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Leaf-area density

These are the functions increasing with the height for the D-canopy and decreasing for the U-canopy. The last feature distinguishes both kinds of a canopy and also the uniform canopy consisting only of stems with the density distribution s(z) = const = 1.25 m2/m3 (column 6 in Table 3.2). Either or should be applied to characterizing such an architecture of the PR structure. They simulate the non-uniformity of the leaf area density in forest canopies (see Section 3.1.4). [Pg.154]

Life-form Summer Overstorey Leaf Nitrogen Content (mg g- ) Overstorey Leaf Area Density (m-kg- ) Sources... [Pg.161]

The results of the DFR assessment of different crop zones indicate that low-volume applications result in a more homogeneous distribution over the crop compared to high-volume applications. A recent study on the interception of high-volume applications in the cultivation of chrysanthemums revealed interception ratios from 0.2 to 1 related to the leaf area index (LAI) (Veerman et al., 1994). In our study, it was not easy to assess the LAI because of the structure of the carnation crop. Estimation of the LAI based on the results of estimation of the crop density (leaf volume index) was not reliable enough and resulted in a large variance of the calculated interception ratio (from 0.4 up to 5). [Pg.134]

On September 9 fresh colonies obtained from alder were reloaded onto the test trees at approximately the same density as In the original load (Figure 3). A census was obtained on September 15, and the remaining larvae were removed and counted on September 21. At this time leaves attacked (%) averaged A (test group), 61.4 3.1 B, 8.5 1.1 C, 9.4 1.7 D, 14.7 2.1. Estimated leaf area loss (%) averaged A, 30.6 t 2.7 B,... [Pg.64]

Figure 3. Relationship between leaf area (A), epidermal cell density (B), stomatal density (C) and stomatal index (D) versus altitude for Nothofagus solandri leaves growing on the slope of Mt. Ruapehu, New Zealand (collected in 1999). Black diamonds indicate the mean of ten counting fields on each leaf, white squares are the averages of five to eight leaves per elevation, with error bars of 1 S.E.M. Nested mixed-model ANOVA with a general linear model indicates significant differences for all factors (p = 0.000). Averages per elevation were used for regression analysis A. y = -0.0212 + 73.1 R2 = 0.276 p = 0.147. B. y = 1.70 + 3122 R2 = 0.505 p = 0.048. C. y = 0.164 + 360 R2 = 0.709 p = 0.009. D. linear (dashed) y = 0.004 + 9.33 R2 = 0.540 p = 0.038 non-linear (solid) y = 0.00001 2 - 0.0206 + 21.132 R2 = 0.770. Figure 3. Relationship between leaf area (A), epidermal cell density (B), stomatal density (C) and stomatal index (D) versus altitude for Nothofagus solandri leaves growing on the slope of Mt. Ruapehu, New Zealand (collected in 1999). Black diamonds indicate the mean of ten counting fields on each leaf, white squares are the averages of five to eight leaves per elevation, with error bars of 1 S.E.M. Nested mixed-model ANOVA with a general linear model indicates significant differences for all factors (p = 0.000). Averages per elevation were used for regression analysis A. y = -0.0212 + 73.1 R2 = 0.276 p = 0.147. B. y = 1.70 + 3122 R2 = 0.505 p = 0.048. C. y = 0.164 + 360 R2 = 0.709 p = 0.009. D. linear (dashed) y = 0.004 + 9.33 R2 = 0.540 p = 0.038 non-linear (solid) y = 0.00001 2 - 0.0206 + 21.132 R2 = 0.770.
Figure 9. Relationship between stomatal density and leaf area for Nothofagus solandri leaves (A), grown at an altitudinal transect on the slope of Mt. Ruapehu, New Zealand, and Quercus kelloggii leaves (B) from California. A. Linear regression y = -1.5148x + 611.22 R2 = 0.119 p = 0.023 B. Linear regression y = —1.3121x + 369.36 R2 = 0.090 p = 0.225. Figure 9. Relationship between stomatal density and leaf area for Nothofagus solandri leaves (A), grown at an altitudinal transect on the slope of Mt. Ruapehu, New Zealand, and Quercus kelloggii leaves (B) from California. A. Linear regression y = -1.5148x + 611.22 R2 = 0.119 p = 0.023 B. Linear regression y = —1.3121x + 369.36 R2 = 0.090 p = 0.225.
Stem number is partly determined by the size of the seed tuber (Barloy, 1988 Louis, 1985) and is closely related to the early canopy development and leaf area index (Baillarge, 1942 Cors and Falisse, 1980). Branching type is genetically controlled, although the number of branches is largely regulated by plant density. [Pg.159]

We will now consider the amount of energy that can be stored because of changes in leaf temperature. For purposes of calculation, we will assume that a leaf has the high specific heat of water (4.18 kJ kg-1 °C 1 at 20° C Appendix I), where specific heat is the energy required to raise the temperature of unit mass by one degree. We will further assume that the leaf is 300 pm thick (e.g., Fig. 1-2) and has an overall density of700 kg m-3 (0.7 g cm-3) — a leaf is often 30% air by volume. Hence, the mass per unit leaf area in this case is... [Pg.321]

We will represent the flux density of water vapor diffusing out of a leaf by the transpiration rate. If we multiply this amount of water leaving per unit time and per unit leaf area, Jw> by the energy necessary to evaporate a unit amount of water at the temperature of the leaf, //vap, we obtain the heat flux density accompanying transpiration, jJji... [Pg.346]

The rate of water vapor diffusion per unit leaf area, Jw> equals the difference in water vapor concentration multiplied by the conductance across which Acm occurs (// = g/Ac - Eq. 8.2). In the steady state (Chapter 3, Section 3.2B), when the flux density of water vapor and the conductance of each component are constant with time, this relation holds both for the overall pathway and for any individual segment of it. Because some water evaporates from the cell walls of mesophyll cells along the pathway within the leaf, is actually not spatially constant in the intercellular airspaces. For simplicity, however, we generally assume that Jm, is unchanging from the mesophyll cell walls out to the turbulent air outside a leaf. When water vapor moves out only across the lower epidermis of the leaf and when cuticular transpiration is negligible, we obtain the following relations in the... [Pg.385]

Reflectance peak sensitive to leaf area, vegetation density, biomass Species identification and assessment of vegetation vigour... [Pg.243]

Natural canopies such as vegetative covers are mostly vertically inhomogeneous that is accounted for in the mathematical model by means of the density being a function of the vertical coordinate z,n = n(z) t const. Practical examples of leaf area distributions can be found in [6, 155, 522] see also Figures 1.7 and 6.3. The same can be expressed by the specific measure of the frontal area s(z) = nS or by the dimensionless canopy density A = A(z) as explained in (3.128). As an example, a function family... [Pg.106]

The dimensionless drag coefficient cd (in meteorological practice the usual factor of 1/2 is omitted) is treated as isotropic and includes the influence of leaf and branch orientation, since the quantity a is the one-sided plant area density (m2/m3), not the cross-section exposed to the wind. Here, U is the scalar wind speed, while ui is the velocity vector in the -direction. [Pg.182]

For this particular choice of canopy density, Lc = 5 m the magnitude of the perturbations induced by the hill are of order the hill slope, H/L. In a canopy with hc = 20 m this corresponds to a Leaf Area Index (LAI) of 4. If LAI = 2 but the other parameters remain unchanged, the magnitude of the perturbation terms all double because the ratio of the momentum absorption distance Lc to the hill lengthscale L plays an important dynamic role in determining the velocity perturbations that drive the scalar fluctuations in the canopy. [Pg.215]

TABLE 6 The Ratio of Forest Evaporation (E) to the Equilibrium Rate (Eg ) and Overstorey (Tree) Leaf Nitrogen Content and Area Density (Leaf Area, Expressed on a One-Sided Basis, Produced ter kg of Carbon Assimilated)(Normalized Values in Parentheses) during Summer in Three Life Forms... [Pg.161]

Forests collect more pollutants than do surrounding surfaces with lower vegetation. For example, the forest edge will disturb the vertical wind profde and induce air turbulence that will in turn increase the dry deposition. The deposition at the front is considerably higher compared to that in the open field (by a factor of between 5 and 20), and also to that within the forest (a factor of 2 to 4). The increased deposition affects the vitality of the trees at the edge. Forest structures (tree species, crown density, stem density) differ widely in terms of aerodynamic roughness and leaf area, and these factors will each influence deposition. [Pg.60]

Figure 2. Changes in the rate of photosynthesis expressed on a leaf area basis (column A) and unit chlorophyll basis (column B) as a function of photon flux density for control ( Q ) smd mildewed ( ) leaves on days 1,5 and 9 after inoculation. Standard errors of the means of three determinations are given for each photon flux density. Figure 2. Changes in the rate of photosynthesis expressed on a leaf area basis (column A) and unit chlorophyll basis (column B) as a function of photon flux density for control ( Q ) smd mildewed ( ) leaves on days 1,5 and 9 after inoculation. Standard errors of the means of three determinations are given for each photon flux density.
In desert areas of southern California fruit are often injured but leaves are seldom injured by sulfur dust. In coastal areas fruit burn is less marked but leaf burn may be acute. Where the air-vapor density is high, leaf temperatures in the sun may sometimes become higher than fruit temperatures. The leaf, a better absorber of radiation and a better radiator than the fruit, has a higher surface-mass ratio and appears to be very sensitive to the heat trap effect of high vapor density its temperature changes with great rapidity, but fruit temperature may lag until the danger period is passed (18). [Pg.251]


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See also in sourсe #XX -- [ Pg.161 ]




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