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Modelling the influence of stand structural, edaphic and climatic influences on juvenile Pinus radiata dynamic modulus of elasticity
Forest Ecology and Management 229 (2006) 136–144 www.elsevier.com/locate/foreco
Modelling the influence of stand structural, edaphic and climatic influences on juvenile Pinus radiata dynamic modulus of elasticity Michael S. Watt a,*, John R. Moore a, Jean-Philippe Fac¸on b, Geoff M. Downes c, Peter W. Clinton a, Graham Coker a, Murray R. Davis a, Robyn Simcock d, Roger L. Parfitt e, John Dando e, Euan G. Mason f, Horacio E. Bown f a
Ensis, PO Box 29237, Christchurch, New Zealand Ecole Polytechnique, 91128 Palaiseau, Cedex, France c CSIRO Forestry and Forest Products, Private Bag 12, Hobart, Australia d Landcare Research, Private Bag 92170, Auckland, New Zealand e Landcare Research, Private Bag 11052, Palmerston North, New Zealand f School of Forestry, University of Canterbury, Private Bag 4800, Christchuch, New Zealand b
Received 12 January 2006; received in revised form 22 March 2006; accepted 22 March 2006
Abstract Data from a nationwide set of Pinus radiata site quality plots established at high stand densities and grown over a period of 4 years were analysed to (i) determine how site and fertiliser influence dynamic modulus of elasticity (E) of the stem at the tree base, and (ii) develop a predictive model of E for basal stemwood. Site had a highly significant (P < 0.001) influence on E, which exhibited an almost three-fold range from 2.3 to 6.3 GPa, across the 21 site quality plots. When compared to the unfertilised controls, fertilisation had a relatively minor and insignificant effect on E, reducing values by on average 6%. This demonstrated the insensitivity of E to Bray phosphorus (P), Olsen P, inorganic P, and exchangeable potassium which were elevated in the soil by on average two- to three-fold by application of fertiliser. In total, 13 variables were found to be significantly related to E. Minimum temperature during early autumn (March) and tree slenderness (determined as tree height/ground-line tree diameter), also known as taper, exhibited the strongest correlations with E, accounting for 61 and 60% of the variance in this property, respectively. A multiple regression model with these two variables predicted 75% of the variance in E. Residuals from this model exhibited little apparent bias with predicted values, or independent variables. Results indicate that E may be relatively simple to predict across environments as stem slenderness can be readily obtained from either regional growth models or stand inventory, while temperature data can be obtained from regional or national climate surfaces. The relationship found between E and stem slenderness is consistent with the Euler buckling formula which suggests in a competitive situation increases in stem slenderness will induce increases in E to reduce the risk of stem buckling. The significant influence of temperature during early autumn on E may be mediated through regulation of latewood development. Given that latewood with high E is forming during early autumn, sites with higher temperatures and increased growth rates over this month are likely to develop a greater percentage of high E latewood, and as a consequence a higher overall stem E. # 2006 Elsevier B.V. All rights reserved. Keywords: Pinus radiata; Modulus of elasticity; Stem slenderness; Taper; Temperature; Environment; Euler buckling
1. Introduction
* Corresponding author. Ensis, PO Box 29237, Fendalton, Christchurch, New Zealand. Tel.: +64 3 364 2949; fax: +64 3 364 2812. E-mail address: [email protected] (M.S. Watt). 0378-1127/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2006.03.016
Advances in tree breeding and changes in silvicultural practice over the last few decades have greatly enhanced growth rates of plantation-grown conifers. These growth gains have led to shorter rotation lengths and an increased proportion of
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juvenile wood (Downes et al., 2000). Juvenile wood is generally characterised by low density, thin cell walls, short tracheids with small lumens, high grain angle, and high microfibril angle, with the result that it has low strength and stiffness, and poor dimensional stability compared to mature wood (Macdonald and Hubert, 2002). The growing recognition that this juvenile wood is of low value, has resulted in a recent shift in the way plantations are managed. Rather than focusing solely on maximisation of merchantable volume, management strategies are now starting to use genetic stock and implement practices which balance growth rate with optimisation of wood properties in the cambium (Evans, 1997; Downes et al., 2000). In the widely grown plantation softwood Pinus radiata, a useful indicator of corewood quality is modulus of elasticity (E) which measures the resistance of wood to deformation under an applied load. Although E is not an important property for pulp, it is used as a threshold criterion in machine stress grading of structural timber (Walker and Nakada, 1999) and is also a key property for determining quality of laminated veneer lumber. Modulus of elasticity is often considered more important than strength (modulus of rupture) for predicting wood quality because P. radiata boards rarely break in normal use; much more frequently a load results in excessive deflection (Walford, 1985). When compared with other internationally traded structural lumber species, plantation-grown P. radiata has relatively poor E and dimensional stability. As stemwood E of P. radiata increases with cambial age up to five-fold over the first 30 years (Cave, 1968), the low values of E found within the corewood are most limiting for timber utilisation. Recent research shows that P. radiata corewood E can be manipulated by management. At single sites significant and substantial gains in E have been shown through increasing initial stand density (Lasserre et al., 2005), reducing the level of weed control (Watt et al., 2005a), and use of clones with improved wood properties (Lindstro¨m et al., 2004). Despite our increased understanding of how management influences E, there is little information to indicate how environment influences E. Understanding environmental influences on E is crucial as this will enable sites to be closely matched to the correct silvicultural regimes and clonal material to optimise product outturn and value. Although there is little empirical evidence, theory suggests that E may be regulated by stem slenderness. When light demanding species such as P. radiata are grown under competition, rapid height growth is important to ensure that they are not overtopped by neighbours. Under high levels of competition trees become etiolated as priority is given to height growth at the expense of diameter increment. Based on Euler’s buckling formula, the critical height (Hcrit) that a vertical tree stem can reach before it undergoes elastic buckling is given by the following equation: Hcrit ¼ C
1=3 E 2=3 Ad r
(1)
where r is the density of green wood, Ad the stem diameter and C is a constant of proportionality (Greenhill, 1881). For a given
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E actual height will approach the critical height as height for a given diameter, or stem slenderness, increases. Eq. (1) shows that trees can increase their critical height to avoid buckling as slenderness increases by increasing their density-specific stiffness (E/r), which is mainly accomplished through increases in E as green density is relatively constant (Lasserre et al., 2005). In addition to stem slenderness a number of edaphic and climatic factors may also influence E. Previous research shows that addition of fertiliser induces a small but significant reduction in E of P. radiata (Downes et al., 2002). Little research, however, has determined which if any soil chemical properties are responsible for alterations to E, through fertilisation. Given that wood with high E forms in latewood (Watt et al., 2005a) site variation in E may also be attributed to variation in climatic variables, which alter the proportion of latewood within the stem. Although research at single sites over sub-annual intervals has reported the importance of air temperature and water availability in regulating microfibril angle and E (Wimmer et al., 2002; Watt et al., 2005a) little research has investigated the influence of climatic conditions on E across broad environmental gradients. Linking the environment with wood properties at a broad scale requires high quality information on the climatic and edaphic conditions over a range of sites, at the time new wood is laid down. This type of data is available from a nationwide series of site quality plots established at sites encompassing the range of climatic and edaphic conditions found throughout plantations of P. radiata within New Zealand (Watt et al., 2005b). At each location trees were grown over a period of 4 years in plots with high stand density (spacing 0.5 0.5 m; 40,000 trees ha1), so that an endpoint (e.g. maximum leaf area) could be reached after a relatively short period of time. Through utilising data from the fertilised and unfertilised P. radiata subplots within this existing site quality network the aims of this study are to (i) determine the influence of site and fertilisation on E at the stem base and (ii) develop a predictive model of E for basal stemwood. 2. Methods 2.1. Location of site quality plots Sites were selected to represent the range in soil properties on which planted forests are currently established in New Zealand. Plots used within the trial series were established within the seven major soil orders on which 97.6% of the P. radiata resource occurs (Simcock, personal communication). The number of sites established on each soil order was weighted to be representative of the corresponding plantation area on which the soil order is found (Fig. 1). Sites were further screened using climatic surfaces (Leathwick and Stephens, 1998) to ensure that selected areas represented the considerable range in meteorological conditions found throughout New Zealand’s planted forests. When compared to long-term average values for all plantation forests (Anon, 1983), meteorological data recorded at each location indicate the 21 selected sites almost completely encompass the
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from the Scion nursery in Rotorua. The site quality plots were installed over 2-year period from 2000 to 2001. In fertilised plots broadcast application of fertiliser was undertaken three times a year during the first year (winter, spring, summer) and thereafter during spring at annual intervals. Over the 4 years of the study the elemental quantity of nitrogen, phosphorus, potassium, sulphur, magnesium and calcium applied to each fertilised plot was 690, 200, 558, 160, 40 and 160 kg ha1, respectively. At sites identified by soil analysis (at time of planting) as being deficient in boron, magnesium and copper, additional applications of these nutrients to fertilised plots were made during summer in sufficient quantities to ensure these nutrients were non-limiting. Disturbed plots were located on areas compacted by previous harvesting operations. 2.3. Measurements
Fig. 1. Distribution map of soil orders in New Zealand, showing location of site quality plots used in this study.
range in total annual rainfall (NZ plantations 609–3718 mm versus our sites 457–3074 mm) and mean annual temperature (NZ plantations 8.0–15.6 8C versus our sites 8.6–15.3 8C). 2.2. Experimental design Site quality plots were located at each of the 21 selected locations. At each location a series of eight plots was installed using a factorial design with the following three factors: species (P. radiata and Cupressus lusitanica Mill.), fertiliser (no fertiliser and nutrients supplied in excess of crop requirements) and disturbance (low and high disturbance). In this paper measurements and modelling were restricted to only the P. radiata subplots. Samples were taken from fertilised and unfertilised subplots in the undisturbed treatments at all but three sites. At these three sites samples were taken from the disturbed plots as excessive mortality precluded use of the undisturbed plots. Each plot was small in size (3 m 3 m) and contained nine measurement trees spaced at 0.5 m 0.5 m (40,000 trees ha1) surrounded by a two-row buffer. Regular applications of herbicide were made to ensure weed-free conditions. All sites were planted with 1-year-old P. radiata seedlings with a growth and form factor of 19 (Vincent and Dunstan, 1989), sourced
Soil physical properties were measured on samples of mineral soil taken from the edges of disturbed and undisturbed plots immediately prior to planting. Air capacity (at 10 kPa), macroporosity (at 5 kPa), total porosity, bulk density, particle density, cone penetration resistance (at 10 kPa), stone content and total available water were determined by horizon down to impermeable layers, following the procedures described by Gradwell (1972). For consistency all soil physical properties reported in this paper are averaged from 0 to100 mm, except total available water content and stone content which has been determined over the root depth, as measured at harvest. A soil pit was excavated down to impermeable layers prior to plot establishment in an undisturbed area adjacent to each site quality plot to determine soil texture. From this pit, particle size was measured by dispersing the field-moist soil in water with an ultrasonic probe and separating the <2, 2–63 and >63 mm fractions by sedimentation. All textural properties reported have been averaged over a depth of 0–100 mm. Ground-line diameter and height of the nine measurement trees were measured annually. Leaf area index, Lt, was estimated every 4 months using a canopy analyser (LAI-2000, Li-Cor Inc., Lincoln, NE, USA). Measurements of photosynthetically active photon flux density, air temperature and relative humidity were taken from sensors installed on a 3 m tower located adjacent to the experimental plots. A tipping bucket rain gauge positioned on top of the tower was used to measure above-canopy rainfall. A comprehensive set of soil chemical measurements were taken from the site quality plots after harvest at age 4 years. Soil chemistry samples were taken from 0 to 100 mm depth at 16 points in all harvested sub-plots to give 16 cores per bag. Sampling points were located at least 0.5 m apart around the nine trees at the centre of the plots. These samples were bulked by treatment then analysed for soil moisture, pH in water, total carbon (C), total soil nitrogen (N), total soil phosphorus (P), soil organic P, Bray P, Olsen P, exchangeable bases, and CEC, following the methods described by Blakemore et al. (1987). Results are expressed on an oven dry basis (105 8C).
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At age 4 years trees were extracted from the ground, when ground-line diameter averaged 46 mm and height averaged 3.7 m (Table 2). Plot level estimates of root depth were determined by measuring the depth of the deepest root on five trees per plot. A 300 mm section of the stem centred around 10% of the total tree height was cut from each tree. This sample was placed in a plastic bag with water and transported back to the laboratory, where it was frozen until measurements were taken. In the laboratory, stem samples were left in water for 48 h to ensure that they were defrosted. Green density (r) was determined as green weight/green volume. Green volume was determined using the immersion technique. Green dynamic modulus of elasticity (Pa) was determined from measurements of green density r (kg m3) and sound velocity V (m s1), using the following equation: E ¼ rV 2
(2)
Sound velocity was measured by the resonance-based tool, Woodspec (Industrial Research, Lower Hutt, New Zealand). This tool uses the impact from a pendulum to generate a stress wave within the wood sample. The acoustic velocity is then determined from the frequency of the reverberation of this stress wave within the sample. The stress wave must travel twice the length of the sample during one oscillation cycle. Therefore, the velocity of the wave is given by V ¼ 2l f
(3)
where f is the fundamental resonance frequency (Hz) and l is the sample length (m). By substituting (3) into (2) E is given by the following equation: E ¼ 4rl2 f 2
(4)
In a recent study using material from 4-year-old P. radiata clones, Lindstro¨m et al. (2002) found that correspondence between E measured using the resonance technique and traditional static bending was very strong (r2 = 0.98) and relatively unbiased (y = 1.04x). 2.4. Determination of root zone water balance A daily water balance equation was used to calculate root zone water storage (W) on the ith day as: Wi ¼ Wi1 þ Pi Eti Etwi Egi Fi
(5)
where Pi is rainfall, Eti the transpiration from the dry tree canopy, Etwi the evaporation of intercepted rainfall from the tree canopy, Egi the evaporation from the soil, and F i is the drainage from the root zone (Whitehead et al., 2001). Transpiration from the tree canopy was calculated using the simple diffusion equation: Et ¼ ’Dgst Lt
(6)
where D is the air saturation deficit, gst the average stomatal conductance for the canopy and Lt is the projected leaf area index, and w will be defined later. The inverse relationship between stomatal conductance and air saturation deficit was
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modelled using the function described by Lohammer et al. (1980) as: 1 ðD Dsmin Þ (7) gst ¼ gstmax 1 þ D0 where gstmax describes maximum stomatal conductance at low air saturation deficit, and D0 is the sensitivity of gst to D, when D > Dsmin. Eg was calculated from the available energy beneath the tree canopy, Gg, as: Eg ¼
’tsGg lðs þ gÞ
(8)
where the coefficient t (1.4) describes the degree of coupling of the soil surface with the air above the canopy (Kelliher et al., 1990), s the slope of the relationship between saturated vapour pressure and temperature at a given air temperature, l the latent heat of vaporisation, g the psychometric constant, and w will be defined later. Values for s, g, and l are temperature-dependant and calculated from standard meteorological tables. Using Beers Law, Gg was calculated from (ekLt Ga ) where Ga is the available flux density above the canopy (assumed to be 70% of short-wave radiation) and k is the light extinction coefficient (assumed to be 0.5 for a spherical leaf angle distribution). The coefficient w was used to reduce evaporation from the soil and transpiration as soil water storage declined. Root zone volumetric water content on the ith day, ui (Wi/[d(1 c)]), was calculated from water storage in the profile (Wi), root zone depth (d), and fractional stone content of the soil (c). The value of the coefficient w was set to 1 at maximum values of u (umax), and was not reduced until u declined to a threshold value (ut). As u progressively declined below this threshold w was linearly reduced from 1 to 0 at minimum values of u (umin). The threshold values (ut) for reducing evaporation from the soil and transpiration, taken from Watt et al. (2003), were assumed to be respectively, 60 and 55% of the fractional available volumetric water content, ua, determined as: ui umin ua ¼ (9) umax umin Estimated evaporation from the soil and transpiration were reduced to 50% of their potential rates on days when rain fell. Drainage from the root zone was assumed to be zero when ui umax and equal to rainfall reaching the soil when ui > umax. Daily meteorological data required for the water balance model include total rainfall and solar radiation, mean air temperature, and average air saturation deficit. Parameter values for gstmax, D0, and Dsmin were assumed to be 0.15 mol2 s1, 0.94 kPa, and 0.5 kPa, respectively. As previously described, values of root depth (d), stone content (c), umax and umin were measured at each site. Lt was modelled at a daily level by interpolating between seasonal measurements using a spline function. Following Landsberg and Waring (1997), wet canopy evaporation as a percentage of daily rainfall, P, was assumed to increase linearly from 0 at Lt of 0 to
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Table 1 Site level variation in climatic variables, and soil physical properties Variable
Mean and range
Climatic variables Mean annual temp. (8C) Min. March temp. (8C) Solar radiation (MJ PAR m2) Rainfall (mm)
11.6 (8.6–15.3) 10.1 (6.8–14.6) 5.6 (4.1–6.8) 1493 (457–3074)
Soil physical properties Coarse sand (%) Medium sand (%) Fine sand (%) Sand (%) Silt (%) Clay (%) Bulk density (g cm3) Particle density (g cm3) Penetration resistance (MPa) Total porosity (%, v/v) Macroporosity (%) Air capacity (%)
7 (0–57) 10 (1–33) 22 (2–69) 39 (5–93) 40 (4–71) 21 (3–49) 0.96 (0.47–1.35) 2.5 (2.2–3.0) 0.85 (0.37–1.75) 63 (49–79) 21 (7–49) 23 (8–45)
Values shown are the mean followed by the range in brackets for the 21 sites.
(0.15P) at Lt of 3, after which there were no further increases. All analyses use average fractional available volumetric water content, ua. During the fourth year after planting monthly gravimetric measurements of ua were made to a depth of 30 cm at three sites subject to seasonal water deficits. Modelled values of ua
exhibited good correspondence with the seasonal measurements at each site. Average absolute differences between measured and modelled ua at the three sites were 1, 8, and 3%, respectively. 2.5. Data analysis All analyses were undertaken in SAS (SAS Institute, 1996). Variables were tested for normality and homogeneity of variance and transformations made as necessary to meet the underlying statistical assumptions of the models used. Values for all structural variables used in the analysis were taken at harvest (age four). Stem slenderness, at age four, is defined here as height/ground-line diameter. A two-way analysis of variance (ANOVA) was used to test for the main effects of fertilisation and site on E, stand structural characteristics, ua, and soil chemical properties within the top 100 mm of the mineral horizon. Univariate relationships between E and all independent variables were examined (see Tables 1 and 2 for list of these variables), using appropriate functional forms to determine which variables were significantly related to E. A multiple regression model for E was constructed using those variables found to be significantly related to this property in the univariate analysis. Using appropriate functional forms and any necessary transformations, variables were sequentially introduced into the model. Variables were only retained if inclusion significantly improved the model and parameter values for the
Table 2 Stand structural characteristics, average fractional available volumetric water content (ua), and soil chemical properties in the top 100 mm of the mineral soil for unfertilised and fertilised plots sampled at 21 sites Unfertilised plots Mean Structural variables, and ua Ground-line diameter (mm) Height (m) Stem slenderness (m m1) Root depth (m) Average ua Chemical properties Carbon (%) Total N (%) CN ratio pH CEC (cmol g1) Exch. Na (cmol g1) Exch. K (cmol g1) Exch. Mg (cmol g1) Exch. Ca (cmol g1) Sum bases (cmol g1) Base saturation (%) Olsen P (mg g1) Bray P (mg g1) Inorganic P (mg g1) Organic P (mg g1)
Fertilised plots Range
Mean
Analysis of variance Range
Site
Fert.
46 3.7 82 0.5 0.69
17–60 0.9–5.7 52–109 0.2–0.8 0.36–0.89
51 4.0 82 0.5 0.68
36–60 2.5–5.4 54–108 0.2–1.0 0.37–0.90
0.72** 0.92*** 0.93*** 0.92*** 0.99***
0.09** 0.02* ns ns ns
6.2 0.30 20 5.1 20 0.27 0.39 1.6 5.0 7.3 35 10 26 136 327
1.7–26.7 0.11–0.85 11–31 4.1–6.0 10–43 0–0.74 0.09–0.99 0.4–3.9 0.1–21.4 0.8–23.3 8–94 2–33 2–184 12–415 74–601
6.4 0.31 20 4.8 20 0.29 0.64 1.7 3.9 6.5 33 28 74 253 328
2.2–24.5 0.13–0.80 14–30 3.9–5.7 9–46 0–0.68 0.13–1.22 0.5–4.1 0.5–12.5 1.4–16.2 8–71 8–65 11–195 32–547 80–657
0.98*** 0.95*** 0.94*** 0.87*** 0.97*** 0.90*** 0.75*** 0.94*** 0.90*** 0.97*** 0.95*** 0.51* 0.67*** 0.72*** 0.93***
ns ns ns 0.07*** ns ns 0.17*** ns 0.02* ns ns 0.32*** 0.19*** 0.19*** ns
The influence of fertilisation (Fert.) and site on each soil property is shown by partial r2 values followed by significance levels. ns: Non-significant at P = 0.05. * Represents significance at P = 0.05. ** Represents significance at P = 0.01. *** Represents significance at P = 0.001.
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included variables were significant. In constructing the model emphasis was placed on developing a simple equation with very little apparent bias. To determine the influence of structural variables on E, independently of climatic variation between sites, a mixed effects model was constructed in SAS. In this model structural variables were treated as fixed effects while site was treated as a random effect. 3. Results 3.1. Variation in site level climatic and edaphic properties There was considerable variation in climate between sites (Table 1). Across sites, mean annual rainfall ranged from 457 mm at an inland east coast site in the South Island (site 19; Fig. 1) up to 3074 mm at a site west of the main divide in the South Island (site 16; Fig. 1). Annual average temperature exhibited a two-fold variation from 8.6 8C at a high elevation South Island site (site 19; Fig. 1) to 15.3 8C at a coastal site (site 3; Fig. 1) in the northern North Island. The selected sites included extremes in soil texture ranging from single-grained scoria and sandy soils to clay loam soils. Variation in soil texture was considerable for all texture classes and exhibited the greatest range for the sand (5–93%), and silt (4–71%) fractions (Table 1). Soil physical properties also exhibited considerable variation between sites. This variation was most pronounced for the closely related variables macroporosity and air capacity which ranged from 7 to 49% and 8 to 45%, respectively, across sites. 3.2. Impact of site and fertilisation on E, structural and edaphic variables Modulus of elasticity exhibited a significant (P < 0.001) three-fold variation across sites (2.3–6.3 GPa). Although fertilisation generally reduced E within sites by an average of 6% (Fig. 2) these differences were not significant. All stand structural characteristics significantly varied between sites (Table 2). The treatment averaged range in
Fig. 2. Site variation in E for fertilised (open circles) and unfertilised (closed circles) plots. Values are sorted in descending order, after averaging at the site level. Each value shown is the mean with associated standard error.
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height and diameter at age four was considerable across sites, varying two-fold for diameter (26–56 mm) and three-fold (1.74–5.52 m) for height. Site level variation was also considerable for stem slenderness (height/ground-line diameter) ranging two-fold from 53 to 109 m m1. Across sites, average fractional available volumetric water content significantly ranged from 0.37 on a dryland site (site 19; Fig. 1) with low annual rainfall (457 mm) to 0.89 on a wet site (site 16; Fig. 1) with annual average rainfall of 3074 mm. Fertilisation had a significant influence on tree ground-line diameter and height inducing gains of 11, and 8%, respectively, for these characteristics (Table 2). Fertilisation did not significantly influence average fractional available volumetric water content, stem slenderness, or root depth. All soil chemical properties exhibited significant variation between sites (Table 2). When averaged at the site level variation was most marked for exchangeable calcium, Bray P, inorganic P and the sum of bases, which exhibited respective ranges of 54-, 25-, 20-, and 18-fold across sites. Fertilisation significantly influenced six of the 15 properties sampled. Fertiliser induced gains were greatest for Olsen P (three-fold), Bray P (three-fold), inorganic P (two-fold) and exchangeable potassium (two-fold). Fertilisation also significantly reduced pH by 6%, relative to the control (4.8 versus 5.1). 3.3. Modelling site effects on E In total, 13 variables were significantly related to E (Table 3). Most of the strongest relationships were with either structural or climatic variables. Stem slenderness, mean annual air temperature, tree height, and root depth had highly significant (P < 0.0001) positive relationships with E. The peaked relationship between E and average fractional available volumetric water content was also highly significant (P < 0.0001). The only soil chemical property significantly related to E was organic phosphorus. This variable exhibited a peaked relationship with E with maximum values of E occurring at organic phosphorus concentrations of 307 mg g1. Table 3 Variables found to be significantly related to E. For each variable the coefficient of determination (r2) and the significance level is shown Variable
r2/P-value
Stem slenderness Mean annual air temp. Tree height Average ua Organic phosphorus Tree root depth Wood density Average particle size Percentage silt Particle density Percent fine sand Root collar diameter Percent sand
0.61*** 0.53*** 0.50*** 0.33*** 0.30** 0.29*** 0.22** 0.22** 0.21** 0.20* 0.18** 0.13* 0.12*
* ** ***
Represents significance at P = 0.05. Represents significance at P = 0.01. Represents significance at P = 0.001.
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(Fig. 3a). Fertilisation did not significantly influence this relationship. The strong (r2 = 0.61) positive linear relationship between stem slenderness and E (Fig. 3b) did not significantly differ between fertilisation treatments. The relationship between E and average fractional available volumetric water content (ua) was peaked with maximum values of E occurring at ua values of 0.66 (Fig. 3c). The final model for E included mean minimum air temperature during March (Tmin) and stem slenderness (S) in the following linear equation: E ¼ 1:45 þ 0:238Tmin þ 0:041S
(10)
The overall model and parameter values for both variables were highly significant (P < 0.001), suggesting that the significant but weak (r2 = 0.30) correlation between Tmin and S was not likely to adversely influence the model. Analysis of covariance indicated that the model was not significantly influenced by fertilisation treatment. The total amount of variance in E explained by the model was 75%. Residuals exhibited very little apparent bias when plotted against either predicted values, or independent variables. A mixed effects model which included site as a random effect and stem slenderness as a fixed effect indicated that after site effects were removed, slenderness had a significant positive influence on E of trees within the site (P < 0.001). Similar analyses with other structural variables indicated that tree height within sites was significantly, although somewhat more weakly, related to E (P < 0.01). Within sites, tree diameter was not significantly related to E. 4. Discussion
Fig. 3. Relationship between E and (a) mean minimum temperature in March, (b) stem slenderness, and (c) fractional available volumetric water content.
When examined at the annual level E exhibited a stronger relationship with average minimum temperature (r2 = 0.57), than either average mean (r2 = 0.53) or average maximum (r2 = 0.43) annual temperature. At the monthly level the strongest relationship between average minimum temperature and E occurred in March during early autumn (r2 = 0.60). This relationship was positive up to 11.5 8C, after which E was relatively insensitive to further increases in temperature
This study shows considerable between site variation in P. radiata E measured in the first four rings. Further research should be undertaken to compare these values with measurements of E obtained from juvenile wood in older plantations where trees are growing at operational stand densities. If further research confirms these findings this could have considerable implications for forest managers given that low corewood values for E commonly limit structural timber utilisation in fast growing conifers (Kretschmann and Bendtsen, 1992; Cave and Walker, 1994; Walker and Butterfield, 1996; Tsehaye et al., 2000). The accurate determination of juvenile wood E across environmental gradients will enable sites to be closely matched to management regimes and clonal material to optimise product outturn and value. The significant influence of temperature on E may be mediated through regulation of latewood development. Analyses show that E was most strongly correlated with minimum temperature in early autumn. Given that latewood with high E is forming during this period (Watt et al., 2005a), it follows that sites with warmer temperatures and increased growth rates over this month will develop a greater percentage of high E latewood, and as a consequence higher overall stem E. The strong relationship found between E and stem slenderness has a sound theoretical basis. Using a variant of the Euler buckling formula, Greenhill (1881) showed that E
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scaled positively with the maximum slenderness that can be attained before buckling occurs. This relation has subsequently been used to determine the maximum slenderness which trees composed of a single tissue type, with known E, can attain (Niklas, 1994). The positive relationship found between E and slenderness in this study is consistent with this relationship and suggests that trees with high slenderness are increasing E to further increase the threshold at which buckling occurs. As heights of the trees in our study were relatively close to the critical buckling height, it is likely that wood properties were influenced by the need to avoid Euler buckling. Assuming the value of density-specific stiffness measured at the base of a tree is representative of the whole stem, our measurements show that the average safety margin (Hcrit/actual height) of the trees in this study was 2.1. These values are consistent with those reported for nine years old sweet gum growing under competition (Holbrook and Putz, 1989). However, they are considerably lower than the five-fold safety margins found by Niklas (1994), using data collected from the tallest specimen trees for 46 open-grown North American species. Stem slenderness was found to be significantly correlated to a number of variables of which the most important were positive relationships with mean annual air temperature (r2 = 0.30) and root depth (r2 = 0.35). As average fractional available volumetric water content (ua) also had a significant effect on slenderness (r2 = 0.2) it is likely that stem slenderness is to some extent regulated by this variable with peak values occurring at ua of 0.68 (data not shown). However, the greater significance of root depth over other related edaphic properties indicates that as well as being an indicator of soil water and sand content, root depth has additional significance as a determinant of stem slenderness, and therefore E. Results provide considerable insight into how environment regulates E. Sites with warm temperatures, and deep, sandy, well-drained soils with optimum ua, are likely to produce trees with high stem slenderness and high E. Conversely, cool sites with shallow soils and low sand content and high departures from optimum ua are likely to produce trees with low stem slenderness and low E. Examination of the data confirms this. The highest overall E (site 3; Fig. 1) occurred on the warmest site (Tmin = 14.6 8C), which had the highest root depth (0.89 m), close to optimum ua (0.69), and the sandiest soils (93%) out of the 21 sites. On a neighbouring site (site 2; Fig. 1) with the second highest Tmin (13.7 8C), close to optimum ua (0.68), but with very contrasting root depth (0.28 m) and sand content (9%) E was 2 MPa lower (6.33 versus 4.33 GPa), placing the site 12th highest out of the 21 sites, in terms of E. The lowest overall E (site 19; Fig. 1) occurred on the coldest site (Tmin = 6.83 8C) which had below average sand content, average root depth and the lowest ua (0.37) out of the 21 sites. The significant relationship found between stem slenderness and E within sites strengthens findings between sites. This result suggests that within site variation in E may be mediated through stem slenderness, and provides further evidence that the less significant effects of diameter and height are mediated through stem slenderness. The within site analysis also shows
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that the between site effect of stem slenderness on E is real and not a byproduct of the between site temperature influence on E. Despite the significant influence of fertilisation on growth rate, this treatment had a minor and insignificant influence on E. This finding indicates that E is relatively insensitive to considerable increases (in the order of two- to three-fold) in soil concentrations of Bray P, Olsen P, inorganic P and exchangeable Potassium. This lack of a response in E to fertiliser is consistent with the univariate relationships. The site level range was extensive for all important chemical properties including soil nitrogen. Despite this considerable site range the only chemical property significantly related to E was organic phosphorus, which was insensitive to application of fertiliser. These results suggest that growth gains obtained through fertiliser application may outweigh corresponding losses in wood quality attributable to reduced E. Although results from this study highlight the key determinants of E across an environmental gradient, further research should be carried out to confirm that these factors are the same for mature stands, grown at conventional stand densities. If further research shows that the key determinants of E identified in our study hold in older stands, the approach used in this study could become a useful operational tool for rapidly determining how environment influences wood quality. In conclusion this paper demonstrates that E may be relatively simple to predict across environments, as the key variables identified from a comprehensive set were temperature and stem slenderness. Stem slenderness could be obtained from either regional growth models or inventory data, while geographic information systems could be used to determine temperature, as splines describing variation in this variable at a fine resolution are currently available within New Zealand (Leathwick and Stephens, 1998). Results also highlight the insignificance of soil chemical properties on E, and suggest that gains in growth attributable to fertilisation may outweigh corresponding losses in E. Acknowledgements We are indebted to the numerous forest companies and private owners for providing sites for the trial series, and Hugh Wilde, Trevor Webb, Amy Taylor, Wim Rijkse, Craig Ross and Malcolm Mcleod who assisted in selection, identification and classification of soils. The help of technicians at the Landcare Research environmental chemistry lab in analysing samples is gratefully acknowledged. This project was funded by the New Zealand Foundation for Research Science and Technology under contract Nos. C04X0304 and C04X0203. References Anonymous, 1983. Summaries of Climatological Observations to 1980. New Zealand Meteorological Service Misc. Pub. 177, Wellington, New Zealand. Blakemore, L.C., Searle, P.L., Daly, B.K., 1987. Methods for chemical analysis of soils. Department of Scientific and Industrial Research, New Zealand Soil Bureau Scientific Report No. 80. Cave, I.D., 1968. The anisotropic elasticity of the plant cell wall. Wood Sci. Technol. 2, 268–278.
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Cave, I.D., Walker, J.C.F., 1994. Stiffness of wood in fast-grown plantation softwoods: the influence of microfibril angle. Forest Prod. J. 44, 43–48. Downes, G.M., Evans, R., Schimleck, L.R., Fritts, H.C., 2000. The commercial cambium: understanding the origin of wood property variation. In: Savidge, R.A., Barnett, J.R., Napier, R. (Eds.), Cell and Molecular Biology of Wood Formation. BIOS Sci., Oxford, pp. 325–336. Downes, G.M., Nyakuengama, J.G., Evans, R., Northway, R., Blakemore, P., Dickson, R.L., Lausberg, M., 2002. Relationship between wood density, microfibril angle and stiffness in thinned and fertilized Pinus radiata. IAWA J. 23, 253–265. Evans, R., 1997. Rapid screening of microfibril angle in increment cores by Xray diffractometry. In: Butterfield, R. (Ed.), Proceedings of the IAWA/ IUFRO International Workshop on the Significance of Microfibril Angle to Wood Quality, Westport, New Zealand, pp. 116–139. Gradwell, M.W., 1972. Methods for physical analysis of soils. New Zealand Soil Bureau Scientific Report No. 10C. Wellington, DSIR. Greenhill, A.G., 1881. Determination of the greatest height consistent with stability that a vertical pole or mast can be made and of the greatest height to which a tree of given proportions can grow. Proc. Cambridge Philos. Soc. 4 (2), 65–73. Holbrook, N.M., Putz, F.E., 1989. Influence of neighbours on tree form: effects of lateral shade and prevention of sway on the allometry of Liquidamber styrafaciflua (Sweet gum). Am. J. Bot. 76 (12), 1740–1749. Kelliher, F.M., Whitehead, D., McAneney, K.J., Judd, M.J., 1990. Partitioning evapotranspiration into tree and understorey components in two young Pinus radiata D. Don stands. Agric. Forest Meteorol. 50, 211– 227. Kretschmann, D.E., Bendtsen, B.A., 1992. Ultimate tensile stress and modulus of elasticity of fast-grown plantation loblolly pine lumber. Wood Fiber Sci. 24, 189–203. Landsberg, J.J., Waring, R.H., 1997. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecol. Manage. 95, 209–228. Lasserre, J.P., Mason, E.G., Watt, M.S., 2005. The effects of genotype and spacing on Pinus radiata [D Don] corewood stiffness in an 11 year old experiment. Forest Ecol. Manage. 205, 375–383. Leathwick, J.R., Stephens, R.T.T., 1998. Climate surfaces for New Zealand. Landcare Res. Contract Report LC9798/126. Landcare Research. Lincoln, New Zealand, p. 19. Lindstro¨m, H., Harris, P., Nakada, R., 2002. Methods for measuring stiffness of young trees. Holz Roh Werkst. 60, 165–174.
Lindstro¨m, H., Harris, P., Sorensson, C.T., Evans, R., 2004. Stiffness and wood variation of 3-year old Pinus radiata clones. Wood Sci. Technol. 38 (8), 579–597. Lohammer, T., Larsson, S., Linder, S., Falk, S.O., 1980. FAST-Simulation models of gaseous exchange in Scots pine. Ecol. Bull. 32, 505–523. Macdonald, E., Hubert, J., 2002. A review of the effects of silviculture on timber quality of Sitka spruce. Forestry 75 (2), 107–138. Niklas, K., 1994. Plant Allometry — the Scaling of Form and Process. University of Chicago Press, p. 395. SAS Institute, 1996. SAS/STAT Software: changes and enhancements through release 6.11. SAS Institute Inc., Cary, NC. Tsehaye, A., Buchanan, A.H., Walker, J.C.F., 2000. Selecting trees for structural timber. Holz Roh Werkst. 58, 162–167. Vincent, T.G., Dunstan, J.S., 1989. Register of commercial seedlots issued by the New Zealand Forest Service. Ministry of Forestry, Rotorua. Forest Research Institute Bulletin No. 144, Forest Research Institute, Rotorua, New Zealand, p. 155. Walford, G.B., 1985. The mechanical properties of New Zealand-grown radiata pine for export to Australia. FRI Bulletin No. 93, Forest Research Institute, New Zealand Forest Service. Walker, J.C.F., Butterfield, B.G., 1996. The importance of microfibril angle for the processing industries. New Zeal. J. Forest. 40, 34–40. Walker, J.C.F., Nakada, R., 1999. Understanding corewood in some softwoods: a selective review on stiffness and acoustics. Int. Forest. Rev. 1, 251–259. Watt, M.S., Whitehead, D., Richardson, B., Mason, E.G., Leckie, A.L., 2003. Modelling the influence of weed competition on the growth of young Pinus radiata at a dryland site. Forest Ecol. Manage. 178, 271–286. Watt, M.S., Downes, G.M., Whitehead, D., Mason, E.G., Richardson, B., Grace, J.C., Moore, J.R., 2005a. Wood properties of juvenile Pinus radiata growing in the presence and absence of competing understory vegetation at a dryland site. Trees: Struct. Funct. 19, 580–586. Watt, M.S., Coker, G., Clinton, P.W., Davis, M., Parfitt, R., Simcock, R., Garrett, L., Payn, T., Richardson, B., Dunningham, A., 2005b. Defining sustainability of plantation forests through identification of site quality indicators influencing productivity — a national view for New Zealand. Forest Ecol. Manage. 216, 51–63. Whitehead, D., Leathwick, J.R., Walcroft, A.S., 2001. Modeling annual carbon uptake for the indigenous forests of New Zealand. Forest Sci. 47 (1), 9–19. Wimmer, R., Downes, G.M., Evans, R., 2002. Temporal variation of microfibril angle in Eucalyptus nitens grown in different irrigation regimes. Tree Physiol. 22, 449–457.
Modelling the influence of stand structural, edaphic and climatic influences on juvenile Pinus radiata dynamic modulus of elasticity Michael S. Watt a,*, John R. Moore a, Jean-Philippe Fac¸on b, Geoff M. Downes c, Peter W. Clinton a, Graham Coker a, Murray R. Davis a, Robyn Simcock d, Roger L. Parfitt e, John Dando e, Euan G. Mason f, Horacio E. Bown f a
Ensis, PO Box 29237, Christchurch, New Zealand Ecole Polytechnique, 91128 Palaiseau, Cedex, France c CSIRO Forestry and Forest Products, Private Bag 12, Hobart, Australia d Landcare Research, Private Bag 92170, Auckland, New Zealand e Landcare Research, Private Bag 11052, Palmerston North, New Zealand f School of Forestry, University of Canterbury, Private Bag 4800, Christchuch, New Zealand b
Received 12 January 2006; received in revised form 22 March 2006; accepted 22 March 2006
Abstract Data from a nationwide set of Pinus radiata site quality plots established at high stand densities and grown over a period of 4 years were analysed to (i) determine how site and fertiliser influence dynamic modulus of elasticity (E) of the stem at the tree base, and (ii) develop a predictive model of E for basal stemwood. Site had a highly significant (P < 0.001) influence on E, which exhibited an almost three-fold range from 2.3 to 6.3 GPa, across the 21 site quality plots. When compared to the unfertilised controls, fertilisation had a relatively minor and insignificant effect on E, reducing values by on average 6%. This demonstrated the insensitivity of E to Bray phosphorus (P), Olsen P, inorganic P, and exchangeable potassium which were elevated in the soil by on average two- to three-fold by application of fertiliser. In total, 13 variables were found to be significantly related to E. Minimum temperature during early autumn (March) and tree slenderness (determined as tree height/ground-line tree diameter), also known as taper, exhibited the strongest correlations with E, accounting for 61 and 60% of the variance in this property, respectively. A multiple regression model with these two variables predicted 75% of the variance in E. Residuals from this model exhibited little apparent bias with predicted values, or independent variables. Results indicate that E may be relatively simple to predict across environments as stem slenderness can be readily obtained from either regional growth models or stand inventory, while temperature data can be obtained from regional or national climate surfaces. The relationship found between E and stem slenderness is consistent with the Euler buckling formula which suggests in a competitive situation increases in stem slenderness will induce increases in E to reduce the risk of stem buckling. The significant influence of temperature during early autumn on E may be mediated through regulation of latewood development. Given that latewood with high E is forming during early autumn, sites with higher temperatures and increased growth rates over this month are likely to develop a greater percentage of high E latewood, and as a consequence a higher overall stem E. # 2006 Elsevier B.V. All rights reserved. Keywords: Pinus radiata; Modulus of elasticity; Stem slenderness; Taper; Temperature; Environment; Euler buckling
1. Introduction
* Corresponding author. Ensis, PO Box 29237, Fendalton, Christchurch, New Zealand. Tel.: +64 3 364 2949; fax: +64 3 364 2812. E-mail address: [email protected] (M.S. Watt). 0378-1127/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2006.03.016
Advances in tree breeding and changes in silvicultural practice over the last few decades have greatly enhanced growth rates of plantation-grown conifers. These growth gains have led to shorter rotation lengths and an increased proportion of
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juvenile wood (Downes et al., 2000). Juvenile wood is generally characterised by low density, thin cell walls, short tracheids with small lumens, high grain angle, and high microfibril angle, with the result that it has low strength and stiffness, and poor dimensional stability compared to mature wood (Macdonald and Hubert, 2002). The growing recognition that this juvenile wood is of low value, has resulted in a recent shift in the way plantations are managed. Rather than focusing solely on maximisation of merchantable volume, management strategies are now starting to use genetic stock and implement practices which balance growth rate with optimisation of wood properties in the cambium (Evans, 1997; Downes et al., 2000). In the widely grown plantation softwood Pinus radiata, a useful indicator of corewood quality is modulus of elasticity (E) which measures the resistance of wood to deformation under an applied load. Although E is not an important property for pulp, it is used as a threshold criterion in machine stress grading of structural timber (Walker and Nakada, 1999) and is also a key property for determining quality of laminated veneer lumber. Modulus of elasticity is often considered more important than strength (modulus of rupture) for predicting wood quality because P. radiata boards rarely break in normal use; much more frequently a load results in excessive deflection (Walford, 1985). When compared with other internationally traded structural lumber species, plantation-grown P. radiata has relatively poor E and dimensional stability. As stemwood E of P. radiata increases with cambial age up to five-fold over the first 30 years (Cave, 1968), the low values of E found within the corewood are most limiting for timber utilisation. Recent research shows that P. radiata corewood E can be manipulated by management. At single sites significant and substantial gains in E have been shown through increasing initial stand density (Lasserre et al., 2005), reducing the level of weed control (Watt et al., 2005a), and use of clones with improved wood properties (Lindstro¨m et al., 2004). Despite our increased understanding of how management influences E, there is little information to indicate how environment influences E. Understanding environmental influences on E is crucial as this will enable sites to be closely matched to the correct silvicultural regimes and clonal material to optimise product outturn and value. Although there is little empirical evidence, theory suggests that E may be regulated by stem slenderness. When light demanding species such as P. radiata are grown under competition, rapid height growth is important to ensure that they are not overtopped by neighbours. Under high levels of competition trees become etiolated as priority is given to height growth at the expense of diameter increment. Based on Euler’s buckling formula, the critical height (Hcrit) that a vertical tree stem can reach before it undergoes elastic buckling is given by the following equation: Hcrit ¼ C
1=3 E 2=3 Ad r
(1)
where r is the density of green wood, Ad the stem diameter and C is a constant of proportionality (Greenhill, 1881). For a given
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E actual height will approach the critical height as height for a given diameter, or stem slenderness, increases. Eq. (1) shows that trees can increase their critical height to avoid buckling as slenderness increases by increasing their density-specific stiffness (E/r), which is mainly accomplished through increases in E as green density is relatively constant (Lasserre et al., 2005). In addition to stem slenderness a number of edaphic and climatic factors may also influence E. Previous research shows that addition of fertiliser induces a small but significant reduction in E of P. radiata (Downes et al., 2002). Little research, however, has determined which if any soil chemical properties are responsible for alterations to E, through fertilisation. Given that wood with high E forms in latewood (Watt et al., 2005a) site variation in E may also be attributed to variation in climatic variables, which alter the proportion of latewood within the stem. Although research at single sites over sub-annual intervals has reported the importance of air temperature and water availability in regulating microfibril angle and E (Wimmer et al., 2002; Watt et al., 2005a) little research has investigated the influence of climatic conditions on E across broad environmental gradients. Linking the environment with wood properties at a broad scale requires high quality information on the climatic and edaphic conditions over a range of sites, at the time new wood is laid down. This type of data is available from a nationwide series of site quality plots established at sites encompassing the range of climatic and edaphic conditions found throughout plantations of P. radiata within New Zealand (Watt et al., 2005b). At each location trees were grown over a period of 4 years in plots with high stand density (spacing 0.5 0.5 m; 40,000 trees ha1), so that an endpoint (e.g. maximum leaf area) could be reached after a relatively short period of time. Through utilising data from the fertilised and unfertilised P. radiata subplots within this existing site quality network the aims of this study are to (i) determine the influence of site and fertilisation on E at the stem base and (ii) develop a predictive model of E for basal stemwood. 2. Methods 2.1. Location of site quality plots Sites were selected to represent the range in soil properties on which planted forests are currently established in New Zealand. Plots used within the trial series were established within the seven major soil orders on which 97.6% of the P. radiata resource occurs (Simcock, personal communication). The number of sites established on each soil order was weighted to be representative of the corresponding plantation area on which the soil order is found (Fig. 1). Sites were further screened using climatic surfaces (Leathwick and Stephens, 1998) to ensure that selected areas represented the considerable range in meteorological conditions found throughout New Zealand’s planted forests. When compared to long-term average values for all plantation forests (Anon, 1983), meteorological data recorded at each location indicate the 21 selected sites almost completely encompass the
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from the Scion nursery in Rotorua. The site quality plots were installed over 2-year period from 2000 to 2001. In fertilised plots broadcast application of fertiliser was undertaken three times a year during the first year (winter, spring, summer) and thereafter during spring at annual intervals. Over the 4 years of the study the elemental quantity of nitrogen, phosphorus, potassium, sulphur, magnesium and calcium applied to each fertilised plot was 690, 200, 558, 160, 40 and 160 kg ha1, respectively. At sites identified by soil analysis (at time of planting) as being deficient in boron, magnesium and copper, additional applications of these nutrients to fertilised plots were made during summer in sufficient quantities to ensure these nutrients were non-limiting. Disturbed plots were located on areas compacted by previous harvesting operations. 2.3. Measurements
Fig. 1. Distribution map of soil orders in New Zealand, showing location of site quality plots used in this study.
range in total annual rainfall (NZ plantations 609–3718 mm versus our sites 457–3074 mm) and mean annual temperature (NZ plantations 8.0–15.6 8C versus our sites 8.6–15.3 8C). 2.2. Experimental design Site quality plots were located at each of the 21 selected locations. At each location a series of eight plots was installed using a factorial design with the following three factors: species (P. radiata and Cupressus lusitanica Mill.), fertiliser (no fertiliser and nutrients supplied in excess of crop requirements) and disturbance (low and high disturbance). In this paper measurements and modelling were restricted to only the P. radiata subplots. Samples were taken from fertilised and unfertilised subplots in the undisturbed treatments at all but three sites. At these three sites samples were taken from the disturbed plots as excessive mortality precluded use of the undisturbed plots. Each plot was small in size (3 m 3 m) and contained nine measurement trees spaced at 0.5 m 0.5 m (40,000 trees ha1) surrounded by a two-row buffer. Regular applications of herbicide were made to ensure weed-free conditions. All sites were planted with 1-year-old P. radiata seedlings with a growth and form factor of 19 (Vincent and Dunstan, 1989), sourced
Soil physical properties were measured on samples of mineral soil taken from the edges of disturbed and undisturbed plots immediately prior to planting. Air capacity (at 10 kPa), macroporosity (at 5 kPa), total porosity, bulk density, particle density, cone penetration resistance (at 10 kPa), stone content and total available water were determined by horizon down to impermeable layers, following the procedures described by Gradwell (1972). For consistency all soil physical properties reported in this paper are averaged from 0 to100 mm, except total available water content and stone content which has been determined over the root depth, as measured at harvest. A soil pit was excavated down to impermeable layers prior to plot establishment in an undisturbed area adjacent to each site quality plot to determine soil texture. From this pit, particle size was measured by dispersing the field-moist soil in water with an ultrasonic probe and separating the <2, 2–63 and >63 mm fractions by sedimentation. All textural properties reported have been averaged over a depth of 0–100 mm. Ground-line diameter and height of the nine measurement trees were measured annually. Leaf area index, Lt, was estimated every 4 months using a canopy analyser (LAI-2000, Li-Cor Inc., Lincoln, NE, USA). Measurements of photosynthetically active photon flux density, air temperature and relative humidity were taken from sensors installed on a 3 m tower located adjacent to the experimental plots. A tipping bucket rain gauge positioned on top of the tower was used to measure above-canopy rainfall. A comprehensive set of soil chemical measurements were taken from the site quality plots after harvest at age 4 years. Soil chemistry samples were taken from 0 to 100 mm depth at 16 points in all harvested sub-plots to give 16 cores per bag. Sampling points were located at least 0.5 m apart around the nine trees at the centre of the plots. These samples were bulked by treatment then analysed for soil moisture, pH in water, total carbon (C), total soil nitrogen (N), total soil phosphorus (P), soil organic P, Bray P, Olsen P, exchangeable bases, and CEC, following the methods described by Blakemore et al. (1987). Results are expressed on an oven dry basis (105 8C).
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At age 4 years trees were extracted from the ground, when ground-line diameter averaged 46 mm and height averaged 3.7 m (Table 2). Plot level estimates of root depth were determined by measuring the depth of the deepest root on five trees per plot. A 300 mm section of the stem centred around 10% of the total tree height was cut from each tree. This sample was placed in a plastic bag with water and transported back to the laboratory, where it was frozen until measurements were taken. In the laboratory, stem samples were left in water for 48 h to ensure that they were defrosted. Green density (r) was determined as green weight/green volume. Green volume was determined using the immersion technique. Green dynamic modulus of elasticity (Pa) was determined from measurements of green density r (kg m3) and sound velocity V (m s1), using the following equation: E ¼ rV 2
(2)
Sound velocity was measured by the resonance-based tool, Woodspec (Industrial Research, Lower Hutt, New Zealand). This tool uses the impact from a pendulum to generate a stress wave within the wood sample. The acoustic velocity is then determined from the frequency of the reverberation of this stress wave within the sample. The stress wave must travel twice the length of the sample during one oscillation cycle. Therefore, the velocity of the wave is given by V ¼ 2l f
(3)
where f is the fundamental resonance frequency (Hz) and l is the sample length (m). By substituting (3) into (2) E is given by the following equation: E ¼ 4rl2 f 2
(4)
In a recent study using material from 4-year-old P. radiata clones, Lindstro¨m et al. (2002) found that correspondence between E measured using the resonance technique and traditional static bending was very strong (r2 = 0.98) and relatively unbiased (y = 1.04x). 2.4. Determination of root zone water balance A daily water balance equation was used to calculate root zone water storage (W) on the ith day as: Wi ¼ Wi1 þ Pi Eti Etwi Egi Fi
(5)
where Pi is rainfall, Eti the transpiration from the dry tree canopy, Etwi the evaporation of intercepted rainfall from the tree canopy, Egi the evaporation from the soil, and F i is the drainage from the root zone (Whitehead et al., 2001). Transpiration from the tree canopy was calculated using the simple diffusion equation: Et ¼ ’Dgst Lt
(6)
where D is the air saturation deficit, gst the average stomatal conductance for the canopy and Lt is the projected leaf area index, and w will be defined later. The inverse relationship between stomatal conductance and air saturation deficit was
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modelled using the function described by Lohammer et al. (1980) as: 1 ðD Dsmin Þ (7) gst ¼ gstmax 1 þ D0 where gstmax describes maximum stomatal conductance at low air saturation deficit, and D0 is the sensitivity of gst to D, when D > Dsmin. Eg was calculated from the available energy beneath the tree canopy, Gg, as: Eg ¼
’tsGg lðs þ gÞ
(8)
where the coefficient t (1.4) describes the degree of coupling of the soil surface with the air above the canopy (Kelliher et al., 1990), s the slope of the relationship between saturated vapour pressure and temperature at a given air temperature, l the latent heat of vaporisation, g the psychometric constant, and w will be defined later. Values for s, g, and l are temperature-dependant and calculated from standard meteorological tables. Using Beers Law, Gg was calculated from (ekLt Ga ) where Ga is the available flux density above the canopy (assumed to be 70% of short-wave radiation) and k is the light extinction coefficient (assumed to be 0.5 for a spherical leaf angle distribution). The coefficient w was used to reduce evaporation from the soil and transpiration as soil water storage declined. Root zone volumetric water content on the ith day, ui (Wi/[d(1 c)]), was calculated from water storage in the profile (Wi), root zone depth (d), and fractional stone content of the soil (c). The value of the coefficient w was set to 1 at maximum values of u (umax), and was not reduced until u declined to a threshold value (ut). As u progressively declined below this threshold w was linearly reduced from 1 to 0 at minimum values of u (umin). The threshold values (ut) for reducing evaporation from the soil and transpiration, taken from Watt et al. (2003), were assumed to be respectively, 60 and 55% of the fractional available volumetric water content, ua, determined as: ui umin ua ¼ (9) umax umin Estimated evaporation from the soil and transpiration were reduced to 50% of their potential rates on days when rain fell. Drainage from the root zone was assumed to be zero when ui umax and equal to rainfall reaching the soil when ui > umax. Daily meteorological data required for the water balance model include total rainfall and solar radiation, mean air temperature, and average air saturation deficit. Parameter values for gstmax, D0, and Dsmin were assumed to be 0.15 mol2 s1, 0.94 kPa, and 0.5 kPa, respectively. As previously described, values of root depth (d), stone content (c), umax and umin were measured at each site. Lt was modelled at a daily level by interpolating between seasonal measurements using a spline function. Following Landsberg and Waring (1997), wet canopy evaporation as a percentage of daily rainfall, P, was assumed to increase linearly from 0 at Lt of 0 to
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Table 1 Site level variation in climatic variables, and soil physical properties Variable
Mean and range
Climatic variables Mean annual temp. (8C) Min. March temp. (8C) Solar radiation (MJ PAR m2) Rainfall (mm)
11.6 (8.6–15.3) 10.1 (6.8–14.6) 5.6 (4.1–6.8) 1493 (457–3074)
Soil physical properties Coarse sand (%) Medium sand (%) Fine sand (%) Sand (%) Silt (%) Clay (%) Bulk density (g cm3) Particle density (g cm3) Penetration resistance (MPa) Total porosity (%, v/v) Macroporosity (%) Air capacity (%)
7 (0–57) 10 (1–33) 22 (2–69) 39 (5–93) 40 (4–71) 21 (3–49) 0.96 (0.47–1.35) 2.5 (2.2–3.0) 0.85 (0.37–1.75) 63 (49–79) 21 (7–49) 23 (8–45)
Values shown are the mean followed by the range in brackets for the 21 sites.
(0.15P) at Lt of 3, after which there were no further increases. All analyses use average fractional available volumetric water content, ua. During the fourth year after planting monthly gravimetric measurements of ua were made to a depth of 30 cm at three sites subject to seasonal water deficits. Modelled values of ua
exhibited good correspondence with the seasonal measurements at each site. Average absolute differences between measured and modelled ua at the three sites were 1, 8, and 3%, respectively. 2.5. Data analysis All analyses were undertaken in SAS (SAS Institute, 1996). Variables were tested for normality and homogeneity of variance and transformations made as necessary to meet the underlying statistical assumptions of the models used. Values for all structural variables used in the analysis were taken at harvest (age four). Stem slenderness, at age four, is defined here as height/ground-line diameter. A two-way analysis of variance (ANOVA) was used to test for the main effects of fertilisation and site on E, stand structural characteristics, ua, and soil chemical properties within the top 100 mm of the mineral horizon. Univariate relationships between E and all independent variables were examined (see Tables 1 and 2 for list of these variables), using appropriate functional forms to determine which variables were significantly related to E. A multiple regression model for E was constructed using those variables found to be significantly related to this property in the univariate analysis. Using appropriate functional forms and any necessary transformations, variables were sequentially introduced into the model. Variables were only retained if inclusion significantly improved the model and parameter values for the
Table 2 Stand structural characteristics, average fractional available volumetric water content (ua), and soil chemical properties in the top 100 mm of the mineral soil for unfertilised and fertilised plots sampled at 21 sites Unfertilised plots Mean Structural variables, and ua Ground-line diameter (mm) Height (m) Stem slenderness (m m1) Root depth (m) Average ua Chemical properties Carbon (%) Total N (%) CN ratio pH CEC (cmol g1) Exch. Na (cmol g1) Exch. K (cmol g1) Exch. Mg (cmol g1) Exch. Ca (cmol g1) Sum bases (cmol g1) Base saturation (%) Olsen P (mg g1) Bray P (mg g1) Inorganic P (mg g1) Organic P (mg g1)
Fertilised plots Range
Mean
Analysis of variance Range
Site
Fert.
46 3.7 82 0.5 0.69
17–60 0.9–5.7 52–109 0.2–0.8 0.36–0.89
51 4.0 82 0.5 0.68
36–60 2.5–5.4 54–108 0.2–1.0 0.37–0.90
0.72** 0.92*** 0.93*** 0.92*** 0.99***
0.09** 0.02* ns ns ns
6.2 0.30 20 5.1 20 0.27 0.39 1.6 5.0 7.3 35 10 26 136 327
1.7–26.7 0.11–0.85 11–31 4.1–6.0 10–43 0–0.74 0.09–0.99 0.4–3.9 0.1–21.4 0.8–23.3 8–94 2–33 2–184 12–415 74–601
6.4 0.31 20 4.8 20 0.29 0.64 1.7 3.9 6.5 33 28 74 253 328
2.2–24.5 0.13–0.80 14–30 3.9–5.7 9–46 0–0.68 0.13–1.22 0.5–4.1 0.5–12.5 1.4–16.2 8–71 8–65 11–195 32–547 80–657
0.98*** 0.95*** 0.94*** 0.87*** 0.97*** 0.90*** 0.75*** 0.94*** 0.90*** 0.97*** 0.95*** 0.51* 0.67*** 0.72*** 0.93***
ns ns ns 0.07*** ns ns 0.17*** ns 0.02* ns ns 0.32*** 0.19*** 0.19*** ns
The influence of fertilisation (Fert.) and site on each soil property is shown by partial r2 values followed by significance levels. ns: Non-significant at P = 0.05. * Represents significance at P = 0.05. ** Represents significance at P = 0.01. *** Represents significance at P = 0.001.
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included variables were significant. In constructing the model emphasis was placed on developing a simple equation with very little apparent bias. To determine the influence of structural variables on E, independently of climatic variation between sites, a mixed effects model was constructed in SAS. In this model structural variables were treated as fixed effects while site was treated as a random effect. 3. Results 3.1. Variation in site level climatic and edaphic properties There was considerable variation in climate between sites (Table 1). Across sites, mean annual rainfall ranged from 457 mm at an inland east coast site in the South Island (site 19; Fig. 1) up to 3074 mm at a site west of the main divide in the South Island (site 16; Fig. 1). Annual average temperature exhibited a two-fold variation from 8.6 8C at a high elevation South Island site (site 19; Fig. 1) to 15.3 8C at a coastal site (site 3; Fig. 1) in the northern North Island. The selected sites included extremes in soil texture ranging from single-grained scoria and sandy soils to clay loam soils. Variation in soil texture was considerable for all texture classes and exhibited the greatest range for the sand (5–93%), and silt (4–71%) fractions (Table 1). Soil physical properties also exhibited considerable variation between sites. This variation was most pronounced for the closely related variables macroporosity and air capacity which ranged from 7 to 49% and 8 to 45%, respectively, across sites. 3.2. Impact of site and fertilisation on E, structural and edaphic variables Modulus of elasticity exhibited a significant (P < 0.001) three-fold variation across sites (2.3–6.3 GPa). Although fertilisation generally reduced E within sites by an average of 6% (Fig. 2) these differences were not significant. All stand structural characteristics significantly varied between sites (Table 2). The treatment averaged range in
Fig. 2. Site variation in E for fertilised (open circles) and unfertilised (closed circles) plots. Values are sorted in descending order, after averaging at the site level. Each value shown is the mean with associated standard error.
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height and diameter at age four was considerable across sites, varying two-fold for diameter (26–56 mm) and three-fold (1.74–5.52 m) for height. Site level variation was also considerable for stem slenderness (height/ground-line diameter) ranging two-fold from 53 to 109 m m1. Across sites, average fractional available volumetric water content significantly ranged from 0.37 on a dryland site (site 19; Fig. 1) with low annual rainfall (457 mm) to 0.89 on a wet site (site 16; Fig. 1) with annual average rainfall of 3074 mm. Fertilisation had a significant influence on tree ground-line diameter and height inducing gains of 11, and 8%, respectively, for these characteristics (Table 2). Fertilisation did not significantly influence average fractional available volumetric water content, stem slenderness, or root depth. All soil chemical properties exhibited significant variation between sites (Table 2). When averaged at the site level variation was most marked for exchangeable calcium, Bray P, inorganic P and the sum of bases, which exhibited respective ranges of 54-, 25-, 20-, and 18-fold across sites. Fertilisation significantly influenced six of the 15 properties sampled. Fertiliser induced gains were greatest for Olsen P (three-fold), Bray P (three-fold), inorganic P (two-fold) and exchangeable potassium (two-fold). Fertilisation also significantly reduced pH by 6%, relative to the control (4.8 versus 5.1). 3.3. Modelling site effects on E In total, 13 variables were significantly related to E (Table 3). Most of the strongest relationships were with either structural or climatic variables. Stem slenderness, mean annual air temperature, tree height, and root depth had highly significant (P < 0.0001) positive relationships with E. The peaked relationship between E and average fractional available volumetric water content was also highly significant (P < 0.0001). The only soil chemical property significantly related to E was organic phosphorus. This variable exhibited a peaked relationship with E with maximum values of E occurring at organic phosphorus concentrations of 307 mg g1. Table 3 Variables found to be significantly related to E. For each variable the coefficient of determination (r2) and the significance level is shown Variable
r2/P-value
Stem slenderness Mean annual air temp. Tree height Average ua Organic phosphorus Tree root depth Wood density Average particle size Percentage silt Particle density Percent fine sand Root collar diameter Percent sand
0.61*** 0.53*** 0.50*** 0.33*** 0.30** 0.29*** 0.22** 0.22** 0.21** 0.20* 0.18** 0.13* 0.12*
* ** ***
Represents significance at P = 0.05. Represents significance at P = 0.01. Represents significance at P = 0.001.
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(Fig. 3a). Fertilisation did not significantly influence this relationship. The strong (r2 = 0.61) positive linear relationship between stem slenderness and E (Fig. 3b) did not significantly differ between fertilisation treatments. The relationship between E and average fractional available volumetric water content (ua) was peaked with maximum values of E occurring at ua values of 0.66 (Fig. 3c). The final model for E included mean minimum air temperature during March (Tmin) and stem slenderness (S) in the following linear equation: E ¼ 1:45 þ 0:238Tmin þ 0:041S
(10)
The overall model and parameter values for both variables were highly significant (P < 0.001), suggesting that the significant but weak (r2 = 0.30) correlation between Tmin and S was not likely to adversely influence the model. Analysis of covariance indicated that the model was not significantly influenced by fertilisation treatment. The total amount of variance in E explained by the model was 75%. Residuals exhibited very little apparent bias when plotted against either predicted values, or independent variables. A mixed effects model which included site as a random effect and stem slenderness as a fixed effect indicated that after site effects were removed, slenderness had a significant positive influence on E of trees within the site (P < 0.001). Similar analyses with other structural variables indicated that tree height within sites was significantly, although somewhat more weakly, related to E (P < 0.01). Within sites, tree diameter was not significantly related to E. 4. Discussion
Fig. 3. Relationship between E and (a) mean minimum temperature in March, (b) stem slenderness, and (c) fractional available volumetric water content.
When examined at the annual level E exhibited a stronger relationship with average minimum temperature (r2 = 0.57), than either average mean (r2 = 0.53) or average maximum (r2 = 0.43) annual temperature. At the monthly level the strongest relationship between average minimum temperature and E occurred in March during early autumn (r2 = 0.60). This relationship was positive up to 11.5 8C, after which E was relatively insensitive to further increases in temperature
This study shows considerable between site variation in P. radiata E measured in the first four rings. Further research should be undertaken to compare these values with measurements of E obtained from juvenile wood in older plantations where trees are growing at operational stand densities. If further research confirms these findings this could have considerable implications for forest managers given that low corewood values for E commonly limit structural timber utilisation in fast growing conifers (Kretschmann and Bendtsen, 1992; Cave and Walker, 1994; Walker and Butterfield, 1996; Tsehaye et al., 2000). The accurate determination of juvenile wood E across environmental gradients will enable sites to be closely matched to management regimes and clonal material to optimise product outturn and value. The significant influence of temperature on E may be mediated through regulation of latewood development. Analyses show that E was most strongly correlated with minimum temperature in early autumn. Given that latewood with high E is forming during this period (Watt et al., 2005a), it follows that sites with warmer temperatures and increased growth rates over this month will develop a greater percentage of high E latewood, and as a consequence higher overall stem E. The strong relationship found between E and stem slenderness has a sound theoretical basis. Using a variant of the Euler buckling formula, Greenhill (1881) showed that E
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scaled positively with the maximum slenderness that can be attained before buckling occurs. This relation has subsequently been used to determine the maximum slenderness which trees composed of a single tissue type, with known E, can attain (Niklas, 1994). The positive relationship found between E and slenderness in this study is consistent with this relationship and suggests that trees with high slenderness are increasing E to further increase the threshold at which buckling occurs. As heights of the trees in our study were relatively close to the critical buckling height, it is likely that wood properties were influenced by the need to avoid Euler buckling. Assuming the value of density-specific stiffness measured at the base of a tree is representative of the whole stem, our measurements show that the average safety margin (Hcrit/actual height) of the trees in this study was 2.1. These values are consistent with those reported for nine years old sweet gum growing under competition (Holbrook and Putz, 1989). However, they are considerably lower than the five-fold safety margins found by Niklas (1994), using data collected from the tallest specimen trees for 46 open-grown North American species. Stem slenderness was found to be significantly correlated to a number of variables of which the most important were positive relationships with mean annual air temperature (r2 = 0.30) and root depth (r2 = 0.35). As average fractional available volumetric water content (ua) also had a significant effect on slenderness (r2 = 0.2) it is likely that stem slenderness is to some extent regulated by this variable with peak values occurring at ua of 0.68 (data not shown). However, the greater significance of root depth over other related edaphic properties indicates that as well as being an indicator of soil water and sand content, root depth has additional significance as a determinant of stem slenderness, and therefore E. Results provide considerable insight into how environment regulates E. Sites with warm temperatures, and deep, sandy, well-drained soils with optimum ua, are likely to produce trees with high stem slenderness and high E. Conversely, cool sites with shallow soils and low sand content and high departures from optimum ua are likely to produce trees with low stem slenderness and low E. Examination of the data confirms this. The highest overall E (site 3; Fig. 1) occurred on the warmest site (Tmin = 14.6 8C), which had the highest root depth (0.89 m), close to optimum ua (0.69), and the sandiest soils (93%) out of the 21 sites. On a neighbouring site (site 2; Fig. 1) with the second highest Tmin (13.7 8C), close to optimum ua (0.68), but with very contrasting root depth (0.28 m) and sand content (9%) E was 2 MPa lower (6.33 versus 4.33 GPa), placing the site 12th highest out of the 21 sites, in terms of E. The lowest overall E (site 19; Fig. 1) occurred on the coldest site (Tmin = 6.83 8C) which had below average sand content, average root depth and the lowest ua (0.37) out of the 21 sites. The significant relationship found between stem slenderness and E within sites strengthens findings between sites. This result suggests that within site variation in E may be mediated through stem slenderness, and provides further evidence that the less significant effects of diameter and height are mediated through stem slenderness. The within site analysis also shows
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that the between site effect of stem slenderness on E is real and not a byproduct of the between site temperature influence on E. Despite the significant influence of fertilisation on growth rate, this treatment had a minor and insignificant influence on E. This finding indicates that E is relatively insensitive to considerable increases (in the order of two- to three-fold) in soil concentrations of Bray P, Olsen P, inorganic P and exchangeable Potassium. This lack of a response in E to fertiliser is consistent with the univariate relationships. The site level range was extensive for all important chemical properties including soil nitrogen. Despite this considerable site range the only chemical property significantly related to E was organic phosphorus, which was insensitive to application of fertiliser. These results suggest that growth gains obtained through fertiliser application may outweigh corresponding losses in wood quality attributable to reduced E. Although results from this study highlight the key determinants of E across an environmental gradient, further research should be carried out to confirm that these factors are the same for mature stands, grown at conventional stand densities. If further research shows that the key determinants of E identified in our study hold in older stands, the approach used in this study could become a useful operational tool for rapidly determining how environment influences wood quality. In conclusion this paper demonstrates that E may be relatively simple to predict across environments, as the key variables identified from a comprehensive set were temperature and stem slenderness. Stem slenderness could be obtained from either regional growth models or inventory data, while geographic information systems could be used to determine temperature, as splines describing variation in this variable at a fine resolution are currently available within New Zealand (Leathwick and Stephens, 1998). Results also highlight the insignificance of soil chemical properties on E, and suggest that gains in growth attributable to fertilisation may outweigh corresponding losses in E. Acknowledgements We are indebted to the numerous forest companies and private owners for providing sites for the trial series, and Hugh Wilde, Trevor Webb, Amy Taylor, Wim Rijkse, Craig Ross and Malcolm Mcleod who assisted in selection, identification and classification of soils. The help of technicians at the Landcare Research environmental chemistry lab in analysing samples is gratefully acknowledged. This project was funded by the New Zealand Foundation for Research Science and Technology under contract Nos. C04X0304 and C04X0203. References Anonymous, 1983. Summaries of Climatological Observations to 1980. New Zealand Meteorological Service Misc. Pub. 177, Wellington, New Zealand. Blakemore, L.C., Searle, P.L., Daly, B.K., 1987. Methods for chemical analysis of soils. Department of Scientific and Industrial Research, New Zealand Soil Bureau Scientific Report No. 80. Cave, I.D., 1968. The anisotropic elasticity of the plant cell wall. Wood Sci. Technol. 2, 268–278.
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