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@ARTICLE{Herbst:18340,
      author       = {Herbst, M. and Prolingheuer, N. and Graf, A. and Huisman,
                      J.A. and Weihermüller, L. and Vanderborght, J. and
                      Vereecken, H.},
      title        = {{M}ultivariate conditional stochastic simulation of soil
                      heterotrophic respiration at plot scale},
      journal      = {Geoderma},
      volume       = {160},
      issn         = {0016-7061},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {PreJuSER-18340},
      pages        = {74 - 82},
      year         = {2010},
      note         = {Special thanks to L Bornemann and F.M. Mertens for
                      providing the EM38 data. Many thanks to R. Harms for support
                      to field experiments and to A. Papritz for the fruitful
                      discussion at the Eurosoil conference. Further, we
                      gratefully acknowledge financial support by the SFB/TR 32
                      "Pattern in Soil-Vegetation-Atmosphere Systems: Monitoring,
                      Modelling and Data Assimilation" funded by the Deutsche
                      Forschungsgemeinschaft (DEG).},
      abstract     = {Soil heterotrophic respiration fluxes at plot scale exhibit
                      substantial spatial and temporal variability. Within this
                      study secondary information was used to spatially predict
                      heterotrophic respiration. Chamber-based measurements of
                      heterotrophic respiration fluxes were repeated for 15
                      measurement campaigns within a bare 13 x 14 m(2) soil plot.
                      Soil water contents and temperatures were measured
                      simultaneously with the same spatial and temporal
                      resolution. Further, we used measurements of soil organic
                      carbon content and apparent electrical conductivity as well
                      as the prior measurement of the target variable. The
                      previous variables were used as co-variates in a stepwise
                      multiple linear regression analysis to spatially predict
                      bare soil respiration. In particular the prior measurement
                      of the target variable, the soil water content and the
                      apparent electrical conductivity, showed a certain, even
                      though limited, predictive power. In the first step we
                      applied external drift kriging and regression kriging to
                      determine the improvement of using co-variates in an
                      estimation procedure in comparison to ordinary kriging. The
                      improvement using co-variates ranged between 40 and $1\%$
                      for a single measurement campaign. The difference in
                      improving the prediction of respiration fluxes between
                      external drift kriging and regression kriging was marginal.
                      In a second step we applied sequential Gaussian simulations
                      conditioned with external drift kriging to generate more
                      realistic spatial patterns of heterotrophic respiration at
                      plot scale. Compared to the estimation approaches the
                      conditional stochastic simulations revealed a significantly
                      improved reproduction of the probability density function
                      and the semi-variogram of the original point data. (C) 2009
                      Elsevier B.V. All rights reserved.},
      keywords     = {J (WoSType)},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Soil Science},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000285908600010},
      doi          = {10.1016/j.geoderma.2009.11.018},
      url          = {https://juser.fz-juelich.de/record/18340},
}