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Physiologia Plantarum 133: 705–. 2008 Copyright ª Physiologia Plantarum 2008, ISSN 0031-9317
REVIEW
Impact of climate change on crop nutrient and water useefficienciesSylvie M. Brouder* and Jeffrey J. Volenec
Department of Agronomy, Lilly Hall of Life Sciences, Purdue University, 915 W. State Street, West Lafayette, IN 47907-2054, USA
Correspondence
*Corresponding author,
e-mail: [email protected]
Received 15 November 2007; revised 1
May 2008
doi: 10.1111/j.1399-3054.2008.01136.x
Implicit in discussions of plant nutrition and climate change is the assumption
thatwe knowwhat to do relative to nutrientmanagement here and nowbut that
these strategies might not apply in a changed climate. We review existingknowledge on interactive influences of atmospheric carbon dioxide concen-
tration, temperature and soil moisture on plant growth, development and yield
as well as on plant water use efficiency (WUE) and physiological and up-
take efficiencies of soil-immobile nutrients. Elevated atmospheric CO2 will
increase leaf and canopy photosynthesis, especially in C3 plants, with minor
changes in dark respiration. Additional CO2 will increase biomass without
marked alteration in drymatter partitioning, reduce transpiration ofmost plants
and improve WUE. However, spatiotemporal variation in these attributes willimpact agronomic performance and crop water use in a site-specific manner.
Nutrient acquisition is closely associated with overall biomass and strongly
influenced by root surface area. When climate change alters soil factors to
restrict root growth, nutrient stress will occur. Plant size may also change but
nutrient concentration will remain relatively unchanged; therefore, nutrient
removal will scale with growth. Changes in regional nutrient requirementswill
bemost remarkable where we alter cropping systems to accommodate shifts in
ecozones or alter farming systems to capture new uses from existing systems.For regions and systems where we currently do an adequate job managing
nutrients, we stand a good chance of continued optimization under a changed
climate. If we can and should do better, climate change will not help us.
Introduction
Climate change variables including precipitation (amount
and distribution), temperature and atmospheric CO2 con-centrations are expected to alter agricultural productivity
patterns worldwide. Carbon dioxide is a plant nutrient,
and atmospheric enrichment has the potential to enhance
plant productivity. Schimel (2006) observed that, at least
in some regions, agriculture may be one of the bright
spots, ‘the silver lining in the climate change cloud’. But
higher global temperatures and altered precipitation
patterns are expected to accompany the higher CO2
levels, and these factors may lessen or negate any pro-
duction increases or even depress production below
current levels. Themyriad of modeling studies attempting
to project the short- and long-term impacts of climatechange on agriculture are consistent only in highlighting
that the nature of the productivity change itself will vary.
Realized yield changes will reflect differences in local
environments as well as differences in access to seed
and management technologies that may offset negative
climate change impacts.
Regardless, with any potential changes in agricultural
productivity comes a potential for associated changes incrop nutrient use. Local potential yield levels are
Abbreviations – AE, agronomic efficiency; FACE, free-air concentration enrichment; PE, physiological efficiency; Ps, net
photosynthesis; Rd, dark respiration; UE, uptake efficiency; WUE, water use efficiency.
Physiol. Plant. 133, 2008 705
determined by prevailing climate, ambient CO2 and crop
characteristics, but these yields are almost always limited
by root zone resources such as nutrients and water and
further reduced by pests and diseases (Goudriaan and
Zadoks 1995). The interactive effects of soil moisture
and nutrient availability are two key edaphic factorsthat determine crop yield (Ziska and Bunce 2007). The
questionwe address here is whether such changeswill be
ones we cannot anticipate based on our existing
knowledge of plant mineral nutrition and soil fertility
management. In other words, current nutrient manage-
ment recommendations are based on an understanding of
crop-specific needs for achieving expected yields and
soil-specific nutrient supply characteristics. To whatextent does our existing knowledge remain useful under
a changed climate? Addressing this question requires an
assessment of the potential for global climate change
factors to influence the physiological efficiency (PE) of
nutrient usewithin the plant and to alter the availability of
nutrients in soil and their transport through soil and across
root membranes. In this review, we conduct an integrated
analysis of whole-plant responses to global climatechange and couple this information to a mechanistic
evaluation of root growth, nutrient availability in soil and
ion movement and uptake at the root surface. It is
important to note that the objective of this review is to be
illustrative in addressing concepts and theory and not
necessarily comprehensive. Our objective is to provide
a conceptual framework useful for understanding how
plant nutrient uptake may change in response to globalclimate change. Our focus is on agroecosystems where,
when feasible, attempts are made to fertilize and remove
nutrient constraints to production and where long-term
sustainability requires replacement of nutrients removed
in harvests. Studies on global climate change andmineral
nutrition remain relatively sparse, with nitrogen being the
primary focus of previous research. Several existing
literature reviews have examined N and climate changeemphasizing key topics such as soil biodiversity (Chapin
2003, Swift et al. 1998), water cycling (Pendall et al.
2004), uptake kinetics (BassiriRad 2000) and soil C/N
cycling in extreme environments (Hobbie et al. 2002).
Thus, our focus is on potassium, and, to a certain extent,
phosphorus and magnesium, the most commonly limit-
ing macronutrients in agroecosystems other than N.
Greenhouse gases and climate change
Consent appears to be solidifying among even the most
recalcitrant public and private sectors that our climate is
changing. From the end of the last glaciation until about
1750, ambient CO2 concentrations were approximately
278 mmol mol21; currently, atmospheric concentrations
are >370 mmol mol21 with a rate of increase of approx-
imately 1 mmol mol21 year21 (Intergovernmental Panel
on Climate Change 2007). Concomitant increases in the
biogenic gasses methane and nitrous oxide have also
been observed. Several factors including our insatiable
appetite for fossil fuel, industrialization, vegetation de-struction and CO2 release from disturbed soils are
considered critical contributors to elevated CO2. The
current concentrations of greenhouse gasses are believed
bymany to have already altered global climate, and there
is some evidence that warming has already negatively
impacted yields. Temperature records from the Northern
Hemisphere show a temperature rise of approximately
0.6�C within a 150-year period that is in sharp contrastto relatively constant temperatures of the preceding
450 years (Mann et al. 1998). Across Europe, average
wheat (Triticum aestivum L.) yields have increased mark-
edly since the early 1960s, but rates of increase have
been slower in more southern countries (e.g. Portugal
and Spain) when compared with the UK and France;
Schar et al. (2004) conclude that these yield trend dif-
ferences reflect a regional, differential impact of thewarming since the early 1990s.
The rate of increase in ambient greenhouse gas con-
centrations is expected to accelerate, and CO2 concen-
trations of 550 mmol mol21 are expected by 2050 (Raven
and Karley 2006). Likewise, rate of increase in temper-
aturewithin the next century are expected to bemarkedly
higher than the changes occurring in the preceding
century. For example, Schlenker et al. (2006) estimatedthat, relative to current conditions, US growing season
temperatures will increase between 2.0 and 2.4�Cbetween 2020 and 2049, whereas dramatic increases
(from 3.6 to 7.4�C) are expected to occur between 2070
and 2099. Themean annual global surface temperature is
projected to increase by 1–3.5�C by 2100 (Southworth
et al. 2000), but, unlike CO2, the magnitude of temper-
ature increase will vary regionally and be accompaniedby altered precipitation patterns. For the conterminous
United States, Izaurralde et al. (2003) estimated average
temperature increases over current ambient temperatures
of up to 4.5�C by 2095, with marked differences among
agriculturally important regions. Climate change effects
will be more intense in the Southern Great Plains than in
the Cornbelt region (Table 1). Greater increases in both
the maximum and the minimum temperatures arepredicted for the Southern Great Plains. Precipitation
will increase at both locations but to a greater extent in
the Cornbelt where runoff losses will also be higher.
Evapotranspiration will increase in proportion to pre-
cipitation in both regions.Water use efficiencies (WUEs),
an estimate of plant growth per unit of water, are expected
to decline to between 83% (Southern Great Plains) and
706 Physiol. Plant. 133, 2008
88% (Cornbelt) of current values by 2095.Models predictonly modest changes in water stress days per year at both
locations, whereas increases in temperature stress days
per year are expected to be pronounced, especially in the
Southern Great Plains. These results agree in general with
those of Schlenker et al. (2006)whoalso predicted greater
growing season precipitation by 2099 but cautioned that
site-specific water and temperature stress will occur,
especially, in the Southern United States.
Crop responses to climate change
The extent to which these expected changes in ambient
CO2 concentration, temperature and precipitation will
influence agriculture is the subject of intense scientificstudy and debate. Because we are only on the cusp of
climate change or in the earliest years of what is antic-
ipated to be radical change in both mean and extreme
conditions, crop models have been major tools for
studying climate change scenarios. Crop growth, devel-
opment and yield responses to climatic variability are
a mixture of linear and non-linear functions. Changes in
the mean, variability and rate of occurrence of extremesin temperature all affect crop processes but not necessar-
ily the same processes (Porter and Semenov 2005).
Photosynthesis and respiration can change continuously
and non-linearly in response to incremental increases in
temperature, but short periods of high temperatures can
do disproportionate damage when coinciding with
flowering or pollination. Likewise, mild water stress has
a different effect than prolonged drought or flooding.Application of the Epic agroecosystems model to US
climate change scenarios produced by the Hadley
Climate Change model (Table 2) illustrates the differen-
tial impact that climate change may have on crop
productivity. Temperatures and rainfall increases coupled
with ambient CO2 of 560 mmol mol21 are expected to
improve general conditions for growth of all major crops
in the US Cornbelt (Izaurralde et al. 2003; Fig. 1). Winterwheat production is predicted to be particularly bene-
fited, presumably from better overwintering in more
northerly regions. A companion study on yield variabilityof selected crops suggests that increased rainfall will
reduce year-to-year variation in Cornbelt maize (Zea
mays L.) yields (Reilly et al. 2003). In contrast, in the
Southern Plains, alfalfa (Medicago sativa L.) is the only
crop projected to benefit significantly from climate
change (Izaurralde et al. 2003). For Southern Plains
maize and wheat, fertilization benefits of increased CO2
are canceled out by yield losses because of increasedtemperature and water stress; for soybean (Glycine max
L. Merril), yields are expected to be reduced by more
than 20%.
As is often acknowledged by authors, results from
climate change – yield impact modeling – vary widely.
Izaurralde et al. (2003) remark that their results for US
wheat and maize are more favorable than the earlier
projections of Brown and Rosenberg (1999) who foundonly small increases in yield with a temperature increase
of 2.5�C and large decreases in yield with a temperature
increase of 5�C. The relative merits of the different results
can be difficult to discern. Changes in assumptions
pertaining to critical drivers such as the interannual
variability of precipitation (intensity and occurrence) and
temperature (extremes and their duration) can drastically
alter model outcomes (Porter and Semenov 2005). Someregions of the world such as the central United States
appear predisposed to respond more beneficially than
others. Furthermore, the extent to which a given agricul-
tural region is vulnerable to negative impacts of climate
change reflects social and economic variables; projec-
tions vary according to assumptions about levels of
available technology and market forces (Reilly and
Schimmelpfennig 1999). For example, Darwin et al.(1995) predict a 20–30% reduction in global cereal
production without technology and market factors, but
a 0.2–1.2% increase with these factors optimized. In
a similar study, Rosenzweig and Parry (1994) specifically
highlight the effect of differential access to technology in
developing countries where available technologies may
not overcome the negative impacts on global climate
change. Finally, new results from free-air concentration
Table 1. Present-day and future (2095) regional temperatures, precipitation and associated crop production-influencing factors as estimated by the
Hadley Centermodel. Adapted from Izaurralde et al. (2003). aUS Cornbelt states areOhio, Indiana, Illinois, Iowa, andMissouri; U.S. Southern Plains states
are Texas and Oklahoma. bWUE is plant or crop WUE.
US regiona
Maximum
temperature
(�C)
Minimum
temperature
(�C)Precipitation
(mm year21)
Runoff
(mm year21)
Evapotranspiration
(mm year21)
WUEb
(kg ha21 mm21)
H2O stress days
(days year21)
Temperature
stress days
(days year21)
Cornbelt Present 16.4 4.5 941 156 581 10.4 6.1 16.1
2095 18.4 7.7 1195 194 774 9.2 5.6 18.2
Southern
Plains
Present 24.7 10.5 727 86 568 9.8 19.4 13.6
2095 27.8 14.2 815 85 642 8.1 19.8 17.4
Physiol. Plant. 133, 2008 707
Table
2.Im
pactofelevated
CO2onmajorplantprocesses
andtheircomponen
ts.
Process
Influen
tialcomponen
tRem
arks
regardingelevated
CO2
Referen
ces
Photosynthesis
C3
Single-leafrate
Averageincrease
of14%;individualincreasesas
highas
50%
Longet
al.(2006),New
man
etal.(2003),So
ussan
aan
dLuscher
(2007)
Can
opy
Averageincrease
of20%;individualincreasesas
highas
100%
primarily
asaresultofgreater
single-leafrate
andad
ditionalleaf
area
per
plant.Leaf
angle,opticalp
roperties
ofleaves,plantheightan
d
verticalleaf
distributionin
thecanopywerenotalteredbyhighCO2
Bunce
(1995),Hillet
al.(2007),Longet
al.(2006),
Soussan
aan
dLuscher
(2007),Teughelset
al.(1995)
C4
Single-leafrate
Averageincrease
of10%;individualincreasesas
highas
25%
Longet
al.(2006),So
ussan
aan
dLuscher
(2007)
Can
opy
Averageincrease
of6%;individualincreasesas
highas
30%
Longet
al.(2006),So
ussan
aan
dLuscher
(2007)
Rd
Tissuemassbasis
Responsesrangefrom
noinfluen
ceofelevated
CO2upto
a
40%
reductionat
elevated
CO2
Atkin
etal.(2005),ElKohen
andMousseau(1994),
Hillet
al.(2007),Zh
aoet
al.(2004)
Can
opybasis
Noeffect;greater
Rdbecau
seofgreater
totalb
iomasswas
offsetby
increasedcanopyphotosynthesisat
elevated
CO2
Dunnet
al.(2007)
Growth
Biomass
Averageincrease
inyieldof17%;upto
a66%
increase
inyield
ofC3plants.Nobiomassresponse
forC4plants
Derner
etal.(2003),Hillet
al.(2007),New
man
etal.(2003),
Soussan
aan
dLuscher
(2007)
Harvestindex
Noeffect
inC3plants;reducedslightlyin
C4
Longet
al.(2006)
Leaf:stem
Noeffect
tomodestincrease
Barrettan
dGifford
(1995),Gueh
letal.(1994)
Root:shoot
Effectsvary
dep
endingonspeciesan
dman
agem
ent
Barrettan
dGifford
(1995),Derner
etal.(2003),Gueh
letal.(1994),Hillet
al.
(2007),Maestre
andReynolds(2006),So
ussan
aan
dLuscher
(2007)
Storedreserves
Tran
sien
tstorage
inleaves
Leaf
sugar
andstarch
concentrationsincrease
atelevated
CO2
ElKohen
andMousseau(1994),Vuet
al.(2002),Zh
aoet
al.(2004)
Long-term
storagein
peren
niatingorgan
s
Increasedconcentrationsin
storageroots,
rhizomes,stolonsan
dstem
bases
Casellaan
dSo
ussan
a(1997)
708 Physiol. Plant. 133, 2008
enrichment (FACE) studies suggest that the beneficial
effects of CO2 fertilization may be far less than had been
suggested by previous experimentation with less sophis-
ticated techniques – resultswhich have been used inmostmodeling studies to date (Long et al. 2006).
In sum, climate will change but details regarding
impact on agriculture remain vague. Mineral stressors on
crop production are one of the many biotic and abiotic
uncertainties that contribute to our inability to predict
future food supply. Lynch and St Clair (2004) identified
this as a critical gap in climate change studies, noting that
most plant systems, natural and agricultural, havingsuboptimal nutrient availability and mineral stress inter-
actions with global climate change variables are likely to
be important but remain understudied. For agriculture,
the obvious and practical question is whether nutrient
inputs will need to increase or change to optimize
productivity responses to climate change and to maintain
or improve the overall use efficiency or agronomic
efficiency (AE) of fertilizer nutrients. The AE of a unit offertilizer is the product of PE and uptake efficiency (UE)
where internal nutrient use efficiency can be quantified
by simple expressions that relate a plant’s productivity
to its nutrient content. Gerloff and Gabelman (1983)
proposed a general nutrient efficiency ratio that was
a function of units of yield and units of nutrient. In
managed systems, PE can be couched in terms of fertilizer
units such that
PE ¼ ðDyield; kgÞ=ðDtissue element content; kgÞ ð1Þ
and
UE ¼ ðDtissue element content; kgÞ=ðfertilizer increment; kgÞ ð2Þ
In the absence of a large body of experimentation on
the interactive effects of global climate change variableswith plant nutrition variables, existing knowledge regard-
ing temperature and moisture impacts on UE and PE can
be reevaluated within the specific context of anticipated
physiological changes related to enhanced CO2 levels.
While detailed mechanistic models exist for crop
plants, for example, Hybrid Maize (Yang et al. 2004) or
CERES-Maize (Jones and Kiniry 1986), for simplicity, we
will describe the impact of CO2 on four processes: netphotosynthesis (Ps, gross photosynthesis minus photores-
piration), dark respiration (Rd), growth and accumula-
tion/use of stored organic reserves (primarily starches and
fructans) that serve to buffer changes in photosynthesis.
These components can be related to one another as
follows:
Net Ps2Rd ¼ growth 1 stored reserves ð3Þ
The left side of Equation 3 (Net Ps 2 Rd) represents the
net carbohydrate that is produced by the plant and is thesource of 90–95% of plant dry mass. The remaining 5–
10% comes from soil nutrients. The right side of Equation
3 represents two alternative sinks for the net carbohy-
drate: plants can use the carbon for irreversible growth or
they can store the carbon for later use when demand for
carbohydrate exceeds that supplied through photosyn-
thesis (e.g. in darkness). While single-factor climate
change experiments may reveal striking effects on plantperformance when supplied alone, when multiple global
change factors are imposed simultaneously, adjustments
in plant growth and physiological processes often dam-
pen the overall response (Dermody, 2006). An integrated
understanding of the responses of model components
in Equation 3 to elevated CO2 will provide key insight
into how important agronomic traits like yield, nutrient
uptake and water use will respond to and interact withclimate change.
Net photosynthesis
Two distinct photosynthetic mechanisms occur in crops,
C3 and C4, named for the number of carbon atoms in the
initial organic molecules fixed by the plant. These plants
are also referred to as having the Calvin–Benson cycle
(C3) and the Hatch–Slack cycle (C4), and the contrasting
Fig. 1. Projected percentage change in crop yields in 2095 for the US
Cornbelt (Ohio, Indiana, Illinois, Iowa and Missouri) and Southern Plains
(Texas and Oklahoma). Projections based on application of the Epic
agroecosystems model to climate change scenarios produced by the
Hadley Center model and assumes ambient CO2 concentrations of
560 mmol mol21. Asterisk (*) identifies changes from current yields are
significant (P � 0.10). Data adapted from Izaurralde et al. (2003).
Physiol. Plant. 133, 2008 709
response of plants with these different photosynthetic
mechanisms to environment including temperature and
CO2 is one of the hallmark traits distinguishing one group
from the other. The C4 plants generally have higher
photosynthetic rates but are sensitive to cool temper-
atures and as such are often referred to as ‘warm-season’plants. Representative agronomic species include maize,
sorghum (Sorghum bicolor L. Moench), sugarcane
(Saccharum officinarum L.) and bermudagrass (Cynodon
dactylon L.). By comparison, C3 plants are well adapted
to cool temperatures (referred to as ‘cool-season plants’)
but have lower photosynthetic rates than C4 plants.
Representative C3 species include soybean, cereals like
wheat and rice (Oryza sativa L.), clover (Trifolium spp.),alfalfa and the cool-season grasses like ryegrass (Lolium
perenne L.).
There is general agreement that both single-leaf and
canopy photosynthesis of C3 plants will increase more
than that of C4 plants as atmospheric CO2 concentrations
increase (Table 2). This is in part because of competitive
inhibition of photorespiration by CO2 in C3 plants,
a process that does not impact photosynthesis of C4plants. Results frommost FACE studies reveal that canopy
photosynthesis of C3 plants increased primarily as a result
of greater single-leaf photosynthetic rate and additional
leaf area per plant (Table 2). However, exceptions to
these general observations can be found in unique
environments. Cook et al. (1998) compared growth of
ecotypes ofNardus strictus that had grown for more than
100 years at 790 mmol CO2 mol21 because of theirproximity to naturally emitting CO2 springs in Iceland
to that of ecotypes of this species growing in an adjacent
area upwind where CO2 concentrations were 360 mmol
mol21. They were surprised to find that ecotypes growing
in elevated CO2 exhibited a 25% reduction in photosyn-
thesis that was associated with less Chl and had lower
amounts of key photosynthetic proteins when compared
with the ecotypes grown upwind from the springs. Lessinvestment of resources into the photosynthetic mecha-
nism may reflect the enhanced photosynthetic efficiency
of the process at high CO2 that has occurred during
100 years of adaptation to high CO2. If similar changes
were to occur in other species in response to high CO2,
higher PE of nutrient usewould result because less N,Mg,
Fe, S and other nutrients directly involved in photosyn-
thesis would be needed.
Dark respiration
Unlike photosynthesis, no fundamental differences in Rd
exist between C3 and C4 plants. In general, Rd per unit
tissue mass is unaffected or declines in plants exposed to
elevated CO2 (Table 2). For example, Hill et al. (2007)
reported that Rd of perennial ryegrass grown in a FACE
systemwas reduced 26% at 600 mmol CO2 mol21 when
compared with ambient CO2. However, Rd on a soil
surface or canopy basis is often greater at elevated CO2
because of greater biomass accumulation in response to
high CO2, especially in C3 plants. Dunn et al. (2007)found that increased seasonal respiration because of
higher biomass in a boreal forest ecosystem is offset by
increased CO2 assimilation through photosynthesis and
resulted in no net effect on season-long CO2 balance.
Temperature is generally considered a key environ-
mental factor influencingRd rate and one that is predicted
to increase significantly with the accumulation of
greenhouse gases (Table 1). The commonly held assump-tion is that Rd rate doubles for each 10�C increase in
temperature. This concept has been recently challenged
by Atkin et al. (2005) who reported no consistent change
in respiration when tree species were allowed to
acclimate to warmer temperatures prior to respiration
measurement. Working with tall fescue [Lolium arundi-
naceum (Schreb.) S.J. Darbyshire], we also observed
acclimation of leaf Rd rate for plants acclimated to a 5�Cincrease in temperature prior to measurement (Volenec
et al. 1984). The homeostatic nature of Rd with modest
temperature increase (2–5�C) simplifies our prediction of
the impact of greenhouse gases on components of our
model (Equation 3) to focus primarily on the direct effect
of CO2.
Summarizing the effects of CO2 on Ps and Rd, this
model predicts a modest increase in net carbohydratefixation (left side of Equation 3) in C4 plants because of
their limited increase in photosynthesis and no or a slight
decline in Rd in response to elevated CO2. By compar-
ison, Ps of C3 plants is expected to increase, in some
cases markedly, in response to elevated CO2. The in-
crease in Ps, along with a decline in Rd, would result in
greater net carbohydrate fixation in these species, carbon
that can be used for growth and/or be stored (right side ofEquation 3).
Growth
The right side of Equation 3 provides two sinks for fixed
carbon, growth and stored reserves. Because the effect of
increased CO2 on Ps differs between C3 and C4 plants
and because 90% or more of plant dry weight is derivedfrom this process, it is not surprising that growth responses
of C3 and C4 plants also differ in response to elevated
CO2 (Table 2). Growth of aboveground biomass of C3
plants is often increased significantly by elevated CO2.
Long et al. (2006) summarized biomass and yield data
from several FACE studies and reported that C3 species
produced an average of 16% more biomass and 13%
710 Physiol. Plant. 133, 2008
greater grain yield at 550 mmol CO2 mol21 when
compared with ambient CO2 concentrations. Neither
biomass nor grain yield of C4 species was responsive to
elevated CO2 in these studies. Responses of specific C3
species can often be substantially greater. For example,
Newman et al. (2003) grew tall fescue in a FACE systemand observed a 50–60% increase in dry matter pro-
duction that was associated with a doubling of tiller
production. Increased vegetative growth such as this
often translates into greater grain yield because of
a relatively constant harvest index (seed mass/total
aboveground biomass) (Table 2). Jackson et al. (1995)
reported greater biomass of Avena barbata in response to
highCO2 andwith this a proportional increase in seed dryweight.
Partitioning of dry matter among leaves, stems and
roots also is an important consideration because greater
aboveground biomass without a concomitant increase in
root biomass could alter key processes like water and
nutrient uptake and could lead to greater incidence of
lodging. In addition, the nutrient composition of leaves,
stems and roots differs considerably and so changingthe relative abundance of these organs will alter plant
nutrient needs. Elevated CO2 does not alter or may
slightly increase the leaf:stem weight ratio of plants
whose growth is enhanced by CO2. For example, Guehl
et al. (1994) observed increased growth of Quercus and
Pinus species at 700 mmol CO2 mol21, but partitioning
of dry matter between leaves, stems and roots was largely
unaffected. By comparison, Barrett and Gifford (1995)reported that leaf:stem ratio of cotton (Gossypium
hirsutum L.) increased with elevated CO2 and that this
coincided with a decline in root:shoot ratio. However,
most studies, including other research with cotton
(Derner et al. 2003), have found little impact of elevated
CO2 on root:shoot ratio. For example, Hill et al. (2007)
grew perennial ryegrass in a FACE system and reported
a 66% increase in shoot mass that was accompanied byan 83% increase in root biomass, resulting in no signi-
ficant change in root:shoot biomass ratio. Thus, changes
in plant biomass in response to elevated CO2, and
not large changes in dry matter partitioning, are expected
to drive changes in nutrient needs as climate change
occurs.
Stored reserves
Several studies have examined the impact of elevated
CO2 on transient accumulation of carbohydrate in leaves,
and most have found that sugars and starches are often
higher in leaves of plants grown at elevated CO2
(Table 2). For example, Vu et al. (2002) reported higher
single-leaf photosynthetic rates, lower transpiration rates
and greater WUE in ‘Ambersweet’ orange [Citrus
reticulata Blanco � (Citrus paradise Macf. � C. reticu-
lata)] at 720 mmol CO2 mol21 when compared with
360 mmol CO2 mol21. Starch accumulated to higher
concentrations in late afternoon in leaves of plants in
elevated CO2. Similar results were reported for cotton(Zhao et al. 2004) and chestnut (Castanea sativa L.) (El
Kohen andMousseau 1994). Accumulation of these non-
structural carbohydrates reflects the imbalance between
photosynthesis and translocation that can occur when
elevated CO2 increases net carbohydrate synthesis
(Equation 1, left side).
Less is known regarding the impact of elevated CO2 on
accumulation of long-term carbohydrate reserves instorage organs. These reserves serve to buffer growth
and Rd against reductions in photosynthesis and are
particularly important in perennial plants. Likewise,
when carbohydrate supply from photosynthesis exceeds
growth and respiratory needs, as might happen in C3
plants grown at elevated CO2, the additional carbohy-
drate can accumulate in storage organs. For example,
Casella and Soussana (1997) reported a 40% increase infructan accumulation in the pseudostem of wheat at
700 mmol CO2 mol21 when compared with plants
grown at 350 mmol CO2 mol21. A 3�C increase in
temperature as might be expected to result from global
warming exerted the same influence on fructan accumu-
lation at 700 mmol CO2 mol21 in this species.
In summary, plant growth responses to elevated CO2
will be species dependent, with C3 plants being moreresponsive than C4 plants. Positive responseswill include
higher photosynthetic rates, greater growth and higher
yields.None of these changes are likely to requiremarked
changes in tissue nutrient concentrations, and major
changes in dry matter partitioning among organs (roots,
stems and leaves) and harvest index are not expected.
Therefore, overall PE for a given nutrient will likely
remain unchanged. Nevertheless, larger plants withgreater yield may influence total water and nutrient
uptake and could impact how plants will ultimately
respond to global climate change.
Water use efficiency
Root-nutrient contact occurs primarily as a result of two
processes: mass flow and ion diffusion. Water is a keycommon denominator in these processes, and bothmight
be altered should plant water relations change markedly
with climate change. In addition, transpiration from leaf
surfaces consumes large quantities of energy through
latent heat of vaporization, which serves to cool foli-
age up to 5�C below prevailing ambient air tempera-
tures. Changes in plant water use or reductions in water
Physiol. Plant. 133, 2008 711
availability may significantly alter nutrient uptake and
possibly increase tissue temperatures.
One measure of whole-plant water use is WUE. WUE
is calculated as the ratio of plant yield to water use
[(kg ha21)/mm]. Species differ, with WUE of C4 plants
often being twice that of C3 plants. This species differenceis primarily because of the advantage C4 plants have
over C3 plants in rate of Ps. Another factor that increases
WUE is partial stomatal closure, which generally reduces
water loss out of a leaf more than it reduces CO2 uptake
into the leaf, thus increasing dry matter accumulation
per unit of water transpired. However, factors that alter
transpiration will have a direct impact on mass flow of
water to the root surface, and with it, alter the mech-anism of ion transport and possibly nutrient uptake
(see below).
Elevated CO2 alters yield in a species-specific manner
as discussed above (Table 2) and also reduces stomatal
conductance in many species. Bunce (1995) reported
that leaf conductance was reduced in the high CO2 en-
vironment to 77–86% of values found in ambient CO2
conditions. However, Samarakoon and Gifford (1995)reported species differences in the effect of elevated
CO2 on transpiration. For cotton, both transpiration and
growth of cotton were increased at high CO2. In contrast,
transpiration of maize was reduced at high CO2, and
these plants exhibited only a modest increase in plant
biomass. Wheat transpiration was not consistently
affected by high CO2 even though plant growth was
much greater under high CO2. Regardless of stomatalresponse,WUE of all species was greater at elevated CO2
and total water use was reduced when compared with
ambient CO2. Such shifts in water use might alter mass
flow of nutrients to the root surface, change soil moisture
patterns and increase foliage temperatures that could
reduce photosynthesis. Chartzoulakis and Psarras (2005)
suggested that, although high CO2 may improve plant
WUE, reductions in precipitation and increased evapo-transpiration will reduce soil moisture in some parts of
southern Europe. They predicted that this will reduce
photosynthesis and alter soil fertility, including soil
organic matter decomposition and nitrate leaching.
However, Manderscheid and Weigel (2007) showed that
the effect of drought was negated somewhat by elevated
CO2 (550 mmol mol21). When compared with ambient
CO2 conditions, high CO2 increasedWUE by 20% underwell-watered conditions but WUE increased by 42% in
response to high CO2 under drought conditions. These
authors concluded that the negative effects of climate
change-induced drought will be mitigated by high CO2.
Clearly, elevated CO2 will result in site-specific changes
inwater availability, but increases inWUEand reductions
in total water use are expected to influence key plant
functions including root-nutrient contact and plant
growth that, in turn, will alter total nutrient needs.
Influence of climate change on nutrientavailability and acquisition
Increases in air temperature and changes in precipitation
will significantly impact prevailing root zone temperature
and moisture regimes. The nature and extent of the
change in these two parameters will be site- and soil-
specific, reflecting meteorological conditions, soil phys-
ical factors and other surface characteristics including
leaf area index and ground litter stores (Kang et al. 2000).
The primary function of roots is acquisition of nutrientsand water, and the successful root system is one that
is adapted to the local conditions to optimize these
functions. UE reflects a suite of physical, chemical and
biological processes that determine whether a nutrient
ion in the soil is in a form that is available to the root and
whether the plant-available ion is actually acquired by
a root. As reviewed by Jungk (2002), plant availability
of nutrients in the soil is a function of soil chemicalproperties aswell as location of the ion relative to the root
surface and the length of the pathway the nutrient must
travel in the soil to reach the root surface; nutrient
acquisition by the plant reflects an array of physiological
phenomena that govern nutrient transport to and into
roots and can alter aspects of both chemical and posi-
tional nutrient availability in the soil. Given that soil
moisture and temperature are primary determinants ofnutrient availability and root growth and development
and that carbon allocation to roots governs nutrient ac-
quisition, it is reasonable to expect that process outcomes
will be reflective of the changed climate. Furthermore,
there is a significant body of work that suggests the
hypothesis that climate change impacts on nutrient UE
will be primarily affected through direct impacts on root
surface area. The foundation of this hypothesis is the largebody of crop modeling work conducted with process-
based models such as the Barber family of single root
models (Barber and Cushman 1981, Claassen and Barber
1976, Cushman 1979, 1980, Itoh and Barber 1983).
Plants accumulate nutrients from the soil solution pool,
and nutrients must be in solution to be mobile in the soil.
In the absence of roots, steady-state solution-phase
concentrations of nutrient ions are controlled by adsorp-tion–precipitation and desorption–dissolution reactions
between nutrients and the surface complex of soil,
mineralization and immobilization for solutes of organic
origin and additions from fertilizer (Table 3). Given the
importance of C and N cycling to both agricultural
productivity and sustainability, the preponderance of
belowground climate change studies have focused on
712 Physiol. Plant. 133, 2008
Table
3.Im
pactofclim
atechan
geonprocesses
andparam
eterscontrollingnutrientavailability.Forin-dep
thdescriptionofparam
eters,seeBarber
(1995).
Nutrient
availability/acquisition
attribute
Soil/plantcontrols
Controllerparam
eters
Rem
arks
regardingglobalclim
atechan
ge
Presen
ceofnutrients
insoilsolution
Adsorption/desorption
Buffer
power
(b),Temperature
(T),pH,soilmoisture
(u)
andsolutionionicstrength
(m)
IncreasedTmay
increase
process
rates;increasedCO2
may
enhan
cerootexudates
that
alterb,
enhan
cefinerootgrowth
andturnover;chan
ges
inu
causedbychan
ges
inrainfallpatternsmay
enhan
ce
ordep
ress
processes.IncreasedTmay
enhan
cevolatilization
ofsurface-ap
pliedNfertilizers;chan
ges
inrainfallpatterns
may
enhan
ceordep
ress
volatilizationan
dleaching
losses
ofnutrients
Mineralization/im
mobilization
u,T,organ
icmatterquality/quan
tity
andmicrobialactivity
Fertilization
Source,
timing,rate
andplacemen
t
Nutrientmovemen
tMassflow
u,soilphysicalproperties
includingbulkden
sity
andhydraulic
conductivity,soilsolutionconcentration(C
l)
andwater
influxrate
into
roots(v0)
IncreasedCO2may
reduce
tran
spiration,dep
ressing
nutrientmovemen
tto
therootthroughmassflow
butmay
increase
rootexudationan
dfinerootgrowth
enhan
cingb,
Clan
dnutrientmovemen
tthroughdiffusion.Increased
Twillalso
enhan
cenutrientdiffusion;chan
ges
inucausedby
chan
ges
inrainfallpatternsmay
enhan
ceordep
ress
mass
flow
and/ordiffusion
Diffusion
u,tortuosity
(interactivew/u
andphysicalproperties),
T,ban
dnutrientuptake
Nutrientuptake
Morphologyan
darchitecture
Length,diameter,surfacearea,branchingan
dspatial
distribution,distance
betweenroots,roothairsan
d
specialized
structures
Elevated
CO2may
enhan
cefinerootdevelopmen
t.IfT
issuboptimal,increasedTwillen
han
cerootsurfacearea
developmen
t;chan
ges
inucausedbychan
ges
inrainfall
patternsmay
enhan
ceordep
ress
massflow
and/ordiffusion.
Intheo
ry,elevated
CO2should
makemore
carbohydrate
availableforactive
uptake
Kinetics
Tran
sporter
capacity(I m
ax,maxim
um
uptake
rate),affinity
(Km,theMichaelis–M
entonconstan
t)an
defficien
cy
(Cmin,minim
um
soilsolutionconcentrationat
which
net
uptake
canstilloccur)
Physiol. Plant. 133, 2008 713
microbiology. Biological transformation betweenorganic
and inorganic pools is strongly influenced by moisture
and temperature, and thus, global climate change may
strongly influence solution concentrations of N as well as
S. Some have speculated that soil C pool size will not
change as increased soil respiration and decompositioncaused by soil warming will be moderated by the
increased C supply belowground (Kirschbaum 2000).
Others, however, note that interactive and indirect effects
of water and soil nutrient availability may lead to
unexpected outcomes as uncertainties abound in our
understanding of key feedback processes (Pendall et al.
2004). For example, many expect elevated CO2 to in-
crease belowground C that will, in turn, enrich micro-bial C, but Zak et al. (2000) reviewed the literature
on microbial C and N responses to elevated CO2 and
found reports of increases, decreases and no change. For
N, the review of Pendall et al. (2004) suggests that
increased CO2may not exert a significant direct effect on
N mineralization per se but associated warming can
cause increased N mineralization, leading to increased
solution-phase N. While few, if any, studies have ex-amined impacts of elevated CO2 on solution-phase
concentrations of nutrients such as K whose availability
is not strongly controlled by biological activity, theory
suggests that any impacts will also be indirectly mediated
by temperature and moisture changes. Rates of adsorp-
tion/desorption reactions will accelerate with increased
temperature, and changes in soil moisture may further
modify reactions by altering the ionic strength of the soilsolution. However, uncertainties surrounding the magni-
tude of temperature increases coupled with the spatial
and temporal variation in soil moisture make it challeng-
ing to predict how climate change will impact plant K
availability.
Almost 50 years ago, Barber proposed that nutrient
transport through the soil matrix toward roots occurred
by two simultaneous processes: mass flow and diffusion(Barber 1962). As a plant transpires, solution-phase nutri-
ents are transported in the convective movement of water
in the bulk soil toward root surfaces. Quantitatively, mass
flow contributions to a nutrient’s acquisition are the
product of the volume of water transpired (v0) and the
mean solution-phase concentration (Cl, Table 3). For
nutrients that are highly buffered and maintained at low
solution-phase concentrations, mass flow does notdeliver sufficient quantities to the root surface. Therefore,
in the presence of a growing root, concentrations of these
nutrients in the solution immediately adjacent to the root
surface will be depleted. Movement by diffusion is
a function of an ion’s diffusivity in water, the water
content of the soil, the tortuous nature of the pathway an
ionmust travel to reach the root, the buffer power and the
concentration gradient created by root uptake (Table 3).
Barber models and other, similar single- and multi-root
models integrate equations for mass flow and diffusive
flux with equations that characterize development of the
root system and transport across the root membrane, the
latter often based on Michaelis–Menton kinetics tocharacterize plant uptake as a function of ion concentra-
tion at the root surface (see Silberbush 2002 for a brief
review of models and their features).
Root surface area and diffusive flux
Previously and again today, as we consider the impacts of
climate change, the value of these models is that theyallow us to explore specific aspects of UE, factors and
processes that are complex, concomitant and non-linear
and that are time consuming, expensive and extremely
difficult to assess with direct experimentation. Indeed,
questions of the impacts of temperature and moisture on
nutrient availability are not new, even if the specific
condition of elevated CO2 has yet to be explicitly
addressed. Ching and Barber (1979) examined the effectof increasing root zone temperature from 15 to 30�C on
availability and uptake of K by maize seedlings. Raising
root zone temperature increased nutrient uptake in both
fertilized and unfertilized treatments (Fig. 2A). They also
observed a positive impact on both availability and
uptake factors. At 30�C, root surface area was increased
approximately 70% at high and low K fertility; K diffusive
flux increased 160 and 50% in low- and high-fertilitytreatments, respectively. Mackay and Barber (1984)
observed a similar effect on maize P accumulation with
a more moderate temperature comparison (19 vs 25�C;Fig. 2B). Again, marked increases in root surface area at
both high- and low-fertility levels accompanied one- to
two-fold increases in nutrient uptake. Temperature
impacts on diffusive flux were again apparent, although
much smaller in magnitude than the changes in rootsurface area. While changes in temperature with global
climate change are expected to be substantially smaller
than the experimental treatments used in these studies,
there is no reason to expect responses to be different other
than in magnitude. Mackay and Barber (1985) also
examined the effect of drought on P uptake and avail-
ability and found reduced nutrient uptake, root surface
area and ion diffusivity with moisture stress for bothhigh and low fertility (Fig. 2C). In this study, the mois-
ture treatments are directly meaningful in the context
of climate change scenarios.
For many, the observation that increasing soil moisture
and temperature from suboptimal to optimal conditions
increases nutrient diffusion and root growth will
seem obvious. Following the Stokes–Einstein equation,
714 Physiol. Plant. 133, 2008
diffusion of an ion in water is a direct function of both
temperature and viscosity; viscosity itself is a function oftemperature (Barber 1995). At 15�C, the rate of diffusion
is only 78% of the rate at 25�C (Weast 1982). Ion dif-
fusivity rates in soil are a direct function of ion diffusiv-
ity inwater and soilmoisture content. At low soilmoisture
content, the diffusion pathway becomes longer as ions
must travel around expanded air pockets. Likewise, cell
expansion requires adequate water, and species-specific
temperature optimums for root growth have beenextensively documented (for a review, see McMichael
and Burke 2002). However, moving beyond the obvious
effects of temperature and moisture on availability and
acquisition, the more difficult and relevant question
concerns the extent to which a specific factor or suite of
factors contributes to observed reductions in nutrient
uptake. In their study on soil moisture and P, Mackay and
Barber (1984) reported a strong, linear relationship(r2 ¼ 0.96) between root surface area and P uptake
across three soils and three moisture levels. They did not
report the relationship between diffusive flux and P
uptake but plotting their tabular data finds amuchweaker
relationship (r2 ¼ 0.36, P ¼ 0.053; data not shown),
suggesting that root surface area reductions may be more
directly important for P uptake. Separate sensitivity
analysis for model performance in predicting both P andK uptake supports this conclusion (Silberbush and Barber
1983a, 1983b). For both nutrients, varying one model
parameter while holding all others constant identified
root growth rate as the single most influential factor
governing nutrient uptake. Increasing diffusivity did not
greatly increase uptake but, within the parameter ranges
explored, proportional decreases in diffusivity reduced
uptake as much as corresponding changes in root surface
area.Certainly, such sensitivity analyses have their short-
comings. In its most simple form, the approach overlooks
parameter interdependence, and not all parameters
are equally amenable to change. But a more thoughtful
tinkering with parameters coupled with targeted exper-
imentation over widely varied plant–soil systems can
produce solid working hypotheses. As reviewed by
Brouder (1999), investigations of K accumulation byflooded rice (Teo et al. 1992), slash pine seedlings grown
alone and in combination with other species (Van Rees
et al. 1990) and cotton grown in a range of soil conditions
(Brouder and Cassman 1994a) also identified root geo-
metry (length and diameter) as highly sensitive and a
potentially dominating parameter controlling K accumu-
lation. Direct evaluations of genotypic differences in root
geometry and K acquisition efficiency of soybean (Silber-bush and Barber 1984), corn (Schenk and Barber 1980)
and cotton (Brouder and Cassman 1990, 1994b) serve to
further substantiate the relative importance of root growth
when compared with other nutrient availability and
acquisition factors for uptake of relatively immobile
nutrients.
These observations on the importance of root explora-
tion of the soil by enhanced root surface areamay seem tobode well for a changed climate where CO2 fertilization
could increase C available for building additional fine
roots. If root:shoot ratios remain constant but the overall
plant is bigger (as discussed above), there may be more
potential for an enlarged root system to capture the
relatively immobile nutrients. The environment of the
root system is extremely heterogeneous in time and
Fig. 2. The effect of temperature or moisture on nutrient uptake of maize and on selected soil availability and root acquisition parameters. Data are
shown as percentage change from the baseline condition. Data are adapted from experiments where (A) root zone temperatures were increased from15
to 29�C in an unfertilized soil and a soil receiving 500 mg K g21 soil (Ching and Barber 1979), (B) root zone temperatureswere increased from18 to 25�Cin a low- and high-P fertility soil (Mackay and Barber 1984) and (C) root zone soil moisture was reduced in soil water potential from233 to2170 kPa in
a low- and high-P fertility soil (Mackay and Barber 1985).
Physiol. Plant. 133, 2008 715
space; the adaptation of extreme phenotypic plasticity to
exploit such an environment is a key attribute of success
(Fitter 2002). Crop plants are expected to be particularly
plastic in response to patchy nutrient availability as such
plants were initially not only adapted to but also
improved in their ability to be strongly responsive toenhanced nutrient supply. As documented in classic
experiments by Drew, fine roots proliferate in zones
enriched with nutrients, particularly NH14 , NO2
3 and P
(Drew 1975, Drew and Saker 1975, 1978, Drew et al.
1973). This phenomenon has been repeatedly shown
both in controlled environment and in the field for many
major crop species [e.g. sorghum-sudangrass (Pothuluri
et al. 1986), winter wheat (Newman and Andrews 1973),corn (Zhang and Barber 1993) and cotton (Brouder and
Cassman 1994b)]. As summarized in several reports
(Lynch and St Clair 2004, Pendall et al. 2004), a few
studies have suggested that root architecturemay respond
to elevated CO2. For example, Pritchard and Rogers
(2000) proposed that elevated CO2 would stimulate
lateral branching, particularly in surface horizons. But
such responses and/or their benefits may be conditionalupon other climate change variables and the quantity and
distribution of nutrients. Some studies have suggested that
elevated CO2 may help negate the impact of increased
temperatures that exceed the optimum for root growth
(Bassow et al. 1994, Wan et al. 2004). In studies of
amodel grassland,Maestre and Reynolds (2006) reported
that belowground biomass increased in response to high
CO2 but only if high levels of nutrients were provided;root proliferation into nutrient patches increased with
increasing nutrient availability but was not influenced by
ambient CO2. As can readily be seen with modeling
studies, root proliferation is of no benefit if roots are
competing with each other. Thus, we may be headed
toward a not too surprising conclusion that growing
a bigger plant with CO2 fertilization may require en-
hanced nutrient inputs.
Water influx and mass flow
In general, model simulations for immobile nutrients
have not been very sensitive to changes in the rate of
water influx into the root (Silberbush and Barber 1983a,
1983b), a point relevant to discussions of the positive
influence of CO2 fertilization on plant WUE. Underconditions of reduced transpiration, some have theorized
that acquisition of nutrients that travel frombulk soil to the
root surface primarily by mass flow will be negatively
affected, resulting in nutrient deficiency (Lynch and St
Clair 2004). Nutrients long considered to be delivered
primarily bymass flow include soil-mobile nutrients such
as nitrate and sulfate and soil-exchangeable nutrients
such asMg andCa that are abundant in the solution phase
but required in relatively small quantities by the plant
(Barber 1995). However, reducing mass flow to a point
where it restricts nutrient delivery but does not cause
a more direct effect of water stress (e.g. reduced root
growth) seems unlikely. Diffusion and mass flow are notmutually exclusive deliverymechanisms; the process that
dominates is not an attribute of the nutrient itself but
a reflection of root zone conditions. When the product of
water uptake per unit root surface area (v0) and ion
concentration in the soil solution (Cl) are equivalent to the
plants needs (Imax, Table 3), mass flow will clearly be
the dominant mode of solute transport to the root (in the
context of the Cushman–Barber model, v0Cl ¼ Imax), butwhen v0Cl < Imax, diffusion contributes to nutrient trans-
port. The Ching and Barber (1979) study discussed above
can be used to illustrate this point. Adding 500 mg K g21
soil increased v0Cl from 3.2 � 1028 to 4.8 � 1026 mmol
cm22 s21, while Imax remained constant at 5.6 � 1027
mmol cm22 s21, switching the dominant transport pro-
cess from diffusion to mass flow (at 15�C, calculatedfrom Ching and Barber 1979). Rerunning the model(Version 1.1, Oates and Barber 1987) and reducing v0to 1 � 1027 cm s21, a >85% reduction does not effect
simulated K uptake for either fertility treatment (<1.5%
uptake reduction; model output not shown). Indeed, Van
Vuuren et al. (1997) showed this phenomenon with
wheat grown in elevated ambient CO2 under conditions
of ample and restricted soil moisture. Transpiration was
repressed at 700 mmol CO2 mol21 but plant P acquisi-tion was not impacted by dry soil conditions. Thus, in
terms of transport, any nutrient stress resulting from
reduced transpiration would likely reflect the failure of
the secondary process of diffusion to deliver adequate
nutrients to the root surface.
Uptake kinetics
Model simulations of uptake of Pand K have also not been
particularly sensitive to changes in kinetic aspects of
acquisition, but this approach may not be sufficiently
rigorous to address the importance of variation in kinetics
to UE. Recent advances in molecular genetics permit
a more critical evaluation of questions focused on the
limitations imposed by kinetic parameters of nutrient
uptake than was previously possible. Genes and compli-mentaryDNAs for dozensof high-affinity nutrient-specific
ion carriers have been cloned and characterized. Expres-
sion of these genes can be driven to high levels by root-
specific and constitutive promoters. Working in model
systems, Misson et al. (2005) identified genes related to
high-affinity P transport across membranes, genes that
Raghothama (2000) had proposed would be critical to
716 Physiol. Plant. 133, 2008
root acquisition of P from low P soils. BassiriRad (2000)
proposed that altering nutrient uptake to meet plant needs
in a changing environment would be best accomplished
by focusing on high-affinity nutrient transporters and their
kinetic parameters. In theory, elevated CO2 should permit
upregulation of transporters as there would be a higheravailability of carbohydrates to meet transporter energy
requirements (Bielenberg andBassiriRad2005).However,
the effectiveness of molecular engineering the kinetic
aspects of nutrient uptake to negate the consequences of
global change has not been critically evaluated.
The advent of molecular techniques has made it
possible to examine the importance of gene expression
for regulation of nutrient uptake across the cell mem-brane. We explored the impact of expression of high-
affinity P transporters on tobacco (Nicotiana tabacum L.)
growth and P uptake (A.S. Berg, 2004, Thesis, Purdue
University, West Lafayette, IN, USA). Expression of high-
affinity P transporter genes from yeast and Arabidopsis,
driven by a constitutive promoter and measured as
transcript abundance, was very high in both root and
shoot tissues. Two control groups were included: trans-genic plants containing the transformation vectorwithout
a P transporter insert and a commercial tobacco cultivar,
W-38. Plants were grown for 7 weeks in soils that had
either low or high soil test P concentrations, and dry
weights and plant P content were measured 4, 5, 6 and
7 weeks after transplanting. As expected, plant growth
andP uptakeweremuchgreater in the high-P soil than the
low-P soil (Fig. 3). Growth and P uptake of the transgenicplants containing the high-affinity P transporters were
similar to the transgenic control plants without the P
transporter insert in both soils. At week 4 in high-P soil,
growth of the commercial cultivar W-38 was less than
both plants transformed with P transporters, and P uptake
of W-38 was reduced when compared with the trans-
formed control plants. However, by week 7, P uptake of
W-38 in the high-P soil was greater than that of the otherplants. There was no influence of overexpression of either
yeast or Arabidopsis P transporter gene on P uptake and
plant growth in the low-P soil.
To date, our study is one of only a very limited number
of studies where transgenic approaches to improve
nutrient uptake have been examined in soils. Recently,
Park et al. (2007) have reported that constitutive ex-
pression of a high-affinity P transporter from tobaccocould increase tissue P concentrations of rice. Although
these authors observed higher instantaneous uptake rates
of 32P in transgenic plants compared with untransformed
control plants, total P uptake was not reported because
tissue mass data were not assessed. Therefore, the re-
ported growth reductions (qualitative results only) were
possibly confounded with observations of higher tissue P
concentrations. Surprisingly, a comprehensive survey of
the literature revealed no published reports focusing on
upregulation of K transporters and its impact on K uptake
from soil. Numerous studies have reported induction of
K transporters in roots exposed to low media (not soil) K
concentrations (Ashley et al. 2006 and references cited
therein) and imply that these changes are essential to
maintain rapid K uptake as solution K concentrationsdecline. However, Garciadeblas et al. (2007) recently
suggested that K transporters may have broader functions
in plants including high-affinity K uptake, K efflux into the
media to reduce tissue K concentrations and as a link
between K nutrition and root morphogenesis. This sug-
gests that the roles of K transporters may go beyond
merely facilitating K uptake across the plasmamembrane
at low K concentrations. Clearly, even without climatechange as an additional variable, we posses only a rudi-
mentary understanding of the role of transporters in
nutrient uptake from soil.
Fig. 3. Trends in total biomass and plant P uptake of tobacco lines grown
in high- and low-P soils during weeks 4–7 posttransplanting. Two lines
contained constitutively expressed high-affinity P transporter genes from
yeast and Arabidopsis, one control line was transformed with the vector
alonewithout a P transporter gene and the fourth linewas the commercial
cultivar W-38. Asterisks indicate dates where significant differences
between W-38 and the other lines occurred (see text for details).
Physiol. Plant. 133, 2008 717
Under P-limited conditions, upregulation of P trans-
porters is just one of several known physiological mech-
anisms plants can use to enhance P uptake. A key
additional physiological mechanism is the secretion of
organic acids (Sanchez-Calderon et al. 2006), also an
important factor for mobilizing other, relatively insol-uble nutrients including Fe (Lynch and St Clair 2004).
Theoretically, enhanced allocation of C belowground as
a result of global climate change could alter the quantity
and quality of exudates that may benefit nutrient uptake
in soils where acidity or alkalinity limit nutrient solubility.
As reviewed by Lynch and St Clair (2004), only a few
studies have critically examined this hypothesis, and
results to date have been mixed; Norby et al. (1987),Hodge (1996) and Uselman et al. (2000) found no effect
of elevated CO2 on exudates, while Hodge and col-
leagues observed reduction in volume and changes in
composition of exudates (Hodge and Millard 1998,
Hodge et al. 1998). As repeatedly remarked in the liter-
ature, the area of root uptake responses to global climate
change are understudied and requiremuchmore intensive
study (BassiriRad 2000, Lynch and St Clair 2004, Pendallet al. 2004).
Conclusions: managing plant nutrition ina changed climate
What are the practical implications of the above
discussions? First and foremost is the concept that crop
plants may be bigger, smaller or similar in size whencompared with today’s specimens, but their nutrient
content and PE will be scaled according to size. To date,
experimentation on crop plants has not found conclusive
evidence that PE is altered in high CO2 environments
(Long et al. 2006). The observation of Schimel (2006) that
‘Some set of biological processes appears to operate to
reduce the impact of CO2 on realized gains in biomass
and yield below that expected from the effects ofphotosynthesis.’ can be viewed as a simple restatement
of the Law of the Minimum within the context of global
climate change. Clearly, nutrient stress has the potential
to reduce growth stimulation by elevated CO2 (Campbell
and Sage 2006, Lynch and St Clair 2004). Modest, crop-
specific benefits in agricultural yieldsmay be realized but
only where nutrient availability can be optimized and
where climate change increases temperatures to a spe-cies-specific optimum and changes precipitation patterns
to reduce water stress (drought or flooding) days. C3
species may also accrue a direct benefit from CO2
fertilization. Nutrient recommendations for a changed
climate will operate on the same premise as current
recommendations – an understanding of the PE that is
specific to the crop and of the UE that is specific to the
unique combination of crop and soil. Simple, empirical
models will continue to be used to translate this in-
formation from theory into practice. We anticipate that
major portions of today’s soil fertility/plant nutrition
recommendations will remain viable irrespective of
climate change.
Implications for nutrient management
Nutrient replacement is a core tenet of many existing
recommendations for sustainable management of rela-
tively immobile nutrients. If plants produced under
elevated CO2 are simply bigger, but otherwise the same
in their gross nutrient content per unit biomass, thenpresent-day nutrient balance calculations for fertilizer
recommendationswill remain applicable. In crop species
that have been extensively improved for agriculture,
nutrient concentrations, especially in grain, can be
relatively constant when yields are not limited by other
factors. Dobermann et al. (1996a) examined irrigated rice
yields and grain composition in the Philippines, Indo-
nesia, Vietnam, China and India and determined that theK concentrations of modern rice varieties were fairly
constant across environments. Fifty percent of all samples
analyzed ranged from 2.5 to 3.3 mg kg21. In a 6-year
study conducted at five locations on widely varying soils,
we have also documented relatively constant nutrient
concentrations in high-yieldingmaize and soybean grain.
Across site-years, P, K and Mg concentrations in maize
grain (yields >10 000 kg ha21) averaged 3.3, 3.9 and1.3 mg kg21, respectively; P, K andMg concentrations in
soybean grain (yields>3500 kg ha21) averaged 5.5, 18.3
and 2.4 mg kg21, respectively (Table 4). Standard devia-
tions in nutrient concentrations were relatively similar
between species, although coefficients of variation
tended to be lower in soybean, reflecting its higher
concentration values. When these average removal
values are used to estimate actual crop removal over thefull range of yielding environments, the relationship
between predicted and measured values is very strong.
For example, the predicted:measured relationship for
yearly K removal is close to unity for both crops (Table 4,
Fig. 4A). The predicted:measured relationship for 6-year
cumulative removal of a maize–soybean rotation has
a 1:1 relationship across all locations (Fig. 4B).
Therefore, provided we continue to pursue a nutrientreplacement philosophy, changes in regional input re-
quirements will be most remarkable where we alter the
cropping system to accommodate shifts in crop ecozones
or alter the farming system to capture new uses from
existing systems (e.g. use of whole-plant maize for bio-
fuels). Climate change may disproportionately increase
the risks of growing one crop species when compared
718 Physiol. Plant. 133, 2008
with an acceptable alternative. Southworth et al. (2000)suggest that variation by 2050 may increase risks
associated with growing maize in southern regions of
the Cornbelt, and growers may elect to modulate risk by
growing a different crop that is better suited to the
emerging ecozone. These authors suggest that growers
may benefit fromplanting indeterminant crop species like
soybean in place of maize to deal with the greater
potential risks associatedwith increased climate variationand, at the same time, derive benefit from increased CO2
that occurs when growing a C3 crop species.
Changes in demand for agricultural products may also
cause dramatic changes in regional requirements for
nutrient inputs. Shortages of fossil fuels and an aggressive
bioenergy agenda shifted large areas of the US Cornbelt
from a maize–soybean rotation to continuous maizeproduction in 2007. Despite lower grain concentrations
of all nutrients (Table 4), maize’s higher yields and lack of
N2 fixation will significantly increase input requirements
for P and N, although K input requirements will be
reduced. In grain crops where cellulosic biomass may
eventually also be harvested, nutrients removed in
residue will need to be replaced and this could require
significant new inputs. For the 74 million ha of irrigatedrice in Asia, Dobermann et al. (1996a) estimate that
harvesting straw for fuel will increase crop K removal
at least five-fold from 0.9–1.2 million t year21 to 5–9
million t year21. Furthermore, residue removal itself
may reduce soil nutrient supply as residue return both
protects against soil erosion loss and replenishes soil
Table 4. Nutrient concentrations in high-yielding maize and soybean grown in Indiana, USA. For all observations, maize (n ¼ 358) and soybean
(n ¼ 474) yields exceeded 10 and 3.5 Mg ha21, respectively. Regression relationship is for all observations in a 6-year, five location (60 plots location21)
study ofmaize–soybean rotations. Predicted values are the product of yield andmean nutrient concentration; observed values are the product of yield and
the measured concentration in subsamples from each plot-year. NS, P > 0.05.
Nutrient
Grain nutrient concentration Nutrient removal regression: observed vs predicted
Mean (mg kg21) SD
Coefficient of
variation (%) Slope Intercept r2
Maize Soy Maize Soy Maize Soy Maize Soy Maize Soy Maize Soy
N 13.7 63.1 1.43 2.72 10.5 4.3 0.97 0.99 4.10 NS 0.81 0.96
P 3.3 5.5 0.72 0.49 22.0 8.9 1.09 1.02 23.42 NS 0.62 0.85
K 3.9 18.3 0.70 1.42 17.8 7.8 1.10 1.07 24.01 24.81 0.70 0.90
Mg 1.3 2.4 0.29 0.30 22.8 12.7 1.05 1.00 21.09 NS 0.60 0.77
S 1.1 3.5 0.18 0.41 16.4 11.8 0.93 1.07 0.66 21.04 0.69 0.82
Ca 0.1 2.6 0.04 0.37 41.2 14.3 0.95 1.01 NS NS 0.30 0.71
Fig. 4. Relationship between measured K removal by maize and soybean crops and predicted K removal based on crop yields and an assumed constant
unit removal value (3.9 and 18.3 mg K kg21 grain dry weight for maize and soybean, respectively; Table 4). Data are from a 6-year, five location, 60 plots
location21 study conducted in Indiana, United States. Data shown are for (A) annual crop removal in each experimental plot and (b) 6-year cumulative
removal in each experimental plot by the maize–soybean rotation. Different symbols are used to identify crop (A) or experimental location (B).
Physiol. Plant. 133, 2008 719
organic C. As discussed above, soil organic C is an im-
portant source of nutrients such as N and helps retain
availability of nutrients such as Fe that can form organic
chelates. Limited research has shown that maize stover
removal can lower grain and stover yields of subsequent
crops and also soil C pools (Wilhelm et al. 1986). Whilethe dynamics of governing biomass conversion to soil
organic C is not well understood and is a subject of
intensive ongoing research (Wilhelm et al. 2007), residue
removal drives changes in soil energy balance. Bare soils
can be >5�C warmer with much higher surface evapo-
transpiration than residue covered soils (reviewed by
Wilhelm et al. 2004), resulting in altered rates of min-
eralization and nutrient diffusion.For regions and systems where we currently do an
adequate jobmanaging nutrients, we stand a good chance
of continuing to optimize nutrient use under a changed
climate. If we can and should do better, climate change
will not help us. To this end, the irrigated rice study of
Dobermann et al. (1996a, 1996b) not only serves
a cautionary warning but also highlights a key aspect of
nutrient management in need of improvement. Theyconclude that current recommendations for K fertilizer
additions in most intensive irrigated rice domains do not
replace the K removed in present-day yields; they remark
that with either increased yields from technology or straw
removal without any increase in yield, K removal will far
exceed the present fertilizer levels and deplete soil K
reserves, ultimately degrading the soil resource. Driving
this imbalance is a lack of appreciation or perhapsknowledge of the K-supplying power of the soil, that
specific combination of the crop and soil that governs UE
(Dobermann et al. 1996b). Review of existing recom-
mendations for the US Cornbelt suggests that this problem
is not unique to Asian rice production. Despite extensive
scientific study and available tools (e.g. high-resolution
soil surveys and spatially and temporally intensive soil
testing results), current recommendations are not welltailored to knownsoil- and crop-specific differences inUE.
Long-term studies in Indiana suggest that additional rates
of 7.5–20 kg ha21 are required to increase available K in
actively farmed soils by 1 mg kg21 for a range of major
agronomic soils (Li and Barber 1988 and ongoing studies)
but recommendations call for only 4.5–7.5 kg ha21
(Vitosh et al. 1995) to achieve this change. The reason
for this clear disconnection between the recommenda-tions for K management and the observations of local soil
responses has been difficult to discern. Thus, while the
empirical model that addresses nutrient replacement is
good, the empiricalmodel for soilmanagement appears to
require significant improvements in at least a few major
agronomic regions if we are to achieve optimum AE in
both present and future production.
Implications for crop improvement
Finally, in our discussions of plant growth and nutrient
needs in a changed climate, we should not overlook the
combined forces of crop improvement and genetic
variation/natural selection. To date, most experimenta-
tion on the effects of elevated CO2 on plant production,
including the elaborate FACE studies, has been con-
ducted by imposing elevatedCO2 levels on plantmaterial
adapted to current atmospheric composition. Genotypic
variation in traits influencing phenotypic expression and
plasticity in important plant attributes such as root
architecture and exudation will allow continued drift
toward form and function adapted to changed conditions.
The Cook et al. (1998) study of evolution of N. strictus
ecotypes under 790 mmol CO2 mol21 is a persistent re-
minder that we should be cautious in drawing conclu-
sions when skipping a 100 years of selection pressure.
Crop improvement efforts will only hasten the process as
suggested by a recent analysis of shifting agroecozones in
the United States. In a study initially designed to examine
the effect that climate change has had to date on cropping
patterns, Reilly et al. (2003) analyzed the geographic
centers of production for maize, soybean and wheat over
the last 100 years. They found a significant north and
westward shift in centroids for both maize and soybean
production, and this shift was accompanied by a 4�Cdecrease in temperature despite an estimated US warm-
ing trend of 0.6�C. This shift reflects management and
genetic technologies including development of new
varieties of soybean that are adapted to longer photo-
periods and earlier maturing maize hybrids that
decreased risk because of early frost. The authors remark
that in the last 100 years, we have seen adaptation to the
magnitude of temperature change that we expect for the
coming century, albeit in the opposite direction.
As noted in the beginning of the paper, pursuit of
adaptive technologies will certainly mitigate negative
impacts and enhance advantages for future plant growth.
While the promise of enhanced nutrient uptake through
transgenic manipulation of transports has yet to be
realized and more research is needed, morphological
traits may be as or more promising crop improvement
targets. As summarized by Lynch (2007), these include
greater root biomass, greater root surface area, longer/
denser root hairs, more adventitious, smaller diameter
roots and shallower basal roots in surface soils and an
architecture that features more dispersed laterals. Other
desirable features are enhanced exudation and mycor-
rhizal symbiosis. For emerging crop species that do not
have a long crop improvement history (e.g. canola;
Svecnjak andRengel 2006), breeding to improvePE (yield
as a function of tissue nutrient content) may afford
720 Physiol. Plant. 133, 2008
significant opportunities as well. Irrespective of climate
change impacts, improvedAEwill be increasingly critical
as cost and availability of scarce resources – food and fuel
– constrain their use. Access to and deployment of such
technology will be as important a driver of realized
changes in production patterns as the increased ambientCO2 and temperature and altered precipitation patterns.
References
Ashley MK, Grant M, Grabov A (2006) Plant responses to
potassium deficiencies: a role for potassium transport
proteins. J Exp Bot 57: 425–436
Atkin OK, Bruhn D, Hurry VM, Tjoelker MG (2005) The hot
and the cold: unraveling the variable response of plant
respiration to temperature. Funct Plant Biol 32: 87–105
Barber SA (1962) A diffusion and mass-flow concept of soil
nutrient availability. Soil Sci 93: 39–49
Barber SA (1995) Soil Nutrient Bioavailability: A Mechanistic
Approach, 2nd Edn. John Wiley and Sons, Inc, New York,
pp 414
Barber SA, Cushman JH (1981) Nitrogen uptake model for
agronomic crops. In: Iskandar IK (ed) Modeling Waste
Water Renovation – Land Treatment. Wiley-Interscience,
New York, pp 382–409
Barrett DJ, Gifford RM (1995) Photosynthetic acclimation to
elevated CO2 in relation to biomass allocation in cotton.
J Biogeogr 22: 331–339
BassiriRad H (2000) Kinetics of nutrient uptake by roots:
responses to global climate change. New Phytol 147:
155–169
Bassow SL, McConnaughay KDM, Bazzaz FA (1994) The
response of temperate tree seedlings grown in elevated
CO2 to extreme temperature events. Ecol Appl 4: 593–603
Bielenberg DG, BassiriRad H (2005) Nutrient acquisition of
terrestrial plants in a changing climate. In: BassiriRad H
(ed) Nutrient Acquisition by Plants: An Ecological
Perspective. Springer-Verlag, New York, pp 311–329
Brouder SM (1999) Modeling soil-plant potassium relations.
In: Oosterhuis DM, Berkowitz GA (eds) Frontiers in
Potassium Nutrition: New Perspectives on the Effects of
Potassium in Physiology of Plants. Potash and Phosphate
Institute, Norcross, GA, pp 143–153
Brouder SM, Cassman KG (1990) Root development of
two cotton cultivars in relation to potassium uptake and
plant growth in vermiculitic soil. Field Crops Res 23:
187–203
Brouder SM, Cassman KG (1994a) Evaluation of
a mechanistic model of potassium uptake by cotton in
vermiculitic soil. Soil Sci Soc Am J 58: 1174–1183
Brouder SM, Cassman KG (1994b) Cotton root and shoot
response to localized supply of nitrate, phosphate and
potassium: split-pot studies with nutrient solution and
vermiculitic soil. Plant Soil 161: 179–193
Brown RA, Rosenberg NJ (1999) Climate change impacts on
the potential productivity of corn and winter wheat in their
primary United States growing regions. Clim Change 41:
73–107
Bunce JA (1995) Long-term growth of alfalfa and orchard grass
plots at elevated carbon dioxide. J Biogeogr 22: 341–348
Campbell CD, Sage RF (2006) Interactions between the
effects of atmospheric CO2 content and P nutrition on
photosynthesis in white lupine (Lupinus albus L.). Plant
Cell Environ 29: 844–853
Casella E, Soussana J-F (1997) Long-term effects of
CO2 enrichment and temperature increase in the
carbon balance of a temperate sward. J Exp Bot 48:
1309–1321
Chapin FS III (2003) Effects of plant traits on ecosystem and
regional processes: a conceptual framework for predicting
the consequences of global climate change. Ann Bot 91:
455–463
Chartzoulakis K, Psarras G (2005) Global change effects on
crop photosynthesis and production in Mediterranean: the
case of Crete, Greece: photosynthesis and abiotic stresses.
Agric Ecosyst Environ 106: 147–157
Ching PC, Barber SA (1979) Evaluation of temperature effects
on K uptake by corn. Agron J 71: 1040–1044
Claassen N, Barber SA (1976) Simulation model for nutrient
uptake from soil by a growing plant root system. Agron J
68: 961–964
Cook AC, Tissue DT, Roberts SW, Oechel WC (1998) Effects
of long-term elevated [CO2] from natural CO2 springs on
Nardus stricta: photosynthesis, biochemistry, growth and
phenology. Plant Cell Environ 21: 417–425
Cushman JH (1979) An analytical solution to solute transport
near root surfaces for low initial concentration: II.
Applications. Soil Sci Soc Am J 43: 1090–1095
Cushman JH (1980) Analytical study of the effect of ion
depletion (replenishment) caused by microbial activity
near roots. Soil Sci 129: 69–87
Darwin R, Tsigas M, Lewandrowski J, Raneses A (1995)
World Agriculture and Climate Change: Economic
Adaptations. USDA Econ Res Serv, Washington, DC,
AER-703 (June)
Dermody O (2006) Mucking through multifactor
experiments; design and analysis of multifactor studies in
global change research. New Phytol 172: 598–600
Derner JD, Johnson HB, Kimball BA, Pinter PJ, Polley HW,
Tischler CR, Boutton TW, Lamorte RL, Wall GW, Adam
NR, Leavitt SW, Ottman MJ, Matthias AD, Brooks TJ (2003)
Above- and below-ground responses of C3-C4 species
mixtures to elevated CO2 and soil water availability. Glob
Chang Biol 9: 452–460
Dobermann A, Cassman KG, Sta. Cruz PC, Adviento MA,
Pampolino MF (1996a) Fertilizer inputs, nutrient balance,
and soil nutrient-supplying power in intensive, irrigated
rice systems. I: potassium uptake and K balance. Nutr Cycl
Agroecosyst 46: 1–10
Physiol. Plant. 133, 2008 721
Dobermann A, Cassman KG, Sta. Cruz PC, Adviento MA,
Pampolino MF (1996b) Fertilizer inputs, nutrient balance,
and soil nutrient-supplying power in intensive, irrigated
rice systems. II: effective soil K-supplying capacity. Nutr
Cycl Agroecosyst 46: 11–21
Drew MC (1975) Comparison of the effects of a localized
supply of phosphate, nitrate, ammonium and potassium on
the growth of the seminal root system, and the shoot, in
barley. New Phytol 75: 479–490
Drew MC, Saker LR (1975) Nutrient supply and the growth of
the seminal root system in barley. II. Localized,
compensatory increases in lateral root growth and rates of
nitrate uptake when nitrate supply is restricted to only part
of the root system. J Exp Bot 26: 79–90
Drew MC, Saker LR (1978) Nutrient supply and the growth of
the seminal root system in barley. III. Compensatory
increases in growth of lateral roots, and in rates of
phosphate uptake, in response to a localized supply of
phosphate. J Exp Bot 29: 435–451
Drew MC, Saker LR, Ashley TW (1973) Nutrient supply and
the growth of the seminal root system in barley. I. The
effect of nitrate concentration on the growth of axes and
laterals. J Exp Bot 24: 1189–1202
Dunn AL, Barford CC, Wofsy SC, Goulden ML, Daube BC
(2007) A long-term record of carbon exchange in a boreal
black spruce forest: means, responses to interannual
variability, and decadal trends. Glob Chang Biol 13:
577–590
El Kohen A, Mousseau M (1994) Interactive effects of
elevated CO2 and mineral nutrition on growth and CO2
exchange of sweet chestnut seedlings (Castanea sativa).
Tree Physiol 14: 679–690
Fitter A (2002) Characteristics and functions of root systems.
In: Waisel Y, Eshel A, Kafkafi U (eds) Plant Roots: The
Hidden Half, 3rd Edn. Marcel Dekker, New York, pp 15–32
Garciadeblas B, Barrero-Gil J, Benito B, Rodriguez-Navarro A
(2007) Potassium transport systems in the moss
Physcomitrella patens: pphak1 plants reveal the
complexity of potassium uptake. Plant J 52: 1080–1093
Gerloff GC, Gabelman WH (1983) Genetic basis of inorganic
plant nutrition. In: Lauchli A, Bieleski RL (eds) Inorganic
Plant Nutrition, Encyclopedia of Plant Physiology, Vol.
15A. Springer-Verlag, New York, pp 453–480
Goudriaan J, Zadoks JC (1995) Global climate change:
modeling the potential response of agro-ecosystems with
special reference to crop protection. Environ Pollut 87:
215–224
Guehl JM, Picon C, Aussenac G, Gross P (1994) Interactive
effects of elevated CO2 and soil drought on growth and
transpiration efficiency and its determinants in two
European forest tree species. Tree Physiol 14:
707–724
Hill PW, Marshall C, Williams GG, Blum H, Harmens H,
Jones DL, Farrar JF (2007) The fate of
photosynthetically-fixed carbon in Lolium perenne
grassland as modified by elevated CO2 and sward
management. New Phytol 173: 766–777
Hobbie SE, Nadelhoffer KJ, Hogberg P (2002) A synthesis:
the role of nutrients as constraints on carbon balances
in boreal and arctic regions. Plant Soil 242:
163–170
Hodge A (1996) Impact of elevated CO2 on mycorrhizal
associations and implications for plant growth. Biol Fertil
Soils 23: 388–398
Hodge A, Millard P (1998) Effect of elevated CO2 on carbon
partitioning and exudate release from Plantago lanceolata
seedlings. Physiol Plant 103: 280–286
Hodge A, Paterson E, Grayston SJ, Campbell CD, Ord BG,
Killham K (1998) Characterisation and microbial
utilisation of exudate material from the rhizosphere of
Lolium perenne grown under CO2 enrichment. Soil Biol
Biochem 30: 1033–1043
Intergovernmental Panel on Climate Change (2007) Climate
Change 2007: The physical Science Basis. Contribution of
Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change. Solomon S,
Qin D, Manning M, Chen Z, Marguis M, Averyt KB, Tignor
M, Miller HL (eds). Cambridge University Press,
Cambridge, UK, pp 23–27
Itoh S, Barber SA (1983) A numerical solution of whole plant
nutrient uptake for soil-root systems with root hairs. Plant
Soil 70: 403–413
Izaurralde RC, Rosenberg NJ, Brown RA, Thomson AM
(2003) Integrated assessment of Hadley Center (HadCM2)
climate-change impacts on agricultural productivity and
irrigation water supply in the conterminous United States.
Agric For Meteorol 117: 97–122
Jackson RB, Luo Y, Cardon ZG, Sala OE, Field CB, Mooney
HA (1995) Photosynthesis, growth and density for the
dominant species in a CO2-enriched grassland. J Biogeogr
22: 221–225
Jones CA, Kiniry JR (1986) CERES–Maize. A Simulation
Model of Maize Growth and Development. Texas A&M
University Press, College Station, TX
Jungk AO (2002) Dynamics of nutrient movement at the
soil-root interface. In: Waisel Y, Eshel A, Kafkafi U (eds)
Plant Roots: The Hidden Half, 3rd Edn. Marcel Dekker,
New York, pp 587–616
Kang S, Kim S, Oh S, Lee D (2000) Predicting spatial and
temporal patterns of soil temperature based on topography,
surface cover and air temperature. For Ecol Manage 136:
173–184
Kirschbaum MUF (2000) Will changes in soil organic carbon
act as a positive or negative feedback in global warming?
Biogeochemistry 48: 21–51
Li R-G, Barber SA (1988) Effect of phosphorus and potassium
fertilizer on crop response and soil fertility in a long term
experiment. Fertil Res 15: 123–136
Long SP, Ainsworth EA, Leakey ADB, Nosberger J, Ort DR
(2006) Food for thought: lower-than-expected crop yield
722 Physiol. Plant. 133, 2008
stimulation with rising CO2 concentrations. Science 312:
1918–1921
Lynch JP (2007) Roots of the second green revolution. Aust J
Bot 55: 493–512
Lynch JP, St Clair SB (2004) Mineral stress: the missing link in
understanding how global climate change will affect
plants in real world soils: linking functional genomics with
physiology for global change research. Field Crops Res 90:
101–115
Mackay AD, Barber SA (1984) Soil temperature effects on
root growth and phosphorus uptake by corn. Soil Sci Soc
Am J 48: 818–823
Mackay AD, Barber SA (1985) Soil moisture effects on root
growth and phosphorus uptake by corn. Agron J 77:
519–523
Maestre FT, Reynolds JF (2006) Spatial heterogeneity
in soil nutrient supply modulates nutrient and biomass
responses to multiple global change drivers in model
grassland communities. Glob Chang Biol 12:
2431–2441
Manderscheid R, Weigel H-J (2007) Drought stress effects on
wheat are mitigated by atmospheric CO2 enrichment.
Agron Sustain Dev 27: 79–87
Mann ME, Bradley RS, Hughes MK (1998) Global-scale
temperature patterns and climate forcing over the past six
centuries. Nature 392: 779–787
McMichael BL, Burke JJ (2002) Temperature effects on root
growth. In: Waisel Y, Eshel A, Kafkafi U (eds) Plant Roots:
The Hidden Half, 3rd Edn. Marcel Dekker, New York,
pp 717–728
Misson J, Raghothama KG, Jain A, Jouhet J, Block MA, Bligny
R, Ortet P, Creff A, Somerville S, Rolland N, Doumas P,
Nacry P, Herrerra-Estrella L, Nussaume L, Thibaud MC
(2005) A genome-wide transcriptional analysis using
Arabidopsis thaliana Affymetrix gene chips determined
plant response to phosphate deprivation. Proc Natl Acad
Sci USA 102: 11934–11939
Newman EI, Andrews RE (1973) Uptake of phosphorus and
potassium in relations to root growth and root density.
Plant Soil 38: 49–69
Newman JA, Abner ML, Dado RG, Gibson DJ, Brookings A,
Parsons AJ (2003) Effects of elevated CO2, nitrogen and
fungal endophyte-infection on tall fescue: growth,
photosynthesis, chemical composition and digestibility.
Glob Chang Biol 9: 425–437
Norby RJ, O‘Neill EG, Hood WG, Luxmoore RJ (1987)
Carbon allocation, root exudation and mycorrhizal
colonization of Pinus echinata seedlings grown under CO2
enrichment. Tree Physiol 3: 203–210
Oates K, Barber SA (1987) Nutrient uptake: a microcomputer
program to predict nutrient absorption from soil by roots.
J Agron Educ 16: 65–68
Park M, Baek S-H, de los Reyes B, Yun S (2007)
Overexpression of a high-affinity phosphate transporter
gene from tobacco (NtPT1) enhances phosphate uptake
and accumulation in transgenic rice plants. Plant Soil
292: 259–269
Pendall E, Bridgham S, Hanson PJ, Hungate B, Kicklighter
DW, Johnson DW, Law BE, Luo Y, Megonigal JP, Olsrud M,
Ryan MG, Wan S (2004) Below-ground process responses
to elevated CO2 and temperature: a discussion of
observations, measurement methods, and models. New
Phytol 162: 311–322
Porter JR, Semenov MA (2005) Crop responses to climatic
variation. Phil Trans R Soc Lond B Biol Sci 360:
2021–2035
Pothuluri JV, Kissel DE, Whitney DA, Thien SJ (1986)
Phosphorus uptake from soil layers having different soil
test phosphorus levels. Agron J 78: 991–994
Pritchard SG, Rogers HH (2000) Spatial and temporal
deployment of crop roots in CO2-enriched environments.
New Phytol 147: 55–71
Raghothama KG (2000) Phosphorus acquisition; plant in the
driver’s seat. Trends Plant Sci 5: 412–413
Raven JA, Karley AJ (2006) Carbon sequestration:
photosynthesis and subsequent processes. Curr Biol 16:
R165–R167
Reilly JM, Schimmelpfennig D (1999) Agricultural impact
assessment, vulnerability, and the scope for adaptation.
Clim Change 43: 745–788
Reilly J, Tubiello F, McCarl B, Abler D, Darwin R, Fuglie K,
Hollinger S, Izaurralde C, Jagtap S, Jones J, Mearns L,
Ojima D, Paul E, Paustian K, Riha S, Rosenberg N,
Rosenzweig C (2003) US agriculture and climate change:
new results. Climatic Change 57: 43–69
Rosenzweig C, Parry ML (1994) Potential impact of
climate change on world food supply. Nature 367:
133–138
Samarakoon AB, Gifford RM (1995) Soil water content under
plants at high CO2 concentration and interactions with the
direct CO2 effects: a species comparison. J Biogeogr 22:
193–202
Sanchez-Calderon L, Lopez-Bucio J, Chacon-Lopez A,
Gutierrez-Ortega A, Hernandez-Abreu E, Herrera-Estrella L
(2006) Characterization of low phosphorus insensitive
mutants reveals a crosstalk between low phosphorus-
induced determinate root development and the activation
of genes involved in the adaptation of Arabidopsis to
phosphorus deficiency. Plant Physiol 140: 879–889
Schar C, Vidale PL, Luthi D, Frei C, Haberli C, Liniger MA,
Appenzeller C (2004) The role of increasing temperature
variability in European summer heat waves. Nature 427:
332–336
Schenk MK, Barber SA (1980) Potassium and phosphorus
uptake by corn genotypes grown in the field as influenced
by root characteristics. Plant Soil 54: 65–76
Schimel D (2006) ECOLOGY: climate change and crop
yields: beyond Cassandra. Science 312: 1889–1890
Schlenker W, Hanemann WM, Fisher AC (2006) The impact
of global warming on U.S. agriculture: an econometric
Physiol. Plant. 133, 2008 723
analysis of optimal growing conditions. Rev Econ Stat 88:
113–125
Silberbush M (2002) Simulation of ion uptake from the soil.
In: Waisel Y, Eshel A, Kafkafi U (eds) Plant Roots: The
Hidden Half, 3rd Edn. Marcel Dekker, New York,
pp 651–661
Silberbush M, Barber SA (1983a) Prediction of phosphorus
and potassium uptake by soybeans with a mechanistic
mathematical model. Soil Sci Soc Am J 47: 287–296
Silberbush M, Barber SA (1983b) Sensitivity analysis of
parameters used in simulating K uptake with a mechanistic
mathematical model. Agron J 75: 851–854
Silberbush M, Barber SA (1984) Phosphorus and
potassium uptake of field-grown soybean cultivars
predicted by a simulation model. Soil Sci Soc Am J 48:
592–596
Soussana J-F, Luscher A (2007) Temperate grasslands and
global atmospheric change: a review. Grass Forage Sci
62: 127–134
Southworth J, Randolph JC, Habeck M, Doering OC, Pfeifer
RA, Rao DG, Johnston JJ (2000) Consequences of future
climate change and changing climate variability on maize
yields in the midwestern United States. Agric Ecosyst
Environ 82: 139–158
Svecnjak Z, Rengel Z (2006) Nitrogen utilization efficiency
in canola cultivars at grain harvest. Plant Soil 283:
299–307
Swift MJ, Andren O, Brussaard L, Briones M, Couteaux M-M,
Ekschmitt K, Kjoller A, Loiseau P, Smith P (1998) Global
change, soil biodiversity, and nitrogen cycling in terrestrial
ecosystems: three case studies. Glob Chang Biol 4:
729–743
Teo YH, Beyrouty CA, Gbur EE (1992) Evaluating a model for
predicting nutrient uptake by rice during vegetative
growth. Agron J 84: 1064–1070
Teughels H, Nijs I, Van Hecke P, Impens I (1995) Competition
in a global change environment: the importance of
different plant traits for competitive success. J Biogeogr
22: 297–305
Uselman SM, Qualls RG, Thomas RB (2000) Effects of
increased atmospheric CO2, temperature, soil N
availability on root exudation of dissolved organic carbon
by a N-fixing tree (Robinia pseudoacacia l.). Plant Soil
222: 191–202
Van Rees KCJ, Comerford NB, McFee WW (1990) Modeling
potassium uptake by slash pine seedlings from
low-potassium-supplying soils. Soil Sci Soc Am J 54:
1413–1421
Van Vuuren MMI, Robinson D, Fitter AH, Chasalow SD,
Williamson L, Raven JA (1997) Effects of elevated
atmospheric CO2 and soil water availability on root
biomass, root length, and N, P and K uptake by wheat.
New Phytol 135: 455–465
Vitosh ML, Johnson JW, Mengel DB (1995) Tri-State Fertilizer
Recommendations for Corn, Soybean, Wheat and
Alfalfa. Extension Bulletin E-2567, Purdue University
Cooperative Extension Service. Available at http://
www.ces.purdue.edu/extmedia/AY/AY-9-32.pdf; verified
April 30, 2008
Volenec JJ, Nelson CJ, Sleper DA (1984) Influence of
temperature on leaf dark respiration of diverse tall fescue
genotypes. Crop Sci 24: 907–912
Vu JCV, Newman YC, Allen JL, Gallo-Meagher M, Zhang
M-Q (2002) Photosynthetic acclimation of young sweet
orange trees to elevated growth CO2 and temperature.
J Plant Physiol 159: 147–157
Wan S, Norb RJ, Pregitzer KS, Ledford J, O’Neill EG (2004)
CO2 enrichment and warming of the atmosphere enhance
both productivity and mortality of maple tree fine roots.
New Phytol 162: 437–446
Weast RC (1982) Handbook of Chemistry and Physics. The
Chemical Rubber Co, Cleveland, OH
Wilhelm WW, Doran JW, Power JF (1986) Corn and
soybean yield response to crop residue management under
no-tillage production systems. Agron J 78: 184–189
Wilhelm WW, Johnson JMF, Hatfield JL, Voorhees WB,
Linden DR (2004) Crop and soil productivity response
to corn residue removal: a literature review. Agron J
96: 1–17
Wilhelm WW, Johnson JMF, Karlen DL, Lightle DT (2007)
Corn stover to sustain soil organic carbon further
constrains biomass supply. Agron J 99: 1665–1667.
Notes: 10.2134/agronj2007.0150
Yang HS, Dobermann A, Lindquist JL, Walters DT, Arkebauer
DJ, Cassman KG (2004) Hybrid-maize – a maize
simulation model that combines two crop modeling
approaches. Field Crops Res 87: 131–154
Zak DR, Pregitzer KS, King JS, Holmes WE (2000) Elevated
atmospheric CO2, fine roots and the response of soil
microorganisms: a review and hypothesis. New Phytol
147: 201–222
Zhang J, Barber SA (1993) Corn root distribution between
ammonium fertilized and unfertilized soil. Commun Soil
Sci Plant Anal 24: 411–419
Zhao D, Reddy KR, Kakani VG, Mohammed AR, Read JJ,
Gao W (2004) Leaf and canopy photosynthetic
characteristics of cotton (Gossypium hirsutum) under
elevated CO2 concentration and UV-B radiation. J Plant
Physiol 161: 581–590
Ziska LH, Bunce JA (2007) Predicting the impact of changing
CO2 on crop yields: some thoughts on food. New Phytol
175: 607–618
Edited by J. K. Schjørring
724 Physiol. Plant. 133, 2008