REVIEW Monitoring of CO2 exchange and carbon pools in vegetation and soil

REVIEW

Monitoring of CO2 exchange and carbon pools in vegetationand soil

Rakesh Pandey • Vijay Paul • Vinay Kumar Sehgal •

Madan Pal Singh • Kalikinkar Bandyopadhyay

Received: 3 July 2012 / Accepted: 12 March 2013 / Published online: 6 August 2013

� Indian Society for Plant Physiology 2013

Abstract Global efforts to reduce the emissions require

proper monitoring and understanding of the carbon inputs

and outputs by the terrestrial ecosystems i.e. vegetation and

soil. Photosynthesis and net primary productivity can be

used as indicators of carbon exchange and their estimate

can be made through traditional approaches as well as other

approaches e.g. mechanistic photosynthesis models and the

light use efficiency with satellite data. Advancements have

taken place for monitoring the CO2 exchange at different

scales viz. leaf, stand-, landscape levels, vertical carbon

column- and satellite observations. There are methods to

partition the fluxes based on discrimination of isotopes of

carbon by terrestrial ecosystem processes. The soil is a vast

reservoir of carbon and has a great potential for atmo-

spheric carbon sequestration. Monitoring of carbon and

fluxes in soil is therefore an essential aspect in the era of

changing climate. The root systems are monitored mostly

in a destructive manner but many non-destructive methods

have also been devised. Similarly, soil carbon estimation

with traditional chemical method can be replaced by

reflectance spectroscopy for rapid and large area estima-

tions. Measurement of soil respiration and its partitioning

also helps in verifying the capacity of soil as a net source or

net sink. Monitoring of the pools and fluxes therefore uses

multi-technique and -disciplinary approaches. Uncertain-

ties in the estimates occur due to the multi-factorial effects

and have implications on carbon trading. Therefore more

effective monitoring and reduction of the uncertainties is

needed.

Keywords Carbon cycle � Carbon sequestration �Carbon trading � Climate change � Eddy covariance �Net primary productivity � Photosynthesis �Respiration � Soil organic carbon � Satellite remote

sensing

Introduction

The increase in greenhouse gases (GHGs) is primarily

responsible for the recent global warming (Henderson-

Sellers 2012). Therefore the goal of reducing the emissions

as mandated by different international agencies (e.g. IPCC)

is now on global priority. Special mechanisms for emission

reduction under Kyoto Protocol include joint implementa-

tion, clean development mechanism and emission trading.

Besides this, nations need to maintain and update the GHG

emission inventories and category on land use change and

forestry. Among these GHGs, the atmospheric CO2

accounts for about 60 % of global warming potential and

by 2050 its level will increase to nearly 450 lmol mol-1

(Karl et al. 2009; IPCC report 2007). However, monitoring

of GHGs is still inadequate in terms of number of sites,

large geographic gaps or spatial resolution (Manning 2011)

and requires a multi-technique approach Canadell et al.

(2000). Moreover, the response of global carbon cycle to

climate change is one of the greatest sources of uncertainty

(Balantyne et al. 2012). Houghton (2005) also mentioned

that estimation of components of the global carbon cycle is

still not accurate. Durant et al. (2011) have emphasized the

need for enhancement of measurement infrastructure to

reduce uncertainty in global carbon balance and estimated

R. Pandey (&) � V. Paul � M. P. Singh

Division of Plant Physiology, Indian Agricultural Research

Institute, New Delhi 110012, India

e-mail: [email protected]

V. K. Sehgal � K. Bandyopadhyay

Division of Agricultural Physics, Indian Agricultural Research

Institute, New Delhi 110012, India

123

Ind J Plant Physiol. (April–June 2013) 18(2):98–117

DOI 10.1007/s40502-013-0016-0

that even 5 % of unreported emissions can cost US$20

billion each year by 2050. Therefore, monitoring of global

carbon exchange processes and the dynamics of carbon

pools has immense importance for determining how global

environment is changing, what drives these changes, its

potential impacts and for developing sound policy deci-

sions on mitigation and adaptation strategies.

As plant researchers, mostly our thinking in relation to

measurements of photosynthesis and carbon accumulation

visualizes the spatial level of leaf and plant only. But to

understand the ecosystem responses, the isolated plant

studies will not yield proper understanding. It is not a simple

and routine task. The need is to take an integrated approach

of plant community, soil processes and the climatic factors

which constitute key components of land ecosystems. The

objective of the present review is therefore to highlight the

monitoring approaches for the CO2 fluxes and the carbon

pools in vegetation and soil and how they affect global car-

bon cycle. The review therefore includes various processes

and components of the carbon cycle at different scales viz.

photosynthesis, respiration, growth of aboveground parts,

root growth, net primary productivity (NPP), vegetation

responses to elevated CO2, soil carbon dynamics, partition-

ing of the fluxes and their interactions. These aspects have

been highlighted for a better understanding about the com-

plexities and uncertainties in monitoring, role of monitoring

in providing accuracy in carbon cycle and how carbon cycle

is affected by climate change and how it affects the regional

and global climate. This will provide a holistic understand-

ing of the role of vegetation and soils under changing cli-

mate. It will therefore be useful for plant-, crop scientists,

environmentalists, climatologists, modelers, planners and

ecosystem managers.

Sources and sinks of carbon and the carbon cycle

The earth’s land, atmosphere, ocean human spheres can be

integrated in a global carbon cycle (Fig. 1) in which the

carbon pools are linked with the exchange of CO2 gas. When

photosynthesis is greater than respiration and fossil fuel

combustion, the land biosphere serves as a sink for carbon

whereas when the carbon losses are greater than photosyn-

thesis the land acts as a carbon source. The source and sinks

of carbon have changed over the past 200 years (Schimel

2004). About 295 GtC has been released from land out of

which 265 GtC is due to fossil fuel emission and 30 GtC is

due to land use change. It has been captured by the atmo-

sphere (180 GtC) and oceans (115 GtC). The sinks of carbon

associated with carbon cycle consist of atmospheric

absorption of 4.3 ± 0.1 PgC year-1, land 2.6 ± 0.8 PgC

year-1 and ocean 2.5 ± 0.5 PgC year-1 (Fig. 1) as per the

decadal average 2002-2011 given by Le Quere et al. (2013)

(1 Pg = 1015 g = 1 Gt = 1 billion metric tonnes; where Pg

refers to Petagram and Gt refers to Gigaton). Thus about half

(45 %) of the total emissions are being absorbed by atmo-

sphere, 26 % by ocean and about 29 % by land ecosystems

(Le Quere et al. 2009). A strong terrestrial carbon sink was

found in the temperate latitudes of the Northern Hemisphere

in 1992 and 1993, the magnitude of which is roughly half of

the global fossil fuel emission of those years (Ciais et al.

1995). Sabine et al. (2004) estimated an annual accumulation

of 0.2–1.4 Pg carbon in the terrestrial biosphere which has

slowed down the rate of rise in the atmospheric CO2.

The source of carbon consists of 8.3 ± 0.4 PgC year-1

from fossil fuel combustion and cement manufacture and 1.0

± 0.5 PgC year-1 from deforestation, biomass burning and

soil cultivation (based on decadal average 2002–2011 values

taken from Le Quere et al. (2013)). Globally, soil contain

approximately 1,500 Pg of organic carbon (Batjes 1996),

which is roughly three times the amount of carbon in vege-

tation and twice the amount in the atmosphere. It is the

largest source of CO2 from terrestrial ecosystems to the

atmosphere (IPCC 2001). However, the soils can act as sinks

if carbon sequestration can be done into long-lived pools of

carbon (Bhattacharyya et al. 2012). Soil carbon sequestration

is defined as the net removal of CO2 from the atmosphere into

long-lived pools of carbon in soil. Besides removing atmo-

spheric CO2 it helps in improving productivity, soil health

and quality of environment and therefore carbon sequestra-

tion is a ‘win–win’ strategy (Lal 2001). The world soils have

a potential of carbon sequestration of 0.4–1.2 GtC year-1.

The potential of C sequestration for cropland soil is 0.4–0.8

GtC year-1, range- and grasslands 0.01–0.03 GtC year-1,

irrigated soil 0.01–0.03 GtC year-1, degraded and deserti-

fied soil 0.2–0.4 Gt year-1 and overall world soil has a car-

bon sequestration potential of 0.4–1.2 GtC year-1 (Lal

2004a, b). For agricultural lands, West et al. (2010) made a

global comparative analysis of carbon stock versus crop

yields and showed that for each unit of land cleared, the

tropics lose nearly two times as much carbon (*120

vs. *63 t ha-1) and produce less than one-half the annual

crop yield compared with temperate regions (1.71 vs. 3.84 t

ha-1 year-1).

Monitoring of the global atmospheric CO2 and carbon

cycle

The Keeling curve

The ‘Keeling curve’ has become a standard icon and evi-

dence of the impact of humankind on the global atmosphere.

This time-series CO2 record of atmosphere (Fig. 2) is a result

of sustained work initiated by Dr. Charles David Keeling

(1928–2005) at Mauna Loa Observatory (USA) since 1957.

Ind J Plant Physiol. (April–June 2013) 18(2):98–117 99

123

Within a year, Dr. Keeling realized a regular seasonal cycle

in atmospheric CO2 due to absorption of CO2 from air during

summer by growing vegetation and release of CO2 into air in

the succeeding winter season. Further work showed a long

term increase in the CO2 concentration (Bolin and Keeling

1963). Based on these studies and the composition of carbon

isotopes, a model of global carbon cycle was given (Ekdahl

and Keeling 1973; Bacastow and Keeling 1973). In fact,

monitoring of CO2 by Dr. Charles David Keeling has been

acknowledged by Dr. Charles Kennel, former Scripps

Director, as ‘‘the single most important environmental data

set taken in the 20th century…’’

The air sampling network and Carbon Tracker

Currently more than 50 GHGs and isotopes are being mea-

sured through a vast network of cooperative sites around the

globe. This is coordinated through the carbon cycle GHGs

group at the Earth System Research Lab (ESRL) in Boulder,

Colorado, USA. It includes the continuous observations by

observatories, weekly gas sampling in glass flasks, aircraft

sampling and tower measurements. Presently, motoring of

the carbon cycle in substantial detail is also being done by a

new data assimilation system called Carbon Tracker built by

(National Oceanic and Atmospheric Administration) NOAA

ESRL. Based on the Carbon Tracker, Peters et al. (2007)

estimated the weekly net CO2 exchange between the ter-

restrial biosphere and the atmosphere from 2000 to 2005.

They concluded that such initiatives are helpful in precisely

finding the sink capacity and the sensitivity of the sink to

climate extremes and to evaluate the effectiveness of efforts

to reduce or store carbon emissions.

The global carbon project

The Global Carbon Project (GCP) was established in 2001

to study the carbon cycle of earth and to develop

Fig. 1 The global carbon cycle

showing different carbon pools

and fluxes. The size of pools

(Pg) is represented from Lal

(2008). The changes in net

source or sink levels (PgC

year-1) in different pools

represent decadal average

values (2002–2011) with

uncertainties reported as ±1

sigma (68 % confidence that the

real value lies within the given

interval) as in Le Quere et al.

(2013)

Fig. 2 Full record of atmospheric CO2 at Mauna Loa Observatory—

‘‘The Keeling Curve’’ (source http://www.esrl.noaa.gov/gmd/ccgg/

trends/ and reference: Dr. Pieter Tans, NOAA/ESRL, www.esrl.noaa.

gov/gmd/ccgg/trends/ and Dr. Ralph Keeling, Scripps Institution of

Oceanography, scrippsco2.ucsd.edu/) (with permission from Dr. Pieter

Tans)

100 Ind J Plant Physiol. (April–June 2013) 18(2):98–117

123

http://www.esrl.noaa.gov/gmd/ccgg/trends/




understanding of its patterns and variability, study of pro-

cesses and interactions and approaches for carbon man-

agement. It also provides the annual updates of the

estimates of the global carbon budgets.

Components of ecosystem carbon cycling and their

estimation

The fundamental model of ecosystem carbon cycling

(Woodwell and Whittaker 1968) embedded in the models

of global carbon cycle is as follows:

NEE or NEP ¼ NPP� Rh: ð1Þ

Alternatively,

NEE or NEP ¼ P� Rmd� Ra� Rh: ð2Þ

GPP is the gross primary production (equivalent to

P - Rmd), P is the photosynthesis, Rmd is the leaf mainte-

nance respiration during day time and is a function of leaf

nitrogen concentration (Ryan 1991), NPP is the net primary

production, Ra is the autotrophic respiration, NEE is the net

ecosystem exchange, NEP is the net ecosystem production

and Rh is the heterotrophic respiration. If Ra \ NPP then

ecosystem acts as carbon sink and if Rh [ NPP then it acts as

net C source (Pietsch and Hasenauer 2009). Part of the car-

bon store of NEP is also lost and the final stored carbon is

termed the net biome production. This is the difference

between the amount of carbon fixed by photosynthetic

assimilation and the amount lost by the oxidation or removal

of plant material by all routes. The NEP of three major

regions of earth is as follows, 0.8 GtC year-1 for North

America, 1.7 GtC year-1 for Eurasia and 0.4 GtC year-1 for

the tropics (Schimel et al. 2001).

On an average, about 80 % of GPP is released to the

atmosphere through respiration (Law et al. 2000), of

which CO2 released from the soil is a substantial part.

Therefore, respiration may be more important than pho-

tosynthesis in relation to the interannual variability in

NEP (Valentini et al. 2000). Soil respiration can be further

divided into different components (Fig. 3) viz. root res-

piration, rhizomicrobial respiration, decomposition of

plant residues, the priming effect induced by root exuda-

tion or by addition of plant residues and basal respiration

by microbial decomposition of soil organic matter (SOM).

Evidences indicate that canopy photosynthesis influences

soil respiration (Kuzyakov and Gavrichkova 2010) and its

speed is based on phloem transport (Mencuccini and

Holtta 2010). Chapin III et al. (2009) emphasized a close

coupling between NPP and heterotrophic respiration (Rh)

because NPP constrains the food available to heterotrophs.

Nearly 40 % of the net fixed carbon is allocated below-

ground (Jones et al. 2009). Of the belowground partitioned

carbon, 50 % resides in root biomass, 33 % is used for res-

piration and 12 % is recorded as soil residues. Jackson et al.

(1997) highlighted the role of fine roots and estimated that

global fine root carbon constitutes about 5 % of all carbon in

the atmosphere and represents about 33 % of global annual

NPP. The root turnover represents annual root production

divided by maximum standing root biomass expressed on per

year basis. A compilation of root turnover across different

climates and vegetation types based on sequential root bio-

mass estimates was overviewed by Gill and Jackson (2000).

Some values of root turnover are as follows—whole tree root

systems (0.10/year), shrublands (0.34/year), fine root system

in grasslands, wet lands or forests (0.53–0.56/year) and fine

root in tropical vegetation (0.6–0.9/year).

Leith and Wittaker (1975) estimated global NPP based

on temperature data and actual evapotranspiration. The

direct estimation of NPP is a time consuming and

labour-intensive process. It also requires the information

on accumulation and turnover of carbon pools in bio-

mass, leaves, shoots, roots, exudates, volatile organic

compounds over a period of time. In reality, estimation

of all these is seldom done and therefore the accuracy of

NPP assessments have been questioned (Geider et al.

2001). The NPP and annual carbon inputs to agro eco-

system estimated by Bolinder et al. (2007) used a series

of plant carbon allocation coefficients for each crop type,

shoot to root ratios and yields. From these, the below-

ground net primary production can be estimated. Johnson

et al. (2006) suggested estimation of source carbon from

crop residues, root studies, rhizodeposits and crop yields.

The NPP and NEP can be estimated through photosyn-

thesis models (Fig. 4) based on the bottom-up and the top-

down approach. In the bottom-up approach the rate of

photosynthesis in plants can be mechanistically calculated

using enzyme kinetics, leaf temperature, absorbed radiation

and photosynthetic electron transport rate according to

different models (Farquhar et al. 1980; DePury and Far-

quhar 1997; Laisk and Edwards 2000). In the top-down

approach, the light use efficiency (LUE) concept originally

given by Monteith (1972) is used and it states that the

photosynthetic production is a function of the absorbed

PAR (APAR) and the efficiency. Integration of the

instantaneous rate of photosynthesis over time (typically a

growing season) and space (typically canopies, stands or

regions) can be expressed as primary productivity or NPP.

The LUE model can be readily applied at several temporal

and spatial scales and can be linked to remote sensing.

Now the remote sensing has become an essential tool for

estimation of photosynthesis and NPP (Gamon et al. 2007).

Both PAR and FAPAR can be determined from remote

sensing (Gamon et al. 2007). The LUE, e, may be a fixed

coefficient or a variable depending upon the environmental

conditions particularly moisture and temperature. For


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example, in the widely used CASA carbon cycle model,

LUE is estimated as a function of theoretical universal

LUE, temperature and water regime (Friend et al. 2009).

The limited spatial coverage of ground based C flux mea-

surements can be overcome through use of remote sensing.

However, GPP cannot be directly estimated from the

remote sensing measurements but estimated from LAI and

fraction of APAR or through the greenness indices like

NDVI. Some satellite based observations to monitor the

photosynthesis and primary productivity are as follows:

(i) Advanced very high resolution radiometer sensor was

used for making 1-km resolution global land-cover

database (Belward 1996).

(ii) Moderate resolution imaging spectroradiometer sen-

sor is hyperspectral in nature (36 bands). It gives

land-cover: 96 day, vegetation indices: 16 day, LAI/

FPAR: 8 day, GPP: 1 day, NPP: 1 year and helps in

estimation of growing season.

(iii) Synthetic aperture radar can above ground biomass

based on microwaves (Kasischke et al. 1997).

(iv) Light detection and ranging sensors give measure-

ments about the three-dimensional distribution of

plant canopies, subcanopy topography, high-resolu-

tion topographic maps, vegetation height and canopy

structure (Lefsky et al. 2002).

(v) The raw fluorescence (from GOSAT) is linearly related

to GPP at global scale (Frankenberg et al. 2011).

(vi) Satellites with hyperspectral bands can be used to

estimate ecosystem CO2 uptake and gross primary

productivity (Penuelas et al. 2011).

Measuring CO2 fluxes at different scales

Leaf enclosure methods

The leaf enclosure methods (Fig. 5) include the portable

photosynthesis systems which basically consist of the

infrared gas analyzers (IRGAs) for measuring CO2/H2O

concentration, air flow pumps, flow control devices and

leaf cuvette for monitoring the leaf gas exchange. The

IRGAs are based on the principle that heteroatomic mol-

ecules (like CO2 and H2O) absorb infrared (IR) radiation

and this absorption obeys Lambert–Beer’s law. The major

IR absorption band used for CO2 and H2O detection are

4.25 and 2.7 lm, respectively. They can be used for eco-

logical survey measurements and give a snapshot of

parameters at leaf level for photosynthesis, transpiration,

stomatal conductance, etc. The present systems have open

type IRGAs and have greater flexibility. Many advanced

features and attachments for control of light, CO2,

humidity and temperature have been provided in the recent

portable photosynthesis systems so that differences in gas

exchange parameters can be measured without confound-

ing effects of fluctuating environmental variables. The

fluorescence parameters, which indicate the physiological

state of plant photosynthesis, can also be taken on the same

leaf while taking photosynthesis in the present instruments

with more advanced features.

Micrometeorological methods: eddy covariance method

The eddy covariance method (Fig. 5) is a micrometeoro-

logical technique that allows non-invasive measurement of

net CO2 exchange (CO2 assimilation and the respiratory

losses) between the atmosphere and the terrestrial ecosys-

tems (Baldocchi et al. 1988; Burba and Anderson 2005).

This quantification over a whole canopy could become

possible due to breakthrough of technologies developed by

micrometeorologists (Swinbank 1951). The eddy covari-

ance method is based on the air flow from a vegetation

which consists of flow of numerous rotating eddies, i.e.,

turbulent vortices of various sizes with horizontal and

vertical components. In a typical setup, the sensors are

mounted on a tower and include rapidly responding CO2/

H2O open path analyzers and sonic anemometers for

Total Photosynthesis 100

Shoot C (50)

Shoot respiration (25)

Root C (13)

Rhizodeposition (3) Root respiration (4.3)Rhizomicrobial respiration (4.7)

Respiration of dead plant material

SOM derived CO2

Total Soil Respiration

75-95% of the total soil respiration in wheat is contributed by root/rhizosphere

Root derived CO2

Fig. 3 Carbon flow to

rhizosphere and its utilization

for root biomass,

rhizodeposition, root respiration

and rhizomicrobial respiration

in wheat (data based on

Kuzyakov 2006; Swinnen 1994)


123

measuring the CO2/H2O concentrations associated with

individual eddies of air and to measure the turbulent fluc-

tuations in the vertical wind velocity. The eddy flux towers

can measure stand fluxes of up to 1 km2. Internationally, a

network of eddy covariance sites has been named as

FLUXNET which helps to understand the responses of

NEE and its components to environment variables (Bal-

docchi et al. 2001). FLUXNET started formally in 1997

and now a network of more than 300 sites are there

worldwide in different regions and climatic zones which

help in the measurement of the fluxes of different vegeta-

tion stand types.

Alternatively, the eddy covariance measurement moni-

tors the breathing of the terrestrial biosphere and integra-

tion of continuous instantaneous net CO2 exchange

between the biosphere and the atmosphere over time can

give net ecosystem productivity (Baldocchi 2008). The

eddy covariance method can give more useful estimate of

the net ecosystem CO2 exchange (NEE) between the land

surface and the atmosphere provided other carbon addition

(e.g. lateral transports) or losses of the dissolved organic

carbon to the groundwater are properly credited. Based on

the global eddy covariance studies, Baldocchi (2008) have

summarized the key findings as follows: (1) greatest net

carbon uptake in ecosystems is not necessarily related to

the greatest canopy photosynthesis but to the longest

growing season, (2) disturbance leads to loss of carbon

from ecosystems, (3) many old-growth forests act as car-

bon sinks and (4) stresses decrease canopy photosynthesis

and respiration in tandem and this leads to differences

observed year to year in net annual exchange of CO2.

Tall towers

In contrast to the smaller size of eddy flux towers, very tall

towers of height more than 400 m (Fig. 5) are being used

for giving the carbon flux measurements at landscape level

(Bakwin et al. 1995).

The carbon column observations

The CO2 data of in situ measurements from the network

of surface sites may be difficult to interpret due to

atmospheric transport, mixing on diurnal and seasonal

NPP = LUE x APAR

Estimation of ecosystem photosynthesis

Bottom-up approach(Farquhar et al. 1980)

Top down approach (Monteith 1972)

Net

Pri

mar

y P

rodu

ctiv

ity

(NP

P)

Absorbed photosynthetically active Radiation (APAR)

NPP = LUE x APARΣ

APAR is derived from satellite observations

APAR = FAPAR x PAR

Variations in the LUE can be estimated asLUE = ε* x T x W

NPP = LUE x APAR

J

A

Rat

e of

CO

2A

ssim

ilati

on(A

, µ

mol

m-2

s-1)

P(CO2) in intercellular spaces

CO2 limited region

RuBP saturated

RuBP limited

PaPi

Rat

e of

ele

ctro

n tr

ansp

ort

(J,

µm

ol (

e )

m-2

s-1)

Γ

Net CO2 assimilation rate:

For CO2 limited and RuBP saturated phase, A(c)

A(c) = {Vcmax (Pi – Γ*) / (Pi + Km)} – Rday

For RuBP limited phase, A(j)

A(j) = {J(Pi – Γ*) / 4(Pi + 2Γ*)} – Rday

Scaling of net photosynthesis to canopy or larger area (NPP)

Estimation of net carbon accumulation of ecosystem= Net Photosynthesis – Soil Respiration

Fig. 4 Approaches for

estimation of ecosystem

photosynthesis and net carbon

assimilation. The symbols are as

follows: A net CO2 assimilation,

Rday day respiration, Vcmax rate

of CO2 assimilation at

saturating intercellular partial

pressure of CO2, Pi intercellular

partial pressure of CO2,

Km Michelis–Menten constant

for carboxylation reaction,

C CO2 compensation point,

C* CO2 compensation point in

the absence of day respiration,

J rate of electron transport,

A(c) rate of CO2 assimilation for

CO2 limited and RuBP saturated

phase, A(j) rate of CO2

assimilation for RuBP limited

phase, MJ APAR mega joule

absorbed photosynthetically

absorbed radiation, NPP net

primary productivity,

APAR absorbed PAR,

LUE light use efficiency

(measured as gC MJ APAR),

e* theoretical optimum LUE,

T temperature, W moisture


123

time scales, variations in surface pressure and atmospheric

water vapour and also proximity to local sources and sinks

of CO2. Therefore, measurements of vertical column-

averaged dry air mole fraction of CO2 and other GHGs are

useful. The column measurements can be taken from

reflected sun observations of the space-based sensors (e.g.

Orbiting Carbon Observatory). But their accuracy is

affected by aerosols, uncertainty in air mass variation and

variations in land surface properties. The other method-

ology is ground based network of Fourier Transform

Spectrometers (FTSs) which can retrieve precise column

abundance of CO2 and other GHGs from near-IR

absorption spectra. This ground based network was

established in 2004 and is called the Total Carbon Column

Observing Network. These can help in the primary vali-

dation of space based instruments (Wunch et al. 2011).

For proper validation, the column measurements need to

be precise enough to 0.1 % to detect the interhemispheric

flux difference of 1 GtC year-1 (Olsen and Randerson

2004).

Satellite-based measurements

The atmospheric IR sounder (AIRS) instrument orbiting

earth on NASAs satellite since 2002 gives daily CO2

concentrations with an accuracy of 2 ppmv. AIRS is a

hyperspectral IR instrument with IR channels ranging from

3.7 to 15.4 lm (Chahine et al. 2008). Similarly the GHGs

Observing SATellite ‘‘IBUKI’’ (GOSAT) satellite of Japan

(Japan Aerospace Exploration Agency) also measures the

total column concentration using IR FTS.

13CO2 discrimination studies for monitoring fossil fuel

emissions and sink partitioning

The two naturally occurring stable isotopes of carbon in air

are 12C (98.9 %) and 13C (1.1 %). Their composition

reveals information about the types of physical, chemical

and metabolic process during different carbon transfor-

mations (Craig 1957; Farquhar et al. 1989). Plant biomass

Flow of air

Enclosure methodse.g. Photosynthesis systemsLeaf / Soil measurements

Canopy photosynthesis,Ecosystem experiments (e.g. FACE)and Open Top Chambers (OTC)Canopy measurements

Eddy covariance methodEcosystem measurements

Tall towers and Carbon column observationsLandscape measurements

Earth observation satellites

And modelsRegional and global

measurements

Measuring CO2 exchange at increasing spatial scales

FACEOTC Local gas flask sampling

Aircraftsampling

Fig. 5 Summary of different methods for measuring CO2 exchange at different spatial scales i.e. from leaf to global level scales


123

shows lesser abundance of 13C as compared to atmosphere

and therefore carbon isotope discrimination occurs during

photosynthesis. Rubisco has higher ability to discriminate13CO2 (d or carbon isotope discrimination values of about

-27 %) as compared to C4 (-5.7 %) plant where the first

fixation of CO2 occours via PEP carboxylase enzyme. The

study of 13C has advantage that all the carbon pools of

plant are labeled, it is non intrusive method and there is

easy handling due to non-radioactivity. Studies on carbon

isotope composition of atmosphere and the ecosystem

carbon isotope discrimination were pioneered by Keeling

(1958, 1960, 1961). These studies revealed that during

daytime, the concentration of 12CO2 are reduced faster

compared to 13CO2 due to isotopic discrimination by

plants. This leads to enrichment of 13CO2 in air during

daytime and during night 12CO2 concentration of air is

increased. Also CO2 concentration and isotope composi-

tion in forest air undergo a regular daily cycle that reflects

the influence of photosynthesis, respiration and atmo-

spheric mixing. Based on this, estimate of the isotope

composition of the respired air can be made using a clas-

sical graphical approach now called as ‘Keeling Plot’. It

has become a standard tool in ecosystem physiology. The

isotopic composition in air is being monitored in the

NOAA/CMDL cooperative sampling network since 1991.

There is global d13CO2 observation network e.g. NOAA/

ESRL which helps in partitioning of the fluxes at finer

spatial and temporal scales (Balantyne et al. 2011).

The carbon isotope discrimination studies have also

provided evidence of the increased atmospheric CO2 due

to burning of fossil fuels. Study of Antarctic ice cores by

Francey et al. (1999) showed a rapid decline of d13C in

the modern era compared with the preindustrial area.

Also, Ciais et al. (1995) were able to locate a large

Northern Hemisphere terrestrial CO2 sink. Battle et al.

(2000) also observed general agreement of the variability

of global carbon sinks with atmospheric CO2 and d13C

values. Based on the studies it has also emerged that the

global flux weighted estimate of discrimination by ter-

restrial biosphere is highly sensitive to total annual pre-

cipitation amount and to a lesser extent to mean annual

temperature (Pataki et al. 2003). Carbon isotope discrim-

ination studies have also been used to partition the net

CO2 uptake between land and oceans. This is based on the

preferential uptake of 12C by the land relative to oceans.

The partitioning of sink activity on the earth surface into

terrestrial and oceanic components is because land dis-

criminates against 13C by about 18 % whereas uptake by

oceans discriminates by about only 2 %. However, earlier

studies have also indicated that temporal variations in

isotope discrimination may occur within a season and

between years in a given biome and this dynamics may

also need to be considered in the partitioning of

atmospheric CO2 between terrestrial biosphere and ocean

(Ciais et al. 1995; Flanagan et al. 1997).

Monitoring roots, soil organic carbon and soil CO2

partitioning

The knowledge of the root system is limited. The effects of

human activities on the belowground zone of earth’s

‘‘critical zone’’ have also not been well quantified (Richter

and Mobley 2009). The contribution of plant roots to soil

and atmospheric carbon is significant and difficult to sur-

vey accurately. The traditional methods are destructive,

labour intensive and limited by soil volume or surface area

to be assessed (Bohm 1979), however, several advances in

the root studies have lead to a better understanding of root

growth, architecture and behavior (Mancuso 2012). Some

methods for measuring root biomass, length, architecture

and functioning are as follows:

(i) Soil core sampling helps in measuring root length

density and surface area parameters.

(ii) Trench profile wall method helps in tracing root

distribution in the soil profile.

(iii) Minirhizotrons allow frequent root observation and

estimation of root production and root longevity.

(iv) High-throughput imaging systems can be used for

studying the root architecture (French et al. 2012).

(v) Ground penetrating radar or microwaves can be

used for estimating the root length, coarse woody

roots, biomass, root diameter and spatial distribution

of roots non-destructively (Hruska et al. 1999;

Butnor et al. 2001).

(vi) Electrical impedance spectroscopy is based on

correlation between electrical capacitance and resis-

tance of roots with root biomass and morphology

e.g., surface area (Repo et al. 2012).

(vii) Multi-electrode resistivity imaging is based on

relationships between root biomass and electrical

resistivity of soils. It helps in visualizing the

distribution of soil volumes with different root

densities rapidly and with minimum disturbance

(Amato et al. 2012).

The measurements of long term soil carbon stock

changes are important but it is difficult and requires

intensive sampling. Moreover it is also needed to gener-

alize the linking of the pool changes with environmental

changes. Several methods have been provided for assess-

ment of soil carbon and in situ soil carbon measurement

(Lal et al. 2001; Gehl and Rice 2007). Also, there is a need

of devising proper sampling strategy and replications for

monitoring carbon stocks in the soil profile (Kravchenko

and Robertson 2011). Some methods e.g. soil reflectance


123

spectra have potential to improve our understanding of soil

C dynamics at a scale of space and time not feasible before.

Some methods for measuring soil carbon are as follows:

(i) Wet chemical method for measuring the oxidizable

C (Walkley and Black 1934).

(ii) Dry combustion method (Nelson and Sommer 1982).

(iii) Laser induced breakdown spectroscopy (Ebinger

et al. 2003).

(iv) Soil reflectance spectra and remote sensing rapidly

and at low cost (Chen et al. 2000; Rourke and

Holden 2011).

(v) Inelastic neutron scattering (Wielopolski et al. 2000,

2003).

The sources of CO2 flux from soil and the partitioning

methods have been reviewed by Kuzyakov (2006). Pre-

diction of the soil respiration CO2 flux remains limited

because of multiple controlling mechanisms that interact

over different temporal and spatial scales (Vargas et al.

2011). Further, the fluxes do not reflect the turnover in the

total carbon pools because most of the fluxes originate

from small pools but having a very fast turnover (Kuzya-

kov 2011a, b). The total CO2 efflux of soil do not provide

sufficient information about the soil’s capacity as a net

source or net sink (Kuzyakov 2006) because not all of the

CO2 released from soil is soil-derived. Therefore, experi-

mentally separating soil respiration into autotrophic and

heterotrophic sources is an important challenge that the

current soil respiration research is facing (Kuzyakov and

Gavrichkova 2010). For example, Hogberg et al. (2001)

designed experiment in which the interruption of carbo-

hydrate supply to roots was done by stem-girdling of the

boreal pine forests. There was up to 37–50 % reduction in

the CO2 fluxes from the soils and established that a major

portion of the soil respiration consists of root respiration.

Some non-isotopic methods for measuring soil respira-

tion and its partitioning are as follows:

(i) Total soil respiration

(a) In situ automated chamber measurements at the

soil surface (IRGA)

(b) In situ automated soil CO2 concentration in soil

profiles (gas wells or solid state CO2 sensors)

(ii) Partitioning of soil respiration to root- and SOM-

derived CO2

(a) Root exclusion techniques (planted vs. unplanted

soil and trenching

(b) Shading and clipping

(c) Regression between root mass and root-derived

CO2 at a given temperature

(d) Component integration by manual separation of

CO2 sources and measuring CO2 from each source

(e) Measuring of respiration of excised roots sep-

arated from soil by IRGA, oxygen electrode or

capture of CO2 in alkali

(f) In situ root respiration

(g) Tree girdling

(h) Gap formation difference of CO2 from soil with

vegetation and from the soil under the gap

(i) Partitioning of root-derived CO2 into root respi-

ration and rhizomicrobial respiration through

component integration and substrate induced

respiration.

The isotopic partitioning methods are advantageous over

other non-isotopic techniques because they impart much

less disturbance to plant–soil system. Isotopic or tracer

approaches help in a direct and quantitative manner about

the links of plant and microbial aspects of soil respiration.

These links include quantification of C transport within

plants, the transfer of C from roots to microbes, SOM, and/

or respiration, and the contributions to soil respiration from

auto- and heterotrophic sources. Tracer studies include

pulse and continuous labeling and also monitoring of

changes occurring in the introduced samples (of CO2, litter,

carbohydrates) to the atmosphere or soil (Kuzyakov 2006;

Pendall et al. 2004; Rochette and Flanagen 1997; Rochette

et al. 1999). Some isotopic methods for partitioning of soil

respiration (Kuzyakov 2006) are:

(i) Partitioning of soil respiration to root- and SOM-

derived CO2

(a) Continuous labeling of shoots in 14CO2 or 13CO2

atmosphere

(b) Pulse labeling of shoots in 14CO2 or 13CO2

atmosphere

(c) 13C natural abundance

(d) Free air carbon dioxide enrichment

(ii) Partitioning of root-derived CO2 into root respiration

and rhizomicrobial respiration

(a) Comparison between root-derived 14CO2 and

rhizomicrobial 14CO2

(b) d13C values of CO2 and microbial biomass.

Studies on the plant responses to elevated CO2

Methodologies for studying and monitoring the plant

responses to elevated CO2 and the carbon dynamics

of ecosystems: chambers and free air CO2 enrichment

(FACE) systems

Most of the studies on plant responses to elevated CO2

have been conducted using open top chambers (OTCs) with


123

diameter of 2–3 m and height of about 2–3 m. The OTCs

with open circular top are made of aluminum frame lined

with transparent PVC sheets. The enclosures/OTCs alter

the canopy microclimate and thus influence transpiration.

However, FACE technology provides natural environment

in terms of crop microclimate. Thus, FACE provides a

better understanding and measurements of stomatal

responses to elevated CO2, canopy evapotranspiration and

soil moisture as compared to enclosure studies. The CO2

exchange dynamics in the vegetation and soil requires use

of ecosystem experimental setups as FACE (Fig. 6). FACE

experiments have provided valuable insight about the

cycling and storage of carbon in the terrestrial ecosystems

(Ainsworth and Long 2005; Norby and Zak 2011). FACE

systems cover large diameter up to 30 m and can accom-

modate trees up to 20 m tall. FACE has therefore, advan-

tage of larger size, longer experimental duration and no

undesirable artifacts due to chamber walls as compared to

OTCs (Hendrey et al. 1999). For example, reports on sto-

matal conductance of trees in growth chambers ranged

from a 5 % increase to a 25 % decrease (Curtis and Wang

1998), whereas in FACE experiments, a 16–23 % decrease

was observed (Ainsworth and Rogers 2007). FACE studies

help in the integration of processes and complexities of the

ecosystems and thus their results can be more interpretable

in relation to the carbon cycle. These ecosystem experi-

ments help in monitoring the response of plant community

or stand, soil, larger and older trees, NPP, etc. which is not

possible from OTCs. Thus FACE studies are useful for

validation of ecosystem models (Leakey et al. 2012). The

study of the impacts of elevated CO2 concentration on

plant responses under changing climate and monitoring of

the carbon fluxes will provide a holistic understanding of

the role of global carbon cycle (Fig. 7).

Plant responses to elevated CO2

Plants growing under elevated atmospheric CO2 are usually

larger due to availability of additional photosynthates

because the present levels of CO2 are lesser than that required

for saturation particularly in C3 plants. The magnitude of

growth stimulation varies depending upon photosynthetic

pathway strategies (Abrol et al. 1991). In FACE experi-

ments, an average increase of 17 % for the aboveground, and

more than 30 % for the belowground portions of plants has

been reported (Ainsworth and Long 2005; de Graaff et al.

2006). The yield of crops also increased by 12–14 % under

elevated CO2 in FACE experiments (Ainsworth 2008; Long

et al. 2006). The increased growth responses may occur

directly due to the increased substrate supply e.g. sucrose or

due to the role of sucrose as a chemical signal by mediating

cyclin activity and thereby promoting cell division (Riou-

Khamlichi et al. 2000). The impact of elevated CO2 would

depend mainly on the acclimation or adjustment to the long

term elevated level of CO2 (Ghildiyal and Sharma-Natu

2000). Comparison of photosynthesis rate in various species

at same level of internal CO2 concentration shows that there

is either an increase or decrease in the photosynthetic

capacity. Therefore the impact of elevated CO2 on crop

production will depend upon the responsiveness of photo-

synthesis in terms of its up regulation or down regulation.

The key determinants of photosynthetic regulation are

growth behaviour and biochemical partitioning of assimi-

lates to starch and sugars. The diagrammatic representation

(Fig. 8) of photosynthetic acclimation to elevated CO2 in is

presented below. Various reviews show the meta analysis of

the plant responses to elevated CO2 (Norby and Zak 2011;

Robinson et al. 2012; Reddy et al. 2010; Pinkard et al. 2010).

It is to be noted that many responses may not upscale from

the leaf level to the plant stand or community (Norby and Zak

2011). A summary of the plant responses to elevated CO2

from reviews and case studies are given in Table 1.

Uncertainties in monitoring and implications

The uncertainties can occur due to discrepancies in the

estimation methods (Houghton 2003; Wang et al. 2009).

For instance, the CO2 concentration near the ground is

affected by the asymmetric transport phenomenon in the

atmosphere and cyclones. The uncertainties can be resolved

through detailed historical reconstructions where data are

available and can be obtained from systematic monitoring

of land use changes with satellite data. Le Quere et al.

(2010) also mentioned role of sophisticated monitoring

mechanisms and development of methods for full GHG

accounting. However, other important aspects also need to

be considered such as—the methods, their rapidity, scala-

bility, non invasiveness, cost effectiveness and accuracy.

The verifiability depends upon the stringency of the meth-

odology. More stringency can cost prohibitively at national

level and least stringency can lead to use of default values.

Intermediate scheme can be of more practical use and

require use of remote sensing, use of controlled experiments

or benchmark sites and models (Smith 2004). The highest

degrees of uncertainty in estimates occur in the source and

sink estimates of the land ecosystem as compared to the

atmosphere, ocean and fossil fuel (Le Quere et al. 2009).

The extent or estimates of these uncertainties (represented

by ±values) have been shown in Fig. 1.

Complexity in ecosystems and climate carbon cycle

feedbacks

The terrestrial CO2 exchange processes and carbon balance

depends upon multiple factors or their interactive effects


123

(Fig. 9) leading to complexity of the terrestrial ecosystems

and difficulties in disentangling their effects. The climate

carbon cycle feedbacks involve changes in the rate of

photosynthesis and respiration due to changes in tempera-

ture and soil moisture (Harvey 2012). Coupled atmo-

sphere–biosphere models are necessary for interpreting

A

Plenum for CO2

entry and circular distribution of CO2 into OTC

Transparent PVC sheet

Open top

B

Ring for CO2 supply and circular distribution of CO2 into the crop canopy

Supports for holding the rings above the ground

Fig. 6 a Diagram of open top

chambers (OTCs) and b free air

CO2 enrichment (FACE) setups

used for studying the plant

response to CO2

Study of plant / community responses to elevated CO2

Integration into Ecosystem models

for validation

Generation of global carbon cycle

response and predictions

Status of different carbon pools and fluxes

from actual monitoring

Better understanding and predictions of

global carbon cycle

Further ecosystem experiments or FACE studies to include more complexity, unexplored ecosystems or longer term experiments

Fig. 7 A scheme depicting the

importance and role of plant

response studies to elevated

CO2 and monitoring of carbon

pools and fluxes for better

understanding the global carbon

cycle

Source-sink activity in balance , assimilate translocation to growing sinks(e.g. growing leaves, stem, seeds, roots, etc.)and stimulation of cell division

Sugars

Starch accumulation in leaf

Reduced sugar accumulation in leaf

Continued or higher transcriptionof Rubisco small subunit gene

More translation of Rubisco small subunit

Enhanced Rubisco content and activity

Acclimation of photosynthesis: Up regulation

Plant response: • Enhanced photosynthetic capacity• Examples: Sunflower, mungbean

Elevated CO2

Source-sink imbalance and reduced translocation

More sugar accumulation in leaf

Sugars More sensing of sugars

Reduced transcription of nuclear encodedphotosynthesis genes (e.g. Rubisco SSU)

Reduced translation of Rubisco small subunit

Reduced Rubisco content and activity

Acclimation of photosynthesis: Down regulation

Plant response: • Reduced photosynthetic capacity• Examples: Wheat, rice

Fig. 8 Schematic representation of the physiological and molecular basis of photosynthetic acclimation to elevated CO2 in plants


123

Table 1 A brief summary of plant responses to the enhanced CO2 concentration

S. nos. Phenomenon Response to elevated CO2 Selected references

(1) Photosynthetic response

and acclimation

The CO2 response curve i.e. A/Ci curve shows following

alterations due to long term exposure to elevated CO2 (i) the

initial slope of the CO2 response unaffected but CO2-

saturated rate of photosynthesis (Amax) increased as in S.

tuberosum, (ii) the initial slope decreased but Amax little

affected as in C. album, P. vulgaris, (iii) both the initial slope

and the Amax decreased as in B. oleracea, S. melongena

Sage et al. (1989)

Decreased activation state of Rubisco in several C3 species

such as Raphanus sativus and wheat

von Caemmerer and

Edmondson (1986),

Theobald et al. (1998)

More starch accumulation in leaves of mungbean and sunflower

under elevated CO2 resulted in less down regulation of

photosynthesis. Accumulation of sugars in leaves of wheat

resulted in more down regulation of photosynthesis

Pandurangam et al.

(2006a)

A large or unrealized sink enhances the responsiveness to

elevated CO2 and improves crop yield

Luo et al. (1999),

Sharma-Natu and

Ghildiyal (2005)

Reduced transcription and translation of Rubisco small subunit

occurred due to elevated CO2 in wheat but was not affected

much in sunflower and mungbean

Pandurangam et al.

(2006a)

(2) Stomatal responses and

water use

Stomata tend to close or reduced stomatal conductance Assmann (1999)

A high air relative humidity favours the acclimation response

and a higher stomatal sensitivity to CO2

Talbott et al. (2003)

In long term stomatal density or stomatal index decreases Woodward (1987)

Water use at both leaf and canopy scales declines and this

improves the water use efficiency (4–44 %). Further, leads to

increased soil water content.

Warren et al. (2011)

(3) Leaf growth Increased leaf production, leading to larger LAI Ainsworth and Long

(2005)

Species with lower LAI (e.g. Aspen–Birch, Aspen and Pine

with LAI \3) showed higher increase in LAI whereas in tree

species with LAI [5 (Sweetgum, Poplars and Hardwoods)

there was less or negligible increase in LAI

Norby and Zak (2011)

Changes in leaf morphology—the number of mesophyll cells

per area, mesophyll thickness and leaf mass per area

Eguchi et al. (2004)

Leaf mass per unit area generally increases Yin (2002)

Accelerated lower leaf blade senescence in rice Seneweera et al. (2011)

(4) Net primary productivity NPP per unit leaf area increased in many ecosystem

experiments due to increase in leaf level photosynthesis.

Thus, FACE experiments helped in concluding that elevated

CO2 conditions increase the photosynthetic C uptake

Norby and Zak (2011)

Promotion of fine root growth with elevated CO2 is also

important aspect as its turnover represents a substantial

proportion of annual net primary productivity in trees and

forests

Norby et al. (2004)

(5) Respiration Marked increase in respiration Leakey et al. (2009a, b)

(6) Response of plant

functional types: C3, C4

and legumes

Plant species with C3 photosynthesis are more responsive

because in the present atmospheric CO2 concentrations the

Rubisco is not saturated. Other species, C4 and CAM are less

responsive to elevated CO2 and these include mostly tropical

grasses and crops—maize, sugar cane, sorghum and the

millets

Cotrufo et al. (1998)

Indirect stimulation of carbon uptake and increse in water use

in C4 plants can occur in situations of drought

Leakey et al. (2009a, b)

Legumes as compared to other non-leguminous C3 plants have

the ability to enhance photosynthesis and N2 fixation under

optimal conditions and rising CO2 may offer some protection

from water stress

Rogers et al. (2009)


123

Table 1 continued


In FACE experiments, soybean showed a greater response to

elevated CO2 than wheat and rice in photosynthesis and

overall growth, although not in harvestable yield

Long et al. (2006)

Tree legumes with a better nodulation will have a competitive

advantage in tropical forests as atmospheric CO2 rises

Cernusak et al. (2011)

CO2 responsiveness in Brassica oxycamp interspecific hybrid

depended on sink size

Uprety et al. (1998)

(7) Carbohydrates Accumulation of sugars and starch in leaf Seneweera et al. (2011)

(8) Leaf nitrogen and

proteins

Leaf nitrogen concentrations in plant tissues typically decrease

in FACE under elevated CO2 with nitrogen per unit leaf mass

decreasing on average by 13 %

Ainsworth and Long

(2005)

Photosynthetic nitrogen use efficiency (PNUE) is markedly

improved in C3 plants grown at elevated CO2

Ainsworth and Long

(2005)

In FACE experiments, protein concentrations in grains of

wheat, rice, barley and in potato tubers are decreased by

5–14 % under elevated CO2

Taub et al. (2008)

The C/N ratio of leaves increased under elevated CO2 Pal et al. (2003)

Increased protein carbonylation in leaves of Arabidopsis and

soybean

Qiu et al. (2008)

(9) Secondary metabolites Carbon-based secondary metabolites e.g. phenolics increase

and decrease in others e.g. terpenes

Robinson et al. (2012),

Ryan et al. (2010)

Decrease in nitrogen-based secondary metabolites Ryan et al. (2010)

(10) Soil responses There will be lesser soil N availability in long term in the soil

under elevated CO2 called progressive nitrogen limitation

hypothesis (PNL). This implies that CO2 benefits can be

realized in future only if extra N is applied to soil

Luo et al. (2004), Lenka

and Lal (2012)

CO2 enrichment in European tree species lead to an increase in

soil microbial respiration and a marked decline in

sequestration of root derived carbon in the soil

Heath et al. (2005)

Stimulates grassland soil respiration by increasing carbon

inputs rather than by enhancing soil moisture

Adair et al. (2011)

The soil carbon pools under elevated CO2 increased as

follows—microbial biomass C (18.98 %), dissolved organic

C (48.8 %), labile C (15.58 %) and carbohydrate C (0.83 %)

Kant et al. (2007)

A slower turnover of root material grown in elevated CO2 may

result in a limited net increase in carbon storage

Groenigen et al. (2005)

(11) Ecosystem carbon storage It is difficult to account the fate of carbon gained by

photosynthesis in the other components of the forest stand’s

carbon budget. The FACE experiments indicate that

ecosystem carbon storage will not necessarily increase with

the increase in the NPP

Bader et al. (2010), Norby

and Zak (2011)

(12) Plant–community

interactions and stand

composition

Long term stand composition will change due to the differential

effect on the competing species

Norby et al. (1999)

In mixed-species experiments under elevated CO2 and under

high fertility conditions, C4 plants may decrease whereas

under low fertility conditions, legumes increased as a

proportion of the biomass of plant communities

Poorter and Navas (2003)

(13) Adaptations to elevated

CO2 concentrations

Stomatal records from the preindustrial to the modern era from

the old herbarium records showed decrease in the stomatal

density. However, in another study there were no detectable

maternal effects of elevated CO2 on Arabidopsis thaliana

over 15 generations

Woodward (1987), Teng

et al. (2009)


123

Table 1 continued


(14) Herbivore responses e.g.

insects

Significant decrease in the relative growth rates of insects,

increase in relative consumption rate and decrease in the

conversion efficiency. The relative damage to plants was

greater

Robinson et al. (2012)

Host plant quality determines the fecundity of herbivorous

insects. The fecundity of some insects increased significantly

Robinson et al. (2012),

Prasannakumar et al.

(2012)

(15) Interactive effect of

elevated CO2 with other

factors e.g. temperature,

water stress, nutrition,

species, pollutants, etc.

Most of the information on the interactive effects has been

generated from the long term experiments done in the

temperate regions and on few species. Evidence from these

studies show that genetic or environmental factors interact

significantly with elevated CO2 leading to an altered response

in magnitude and/or direction of response. Information is not

available on the crop and ecosystem responses in many

important regions especially the tropics and subtropics and

also on the response of many species

Leakey et al. (2012)

CO2 9 T An increase in temperature can offset the beneficial effect of

CO2 on the brassica crop

Frenck et al. (2012)

CO2 9 N Low N availability limits the response to elevated CO2 Ainsworth and Long

(2005)

CO2 9 P Low P availability limits the response to elevated CO2 Lewis et al. (2010)

CO2 9 water Under water stress the elevated CO2 grown Brassica plants

maintained higher water potential and photosynthesis as

compared to water stressed plant grown at ambient CO2

plants

Rabha and Uprety (1998)

Elevated CO2 may not ameliorate the water stress under high

temperature

Luo et al. (2008)

CO2 9 T 9 species Elevated CO2 may stimulate C4 photosynthesis under high

temperature

Leakey et al. (2012)

CO2 9 T 9 water Better photosynthesis in a temperate grass with warming Albert et al. (2012)

CO2 9 species Wheat is less responsive to elevated CO2 as compared to

sunflower and mungbean

Pandurangam et al.

(2006a)

CO2 9 light 9 species Wheat cultivars grown under elevated CO2 showed a lesser

response to irradiance than ambient grown plants whereas in

the sunflower cultivars there was no difference

Pandurangam et al.

(2006b)

The trees of Fagus sylvatica L. and Picea abies L. were

exposed to five dynamic light regimes from variable to

steady-states as observed in the forest canopy. Photosynthesis

under elevated CO2 increased in all light regimes and to a

higher level in Picea

Holisova et al. (2012)

CO2 9 T 9 ozone Elevated CO2 may not ameliorate the combined effect of high

temperature and ozone

Frenck et al. (2012)

CO2 9 T and model-

based projections

Due to acclimation, the photosynthetic response optimum shifts

to higher temperature whereas respiration may not increase at

higher temperature as compared to control. Study and use of

these acclimation responses is important for making better

quality model based projections of the future rates of climate

change

Smith and Dukes (2013)

Precipitation 9 T 9 CO2

interactions using

models

Models were used to quantify interactive effects of climate

warming (T), altered precipitation and elevated CO2 (C) on

NPP, Rh, NEP, transpiration, and runoff. The dry ecosystems

showed more vulnerability to global change and the wet

ecosystems had larger potential to alter terrestrial carbon

balance

Luo et al. (2008)


123

measurements of CO2 concentration and estimation of

whether a given area is a source or sink for CO2 (Berry

2012).

Uncertainties due to the plant responses and CO2

carbon cycle feedback

The magnitude of sink from CO2 fertilization is still with

large uncertainty. The CO2 fertilization effect gives nega-

tive feedback but is also sensitive to climate as well as to

atmospheric CO2 concentration (Cox et al. 2000). Mixed

results of CO2 fertilization have emerged from the eco-

system experiments e.g. FACE (Norby and Zak 2011). On

one hand, Kohlmaier et al. (1989) estimated CO2 fertil-

ization level as equal to terrestrial sink whereas Thompson

et al. (1996) concluded that CO2 may not act as sole driver

for the historical sink. Therefore, directly ascribing the

missing sink to the CO2 fertilization effect is not so simple.

Estimates indicated that CO2 fertilization accounts for

about one-half of the sink or less and it can modulate the

rate of CO2 increase in the atmosphere (Field 2001). This

increased C storage in the terrestrial biosphere creates a

negative feedback on the rate of CO2 accumulation in the

atmosphere and can moderate the trajectory of climate

change (Matthews 2007). Therefore, the long term study of

fertilization effects of CO2 on the carbon cycling needs

further investigation. In the changing climatic scenario

there are uncertainties about how the biotic- (Friend 2010)

and soil carbon (Heimann and Reichstein 2008; Norby and

Luo 2004) will respond to the climate change. It is because

of the fact that there will not only be increased incidences

of changes in temperature, soil moisture, extreme events,

etc. but the plants also will acclimate to the elevated CO2

i.e. their capacity for photosynthesis may be up- or down-

regulated (Pandurangam et al. 2006a, b). Canadell et al.

(2007) have also pointed out that increase in the rate of

airborne fractions of CO2 emission in the recent years also

implies a decline in the efficiency of CO2 sinks (i.e. down

regulation). They also observed that carbon cycle has

changed faster than that simulated by models. These may

be due to changes in plant responses e.g. respiratory pat-

terns (Leakey et al. 2009b), nitrogen and water relations

(Leakey et al. 2009a) and assimilate partitioning to roots

(Pendall et al. 2004).

Uncertainties due to the soil responses

With global warming, the interactive effect of temperature,

nutrient availability and soil moisture on the total below-

ground carbon flux needs to be further studied so that

partitioning of global primary productivity to the total

belowground carbon flux can be helpful in predicting car-

bon sequestration and these can then be incorporated into

global scale carbon cycling models. Another hypothesis is

that increased CO2 released from soil can accelerate global

climate change, acting as positive feedback (IPCC 2007;

Wixon and Balser 2009). It is however difficult to conclude

on this hypothesis and it needs to be further investigated,

particularly the complex relationship of organic matter

decomposition and temperature (Agren and Wetterstedt

2007). It seems rightly stated by Leonardo Da Vinci, ‘‘We

know better the mechanics of celestial bodies than the

functioning of the soil below our feet’’ (Dessaux et al.

2009).

Conclusions

Global efforts are being made to reduce the emissions and

to slow down the pace of climate change. The quantifica-

tion of source and sink abilities of different ecosystems for

CO2 is of immense importance. The flux of major GHG

i.e., CO2 needs to be monitored at different scales. This

flux of CO2 and C among various pools in carbon cycle

occurs due to different processes such as; photosynthesis,

respiration, deposition of carbon into soil, anthropogenic

emissions and other natural processes. Therefore the

measurements, monitoring and understanding of controls

of carbon movement in the carbon cycle has become

increasingly important. The key measures of input of car-

bon in a system are NPP and NEP. Estimates of photo-

synthesis and NPP can be made through traditional

approaches as well as other approaches e.g. bottom-up

approach (using mechanistic photosynthesis models) and

the top-down approach (using LUE with satellite data).

Advancements have taken place for monitoring the CO2

exchange at different levels such as leaf (portable photo-

synthesis systems), stand (eddy covariance method), land-

scape (tall towers) and vertical carbon column observations

(FTSs and satellites). Methods have also been developed to

partition the fluxes into land and oceans, for example,

Biodiversity Changes in species composition

Nutrients

Disturbances (insect pest, floods etc.)

Land use change (deforestation, burning etc.)

WaterTemperature

Light

Age of vegetation

CO2 CO2

exchange processes: vegetation

and soilSoil properties

Root growth

Fig. 9 Multiple factors affecting the ecosystem CO2 exchange

processes


123

discrimination of isotope of carbon (13C) by terrestrial

ecosystem processes. The CO2 exchange dynamics in the

vegetation and soil can be investigated with OTCs and

FACE. These studies help in integration of processes and

complexities of ecosystems and are useful for validation of

ecosystem models, particularly FACE. The impacts of

elevated CO2 concentration on plant responses under

changing climate and monitoring of carbon fluxes will

provide a holistic understanding of the roles of ecosystems

in global carbon cycle. Similarly, soil is a vast reservoir of

carbon and has a great potential for carbon sequestration as

well as source of emissions. Monitoring of roots, soil

carbon and CO2 fluxes from soil is therefore an essential

aspect in the era of changing climate, particularly with non-

destructive methods for rapid and large area estimations.

The uncertainties in the estimates need understanding of

the multi-factorial effects on carbon exchange processes,

plant acclimation responses and feedback response from

changing climate. Monitoring therefore needs concerted

efforts, enhancement of infrastructure for measurement at

different scales, use of multi-techniques and -disciplinary

approaches so that more constrained and better estimates

can be made. This has immense importance for determin-

ing how global environment is changing, what drives these

changes, its potential impacts and also for developing

sound policy decisions on mitigation and adaptation

strategies.

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REVIEW Monitoring of CO2 exchange and carbon pools in vegetation and soil

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