Allometry and evaluation of in situ optical LAI ... - Tree Physiology

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728 JONCKHEERE, MUYS AND COPPIN Table 5. Allometric relationships for Scots pine branches, trees and stand at Hechtel-Eksel, Belgium, based on the destructive sampling of six sample trees. Abbreviations: DM = dry mass; and DBH = diameter at breast height. Variables Regression equation r 2 Branch x = Branch cross-sectional area (cm 2 ) y = Needle area (m 2 branch –1 ) y = 15.543x 0.9906 y = Needle DM (kg branch –1 ) y = 29.908x 0.6604 Tree x = DBH (cm) y = Needle area (m 2 tree –1 ) y = 0.2988x 2 – 7.5336x + 74.075 0.94 y = Crown projected area (m 2 tree –1 ) y = 0.0066x 2 + 0.2115x 0.88 y = Needle DM (kg tree –1 ) y = –0.001x 2 + 0.0527x – 0.4586 0.95 Stand x = Basal area (m 2 ) y = Needle area (m 2 ha –1 ) y = 5791.9x 2 + 1344.7x – 7.1147 0.94 y = Crown projected area (m 2 ha –1 ) y = – 492.83x 2 + 173.86x 0.84 y = Needle DM (kg ha –1 ) y = 23.036x 2 + 204.42x 0.91 y = Number of needles (thousand ha –1 ) y = 1.789x (x in cm 2 ) 0.95 needle dry mass and crown projected area as dependent variables (Figure 3). Stand-level canopy coverage estimate Regression equations between DBH and basal area and between DBH and crown projected area of the trees (Table 5) were used to estimate the ground projection area of the average tree from all DBH classes, and these values were then used to scale up the crown projection of the individual trees to the entire stand to obtain an estimate of canopy coverage at the stand level. Canopy cover calculated based on the DBH versus basal area and DBH versus crown projected area regressions yielded values of 0.37 and 0.44, respectively. Because these allometric estimates of canopy cover (including within-crown gaps) are lower than the visual estimate of canopy cover (55–60%), we calculated canopy cover from hemispherical photographs as described by Soudani et al. (2002). The photographs gave a mean canopy cover of 61% for the stand, which is in good agreement with the visual estimate of coverage. Consequently, we concluded our crown radius was underestimated by our allometric regression equations. The subsampling of the six trees may have been insufficient to account for the high variability in crown projection area in the stand. These regression equations were therefore not used to calculate stand-level LAI. Stand-level LAI estimates Based on the regression equations in Table 5, empirical values of projected needle area, obtained Table 6. Regression equations (Equation 13; Rayleigh equation) for the relationship between tree height (both for total height and bole length) and stem diameter at breast height (DBH) for Scots pine trees. Variables Regression equation x =DBH,y = bole length y = 12.27(1 – e –x /5.05 ) 7.66 x = DBH, y = total height y = 29.96(1 – e –x / 39.34 ) 0.69 TREE PHYSIOLOGY VOLUME 25, 2005 0.86 0.83 by measuring detached needles directly with an optical planimeter, were calculated as functions of DBH and basal area. Total projected needle area (PLA) for the stand was then calculated by applying the relationship between DBH and projected needle area: 2 y = 02988 . x − 75336 . x + 74. 075 (7) or by applying the equation linking basal area and projected needle area: 2 y = 5791.9x + 1344.7x – 71147 . (8) From Equations 7 and 8 we obtained stand-level PLA values of 2.77 and 2.74, respectively. To make a reliable comparison of the projected needle area with estimates of LAI from optical methods, hemi-surface leaf area (HSLA), defined as one half the total surface area (Chen Figure 2. Relationship between needle area and branch diameter for Scots pine in Pijnven Forest, Hechtel-Eksel, Belgium. The solid line represents the needle area per branch (cm 2 ) based on a simple regression with branch diameter as the independent variable ( y = 15.543x 0.9906 ; r 2 = 0.86; n = 23). Downloaded from http://treephys.oxfordjournals.org/ by guest on December 6, 2012
et al. 1997), was calculated from PLA based on assumptions about the cross-sectional needle geometry (Brand 1987, Bond-Lamberty et al. 2003). The cross section of a Scots pine needle was assumed to be hemicylindrical with the ratio of the major to minor axis being equal to one. The assumptions about the geometry of Scots pine needles were verified based on analysis of needles from a random sample of all age cohorts from the sample trees. Given the total measured needle projected area and the cross-sectional shape of randomly oriented Scots pine needles, the surface area can be calculated and divided by 2 to yield HSLA (Chen et al. 1997): ⎛ 1+ π / 2 ⎞ HSLA = ⎜ ⎟PLA ⎝ 2 ⎠ ALLOMETRY AND EVALUATION OF OPTICAL LAI DETERMINATION 729 Figure 3. Relationship between total needle area per tree and diameter at breast height (DBH) for Scots pine in Pijnven Forest, Hechtel- Eksel, Belgium. The solid line represents the up-scaled needle area per tree (m 2 ) based on a simple regression with DBH as the independent variable ( y = 0.2988x 2 – 7.5336x + 74.075; r 2 = 0.94; n =6). The HSLA equalled 3.57 and 3.53 for the LAI estimates based on DBH and basal area, respectively. Optical gap fraction and LAI measurements Gap fraction estimation Figure 4 shows the variation in mean gap fraction as a function of zenith angles, estimated with the LAI-2000 or from hemispherical photographs. The LAI-2000 data showed an increase in gap fraction from the zenith to the Figure 4. Mean gap fraction values obtained for the Scots pine stand at various zenith angles with an LAI-2000 plant canopy analyzer ( � ) and with hemispherical photographs (with 36 azimuth sectors) (�). Symbols represent the mean and error bars represent the standard deviations of the respective measurements. (9) TREE PHYSIOLOGY ONLINE at http://heronpublishing.com viewing angles in the third ring, with a peak around the 40° viewing angle, after which the gap fraction decreased toward the horizon. Nilson and Kuusk (2004) recently reported that the gap fraction in the uppermost rings is frequently underestimated because the sampling points are situated under tree crowns. The low gap fraction at near-zenith angles and the increase between ring 1 and ring 3 is likely caused by the instability of the instrument in the first two rings as well as by a positioning effect of the LAI-2000 causing a slightly different view of the canopy. The decrease in gap fraction with distance from the sampling point was attributed to increasingly dense foliage (and stems) toward the horizon. The LAI-2000 data also showed a regular decrease in data dispersion with increasing zenith angle. This agrees with expectations, because gap fraction values are highly variable especially in the uppermost ring(s) because of inadequate spatial sampling (Nilson and Kuusk 2004). These trends were less clear in the hemispherical photographs, perhaps reflecting the higher intra-variability among photographs, because the sky sectors used for gap fraction calculations were small. Nevertheless, discrepancies between the data sets from the LAI-2000 and hemispherical photographs were low, never exceeding 5%. Leaf area index estimation Mean stand-level LAI (LAI stand) values from both tree allometry and the various indirect optical methods are shown in Table 7. To investigate the influence of clumping at the shoot, branch and tree levels and the influence of non-leafy material on LAI measurements, three methods were used to correct the LAI e estimates based on measurements with the optical devices. As expected, the LAI estimates based on indirect optical measurements were lower than the direct LAI estimates. Agreement between LAI values estimated by direct and indirect methods increased substantially when only the four central sky sectors were considered, indicating that the fifth sky sector, which is centered on a zenith angle of around 68° and includes that portion of the stands that is far from the measuring point (Li-Cor 1992), increases the likelihood that measurements will be influenced by light at low zenith angles. Figure 5 shows the pairwise comparison of the mean LAI values for all tested methods after correction for clumping and non-leafy material. Solid bars in Figure 5 represent the mean LAI based on the whole field-of-view of the optical instruments, whereas open bars represent the mean LAI based on four rings ( 0–60°). Error bars indicate the 99% confidence intervals (CI), which were generated by a pair-wise Bonferroni test with α = 0.01. An increase in estimated LAI was observed when data from the outer ring were omitted from both the LAI-2000 measurements and hemispherical photographs. The indirect estimates agreed fairly well with the allometric estimates after correction, highlighting the importance of correcting LAI before making comparisons. Discussion We found that LAIe derived from optical measurements underestimated LAI calculated from direct measurements (Table 7), as reported in many previous studies (e.g., Fassnacht et al. Downloaded from http://treephys.oxfordjournals.org/ by guest on December 6, 2012
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Allometry and evaluation of in situ optical LAI ... - Tree Physiology

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