Leaf Position and Structure

Leaf position and structure were studied by measuring leaves from all 3 poplar clones during August 2016 at the FastWOOD trial site fw11 Stiedenrode I. The above-ground biomass, which consists of stem and crown biomass that has grown from resprouting after harvesting 3 years ago, was aged 1 to 3 years at this time.

The below-ground biomass, which has basically grown since the year of planting, was 1 to 6 years old. All in all 5 trees were selected at random from 4 plots (see table 3.4).

Table 3.4: Trees that were randomly selected for leaf structure measurement in fw11 Stiedenrode I during August 2016.

Clone Plot Row Tree

MAX 71 4 6

MAX 71 4 8

HYB 22 4 6

HYB 77 4 7

AF2 76 4 5

The measurement itself consists of three steps: First measuring the tree as a whole, second measuring the branching structure of the stems per tree and third measuring the leaf structure of single leaves per branch. The first 2 steps were conducted in the same manner as devised for the structural measurement in leafless condition (see list in section 3.1.3). The detailed measuring of branching structure and structure of single leaves could not be conducted with the trees still standing since they had reached heights of 6 to 8 m. Therefore the examined stems were cut before measuring. An additional difficulty that arose from this practice was that stems and their branches usually had to be discarded if the measuring was not completed after one day at the latest because the leaves would start to wilt and lose their stability leading to distorted results. Due to the described wilting issue, watering the shoots was an additional step to delay any unwanted effects from withering. These were decreased further by protecting the cut off stems and branches from direct sunlight and wind. The latter was also important for establishing calm conditions that prevent the leaf blades from moving too heavily in the wind which can basically make measuring impossible.

Small gaps in the plantation stand can serve as suitable places for measuring

after separating the stems and their branches. Figure 3.9 contains an exemplary setup for measuring which can also be established in stand gaps.

Figure 3.9: Exemplary setup for measuring leaf structure. Shown here is the 3rd growth unit from the main stem of an ’AF2’ tree. The shoot was mounted to a pole while being watered at the shoot base (cutting surface). The measurement here is conducted outside of the plantation stand.

After establishing a proper mensuration setup the leaf structure was recorded with an adapted methodology based on the dtd format. A basis for the adaptation is given e.g. in Kurth (2014). The parameters that were measured at the single leaf level are listed in table 3.5.

Table 3.5: All parameters that where measured for leaf structure in 2016 on a single leaf level. Values for variables petiR and petiBladR are given as classified angles (see Figure 3.2). The parameters from the associated structural measurements in 2016 conform with the dtd specifications.

Variable Description Unit

mother Identifier of mother growth unit

nodeLeaf Binary variable: count of nodes carrying leaves (1) versus no leaves (0) leaf Rank Leaf rank as leaf number from base

iN odeL Internode length [mm]

heightRel Relative height of leaf in reference to maximum tree height [%]

relP os Relative position in reference to growth unit length [%]

petiL Petiole length [mm]

petiD Petiole diameter [mm]

petiW Orientation angle between internode and petiole [° ] petiR Directional angle of petiole to shoot in regard to reference direction [° ]

petiBladW Angle between leaf blade and petiole [° ]

petiBladR Angle of the rotation of the leaf blade in reference to the petiole [° ]

bladL Length of leaf blade [mm]

bladW Width of leaf blade [mm]

For easier understanding of the meaning of each variable, Figure 3.10 contains a display of all variables shown for example leaves and their mother growth units.

petiW

iNodeL

petiL

petiD

bladL bladW

petiBladW

(a)

(b)

(c)

Figure 3.10: Explanatory display for better understanding of variables measured with the dtd format adapted to leaf shape. Part (a) shows most of the variables described in Table 3.5. Variable petiR and its value is not marked but can be acquired from the directional schema at the bottom of the GU. The value is R3 here. Parts (b) and (c) exemplify different values for parameter petiBladR: R3-7 for (b) and R2-6 for (c).

While measuring the leaf structure the occurrence of leaf whorls could be ob-served, meaning that more than one leaf was present per node. A majority of these whorls was observed on growth units from the last vegetation period. On some of these growth units of age 2, single leaves were also observed. An ex-ample is given in Figure 3.11. Panel (a) illustrates a comparably high frequency of what appears to be leaf whorls on growth unit 2 (2 years old, order 0) while the upper growth units carry mostly single leaves. This separation of more alleged leaf whorls in the lower crown and more single leaves in the upper crown can be supported with the images in panels (b) and (c).

(a) (b) (c)

Figure 3.11: Example of occurrence of single leaves and what appears to be leaf whorls. All 3 photographs were taken from ’Hybride 275’ trees. The left panel (a) shows the top of the main stem of tree 77_4.7. The middle panel (b) shows the border between growth unit 1 (age 3, order 0) and 2 (age 2, order 0) of the main stem of tree 22_4.6. The panel on the right (c) shows the border between growth unit 2 (age 2, order 0) and 3 (age 1, order 0) of the same main stem of tree 22_4.6. The border is marked with a black line facing north in both cases.

Due to the position of 2 year old growth units, these leaves, either single or in whorls, were mainly observed in the lower half of the tree. At first these leaves were recorded in the same manner as leaves on growth units that had developed in the current vegetation period. For leaves in whorls, an additional identifier

was given to record whorl affiliation. The orientation of the whorl itself and the orientation of the leaves within a whorl was documented. By closer investigation and discussion of the results it became obvious that single leaves and whorls that were originally recorded with a 2 year old mother growth unit were actually growing on short shoots with very short internodes (compare also Critchfield, 1960; Dickmann et al., 2002). These short shoots hence had developed during the current growing season. To give a botanically sound representation of this background, short shoots were added to the structural data that inherited some of their properties from the initially recorded leaf position like insertion height and orientation. These short shoots were then set as the mother growth unit of the respective leaves.

Due to the overall high detail of the whole manual measuring technique, which inherently implies a comparably high time consumption, not all branches and leaves of the selected trees were measured. Only every 3rd growth unit was fully measured with all leaves. For the “non-detailed” GUs only the branching architec-ture, the number of single leaves and leaves per short shoots were recorded. For the “detailed” GUs the leaves on every 4th node including single leaves and all leaves on a short shoot where fully measured with all parameters from Table 3.5.

Leaves at the shoot tip were always measured even if their leaf rank didn’t fall into the measuring grid. For the remaining leaves only the iNodeL, petiR, bladL and bladW values were recorded.

After acquisition all data was digitized and imported into R. The data was con-trolled with some plausibility checks and then prepared for further processing.

The structural data that was acquired was transformed into the dtd format and then imported into GroIMP. GroIMP offers some of the Grogra functionalities in-cluding listing all shoots and their x-,y-, and z-coordinates. The information can be outputted in several formats like txt or csv. This can then be reimported into R for calculating the height of leaves and growth units. The calculation could be implemented in R as well, but it seemed more convenient to use the already available GroIMP features.