Leaves are the active interface of energy, carbon, and water vapour exchange be-tween forest canopies and the atmosphere. The leaf area index (LAI, in m2 m-2), de-fined by Watson (1947) as the total one-sided area of leaf tissue per unit ground sur-face area or by Chen and Black (1991, 1992) as half the total green leaf area per unit ground area, is therefore one of the most important physiological characteristics of canopy structure.
Direct, destructive methods such as harvesting trees and the planimetry of their re-spective leaf area to estimate LAI are very labour-intensive, require many replicates to reduce sampling errors (Chason et al. 1991) and must depend on extrapolation using allometric methods (Chen et al. 1997). More rapid, indirect estimates can be obtained by measuring light transmission through a plant canopy and using Lambert-Beer’s law or gap fraction theory (cf. Norman and Campbell 1989, Weiss et al. 2004) to infer the thickness of the absorbing plant layer. The gap fraction is the ratio of the above to the below-canopy radiation. A widely used instrument to estimate LAI based on gap fraction measurements is the Li-Cor LAI-2000 Plant Canopy Analyser (PCA;
Li-Cor Inc., Lincoln, Nebraska, USA). A semi-direct, non-destructive method suited to deciduous forests with a single, comparatively short leaf-fall season, is the collection of litter in traps below the canopy.
In the present study, direct, semi-direct and indirect methods were employed to as-sess the leaf area of trees (Alt) and LAI, since all the temporal and spatial levels of resolution mentioned are important in characterising and analysing structure-function relationships for different species and stands over time.
4.4.1. Direct estimates of LAI, allometric relationships
Direct LAI estimates, based on branch harvests and subsequent leaf planimetry, site-and species-specific allometry (e.g. Dixon 1971, Grier site-and Waring 1974, Waring et al.
1977) and scaling to stand level, were formed in close cooperation with the present study by S. Fleck, Plant Ecology, University of Bayreuth, for four trees at the same investigation sites in 1997 and 1998: one beech and one oak tree at Großebene and two beech trees at Farrenleite (see Fleck 2002). Harvesting was leaf-cloud-oriented (cf. Fleck 2002) and all the branches of the oak at Großebene and of the two beech trees at Farrenleite were harvested; of the beech at Großebene about 40 % of all the branches were harvested. For the purpose of a detailed three-dimensional mechanis-tic gas exchange model (Fleck 2002), description of structural parameters was very detailed on a sub-tree level, namely on leaf and leaf cloud level, and thus only a few mature trees could be tackled with this strategy. The tree canopies were accessed via a hydraulic lift (Teupen Hylift, Gronau, Germany) whose platform reached 23 m above ground. For a more detailed description of the procedures see Fleck (2002).
Given the limited number of trees considered, more general relationships for beech and oak between the leaf area of a tree (Alt) and an easily accessible scalar like DBH or basal area of a tree (Abt) were sought. Fleck (2002) and Fleck et al. (2004) ap-proximated the following allometric relationships, for F. sylvatica based on harvests by Pellinen (1986), Bartelink (1997) and Fleck (2002), a total of 45 trees:
Alt = 0.876 Abt0.81
[m2], r2 = 0.89 (beech), (Eq. 4.4.1)
for Q. petraea using results from Burger (1947, including data from Q. robur) and Fleck (2002), totalling 52 trees:
Alt = 0.871 Abt0.854 [m2], r2 = 0.854 (oak), (Eq. 4.4.2) with Abt in cm2.
These data showed a considerable variation among the older trees, which appeared to be stand-specific (Fleck et al. 2004). Leaf area estimated with the above regres-sions yielded values 10 % (beech) and 27 % (oak) larger than calculated from direct measurements on the trees harvested at Großebene (Fleck 2002). A stand-specific calibration reduced constants in the above equations to 0.77 for beech and to 0.616 for oak (Fleck, pers. comm.):
Alt = 0.77 Abt0.81
[m2] (beech), (Eq. 4.4.3)
Alt = 0.616 Abt0.854
[m2] (oak), (Eq. 4.4.4)
with Abt in cm2.
To calculate LAI from these allometric relationships, the equations were applied to all stem diameters of the respective plot, totalled and divided by the plot area (see Fleck 2002). This resulted in values of LAI of 6.4 (Steinkreuz) and 6.3 (Großebene) using the stand-adjusted constants (Fleck et al. 2004). Adjusted LAI at Farrenleite was 8.1 (Fleck 2002).
4.4.2. Semi-direct estimates of LAI, leaf area per unit dry mass
Semi-direct LAI estimates were gained from non-destructive and less labour-inten-sive litter collections. 10 square-shaped litter traps of 1 m2 or 0.15 m2 surface area were set up on the forest floor at Steinkreuz and Großebene respectively, and three at Farrenleite (0.15 m2). Drainage was facilitated by the use of coarse-meshed mate-rial for the bottom of the traps. Litter was collected from the traps weekly or biweekly during autumn. Depending on the amount of foliage, the projected, half-total surface leaf area of the whole sample from a litter trap or of a subsample was measured and scaled up to the whole sample by leaf area per unit of dry mass (or specific leaf area;
SLA) after drying the sample and subsample at 70 °C to a constant mass. The SLA was determined separately for each trap because of the potentially large spatial vari-ability of SLA due to differences in stand structure (see Bouriaud et al. 2003) and large potential errors of up to 24 % when computing LAI from SLA (Bouriaud et al.
2003). Additionally, the SLA was determined for each sampling date individually be-cause of the known seasonal variability in SLA (Heller and Götsche 1986, Gratani et al. 1987, both in the sun and shade crown), except for Steinkreuz in the year 2000, where an average value from the year 1999 was used (198 cm2 g-1 and 138 cm2 g-1 for beech and oak respectively). In Großebene, in 1999 the leaf area of all samples was measured and no SLA determined. Projected leaf areas were measured using either a Delta-T Image Analysis System (DIAS; Delta-T Devices Ltd., Cambridge, UK) or a LI-3100 Area Meter (Li-Cor Inc., Lincoln, Nebraska, USA).
4.4.3. Indirect estimates of LAI
Indirect LAI estimates were derived from measurements with the LAI-2000 Plant Canopy Analyser (PCA; Li-Cor Inc., Lincoln, Nebraska, USA). LAI (or more precisely the plant or vegetation area index, PAI or VAI, respectively, see below) is calculated using inverted gap fraction data. The PCA uses fisheye optics to project a hemi-spheric image of the canopy above the horizontally exposed lenses onto five silicone detectors (photodiodes) arranged in concentric rings. The field of view of those con-centric rings is centred around zenith angles of 7°, 23 °, 38°, 53°, 68°, numbered 1 to 5, respectively (Li-Cor 1992). The azimuthal field of view is 360°. An optical filter which restricts transmitted radiation to below 490 nm minimises the contribution of light scattered by foliage (Welles 1990, Welles and Norman 1991). The lower limit for radiation measurement is 400 nm (Chen et al. 1997).
Two LAI-2000 Plant Canopy Analyser-units were used in this study. The instruments were used in remote mode, their clocks synchronised and silicone detectors cali-brated to each other before any reading was taken at each measurement day. The reference unit was programmed to take readings of the “above canopy” radiation every 15 seconds in nearby forest openings that were large enough not to block more of the horizon than what is detected by the outermost concentric ring of the fisheye optics, since this ring was not going to be used anyway for methodological considerations (see below). The below-canopy measurements were made at 5 m grid points in 50 m x 50 m plots (110 sampling points, marked with wooden posts and tagged lines) in the Steinkreuz and Großebene stands, and around the centre of the plot in Farrenleite in 5, 10, 15 and 20 m distance in the four cardinal directions.
Readings were taken at 2 m height above the ground in all stands, the sensor head clamped onto a 2 m long wooden stick and levelled from below. This avoided unin-tended shading of the optics by the operator and standardised the sampling proce-dure. A view restrictor (Li-Cor 1992) was not used. Since the theory of gap fraction analysis assumes that only skylight is seen by the sensors, measurements were carried out under diffuse light as advised by Welles and Norman (1991), either under overcast sky conditions, or at dawn or dusk. Measurements were repeated several times over the course of the growing seasons and also during winter.
Since all parts of plants (leaves, branches, stems) intercept light on its way through the canopy to the below-canopy sensor, the PCA primarily estimates the plant area index (PAI). PAI was calculated using the Li-Cor software C2000 (Li-Cor 1992), com-bining the above-canopy and below-canopy light values from the two units based on the time of observation. Readings from the outermost ring (zenith viewing angles 61°–74°) were omitted using only rings 1 to 4 to improve accuracy (Dufrêne and Bréda 1995, Cutini et al. 1998). PCA-readings from sampling points directly beside a tree trunk or directly under low branches were rejected (a total of 12 in Steinkreuz and 2 in Großebene) and interpolated from the readings of the surrounding sampling points.
PAI-estimates were afterwards corrected for light interception by woody elements (stems, branches) and for foliage element non-randomness (element clumping) as suggested by Kucharik et al. (1998) to result in LAI. Gap fraction theory assumes random spatial distribution of light intercepting elements (Welles 1990, Welles and Cohen 1996). The non-randomness correction factor for foliage (Kucharik et al. 1998) in closed temperate deciduous oak and maple forest canopies was measured to be close to one (randomness; Kucharik et al. 1999). The LAI of those stands was 4.5
and 6, respectively, and thus comparable to the Steigerwald and Fichtelgebirge sites.
Values for the non-randomness correction factor were taken from Fig. 5 in Kucharik et al. (1999) and estimated to be on average 0.91 for oak and 0.96 for beech (sugar maple in their study, assumed to be very similar to beech in its canopy structure) for the zenith angles used in the present data evaluation (5°–60°, rings 1–4 of PCA).
These values have been corroborated by Eriksson et al. (2005). For the mixed spe-cies stands under regard here, the non-randomness correction factors for oak and beech were weighted by the species’ contribution to stand density. The PAI-estimate calculated by the C2000-software was then divided by this site-adjusted non-random-ness correction factor. Then the stem hemi-surface area index (SAI) beneath crowns was estimated by approximating the projected stem area from the height of insertion of the lowest living branch and the stem diameter, and dividing their sum by the plot area (cf. Kucharik et al. 1998). Branch hemi-surface area is mostly masked by foliage in oak and beech canopies during the vegetation period (Dufrêne and Bréda 1995, Kucharik et al. 1999) and was found to amount to only about 6 % of the leaf area of leaf clouds of beech and oak at Großebene (Fleck et al. 2004) and consequently negligible for corrections. Below-crown SAI was then subtracted from non-random-ness corrected PAI to give LAI (Kucharik et al. 1998).