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@ARTICLE{Schnepf:848357,
      author       = {Schnepf, A. and Huber, K. and Landl, M. and Meunier, F. and
                      Petrich, L. and Schmidt, V.},
      title        = {{S}tatistical {C}haracterization of the {R}oot {S}ystem
                      {A}rchitecture {M}odel {CR}oot{B}ox},
      journal      = {Vadose zone journal},
      volume       = {17},
      number       = {1},
      issn         = {1539-1663},
      address      = {Madison, Wis.},
      publisher    = {SSSA},
      reportid     = {FZJ-2018-03598},
      pages        = {},
      year         = {2018},
      abstract     = {The connection between the parametrization of
                      three-dimensional (3D) root architecture models and
                      characteristic measures of the simulated root systems is
                      often not obvious. We used statistical methods to analyze
                      the simulation outcome of the root architecture model
                      CRootBox and built meta-models that determine the dependency
                      of root system measures on model input parameters. Starting
                      with a reference parameter set, we varied selected input
                      parameters one at a time and used CRootBox to compute 1000
                      root system realizations as well as their root system
                      measures. The obtained data sets were then statistically
                      analyzed with regard to dependencies between input
                      parameters, as well as distributions and correlations
                      between different root system measures. While absolute root
                      system measures (e.g., total root length) were approximately
                      normally distributed, distributions of ratios of root system
                      measures (e.g., root tip density) were highly asymmetric and
                      could be approximated with inverse gamma distributions. We
                      derived regression models (meta-models) that link
                      significant model parameters to 18 widely used root system
                      measures and determined correlations between different root
                      system measures. Statistical analysis of 3D root
                      architecture models helps to understand the impact of input
                      parametrization on specific root architectural measures. Our
                      developed meta-models can be used to determine the effect of
                      parameter variations on the distribution of root system
                      measures without running a full simulation. Model
                      intercomparison and benchmarking of root architecture models
                      is still missing. Our approach provides a means to compare
                      different models with each other and with experimental
                      data.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000439708700001},
      doi          = {10.2136/vzj2017.12.0212},
      url          = {https://juser.fz-juelich.de/record/848357},
}