Temperature Dependence of Soil Respiration Modulated by Thresholds in Soil Water Availability Across European Shrubland Ecosystems
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Soil respiration (SR) is a major component of the global carbon cycle and plays a fundamental role in ecosystem feedback to climate change. Empirical modelling is an essential tool for predicting ecosystem responses to environmental change, and also provides important data for calibrating and corroborating process-based models. In this study, we evaluated the performance of three empirical temperature–SR response functions (exponential, Lloyd–Taylor and Gaussian) at seven shrublands located within three climatic regions (Atlantic, Mediterranean and Continental) across Europe. We investigated the performance of SR models by including the interaction between soil moisture and soil temperature. We found that the best fit for the temperature functions depended on the site-specific climatic conditions. Including soil moisture, we identified thresholds in the three different response functions that improved the model fit in all cases. The direct soil moisture effect on SR, however, was weak at the annual time scale. We conclude that the exponential soil temperature function may only be a good predictor for SR in a narrow temperature range, and that extrapolating predictions for future climate based on this function should be treated with caution as modelled outputs may underestimate SR. The addition of soil moisture thresholds improved the model fit at all sites, but had a far greater ecological significance in the wet Atlantic shrubland where a fundamental change in the soil CO2 efflux would likely have an impact on the whole carbon budget.
Keywordsannual soil respiration empirical soil respiration models soil moisture threshold shrubland temperature dependence temperature sensitivity
We gratefully acknowledge the support of the INCREASE Project (http://increase.ku.dk) funded by the EC FP7-Infrastructure-2008-1 Grant Agreement 227628, and the Hungarian Scientific Research Fund (OTKA K112576 and PD115637). ME and JP research was supported by the European Research Council Synergy Grant ERC-2013-SyG-610028 IMBALANCE-P, the Spanish Government Grant CGL2013-48074-P and the Catalan Government Grant SGR 2014-274. We thank the two anonymous reviewers for helpful comments and suggestions.
- Beier C, Emmett B, Tietema A, Schmidt IK, Peñuelas J, Kovács-Láng E, Duce P, de Angelis P, Gorissen A, Estiarte M, de Dato G, Sowerby A, Kröel-Dulay G, Lellei-Kovács E, Kull O, Mand P, Petersen H, Gjelstrup P, Spano D. 2009. Carbon and nitrogen balances for six shrublands across Europe. Glob Biogeochem Cycles 23:GB4008.CrossRefGoogle Scholar
- Burnham KP, Anderson DR. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edn. New York: Springer.Google Scholar
- IPCC 2013. The physical science basis. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM, Eds. Climate change 2013: contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.Google Scholar
- Mikkelsen TN, Beier C, Jonasson S, Holmstrup M, Schmidt IK, Ambus P, Pilegaard K, Michelsen A, Albert K, Andresen LC, Arndal MF, Bruun N, Christensen S, Danbæk S, Gundersen P, Jørgensen P, Linden LG, Kongstad J, Maraldo K, Priemé A, Riis-Nielsen T, Ro-Poulsen H, Stevnbak K, Selsted MB, Sørensen P, Larsen KS, Carter MS, Ibrom A, Martinussen T, Miglietta F, Sverdrup H. 2008. Experimental design of multifactor climate change experiments with elevated CO2, warming and drought: the CLIMAITE project. Funct Ecol 22:185–95.Google Scholar
- Peñuelas J, Prieto P, Beier C, Cesaraccio C, de Angelis P, de Dato G, Emmett BA, Estiarte M, Garadnai J, Gorissen A, Kovács-Láng E, Kröel-Dulay G, Llorens L, Pellizzaro G, Riis-Nielsen T, Schmidt IK, Sirca C, Sowerby A, Spano D, Tietema A. 2007. Response of plant species richness and primary productivity in shrublands along a north-south gradient in Europe to seven years of experimental warming and drought: reductions in primary productivity in the heat and drought year of 2003. Glob Change Biol 13:2563–81.CrossRefGoogle Scholar
- R Development Core Team. 2008. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. ISBN 3-900051-07-0. http://www.R-project.org.
- Reichstein M, Tenhunen JD, Roupsard O, Ourcival JM, Rambal S, Miglietta F, Peressotti A, Pecchiari M, Tirone G, Valentini R. 2002. Severe drought effects on ecosystem CO2 and H2O fluxes at three Mediterranean evergreen sites: revision of current hypotheses? Glob Change Biol 8:999–1017.CrossRefGoogle Scholar
- Vicca S, Bahn M, Estiarte M, van Loon EE, Vargas R, Alberti G, Ambus P, Arain MA, Beier C, Bentley LP, Borken W, Buchmann N, Collins SL, de Dato G, Dukes JS, Escolar C, Fay P, Guidolotti G, Hanson PJ, Kahmen A, Kröel-Dulay G, Ladreiter-Knauss T, Larsen KS, Lellei-Kovács E, Lebrija-Trejos E, Maestre FT, Marhan S, Marshall M, Meir P, Miao Y, Muhr J, Niklaus PA, Ogaya R, Peñuelas J, Poll C, Rustad LE, Savage K, Schindlbacher A, Schmidt IK, Smith AR, Sotta ED, Suseela V, Tietema A, van Gestel N, van Straaten O, Wan S, Weber U, Janssens IA. 2014. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments. Biogeosciences 11:2991–3013.CrossRefGoogle Scholar
- Xu L, Baldocchi DD, Tang J. 2004. How soil moisture, rain pulses, and growth alter the response of ecosystem respiration to temperature. Glob Biogeochem Cycles 18:GB4002.Google Scholar
- Zhou X, Sherry RA, An Y, Wallace LL, Luo Y. 2006. Main and interactive effects of warming, clipping, and doubled precipitation on soil CO2 efflux in a grassland ecosystem. Glob Biogeochem Cycles 20:GB1003.Google Scholar
- Zhou X, Wan SQ, Luo YQ. 2007. Source components and interannual variability of soil CO2 efflux under experimental warming and clipping in a grassland ecosystem. Glob Change Biol 13:761–75.Google Scholar