Net carbon ecosystem exchange during 24 years in the Sorø Beech Forest – relations to phenology and climate

References

• Babst, F., Bouriaud, O., Papale, D., Gielen, B., Janssens, I. A. and co-authors. 2014. Above-ground woody carbon sequestration measured from tree rings is coherent with net ecosystem productivity at five eddy-covariance sites. New Phytol. 201, 1289–1303. doi:10.1111/nph.12589
   Web of Science ®Google Scholar
• Baldocchi, D., Chu, H. and Reichstein, M. 2018. Inter-annual variability of net and gross ecosystem carbon fluxes: a review. Agric. For. Meteorol. 249, 520–533. URL http://www.sciencedirect.com/science/article/pii/S0168192317301806, doi:10.1016/j.agrformet.2017.05.015.
   Web of Science ®Google Scholar
• Baldocchi, D. D. 2020. How eddy covariance flux measurements have contributed to our understanding of Global Change Biology. Glob. Change Biol. 26, 242–260. doi:10.1111/gcb.14807.
   Web of Science ®Google Scholar
• Dellwik, E. and Jensen, N. O. 2005. Flux-profile relationships over a fetch limited beech forest. Boundary-Layer Meteorol. 115, 179–204. doi:10.1007/s10546-004-3808-y
   Web of Science ®Google Scholar
• Ellermann, T., Nygaard, J., Nøjgaard, J. K., Nordstrøm, C., Brandt, J. and co-authors. 2018. The Danish Air Quality Monitoring Programme. Annual Summary for 2017, Scientific Report from DCE – Danish Centre for Environment and Energy No. 281, Aarhus University, DCE – Danish Centre for Environment and Energy, Scientific Report from DCE – Danish Centre for Environment and Energy 281, Aarhus University, DCE – Danish Centre for Environment and Energy,.
   Google Scholar
• Fernandez-Martinez, M., Vicca, S., Janssens, I., Ciais, P., Obersteiner, M. and co-authors. 2017. Atmospheric deposition, CO2, and change in the land carbon sink. Sci. Rep. 7, 1–13. s41598-017-08755-8
   Web of Science ®Google Scholar
• Fernández-Martínez, M., Sardans, J., Chevallier, F., Ciais, P., Obersteiner, M. and co-authors. 2019. Global trends in carbon sinks and their relationships with CO2 and temperature. Nature Clim. Change 9, 73–79. doi:10.1038/s41558-018-0367-7
   Web of Science ®Google Scholar
• Foken, T. and Wichura, B. 1996. Tools for quality assessment of surface-based flux measurements. Agric. For. Meteorol. 78, 83–105. doi:10.1016/0168-1923(95)02248-1
   Web of Science ®Google Scholar
• Frank, D., Reichstein, M., Bahn, M., Thonicke, K., Frank, D. and co-authors. 2015. Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts. Glob. Chang. Biol. 21, 2861–2880. 2015. doi:10.1111/gcb.12916
   PubMed Web of Science ®Google Scholar
• Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Hauck, J. and co-authors. 2019. Global Carbon Budget 2019. Earth Syst. Sci. Data 11, 1783–1838. doi:10.5194/essd-11-1783-2019
   Web of Science ®Google Scholar
• Hollinger, D. Y. and Richardson, A. D. 2005. Uncertainty in eddy covariance measurements and its application to physiological models. Tree Physiol. 25, 873–885. doi:10.1093/treephys/25.7.873
   PubMed Web of Science ®Google Scholar
• Horst, T. 1997. A simple formula for attenuation of eddy fluxes measured with first-order-response scalar sensors. Boundary. Layer Meteorol. 82, 219–233. doi:10.1023/A:1000229130034
   Web of Science ®Google Scholar
• Ibrom, A., Dellwik, E., Flyvbjerg, H., Jensen, N. O. and Pilegaard, K. 2007. Strong low-pass filtering effects on water vapour flux measurements with closed-path eddy correlation systems. Agric. For. Meteorol. 147, 140–156. doi:10.1016/j.agrformet.2007.07.007
   Web of Science ®Google Scholar
• Ibrom, A., Dellwik, E., Larsen, S. E. and Pilegaard, K. 2007b. On the use of the Webb - Pearman - Leuning - theory for closed-path eddy correlation measurements. Tellus 59, 937–946. doi:10.1111/j.1600-0889.2007.00311.x
   Google Scholar
• Jiang, M., Medlyn, B. E., Drake, J. E., Duursma, R. A., Anderson, I. C. and co-authors. 2020. The fate of carbon in a mature forest under carbon dioxide enrichment. Nature 580, 227–231. doi:10.1038/s41586-020-2128-9
   Web of Science ®Google Scholar
• Keenan, T. and Williams, C. 2018. The terrestrial carbon sink. Annu. Rev. Environ. Resour. 43, 219–243. doi:10.1146/annurev-environ-102017-030204
   Web of Science ®Google Scholar
• Keenan, T. F., Gray, J., Friedl, M. A., Toomey, M., Bohrer, G. and co-authors. 2014. Net carbon uptake has increased through warming-induced changes in temperate forest phenology. Nature Clim. Change 4, 598–604. doi:10.1038/nclimate2253
   Web of Science ®Google Scholar
• Kljun, N., Calanca, P., Rotach, M. W. and Schmid, H. P. 2015. A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP). Geosci. Model Dev. 8, 3695–3713. doi:10.5194/gmd-8-3695-2015
   Web of Science ®Google Scholar
• Ladekarl, U. 2001. Soil moisture, evapotranspiration and groundwater recharge in forest and heathland, Ph.D. thesis, Department of Earth Sciences, University of Aarhus, Denmark.
   Google Scholar
• Liu, X., He, B., Guo, L., Huang, L. and Chen, D. 2020. Similarities and Differences in the Mechanisms Causing the European Summer Heatwaves in 2003, 2010, and 2018, Earth’s Future, n/a, e2019EF001386. URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019EF001386.
   Google Scholar
• Møller, C. M. 1933. Bonitetsvise tilvaekstoversigter for bøg, eg og rødgran i Danmark (in Danish). Dansk Skovforenings Tidsskrift 18, 1–12.
   Google Scholar
• Moore, C. 1986. Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol. 37, 17–35. doi:10.1007/BF00122754
   Web of Science ®Google Scholar
• Morgenstern, K. 2000. Turbulent CO2-, H2O- and energy fluxes above a Mediterranean oak and a mountainous spruce forest investigated by eddy-covariance measurements, Ph.D. thesis, Institut für Bioklimatologie. Georg-August-Universität Göttingen, Göttingen.
   Google Scholar
• Muggeo, V. M. 2008. Segmented: an R Package to Fit Regression Models with Broken-Line Relationships., R News, 8, 20–25, URL 2008. https://cran.r-project.org/doc/Rnews/
   Google Scholar
• Nakai, T., van der Molen, M. K., Gash, J. H. C. and Kodama, Y. 2006. Correction of sonic anemometer angle of attack errors. Agric. For. Meteorol. 136, 19–30. doi:10.1016/j.agrformet.2006.01.006
   Web of Science ®Google Scholar
• Nieuwstadt, F. T. M. 1981. The steady-state height and resistance laws of the nocturnal boundary layer: Theory compared with cabauw observations. Boundary-Layer Meteorol. 20, 3–17., doi:10.1007/BF00119920
   Web of Science ®Google Scholar
• Norby, R. J. and Zak, D. R. 2011. Ecological Lessons from Free-Air CO2 Enrichment (FACE) Experiments. Annu. Rev. Ecol. Evol. Syst. 42, 181–203., URL, doi:10.1146/annurev-ecolsys-102209-144647
   Web of Science ®Google Scholar
• Østergård, J. 2000. Jordbundsdannelse under bøgeskov og mark ved Lille Bøgeskov, Sorø (in Danish), Master’s thesis, Department of Earth Sciences, University of Aarhus, Denmark.
   Google Scholar
• Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E. and co-authors. 2011. A large and persistent carbon sink in the world’s forests. Science 333, 988–993. doi:10.1126/science.1201609
   PubMed Web of Science ®Google Scholar
• Pilegaard, K., Hummelshøj, P., Jensen, N. O. and Chen, Z. 2001. Two years of continuous CO2 eddy-flux measurements over a Danish beech forest. Agric. For. Meteorol. 107, 29–41. doi:10.1016/S0168-1923(00)00227-6
   Web of Science ®Google Scholar
• Pilegaard, K., Ibrom, A., Courtney, M. S., Hummelshøj, P. and Jensen, N. O. 2011. Increasing net CO2 uptake by a Danish beech forest during the period from 1996 to 2009. Agric. For. Meteorol. 151, 934–946. doi:10.1016/j.agrformet.2011.02.013
   Web of Science ®Google Scholar
• Press, H., Teukolsky, S., Vetterling, W. and Flannery, B. 1992. Numerical Recipes in C. 2nd edn. Cambridge: Cambridge University Press.
   Google Scholar
• Pugh, T. A. M., Lindeskog, M., Smith, B., Poulter, B., Arneth, A. and co-authors. 2019. Role of forest regrowth in global carbon sink dynamics. Proceedings of the National Academy of Sciences, 116, 4382–4387. https://www.pnas.org/content/116/10/4382.
   Google Scholar
• R Core Team. 2019. R: a language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
   Google Scholar
• Rannik, U. and Vesala, T. 1999. Autoregressive filtering versus linear detrending in estimation of fluxes by the eddy covariance method. Boundary. Layer Meteorol. 91, 259–280. doi:10.1023/A:1001840416858
   Web of Science ®Google Scholar
• Reyer, C. P. O., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf, Y. and co-authors. 2019. The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests. Earth Syst. Sci. Data Discuss. 12, 1–47. https://www.earth-syst-sci-data-discuss.net/essd-2019-220/, 2019.
   Web of Science ®Google Scholar
• Sabbatini, S., Mammarella, I., Arriga, N., Fratini, G., Graf, A. and co-authors. 2018. Covariance raw data processing for CO2 and energy fluxes calculation at ICOS ecosystem stations. Int Agrophys. 32, 495. doi:10.1515/intag-2017-0043
   Web of Science ®Google Scholar
• Thomas, C. K., Law, B. E., Irvine, J., Martin, J. G., Pettijohn, J. C. and co-authors. 2009. Seasonal hydrology explains interannual and seasonal variation in carbon and water exchange in a semiarid mature ponderosa pine forest in central Oregon. J. Geophys. Res. 114, 1–22. doi:10.1029/2009JG001010.
   Web of Science ®Google Scholar
• Vicente-Serrano, S., Begueria, S. and Lopez-Moreno, J. I. 2010. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J. Climate 23, 1696–1718., doi:10.1175/2009JCLI2909.1
   Web of Science ®Google Scholar
• Vickers, D. and Mahrt, L. 1997. Quality control and flux sampling problems for tower and aircraft data. J. Atmos. Oceanic Technol. 14, 512–526. doi:10.1175/1520-0426(1997)014<0512:QCAFSP>2.0.CO;2
   Web of Science ®Google Scholar
• Vitasse, Y. and Basler, D. 2013. What role for photoperiod in the bud burst phenology of European beech. Eur. J. Forest Res. 132, 1–8. doi:10.1007/s10342-012-0661-2
   Web of Science ®Google Scholar
• Wolf, S., Keenan, T. F., Fisher, J. B., Baldocchi, D. D., Desai, A. R. and co-authors. 2016. Warm spring reduced carbon cycle impact of the 2012 US summer drought, Proceedings of the National Academy of Sciences, 113, 5880–5885., URL https://www.pnas.org/content/113/21/5880
   Google Scholar
• Wu, J., Larsen, K., van der Linden, L., Beier, C., Pilegaard, K. and co-authors. 2013. Synthesis on the carbon budget and cycling in a Danish, temperate deciduous forest. Agric. For. Meteorol. 181, 94–107. doi:10.1016/j.agrformet.2013.07.012
   Web of Science ®Google Scholar
• Wutzler, T., Lucas-Moffat, A., Migliavacca, M., Knauer, J., Sickel, K. and co-authors. 2018. Basic and extensible post-processing of eddy covariance flux data with REddyProc. Biogeosciences 15, 5015–5030. doi:10.5194/bg-15-5015-2018
   Web of Science ®Google Scholar
• Xu, B., Arain, M. A., Black, T. A., Law, B. E., Pastorello, G. Z. and co-authors. 2020. Seasonal variability of forest sensitivity to heat and drought stresses: a synthesis based on carbon fluxes from North American forest ecosystems. Glob. Chang. Biol. 26, 901–918. doi:10.1111/gcb.14843
   Web of Science ®Google Scholar
• Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z. and co-authors. 2016. Greening of the Earth and its drivers. Nature Clim. Change 6, 791–795. doi:10.1038/nclimate3004
   Web of Science ®Google Scholar