Dia

tom

s



Diatoms

10 mm

Dinoflagellates Cyanobacteria

~1 mm cells

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/145)x1.794

r = 0.321


0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Din

ofla

gella

tes


10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/9)x0.913

r = 0.630


1

2

3

4

5

6

7

Dia

tom

s



Diatoms

10 mm


~1 mm cells

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/145)x1.794

r = 0.321


0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Din

ofla

gella

tes


Chl

or C

arbo

n (m

g m

3 )

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/161)x0.694

r = 0.375


0.02

0.04

0.06

0.08

0.1

Cya

noba

cter

ia


-2.5 -2 -1.5 -1 -0.5 0-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

log10(Rrs488/Rrs547)-log10(Temp)

log1

0(Ze

axan

thin

) (m

g m

-3)

Y = -9.885+-14.84X+-9.23X2+-1.998X3

In situ dataPan et al.

-0.4 -0.2 0 0.2 0.4 0.6 0.8 1-1.5

-1

-0.5

0

0.5

1

1.5

2

log10(Rrs488/Rrs547)

log1

0(C

hl a

) (m

g m

-3)

Y = 0.03664+-3.451X+2.276X2+-1.096X3


-0.4 -0.2 0 0.2 0.4 0.6 0.8 1-2.5

-2

-1.5

-1

-0.5

0

0.5

1


log1

0(Pe

ridin

in) (

mg

m -3

)

Y = -1.401+-2.817X+2.634X2+-2.396X3


-0.4 -0.2 0 0.2 0.4 0.6 0.8 1-1.5

-1

-0.5

0

0.5

1

1.5

2


log1

0(Fu

coxa

nthi

n) (m

g m

-3)

Y = -0.6208+-3.928X+1.339X2+0X3


Diagnostic pigment retrieval from RrsPan et al. 2010 band ratio algorithms AERONET-OC

SeaPRISM, Rrs(l)

Discrete samplesHPLC pigment analysis

Chl a Fucoxanthin

Peridinin Zeaxanthin

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/161)x0.694

r = 0.375


0.02

0.04

0.06

0.08

0.1

Cya

noba

cter

ia


10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/9)x0.913

r = 0.630


1

2

3

4

5

6

7

Dia

tom

s



Diatoms

10 mm


~1 mm cells

10-2

100

102

10-4

10-3

10-2

10-1

100

101

FCM carbon (mg m-3)

CH

EM

TAX

Chl

a (m

g m

-3) y = (1/145)x1.794

r = 0.321


0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Din

ofla

gella

tes


Chl

or C

arbo

n (m

g m

3 )


1

2

3

4

5

6

7

Dia

tom

s

CHEMTAX Chla, HPLCCHEMTAX Chla, SeaPRISM

Remote sensing retrieval of taxonomic groups

Diatoms Dinoflagellates Cyanobacteria


0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Din

ofla

gella

tes



0.02

0.04

0.06

0.08

0.1

Cya

noba

cter

ia


AERONET-OCSeaPRISM, Rrs(l)

Following:Pan et al. 2010 band ratio algorithmsPan et al. 2011 CHEMTAX application

Loss of seasonal resolution

Chl

or C

arbo

n (m

g m

3 )


0.2

0.4

0.6

0.8

1

Dia

tom

s




Frac

tion

of C

hl a


0.05

0.1

0.15

0.2

0.25

Din

ofla

gella

tes

(chl

frac

)



0.02

0.04

0.06

0.08

0.1

Cya

noba

cter

ia (c

hl fr

ac)


AERONET-OCSeaPRISM, Rrs(l)

Relative contribution to total Chl a

Loss of seasonal resolution

Following:Pan et al. 2010 band ratio algorithmsPan et al. 2011 CHEMTAX application


0.2

0.4

0.6

0.8

1

Dia

tom

s



0.2

0.4

0.6

0.8

1

Dia

tom

s (c

hl fr

ac)

CHEMTAX Chla, HPLCCHEMTAX Chla, MODIS



Frac

tion

of C

hl a

Frac

tion

of C

hl a


0.05

0.1

0.15

0.2

0.25

Din

ofla

gella

tes

(chl

frac

)



0.02

0.04

0.06

0.08

0.1

Cya

noba

cter

ia (c

hl fr

ac)



0.05

0.1

0.15

0.2

0.25

Din

ofla

gella

tes

(chl

frac

)



0.02

0.04

0.06

0.08

0.1

Cya

noba

cter

ia (c

hl fr

ac)


Ecosystem characterization

Decadal increase in pico-cyanobacteria at MVCO

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20140

20

40

60C

arbo

n ( m

g m

L-1)


.

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014-1.5

-1

-0.5

0

0.5

1

1.5

Syn

echo

cocc

us

log(

mL-1

), an

omal

y


Peacock et al. 20142003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

0

20

40

60C

arbo

n ( m

g m

L-1)


.

50 mm


Interannual fluctuations in diatoms related to parasite infection linked to temperature

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20140

20

40

60C

arbo

n ( m

g m

L-1)


.

0 2 4 6 8 100

1000

2000

3000

4000

5000

Inte

grat

ed G

. del

icat

ula

(cha

ins

ml -1

d)

Average infection rate (%)

Mar-10

Feb-13

Feb-07

Feb-09

Jul-09

Sep-09

Feb-11

Jan-12

Jun-11

Peacock et al. 2014

Looking forward on PFT characterization

Time series observationssingle cells phytoplankton community bulk water optical properties sea surface optical properties (air and water) MODIS optical properties

Martha’s Vineyard Coastal Observatory

Tower mountedAERONET-OC

MODIS productsSubmersible Imaging

Flow Cytometry

Local detail Trends and patterns of change

Regional to basin scales

Combinedin situ & satellite

observations

http://ifcb-data.whoi.edu/

Open data access

Standard formats

Processing pipelines

End-to-end provenance


-4 -2 0 2 4-4

-2

0

2

4

r2 = 0.42

Temperature anomaly (relative)

Taxo

n an

omal

y (re

lativ

e)

Syn

-4 -2 0 2 4

-5

0

5

January

r2 = 0.59

Ditylum

-4 -2 0 2 4

-5

0

5

r2 = 0.39

Corethron

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

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 cytometryFluorescence and light scattering

Flow cytometry with video imaging

Automated features for extended deployment (>6 months)

Enumeration, identification, and cell sizing

Thousands of individual cellsevery hour

Olson et al. 2003 Olson & Sosik 2007

Single Cells to Biomass

FlowCytobot

Picoplankton

Imaging FlowCytobot

Microplankton

Light scattering

Cel

l vol

ume

(mm

3 )

Sosik and Olson 2007Moberg & Sosik 2012

Olson et al. 2003Volume from laser scattering

Volume from image analysisnew “distance map” approach

Menden-Deuer and Lessard 2000

heidi m. sosik hui feng

Documents

phytoplankton cells

situ time series

phytoplankton biomass

unique time series

sake of time

multilevel time series

bulk water properties

phytoplankton functional