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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


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


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


highas

25%

Longet

al.(2006),So

ussan

aan

dLuscher

(2007)

Can

opy

Averageincrease


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)


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).


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%


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


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


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)


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,


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).


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


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).


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


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).


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


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


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


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


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


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