Modelling the influence of stand structural, edaphic and climatic influences on juvenile Pinus radiata fibre length

Forest Ecology and Management 254 (2008) 166–177 www.elsevier.com/locate/foreco

Modelling the influence of stand structural, edaphic and climatic influences on juvenile Pinus radiata fibre length Michael S. Watt a,*, Ryan D’Ath b, Alan C. Leckie a, Peter W. Clinton a, Graham Coker a, Murray R. Davis a, Robyn Simcock c, Roger L. Parfitt d, John Dando d, Euan G. Mason e a

Ensis, P.O. Box 29237, Fendalton, Christchurch, New Zealand Ministry of Agriculture and Forestry, P.O. Box 25022, Christchurch, New Zealand c Landcare Research, Private Bag 92170, Auckland, New Zealand d Landcare Research, Private Bag 11052, Palmerston North, New Zealand e School of Forestry, University of Canterbury, Private Bag 4800, Christchuch, New Zealand b

Received 21 May 2007; received in revised form 27 July 2007; accepted 31 July 2007

Abstract The objectives of this study were to determine the influence of site, fertilisation and age on fibre length and develop predictive models of fibre length from a comprehensive set of climatic, edaphic and stand variables. Data were collected from a nationwide set of 22 site quality plots where Pinus radiata D. Don was established at high stand densities (40 000 stems ha1) and grown over a period of 4 years. The main environmental drivers of fibre length were identified by assessing the strength of bivariate correlations and use of multiple regression. Path analysis was used as an extension to multiple regression to separate cause from effect and quantify the direct influence of variables significantly related to fibre length. Fibre length exhibited significant variation between sites. When averaged across fertiliser treatments, site variation for fibre length in rings 1–4 ranged from 1.08 to 1.76 mm. Fertilisation did not significantly affect fibre length. Fibre length significantly increased with age from an average of 1.10 mm in rings 1–2 to 1.62 mm in rings 3–4. The interaction between age and fertilisation was insignificant. In total 16 variables were significantly related to fibre length. For rings 1–4, fibre length exhibited the strongest significant relationships with stem slenderness (r = 0.69), mean minimum air temperature (r = 0.67), green crown height (r = 0.66), tree height (r = 0.64) and average air temperature (r = 0.62). The best multiple regression models for both age classes and the whole stem included mean minimum air temperature and stem slenderness in a linear formulation. Path analysis indicated that the direct positive contribution of both these variables to fibre length was of a similar magnitude (path coefficients of 0.52 versus 0.49). Significant determinants of P. radiata fibre length in our study were similar to those identified in trees grown at conventional stockings across a similar environmental gradient in New Zealand. Although these studies did not examine how stem slenderness influences fibre length, they found average air temperature to be the strongest environmental determinant of fibre length, and that soil fertility, as indexed by Olsen phosphorus and total nitrogen and pH had little influence on fibre length. Further research is needed in conventionally stocked stands to confirm the link found here between stem slenderness and fibre length. # 2007 Elsevier B.V. All rights reserved. Keywords: Environment; Fibre length; Path analysis; Pinus radiata; Stem slenderness; Taper; Temperature; Tracheid length

1. Introduction 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

* Corresponding author. Tel.: +64 3 364 2949; fax: +64 3 364 2812. E-mail address: [email protected] (M.S. Watt). 0378-1127/$ – see front matter # 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2007.07.036

to shorter rotation lengths and an increased proportion of juvenile wood (Downes et al., 2000). Juvenile wood is generally characterised by low density, thin cell walls, short fibres 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

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maximisation of merchantable volume, management strategies are now starting to use genetic stock and implement silvicultural practices which balance growth rate with optimisation of wood properties in the cambium (Evans, 1997; Downes et al., 2000). In conifer species the short fibre length which is found within juvenile wood has a strong influence on the quality of paper and solid products. A minimum fibre length is required to make paper with an acceptable tear strength (Zobel and van Buijtenen, 1989), and strong correlations between fibre length and tear index have been reported for both softwoods and hardwoods (Watson and Dadswell, 1961; Wandgaard and Williams, 1970; DuPlooy, 1980; Labosky and Ifju, 1981; Malan et al., 1994). Longer fibre lengths have also been linked to stronger and more stable boards (Pearson and Gilmore, 1980), although the actual contribution of fibre length to board strength is not fully understood (Zobel and van Buijtenen, 1989). The identification of environmental factors which influence fibre length is important, as this type of information can be used to develop models which allow predictions of this property to be made across broad environmental gradients. This is particularly important for fibre length within the juvenile core, where values of tear strength are often lower than those required (Tutty, 1980). Development of site models of fibre length, which can be integrated with models describing how silviculture and tree breed influence this property over the stem length, would enable managers to match silviculture with site to optimise end-product value. Despite the importance of characterising how environment influences fibre length, little research to date has modelled site variation in conifer fibre length as a function of climatic, edaphic and stand structural factors. Although many studies report significant variation in fibre length between different geographical localities (Jackson and Strickland, 1962; Taylor, 1982), often as a function of latitude (Harris, 1967) and altitude (Ta-wei et al., 1972; Ladrach, 1986), few studies have used more process-based variables such as temperature, water availability, soil fertility and stand structure to model this site variation. Perhaps some of the most comprehensive research in this regard has been undertaken for Pinus radiata D. Don grown within New Zealand. In these previous studies the strongest environmental determinant was found to be mean annual temperature which exhibited a significant positive relationship with fibre length (Harris, 1965; Cown et al., 1991). While linkages between edaphic properties and wood properties have not been widely explored, considerable research has investigated the effect of an overall increase in soil nutrition, through application of fertiliser, on fibre length. Although fertilisation has been found to generally reduce fibre length in some fast growing conifers (Zobel, 1961; Nicholls, 1971; Ma¨kinen et al., 2002) the effects of this treatment on fibre length are not so clear for the fast growing and widely planted conifer, P. radiata, with some studies reporting a reduction (Bisset et al., 1951; Cown, 1977) and others no significant effect (Cown and McConchie, 1981). This variability may reflect diversity in the type and amount of fertiliser applied and variability in soil

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fertility of the control treatment. To ensure that results are generally applicable, determination of how fertiliser affects wood properties should ideally be undertaken across wide environmental gradients, which include a broad range of unfertilised control values for important soil properties such as nitrogen and phosphorus. This approach also provides a useful means for identifying the key soil chemical determinants of fibre length, as the fertility range across an environmental gradient, has been shown to be greater than the within site range induced by fertilisation (Watt et al., 2005), This greater range in chemical properties increases the likelihood of identifying significant relationships and allows examination of the relationship form across the entire operational range of soil fertility. Linking the environment with wood properties at a broad scale requires high quality information on the climatic and edaphic conditions at the time the wood was laid down. This type of information is available for the fast growing conifer, P. radiata, from a set of 22-site quality plots (Fig. 1) established across a wide environmental gradient within New Zealand. These plots form a representative subset of a national network of plots grown over a period of 4 years at high tree density. Through establishing these plots at high stem density this approach aims to effectively compress the experimental period over which the stand develops, by increasing inter-tree competition and the rate at which stand leaf area develops and the green crown recedes. In these plots, canopy closure is typically attained at most sites within 2 years of planting. This technique has significant advantages over conventional experimental methods as time frames over which measurements can be taken are shortened and relatively large numbers of plots can be installed permitting sampling of a wide range of environments. Through utilising data from the fertilised and unfertilised P. radiata plots within this site quality network, the aims of this study were to (i) determine the influence of site, fertilisation and age on fibre length and (ii) develop predictive models of fibre length from a comprehensive set of climatic, edaphic and stand structural variables. 2. Methods 2.1. Location of site quality plots Sites were selected to represent the range in soil properties on which plantation 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

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Fig. 1. Distribution map of soil orders in New Zealand, showing the location of site quality plots used in this study.

indicated the 22 selected sites almost completely encompass the range in total annual rainfall (NZ plantations 609–3718 mm versus our sites 458–3079 mm) and mean annual temperature (NZ plantations 8.0–15.6 8C versus our sites 8.6–16.9 8C). 2.2. Experimental design Site quality plots were located at each of the 22 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). The plots were located in close proximity to each other and were of similar slope and aspect. In this paper, measurements and modelling were restricted to the P. radiata subplots. Measurements were taken from fertilised and unfertilised subplots in the undisturbed treatments at 19 of the 22 sites. At the remaining three sites measurements were taken from the disturbed plots, located on areas compacted by previous harvesting operations, 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 ha1) surrounded by a two-row buffer. Regular applications of

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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 from the Scion nursery in Rotorua. The site quality plots were installed over a 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 (N), phosphorus (P), potassium (K), sulphur, magnesium and calcium (Ca) applied to each fertilised plot was 690, 200, 558, 160, 40 and 160 kg ha1, respectively. At sites identified by forest history or 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. 2.3. Climatic measurements Measurements of photosynthetically active radiation, 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. Vapour pressure deficit (VPD) was determined from relative humidity and temperature measurements using standard formulae. 2.4. Measurements of soil properties 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 to 100 mm, except root-zone water storage and stone content which has been determined over the root depth, as measured at harvest (i.e. 4 years after planting). A soil pit was excavated down to impermeable layers prior to plot establishment in an undisturbed area adjacent to the plots at each location 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 mm, 2–63 mm and >63 mm fractions by sedimentation. All textural properties reported have been averaged over a depth of 0–100 mm. 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 between trees from 0 to 100 mm depth at 16 points in all harvested plots and bulked to give 16 cores per plot. Sampling points were located approximately 0.5 m apart around the nine trees at the centre of the plots. These samples were analysed for soil moisture, pH in water, total carbon (C), total soil N, total soil P, soil organic P, Bray P,

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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). 2.5. Determination of root-zone water storage A daily water balance equation was used to calculate rootzone water storage (W) on the ith day as, W i ¼ W i1 þ Pi  Eti  Etwi  Egi  F i

(1)

where Pi is rainfall, Eti is transpiration from the dry tree canopy, Etwi evaporation of intercepted rainfall from the tree canopy, Egi evaporation from the soil, and F i drainage from the root-zone (Whitehead et al., 2001). Using the methods described in Watt et al. (2006a), Wi, was modelled over the 4-year period, and successfully validated at three sites in the final year (Watt et al., 2006a). In all analyses modelled values of average root-zone water storage have been expressed as a fractional available volumetric water content, ua = [(ui  umin)/(umax  umin)], where umin and umax are minimum and maximum volumetric water content. Daily volumetric water content, ui, was determined as; ui = Wi/ [d(1  c)], where d and c are root-zone depth, and fractional stone content of the soil, respectively. 2.6. Tree dimensions Ground-line diameter and height of the nine measurement trees were measured annually. Stem slenderness was determined from these measurements as tree height/ground-line diameter. Green crown height was determined at the same time as the distance from the ground to the base of the green crown. Leaf area index, Lt, was estimated every 4 months using a canopy analyser (LAI-2000, Li-Cor Inc., Lincoln, NE, USA). Four years after planting all trees were extracted from the ground, when ground-line diameter averaged 48 mm and height averaged 3.9 m. Plot level estimates of root depth were determined by measuring the depth of the deepest root on five trees per plot. 2.7. Measurements of wood properties In the field a 300 mm section of the stem centred around 10% of the total tree height was cut from each of the five destructively sampled trees. This sample was placed in a plastic bag with water and transported back to the laboratory for analysis of wood properties. In the laboratory samples were debarked and green dynamic modulus of elasticity, green density and basic density were measured on intact samples following the methods described in Watt et al. (2006a). On the oven dried samples a 30 mm section was cut radially from the centre of the 300 mm sample. From this section a wedge was cut which measured 2–3 mm on the outer circumference (outside of the tree) and declined to a point outside the pith, determined as the diameter at the time of planting, from field measurements. Each wedge was then split longitudinally in two

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at the latewood and earlywood boundary between rings 2 and 3, giving a 1–2-year old sample and a 3–4-year old sample. The samples were heated in a 10% NaOH solution in a water bath at 95 8C for 4 h. The samples were rinsed five times with tap water, then digested in peracetic acid (50% CH3COOH and 50% H2O2) in a water bath at 95 8C for another 4 h, before being rinsed with tap water a further five times. In each sample any fines (broken tracheids) that resulted from any previous cutting of the samples were removed. A manual disintegrator was used to break up the now delignified wood samples to produce a mass of individual fibres in water, ready for analysis. Fibre length was measured by a Metso FiberLab analyser. The analyser was calibrated weekly to ensure accurate results were obtained. To measure fibre length, 2 ml of the fibre/water solution was mixed with 400 ml of water. This sample was run through the FiberLab analyser, and fibre properties were recorded. All measurements reported in this paper are length weighted average fibre length, LL, determined as, LL ¼

Si ni L2i Si ni Li

Table 1 Site level variation in climatic variables and soil physical properties Variable

Mean and range

Climatic variables Mean annual air temp. (8C) Mean min. annual air temp (8C) Mean PAR (MJ PAR m2 d1) Mean annual rainfall (mm year1) Mean annual VPD (kPa)

13.7 (8.6–16.9) 7.6 (3.7–12.3) 5.5 (3.8–6.7) 1521 (458–3079) 0.55 (0.35–0.69)

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) Air capacity (%) Macroporosity (%)

7 (0–57) 10 (1–33) 22 (2–69) 39 (5–93) 40 (4–71) 21 (3–49) 0.94 (0.47–1.35) 2.5 (2.2–3.0) 0.85 (0.37–1.75) 63 (49–79) 23 (8–45) 21 (7–49)

(2)

where ni is the number of fibres of length Li. 2.8. Data analysis All analyses were undertaken in SAS (SAS Institute, 1996), using plot level data. Variables were tested for normality and homogeneity of variance and transformations made as necessary to meet the underlying statistical assumptions of the models used. Two-way analysis of variance was used to test for the effect of site and fertilisation on water balance characteristics and soil chemical properties. The effect of site, fertilisation and age on wood properties and stand structural variables was tested using a three-way analysis of variance. Measurements of fibre length were not available for the unfertilised treatment at site nine. To maintain balance in the analysis, this site was not used in the analysis of variance, but data from the fertilised treatment was included in the modelling of fibre length (see below). Bivariate correlations between wood properties and all independent variables were examined (see Tables 1–3 for list of these variables) using appropriate functional forms to determine which variables were significantly related to fibre length. Multiple regression models of fibre length for rings 1–4 and each of the two age classes (rings 1–2 and rings 3–4) were then constructed. Tree dimension data for each age class model, included the tree measurements at the end of the age class period (x) and the average value over the period (xa). Fibre length and tree dimensions for rings 1–4 were determined by weighting the values for each of the two age classes by basal area growth over each of the two periods to create a basal area weighted value (xw). This weighting was undertaken to ensure that values for fibre length and tree dimensions were representative of the entire stem cross section. Using appropriate functional forms and any necessary transformations, variables were introduced into the model,

using a forward stepping procedure. The significance limit for inclusion in the model was set at P = 0.05 and variables were only retained if inclusion significantly improved the overall model coefficient of determination (R2), by at least 5%. For the final model the degree of multicollinearity between variables was assessed using the variance inflation factor, with values of less than 10 indicating that multicollinearity is within acceptable bounds (Der and Everitt, 2001). Residuals for both models were tested for normality using the Shapiro–Wilk test and plotted against independent variables and predicted values to determine model bias. Although regression analysis provides useful information of the strength and form of relationships it does not separate indirect from direct effects or account for the complex interplay between cause and effect. Path analysis was used as an extension to regression analysis, to separate cause from effect. Using the variables identified by regression analysis as significantly affecting fibre length, path analysis was used to construct a diagram outlining the possible pathways by which each variable influences fibre length and determine the magnitude of the direct effect of each independent variable on fibre length. The path analysis method, which is briefly outlined in the Appendix A, is more fully described in Wright (1921,1934), Li (1975) and Rao and Morton (1980). 3. Results 3.1. Site level variation in climate, soil properties, tree dimensions and wood properties There was considerable variation in climate between sites (Table 1). Across sites, mean annual rainfall ranged from 458 mm at an inland east coast site in the South Island (site 20; Fig. 1) up to 3079 mm at a site west of the main divide in the South Island (site 17; Fig. 1). Annual average temperature ranged from 8.6 8C at a high elevation South Island site (site 21;

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Table 2 Water balance characteristics and soil chemical properties in the top 100 mm of the mineral soil for unfertilised and fertilised plots sampled at the 22 sites Unfertilised plots Mean Water balance characteristics Root depth (m) Average ua Soil 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) Total P (mg g1)

Fertilised plots Range

Mean

Analysis of variance Range

0.48 0.70

0.20–0.82 0.37–0.89

0.49 0.69

0.21–0.82 0.37–0.90

6.3 0.30 20 5.1 20 0.27 0.39 1.6 5.1 7.4 35 9 26 142 338 480

1.7–26.7 0.11–0.85 10–31 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 91–914

6.5 0.32 20 4.8 20 0.28 0.66 1.7 4.1 6.8 33 27 72 258 346 604

2.2–24.5 0.13–0.80 13–30 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 80–701 112–1067

Site

Fert.

9.5 (<0.0001) 163 (<0.0001) 48.9 21.9 17.4 15.6 33.3 3.7 8.1 14.7 11.3 17.8 13.7 2.9 4.9 8.4 14.2 15.4

(<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001) (0.01) (0.0004) (<0.0001) (<0.0001) (<0.0001)

0.1 (0.73) 1.4 (0.26) 0.4 1.3 0.2 22.5 0.0 0.3 39.5 0.9 4.6 2.0 1.1 35.0 27.6 42.1 0.2 20.0

(0.54) (0.26) (0.70) (0.0001) (0.91) (0.62) (<0.0001) (0.36) (0.05) (0.17) (0.3) (<0.0001) (<0.0001) (<0.0001) (0.68) (0.0002)

For the analysis of variance the influence of site and fertilisation (Fert.) on each variable is shown by an F-value followed by a P-value in brackets.

Fig. 1) to 16.9 8C at a coastal site (site 3; Fig. 1) in the northern North Island. Soil physical properties also exhibited considerable variation between sites. 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). Variation was also pronounced for the closely related variables macroporosity and air capacity which ranged from 7 to 49% and 8 to 45%, respectively, across sites. All soil chemical properties exhibited significant variation between sites (Table 2). When averaged across treatments, variation was most marked for exchangeable Ca, Bray P, inorganic P and the sum of bases, which exhibited respective ranges of 54-fold, 25-fold, 20-fold and 18-fold across sites.

Across sites the average fractional available volumetric water content (ua) significantly ranged from 0.37 on a dryland site (site 20; Fig. 1) with low annual rainfall (458 mm) to 0.89 on a wet site (site 17; Fig. 1) with annual average rainfall of 3079 mm (Table 2). All stand structural characteristics significantly varied between sites (Tables 3 and 4). The treatment averaged range in height and ground-line diameter at age four was considerable across sites, varying two-fold for ground-line diameter (27– 56 mm) and three-fold (1.8–5.3 m) for height. Site level variation was also considerable for stem slenderness (height/ ground-line diameter) ranging two-fold from 54 to 110 m m1. All wood properties exhibited significant variation between sites. When averaged across treatments, site variation in fibre length significantly ranged from 1.08 at site 20 to 1.76 mm at site three (Tables 3 and 4). Green dynamic modulus of elasticity

Table 3 Wood properties and stand structural variables for unfertilised and fertilised plots sampled at the 22 sites Unfertilised plots

Wood properties Fibre length, rings 1–4 (mm) Fibre length, rings 1–2 (mm) Fibre length, rings 3–4 (mm) Green dynamic modulus of elasticity (GPa) Basic density (kg m3) Stand structural variables Ground-line diameter, age 4 (mm) Height, age 4 (m) Stem slenderness, age 4 (m m1) Green crown ht., age 4 (m) Average leaf area index (m2 m2)

Fertilised plots

Mean

Range

Mean

Range

1.42 1.11 1.62 4.42 386

1.11–1.77 0.90–1.43 1.19–2.20 2.33–6.92 343–459

1.39 1.10 1.60 4.13 377

1.05–1.74 0.91–1.39 1.11–2.10 2.18–5.79 340–431

46 3.8 82 0.9 2.7

16–61 0.8–5.7 52–109 0–2.3 0.7–4.3

50 4.0 82 1.1 3.0

36–61 2.5–5.3 54–108 0–2.3 0.7–4.2

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Table 4 Source of variation, F-value and P-value (in brackets) for fibre length and tree dimensions

Site Age Fert. Age  fert.

Fibre length

Ground-line diameter

Height

Stem slenderness

Green crown height

Average leaf area index

12.1 (<0.0001) 2338 (<0.0001) 0.4 (0.52) 0.94 (0.34)

4.5 (0.0007) 1279 (<0.0001) 6.8 (0.02) 0.4 (0.52)

16.3 (<0.0001) 2455 (<0.0001) 5.0 (0.04) 0.6 (0.44)

12.5 (<0.0001) 485 (<0.0001) 1.0 (0.33) 0.32 (0.58)

31 (<0.0001) 1395 (<0.0001) 1.7 (0.20) 0.3 (0.61)

9.3 (<0.0001) 1021 (<0.0001) 11.2 (0.003) 6.9 (0.02)

significantly varied across sites (F-value = 7.8; P < 0.0001) by three-fold while basic density significantly (F-value = 6.9; P < 0.0001) ranged from 347 to 439 kg m3 (Table 3).

stand structural and climatic variables (Fig. 2). For both age classes average air temperature, stem slenderness, tree height, and mean minimum air temperature were most strongly related to fibre length (Fig. 2). The relationship between ground-line

3.2. Impact of fertilisation on soil properties, tree dimensions and wood properties Fertilisation significantly influenced six of the 16 soil chemical properties sampled (Table 2). Fertiliser induced percentage gains (fertilised values/control values) were greatest for Olsen P (300%), Bray P (277%), inorganic P (182%) and exchangeable K (169%). Fertilisation also significantly reduced soil pH from 5.1 to 4.8. Fertilisation did not significantly affect fractional available volumetric water content. Fertilisation had a greater influence on stem dimensions than wood properties (Tables 3 and 4). Tree ground-line diameter, height and leaf area index in fertilised plots significantly exceeded values for the control plots by 9, 5 and 11%. In contrast, fertilisation had no significant effect on fibre length (Tables 3 and 4), green dynamic modulus of elasticity (F-value = 2.7; P = 0.12) or basic density (F-value = 3.8; P = 0.06). 3.3. Influence of age on fibre length and tree dimensions Fibre length significantly increased with age from 1.10 mm in rings 1–2 to 1.62 mm in rings 3–4. All tree dimensions significantly increased with age (Table 4). Gains over time were most marked for green crown height and leaf area index which increased 17-fold and four-fold, respectively, over the two age periods. The interaction between age and fertilisation was only significant for leaf area index as changes in leaf area index over the two age periods were slightly greater in fertilised plots than unfertilised plots (Table 4). 3.4. Bivariate correlations between fibre length and climate, edaphic and structural variables In total 16 environmental and stand structural variables were significantly related to fibre length (Fig. 2). For rings 1–4, fibre length exhibited the strongest relationships with stem slenderness (r = 0.69; P < 0.0001), mean minimum air temperature (r = 0.67; P < 0.0001), green crown height (r = 0.66; P < 0.0001), tree height (r = 0.64; P < 0.0001) and average air temperature (r = 0.62; P < 0.0001). Fibre length was also strongly correlated to the wood property green dynamic modulus of elasticity (r = 0.83; P < 0.0001), but not significantly correlated to basic density (r = 0.23; P = 0.14). The strongest bivariate relationships exhibited considerable similarity between the two age categories and were mainly

Fig. 2. The strength of the correlation coefficient between predictive variables and fibre length for (a) rings 1–4; (b) rings 1–2; and (c) rings 3–4. On each figure the horizontal dotted line shows the correlation coefficient at which P = 0.05. All variables shown are significantly related to fibre length in at least one of the three age categories.

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diameter and fibre length was somewhat lower in strength, but consistent between the two age classes (Fig. 2). The strength of the relationships between fibre length and other structural variables exhibited some disparity between age classes (Fig. 2). The correlation coefficient between fibre length and leaf area index declined with age from 0.64 (P < 0.0001) for rings 1–2 to 0.35 (P = 0.023) for rings 3–4. Ring width exhibited a significant positive relationship with fibre length in rings 1–2 (r = 0.39; P = 0.009), but an insignificant negative relationship with fibre length in rings 3–4 (r = 0.27; P > 0.05). Distance to the green crown was not significantly related to fibre length in rings 1–2, but exhibited a highly significant relationship (r = 0.74, P < 0.0001) with fibre length in rings 3–4. Although still significant, fibre length was less strongly correlated with average fractional available volumetric water content (ua) and soil properties than climatic and stand structural variables (Fig. 2). As average ua exhibited a quadratic relationship with fibre length, the variable was transformed so that it exhibited a linear relationship with fibre length by calculating absolute differences in ua from the optimum value of 0.66. When transformed, average ua exhibited an insignificant correlation of 0.29 (P > 0.05) with fibre length in rings 1–2 but a highly significant correlation of 0.55 (P = 0.0001) in rings 3–4. In contrast, average annual rainfall was not

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significantly related to fibre length for either of the two age classes. Significant positive linear relationships were also observed between fibre length and fine sand percentage, particle density, bulk density, and medium sand percentage, while there were significant negative relationships between fibre length and silt percentage, soil porosity and organic P (Fig. 2). The strongest bivariate correlations did not account for significant differences in fibre length between the two age classes. Analysis of covariance showed that the relationship between mean minimum air temperature and fibre length (Fig. 3a) had significantly different slopes (F-value = 48.33, P < 0.0001) and intercepts (F-value = 13.60, P = 0.0005) between the two age classes. Differences between the two age classes were reduced using stem slenderness as a predictive variable (Fig. 3b), although there were still significant differences in slopes (F-value = 12.25, P = 0.0009) between the two age classes. 3.5. Multiple regression and path analysis The multiple regression models of fibre length for both age classes and years 1–4 included positive relationships with mean minimum air temperature and stem slenderness in a linear formulation (Table 5). For rings 1–2 mean minimum air temperature accounted for the greater part of the variance in fibre length while for rings 1–4 and rings 3–4 stem slenderness was of greater importance than mean minimum air temperature. The three models accounted for a large proportion of the variance in fibre length (R2 range 0.67–0.77). The significance level for both variables in each of the three models was very high (P < 0.0001), and all three models were highly significant (P < 0.0001). The low variance inflation factor for all variables indicated that multicollinearity between independent variables Table 5 Summary of model statistics and coefficient values for multiple regression models of fibre length for rings 1–4, rings 1–2 and rings 3–4

Fig. 3. Relationship between (a) fibre length and mean minimum air temperature for rings 1–2 (closed circles) and rings 3–4 (open circles) and (b) fibre length and stem slenderness in rings 1–2 (closed circles), and rings 3–4 (open circles). Linear lines of best fit have been drawn through data for rings 1–2 (solid line) and rings 3–4 (dotted line) in both figures.

Model term

Coefficient

R2 values and significance

VIF

Rings 1–4 Intercept Sw Tmin

0.598 0.008 0.036

0.47 (0.47)*** 0.20 (0.67)***

1.2 1.2

Rings 1–2 Intercept Tmin S

0.457 0.033 0.007

0.57 (0.57)*** 0.18 (0.75)***

1.2 1.2

Rings 3–4 Intercept Sa Tmin

0.486 0.011 0.049

0.60 (0.60)*** 0.17 (0.77)***

1.4 1.3

Shown are the partial R2, cumulative R2 in brackets, and P-category for stem slenderness and mean minimum air temperature (Tmin). The symbols shown for stem slenderness refer to; S, stem slenderness determined at the end of the 2 year period; Sa, average stem slenderness over the 2-year period; Sw, basal area weighted stem slenderness. Also shown is the variance inflation factor (VIF) for each model term. *** Asterisks denote significance at P = 0.001.

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Fig. 4. Proposed causal pathways linking environmental variables and stand structural variables with fibre length. Solid lines represent direct pathways of influence, while dotted lines represent indirect pathways. Exogenous variables are denoted as an ellipse while the endogenous variables are shown as squares.

was within acceptable limits. Residuals for all three models were normally distributed and exhibited little apparent bias when plotted against either predicted values or independent variables (data not shown). An initial path analysis model was constructed for fibre length in rings 1–4 from independent variables found to be significantly (P < 0.05) related to fibre length. Average ua was transformed as previously described and mean minimum air temperature was used rather than average air temperature as the former was more strongly related to fibre length. Within the hypothesised model, outlined in Fig. 4, predictive variables may influence fibre length directly (solid line), indirectly, whereby their effect is mediated through another variable (dotted line), or both directly and indirectly. Direct pathways have been drawn from ground-line diameter and height to stem slenderness. Given that tree height has a strong effect on green crown height (Beekhuis, 1965) a direct pathway has been added between these variables. In addition to these pathways the direct effect of all variables on fibre length was also tested. The initial path model was modified according to the significance of pathways and the overall fit of the model to the data as assessed through examination of a range of statistics (see Appendix A for details). A number of modifications were made to the initial model. As the direct relationship between green crown height and fibre length was not significant this variable was dropped from the model. Although the direct relationship between ground-line diameter and stem slenderness was significant, inclusion of ground-line diameter in the model resulted in overall model statistics which indicated a poor fit between the model and the data (Chi-square <0.0001, goodness of fit indices <0.84 and maximum normalised residuals >2.0). Given these poor fit statistics ground-line diameter was removed from the model. Removal of ground-line diameter from the model did not markedly alter any of the remaining relationships between variables. Of the environmental variables originally examined only mean minimum air temperature and percentage silt were found to significantly affect tree height, stem slenderness or fibre length. For the final modified model outlined in Fig. 5, an acceptable level of model fit to the data was demonstrated by all goodness of fit indices (all >0.92) and the Chi-square ratio (P = 0.44). None of the normalised residuals exceeded 1.2 in magnitude. In

Fig. 5. Final path analysis model. Significant (P < 0.05) pathways, shown as black lines, are accompanied by a path coefficient. Exogenous variables are denoted as ellipses while the endogenous variables are given as squares. The amount of variance (R2) explained for each endogenous variable is shown. For clarity insignificant pathways (including the covariance between the exogenous variables) are not shown on the diagram.

addition all remaining pathways in the model were significant (t-values >1.96). Path coefficients within the modified model (Fig. 5) indicated that both stem slenderness and mean minimum air temperature had positive direct effects of a similar magnitude on fibre length (path coefficients of 0.52 versus 0.49). Although tree height did not directly affect fibre length, this variable did indirectly influence fibre length via a direct influence on stem slenderness (path coefficient of 0.82). In turn, tree height was significantly directly affected by mean minimum air temperature (path coefficient = 0.26) and percentage silt (path coefficient = 0.47). The final model explained 65% of the variance in fibre length, 67% of the variance in stem slenderness and 33% of the variance in tree height. 4. Discussion This study showed significant variation in fibre length occurs across environmental gradients. Results from both the bivariate correlations and multiple regression clearly identify stem slenderness and mean minimum air temperature as key determinants of site variation in fibre length for all age classes. This finding is supported by the path analysis results which showed both variables to have a significant direct positive influence of a similar magnitude on fibre length. The significant positive influence of air temperature on fibre length found in this study is consistent with previous experimental work and field research. Experimentation by Richardson (1964) found air temperature to be positively related to fibre length for a range of conifers, including P. radiata. In P. radiata stands grown at conventional densities across a wide environmental gradient in New Zealand, both Harris (1965) and Cown et al. (1991) report a significant positive relationship between air temperature and fibre length. The strong relationship between stem slenderness and fibre length has a theoretical basis. High stem slenderness results from strong competition for light. Under these conditions height growth occurs at the expense of ground-line diameter growth to ensure trees are not outcompeted by neighbours. The resulting increase in height is likely to create a high water potential gradient which can be mitigated either through

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increasing the basal cross sectional area (i.e. ground-line diameter) or through increasing specific conductivity. Given the low rates of diameter growth which occur under high levels of competition, increases in specific conductivity may provide a more effective means of reducing the water potential gradient. Previous research has shown a strong positive correlation between fibre length and specific conductivity, which is thought to occur as increases in fibre length reduce the number of times water must pass through a bordered pit (Mencuccini et al., 1997). The relationship found between fibre length and stem slenderness may therefore be an adaptation to ensure adequate water flow in slender trees where path length is high relative to the stem basal cross sectional area. The strong correlation found between green dynamic modulus of elasticity (MOE) and fibre length suggests that under high levels of competition the goals of maintaining stability and hydraulic needs are not antagonistic. Previous modelling of MOE across the same site series (Watt et al., 2006a,b) has shown that the main determinants of MOE were mean minimum air temperature and stem slenderness, which both exhibited strong positive linear relationships with MOE. The relationship between MOE and stem slenderness is consistent with the Euler buckling formula which suggests, in a competitive situation, increases in stem slenderness will induce increases in MOE to reduce the risk of stem buckling though self weight. Although a mathematical relationship between fibre length and microfibril angle (a property strongly related to MOE) was originally proposed by Preston (1934), this has since been disputed, as secondary wall formation begins at the end of the cell extension phase (Barnett and Bonham, 2004). Given this independence it seems likely that as inter-tree competition and stem slenderness increase, the internal properties fibre length and MOE also synchronously increase, to improve water uptake and stability, respectively. Results clearly show that distance to the green crown was not an important determinant of fibre length. Fibre length was not significantly related to green crown height in rings 1–2. Although green crown height was significantly related to fibre length during ages 3–4 the lack of significance over rings 1–2 suggests this relationship was not causal, but an artefact of the collinearity between green crown height and both stem slenderness (r = 0.81) and tree height (r = 0.86) during this period. Results from the path analysis confirm this supposition, by showing the direct relationship between fibre length and distance to the green crown to be insignificant (P > 0.05). Compared to other structural variables ring width exhibited a relatively weak degree of correlation with fibre length, which was only significant in rings 3–4. Although ring width has been widely cited as a key determinant of fibre length, Richardson (1964) did point out the inconsistency of reported correlations between the two variables which have been negative, positive and non-existent. Results from our study reinforce this inconsistency as the correlation between ring width and fibre length was positive in rings 1–2 and negative in rings 3–4. Although fertilisation generally reduces fibre length in fast growing conifers (Zobel, 1961; Nicholls, 1971; Ma¨kinen et al., 2002) the effects of this treatment on fibre length are not clear

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for P. radiata stands grown at conventional densities, with some studies reporting a reduction (Bisset et al., 1951; Cown, 1977) and others no significant effect (Cown and McConchie, 1981). Results from our study clearly show no effect of fertilisation on fibre length despite the significant effects of this treatment on growth rate. This finding indicates that fibre length is relatively insensitive to considerable fertiliser induced increases in soil concentrations of Bray P, Olsen P, inorganic P, and exchangeable K. This lack of a response in fibre length to fertilisation is consistent with the modelling in which no soil related variables strongly affected by fertilisation were significantly related to fibre length. These results suggest that growth gains obtained through fertiliser application will outweigh any losses in wood quality attributable to reduced fibre length. The experimental design used in this study may provide a useful means of accelerating stand dynamics so that rotation length changes in wood properties over long periods at conventional densities can be compressed into shorter time frames. As this experimental method accelerates stand dynamics it is likely to influence some of the stimuli affecting cambial activity. However, it should be noted that this method will not accelerate cambial aging. Further research is therefore needed to determine the extent to which aging of the canopy influences wood properties, independent of changes in stand dynamics. Results from this study indicate that the effect of age on fibre length was reduced, but still significant, after accounting for changes in stem slenderness with age. Although comparisons are somewhat limited, the general consistency of our data with previous research suggests that young densely planted mini-plots can be used to rapidly identify key environmental and stand structural determinants of wood quality. Significant drivers of P. radiata fibre length in our study were similar to those identified in trees grown at conventional stockings across a similar environmental gradient in New Zealand (Harris, 1965; Cown et al., 1991). Although these studies did not examine how stem slenderness influences fibre length they found average air temperature to be the strongest environmental determinant of fibre length and that soil nutrition (Olsen P and N) and pH had little influence on fibre length (Cown et al., 1991). Further research is needed in conventionally stocked stands to confirm the link found here between stem slenderness and fibre length. If further research supports this finding, young densely planted mini-plots could become a useful operational tool for rapidly determining how environment influences wood properties, such as fibre length. In conclusion, this paper demonstrates significant variation in fibre length across a wide environmental gradient. This variation was largely attributable to variation in mean minimum air temperature and stem slenderness, which both exhibited significant direct effects on fibre length. Mean minimum air temperature also had a significant indirect effect on fibre length which was mediated through tree height and stem slenderness. These results suggest that fibre length may be relatively simple to predict across environmental gradients. Stem slenderness could be obtained from either regional growth models or inventory data. Geographic information systems could be used to determine mean minimum air temperature, as splines

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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 fibre length, and suggest that gains in growth attributable to fertilisation considerably outweigh corresponding losses in fibre length. 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. We thank two anonymous referees who provided a comprehensive and very useful review of the paper. We are also very grateful to Marcela Avalos for measuring fibre length on a large proportion of the samples and Geoff Downes who provided useful advice on analysing the data. The help of technicians at the Landcare Research environmental chemistry lab in analysing soil samples is gratefully acknowledged. This project was funded by the New Zealand Foundation for Research Science and Technology under contract No. C04X0304.’Protecting and Enhancing the Environment through Forestry’. Appendix A Path analysis is an extension of regression analysis used to test the fit of the correlation matrix against two or more causal models. A regression is done for each variable in the model as dependent on others which the model indicates are causes. The regression weights predicted by the model are compared with the observed correlation matrix for the variables, and a goodness-of-fit statistic is calculated. The best-fitting of two or more models is selected as the best model for advancement of theory. A comprehensive range of tests are used to determine significance of pathways and final model fit. The significance of pathways between variables in the causal model should be assessed to ensure that they are significant at the 5% level (absolute t-value >1.96). For the overall model values of the Chi-square ratio greater than 0.05 indicate an acceptable fit between model and data. However, as the Chi-square statistic has some limitations as an inferential test (see Kaplan, 1990, for review), the goodness of fit index, normed fit index and comparative fit index (CFI) are also used to determine the adequacy of the model fit to the data. All of these indices range from 0 to 1, with values over 0.9 indicating an acceptable fit between model and data. A model exhibiting acceptable fit between the model and the data also has normalised residuals which are less than 2.00. For the final model, the magnitude of the standardised coefficient, which ranges from 0 to 1, should be examined to evaluate the relative importance of relationships between variables. As the standardised coefficients indicate the fraction of a unit change in standard deviation of the response variable for a one-unit change in standard deviation of the driving variable, values closer to 1 indicate a greater degree of influence.

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