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Cai X, Ballif J, Endo S, Davis E, Liang M, Chen D, DeWald D, Kreps J,
Zhu T, Wu Y. 2007. A putative CCAAT-binding transcription factor is
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CM, Hempel FD, Ratcliffe OJ. 2008. The nuclear factor Y subunits
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723.
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183: 723–732.
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106: 4555–4560.
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McPartland M, Hymus GJ, Adam L, Marion C et al. 2010. The
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Key words: CCT (CONSTANS-CONSTANS LIKE-TIMING OF CAB 1)
domain, CONSTANS, flowering, FLOWERING LOCUS T, HEME
ACTIVATOR PROTEIN (HAP), NUCLEAR FACTOR Y (NF-Y),
photoperiod.
The Authors (2010)
Journal compilation New Phytologist Trust (2010)
Commentary
Forum
Biotic and abiotic factors act
in coordination to amplify
hydraulic redistribution and
lift
The possibility that water can flow from roots to the soil
has been a major focus of attention for well over 70 yr in
ecology and agronomy (Kramer, 1933) and much effort has
been devoted to demonstrate its existence and to quantify
its magnitude (Molz & Peterson, 1976). When the rootxylem tissue interfacing the soil has a hydraulic conductivity
(Kr) well in excess of the soil hydraulic conductivity, the
flow of water from a root to adjacent soil pore spaces can
occur provided that the root water tension is smaller than
the adjacent soil water tension. However, the idea that this
mechanism may be part of a water-redistribution network
induced by the rooting system as a plant strategy to buffer
against prolonged droughts emerged later. It was shown
that some species delay the onset of water stress by preferentially transporting soil water from the upper soil layers into
deeper layers after rainfall and then releasing water from the
deeper layers into the upper soil layers, where needed, via
this rooting network (Mooney et al., 1980). Hydraulic lift
(HL), which occurs primarily at night, was coined to
describe the latter mechanism (Caldwell et al., 1998), while
hydraulic redistribution (HR) is used to emphasize that the
rooting system can distribute water passively within the soil
profile from wet to dry soil layers. With the proliferation of
sap-flow and stable isotope measuring techniques over the
last two decades (Emerman & Dawson, 1996), evidence of
HL has been reported for shrub, grasses and tree species,
and for temperate, tropical and desert ecosystems (Caldwell
et al., 1998; Horton & Hart, 1998; Oliveira et al., 2005).
Despite the widespread evidence and voluminous data on
the occurrence of HL and HR, three inter-related topics
have resisted rigorous treatments to date: to what extent HR
and HL confer advantages to the entire ecosystem in terms
of carbon (C) gains (Emerman & Dawson, 1996); to what
degree biotic and abiotic processes work in coordination to
‘amplify’ HR or HL; and given the reported magnitudes of
HR and HL, how their effects can be represented in future
generations of large scale C–water transport models, a topic
now receiving attention in climate systems (Lee et al.,
2005). The study by Domec et al. (pp. 171–183), in this
issue of New Phytologist, considered the first topic for a
loblolly pine stand during months of normal and belownormal precipitation and ‘fingerprinted’ the effects of HR
on tree transpiration, ecosystem water use and the key components of the C balance. Using combinations of long-term
New Phytologist (2010) 187: 3–6
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4 Forum
New
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Commentary
sapflow, soil moisture and eddy-covariance flux measurements, they showed that HR was amplified most at intermediate soil-moisture states during the drought period.
They also showed that the understory species was dependent
on the HR induced by the deeper rooting system of the
overstory pine trees for water supply during the drought.
These long-term measurements further showed that in the
absence of any HR benefit, gross ecosystem productivity
and net ecosystem exchange were reduced by as much
as 750 g C m)2 yr)1 and 400 g C m)2 yr)1, respectively.
With these estimates, Domec et al. unequivocally calls into
question the current treatment of root-water uptake in
models and necessitates novel theoretical tactics to begin
tackling the second and third topics raised here, the
compass of this Commentary.
‘Despite the widespread evidence and voluminous
data on the occurrence of HL and HR, three interrelated topics have resisted rigorous treatments to
date …’
Any progress on these two topics must separate HR
induced by the rooting system from the soil-moisture redistribution mechanism across soil layers (Fig. 1). In the
absence of any rooting system, water movement occurs from
regions of wet- to dry-soil layers based on matric potential
gradients and Darcy’s law, with magnitudes dictated by the
soil water-retention and hydraulic-conductivity functions.
This soil-induced redistribution mechanism occurs at all
times and is not restricted to nocturnal conditions. Fig. 1
presents the modeled time evolution of the soil-moisturecontent profile for a 1-m uniform bare soil column where
soil evaporation is censored and water is only allowed to
drain from the 1 m base. After 100 d, the upper 30-cm
layers experience increases in soil moisture that can only
originate from the deeper layers. These soil-moisture
increases are commensurate with values reported by Domec
et al. However, Domec et al. (Fig. 1b in their paper) were
able to show that HL was recharging the top layers at much
faster rates (c. 0.6 mm d)1) than the calculations in Fig. 1
would suggest (c. 0.15 mm d)1), especially in the summer
months of the drought and only during nocturnal conditions. When comparing the results in Fig. 1 with those of
Domec et al., one question that can be raised is whether
biotic and abiotic factors are acting in coordination to
amplify HR well beyond the soil-distribution mechanism
highlighted in Fig. 1.
To address this issue, the interplay among soil-moisture
redistribution, the structure of the rooting system and its
hydraulic properties, soil type and the transpiration rate
required to satisfy the plant C demands were analyzed
using a numerical model (Siqueira et al., 2008, 2009). In
this model, two flow patterns simultaneously occur – the
first is at scales comparable to the root zone depth
(c. meters) and the second is at length scales inversely
related to root densities (c. millimeters), taken here to
represent the radial distance between rootlets (Mendel
et al., 2002). The scale separation between the two flow
patterns justified the computation of each independently
Low θ
Soil HD
HL
0
z (cm)
–10
–10
0.4
–20
–20
–30
0.35 –30
–40
Soil HD in isolation
Richard’s equation
t = 100 d
Soil HD
only
–40
0.3
–50
–50
0.25
–60
–60
0.2 –70
–70
t=0
–80
–80
0.15
–90
20 40 60 80
Time (d)
–90
–100
0.1
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0.2
0.3
θ
0.4
High θ
0.5
Fig. 1 Illustration of the hydraulic lift (HL)
induced by the rooting system and how it
differs from soil moisture-induced
distribution (soil HD) quantified using the
boxed one-dimensional Richard’s (1931)
equation. Here, t and z are time and depth
from the ground surface, respectively; q is
the water flux along z given by Darcy’s law;
k(h) and w(h) are the soil hydraulic
conductivity function and soil water pressure
potential, respectively, at a given soil
moisture, h, approximated by power-law
functions, with ks, ws, hs and b varying by soil
type. In these runs, the hydraulic properties
employed are presented elsewhere (Oren
et al., 1998). The assumed initial soil
moisture content is shown in dashed lines,
and the solid line represents the soil-moisture
profile after 100 d. Notice the accumulation
of water in the top layers (referred to as soil
HD).
The Authors (2010)
Journal compilation New Phytologist Trust (2010)
New
Phytologist
Forum
Commentary
at fine time steps and recoupling them through a mathematical homogenization technique in space. This model can
account for many known features of root uptake, including
diurnal hysteresis in canopy conductance, HL and HR
(Siqueira et al., 2008). The model assumes that root absorption is driven by pressure differences between the root–soil
interface and root xylem tissue characterized by Kr. In
essence, the model neglects osmotic transport that can be
significant for near-saturated soil conditions (Siqueira et al.,
2008). The model calculations also neglect pressure losses
within the root xylem, which have been considered in other
recent models (Amenu & Kumar, 2008). Order-ofmagnitude analysis shows that the root pressure is in a
quasi-hydrostatic state and primarily adjusts in time to
maintain the transpiration demand of the plant, the latter
being driven by photosynthesis. This argument simplifies
the modeling of water flow inside the rooting system. The
assumption becomes more realistic as the soil dries because
the soil hydraulic conductivity decreases dramatically compared with Kr. The model further assumes horizontal
homogeneity for the root area distribution. In addition,
gravitational effects are neglected in the radial domain,
making the rootlet orientation immaterial. The higher
gradients and faster dynamics in the radial direction justify
this assumption. Model calculations were performed
(assuming both high and low Kr values to regulate the
strength of HR) for: three types of root-density profiles
(constant, linear and power-law; Fig. 2a inset) in a silt clay
soil; and three soil types (sand, silt clay and clay) for a
linearly distributed root-density profile. All the plant physiological attributes related to leaf-level physiological traits
and to radiative and aerodynamic parameters are identical
across model runs. Also, the diurnal environmental forcing
variables, including incident short- and long-wave
radiation, mean wind speed, and air and dew-point
temperatures, were assumed to be periodic so that all
space–time variations in soil moisture are the result of
the interaction between biotic and abiotic factors. These
calculations have shown that, in all cases, the HL delays
the onset of soil-moisture stress within the 1-m rooting
zone by some 20–40 d (Siqueira et al., 2008). Moreover,
it is amplified most for intermediate soil-moisture states,
consistent with Domec et al. Based on the data shown in
Fig. 2, the soil type and the root-density distributions
appear to have comparable effects on HL.
To ‘encode’ these findings in larger-scale C–water cycling
models, the reductions of transpiration with soil moisture
for the soil-moisture states below field capacity are presented in Fig. 2(a,b). This representation, often the basis of
the so-called loss function, is now routinely used in ecohydrological applications (D’Odorico & Porporato, 2004)
to reproduce plant response to water stress. It is safe to state
that the effects of elevated HL are to shift the onset of transpiration reductions to lower root-zone soil moisture,
thereby allowing the ecosystem to sequester more C, as
found in Domec et al. Moreover, the effects of HL for
intermediate ranges of soil moisture are commensurate to
those reported by Domec et al. Fig. 2 further demonstrates that for a uniform rooting-density profile, HL confers
minor benefits to the plant. We have conducted a
number of model calculations similar to the ones shown
in Fig. 2, with all combinations of soil types and root
distribution, and have concluded that the effectiveness of
the HL is mainly controlled by the root vertical distribution, while the soil-moisture levels at which HL is most
effective appear to be dictated by the soil hydraulic
0
3
z (m)
Transpiration (mm d–1)
(a)
2
Constant root
Linear root
Power law root
1
Solid lines:
Dashed lines:
−0.5
−1
−1.5
High hydraulic lift
Low hydraulic lift
0
5
10
λ (km m–3)
15
0
Fig. 2 Loss function from model runs
comparing plant response to root-zone soil
moisture (h) with high hydraulic lift (HL)
(high Kr value) and low HL (low Kr value).
(a) Responses with different root-density
distributions in a silt loam soil, and
(b) responses to different soil types with a
linearly distributed root-density profile. The
inset in panel a, shows the three different
root-density (k) profiles used in the runs.
The rooting zone is only 1 m deep.
The Authors (2010)
Journal compilation New Phytologist Trust (2010)
Transpiration (mm d–1)
(b)
3
2
Sandy loam
Silt loam
Loan
1
0
0.05
Solid lines:
Dashed lines:
0.1
0.15
0.2
High hydraulic lift
Low hydraulic lift
0.25
0.3
0.35
0.4
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Commentary
properties and the atmospheric water-vapor demand
(Siqueira et al., 2008).
To conclude, Bonner (1959) stated that some of the
problems pertaining to water movement in plant physiology
are becoming increasingly amenable to mathematical
analysis and called for the creation of a branch in plant
physiology titled ‘Phytobiophysics’. This call was made in
1959 – and the occurrence of phenomena such as HL and
HR simply reinforce this call today.
Gabriel G. Katul1* and Mario B. Siqueira2
1
Nicholas School of the Environment, Duke University,
Durham, NC, USA;
2
Departamento de Engenharia Mecânica, Universidade de
Brası́lia, Brası́lia, Brazil
(*Author for correspondence: tel +1 919 613 8033;
email [email protected])
New
Phytologist
Richards LA. 1931. Capillary conduction of liquids through porous
mediums. Physics-A Journal of General and Applied Physics 1: 318–333.
Siqueira M, Katul G, Porporato A. 2008. Onset of water stress, hysteresis
in plant conductance, and hydraulic lift: scaling soil water dynamics
from millimeters to meters. Water Resources Research 44: 14.
Siqueira M, Katul G, Porporato A. 2009. Soil moisture feedbacks on
convection triggers: the role of soil–plant hydrodynamics. Journal of
Hydrometeorology 10: 96–112.
Key words: carbon–water cycling models, drought, hydraulic
redistribution, soil moisture, transpiration.
What’s good for you may be
good for me: evidence for
adaptive introgression of
multiple traits in wild
sunflower
References
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D’Odorico P, Porporato A. 2004. Preferential states in soil moisture and
climate dynamics. Proceedings of the National Academy of Sciences, USA
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Domec JC, King J, Noormets A, Sun GE, McNulty S, Gavazzi M. 2010.
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New Phytologist (2010) 187: 6–9
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Interspecific hybridization has long been considered an
important evolutionary mechanism in plants (Arnold,
2004). In particular, the transfer of adaptations among
related taxa mediated by interspecific hybridization has
received considerable attention from theoretical and empirical points of views. This process, often called ‘adaptive
introgression’, involves the transfer of fitness-increasing
alleles and their phenotypic effects from one taxon to
another (Whitney et al., 2006; Fig. 1). Although many
empirical examples of this process have been proposed
(Rieseberg & Wendel, 1993; Table 1), and some of them
convincingly demonstrated using appropriate empirical
approaches (e.g. Martin et al., 2006; Whitney et al., 2006),
it remains difficult to evaluate the overall importance of this
process between related taxa. Moreover, even in documented cases, it is typically unknown whether multiple
traits are involved in adaptive introgression, and which
traits are more likely to introgress. Theoretical studies
indicate that under heterogeneous environments, a single
allele that is at an advantage in the alternative environment
and genetic background is expected to introgress readily
(Barton, 2001). However the transfer of multiple traits in
introgressed populations, possibly with complex epistatic
interactions, is not straightforward and depends heavily on
conditions such as the rate and duration of hybridization
and the detailed genetics of hybrid fitness (Barton, 2001).
In this issue of New Phytologist, Whitney et al. (pp. 230–
239) specifically address the issue of adaptive introgression
of multiple traits by comparing phenotypes and fitness of
natural and synthetic hybrids of two wild sunflower species,
Helianthus annuus and Helianthus debilis. Together with the
results obtained in a previous investigation (Whitney et al.,
The Authors (2010)
Journal compilation New Phytologist Trust (2010)