Authors
S Vicca, M Bahn, M Estiarte, EE van Loon, R Vargas, G Alberti, Per Ambus, MA Arain, Claus Beier, LP Bentley, W Borken, N Buchmann, SL Collins, G De Dato, Jeffrey S Dukes, C Escolar, P Fay, G Guidolotti, PJ Hanson, A Kahmen, G Kröel-Dulay, T Ladreiter-Knauss, Klaus Steenberg Larsen, E Lellei-Kovacs, E Lebrija-Trejos, FT Maestre, S Marhan, M Marshall, P Meir, Y Miao, Jan Muhr, PA Niklaus, R Ogaya, J Peñuelas, Christian Poll, LE Rustad, K Savage, A Schindlbacher, IK Schmidt, AR Smith, ED Sotta, V Suseela, A Tietema, N Van Gestel, O Van Straaten, S Wan, Ulrich Weber, Ivan A Janssens
Publication date
2014
Journal
Biogeosciences
Volume
11
Issue
11
Pages
2991-3013
Description
As a key component of the carbon cycle, soil CO2 efflux (SCE) is being increasingly studied to improve our mechanistic understanding of this important carbon flux. Predicting ecosystem responses to climate change often depends on extrapolation of current relationships between ecosystem processes and their climatic drivers to conditions not yet experienced by the ecosystem. This raises the question of to what extent these relationships remain unaltered beyond the current climatic window for which observations are available to constrain the relationships. Here, we evaluate whether current responses of SCE to fluctuations in soil temperature and soil water content can be used to predict SCE under altered rainfall patterns. Of the 58 experiments for which we gathered SCE data, 20 were discarded because either too few data were available or inconsistencies precluded their incorporation in the analyses. The 38 remaining experiments were used to test the hypothesis that a model parameterized with data from the control plots (using soil temperature and water content as predictor variables) could adequately predict SCE measured in the manipulated treatment. Only for 7 of these 38 experiments was this hypothesis rejected. Importantly, these were the experiments with the most reliable data sets, i.e., those providing high-frequency measurements of SCE. Regression tree analysis demonstrated that our hypothesis could be rejected only for experiments with measurement intervals of less than 11 days, and was not rejected for any of the 24 experiments with larger measurement intervals. This highlights the importance of high-frequency …
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