Tree Physiology Advance Access published January 24, 2015
Tree Physiology 00, 1–14 doi:10.1093/treephys/tpu113
Research paper
Indira Paudel1,2, Amos Naor3, Yoni Gal4 and Shabtai Cohen1,5 1Department
of Environmental Physics and Irrigation, Institute of Soil, Water and Environmental Sciences, ARO Volcani Center, PO Box 6, Bet Dagan 50250, Israel; Soil and Water Sciences, The R.H. Smith Faculty of Agriculture Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel; 3Golan Research Institute, PO Box 97, Kazrin 12900, Israel; 4Ministry of Agriculture and Rural Development, 10200 Kiryat Shmona, Israel; 5Corresponding author ([email protected]) 2Department of
Received July 6, 2014; accepted November 21, 2014; handling Editor Maurizio Mencuccini
For isohydric trees mid-day water uptake is stable and depends on soil water status, reflected in pre-dawn leaf water potential (Ψpd) and mid-day stem water potential (Ψmd), tree hydraulic conductance and a more-or-less constant leaf water potential (Ψl) for much of the day, maintained by the stomata. Stabilization of Ψl can be represented by a linear relationship between canopy resistance (Rc) and vapor pressure deficit (D), and the slope (BD) is proportional to the steady-state water uptake. By analyzing sap flow (SF), meteorological and Ψmd measurements during a series of wetting and drying (D/W) cycles in a nectarine orchard, we found that for the range of Ψmd relevant for irrigated orchards the slope of the relationship of Rc to D, BD is a linear function of Ψmd. Rc was simulated using the above relationships, and its changes in the morning and evening were simulated using a rectangular hyperbolic relationship between leaf conductance and photosynthetic irradiance, fitted to leaflevel measurements. The latter was integrated with one-leaf, two-leaf and integrative radiation models, and the latter gave the best results. Simulated Rc was used in the Penman–Monteith equation to simulate tree transpiration, which was validated by comparing with SF from a separate data set. The model gave accurate estimates of diurnal and daily total tree transpiration for the range of Ψmds used in regular and deficit irrigation. Diurnal changes in tree water content were determined from the difference between simulated transpiration and measured SF. Changes in water content caused a time lag of 90–105 min between transpiration and SF for Ψmd between −0.8 and −1.55 MPa, and water depletion reached 3 l h−1 before noon. Estimated mean diurnal changes in water content were 5.5 l day−1 tree−1 at Ψmd of −0.9 MPa and increased to 12.5 l day−1 tree−1 at −1.45 MPa, equivalent to 6.5 and 16.5% of daily tree water use, respectively. Sixteen percent of the dynamic water volume was in the leaves. Inversion of the model shows that Ψmd can be predicted from D and Rc, which may have some importance for irrigation management to maintain target values of Ψmd. That relationship will be explored in future research. Keywords: capacitance, isohydric behavior.
Introduction Use of sap flow (SF) sensors in the past few decades has resulted in an improved understanding of the responses of plant water relations to environment on the whole-plant level. Early on, it was found that under high-light conditions canopy
conductance (Gc) is negatively related to the vapor pressure deficit of ambient air (D) (e.g., Granier et al. 1996b, Oren et al. 1998, Li et al. 2002), a response that stabilizes transpiration and mid-day leaf water potential as D increases (Monteith and Unsworth 1990, Cohen and Naor 2002, David et al. 2004). Stabilization of leaf water potential is typical isohydric behavior
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]
Downloaded from http://treephys.oxfordjournals.org/ at University of California, San Francisco on March 31, 2015
Simulating nectarine tree transpiration and dynamic water storage from responses of leaf conductance to light and sap flow to stem water potential and vapor pressure deficit
2 Paudel et al.
Tree Physiology Volume 00, 2015
More detailed models predict instantaneous rates of water use. These can be used to gain insight into plant processes (Meinzer et al. 2009, Manzoni et al. 2012), for example determining the difference between transpiration from the leaves and uptake of water from the soil, or the hydraulic capacitance of the plant (Sperry et al. 2002, Manzoni et al. 2012). Sometimes changes in water content can be determined from direct measurements, e.g., where eddy covariance measurements or SF measurements in the upper branches are made simultaneously with monitoring of soil water balance and trunk SF (Moore et al. 2008, Richards et al. 2013). Capacitance is an important feature of plant water relations since the leaves draw on stored water, water content declines along with water potential and thus water is drawn from the soil. Capacitance introduces a significant time lag between trunk SF and transpiration (Phillips et al. 1997, Goldstein et al. 1998, Ford et al. 2005, Kumagai et al. 2009). Time constants associated with the lag can be estimated as the product of hydraulic resistance and hydraulic capacitance between the soil and the reference point within the plant, and especially in the leaves (Meinzer et al. 2004, Cermak et al. 2007). Detailed models of plant capacitances have been developed and some of these include descriptions of daily stem contractions (e.g., Zweifel et al. 2001, Steppe et al. 2006), which is important because stem contractions can be measured with dendrometers and are useful for irrigation control (e.g., Naor and Cohen 2003, Fernandez and Cuevas 2010). Here, we use a combination of SF measurements and a model of tree transpiration to determine the dynamics of water storage in the plant. The hypothesis of our study is that nectarine water use for different levels of soil water content can be determined from a model of climate demand for transpiration and the response of canopy conductance to D, mid-day stem water potential (Ψmd) and radiation. In order to study the ability of the model to predict diurnal changes, plant water storage, which plays a significant role in the daily cycle of water uptake and loss from the plant, was quantified as the difference between simulated transpiration and SF. Our objectives were to (i) develop a model of canopy conductance based on experimentally derived relations under nonstress and water stress conditions, (ii) validate the model and compare alternatives for modeling radiation and (iii) explore the use of the model to predict changes in tree water content resulting from temporal differences between model transpiration and water uptake.
Theory: model description Canopy conductance from SF measurements Canopy conductance (Gc, m s−1) was computed with an inversion of the Penman–Monteith equation as
Downloaded from http://treephys.oxfordjournals.org/ at University of California, San Francisco on March 31, 2015
of many tree species (Tardieu and Simonneau 1998). The relationship of Gc to D is similar, but not identical, to the response of leaf-level conductance to D. At the whole-plant level, the response is related to the tendency of whole plants to coordinate water use with internal constraints on water transport, like the hydraulic capacity of the stem and roots (Solari et al. 2006, Cohen et al. 2007) and the negative water potential at which the stomata are observed to close (Buckley et al. 2012). Those plant traits are in turn related to the structural properties and physical limits of the water transport system, as demonstrated by many studies showing the correspondence between water potential at which the stomata are observed to close and that at which hydraulic capacity is impaired (Kocher et al. 2013). However, water potential in the plant is not fixed and depends on soil water content (David et al. 2004, Meinzer et al. 2004). The relationship of canopy conductance to D has been fitted empirically to an exponential function (Jones 1992, Granier et al. 1996a, 1996b, Oren et al. 1998, 1999a, Ewers et al. 2002, Orgaz et al. 2007, Katul et al. 2012), and parameters of that function for many species have been reviewed (Oren et al. 1999b, Katul et al. 2012). A simpler option is an inverse relationship, i.e., a linear relationship between canopy resistance and D (Cohen and Naor 2002, David et al. 2004). Villalobos et al. (2013) showed that the linear relationship could be derived from the Ball–Berry model of leaf photosynthesis (Dewar 2002). These models have dealt with forests and irrigated orchards, but how the relationship changes when soil water content decreases has not been addressed. Models of the response of daily plant water use to soil and climate provide basic information necessary for irrigation management. Currently, the most widely used is the Penman– Monteith model (Penman 1948, Monteith 1965) applied to a well-irrigated cut-grass surface (the FAO56 model, Allen et al. 1998), which has been validated by lysimeter measurements (e.g., Sumner and Jacobs 2005). Application of the model to other crops involves the use of an empirical crop factor, which can also be adjusted for deficit irrigation conditions (Allen et al. 1998, Naor 2006, Katul et al. 2012, Villalobos et al. 2013). Canopy conductance of the grass (or other) crop is fixed and therefore reference crop evapotranspiration (ET0) increases with the atmospheric demand for evaporation, i.e., as a wet surface. Models that include the response of canopy conductance to D may be a useful extension of the standard ET0 calculation, since for many crops the resulting ET0 would be more realistic in predicting actual crop water use (Goldstein et al. 1998, Phillips et al. 2003, Testi et al. 2006, Orgaz et al. 2007, Katul et al. 2012, Villalobos et al. 2013). Another possible advance might be the introduction of models that predict daily water use accurately using only D and radiation (e.g., Testi et al. 2006, Orgaz et al. 2007, Buckley et al. 2012, Villalobos et al. 2013), which would preclude the need for measurement of wind speed in agro-meteorological stations.
Simulating nectarine tree transpiration and dynamic water storage 3
Gc =
F λGa , ∆(Rn − G ) + ρ Cp DGa − F λ (∆ + γ )
(1)
Ga = 0.1 × u.
(2)
The canopy conductance Gc ′ model Relationships to D and Ψmd Canopy conductance was simulated based on relationships found between canopy conductance Gc and other parameters, where Gc was computed from SF using Eq. (1). The influence of D on simulated canopy resistance (Rc,D) was expressed as
1/ Gc′ = Rc,D = AD + BD × D,
(3)
where G c ′ is simulated canopy conductance; AD is the resistance when D = 0 and B D is the slope, which should be proportional to a steady-state rate of transpiration and sap flux maintained by the plant as D varies. Here the linear relationship Eq. (3) was found to apply for mid-day conditions and a wide range of Ψmds measured in the wetting and drying cycles (Figure 2a). The constant AD was not found to change significantly with Ψmd and its average value was 0.045 ± 0.001 (Figure 2c; Table 1). B D was linearly related to Ψmd, i.e.,
BD = AΨ + BΨ × Ψmd ,
(4)
where AΨ and BΨ were 0.0362 and −0.116, respectively (Figure 2b; R2 = 0.89; P
Tree Physiology 00, 1–14 doi:10.1093/treephys/tpu113
Research paper
Indira Paudel1,2, Amos Naor3, Yoni Gal4 and Shabtai Cohen1,5 1Department
of Environmental Physics and Irrigation, Institute of Soil, Water and Environmental Sciences, ARO Volcani Center, PO Box 6, Bet Dagan 50250, Israel; Soil and Water Sciences, The R.H. Smith Faculty of Agriculture Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel; 3Golan Research Institute, PO Box 97, Kazrin 12900, Israel; 4Ministry of Agriculture and Rural Development, 10200 Kiryat Shmona, Israel; 5Corresponding author ([email protected]) 2Department of
Received July 6, 2014; accepted November 21, 2014; handling Editor Maurizio Mencuccini
For isohydric trees mid-day water uptake is stable and depends on soil water status, reflected in pre-dawn leaf water potential (Ψpd) and mid-day stem water potential (Ψmd), tree hydraulic conductance and a more-or-less constant leaf water potential (Ψl) for much of the day, maintained by the stomata. Stabilization of Ψl can be represented by a linear relationship between canopy resistance (Rc) and vapor pressure deficit (D), and the slope (BD) is proportional to the steady-state water uptake. By analyzing sap flow (SF), meteorological and Ψmd measurements during a series of wetting and drying (D/W) cycles in a nectarine orchard, we found that for the range of Ψmd relevant for irrigated orchards the slope of the relationship of Rc to D, BD is a linear function of Ψmd. Rc was simulated using the above relationships, and its changes in the morning and evening were simulated using a rectangular hyperbolic relationship between leaf conductance and photosynthetic irradiance, fitted to leaflevel measurements. The latter was integrated with one-leaf, two-leaf and integrative radiation models, and the latter gave the best results. Simulated Rc was used in the Penman–Monteith equation to simulate tree transpiration, which was validated by comparing with SF from a separate data set. The model gave accurate estimates of diurnal and daily total tree transpiration for the range of Ψmds used in regular and deficit irrigation. Diurnal changes in tree water content were determined from the difference between simulated transpiration and measured SF. Changes in water content caused a time lag of 90–105 min between transpiration and SF for Ψmd between −0.8 and −1.55 MPa, and water depletion reached 3 l h−1 before noon. Estimated mean diurnal changes in water content were 5.5 l day−1 tree−1 at Ψmd of −0.9 MPa and increased to 12.5 l day−1 tree−1 at −1.45 MPa, equivalent to 6.5 and 16.5% of daily tree water use, respectively. Sixteen percent of the dynamic water volume was in the leaves. Inversion of the model shows that Ψmd can be predicted from D and Rc, which may have some importance for irrigation management to maintain target values of Ψmd. That relationship will be explored in future research. Keywords: capacitance, isohydric behavior.
Introduction Use of sap flow (SF) sensors in the past few decades has resulted in an improved understanding of the responses of plant water relations to environment on the whole-plant level. Early on, it was found that under high-light conditions canopy
conductance (Gc) is negatively related to the vapor pressure deficit of ambient air (D) (e.g., Granier et al. 1996b, Oren et al. 1998, Li et al. 2002), a response that stabilizes transpiration and mid-day leaf water potential as D increases (Monteith and Unsworth 1990, Cohen and Naor 2002, David et al. 2004). Stabilization of leaf water potential is typical isohydric behavior
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]
Downloaded from http://treephys.oxfordjournals.org/ at University of California, San Francisco on March 31, 2015
Simulating nectarine tree transpiration and dynamic water storage from responses of leaf conductance to light and sap flow to stem water potential and vapor pressure deficit
2 Paudel et al.
Tree Physiology Volume 00, 2015
More detailed models predict instantaneous rates of water use. These can be used to gain insight into plant processes (Meinzer et al. 2009, Manzoni et al. 2012), for example determining the difference between transpiration from the leaves and uptake of water from the soil, or the hydraulic capacitance of the plant (Sperry et al. 2002, Manzoni et al. 2012). Sometimes changes in water content can be determined from direct measurements, e.g., where eddy covariance measurements or SF measurements in the upper branches are made simultaneously with monitoring of soil water balance and trunk SF (Moore et al. 2008, Richards et al. 2013). Capacitance is an important feature of plant water relations since the leaves draw on stored water, water content declines along with water potential and thus water is drawn from the soil. Capacitance introduces a significant time lag between trunk SF and transpiration (Phillips et al. 1997, Goldstein et al. 1998, Ford et al. 2005, Kumagai et al. 2009). Time constants associated with the lag can be estimated as the product of hydraulic resistance and hydraulic capacitance between the soil and the reference point within the plant, and especially in the leaves (Meinzer et al. 2004, Cermak et al. 2007). Detailed models of plant capacitances have been developed and some of these include descriptions of daily stem contractions (e.g., Zweifel et al. 2001, Steppe et al. 2006), which is important because stem contractions can be measured with dendrometers and are useful for irrigation control (e.g., Naor and Cohen 2003, Fernandez and Cuevas 2010). Here, we use a combination of SF measurements and a model of tree transpiration to determine the dynamics of water storage in the plant. The hypothesis of our study is that nectarine water use for different levels of soil water content can be determined from a model of climate demand for transpiration and the response of canopy conductance to D, mid-day stem water potential (Ψmd) and radiation. In order to study the ability of the model to predict diurnal changes, plant water storage, which plays a significant role in the daily cycle of water uptake and loss from the plant, was quantified as the difference between simulated transpiration and SF. Our objectives were to (i) develop a model of canopy conductance based on experimentally derived relations under nonstress and water stress conditions, (ii) validate the model and compare alternatives for modeling radiation and (iii) explore the use of the model to predict changes in tree water content resulting from temporal differences between model transpiration and water uptake.
Theory: model description Canopy conductance from SF measurements Canopy conductance (Gc, m s−1) was computed with an inversion of the Penman–Monteith equation as
Downloaded from http://treephys.oxfordjournals.org/ at University of California, San Francisco on March 31, 2015
of many tree species (Tardieu and Simonneau 1998). The relationship of Gc to D is similar, but not identical, to the response of leaf-level conductance to D. At the whole-plant level, the response is related to the tendency of whole plants to coordinate water use with internal constraints on water transport, like the hydraulic capacity of the stem and roots (Solari et al. 2006, Cohen et al. 2007) and the negative water potential at which the stomata are observed to close (Buckley et al. 2012). Those plant traits are in turn related to the structural properties and physical limits of the water transport system, as demonstrated by many studies showing the correspondence between water potential at which the stomata are observed to close and that at which hydraulic capacity is impaired (Kocher et al. 2013). However, water potential in the plant is not fixed and depends on soil water content (David et al. 2004, Meinzer et al. 2004). The relationship of canopy conductance to D has been fitted empirically to an exponential function (Jones 1992, Granier et al. 1996a, 1996b, Oren et al. 1998, 1999a, Ewers et al. 2002, Orgaz et al. 2007, Katul et al. 2012), and parameters of that function for many species have been reviewed (Oren et al. 1999b, Katul et al. 2012). A simpler option is an inverse relationship, i.e., a linear relationship between canopy resistance and D (Cohen and Naor 2002, David et al. 2004). Villalobos et al. (2013) showed that the linear relationship could be derived from the Ball–Berry model of leaf photosynthesis (Dewar 2002). These models have dealt with forests and irrigated orchards, but how the relationship changes when soil water content decreases has not been addressed. Models of the response of daily plant water use to soil and climate provide basic information necessary for irrigation management. Currently, the most widely used is the Penman– Monteith model (Penman 1948, Monteith 1965) applied to a well-irrigated cut-grass surface (the FAO56 model, Allen et al. 1998), which has been validated by lysimeter measurements (e.g., Sumner and Jacobs 2005). Application of the model to other crops involves the use of an empirical crop factor, which can also be adjusted for deficit irrigation conditions (Allen et al. 1998, Naor 2006, Katul et al. 2012, Villalobos et al. 2013). Canopy conductance of the grass (or other) crop is fixed and therefore reference crop evapotranspiration (ET0) increases with the atmospheric demand for evaporation, i.e., as a wet surface. Models that include the response of canopy conductance to D may be a useful extension of the standard ET0 calculation, since for many crops the resulting ET0 would be more realistic in predicting actual crop water use (Goldstein et al. 1998, Phillips et al. 2003, Testi et al. 2006, Orgaz et al. 2007, Katul et al. 2012, Villalobos et al. 2013). Another possible advance might be the introduction of models that predict daily water use accurately using only D and radiation (e.g., Testi et al. 2006, Orgaz et al. 2007, Buckley et al. 2012, Villalobos et al. 2013), which would preclude the need for measurement of wind speed in agro-meteorological stations.
Simulating nectarine tree transpiration and dynamic water storage 3
Gc =
F λGa , ∆(Rn − G ) + ρ Cp DGa − F λ (∆ + γ )
(1)
Ga = 0.1 × u.
(2)
The canopy conductance Gc ′ model Relationships to D and Ψmd Canopy conductance was simulated based on relationships found between canopy conductance Gc and other parameters, where Gc was computed from SF using Eq. (1). The influence of D on simulated canopy resistance (Rc,D) was expressed as
1/ Gc′ = Rc,D = AD + BD × D,
(3)
where G c ′ is simulated canopy conductance; AD is the resistance when D = 0 and B D is the slope, which should be proportional to a steady-state rate of transpiration and sap flux maintained by the plant as D varies. Here the linear relationship Eq. (3) was found to apply for mid-day conditions and a wide range of Ψmds measured in the wetting and drying cycles (Figure 2a). The constant AD was not found to change significantly with Ψmd and its average value was 0.045 ± 0.001 (Figure 2c; Table 1). B D was linearly related to Ψmd, i.e.,
BD = AΨ + BΨ × Ψmd ,
(4)
where AΨ and BΨ were 0.0362 and −0.116, respectively (Figure 2b; R2 = 0.89; P
