Relationship between growth rates and xylem hydraulic characteristics in young, mature and old-growth ponderosa pine trees

Authors


Correspondence: Jean-Christophe Domec. Fax: +1 541 737 3385; e-mail: jc.domec@orst.edu

ABSTRACT

The first objective of the present study was to quantify the effects of tree age and stem position on specific conductivity (ks), vulnerability to embolism and water storage capacity (capacitance) in trunks of young, mature and old-growth ponderosa pine. The second objective was to determine relationships between hydraulic characteristics and radial and height growth rates to increase the understanding of possible tradeoffs. Within sapwood at all heights and in all ages of trees, outer sapwood had 25–60% higher ks than inner sapwood. The water potential at which embolism started (air entry point) was 1.3 MPa lower in inner sapwood than outer sapwood within the mature trees, but there was no difference in the other trees. There was no significant difference in capacitances between the tops of the old growth trees, the mature trees and the young trees. Taking all data together, the capacitances increased sharply with an increase in ks and an increase in vulnerability to embolism. The hydraulic characteristics of the three age classes were correlated with the height growth rate but not with the diameter growth rate. Within these age classes, high ks was associated with the slowest yearly increase in sapwood area and with a low percentage of latewood, whereas high vulnerability to embolism and high capacitance were more closely associated with high height growth rates.

INTRODUCTION

Nearly all of our understanding of vulnerability to embolism in trees comes from the study of branches, roots or young trees (Sperry & Tyree 1988; Cochard 1992; Tyree, Alexander & Machado 1992; Kavanagh et al. 1999). Recently, however, vulnerability curves (VCs), which are plots of specific conductivity (ks) versus water potential, were reported from the trunks of mature Douglas-fir (Pseudotsuga menziesii) trees, a conifer species with narrow sapwood (Domec & Gartner 2001). There is a crucial lack of information on the hydraulic functioning of the whole trunk for conifer species, especially those with wide sapwood, such as ponderosa pine (Pinus ponderosa Dougl. ex Laws.), and for trees of different ages. Although it has been shown that stem segments from seedlings and saplings exhibited more resistance to embolism than those from adult trees (Sperry & Saliendra 1994; Matzner, Rice & Richards 2001), no studies have investigated the vulnerability to embolism in the main trunk of trees of different ages growing in similar conditions.

First, this study asks whether radial changes in the xylem structure affect water transport in ponderosa pine, both in the presence of water stress and when not under water stress. Vulnerability to embolism is influenced by the structure of the xylem (Hacke et al. 2001; Domec & Gartner 2002). Trees have a wide range of wood properties that change systematically (but with a species-dependent pattern, e.g. Zobel & van Buijtenen 1989) with distance from the pith. The first 10–30 rings outward from the pith are called juvenile wood (JW), and the wood produced subsequently are called mature wood (MW). Throughout its life, in any given year, the tree produces JW in the upper 10–30 nodes of the bole and MW below that region. Douglas-fir, ponderosa pine, and most other conifers produce JW with lower density, smaller cells, and a lower proportion of latewood than MW (Panshin & de Zeeuw 1980). In Douglas-fir, the JW appears to have a larger role in the hydraulic than in the mechanical functioning of the tree (Domec & Gartner 2002), suggesting that the different properties of JW versus MW have evolved for hydraulic rather than mechanical purposes for that species. The JW has lower ks than MW, both in studies of different-aged trees (Pothier et al. 1989; Mencuccini, Grace & Fioranvanti 1997) and different heights within trees (Spicer & Gartner 2001; Domec & Gartner 2002). However, there are no reports comparing the VCs or ks of JW and MW in species such as ponderosa pine, which have very wide sapwood.

Second, this study investigated the relationship between growth rate and water transport. Poor growing conditions, and particularly drought, can lead to decreased diameter and height growths (Zhang, Marshall & Fins 1996; Marshall, Rehfelt & Monserud 2001), poor resistance to other stresses, disruption of food production and distribution, and changes in timing and rate of physiological processes (Wright 1976). In conifers, plant height growth with time is generally sigmoidal, with the growth rate declining to almost zero after 150 years (Monson & Grant 1989; Larcher 1995; O’Hara 1996). The hydraulic limitation hypothesis for this decline in height growth states that hydraulic resistance increases as trees grow, resulting in lower photosynthetic and transpiration rates per unit leaf area, and reduced productivity in older trees (Ryan & Yoder 1997; Bond & Ryan 2001). Herein, we examined the relationship of hydraulic parameters (ks, vulnerability to embolism, and water storage capacity) to radial and height growth rates to infer which, if any, of the wood hydraulic factors appears to control growth rate.

The questions defined above were explored by investigating the hydraulic and anatomical properties of trunks in old-growth (> 220 years), mature and young individuals of ponderosa pines. This species often grows in pure multi-aged stands at low density (Barrett 1979; Smith 1986), which allowed us to study several age classes growing in the same apparent conditions. Our hypotheses were: (1) MW is more vulnerable to embolism than is JW in ponderosa pine; (2) old-growth trees are more vulnerable to water-stress induced embolism than mature and young trees because old trees have a lower proportion of sapwood JW than do young trees; and (3) growth rates are positively correlated with both sapwood ks and vulnerability to embolism.

MATERIALS AND METHODS

Plant material and sample preparation

The study site is a mixed-age ponderosa pine stand located on the eastern side of the Oregon Cascade Range (43°32′ N, 121°41′ W) on private forestland (Crown Pacific Co.). The mean annual precipitation is 645 mm (http:www.orst.eduDepartmentIPPC) and the elevation is 1355 m with soils derived from deep volcanic ash. The stand is a mix of ponderosa pine and lodgepole pine (Pinus contorta) ranging from 15 to 400 years old, and with approximately 250 trees per hectare. The sampled trees were the same trees as used by Pruyn, Gartner & Harmon (2002). Six old-growth trees (> 220 years old) in March 1999, and six mature trees (> 70 years old) and six young trees (> 30 years old) in March 2000 were selected based on their cambial age at breast height (estimated from increment cores), and their health (free of broken tops, stem deformities or disease) (Table 1). After the trees were felled, four heights of the old-growth trees were sampled, at 1 m height (node 220), at nodes 65 (lower third part of the crown), 50 and 15 counting down from the treetop. For the mature trees, only nodes 50 and 15 were sampled, and for the young trees, only node 15. The height to each of these sampled nodes was recorded (Table 2). At each height, and from each tree, discs about 20 cm thick were cut, immediately transported to the laboratory (a 3 h journey) in wet plastic bags, and stored at 5 °C until blocks were prepared within 3 days of felling. A thinner second disc was also cut for use in measuring sapwood and heartwood areas (see below). From each of the thick discs, four blocks were cut: two from the inner sapwood and two from the outer sapwood. Preparation of these specimens made from the blocks followed the procedures outlined by Domec & Gartner (2001). The specimens (about 10 mm radial direction, 10 mm tangential direction, and 130–170 mm axial direction) were split along the grain first with a maul and wedge, and then with a chisel, then stored at 3 °C in clean water which was changed daily until they were used within 3 weeks.

Table 1.  Morphological characteristics of young, mature and old-growth ponderosa pine trees sampled from the same site (mean ± SE, n = 6)
 Height
(m)
Age at tree base (year)Diameter at breast
height (cm)
Sapwood area at
the base (cm2)
Old-growth trees33.3 ± 0.4225 ± 2762.1 ± 1.92390 ± 114
Mature trees12.4 ± 0.9 72 ± 526.8 ± 1.8 375 ± 71
Young trees 2.9 ± 0.1 31 ± 3 7.7 ± 0.6 55.7 ± 6.2
Table 2.  Morphological characteristics of ponderosa pine trees by height position (node) counting down from the top of the tree, and at the base (about 30 cm; mean ± SE, n = 6)
Age classNodes
from top
Height
(m)
Diameter
(cm)
Sapwood
area (cm2)
Heartwood
area (cm2)
Outer
sapwood (%)
Sapwood
rings (no.)
  1. The base of the live crown for the old-growth trees averaged a few nodes below node 65 at a mean height of 19 ±1 m. For the mature and young trees, the base of the live crown averaged 2 ±1 and 1 ±1 m from the ground, respectively. Outer sapwood (%) is the outer sapwood area divided by the total sapwood area.

Young treesNode 15 1.1 ± 0.2 7.7 ± 0.6 35.2 ± 5.90.12 ± 0.04100 15 ± 1
Base 0.310.1 ± 0.5 55.7 ± 4.40.14 ± 0.07 70 ± 1 29 ± 3
Mature treesNode 15 8.6 ± 0.89.48 ± 0.5 55.5 ± 7.40.64 ± 0.12100 16 ± 1
Node 50 1.6 ± 0.219.2 ± 0.8 192 ± 28 9.5 ± 2.9 67 ± 1 41 ± 2
Base 0.326.8 ± 1.8 375 ± 71 4.4 ± 2.2 71 ± 1 54 ± 3
Old-growth treesNode 1531.0 ± 0.36.92 ± 0.2 24.1 ± 3.1 2.6 ± 0.3100 14 ± 1
Node 5025.5 ± 1.222.1 ± 1.1 322 ± 6117.7 ± 3.5 66 ± 1 41 ± 3
Node 6521.4 ± 1.231.8 ± 0.8 624 ± 4353.4 ± 8.3 65 ± 1 52 ± 1
Base 0.4 ± 0.162.1 ± 1.92387 ± 114 213 ± 41 64 ± 1116 ± 5

Hydraulic specific conductivity, vulnerability and relative water content curves

Samples were soaked under a vacuum for 48 h to refill some of the embolized tracheids. Initial specific conductivity (ks(i)) was then measured on a segment as described below. Using Darcy's law, we expressed ks(i) in square metres (m2), which is the direct consequence of separating the viscosity (MPa s) from the water flux (m3 m−2 s) divided by pressure gradient (MPa m−1). Vulnerability curves (VCs) of the tree trunks were constructed using the method described by Domec & Gartner (2001). The method allows calculation of the percentage loss of conductivity (PLC) on segments taken directly from the trunk after moving the sample alternately between the membrane-lined pressure sleeve to measure ks (Spicer & Gartner 1998) and the double-ended pressure chamber for causing embolism using air injection (Sperry & Saliendra 1994). We measured ks(i) using filtered (0.22 µm) water adjusted with HCl to pH 2 in order to prevent microbial growth, and using a hydraulic pressure head of 2.79 kPa. Efflux was collected in a 1-mL-graduated micropipette (0.01 mL graduation). We recorded the time required for the meniscus to cross five consecutive graduation marks, and only used the values that were steady. Samples were subjected to several air pressures ranging from 0.5 to 6.0 MPa until more than 95 PLC was reached. The temperature of the solution (to calculate water viscosity), the fresh mass (Mf), the volume (Vf) and the length of each sample were recorded before and after each hydraulic conductivity measurement (see below). After each ks measurement, we removed about 1 mm of wood from each end of the stems to have new surfaces for each experiment.

Vulnerability curves were fitted by the least squares method based on a sigmoidal function:

image(1)

where PLC is the percentage loss of conductivity [(ks(i) − ks(Ψ))/ks(i)], the parameter a1 is an indicator of the slope of the linear part of the vulnerability curve and b1 is the pressure at which 50 PLC occurred. The actual slope (s = a1 · 25) of the linear part of the vulnerability curve and the pressures at 12 PLC (Ψ12 = 2/a1 + b1) and at 88 PLC (Ψ88 = −2/a1 + b1) were determined from the fitted curves (Domec & Gartner 2001). The value Ψ12, termed the air entry point (Sparks & Black 1999), is an estimate of the xylem tension at which the runaway cavitation and embolism begin when the resistance to air entry of pit membranes within the conducting xylem is overcome (Sperry & Tyree 1988). Of course, Ψ12 is only a linear approximation of the true air entry point, which from the VCs starts very close to Ψ = 0, but it provides a very useful value to compare among curves. Likewise, Ψ88 is the full embolism point, interpreted as approximating the actual tension of the xylem before it becomes non-conductive (Domec & Gartner 2001).

To estimate the change in relative water content (RWC) associated with embolism, we determined RWC initially and after each applied pressure by recording the sample's volume (Vf; cm3, measuring water displacement on a balance using the Archimedean principle), the fresh mass (Mf; g) and the length. Following final pressurization, we recorded the dry mass (Md; g) and by using the length, back-calculated the dry mass and then calculated RWC assuming a density of dry cell wall material of 1.53 g cm−3 (Siau 1984):

image(2)

Xylem water deficit or the loss of RWC (100 − %RWC) over the range of applied pressure was fit using the following sigmoidal function:

image(3)

where Max is the maximum loss of RWC possible, a2 is an indicator of the slope of the linear part of the curve and b2 is the pressure at which Max/2 loss of RWC occurred (ΨMax/2).

Water storage capacity can be defined as the amount of water withdrawn from the stem at a given water potential relative to zero water potential (Holbrook 1995). For the same volume of water, RWC varies depending on wood density (Eqn 2; Domec & Gartner 2002). We expressed water storage capacity as the change in RWC per unit change in applied pressure, which allows us to compare differences in storage capacities that are not only related to a difference in total water volume but also to tissue density. One cannot accurately estimate capillary water changes by using the pressure chamber because positive pressure cannot displace capillary water. The maximum capillary water storage will be released at a pressure potential close to zero, and would stop before −0.5 MPa (Tyree & Yang 1990; Holbrook 1995). Therefore, to avoid underestimating capillary water at low applied pressure, volumetric RWC-based capacitance, defined as CRWC = dRWC/d (Edwards & Jarvis 1982) was computed for a range in each dehydration curve from 0.5 to 2.0 MPa (C0.5−2). This range corresponds to the natural range of water potential encountered by these trees (Hubbard, Bond & Ryan 1999; Ryan et al. 2000; authors’ field observations).

We have analysed these data further by looking at the values from the derivative of Eqn 3, which gives us the slope of the tangent at a given pressure, which, by definition, is the instantaneous water storage capacitance. The derivative of Eqn 3 is:

image(4)

The instantaneous volumetric RWC-based capacitance was computed at the air entry point Ψ12 (CΨ12) and at a pressure corresponding to the maximum water storage capacity possible within the entire range of applied pressure (Cmax). Cmax occurs when Ψ = b2 and therefore also corresponds to the slope of the linear part of the sigmoidal curve (Domec & Gartner 2001):

Cmax = a2 · Max/4(5)

Wood density and latewood proportion

Wood density values (g cm−3) were determined for each sample that was tested hydraulically:

Density = Md/Vf,(6)

where Md is the oven dry mass (dried at 105 °C), and Vf is the fresh volume (see above). We then used a transverse section made with a microtome and stained with safranin-O to determine the latewood proportion of each sample used for the VCs. We analysed each section (one line scan through each sample) with an image analysis system consisting of a compound microscope, a video camera, and the software package NIH Image (v. 1.60, Rasband 1996). We calculated an average latewood proportion for each sample as the mean of the average latewood proportion of all the growth rings analysed for that sample.

Tree growth rates

Mean annual growth rate in height (cm year−1) for the corresponding number of sapwood rings was estimated by dividing the mean height of growth above each disc by the cambial age (Table 2). Because no heartwood was present at or above node 15, we divided the height to the top of the tree directly by the number of rings. For node 65, the number of rings in sapwood corresponded to the height growth above the next disc (between node 50 and treetop). For the base and node 50, the number of rings in sapwood corresponded to a growth located between nodes 110–230 and nodes 15–50, respectively, so we took a weighted average (by year) between the total annual growth height between these two discs.

Number of rings in heartwood and sapwood as well as heartwood and sapwood areas were determined on the thin disc from each height for each tree. We drew two perpendicular diameters, counted the rings, measured heartwood and total widths, and then averaged values for the two diameters. Sapwood area was taken as the area of whole disc (excluding bark and cambium) minus the area of heartwood. The annual radial growth rate (cm year−1) for each sample (outer and inner) was calculated by dividing the number of growth rings in each sample by the sample width. Using the growth rate of the outer samples, percentage yearly increase in sapwood area (in.Sap in % year−1) was calculated by dividing the difference between the sapwood areas of the last two rings by the total sapwood area, assuming that no sapwood was lost.

Statistical analysis

Least squares methods were used to fit relationships between hydraulic parameters and applied pressure, and linear and non-linear relationships among hydraulic parameters. Each sample was used as a single replicate that gave a single value of each hydraulic parameter (ks, s, Ψ12, Ψ50, Ψ88, Cmax, CΨ12 and C0.5−2). These hydraulic parameters were compared among locations (radial and height positions) with an analysis of variance (anova). We used a strip-plot randomized complete block design (trees as block) with radial tissue and height position as the strip plot factors. The first task was to investigate the assumptions of normal distribution and constant variance among treatment groups in the residuals. In order to check for normality, we first examined the stem leaf and box-plot of the residuals. It showed a fairly symmetric and non-skewed distribution, which suggested that the residuals were normally distributed. Constant variance over the sample positions was ascertained by examining the plot of the residuals versus the predicted values. The experiment was designed to assess values at both inner and outer sapwood, but for height position we were interested in an estimate of the entire sapwood. Therefore, the effect of height position on the hydraulic parameters was made by weighting the values by the proportion of the total sapwood area occupied by the outer and inner sapwood shells (Table 2). The inner shell represented the area from the third growth ring exterior to the heartwood/sapwood boundary to the middle of the sapwood zone, and the outer shell represented the area from the middle of the sapwood zone to the cambium. All statistical procedures were conducted with Statistical Analysis Systems software (SAS 1997). Least square (LS) means were generated from a PROC MIXED procedure, and multiple comparisons among means were calculated using least square differences (LSD), and the pooled standard error was reported.

RESULTS

Specific conductivity and vulnerability to embolism parameters

Using the weighted values from each disc, specific conductivity (ks) for the disc below the living branches increased with tree age from 1.4 ± 0.4 × 10−12 m2 in the young trees (node 15) to about 5.1 ± 0.4 × 10−12 m2 in the mature trees (node 50) and 8.0 ± 0.4 × 10−12 m2 in the old-growth trees (node 65; Table 3). At the top of the trees (node 15), ks was 73 and 40% higher in the mature trees than in the young and old-growth trees, respectively. Outer sapwood always had significantly higher ks than inner sapwood (P < 0.05). The largest differences occurred at nodes 50 with a 59 and a 49% increase between inner and outer sapwood in the mature and old-growth trees, respectively.

Table 3.  Effect of position and tissue in the tree on the specific hydraulic conductivity (ks), the slope of the linear portion of the vulnerability curve (s), the pressure (b1) at which 50% loss of ks is reached, the air entry point (Ψ12) and the full embolism point (Ψ88) (mean ± SE, n = 6 trees)
Age classTissuePositionks
(10−12 m2)
s1 = 25 · a
(%Loss ks MPa−1)
Ψ12
(MPa)
b1 = Ψ50
(MPa)
Ψ88
(MPa)
  1. Values with different letters within a column are significantly different (P < 0.05). Multiple comparisons were calculated according to the mixed procedure, and the pooled standard error is reported.

YoungOuter sapwoodNode 151.4 ± 0.4 a43.1 ± 7.3 a−3.0 ± 0.1 a−4.1 ± 0.1 a−5.0 ± 0.2 a
MatureOuter sapwoodNode 155.3 ± 0.4 b46.0 ± 7.3 ab−1.4 ± 0.1 b−2.5 ± 0.1 b−3.3 ± 0.2 b
Node 505.7 ± 0.4 b43.9 ± 7.3 a−2.2 ± 0.1 c−3.1 ± 0.1 c−4.0 ± 0.2 c
Inner sapwoodNode 502.9 ± 0.4 c29.1 ± 7.3 a−0.9 ± 0.1 d−2.5 ± 0.1 b−4.0 ± 0.2 c
Old-growthOuter sapwoodNode 153.2 ± 0.4 cg53.2 ± 7.3 ab−2.9 ± 0.1 a−3.7 ± 0.1 ad−4.6 ± 0.2 a
Node 508.4 ± 0.4 d78.1 ± 7.3 c−2.5 ± 0.1 c−3.1 ± 0.1 c−3.7 ± 0.2 bc
Node 659.7 ± 0.4 e67.6 ± 7.3 bc−2.2 ± 0.1 c−2.9 ± 0.1 bc−3.6 ± 0.2 bc
1 m5.5 ± 0.4 b47.3 ± 7.3 ab−2.9 ± 0.1 a−3.8 ± 0.1 a−4.6 ± 0.2 a
Inner sapwoodNode 503.4 ± 0.4 cg54.3 ± 7.3 ab−2.3 ± 0.1 c−3.1 ± 0.1 c−4.0 ± 0.2 c
Node 654.9 ± 0.4 bf75.8 ± 7.3 c−2.2 ± 0.1 c−2.8 ± 0.1 bc−3.4 ± 0.2 b
1 m4.2 ± 0.4 fg51.7 ± 7.3 ab−2.7 ± 0.1 a−3.5 ± 0.1 d−4.4 ± 0.2 ac

At the top (node 15), mature trees were more vulnerable to embolism than young and old-growth trees (Fig. 1). The applied air pressure at which embolism started (Ψ12), the pressure causing 50 PLC (Ψ50) and the pressure causing full embolism (Ψ88) were 1.6 and 1.3 MPa lower in mature trees than in young and old-growth trees, respectively (Tables 3, P < 0.002 for comparisons of Ψ12, Ψ50 andΨ88). There were no significant differences in any of these parameters between the old-growth trees and the young trees (P > 0.16). The slope s of the vulnerability curves for the top of the trees were not significantly different by age class (P > 0.15), with a mean value for all three age classes combined of 60.5 ± 5.5 PLC MPa−1.

Figure 1.

Percentage loss of conductivity (PLC) and percentage water deficit (100-relative water content) versus the negative of applied air pressure in old-growth (triangles) mature (squares) and young (circle) ponderosa pine trees (mean ± SE, n= 6 trees). Curves represent the top (node 15, outer sapwood) and the base of the trunk (outer and inner sapwood). Filled symbols/solid lines are for the outer sapwood and open symbols/dashed lines are for the inner sapwood.

The outer wood at the base of mature trees (node 50) was 1.0 MPa less resistant to embolism than at the base of young trees (node 15) for Ψ12, Ψ50 andΨ88 (P < 0.007), and was also 0.5 MPa less resistant to embolism than at the base of old-growth trees (1 m) for Ψ12 and Ψ50 (P < 0.01) but was only marginally more vulnerable for Ψ88 (P = 0.07). There were no differences between the base of the old-growth and the base of the young trees for any of these hydraulic parameters (P > 0.09; Table 3). The slopes s of the vulnerability curves at the base of the trees from the three different age-classes were not significantly different (P > 0.26), with a mean value for all age-classes combined of 56.4 ± 6.2 PLC MPa−1.

Within the old-growth trees, considering height and radial position as fixed effects for the lower three heights, there was no significant difference between the overall inner and outer sapwood for either Ψ12 (F1,5 = 1.40, P = 0.29), Ψ50 (F1,5 = 0.90, P = 0.39) or Ψ88 (anova, F1,5 = 0.08, P = 0.79). Within the mature trees, inner sapwood at node 50 was 1.2 MPa less resistant to embolism than outer sapwood for Ψ12 (P = 0.04) (Table 3). Using the weighted values from each disc and comparing the three age classes, ks was strongly correlated with the slope s and Ψ88 (P < 0.05) but not with Ψ12 and Ψ50 (Fig. 2). However, when comparing ks with the other vulnerability parameters within the old-growth trees only, we found strong and significant relationships (filled triangles, Fig. 2).

Figure 2.

Trunk xylem safety versus xylem efficiency of ponderosa pine trees (mean ± SE, n= 6 trees). Trunk xylem safety is represented by the slope of the linear part of the sigmoidal curve (s), the mean air entry tension (Ψ12), mean embolism tension (Ψ50) and maximum embolism tension (Ψ88). Xylem efficiency is represented by the mean specific conductivity (ks).

Trunk water storage capacity

There was a sigmoidal relationship between RWC and the applied pressure, with significantly steeper slopes (represented by Cmax) at nodes 50 and 65 than at base of the old-growth trees (P < 0.05, Table 4, Fig. 1). There was no significant difference in Cmax between the top of the old-growth trees, the mature trees and the young trees (P > 0.2; Table 4).

Table 4.  Effect of position and tissue in the tree on the maximum water deficit (100 − RWC) reached (Max), the pressure (b2) at 50% loss of RWC, the maximum water storage capacity (Cmax), the capacitance at the air entry point (CΨ12), and between 0.5 and 2.0 MPa (C0.5−2) (mean ± SE, n= 6 trees)
Age classTissuePositionMax
(%RWC)
b2=ΨMax/2
(MPa)
Cmax= Max · a2/4
(%RWC MPa−1)
CΨ12
(%RWC MPa−1)
C0.5−2
(%RWC MPa−1)
  1. Values with different letters within a column are significantly different (P < 0.05). Multiple comparisons were calculated according to the mixed procedure, and the pooled standard error is reported.

YoungOuter sapwoodNode 1565.2 ± 5.4 a−4.8 ± 0.2 a 16.5 ± 2.1 a 7.7 ± 1.5 a 4.3 ± 1.4 a
MatureOuter sapwoodNode 1569.1 ± 2.1 a−2.9 ± 0.2 b 19.9 ± 2.1 a 9.9 ± 1.5 a 9.7 ± 1.4 b
Node 5061.2 ± 2.1 a−3.6 ± 0.2 c 18.2 ± 2.1 a 9.5 ± 1.5 a 6.9 ± 1.4 a
Inner sapwoodNode 5073.7 ± 2.1 b−3.1 ± 0.2 b 18.8 ± 2.1 a 6.5 ± 1.5 a10.6 ± 1.4 b
Old-growthOuter sapwoodNode 1553.9 ± 2.1 c−3.7 ± 0.2 c 17.0 ± 2.1 a13.1 ± 1.5 b 5.5 ± 1.4 a
Node 5057.2 ± 2.1 ac−3.2 ± 0.2 bc 28.0 ± 2.1 b18.1 ± 1.5 c 5.2 ± 1.4 a
Node 6560.3 ± 2.1 a−3.0 ± 0.2 b 25.1 ± 2.1 bc17.6 ± 1.5 c 6.1 ± 1.4 a
1 meter64.2 ± 2.1 a−4.1 ± 0.2 c 15.4 ± 2.1 a11.1 ± 1.5 ab 5.5 ± 1.4 a
Inner sapwoodNode 5058.2 ± 2.1 a−3.2 ± 0.2 b 21.7 ± 2.1 c13.6 ± 1.5 b 4.8 ± 1.4 a
Node 6557.7 ± 2.1 ac−2.8 ± 0.2 b 24.9 ± 2.1 bc19.1 ± 1.5 c 6.0 ± 1.4 a
1 meter63.4 ± 2.1 a−3.6 ± 0.2 c18.27 ± 2.1 a13.9 ± 1.5 b 5.4 ± 1.4 a

In the old-growth trees and at node 50 only, CΨ12 and Cmax in the outer sapwood were significantly higher than in the inner sapwood (P < 0.05; Table 4). In an anova with height and radial position as fixed effects, there was no significant difference between the overall inner and outer sapwood for either C0.5−2 (F1,5 = 0.11, P = 0.75) or CΨ12 (F1,5 = 2.60, P = 0.17). There was, however, a significant difference in Cmax between the overall inner and outer sapwood (F1,5 = 8.46, P = 0.033). For the first three discs, this effect is due to the significant difference between the outer and inner samples at node 50 (Table 4). For every sample, CΨ12 was significantly higher than C0.5−2 (P < 0.01) for the old-growth trees and young trees but not for the mature trees (P = 0.43). Cmax and CΨ12 increased sharply with an increase in ks and Ψ12, respectively (Fig. 3), from approximately 16% RWC MPa−1 at node 15 to 26% RWC MPa−1 at node 65.

Figure 3.

(a) Mean air entry tension (Ψ12) versus the capacitance between 0.5 and 2.0 MPa of ponderosa pine trees. (b) Specific conductivity (ks) versus maximum capacitance (Cmax) (mean ± SE, n= 6 trees).

Trade-off between hydraulic parameters, growth rates and wood density

Wood density increased by 2% from the inner to the outer sapwood growth rings at the base of the old-growth trees and by 6% at the base of the mature trees. Between the bottom and the top, wood density of the outer sample (same year of growth) decreased by 20 and 19% for the old-growth and mature trees, respectively (Fig. 4a). There was a strong linear relationship between the percentage latewood and wood density for the pooled data from the trunk of old-growth, mature and young trees:

Figure 4.

(a) Wood density and (b) radial growth rate as a function of cambial age (ring from pith) within the old-growth trees and the mature trees (inserts) (mean ± SE, n= 6 trees).

Percentage latewood  =  130.6 · Density  −  30.5   (r2  =  0.80, P  <  0.001)(7)

By looking at either JW or MW, we determined there were strong relationships between wood density, percentage latewood and hydraulic parameters within that wood type for ks, and Ψ88 (Table 5). Density and percentage latewood of MW were more strongly correlated with the vulnerability parameters than was density of JW. Percentage latewood was correlated with the three kinds of capacitances in JW but not in MW (Table 5). There were very few correlations when all the data were pooled together, and these correlations were always lower than for either wood type alone.

Table 5.  Slopes and intercepts (in parenthesis) of the linear regressions of the following parameters versus the wood density or percentage latewood: specific hydraulic conductivity (ks), the air entry point (Ψ12), the pressure at which 50% loss of RWC is reached (b1 = Ψ50), the full embolism point (Ψ88), the slope of the linear portion of the vulnerability curve (s), the capacitance between 0.5 and 2.0 MPa (C0.5−2), the capacitance at the air entry point (CΨ12) and the maximum water storage capacity (Cmax)
 
JWMWAllJWMWAll
  • Samples were separated into wood type based on their mean ring number from the pith (cambial age), as follows: juvenile wood (JW) is samples ≤25 rings from the pith (n = 36), mature wood (MW) is samples ≥50 rings (n = 24), and all types of wood regardless of cambial age (n = 66). Values in boldface represent values of the slopes of the regressions with a significance level < 0.001. Slopes with different letters between JW and MW for either wood density or percentage latewood are significantly different (P < 0.05).

  • A

    Significance levels refer to the slope of the regression; NS, not significant (P > 0.05);

  • *

    P < 0.05;

  • **

    P < 0.01.

ks (10−12 m2)27.3 (13.6) a42.3 (23.7) b−21.6 (13.2)0.16 (6.12) a0.25 (12.64) a−0.03 (5.61)
r2 = 0.56**Ar2 = 0.78**r2 = 0.16*r2 = 0.35**r2 = 0.46**r2 = 0.01 NS
Ψ12 (MPa)−4.7 (0.5)−5.4 (−0.3)−5.0 (−0.5)0.04 (−1.55)−0.04 (−1.33)−0.04 (−1.72)
r2 = 0.06 NSr2 = 0.23*r2 = 0.11*r2 = 0.09 NSr2 = 0.29*r2 = 0.13*
Ψ50 (MPa)−9.4 (0.3) a7.7 (−0.2) a7.8 (−0.3)−0.06 (−2.17) a0.05 (−2.09) a−0.04 (−2.42)
r2 = 0.30**r2 = 0.65 **r2 = 0.35 **r2 = 0.25**r2 = 0.47**r2 = 0.23**
Ψ88 (MPa)14.1 1.1 a9.7 (−0.2) a10.7 (−0.1)0.08 (−2.79) a0.05 (−2.85) a−0.05 (−3.17)
r2 = 0.52**r2 = 0.81**r2 = 0.50**r2 = 0.32**r2 = 0.41**r2 = 0.24**
s (PLC MPa−1)−325 183 a−153 (126) b−220 (150)−1.35 (85.50)−0.27 (71.05)−0.62 (78.12)
r2 = 0.25**r2 = 0.21*r2 = 0.16*r2 = 0.08 NSr2 = 0.01 NSr2 = 0.03 NS
C0.5−2 (RWC MPa−1)−2.7 (7.8)18.2 (13.0)−13.3 (11.4)−0.37 (29.31)−0.27 (18.96)−0.04 (23.25)
r2 = 0.01 NSr2 = 0.14*r2 = 0.02 NSr2 = 0.17*r2 = 0.06 NSr2 = 0.01 NS
CΨ12 (RWC MPa−1)−57.4 (34.3)−15.0 (21.3)−34.2 (26.8)−0.46 (20.69)−0.02 (14.34)−0.11 (15.80)
r2 = 0.21*r2 = 0.04 NSr2 = 0.09*r2 = 0.29**r2 = 0.01 NSr2 = 0.02 NS
Cmax (RWC MPa−1)−40.7 (38.2)−21.2 (16.7)−7.3 (26.8)−0.37 (29.30)0.44 (14.44)0.04 (23.25)
r2 = 0.11 NSr2 = 0.02 NSr2 = 0.01 NSr2 = 0.18*r2 = 0.06 NSr2 = 0.01 NS

Radial growth rate of JW was 53% higher than MW (P = 0.02). There was no difference in radial growth rate for the last 200 years of growth within the mature trees (Fig. 4b), with an average value of 0.15 ± 0.01 cm year−1. Each new ring at node 15 increased the sapwood area by 11, 9 and 16% within the old-growth, mature and young trees, respectively. At the base of the old-growth and mature trees, the yearly increment of sapwood (in.Sap) was 2 and 4%, respectively.

Height growth rates of ponderosa pine were significantly higher in the mature trees than in the other trees (P < 0.002) with a peak at 75 years (Fig. 5a). In the mature trees the rates stayed constant through the life span of the trees with an average value of 0.22 ± 0.02 cm year−1. For the top of the trees (node 15), height growth rates of old-growth and young trees were not significantly different (P > 0.16), with an average value of 13 ± 1 cm year−1. We could not fit the usual height growth curves (Barrett 1978) because the predicted curve underestimated the height of the trees after 150 years (Fig. 5b).

Figure 5.

(a) Height growth rate and (b) tree height as a function of cambial age (ring from pith) within the old-growth trees and the mature trees (insert) (mean ± SE, n= 6 trees). The solid line represents the published curves of height growth with tree age for ponderosa pine and for a calculated site index of 28 (Barrett 1978).

Using the weighted values from each disc with the three age classes, we asked whether there was a relationship between the hydraulic parameters and the height growth rate, diameter growth rate, and/or the yearly increment of sapwood (in.sap). For all type of samples, Ψ12 was strongly and positively correlated with the height growth rate (Figs 6a; P < 0.001). Within the old-growth trees only, height growth rate was positively correlated (P < 0.05) with ks and with the annual percentage increment of sapwood (Fig. 6b). For all type of samples, Ψ12 and ks were correlated (P < 0.05) with in.sap (Fig. 7). There was, however, no correlation between any of the hydraulics parameters and the diameter growth rate (data not shown).

Figure 6.

Height growth rate (GRH) versus (a) the mean air entry point (Ψ12) and (b) the specific conductivity (ks) (mean ± SE, n= 6 trees). The regression line in (b) was fitted through the young and old-growth trees only.

Figure 7.

Percentage yearly increase in sapwood area (in.Sap) versus (a) the mean air entry point (Ψ12) and (b) the specific conductivity (ks) (mean ± SE, n= 6 trees).

DISCUSSION

Contrast between ponderosa pine and Douglas-fir trunks

This study showed that ponderosa pine trunks exhibited greater vulnerability to embolism than those of Douglas-fir trunks (Domec & Gartner 2001). At the branch level, Linton, Sperry & Williams (1998), and Piñol & Sala (2000) showed that pine species maintain a large amount of sapwood and a high leaf specific conductivity at the cost of being more vulnerable to embolism than the other conifers studied. There was also a steeper slope s in ponderosa pine (current study) than in Douglas-fir (Domec & Gartner 2001), which indicates a more conservative evolved strategy of the xylem because of a smaller margin of safety between the air entry point (Ψ12) and the full embolism point, Ψ88 (Sperry 1995), and because of a twofold difference in Cmax. For the old-growth trees, contrary to what we found within the trunk of mature Douglas-fir, water storage capacities for the natural range of Ψ were not significantly lower for the top of tree than for any other locations. This result may be a consequence of higher sapwood volume in ponderosa pine, which compensates for lower values of capacitance at the base of the trees. However, the strong relationships between ks and the vulnerability parameters by height position within the old-growth trees were consistent with the Douglas-fir pattern.

For the air entry point (Ψ12), inner sapwood was more vulnerable to embolism than outer sapwood only in the mature trees, not within the old-growth trees, which supported what we found in Douglas-fir (Domec & Gartner 2001). After more than 110 years, inner (old) sapwood of conifers is still as efficient and safe as outer (young) sapwood.

Hydraulic trends between trees

Contrary to our expectations, no general trend could be extracted regarding tree age versus vulnerability to embolism. Mature trees were less resistant to embolism than the older and younger age classes and this trend was not compensated by high water storage capacity compared to young and old-growth trees (Table 3). Mature trees had 12 PLC at −1.6 and −1.9 MPa for nodes 15 and 50, respectively, which are water potentials (Ψ) likely to occur in dry ponderosa pine sites (Hubbard et al. 1999; Ryan et al. 2000; authors’ field observations). In ponderosa pine branches, 50 PLC occurred at mean water potential (Ψ50) of −2.6 MPa (Maherali & DeLucia 2000), which approximates the value reported in the trunk for mature trees but is higher than the trunk values of old-growth trees (Table 3).

Embolized tracheids will be diluted by new growth more rapidly in young parts of trees than in the base of old trees because new growth makes up a lower proportion of the base of a tree, which can have 150 or 200 years of sapwood. This faster replacement in young trees was associated with a lower ks (Fig. 7b), suggesting that the less efficient the sapwood is for water transport, the more dependent the old sapwood is on the new sapwood. Many studies have shown a clear relationship between the occurrence of embolisms in conducting cells and a reduction in ks of the xylem (Tyree et al. 1991; Zwieniecki & Holbrook 1998). Although still poorly understood (Tyree et al. 1999), the refilling of tracheids may be important to compensate for the low increase in sapwood area from one year to another in old trees.

Hydraulic trends within trees

Contrary to one of our initial hypotheses, vulnerability to embolism in JW was not lower than in MW for any of the vulnerability parameters (Fig. 1, Table 3). In the main trunk of ponderosa pine, we found that the base and the top (node 15) of the old-growth trees were less vulnerable to embolism than were the intermediate parts of the trunk (node 65 and node 50). Subject to higher Ψ, the base of the old-growth would be at lower risk of embolism than the other parts of the trunk, with the node 65 (lower third of the live crown) being the least safe of all. There appears to be a trade-off between ks and resistance to embolism. The vulnerability parameters were negatively correlated with ks within the old-growth trees and the young trees (However, this negative correlation was not seen for the mature trees for Ψ12,Fig. 2). For the young and old-growth trees, the low storage capacity found for the range of Ψ at which the plants operate (generally 0.5–2.0 MPa) suggests that water uptake would be in phase with water loss. The advantage of maintaining this steady state flow is underscored by the fact little conductivity is lost at water potential less negative than −2.5 MPa (Fig. 1).

Trade-offs between water transport and mechanical properties

This research showed a complex relationship between water transport and mechanical properties in the ponderosa pine xylem. There were relatively strong negative relationships between the three hydraulic parameters (ks, Ψ50, andΨ88) and the two mechanical measures (wood density and latewood proportion; Table 5). However, in most cases, these relationships were much stronger for either JW or MW alone than for the two types combined. The fact that JW and MW had different relationships between hydraulic parameters and wood density implies that on the whole-disc scale there is not a trade-off between water transport and mechanical properties.

The ks was more sensitive to changes in density in MW than in JW. Within MW but not within JW, wood density was also strongly correlated with Ψ12. It appears that MW can adjust its resistance to embolism by increasing its wood density (Hacke et al. 2001) but at a cost of reducing ks. On the other hand, an increase in hydraulic efficiency in JW due to decreasing wood density would have no effect on its hydraulic safety.

We propose that distinct differences between JW and MW evolved in conifers for hydraulic reasons, as shown within mature Douglas-fir (Domec & Gartner 2002). The relationships within MW are the easiest to understand: MW is relatively uniform in its wood anatomy with respects to growth ring width, latewood proportion, tracheid diameter and tracheid length (Megraw 1986), and so samples with high density will tend to have thicker cell walls and smaller lumens than samples with lower density. In JW, it is more complex because the anatomical patterns change from one growth ring to the next (i.e. inner rings are wider than outer ones, and cells get wider and longer from inner to outer JW). The anatomical patterns will tend to cause an increase in ks. However, density can follow a complex pattern in JW, with high values near the pith, decreasing to lower values, and than an increase again (Fig. 4a). Therefore relationships of ks and density within JW will not necessarily be strong

Correlation between hydraulic parameters and height growth

Both ks and Ψ12 were correlated with height growth rate (Fig. 6). These correlations suggest that in ponderosa pine trees, the primary meristem and/or its products has some sort of influence over the hydraulic properties of the wood developed from the secondary meristem. However, the lack of correlation between these hydraulic parameters and the diameter growth rate suggests that there is no direct control by the secondary cambium over the ability of wood to resist to embolism. A previous study showed that the secondary cambium starts making MW when trees culminate their height growth (Kucera 1994) in one coniferous species.

Seasonal changes in allocation may decrease wood and height growth through increased respiration of woody biomass (Ryan, Binkley & Fownes 1997) and/or increased root costs because of decreased nutrition (Grulke & Retzlaff 2001). A concurrent study on the same trees as those used here reported that sapwood at the treetop released 50% more CO2 than at the base, and that sapwood of the mature trees had lower rates of respiration than the old-growth and young trees under controlled conditions (Pruyn et al. 2002). These data suggest that the release of water through embolism in mature trees could decrease wood respiration, although the mechanism and adaptive value are unclear. More detailed measurements of trunk respiration in response to Ψ and embolism are necessary to link an increase in height growth rate to a decrease in respiration as a consequence of water released by embolism.

Height growth at our study site (Fig. 5b) did not fit the growth curves found in the literature (Barrett 1978), which could be related to the fact that water limitation has more of an effect on even-aged than multi-aged stand structures (Nagel & O’Hara 2002). Water supply is determined by the Ψ gradient from soil to leaf, and the conductivity and capacitance of the hydraulic pathway. In this study, conductivities and capacitances were higher in the old-growth trees than in the mature and small trees. Ryan & Yoder (1997) proposed that transpiration and net CO2 uptake, and therefore growth, are limited by increasing axial hydraulic resistance as trees become older and taller. A negative feedback would then exist between tree height and hydraulic conductance. To maintain flow rates over longer distances, West, Brown & Enquist (1999) hypothesized that larger trees compensate by widening tracheids or vessels (which increases ks). We indeed found an increase in ks with cambial age at any given height within the old-growth trees (Table 3), but also a positive correlation between growth rate and ks (Fig. 6b). Therefore at the cell level, the hydraulic limitation to tree height was not confirmed by this study. If trees had to compensate hydraulically for their height with a more efficient xylem, then the growth rate would have been lower. On the other hand, the strong negative relationship between xylem safety and height growth rate support the hydraulic limitation hypothesis (Fig. 6a). Trees were able to compensate for their lower growth rate by the production of a safer xylem. These findings should be confirmed by studying the trade-offs between hydraulic parameters and growth efficiency expressed as trunk volume increment per unit leaf area (Waring 1983).

As in this study, Hann & Scrivani (1987) and Stanfield & McTague 1991) showed more rapid growth rates between the ages of 45 and 70 years (corresponding to our mature trees). Zhang et al. (1996, 1997) reported that some populations of Douglas-fir, ponderosa pine, and western larch used water and accumulated biomass quickly when water was available, but closed their stomata when water stress was imposed. Consistent with these observations, we found that the relative height growth rate of the ponderosa pine was highest for the trees most vulnerable to embolism, but was intermediate for trees that were less vulnerable. The plastic response of the mature trees would be advantageous in dealing with environmental stresses because it would confer a competitive benefit by optimizing carbon gain under favourable conditions and minimizing water loss when water is limited (Scheiner 1993; Irvine et al. 2002). However, this plasticity did come at the cost of increased vulnerability to embolism as suggested by Tyree & Ewers (1991). Partial trunk embolism would reduce transpiration rates and stomatal conductance through a reduction in hydraulic conductance (Meinzer & Grantz 1990; Hubbard et al. 2001). Stomata close to maintain leaf Ψ above a critical level that would cause irreversible embolism (Cochard, Bréda & Granier 1996; Salleo et al. 2000). Maintenance of a high rate of height growth was at the cost of having partial trunk embolism. However, it was compensated by higher capacitance between 0.5 and 2.0 MPa (Fig. 3a) that could buffer an increased hydraulic resistance (Stratton, Goldstein & Meinzer 2000; Phillips et al. 2002).

ACKNOWLEDGMENTS

This project was supported by USDA CSREES 96-35103-3832 and 97-35103-5052, and a special USDA grant to Oregon State University for wood utilization research. The authors acknowledge the assistance with tree felling provided by Roy Anderson, Michele Pruyn, Jennifer Swenson and André Meliott. We thank Crown Pacific Limited partnership, Gilchrist Forestry Division, OR for providing the trees.

Received 18 June 2002; received in revised form 13 September 2002; accepted for publication 20 September 2002

Ancillary