CHAPTER 2: MATERIALS AND METHODS
2.2 Destructive harvesting and sample analysis
Log(V)= 1.95322 xlog(dbh)+12315 x log(h) -1.74069
Wheredbhis diameter at breast height andhis tree height.
[Equation 1]
[Equation 2]
Where 515 is site index at five years,agestand is the stand age in years, agesI is the site index age (5 years in this case) andh, is the top height (i.e. 80th percentile stand tree height).
field and after oven drying. This ratio was multiplied with the total mass taken infield to detemline the total dry mass of each separate tree component. All oven drying was done at 70 QC until no further mass loss was observed.
Further stem sub-samples were taken as 2 cm thick cross-sectional discs, cut at 2.4 metre distances along the tree from the base. Density was determined from these stem samples by a water displacement method (Tappi, 1985). This involved saturating the discs with water and then measuring the mass of water displaced by inserting them into a known volume of water.
Since the density of water can be taken as Ig cm-3the oven dry mass of each disc divided by the water displaced mass was taken as the wood density.
2.2.1 Measurement of sapwood area
Additional discs were taken from each tree at 1.3 above-ground level and used to detennine sapwood area. Heattwood was distinguished as having a distinctly darker colour than that of the sapwood. Sapwood area was estimated by scanning each disk on a flat bed scanner along with a plastic card of known size. The plastic card was used to calibrate the area measuring software in order to obtain accurate measurements. Analysis was performed on a computer using the free UTHSCSA ImageTool program (UTHSCSA, 2002). Whole disc area was digitally calculated by tracing the outside of the debarked stem and subtracting a traced area around the heartwood.
2.2.2 Optical plant area index measurement
The PAl was estimated using a LlCOR-LAI2000 plant canopy analyser (PCA). This instrument records the fraction of light below the canopy to the above canopy light at 5 zenith3 angles through a fish eye lens. The measurements are integrated over the five angles and a gap fraction calculation is used to estimate plant area index at points under a forest canopy (Ll-COR, 1992).
The gap fraction method is a widely used method of optical leaf area determination using the relationship between leaf area and the probability of light being intercepted as it passes through the canopy. In order to simplify the estimation of LAI by gap fraction, a number of assumptions are made (Chason et al., 1991; Ll-COR, 1992). The canopy is asswned to be horizontally homogenous with the foliage elements being small and black, and having a set angular distribution while being randomly distributed azimuthalll and in space. As some level of fohar
a The angle from the vettical to horizontal plane. (Directly up is 0")
b A top down view angle between the vertical plane and a rotational direction. (Facing North, East is 90")
clumping (gathering of leaves into clusters along the branches) and light scattering and transmission of light through the foliage occurs, the assumptions cmmot be fully adhered to.
The entire canopy area or PAl is measured with the PCA, as it does not distinguish between foliage, branch and stem elements in making light measurements. A calibration model may be developed to convert PAl to LAl using destructively detennined LAl, provided a good relationship exists between the two methods of LAl determination.
A total of 90 PAl samples (3 replications of 30 samples) were taken in each sample plot to capture as much variability as possible. A 45° lens cap was used to cover the sensor lens to obscure the operator from the instrument's field of view. Samples were taken in transects between the 3 m spaced tree rows within each plot. The fifth ring or zenith angle was removed in calculating the PAl with the LICOR-C2000 software to exclude any possible edge effects recorded by this low field of view light sensor.
2.2.3 Nutrient determination
Samples from this study were used determine nutrient concentrations in stands ofA. mearnsii across four age classes and three site qualities. The sample set of 48 trees comprised stem wood, bark, dead branches, live branches and foliage. Sub-samples of each tree were collected for each sample tree component, except the stem, and dried at 60°C until constant mass. Stem samples were taken as 2.0 cm thick discs at 1.2 m intervals from the base of the stem to 5.0 cm over bark diameter. Five macronutrients, N, P, K, Ca and Mg and four micronutrients, Mn, Fe, Cu and Zn, and Na were assessed on a dry mass nutrient concentration basis (Kalra and Maynard, 1991).
Plant material was analysed for total N by Kjeldahl digestion and titration. Phosphorus concentration was determined spectrophotometrically after dry ashing, using the molybdenum blue method and a segmented flow analyser. Flame emission spectroscopy was used for the analysis of K and Ca Mg Mn, Cu, Fe, Zn were analysed using atomic adsorption spectroscopy (Kalra and Maynard, 1991; Kalra, 1998). Since Bloemendal was sampled in early summer (late October) followed by Mistley in mid SUl1lliler, and then SeeleMtH later in summer (mid February), the effect of time within season may have influenced the nutrient concentrations, particularly in the foliage.
Tree component masses predicted using the allometric relationships and nutrient concentrations were used to estimate masses of nutrients in each tree component. Nutrients contained in the AGB of each tree component were used to estimate nutrient removals for various harvestina
b
intensities. General sample tree data are shown in Appendix A, Tables Al to A3 and concentrations are shown by site, age and component and element in Appendix B, Tables Bl to B3.