@article{EllsaesserRoellAhongshangbametal.2020,
  author    = {Ells{\"a}ßer, Florian and R{\"o}ll, Alexander and Ahongshangbam, Joyson and Waite, Pierre-Andr{\´e} and Hendrayanto, and Schuldt, Bernhard and H{\"o}lscher, Dirk},
  title     = {Predicting tree sap flux and stomatal conductance from drone-recorded surface temperatures in a mixed agroforestry system — a machine learning approach},
  series = {Remote Sensing},
  volume    = {12},
  journal   = {Remote Sensing},
  number    = {24},
  issn      = {2072-4292},
  doi       = {10.3390/rs12244070},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-220059},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@article{FuchsHertelSchuldtetal.2020,
  author    = {Fuchs, Sebastian and Hertel, Dietrich and Schuldt, Bernhard and Leuschner, Christoph},
  title     = {Effects of summer drought on the fine root system of five broadleaf tree species along a precipitation gradient},
  series = {Forests},
  volume    = {11},
  journal   = {Forests},
  number    = {3},
  issn      = {1999-4907},
  doi       = {10.3390/f11030289},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203189},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}