Motivation for trait-based physiology  

•  Deciduous and evergreen plants invest nutrients differently in their leaves.

•  Huge amount of new data. The new parameters are based on 6169 species-specific observations of leaf N, 5920 of leaf thickness,1757 of Vcmax

low nutrient concentrationthick leaves

high nutrient concentration

thin leavesTRY  database:  Ka-ge  et  al.  2011    

Application: 2010 Amazon drought

2.5 million km2 affected 1.6 PgC lost 1-in-100 year event

3.2 million km2 affected 2.2 PgC lost 1-in-100+ year event

Lewis et al. 2011!

Soil moisture stress & roots  •  Use plant available water (in kg m-2)

instead of volumetric water content for calculating fsmc.

•  Root depths from Zeng 2001

•  Assume efficient tap roots can access lots of soil moisture despite low density (as long as water content is above the wilt pt):

•  Remove root-weighting of fsmc,

•  Remove the fsmc-weighting of water extraction

IBIS  JULES  SiB3  

New global observations of the terrestrial carbon cyclefrom GOSAT: Patterns of plant fluorescence with grossprimary productivity

Christian Frankenberg,1 Joshua B. Fisher,1 John Worden,1 Grayson Badgley,1

Sassan S. Saatchi,1 Jung‐Eun Lee,1 Geoffrey C. Toon,1 André Butz,2 Martin Jung,3

Akihiko Kuze,4 and Tatsuya Yokota5

Received 30 June 2011; revised 11 August 2011; accepted 16 August 2011; published 14 September 2011.

[1] Our ability to close the Earth’s carbon budget and pre-dict feedbacks in a warming climate depends critically onknowing where, when and how carbon dioxide is exchangedbetween the land and atmosphere. Terrestrial gross primaryproduction (GPP) constitutes the largest flux component inthe global carbon budget, however significant uncertaintiesremain in GPP estimates and its seasonality. Empirically,we show that global spaceborne observations of solarinduced chlorophyll fluorescence – occurring during photo-synthesis – exhibit a strong linear correlation with GPP. Wefound that the fluorescence emission even without any addi-tional climatic or model information has the same or betterpredictive skill in estimating GPP as those derived from tra-ditional remotely‐sensed vegetation indices using ancillarydata and model assumptions. In boreal summer the generallystrong linear correlation between fluorescence and GPPmodels weakens, attributable to discrepancies in savannas/croplands (18–48% higher fluorescence‐based GPP derivedby simple linear scaling), and high‐latitude needleleaf for-ests (28–32% lower fluorescence). Our results demonstratethat retrievals of chlorophyll fluorescence provide directglobal observational constraints for GPP and open anentirely new viewpoint on the global carbon cycle. Weanticipate that global fluorescence data in combination withconsolidated plant physiological fluorescence models willbe a step‐change in carbon cycle research and enable anunprecedented robustness in the understanding of the currentand future carbon cycle. Citation: Frankenberg, C., et al.(2011), New global observations of the terrestrial carbon cycle fromGOSAT: Patterns of plant fluorescence with gross primary produc-t iv i ty , Geophys . Res . Le t t . , 38 , L17706, doi :10 .1029/2011GL048738.

[2] Gross primary production (GPP) through photosyn-thesis by terrestrial ecosystems constitutes the largest globalland carbon flux [Zhao and Running, 2010; Beer et al.,2010]. Currently there are two main spatially explicit

approaches to quantify GPP globally: 1) meteorology‐driven full land surface carbon cycle models [Friedlingsteinet al., 2006; Sitch et al., 2008]; and, 2) remote sensing‐driven [Zhao and Running, 2010] and/or flux tower based[Beer et al., 2010; Jung et al., 2011] semi‐empirical modelsfocused on GPP or net primary production (NPP). Signifi-cant uncertainties related with the first approach are due todiffering model sensitivities to meteorological parametersand uncertain global meteorological data sets [Friedlingsteinet al., 2006; Sitch et al., 2008]. Uncertainties with the secondapproach exist because GPP cannot directly be estimatedfrom the remote sensing measurements but is also modeledas a function of leaf area index (LAI) and fraction ofabsorbed photosynthetically active radiation (fAPAR) orgreenness indices such as the normalized difference orenhanced vegetation indices (NDVI, EVI) [Zhao et al.,2005]. These indices are often contaminated by atmo-spheric interference, and may contribute a misleading signalwhen vegetation becomes stressed, e.g., green canopies thatare not photosynthesizing [Huete et al., 2002].[3] Remote sensing of solar‐induced chlorophyll fluores-

cence (Fs) [Krause and Weis, 1991], as intended with theFLEX satellite mission, offers a direct physiology‐basedmeasure of global photosynthetic activity. Absorbed pho-tosynthetically active radiation (APAR) within 400–700 nmwavelengths drives photosynthesis, but can also be dissi-pated into heat or re‐radiated at longer wavelengths (660–800 nm), which is termed fluorescence. At the laboratoryand field scale, chlorophyll fluorescence has been inten-sively studied [Moya et al., 2004; Corp et al., 2006; Baker,2008; Campbell et al., 2008; Genty et al., 1989] but space‐borne remote sensing of fluorescence is more difficult[Frankenberg et al., 2011] and accurate data has so far notbeen available. Concerning solar‐induced steady statefluorescence, an implicit direct correlation with GPP existsas both depend on absorbed radiation. Also, field studies[Flexas et al., 2002; Damm et al., 2010; Rascher et al.,2009] as well as theoretical modelling [Van der Tol et al.,2009] show a clear positive correlation of CO2 assimila-tion and stomatal conductance with Fs, especially becauseincreases in heat dissipation under high light conditionscause a concurrent reduction of both fluorescence andphotosynthesis yield. These physiological signals providedby fluorescence are not directly achievable with traditionalvegetation remote sensing products, which model GPPusing a multitude of ancillary data and model assumptions,all of which are prone to errors. Especially light use effi-ciency (LUE) is difficult to model on a global scale as it

1Jet Propulsion Laboratory, California Institute of Technology,Pasadena, California, USA.

2Karlsruhe Institute of Technology, Institute for Meteorology andClimate Research, Leopoldshafen, Germany.

3Biogeochemical Model-Data Integration Group, Max PlanckInstitute for Biogeochemistry, Jena, Germany.

4Japan Aerospace Exploration Agency, Tsukuba, Japan.5National Institute for Environmental Studies, Tsukuba, Japan.

Copyright 2011 by the American Geophysical Union.0094‐8276/11/2011GL048738

GEOPHYSICAL RESEARCH LETTERS, VOL. 38, L17706, doi:10.1029/2011GL048738, 2011

L17706 1 of 6

Biogeosciences, 8, 637–651, 2011www.biogeosciences.net/8/637/2011/doi:10.5194/bg-8-637-2011© Author(s) 2011. CC Attribution 3.0 License.

Biogeosciences

First observations of global and seasonal terrestrial chlorophyllfluorescence from spaceJ. Joiner1, Y. Yoshida2, A. P. Vasilkov2, Y. Yoshida3, L. A. Corp4, and E. M. Middleton11NASA Goddard Space Flight Center, Greenbelt, MD, USA2Science Systems and Applications Inc., 10210 Greenbelt, Rd., Ste 400, Lanham, MD, USA3National Institute for Environmental Studies (NIES), Tsukuba-City, Ibaraki, Japan4Sigma Space Corp., 4600 Forbes Blvd., Lanham, MD, USA

Received: 19 October 2010 – Published in Biogeosciences Discuss.: 11 November 2010Revised: 27 February 2011 – Accepted: 1 March 2011 – Published: 8 March 2011

Abstract. Remote sensing of terrestrial vegetation fluores-cence from space is of interest because it can potentially pro-vide global coverage of the functional status of vegetation.For example, fluorescence observations may provide a meansto detect vegetation stress before chlorophyll reductions takeplace. Although there have been many measurements offluorescence from ground- and airborne-based instruments,there has been scant information available from satellites.In this work, we use high-spectral resolution data from theThermal And Near-infrared Sensor for carbon Observation– Fourier Transform Spectrometer (TANSO-FTS) on theJapanese Greenhouse gases Observing SATellite (GOSAT)that is in a sun-synchronous orbit with an equator cross-ing time near 13:00 LT. We use filling-in of the potassium(K) I solar Fraunhofer line near 770 nm to derive chloro-phyll fluorescence and related parameters such as the fluo-rescence yield at that wavelength. We map these parame-ters globally for two months (July and December 2009) andshow a full seasonal cycle for several different locations, in-cluding two in the Amazonia region. We also compare thederived fluorescence information with that provided by theMODIS Enhanced Vegetation Index (EVI). These compar-isons show that for several areas these two indices exhibitdifferent seasonality and/or relative intensity variations, andthat changes in fluorescence frequently lead those seen in theEVI for those regions. The derived fluorescence thereforeprovides information that is related to, but independent ofthe reflectance.

Correspondence to: J. Joiner(joanna.joiner@nasa.gov)

1 Introduction

Vegetation is the functional interface between the Earth’s ter-restrial biosphere and the atmosphere. Terrestrial ecosystemsabsorb approximately 120Gt of carbon annually through thephysiological process of photosynthesis. About 50% of thecarbon is released by ecosystem respiration processes withinshort time periods. The remaining carbon is referred to asNet Primary Production (NPP). Disturbances and long termchanges of ecosystems release parts of this carbon within thetime frame of centuries. There are currently great uncertain-ties for the human impact on the magnitude of these pro-cesses.Photosynthesis is the conversion by living organisms of

light energy into chemical energy and fixation of atmosphericcarbon dioxide into sugars; it is the key process mediating90% of carbon and water fluxes in the coupled biosphere-atmosphere system. Until now, most of the information thathas been acquired by remote sensing of the Earth’s surfaceabout vegetation conditions has come from reflected light inthe solar domain. There is, however, one additional source ofinformation about vegetation productivity in the optical andnear-infrared wavelength range that has not been globally ex-ploited by satellite observations. This source of informationis related to the emission of fluorescence from the chloro-phyll of assimilating leaves; part of the energy absorbed bychlorophyll cannot be used for carbon fixation and is thus re-emitted as fluorescence at longer wavelengths (lower energy)with respect to the absorption.The fluorescence signal originates from the core com-

plexes of the photosynthetic machinery where energy conver-sion of absorbed photosynthetically active radiation (APAR)occurs. Because the photosynthetic apparatus is an organizedstructure, the emission spectrum of fluorescence that origi-nates from it is well known; it occurs as a convolution of

Published by Copernicus Publications on behalf of the European Geosciences Union.

Terrestrial Gross Primary Production Inferred From Satellite Fluorescence and Vegetation Models, Parazoo et al. 2014, GCB"

Interpreting seasonal changes in the carbon balance of southernAmazonia using measurements of XCO2 and chlorophyll fluorescencefrom GOSAT

Nicholas C. Parazoo,1,2 Kevin Bowman,1,2 Christian Frankenberg,1 Jung-Eun Lee,1

Joshua B. Fisher,1 John Worden,1 Dylan B. A. Jones,2,3 Joseph Berry,4

G. James Collatz,5 Ian T. Baker,6 Martin Jung,7 Junjie Liu,1 Gregory Osterman,1

Chris O’Dell,6 Athena Sparks,1 Andre Butz,8 Sandrine Guerlet,9 Yukio Yoshida,10

Huilin Chen,11,12 and Christoph Gerbig7

Received 7 March 2013; revised 4 April 2013; accepted 5 April 2013; published 6 June 2013.

[1] Amazon forests exert a major influence on the globalcarbon cycle, but quantifying the impact is complicated bydiverse landscapes and sparse data. Here we examineseasonal carbon balance in southern Amazonia using newmeasurements of column-averaged dry air mole fraction ofCO2 (XCO2) and solar induced chlorophyll fluorescence(SIF) from the Greenhouse Gases Observing Satellite(GOSAT) from July 2009 to December 2010. SIF, whichreflects gross primary production (GPP), is used to disentanglethe photosynthetic component of land-atmosphere carbonexchange. We find that tropical transitional forests in southernAmazonia exhibit a pattern of low XCO2 during the wetseason and high XCO2 in the dry season that is robust toretrieval methodology and with seasonal amplitude doublethat of cerrado ecosystems to the east (4 ppm versus 2 ppm),including enhanced dilution of 2.5 ppm in the wet season.Concomitant measurements of SIF, which are inverselycorrelated with XCO2 in southern Amazonia (r =!0.53,p< 0.001), indicate that the enhanced variability is driven byseasonal changes in GPP due to coupling of strong vertical

mixing with seasonal changes in underlying carbon exchange.This finding is supported by forward simulations of theGoddard Chemistry Transport Model (GEOS-Chem) whichshow that local carbon uptake in the wet season and loss inthe dry season due to emissions by ecosystem respiration andbiomass burning produces best agreement with observedXCO2. We conclude that GOSAT provides criticalmeasurements of carbon exchange in southern Amazonia, butmore samples are needed to examine moist Amazon forestsfarther north. Citation: Parazoo, N. C., et al. (2013), Interpretingseasonal changes in the carbon balance of southern Amazonia usingmeasurements of XCO2 and chlorophyll fluorescence from GOSAT,Geophys. Res. Lett., 40, 2829–2833, doi:10.1002/grl.50452.

1. Introduction

[2] The Amazon basin plays a significant role in the globalcarbon cycle. Nearly half of all tropical biomass (120 PgC)is stored in roots and trees, with 0.5 PgC year!1 lost throughdeforestation and 0.6 PgC year!1 gained by intact forests[Malhi et al., 2009, and references therein]. There is alsosignificant interannual variability in carbon exchange, drivenby changes in the biophysical state of rain forests duringlarge-scale disturbances such as drought, which cause anom-alies in the global growth rate of atmospheric CO2 [Bousquetet al., 2000]. With vulnerability to drought stress expected toincrease with climate change [e.g., Phillips et al., 2009],Amazonian forests may play a more prominent role inmodulating future increases of atmospheric CO2 and,through radiative forcing, climate change [e.g., Cox et al.,2004]. However, there is still much uncertainty in our under-standing of basin-wide carbon balance.[3] In particular, seasonal patterns of net ecosystem

exchange (NEE) measured from flux towers vary signifi-cantly across Amazonia, with weak seasonal cycles in thenorth at Manaus, stronger seasonality to east at TapajosNational Forest near Santarem and south at Jarú Reserveand Fazenda Maracai (SIN), and still stronger seasonalitysoutheast of Amazonia (e.g., Pe DeGigante) (sites describedin Keller et al. [2004] and Baker et al., [2013] and shown inFigure 1). These patterns predominantly follow vegetationand precipitation gradients [e.g., da Rocha et al., 2009];however, additional factors such as vegetation age, topogra-phy, and soil properties also influence NEE [e.g., Kelleret al., 2004]. Ecosystem models and flux tower measure-ments of gross primary production (GPP) and ecosystem

Additional supporting information may be found in the online version ofthis article.

1Jet Propulsion Laboratory, California Institute of Technology,Pasadena, California, USA.

2Joint Institute for Regional Earth System Science and Engineering,University of California, Los Angeles, California, USA.

3Department of Physics, University of Toronto, Toronto, Ontario,Canada.

4Department of Global Ecology, Carnegie Institution for Science,Stanford, California, USA.

5National Aeronautics’ Space Administration, Goddard Space FlightCenter, Greenbelt, Maryland, USA.

6Department of Atmospheric Science, Colorado State University, FortCollins, Colorado, USA.

7Department for Biogeochemical Systems, Max Planck Institute forBiogeochemistry, Jena, Germany.

8IMK-ASF, Karlsruhe Institute of Technology, Leopoldshafen, Germany.9Netherlands Institute for Space Research, Utrecht, Netherlands.10Center for Global Environmental Research, National Institute for

Environmental Studies, Tsukuba, Japan.11NOAA Earth System Research Laboratory, Boulder, Colorado, USA.12Now at Center for Isotope Research, University of Groningen,

Groningen, The Netherlands.

Corresponding author: N. Parazoo, Jet Propulsion Laboratory,California Institute of Technology, Pasadena, CA 91109, USA. (Nicholas.C.Parazoo@jpl.nasa.gov)

©2013. American Geophysical Union. All Rights Reserved.0094-8276/13/10.1002/grl.50452

2829

GEOPHYSICAL RESEARCH LETTERS, VOL. 40, 2829–2833, doi:10.1002/grl.50452, 2013

Global:  Prescribed  vegeta3on  cover  JULES3.2  New  PFTs  GPP,  1982-­‐2012  Global  =  165  GtC/yr    

JULES3.2  Old  PFTs  GPP,  1982-­‐2012  Global  =  131  GtC/yr    

MTE  GPP*,  1982-­‐2012  Global  =  115  GtC/yr    

0        1          2        3          4          5        6        7        8          9        10      11  gC  m-­‐2  d-­‐1    

*Jung et al. 2011, JGR  -­‐5      -­‐4    -­‐3    -­‐2    -­‐1        0      1        2      3        4        5  

gC  m-­‐2  d-­‐1    

New  PFTs  -­‐  MTE  GPP,  1982-­‐2012  

GPP & NPP  JULES3.2  New  PFTs  GPP,  1982-­‐2012  Global  =  142  GtC/yr    

JULES3.2  GPP,  1982-­‐2012  Global  =  148  GtC/yr  

•  Global  NPP  is  closer  to  what  we  expect  from  observa3onal  constraints  (50-­‐60  GtC)    

•  NPP  =64  GtC  (Old  PFTs)  

•  NPP=  52  GtC  (New  PFTs)  

•  But  low  carbon  use  efficiency  (NPP/GPP)  à  Rauto  is  high.  

0        1          2        3          4          5        6        7        8          9        10      11  gC  m-­‐2  d-­‐1    

JULES3.2  New  PFTs  NPP/GPP,  1980-­‐2012  Global  =  0.36  

JULES3.2  Old  PFTs  NPP/GPP,  1980-­‐2012  Global  =  0.43