% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Fti:808531,
      author       = {Fóti, Szilvia and Balogh, János and Herbst, Michael and
                      Papp, Marianna and Koncz, Péter and Bartha, Sándor and
                      Zimmermann, Zita and Komoly, Cecília and Szabó, Gábor and
                      Margóczi, Katalin and Acosta, Manuel and Nagy, Zoltán},
      title        = {{M}eta-analysis of field scale spatial variability of
                      grassland soil {CO}$_{2}$ efflux: {I}nteraction of biotic
                      and abiotic drivers},
      journal      = {Catena},
      volume       = {143},
      issn         = {0341-8162},
      address      = {New York, NY [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2016-02269},
      pages        = {78 - 89},
      year         = {2016},
      abstract     = {In this study eight temperate grassland sites were
                      monitored for soil CO2 efflux (Rs) and the spatial covariate
                      soilwater content (SWC) and soil temperature (Ts) at fine
                      scale in over 77 measurement campaigns. The goals of
                      thismultisite study were to explore the correlations between
                      environmental gradients and spatial patterns of Rs, SWCand
                      Ts, which are not site-specific and to quantify the
                      relevance of biotic and abiotic controls over spatial
                      patternsalong increasing vegetation structural complexity.
                      These patterns in water-limited ecosystems in
                      East-CentralEurope are likely to be influenced by summer
                      droughts caused by the changing climate.A consistent
                      experimental setupwas applied at the study sites including
                      75 sampling locations along 15m circulartransects. Spatial
                      data processing was mainly based on variography. Two proxy
                      variables were introduced torelate the site characteristics
                      in terms of soils, water status and vegetation. Normalised
                      SWC (SWCn) reconciledsite-specific soil water regimes while
                      normalised day of year integrated temperature and vegetation
                      phenology.A principal component analysis revealed that the
                      progressing closure of vegetation in combination with large
                      Rsand SWCn values, as well as low Ts and Rs variability
                      support the detectability of spatial patterns found in both
                      theabiotic and biotic variables. Our results showed that
                      apart from SWC the pattern of soil temperature also had
                      aneffect on spatial structures.We detected that when the
                      spatially structured variability of Ts was low, a strong
                      negativecorrelation existed between SWCn and the spatial
                      autocorrelation length of Rs with r = 0.66 (p b
                      0.001).However, for high spatially structured variability of
                      Ts, occurring presumably at low Ts in spring and autumn,the
                      correlation did not exist and itwas difficult to quantify
                      the spatial autocorrelation of Rs. Our results are
                      indicativeof a potential shift from homogeneity and
                      dominance of biotic processes to an increased heterogeneity
                      andabiotic regulation in drought prone ecosystems under
                      conditions of decreasing soil moisture.},
      cin          = {IBG-3},
      ddc          = {910},
      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:000376800800010},
      doi          = {10.1016/j.catena.2016.03.034},
      url          = {https://juser.fz-juelich.de/record/808531},
}