580 Pflanzen (Botanik)
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- Acer platanoides (1)
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- Fraxinus excelsior (1)
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Mobile laser scanning and geometrical analysis revealed relationships between tree geometry and seed dispersal mechanism, latitude of origin, as well as growth.
Abstract
The structure and dynamics of a forest are defined by the architecture and growth patterns of its individual trees. In turn, tree architecture and growth result from the interplay between the genetic building plans and environmental factors. We set out to investigate whether (1) latitudinal adaptations of the crown shape occur due to characteristic solar elevation angles at a species’ origin, (2) architectural differences in trees are related to seed dispersal strategies, and (3) tree architecture relates to tree growth performance. We used mobile laser scanning (MLS) to scan 473 trees and generated three-dimensional data of each tree. Tree architectural complexity was then characterized by fractal analysis using the box-dimension approach along with a topological measure of the top heaviness of a tree. The tree species studied originated from various latitudinal ranges, but were grown in the same environmental settings in the arboretum. We found that trees originating from higher latitudes had significantly less top-heavy geometries than those from lower latitudes. Therefore, to a certain degree, the crown shape of tree species seems to be determined by their original habitat. We also found that tree species with wind-dispersed seeds had a higher structural complexity than those with animal-dispersed seeds (p < 0.001). Furthermore, tree architectural complexity was positively related to the growth performance of the trees (p < 0.001). We conclude that the use of 3D data from MLS in combination with geometrical analysis, including fractal analysis, is a promising tool to investigate tree architecture.
Farmland tree cultivation is considered an important option for enhancing wood production. In South India, the native leaf-deciduous tree species Melia dubia is popular for short-rotation plantations. Across a rainfall gradient from 420 to 2170 mm year\(^{–1}\), we studied 186 farmland woodlots between one and nine years in age. The objectives were to identify the main factors controlling aboveground biomass (AGB) and growth rates. A power-law growth model predicts an average stand-level AGB of 93.8 Mg ha\(^{–1}\) for nine-year-old woodlots. The resulting average annual AGB increment over the length of the rotation cycle is 10.4 Mg ha\(^{–1}\) year\(^{–1}\), which falls within the range reported for other tropical tree plantations. When expressing the parameters of the growth model as functions of management, climate and soil variables, it explains 65% of the variance in AGB. The results indicate that water availability is the main driver of the growth of M. dubia. Compared to the effects of water availability, the effects of soil nutrients are 26% to 60% smaller. We conclude that because of its high biomass accumulation rates in farm forestry, M. dubia is a promising candidate for short-rotation plantations in South India and beyond.
Plant transpiration is a key element in the hydrological cycle. Widely used methods for its assessment comprise sap flux techniques for whole-plant transpiration and porometry for leaf stomatal conductance. Recently emerging approaches based on surface temperatures and a wide range of machine learning techniques offer new possibilities to quantify transpiration. The focus of this study was to predict sap flux and leaf stomatal conductance based on drone-recorded and meteorological data and compare these predictions with in-situ measured transpiration. To build the prediction models, we applied classical statistical approaches and machine learning algorithms. The field work was conducted in an oil palm agroforest in lowland Sumatra. Random forest predictions yielded the highest congruence with measured sap flux (r\(^2\) = 0.87 for trees and r\(^2\) = 0.58 for palms) and confidence intervals for intercept and slope of a Passing-Bablok regression suggest interchangeability of the methods. Differences in model performance are indicated when predicting different tree species. Predictions for stomatal conductance were less congruent for all prediction methods, likely due to spatial and temporal offsets of the measurements. Overall, the applied drone and modelling scheme predicts whole-plant transpiration with high accuracy. We conclude that there is large potential in machine learning approaches for ecological applications such as predicting transpiration.
While much research has addressed the aboveground response of trees to climate warming and related water shortage, not much is known about the drought sensitivity of the fine root system, in particular of mature trees. This study investigates the response of topsoil (0–10 cm) fine root biomass (FRB), necromass (FRN), and fine root morphology of five temperate broadleaf tree species (Acer platanoides L., Carpinus betulus L., Fraxinus excelsior L., Quercus petraea (Matt.) Liebl., Tilia cordata Mill.) to a reduction in water availability, combining a precipitation gradient study (nine study sites; mean annual precipitation (MAP): 920–530 mm year\(^{−1}\)) with the comparison of a moist period (average spring conditions) and an exceptionally dry period in the summer of the subsequent year. The extent of the root necromass/biomass (N/B) ratio increase was used as a measure of the species’ belowground sensitivity to water deficits. We hypothesized that the N/B ratio increases with long-term (precipitation gradient) and short-term reductions (moist vs. dry period) of water availability, while FRB changes only a little. In four of the five species (exception: A. platanoides), FRB did not change with a reduction in MAP, whereas FRN and N/B ratio increased toward the dry sites under ample water supply (exception: Q. petraea). Q. petraea was also the only species not to reduce root tip frequency after summer drought. Different slopes of the N/B ratio-MAP relation similarly point at a lower belowground drought sensitivity of Q. petraea than of the other species. After summer drought, all species lost the MAP dependence of the N/B ratio. Thus, fine root mortality increased more at the moister than the drier sites, suggesting a generally lower belowground drought sensitivity of the drier stands. We conclude that the five species differ in their belowground drought response. Q. petraea follows the most conservative soil exploration strategy with a generally smaller FRB and more drought-tolerant fine roots, as it maintains relatively constant FRB, FRN, and morphology across spatial and temporal dimensions of soil water deficits.