Photosynthesis in silicoUnderstanding Complexity from Molecules to Ecosystems

Advances in Photosynthesis and Respiration

VOLUME 29

Series Editor:

GOVINDJEEUniversity of Illinois, Urbana, Illinois, U.S.A.

Consulting Editors:Julian EATON-RYE, Dunedin, New Zealand

Christine H. FOYER, Harpenden, U.K.David B. KNAFF, Lubbock, Texas, U.S.A.

Anthony L. MOORE, Brighton, U.K.Sabeeha MERCHANT, Los Angeles, California, U.S.A.

Krishna NIYOGI, Berkeley, California, U.S.A.William PARSON, Seatle, Washington, U.S.A.Agepati RAGHAVENDRA, Hyderabad, India

Gernot RENGER, Berlin, Germany

The scope of our series, beginning with volume 11, reflects the concept that photosynthesis andrespiration are intertwined with respect to both the protein complexes involved and to the entirebioenergetic machinery of all life. Advances in Photosynthesis and Respiration is a book seriesthat provides a comprehensive and state-of-the-art account of research in photosynthesis andrespiration. Photosynthesis is the process by which higher plants, algae, and certain species ofbacteria transform and store solar energy in the form of energy-rich organic molecules. Thesecompounds are in turn used as the energy source for all growth and reproduction in theseand almost all other organisms. As such, virtually all life on the planet ultimately depends onphotosynthetic energy conversion. Respiration, which occurs in mitochondrial and bacterialmembranes, utilizes energy present in organic molecules to fuel a wide range of metabolicreactions critical for cell growth and development. In addition, many photosynthetic organismsengage in energetically wasteful photorespiration that begins in the chloroplast with an oxy-genation reaction catalyzed by the same enzyme responsible for capturing carbon dioxide inphotosynthesis. This series of books spans topics from physics to agronomy and medicine,from femtosecond processes to season long production, from the photophysics of reactioncenters, through the electrochemistry of intermediate electron transfer, to the physiology ofwhole organisms, and from X-ray crystallography of proteins to the morphology or organellesand intact organisms. The goal of the series is to offer beginning researchers, advanced under-graduate students, graduate students, and even research specialists, a comprehensive, up-to-date picture of the remarkable advances across the full scope of research on photosynthesis,respiration and related processes.

For other titles published in this series, go to

www.springer.com/series/5599

Photosynthesis in silicoUnderstanding Complexity from Molecules

to Ecosystems

Edited by

Agu LaiskUniversity of Tartu

Estonia

Ladislav NedbalInstitute of Systems Biology and Ecology

Academy of Sciences of the Czech RepublicNové Hrady

Czech Republic

and

GovindjeeUniversity of Illinois at Urbana-Champaign

UrbanaIllinoisUSA

Library of Congress Control Number: 2009921443

ISBN 978-1-4020-9236-7 (HB)ISBN 978-1-4020-9237-4 (e-book)

Published by Springer,P.O. Box 17, 3300 AA Dordrecht, The Netherlands.

www.springer.com

Cover: Photosynthesis in silico. Photo by Eero Talts, University of Tartu

Printed on acid-free paper

All Rights Reservedc© 2009 Springer Science+Business Media B.V.

No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means,electronic, mechanical, photocopying, microfi lming, recording or otherwise, without written permission from the Publisher,

with the exception of any material supplied specifi cally for the purpose of being entered and executed on a computersystem, for exclusive use by the purchaser of the work.

From the Series Editor

I am highly obliged to each and everyone of theauthors from fifteen countries(Australia, Austria,Brazil, Canada, China, Czech Republic, Esto-nia, France, Germany, Lithuania, Russia, Switzer-land, The Netherlands, U.K., and U.S.A.) fortheir valuable contributions to the successful andtimely production of this unique book, Volume 29in Advances in Photosynthesis and Respiration:‘Photosynthesis in silico—Understanding Com-plexity from Molecules to Ecosystems’, editedby two of the pioneers in the field (Agu Laisk,of Estonia; and Ladislav Nedbal, of the CzechRepublic).

The authors are: Niels P.R. Anten (TheNetherlands; Chapter 16); Michael J. Behrenfeld(U.S.A.; Chapter 20); Carl J. Bernacchi (U.S.A.;Chapter 10); Joseph Berry (U.S.A.; Chapter 9);Jan Cervený (Czech Republic; Chapter 2); JanP. Dekker (The Netherlands; Chapter 3); GeraldEdwards (U.S.A.; Chapter 14); Hillar Eichelmann(Estonia: Chapter 13); Hadi Farazdaghi (Canada;Chapter 12); Graham Farquhar (Australia; Chap-ters 9 and 10); Arvi Freiberg (Estonia; Chapter4); Andrew Friend (U.K.; Chapter 20); RichardJ. Geider (U.K.; Chapter 20); Jeremy Harbinson(The Netherlands; Chapter 11); HubertHasenauer (Austria; Chapter 19) Michael Hucka(U.S.A.; Chapter 1); Manfred Küppers (Ger-many; Chapter 18); Agu Laisk (Estonia; Chapters13 and 14); Jérôme Lavergne (France; Chapter8); Dušan Lazár (Czech Republic; Chapter 5);Stephen P. Long (U.S.A.; Chapters 10 and 17);Ladislav Nedbal (Czech Republic; Chapter 2);Ülo Niinemets (Estonia; Chapter 16); VladimirI. Novoderezhkin (Russia; Chapter 3); Vello Oja(Estonia; Chapter 13); Michael Pfiz (Germany;Chapter 18); Stephen A. Pietsch (Austria;Chapter 19); Carlos Pimentel (Brazil; Chapter10); Ondrej Prášil (Czech Republic; Chapter 6);Galina Riznichenko (Russia; Chapter 7); DavidM. Rosenthal (U.S.A.; Chapter 10); AndrewRubin (Russia; Chapter 7); James Schaff (U.S.A.;Chapter 1); Gert Schansker (Switzerland; Chap-ter 5); Henning Schmidt (Germany; Chapter 2);

Christopher J. Still (U.S.A.; Chapter 20); Paul C.Struik (The Netherlands; Chapter 11); GediminasTrinkunas (Lithuania; Chapter 4); Rienk vanGrondelle (The Netherlands; Chapter 3); Susannevon Caemmerer (Australia; Chapter 9); WimVredenberg (The Netherlands; Chapter 6); Ian E.Woodrow (Australia; Chapter 15); Xinyou Yin(The Netherlands; Chapter 11), and Xin-GuangZhu (China; Chapter 17).

I also thank Jacco Flipsen, Noeline Gibsonand André Tournois of Springer (Dordrecht, TheNetherlands) for their patience with me duringthe production of this book. I am particularlythankful to Albert André Joseph (of SPi Tech-nologies India Private Limited) for his wonder-ful cooperation in efficiently taking care of thecorrections in the proofs of this book. Finally, Iam grateful to my wife, Rajni Govindjee, and theoffices of the Department of Plant Biology (FengSheng Hu, Head) and of Information Technology,Life Sciences (Jeff Haas, Director), of the Uni-versity of Illinois at Urbana-Champaign, for theirconstant support.

A list of books, published under the Series‘Advances in Photosynthesis and Respiration’ isavailable at the Springer web site: <http://www.springer.com/series/5599>. Members of theISPR (International Society of PhotosynthesisResearch) receive 25 % discount. For the Tableof Content of most of the earlier volumes, see myweb site at: <http://www.life.uiuc.edu/govindjee/Reference-Index.htm>.

GovindjeeFounding Editor of Advances in Photosynthesis

and RespirationDepartments of Biochemistry and Plant Biology

and Center of Biophysics & ComputationalBiology

University of Illinois at Urbana-Champaign,Illinois, USA

E-mail: gov@life.illinois.edu

v

Contents

From the Series Editor v

Preface xv

The Editors xvii

Author Index xxi

Color Plates CP1

Part I: General Problems of Biological Modeling

1 Trends and Tools for Modeling in Modern Biology 3–15Michael Hucka and James Schaff

Summary 3I. Introduction 4II. Representing Model Structure and Mathematics 4III. Augmenting Models with Semantic Annotations 6IV. Connecting Models to Results 9V. Future Directions for Systems Biology Markup Language (SBML) 13VI. Conclusions 13References 14

2 Scaling and Integration of Kinetic Models of Photosynthesis:Towards Comprehensive E-Photosynthesis 17–29

Ladislav Nedbal, Jan Cervený and Henning Schmidt

Summary 17I. Introduction 18II. Mapping Partial Photosynthesis Models into the Comprehensive

Model Space (CMS): The Principles and Strategies 19III. Mapping of Photosystem II Models into the Comprehensive

Model Space (CMS) 21IV. Concluding Remarks 27Acknowledgments 28References 28

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Part II: Modeling of Light Harvesting and PrimaryCharge Separation

3 Modeling Light Harvesting and Primary Charge Separationin Photosystem I and Photosystem II 33–53

Rienk van Grondelle, Vladimir I. Novoderezhkin and Jan P. Dekker

Summary 34I. Introduction 34II. Physical Models of Energy Transfer 35III. Exciton Spectra and Energy Transfer in Photosystem I (PS I) Core 40IV. Excitation Dynamics in Major Light Harvesting Complex II (LHCII) 41V. Energy Transfers and Primary Charge Separation in Photosystem II

Reaction Center 44VI. Concluding Remarks 50Acknowledgments 50References 50

4 Unraveling the Hidden Nature of Antenna Excitations 55–82Arvi Freiberg and Gediminas Trinkunas

Summary 55I. Introduction 56II. Disordered Frenkel Exciton Model for Absorbing States

of Circular Antenna Aggregates 59III. Shortcomings of the Disordered Frenkel Exciton Model 63IV. Excitonic Polaron Model of the Antenna Fluorescing States 64V. Evaluation of the Model Parameters from the Experimental Spectra 70VI. Conclusions and Outlook 76Acknowledgments 77References 77

Part III: Modeling Electron Transport and Chlorophyll Fluorescence

5 Models of Chlorophyll a Fluorescence Transients 85–123Dušan Lazár and Gert Schansker

Summary 86I. Fluorescence Induction 86II. Approaches and Assumptions in the Modeling of the Fluorescence Rise 91III. Particular Models for the Fluorescence Rise 100IV. Modeling the Whole Fluorescence Induction 111V. Conclusions and Future Perspectives 115Acknowledgments 115References 115

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6 Modeling of Chlorophyll a Fluorescence Kinetics in Plant Cells:Derivation of a Descriptive Algorithm 125–149

Wim Vredenberg and Ondrej Prášil

Summary 126I. Introduction 126II. Variable (Chlorophyll) Fluorescence – Some Basics 128III. Application of Single, Twin and Multiple Turnover Flashes 132IV. Distinguishable Phases of Fluorescence Response

upon Multiturnover Excitation 135V. Fluorescence Induction Algorithm for Experimental Curves 137VI. Concluding Remarks 144Acknowledgments 146References 146

7 Modeling of the Primary Processes in a Photosynthetic Membrane 151–176

Andrew Rubin and Galina Riznichenko

Summary 151I. Introduction 152II. Fluorescence as an Indicator of the Photosystem State 153III. General Kinetic Model of the Processes in Photosynthetic

Thylakoid Membrane 154IV. Multiparticle Modeling of the Processes in the Photosynthetic Membrane 166V. Concluding Remarks and Future Perspectives 171Acknowledgments 171References 171

8 Clustering of Electron Transfer Components:Kinetic and Thermodynamic Consequences 177–205

Jérôme Lavergne

Summary 177I. Introduction 178II. Thermodynamic Performance of Integrated and Diffusive

Photosynthetic Models 179III. Integrated Versus Diffusive Electron Transfer Chain 183IV. The Small Apparent Equilibrium Constant in the Donor Chain

of Rhodobacter sphaeroides 189V. Quinone Domains 195VI. Statistical and Non Statistical Heterogeneities 198VII. Pool Function Test at Steady State 199VIII. Kinetic Analysis: Playing with Inhibitors, Redox Potential and Flash Intensity 201IX. Concluding Remarks 203Acknowledgments 203References 203

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Part IV: Integrated Modeling of Light and Dark Reactionsof Photosynthesis

9 Biochemical Model of C3 Photosynthesis 209–230Susanne von Caemmerer, Graham Farquhar and Joseph Berry

Summary 210I. Introduction 210II. The Rate Equations of CO2 Assimilation 211III. Parameters and their Temperature Dependencies 215IV. The Role of Rubisco Activation State 218V. Estimating Chloroplast pCO2 219VI. Predicting Photosynthesis from Chloroplast Biochemistry 220VII. Predicting Chloroplast Biochemistry from Leaf Gas Exchange 223VIII. Concluding Remarks 224References 225

10 Modeling the Temperature Dependence of C3 Photosynthesis 231–246Carl J. Bernacchi, David M. Rosenthal, Carlos Pimentel,Stephen P. Long and Graham D. Farquhar

Summary 232I. Introduction 232II. Processes Limiting to C3 Photosynthesis 233III. Modeling Photosynthesis and the Supply of CO2 240IV. Concluding Remarks 242Acknowledgments 243References 243

11 A Model of the Generalized Stoichiometry of Electron TransportLimited C3 Photosynthesis: Development and Applications 247–273

Xinyou Yin, Jeremy Harbinson and Paul C. Struik

Summary 247I. Introduction 248II. Model Development 250III. Model Applications 255IV. Concluding Remarks 269Acknowledgments 269References 270

12 Modeling the Kinetics of Activation and Reaction of Rubiscofrom Gas Exchange 275–294

Hadi Farazdaghi

Summary 275I. Introduction 276II. Fundamental Photosynthesis Models 276III. Rubisco and Its Sequentially Ordered Reaction 279

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IV. Rubisco in Steady State: Biochemical Models 281V. Experimental Evaluation of the Models 287VI. Concluding Remarks 290Acknowledgments 291References 291

13 Leaf C3 Photosynthesis in silico:Integrated Carbon/Nitrogen Metabolism 295–322

Agu Laisk, Hillar Eichelmann and Vello Oja

Summary 295I. Introduction 296II. The Structure of the Model 297III. Mathematics 302IV. Simulations 312V. Concluding Remarks 317Acknowledgments 319References 319

14 Leaf C4 Photosynthesis in silico:The CO2 Concentrating Mechanism 323–348

Agu Laisk and Gerald Edwards

Summary 324I. Introduction 324II. Principles of NADP-ME Type C4 Photosynthesis 325III. The C4 Model 329IV. Simulations 334V. Knowns and Unknowns in Photosynthesis 338Acknowledgments 345References 345

15 Flux Control Analysis of the Rate of PhotosyntheticCO2 Assimilation 349–360

Ian E. Woodrow

Summary 349I. Introduction 350II. Flux Control Coefficients: Theory and Challenges 352III. Reversible Reactions Can Be Flux Limiting 352IV. Small Control Coefficients Are Hard to Detect 354V. Enzymes with Higher Control Coefficients 356VI. Photosynthetic Electron Transport 358VII. Concluding Remarks 358Acknowledgments 359References 359

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Part V: From Leaves to Canopies to the Globe

16 Packing the Photosynthetic Machinery: From Leaf to Canopy 363–399Ülo Niinemets and Niels P.R. Anten

Summary 364I. Introduction 364II. Inherent Differences in Microenvironment and Photosynthetic Potentials

Within the Canopy 367III. Scaling Photosynthesis from Leaves to Canopy 379IV. Concluding Remarks 389Acknowledgments 389References 390

17 Can Increase in Rubisco Specificity Increase Carbon Gainby Whole Canopy? A Modeling Analysis 401–416

Xin-Guang Zhu and Stephen P. Long

Summary 401I. Introduction 402II. Theory and Model Description 404III. The Impact of the Inverse Relationship on Leaf and Canopy

Level Photosynthesis 407IV. Current Efforts of Engineering Rubisco for Higher Photosynthesis 410V. Why Has Evolution Failed to Select the Optimal Rubisco? 412VI. Concluding Remarks 413Acknowledgments 413References 413

18 Role of Photosynthetic Induction for Daily and Annual CarbonGains of Leaves and Plant Canopies 417–440

Manfred Küppers and Michael Pfiz

Summary 417I. Introduction 418II. Representation of Plant Architecture by Digital Reconstruction 418III. The Dynamic Light Environment 419IV. Models of Dynamic Photosynthesis 427V. Calculation of Crown Carbon Acquisition 429VI. Annual Carbon Gains from Steady-state and Dynamic

Photosynthesis Simulations 431VII. Concluding Remarks 436Acknowledgments 436References 436

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19 Photosynthesis Within Large-Scale Ecosystem Models 441–464Stephan A. Pietsch and Hubert Hasenauer

Summary 441I. Introduction 442II. Biogeochemical Cycles 443III. Models of Biogeochemical Cycles 446IV. Model Application 452V. Examples of Model Application 456VI. Concluding Remarks 461Acknowledgments 462References 462

20 Photosynthesis in Global-Scale Models 465–497Andrew D. Friend, Richard J. Geider, Michael J. Behrenfeldand Christopher J. Still

Summary 466I. Introduction 467II. Description of Model Approaches 469III. Global Simulation 480IV. Concluding Remarks 486Acknowledgments 488References 488

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Index 499

Preface

Scientific perception of nature relies on a pro-cess of transforming data to information, and theninformation into understanding. Data consist ofobservations and measurements and informationis data organized according to some ontology,i.e. some set of assumptions about what entitiesexist and how they should be classified. Under-standing is a model in the investigator’s mind thatdescribes how the entities relate to each other,a model created in the investigator’s mind as aresult of thinking. Thinking is thus a kind of self-programing of the brain, as a result of whichunderstanding is achieved. When it “runs” in ourbrains, it allows us to predict the behavior ofnatural objects, e.g. in their temporal and spatialaspects. For communication within the scientificcommunity, we first share new data, but thenshare the rigorous forms of the models, whichmay be verbal, graphic, or at their best, math-ematical constructions, reflecting essential fea-tures of a natural system. The latter way of pre-sentation of our understanding of photosynthesisis the subject of this book. In many chapters, themodels are represented by differential equationsthat can reproduce the dynamics of the naturalsystem, or in form of linear equations that definesteady state fluxes or stoichiometries of such asystem. A good model can not only reproducealready measured data about the behavior of theinvestigated system, but it can also predict resultsfor future experiments.

By definition, models are approximations ofnature that are by no means capable of capturingall aspects of the investigated system, no matterhow powerful computers we may have used for it.In the early days of photosynthesis research, mod-els were ingenious by their capacity to explaina prominent feature of the investigated process,such as, for example, the photochemical quench-ing of chlorophyll fluorescence. The early modelswere frequently relatively simple, not requiringa complex code or ontology. The closing of thereaction centers of Photosystem II during chloro-phyll fluorescence induction was well describedby Louis N. M. Duysens assuming a single com-ponent – the quencher Q. With increasing experi-mental accuracy and increasing complexity of the

experimental protocols, this simple model was, interms of Karl Popper’s logic of scientific discov-ery, falsified or, in other words, its validity limitswere found. The simple ‘Quencher ‘Q’ model’of Duysens fell short, for example, in explain-ing the periodicity of four that occurs in chloro-phyll fluorescence emission with multiple singleturnover flashes, or in explaining the sigmoidalshape of the chlorophyll fluorescence inductioncurve. This and other models are perpetuallyexpanding to explain new data obtained with newexperimental protocols.

Such an expectation of the linear expansionof the models is by itself a simplified model.Sometimes an established, “generally accepted”,feature of the model is replaced by another modi-fication, a novel mechanism that explains alreadyknown data as well as the previously assumedmechanism, but widens and deepens the predic-tive power of the model. Thus, different mod-els can explain similar or related phenomena,but only those are accepted for wider use thatare able to accommodate new experimental dataand more sophisticated protocols. The ‘falsified’older and simpler models are not necessarilyrejected and forgotten. Much more often theycontinue to be used with reservation about theirrange of applicability. For example, one does notneed to consider the participation of pheophytinfor the understanding of simple chlorophyll fluo-rescence induction curve on the time scale of sec-onds. In the area of whole photosynthetic processthat specifically includes carbon fixation, GrahamFaquhar, Susanne von Caemmerer and JosephBerry have elegantly approximated it with twoenzymatic reactions only. These ontogeneticallyolder (in the sense of model development) modelsare typically easier to solve and can be obtainedfrom the newer models by mathematically rigor-ous or empirical dimensionality reduction.

Photosynthesis is a complex process spanningfrom femtoseconds to days to seasons to centuriesin time domain and from atoms to the globalbiosphere in spatial domain. No single model candescribe photosynthesis in its full complexity andeven approaching such an elusive goal would notbe practical because such a mathematical model

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would not be solvable, being as complex in itsstructure as nature itself. Rather, the process canbe described in a mosaic of models such as theones offered in this book. With increasing com-plexity of the models, we suggest that the read-ers consult the first two chapters of this bookfor a standardization of the model description,so that models become more than abstractionsof individual modelers that are hard to share,merge or even compare with each other. Weexpect this book to be a beginning for creatinga comprehensive modeling space of photosyn-thetic processes that would facilitate an ongoing‘falsification-upgrade’ modeling spiral and wouldallow mergers between related model lines. Theindividual model areas represented here beginwith the absorption of a photon and include elec-tron transport, carbon assimilation, and productsynthesis. With all these molecular models athand one can upscale to cell, organ, plant, canopy,and eventually to global biosphere. Chapters pre-sented in this book show how different levels ofbiological hierarchy overlay and interact in theamazing process of photosynthesis.

Photosynthesis in silico is a unique book inits integrated approach to the understanding ofphotosynthesis processes from light absorptionand excitation energy transfer to global aspects ofphotosynthetic productivity – all interconnectedby the use of mathematical modeling. The bookis written by 44 international authorities from 15countries. Chapters in this book are presentedin a review style with emphasis on the latestbreakthroughs. Instead of providing mathemati-cal details, only the key equations, the basis forthe novel conclusions, are provided, with refer-ences to the original work at the end of eachchapter. Thus, de facto this is not a mathemat-ical book of equations, but dominantly verbaldiscussion showing why the quantitative logic ofmathematics has been so efficient for understand-ing the subject. Yet, in order to exploit the fullpotential of the book, we hope the models willeventually be translated to the universal formatof the Systems Biology Mark-Up Language andmade accessible also in their full mathematicalform on the internet. As argued in Chapter 1,

we stand here at the beginning of a qualitativelynew scientific collaboration with its dynamicslargely dependent on willingness of our researchcommunity to share resources to generate a free-access model database of photosynthesis. Suchan endeavor is fully justified by an increasinglyrecognized role of photosynthesis in nature andlately also as an important alternative for tech-nological solutions of currently surging energyneeds of the humankind.

We thank our families and coworkers in ourlaboratories for their patience with us, and fortheir support during the preparation of this book.We also thank Noeline Gibson, Jacco Flipsen andAndré Tournois, of Springer, for their friendlyand valuable guidance during the typesetting andprinting of this book.

Agu LaiskInstitute of Molecular and Cell Biology

University of Tartu, Riia 23, Tartu 51010Estonia

Telephone: 372 736 6021Fax: 372 742 0286

e-mail: alaisk@ut.ee

Ladislav NedbalDepartment of Biological Dynamics

Institute of Systems Biology and Ecology CASZámek 136, 37333 Nové Hrady

Czech RepublicTelephone/Fax: 420 386 361 231

e-mail: nedbal@greentech.cz

GovindjeeDepartment of Plant Biology

University of Illinois at Urbana-Champaign265 Morrill Hall, 505 South Goodwin Avenue

Urbana, IL 61801-3707, USATelephone: 1 217 337 0627

Fax: 1 217 244 7246e-mail: gov@illinois.edu

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The Editors

Agu Laisk, born in 1938, obtained BS and MSdegrees in Physics at the University of Tartu(Estonia) in 1961. He then joined the researchgroup of Juhan Ross to study the penetrationof sunlight into plant canopies for the purposeof modeling of plant productivity. His “candidateof science” work (equivalent to Ph.D., in the for-mer Soviet Union), on the ‘statistical distributionof light in the canopy’, was completed in 1966.Since then he became interested in mechanismsthat determine the rate of photosynthesis of aleaf. Together with his former student Vello Oja,he observed that in photosynthesis O2 competeswith CO2 for one and the same acceptor and in1970 published a mathematical model of pho-tosynthesis and photorespiration, based on thecompetition of CO2 and O2 for ribulosebispho-sphate (RuBP). Then he observed that at highCO2 concentrations, O2 enhances photosynthe-sis, showing the importance of the Mehler reac-tion. Soon thereafter, sophisticated experimentson “flashing” a leaf with short pulses of CO2showed that photosynthesis is limited by Rubiscoat low CO2, but by RuBP regeneration at highCO2 levels. For these findings, the degree of Doc-tor of Science in Biology was awarded to him in1976 by the Timiryazev Institute of Plant Phys-iology in Moscow (published as a monograph“Kinetics of Photosynthesis and Photorespirationin C3 Plants” by “Nauka”, Moscow, 1977). The

specific approach of Laisk’s group is in usingonly intact leaves as objects for measurements.This requires original equipment to be built inthe laboratory – now appreciated in several otherlaboratories and, in principle, described in a book(together with Vello Oja) “Dynamics of Leaf Pho-tosynthesis. Rapid-Response Measurements andtheir Interpretations”, edited by Barry Osmond(CSIRO, Australia, 1998). A recent unexpectedresult from Laisk’s laboratory is that cyclic elec-tron transport around Photosystem I is muchfaster than necessary to cover the possible deficitin ATP synthesis – indicating that cyclic elec-tron flow may be largely uncoupled from pro-ton translocation or there must be a controllableproton leak. The interpretation of such kineticexperiments is unthinkable without the applica-tion of mathematical modeling. Agu Laisk is aFellow Member of Estonian Academy of Sci-ence, life-time corresponding member of TheAmerican Society of Plant Biologists (ASPB), amember of the editorial board of PhotosynthesisResearch and of Photosynthetica. He has receivedNational Science Awards from the Estonian Gov-ernment. His international collaborators, whohave deeply influenced his views, include: UlrichHeber (Germany), David Walker (UK), BarryOsmond (Australia), Gerry Edwards (USA) andRichard Peterson (USA). At Tartu University, heteaches Bioenergetics.

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Ladislav Nedbal, born in 1955, studied Bio-physics at the Faculty of Mathematics andPhysics, Charles University in Praha, CzechRepublic. He graduated in 1981 with a thesison the ‘theory of the excitonic energy trans-fer in molecular crystals’. He learned about thefascinating process of photosynthesis from IvanŠetlík, who is one of the founders of algalbiotechnology. He moved over from doing model-ing of energy transfer to research in experimentalphotosynthesis in the early years of his scientificcareer; this led to his present interest in modelingphotosynthesis. Yet, preceding the present déjà vuwith mathematical models were many more yearsof apprenticeship in experimental science thatwere marked with discreet advice from Govind-jee. It was the present Series Editor of Advancesin Photosynthesis and Respiration, who taughthim the principles of technical writing in the late1980s and introduced him, in 1990, to John Whit-marsh of the University of Illinois at Urbana-Champaign, USA. It was in John‘s lab whereNedbal discovered the photoprotective role ofcytochrome b559. His other important tutors wereTjeerd Schaafsma in Wageningen, The Nether-lands, and Anne-Lise Etienne in France. A sig-nificant inspiration came from David Kramer dur-ing the postdoc years in Urbana-Champaign andin Paris, where they collaborated in constructing

a modulated light spectrophotometer and fluo-rometer. In that project he met Martin Trtilek,with whom he founded Photon Systems Instru-ments (PSI), a small company that has createda number of innovative instruments for photo-synthesis research. The most important achieve-ment was the development of the first commercialPulse Amplitude Modulating (PAM) type imag-ing fluorometer – FluorCam. Recently, collabo-ration with Martin resulted in the construction of‘intelligent’ photobioreactor for the cultivation ofalgae and cyanobacteria. The instrument collects,in real time, detailed information on the culture’sphotochemical yields and on its growth dynam-ics. The combination of mathematical modelingwith experimental research in photosynthesis andengineering approaches logically led to anotherdéjà vu in his career, this time with algal biotech-nology. In this area, mathematical models bringto light yet unexplored pathways towards com-mercially viable use of algae and cyanobacte-ria. Further stimulating his interest in modelsare the mysterious dynamic features that he andhis co-workers, including both his co-Editors ofthe present volume Agu Laisk and Govindjee,recently discovered in harmonically modulatedlight. Understanding plant behavior in dynamiclight remains a major challenge that will be tack-led by the current book Photosynthesis in silico.

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Govindjee, born in 1932, obtained his B.Sc.(Chemistry, Biology) and M.Sc. (Botany) in 1952and 1954, from the University of Allahabad,India, and his Ph.D. (Biophysics) in 1960, fromthe University of Illinois at Urbana-Champaign(UIUC), IL, USA. His mentors were RobertEmerson and Eugene Rabinowitch. He is bestknown for his research on the excitation energytransfer, light emission, the primary photochem-istry and the electron transfer in PhotosystemII (PS II). His research, with many collabo-rators, has included the discovery of a short-wavelength form of chlorophyll (Chl) a func-tioning in the Chl b-containing system of PS II;of the two-light effects in Chl a fluorescenceand in NADP reduction in chloroplasts (EmersonEnhancement); the basic relationships betweenChl a fluorescence and photosynthetic reactions;the unique role of bicarbonate at the acceptorside of PS II. He provided the theory of thermo-luminescence in plants, made the first picosec-ond measurement on the primary photochem-istry of PS II and used Fluorescence LifetimeImaging Microscopy (FLIM) of Chl a fluores-cence in understanding photoprotection againstexcess light. His current focus is on the historyof photosynthesis research, photosynthesis edu-cation, and possible existence of extraterrestriallife. He has served on the faculty of UIUC forabout 40 years. Since 1999 he has been ProfessorEmeritus of Biochemistry, Biophysics and PlantBiology at the same institution. He is coauthorof ‘Photosynthesis’ (with E. Rabinowitch; JohnWiley, 1969), and editor of several books includ-ing Bioenergetics of Photosynthesis (Academic

Press, 1975); Photosynthesis, Volumes I and II(Academic Press, 1982); Light Emission of Plantsand Bacteria (with J. Amesz and D.C. Fork;Academic Press, 1986); Chlorophyll a Fluores-cence: A Signature of Photosynthesis (with G.C.Papageorgiou, Springer, 2004); and Discoveriesin Photosynthesis (with J.T. Beatty, H. Gest andJ.F. Allen; Springer, 2005). His honors include:Fellow of the American Association of Advance-ment of Science; Distinguished Lecturer of theSchool of Life Sciences, UIUC; Fellow and Life-time member of the National Academy of Sci-ences (India); President of the American Societyfor Photobiology (1980–1981); Fulbright Scholarand Fulbright Senior Lecturer; Honorary Pres-ident of the 2004 International PhotosynthesisCongress (Montréal, Canada); the 2006 Recipi-ent of the Lifetime Achievement Award from theRebeiz Foundation for Basic Biology; the 2007Recipient of the Communication Award of theInternational Society of Photosynthesis Research(ISPR); and the 2008 Liberal Arts and SciencesAlumni Achievement Award of the University ofIllinois. During 2007, Photosynthesis Researchcelebrated Govindjee’s 50 years in Photosynthe-sis, and his 75th birthday through a two-Partspecial volume of the journal (Julian Eaton-Rye,editor). To celebrate his life-long achievement inPhotosynthesis Research, Education, and its His-tory, University of Indore, India, recently helda 3-day International Symposium (Nov. 27–29,2008) on ‘Photosynthesis in Global Perspective’(K.N. Guruprasad, Convener).

Govindjee has trained more than 20 Ph.D. stu-dents and about 10 postdoctoral associates.

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Author Index

Anten, Niels P.R. 363–399

Behrenfeld, Michael J. 465–497Bernacchi, Carl. J. 231–246Berry, Joseph 209–230

Cervený, Jan 17–29

Dekker, Jan P. 33–53

Edwards, Gerald 323–348Eichelmann, Hillar 295–322

Farazdaghi, Hadi 275–294Farquhar, Graham 209–230, 231–246Freiberg, Arvi 55–82Friend, Andrew D. 465–497

Geider, Richard J. 465–497

Harbinson, Jeremy 247–273Hasenauer, Hubert 441–464Hucka, Michael 3–15

Küppers, Manfred 417–440

Laisk, Agu 295–322, 323–348Lavergne, Jérôme 177–205Lazár, Dušan 85–123Long, Stephen P. 231–246, 401–416

Nedbal, Ladislav 17–29Niinemets, Ülo 363–399Novoderezhkin, Vladimir I. 33–53

Oja, Vello 295–322

Pfiz, Michael 417–440Pietsch, Stephan A. 441–464Pimentel, Carlos 231–246Prášil, Ondrej 125–149

Riznichenko, Galina 151–176Rosenthal, David M. 231–246Rubin, Andrew 151–176

Schaff, James 3–15Schansker, Gert 85–123Schmidt, Henning 17–29Still, Chrisostopher J. 465–497Struik, Paul C. 247–273

Trinkunas, Gediminas 55–82

Van Grondelle, Rienk 33–53Von Caemmerer, Susanne 209–230Vredenberg, Wim 125–149

Woodrow, Ian E. 349–360

Yin, Xinyou 247–273

Zhu, Xin-Guang 401–416

xxi

Color Plates

F(t)/F0 = 1+p+rFv∗(1–k1/(k1–kL)∗exp(–kL∗t)+kL/(k1–kL)∗exp(–k1∗t))∗((1–beta)∗kL/(kL+kAB1)+beta∗(1+(1–k1/(k1–kL)∗exp(–kL∗t)+kL/(k1–kL)∗exp(–k1∗t))∗exp(–k2AB∗t)))+rFv∗(1–exp(–k2∗t))+IP∗(1–exp(–kIP∗t)∗(1+kIP∗t)) [t in ms]

Fig. 1. Display of the curve fitting procedure, using global optimization simulation annealing (GOSA) with equation derivedafter summation of Eqs. (6.9–6.11) (bottom line). Symbols are experimental points, line is the simulated curve. Note that the fitwas obtained after an about 4 min iteration time. See Chapter 6, p. 139

CP1

Ochroma lagopus

March 1996 October 1996

October 1996

March 1997

1 m

March 1997March 1996

Time of investigation

Tree height [m]

Total leaf area [m2] (gain/ loss)

Total leaf biomass [g] (gain/ loss)

Supporting tissue [g] (gain/ loss)

Aboveground biomass [g] (gain/ loss)

Total carbon gain

Carbon allocation to supporting tissue

Carbon allocation to leaves

Resulting carbon allocation to roots

2.79

2.21

185.5

374

560

via abovegroundbiomass monitoring

3561 g

1359 g

2202 g

4.54

6.39 (9.46/5.28)

537 (794/443)

1267 (1075/182)

1804 (1869/625)

380 d

via ‘steady-state’ model

6393 g

35%

21%

2832 g (44%) 975 g (21%)

4.89

3.56 (6.70/9.54)

299 (564/802)

2028 (1127/366)

2327 (1691/1168)

4536 g

30%

49%

via ‘dynamic’ model

a

b

c

d

Fig. 2. Development of an individual of the shade-intolerant pioneer Ochroma lagopus from an open site and deduction of itsannual carbon allocation. Light green leaf area: sun exposed, dark green: (self-)shaded (from Timm et al., 2004). (a) Above-ground architectural development as reconstructed via the method described in Fig. 18.1; (b) change in the individual’s lightenvironment as indicated by hemispherical photography immediately above its uppermost leaves; (c) growth and biomassparameters of the respective individual; (d) deduction of annual assimilate flux balances (carbon allocation) as percentageof total annual crown carbon gain, either via a steady-state or a dynamic photosynthesis model. Carbon gain and allocation ofbiomass are given in equivalents of dry matter (CH2O)n. See Chapter 18, p. 423

CP2

Billia colombiana

March 1996 October 1996

October 1996

March 1997

1 m

March 1997March 1996

Time of investigation

Tree height [m]

Total leaf area [m2] (gain/ loss)

Total leaf biomass [g] (gain/ loss)

Supporting tissue [g] (gain/ loss)

Aboveground biomass [g] (gain/ loss)

Total carbon gain

Carbon allocation to supporting tissue

Carbon allocation to leaves

Resulting carbon allocation to roots

2.1

0.42

27.6

58.7

86.3

via abovegroundbiomass monitoring

64.9 g

19.1 g

45.8 g

2.26

0.581 (0.204/0.045)

38 (13.3/2.9)

90.0 (32.1/0.76)

128.0 (45.5/3.7)

380 d

via ‘steady-state’ model

194.1 g

24%

10%

129.2 g (66%) 16.9 g (21%)

2.45

0.632 (0.089/0.038)

41.3 (5.8/2.5)

103.0 (13.7/0.68)

144.3 (19.5/3.2)

81.8 g

23%

56%

via ‘dynamic’ model

a

b

c

d

Fig. 3. The same as Fig. 18.4, but for an individual of the mid- to late-successional shade-tolerant Billia colombiana below aclosed canopy. Red leaf area: newly developed (from Timm et al., 2004). See Chapter 18, p. 424

CP3

1 m

71–85

25–39

>67>63>59>55>51>47>43

>39

Daily carbon gain mmol m–2 d– –1

Fig. 4. Daily carbon balance of each individual leaf in the crown of a Salacia petenensis plant. Crown carbon gain wasdetermined by summing up the individual balances. In the mean over 380 days carbon gain amounted to 426 mg day−1 (fromTimm et al., 2004). See Chapter 18, p. 432

CP4

Fig. 5. Modeled pools and fluxes for the virgin forest reserve Rothwald using model parameters for Common beech forests.Upper graph: Comparison of the temporal development of modeled soil, necromass, stem and total ecosystem carbon content for600 simulation years at landscape level steady state. Lower graph: Corresponding annual C fluxes from heterotrophic respiration(Rh), net primary production (NPP) and net ecosystem exchange (NEE). I – optimum phase; II – breakdown/regeneration phase;III – juvenescence (Pietsch and Hasenauer, 2006). See Chapter 19, p. 457

Fig. 6. Attractor of modeled NEE for the successional cycle evident within the virgin forest reserve Rothwald. a: NEE-Attractorfor the virgin forest successional cycle reconstructed from model results using site and climate conditions of 18 research plots.b: Attractor reconstructed for one single plot and one successional cycle. Arrows indicate the trends of model behavior duringdifferent phases of the successional cycle. (S.A. Pietsch, unpublished) See Chapter 19, p. 460

CP5

Net Primary Productivity (kg Cm−2 yr−1)

0 0.03 0.1 0.3 0.5 0.8 1.0 1.5

Fig. 7. Mean annual net primary productivity (NPP) simulated by Hybrid6.5 (land) and the CbPM (ocean) for the period 2000–2007. Total mean annual NPP is 107.3 Pg C year−1, with 51.1% coming from land and 48.9% from the oceans. Land pixelssimulated with 1/4

◦ resolution and ocean pixels with 1/12◦ resolution. Land leaf area dynamics prescribed from MODIS satellite

retrievals, ocean production calculated using data from the SeaWiFS instrument. Full simulation details are given in the text.See Chapter 20, p. 486

CP6