Environmental control of land-atmosphere CO₂ fluxes from temperate ecosystems: a statistical approach based on homogenized time series from five land-use types

References

• Ahlström, A., Raupach, M. R., Schurgers, G., Smith, B., Arneth, A., and co-authors. 2015. Carbon cycle. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348, 895–899. doi:10.1126/science.aaa1668
   PubMed Web of Science ®Google Scholar
• Allard, V., Ourcival, J. M., Rambal, S., Joffre, R. and Rocheteau, A. 2008. Seasonal and annual variation of carbon exchange in an evergreen Mediterranean forest in southern France. Glob. Change Biol. 14, 714–725. doi:10.1111/j.1365-2486.2008.01539.x
   Web of Science ®Google Scholar
• Amiro, B. D., Barr, A. G., Barr, J. G., Black, T. A., Bracho, R., and co-authors. 2010. Ecosystem carbon dioxide fluxes after disturbance in forests of North America. J. Geophys. Res 115, G00K02, doi:10.1029/2010JG001390
   Web of Science ®Google Scholar
• Aubinet, M., Hurdebise, Q., Chopin, H., Debacq, A., De Ligne, A., and co-authors. 2018. Inter-annual variability of Net Ecosystem Productivity for a temperate mixed forest: A predominance of carry-over effects? Agric. For. Meteorol. 262, 340–353. doi:10.1016/j.agrformet.2018.07.024
   Web of Science ®Google Scholar
• Baldocchi, D. 2008. Breathing” of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems. Aust. J. Bot. 56, 1. doi:10.1071/BT07151
   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. doi:10.1016/j.agrformet.2017.05.015
   Web of Science ®Google Scholar
• Baldocchi, D., Falge, E. and Wilson, K. 2001. A spectral analysis of biosphere–atmosphere trace gas flux densities and meteorological variables across hour to multi-year time scales. Agric. For. Meteorol. 107, 1–27. doi:10.1016/S0168-1923(00)00228-8
   Web of Science ®Google Scholar
• Béziat, P., Ceschia, E. and Dedieu, G. 2009. Carbon balance of a three crop succession over two cropland sites in South West France. Agric. For. Meteorol. 149, 1628–1645. doi:10.1016/j.agrformet.2009.05.004
   Web of Science ®Google Scholar
• Bréda, N., Huc, R., Granier, A. and Dreyer, E. 2006. Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences. Ann. For. Sci. 63, 625–644. doi:10.1051/forest:2006042
   Web of Science ®Google Scholar
• Breiman, L. 2001. Random forests. Mach. Learn. 45, 5–32. doi:10.1023/A:1010933404324
   Web of Science ®Google Scholar
• Burba, G. G., Mc Dermitt, D. K., Grelle, A., Anderson, D. J. and Xu, L. 2008. Addressing the influence of instrument surface heat exchange on the measurements of CO2 flux from open-path gas analyzers. Glob. Change Biol. 14, 1854–1876. doi:10.1111/j.1365-2486.2008.01606.x
   Web of Science ®Google Scholar
• Buysse, P., Bodson, B., Debacq, A., De Ligne, A., Heinesch, B., and co-authors. 2017. Carbon budget measurement over 12 years at a crop production site in the silty-loam region in Belgium. Agric. For. Meteorol 246, 241–255. doi:10.1016/j.agrformet.2017.07.004
   Web of Science ®Google Scholar
• Cabon, A., Mouillot, F., Lempereur, M., Ourcival, J.-M., Simioni, G. and co-authors. 2018. Thinning increases tree growth by delaying drought-induced growth cessation in a Mediterranean evergreen oak coppice. For. Ecol. Manag. 409, 333–342. doi:10.1016/j.foreco.2017.11.030
   Web of Science ®Google Scholar
• Chu, H., Baldocchi, D. D., John, R., Wolf, S. and Reichstein, M. 2017. Fluxes all of the time? A primer on the temporal representativeness of FLUXNET. J. Geophys. Res. Biogeosci. 122, 289–307. doi:10.1002/2016JG003576
   Web of Science ®Google Scholar
• Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., and co-authors. 2005. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437, 529–533. doi:10.1038/nature03972
   PubMed Web of Science ®Google Scholar
• Damour, G., Simonneau, T., Cochard, H. and Urban, L. 2010. An overview of models of stomatal conductance at the leaf level. Plant Cell Environ. 33, 1419–1438.
   PubMed Web of Science ®Google Scholar
• Dannoura, M., Maillard, P., Fresneau, C., Plain, C., Berveiller, D., and co-authors. 2011. In situ assessment of the velocity of carbon transfer by tracing 13 C in trunk CO2 efflux after pulse labelling: variations among tree species and seasons. New Phytol. 190, 181–192. doi:10.1111/j.1469-8137.2010.03599.x
   Web of Science ®Google Scholar
• Delpierre, N. 2009. Etude du déterminisme des variations interannuelles des échanges carbonés entre les écosystèmes forestiers européens et l’atmosphère: une approche basée sur la modélisation des processus (thesis). Paris 11.
   Google Scholar
• Delpierre, N., Berveiller, D., Granda, E. and Dufrêne, E. 2016. Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest. New Phytol. 210, 459–470. doi:10.1111/nph.13771
   Web of Science ®Google Scholar
• Delpierre, N., Soudani, K., François, C., Köstner, B., Pontailler, J.-Y., and co-authors. 2009. Exceptional carbon uptake in European forests during the warm spring of 2007: a data–model analysis. Glob. Change Biol. 15, 1455–1474. doi:10.1111/j.1365-2486.2008.01835.x
   Web of Science ®Google Scholar
• Delpierre, N., Soudani, K., François, C., Le Maire, G., Bernhofer, C., and co-authors. 2012. Quantifying the influence of climate and biological drivers on the interannual variability of carbon exchanges in European forests through process-based modelling. Agric. For. Meteorol. 154-155, 99–112. doi:10.1016/j.agrformet.2011.10.010
   Web of Science ®Google Scholar
• Dou, X., Chen, B., Black, T. A., Jassal, R. S. and Che, M. 2015. Impact of nitrogen fertilization on forest carbon sequestration and water loss in a chronosequence of three Douglas-Fir stands in the Pacific Northwest. Forests 6, 1897–1921. doi:10.3390/f6061897
   Web of Science ®Google Scholar
• Dou, X., Yang, Y. and Luo, J. 2018. Estimating forest carbon fluxes using machine learning techniques based on eddy covariance measurements. Sustainability 10, 203. doi:10.3390/su10010203
   Web of Science ®Google Scholar
• Etchanchu, J., Rivalland, V., Gascoin, S., Cros, J., Tallec, T., and co-authors. 2017. Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France). Hydrol. Earth Syst. Sci. 21, 5693–5708. doi:10.5194/hess-21-5693-2017
   Web of Science ®Google Scholar
• Falge, E., Baldocchi, D., Olson, R., Anthoni, P., Aubinet, M., and co-authors. 2001. Gap filling strategies for defensible annual sums of net ecosystem exchange. Agric. For. Meteorol 107, 43–69. doi:10.1016/S0168-1923(00)00225-2
   Web of Science ®Google Scholar
• Fares, S., Vargas, R., Detto, M., Goldstein, A. H., Karlik, J. and co-authors. 2013. Tropospheric ozone reduces carbon assimilation in trees: estimates from analysis of continuous flux measurements. Glob. Chang. Biol. 19, 2427–2443. doi:10.1111/gcb.12222
   Web of Science ®Google Scholar
• Farquhar, G. D. 1978. Feedforward responses of stomata to humidity. Functional Plant Biol. 5, 787–800. doi:10.1071/PP9780787
   Web of Science ®Google Scholar
• Farquhar, G. D., Walker, D. A. and Osmond, C. B. 1989. Models of integrated photosynthesis of cells and leaves. Philos. Trans. R. Soc. Lond. B Biol. Sci. 323, 357–367.
   Web of Science ®Google Scholar
• Fernández-Martínez, M., Vicca, S., Janssens, I. A., Ciais, P., Obersteiner, M., and co-authors. 2017. Atmospheric deposition, CO2, and change in the land carbon sink. Sci. Rep. 7, 9632. doi:10.1038/s41598-017-08755-8
   Web of Science ®Google Scholar
• Fratini, G., Ibrom, A., Arriga, N., Burba, G. and Papale, D. 2012. Relative humidity effects on water vapour fluxes measured with closed-path eddy-covariance systems with short sampling lines. Agric. For. Meteorol. 165, 53–63. doi:10.1016/j.agrformet.2012.05.018
   Web of Science ®Google Scholar
• Fu, Z., Gerken, T., Bromley, G., Araújo, A., Bonal, D., and co-authors. 2018. The surface-atmosphere exchange of carbon dioxide in tropical rainforests: Sensitivity to environmental drivers and flux measurement methodology. Agric. For. Meteorol. 263, 292–307. doi:10.1016/j.agrformet.2018.09.001
   Web of Science ®Google Scholar
• Fu, Z., Stoy, P. C., Poulter, B., Gerken, T., Zhang, Z., and co-authors. 2019. Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange. Glob. Chang. Biol. 25, 3381–3394. doi:10.1111/gcb.14731
   Web of Science ®Google Scholar
• Gash, J. H. C. and Culf, A. D. 1996. Applying a linear detrend to eddy correlation data in realtime. Boundary-Layer Meteorol. 79, 301–306. doi:10.1007/BF00119443
   Web of Science ®Google Scholar
• Granier, A., Bréda, N., Biron, P. and Villette, S. 1999. A lumped water balance model to evaluate duration and intensity of drought constraints in forest stands. Ecol. Model 116, 269–283. doi:10.1016/S0304-3800(98)00205-1
   Web of Science ®Google Scholar
• Granier, A. and Loustau, D. 1994. Measuring and modelling the transpiration of a maritime pine canopy from sap-flow data. Agric. For. Meteorol 71, 61–81. doi:10.1016/0168-1923(94)90100-7
   Web of Science ®Google Scholar
• Granier, A., Loustau, D. and Br⏧da, N. 2000. A generic model of forest canopy conductance dependent on climate, soil water availability and leaf area index. Ann. For. Sci. 57, 755–765. doi:10.1051/forest:2000158
   Web of Science ®Google Scholar
• Granier, A., Reichstein, M., Bréda, N., Janssens, I. A., Falge, E., and co-authors. 2007. Evidence for soil water control on carbon and water dynamics in European forests during the extremely dry year: 2003. Agric. For. Meteorol 143, 123–145. doi:10.1016/j.agrformet.2006.12.004
   Web of Science ®Google Scholar
• Hollinger, D. Y., Aber, J., Dail, B., Davidson, E. A., Goltz, S. M., and co-authors. 2004. Spatial and temporal variability in forest–atmosphere CO2 exchange. Global Change Biol. 10, 1689–1706. doi:10.1111/j.1365-2486.2004.00847.x
   Web of Science ®Google Scholar
• Hong, J. and Kim, J. 2011. Impact of the Asian monsoon climate on ecosystem carbon and water exchanges: a wavelet analysis and its ecosystem modeling implications. Glob. Change Biol. 17, 1900–1916. doi:10.1111/j.1365-2486.2010.02337.x
   Web of Science ®Google Scholar
• Horst, T. W. and Lenschow, D. H. 2009. Attenuation of scalar fluxes measured with spatially-displaced sensors. Boundary-Layer Meteorol. 130, 275–300. doi:10.1007/s10546-008-9348-0
   Web of Science ®Google Scholar
• Janssens, I. A., Lankreijer, H., Matteucci, G., Kowalski, A. S., Buchmann, N., and co-authors. 2001. Productivity overshadows temperature in determining soil and ecosystem respiration across European forests. Global Change Biol. 7, 269–278. doi:10.1046/j.1365-2486.2001.00412.x
   Web of Science ®Google Scholar
• Jarosz, N., Brunet, Y., Lamaud, E., Irvine, M., Bonnefond, J.-M. and co-authors. 2008. Carbon dioxide and energy flux partitioning between the understorey and the overstorey of a maritime pine forest during a year with reduced soil water availability. Agric. For. Meteorol. 148, 1508–1523. doi:10.1016/j.agrformet.2008.05.001
   Web of Science ®Google Scholar
• Jia, X., Zha, T., Gong, J., Zhang, Y., Wu, B., and co-authors. 2018. Multi-scale dynamics and environmental controls on net ecosystem CO2 exchange over a temperate semiarid shrubland. Agric. For. Meteorol. 259, 250–259. doi:10.1016/j.agrformet.2018.05.009
   Web of Science ®Google Scholar
• Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S., and co-authors. 2017. Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature 541, 516–520. doi:10.1038/nature20780
   PubMed Web of Science ®Google Scholar
• Katul, G., Lai, C.-T., Schäfer, K., Vidakovic, B., Albertson, J., and co-authors. 2001. Multiscale analysis of vegetation surface fluxes: from seconds to years. Adv. Water Resour. 24, 1119–1132. doi:10.1016/S0309-1708(01)00029-X
   Web of Science ®Google Scholar
• Klumpp, K., Tallec, T., Guix, N. and Soussana, J.-F. 2011. Long-term impacts of agricultural practices and climatic variability on carbon storage in a permanent pasture. Glob. Change Biol. 17, 3534–3545. doi:10.1111/j.1365-2486.2011.02490.x
   Web of Science ®Google Scholar
• Law, B. E., Falge, E., Gu, L., Baldocchi, D. D., Bakwin, P., and co-authors. 2002. Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation. Agric. For. Meteorol. 113, 97–120. doi:10.1016/S0168-1923(02)00104-1
   Web of Science ®Google Scholar
• Liaw, A. and Wiener, M. 2018. RandomForest Package, 2018. Breiman and Cutler’s Random Forests for Classification and Regression. 29pp. Online at: https://cran.r-project.org/web/packages/randomForest/randomForest.pdf
   Google Scholar
• Liu, Z., Ballantyne, A. P., Poulter, B., Anderegg, W. R. L., Li, W., and co-authors. 2018. Precipitation thresholds regulate net carbon exchange at the continental scale. Nat. Commun. 9, 3596. doi:10.1038/s41467-018-05948-1
   Web of Science ®Google Scholar
• Loescher, H. W., Oberbauer, S. F., Gholz, H. L. and Clark, D. B. 2003. Environmental controls on net ecosystem-level carbon exchange and productivity in a Central American tropical wet forest. Global Change Biol. 9, 396–412. doi:10.1046/j.1365-2486.2003.00599.x
   Web of Science ®Google Scholar
• Loustau, D. and Granier, A. 1993. Environmental control of water flux through maritime pine (Pinus pinaster Ait.). In: Water Transport in Plants under Climatic Stress (eds. M. Borghetti, J. Grace, A. Raschi). Cambridge University Press, Cambridge, 205–18 pp.
   Google Scholar
• Loustau, D., Bosc, A., Colin, A., Ogée, J., Davi, H., and co-authors. 2005. Modeling climate change effects on the potential production of French plains forests at the sub-regional level. Tree Physiol. 25, 813–823. doi:10.1093/treephys/25.7.813
   PubMed Web of Science ®Google Scholar
• Luyssaert, S., Inglima, I., Jung, M., Richardson, A. D., Reichstein, M., and co-authors. 2007a. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Global Change Biol. 13, 2509–2537. doi:10.1111/j.1365-2486.2007.01439.x
   Web of Science ®Google Scholar
• Luyssaert, S., Janssens, I. A., Sulkava, M., Papale, D., Dolman, A. J., and co-authors. 2007b. Photosynthesis drives anomalies in net carbon-exchange of pine forests at different latitudes. Global Change Biol. 13, 2110–2127. doi:10.1111/j.1365-2486.2007.01432.x
   Web of Science ®Google Scholar
• Marcolla, B., Cescatti, A., Manca, G., Zorer, R., Cavagna, M., and co-authors. 2011. Climatic controls and ecosystem responses drive the inter-annual variability of the net ecosystem exchange of an alpine meadow. Agric. For. Meteorol 151, 1233–1243. doi:10.1016/j.agrformet.2011.04.015
   Web of Science ®Google Scholar
• Mauder, M. and Foken, T. 2004. Documentation and Instruction Manual of the Eddy Covariance Software Package TK2 – Universität Bayreuth. Abt. Mikrometeorologie, Arbeit-Sergebnisse 26, 44. pp. (Print: ISSN 1614-8916; Internet:ISSN 1614-8926).
   Google Scholar
• McInerney, D. and Nieuwenhuis, M. 2009. Comparative analysis of kNN and decision tree methods for the Irish National Forest Inventory. Int J. Remote Sens 30, 4937–4955. doi:10.1080/01431160903022936
   Web of Science ®Google Scholar
• Medlyn, B. E., Duursma, R. A., Eamus, D., Ellsworth, D. S., Prentice, I. C., and co-authors. 2011. Reconciling the optimal and empirical approaches to modelling stomatal conductance. Glob. Change Biol 17, 2134–2144. doi:10.1111/j.1365-2486.2010.02375.x
   Web of Science ®Google Scholar
• Moffat, A. M., Beckstein, C., Churkina, G., Mund, M. and Heimann, M. 2010. Characterization of ecosystem responses to climatic controls using artificial neural networks. Glob. Change Biol. 16, 2737–2749. doi:10.1111/j.1365-2486.2010.02171.x
   Web of Science ®Google Scholar
• Moncrieff, J., Clement, R., Finnigan, J. and Meyers, T. 2005. Averaging, detrending, and filtering of Eddy covariance time series. In: Handbook of Micrometeorology: A Guide for Surface Flux Measurement and Analysis, Atmospheric and Oceanographic Sciences Library (eds. X. Lee, W. Massman, B. Law). Springer, Dordrecht, Netherlands, 7–31 pp.
   Google Scholar
• Moncrieff, J. B., Massheder, J. M., de Bruin, H., Elbers, J., Friborg, T., and co-authors. 1997. A system to measure surface fluxes of momentum, sensible heat, water vapour and carbon dioxide. J. Hydrol., HAPEX-Sahel 188-189, 589–611. doi:10.1016/S0022-1694(96)03194-0
   Web of Science ®Google Scholar
• Moreaux, V., Lamaud, É., Bosc, A., Bonnefond, J.-M., Medlyn, B. E. and co-authors. 2011. Paired comparison of water, energy and carbon exchanges over two young maritime pine stands (Pinus pinaster Ait.): effects of thinning and weeding in the early stage of tree growth. Tree Physiol. 31, 903–921. doi:10.1093/treephys/tpr048
   PubMed Web of Science ®Google Scholar
• Morlet, J., Arens, G., Fourgeau, E. and Giard, D. 1982. Wave propagation and sampling theory—Part II: Sampling theory and complex waves. Geophysics 47, 222–236. doi:10.1190/1.1441329
   Web of Science ®Google Scholar
• Mouillot, F., Rambal, S. and Lavorel, S. 2001. A generic process-based SImulator for meditERRanean landscApes (SIERRA): design and validation exercises. For. Ecol. Manag. 147, 75–97. doi:10.1016/S0378-1127(00)00432-1
   Web of Science ®Google Scholar
• Moya, M. R., Sánchez-Cañete, E. P., Vargas, R., López-Ballesteros, A., Oyonarte, C., and co-authors. 2019. CO2 dynamics are strongly influenced by low frequency atmospheric pressure changes in semiarid grasslands. J. Geophys. Res. Biogeosci. 124, 902–917. doi:10.1029/2018JG004961
   Web of Science ®Google Scholar
• Niu, S., Fu, Z., Luo, Y., Stoy, P. C., Keenan, T. F., and co-authors. 2017. Interannual variability of ecosystem carbon exchange: From observation to prediction. Global Ecol. Biogeogr. 26, 1225–1237. doi:10.1111/geb.12633
   Google Scholar
• Novick, K. A., Ficklin, D. L., Stoy, P. C., Williams, C. A., Bohrer, G., and co-authors. 2016. The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nature Clim. Change 6, 1023–1027. doi:10.1038/nclimate3114
   Web of Science ®Google Scholar
• Ogée, J., Brunet, Y., Loustau, D., Berbigier, P. and Delzon, S. 2003. MuSICA, a CO2, water and energy multilayer, multileaf pine forest model: evaluation from hourly to yearly time scales and sensitivity analysis. Global Change Biol. 9, 697–717. doi:10.1046/j.1365-2486.2003.00628.x
   Web of Science ®Google Scholar
• Oren, R., Sperry, J. S., Katul, G. G., Pataki, D. E., Ewers, B. E., and co-authors. 1999. Survey and synthesis of intra- and interspecific variation in stomatal sensitivity to vapour pressure deficit. Plant Cell Environ. 22, 1515–1526. doi:10.1046/j.1365-3040.1999.00513.x
   Web of Science ®Google Scholar
• Ouyang, Z., Chen, J., Becker, R., Chu, H., Xie, J., and co-authors. 2014. Disentangling the confounding effects of PAR and air temperature on net ecosystem exchange at multiple time scales. Ecol. Complex 19, 46–58. doi:10.1016/j.ecocom.2014.04.005
   Web of Science ®Google Scholar
• Papale, D., Black, T. A., Carvalhais, N., Cescatti, A., Chen, J., and co-authors. 2015. Effect of spatial sampling from European flux towers for estimating carbon and water fluxes with artificial neural networks. J. Geophys. Res. Biogeosci. 120, 1941–1957. doi:10.1002/2015JG002997
   Web of Science ®Google Scholar
• Papale, D. and Valentini, R. 2003. A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization. Global Change Biol. 9, 525–535. doi:10.1046/j.1365-2486.2003.00609.x
   Web of Science ®Google Scholar
• Pereira, J. S., Mateus, J. A., Aires, L. M., Pita, G., Pio, C., and co-authors. 2007. Net ecosystem carbon exchange in three contrasting Mediterranean ecosystems - the effect of drought. Biogeosciences 4, 791–802. doi:10.5194/bg-4-791-2007
   Web of Science ®Google Scholar
• Pita, G., Gielen, B., Zona, D., Rodrigues, A., Rambal, S., and co-authors. 2013. Carbon and water vapor fluxes over four forests in two contrasting climatic zones. Agric. For. Meteorol. 180, 211–224. doi:10.1016/j.agrformet.2013.06.003
   Web of Science ®Google Scholar
• Rambal, S., Ourcival, J.-M., Joffre, R., Mouillot, F., Nouvellon, Y., and co-authors. 2003. Drought controls over conductance and assimilation of a Mediterranean evergreen ecosystem: scaling from leaf to canopy. Global Change Biol. 9, 1813–1824. doi:10.1111/j.1365-2486.2003.00687.x
   Web of Science ®Google Scholar
• Rayment, M. B., Loustau, D. and Jarvis, P. J. 2002. Photosynthesis and respiration of black spruce at three organizational scales: shoot, branch and canopy. Tree Physiol. 22, 219–229. doi:10.1093/treephys/22.4.219
   PubMed Web of Science ®Google Scholar
• Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., and co-authors. 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biol. 11, 1424–1439. doi:10.1111/j.1365-2486.2005.001002.x
   Web of Science ®Google Scholar
• Richardson, A. D., Hollinger, D. Y., Aber, J. D., Ollinger, S. V. and Braswell, B. H. 2007. Environmental variation is directly responsible for short- but not long-term variation in forest-atmosphere carbon exchange. Glob. Change Biol. 13, 788–803. doi:10.1111/j.1365-2486.2007.01330.x
   Web of Science ®Google Scholar
• Rösch, A. and Schmidbauer, H. 2018. WaveletComp 1.1: A guided tour through the R package. Online at: https://CRAN.R-project.org/package=WaveletComp58pp.
   Google Scholar
• Shao, J., Zhou, X., Luo, Y., Li, B., Aurela, M., and co-authors. 2016. Direct and indirect effects of climatic variations on the interannual variability in net ecosystem exchange across terrestrial ecosystems. Tellus B Chem. Phys. Meteorol. 68, 30575. doi:10.3402/tellusb.v68.30575
   Web of Science ®Google Scholar
• Sierra, C. A., Trumbore, S. E., Davidson, E. A., Vicca, S. and Janssens, I. 2015. Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture. J. Adv. Model. Earth Syst. 7, 335–356. doi:10.1002/2014MS000358
   Web of Science ®Google Scholar
• Stoy, P. C., Dietze, M. C., Richardson, A. D., Vargas, R., Barr, A. G., and co-authors. 2013. Evaluating the agreement between measurements and models of net ecosystem exchange at different times and timescales using wavelet coherence: an example using data from the North American Carbon Program Site-Level Interim Synthesis. Biogeosciences 10, 6893–6909. doi:10.5194/bg-10-6893-2013
   Web of Science ®Google Scholar
• Stoy, P. C., Katul, G. G., Siqueira, M. B. S., Juang, J.-Y., McCarthy, H. R., and co-authors. 2005. Variability in net ecosystem exchange from hourly to inter-annual time scales at adjacent pine and hardwood forests: a wavelet analysis. Tree Physiol. 25, 887–902. doi:10.1093/treephys/25.7.887
   PubMed Web of Science ®Google Scholar
• Stoy, P. C., Richardson, A. D., Baldocchi, D. D., Katul, G. G., Stanovick, J., and co-authors. 2009. Biosphere-atmosphere exchange of CO2 in relation to climate: a cross-biome analysis across multiple time scales. Biogeosciences 6, 2297–2312. doi:10.5194/bg-6-2297-2009
   Web of Science ®Google Scholar
• Torrence, C. and Compo, G. P. 1998. A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79, 18.
   Web of Science ®Google Scholar
• Torrence, C. and Webster, P. J. 1999. Interdecadal changes in the ENSO–Monsoon System. J. Clim. 12, 12.
   Web of Science ®Google Scholar
• Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., and co-authors. 2016. Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms. Biogeosciences 13, 4291–4313. doi:10.5194/bg-13-4291-2016
   Web of Science ®Google Scholar
• Urbanski, S., Barford, C., Wofsy, S., Kucharik, C., Pyle, E., and co-authors. 2007. Factors controlling CO2 exchange on timescales from hourly to decadal at Harvard Forest. J. Geophys. Res. 112, G02020.
   Web of Science ®Google Scholar
• Vargas, R., Baldocchi, D. D., Allen, M. F., Bahn, M., Black, T. A., and co-authors. 2010a. Looking deeper into the soil: biophysical controls and seasonal lags of soil CO2 production and efflux. Ecol. Appl. 20, 1569–1582. doi:10.1890/09-0693.1
   PubMed Web of Science ®Google Scholar
• Vargas, R., Detto, M., Baldocchi, D. D. and Allen, M. F. 2010b. Multiscale analysis of temporal variability of soil CO2 production as influenced by weather and vegetation. Glob. Change Biol. 16, 1589–1605. doi:10.1111/j.1365-2486.2009.02111.x
   Web of Science ®Google Scholar
• Vargas, R., Baldocchi, D. D., Bahn, M., Hanson, P. J., Hosman, K. P., and co-authors. 2011. On the multi-temporal correlation between photosynthesis and soil CO2 efflux: reconciling lags and observations. New Phytol. 191, 1006–1017. doi:10.1111/j.1469-8137.2011.03771.x
   Web of Science ®Google Scholar
• Vialet-Chabrand, S. R. M., Matthews, J. S. A., McAusland, L., Blatt, M. R., Griffiths, H. and co-authors. 2017. Temporal dynamics of stomatal behavior: Modeling and implications for photosynthesis and water use. Plant Physiol. 174, 603–613. doi:10.1104/pp.17.00125
   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.(1997)014 < 0512:QCAFSP > 2.0.CO;2 doi:10.1175/1520-0426(1997)014<0512:QCAFSP>2.0.CO;2
   Web of Science ®Google Scholar
• Vuichard, N., Soussana, J.-F., Ciais, P., Viovy, N. and Ammann, C, and co-authors. 2007. Estimating the greenhouse gas fluxes of European grasslands with a process-based model: 1. Model evaluation from in situ measurements. Glob. Biogeochem. Cycles 21, GB1004, doi:10.1029/2005GB002611.
   Web of Science ®Google Scholar
• Webb, E. K., Pearman, G. I. and Leuning, R. 1980. Correction of flux measurements for density effects due to heat and water vapour transfer. QJ. Royal Met. Soc. 106, 85–100. doi:10.1002/qj.49710644707
   Web of Science ®Google Scholar
• White, M. A., Running, S. W. and Thornton, P. E. 1999. The impact of growing-season length variability on carbon assimilation and evapotranspiration over 88 years in the eastern US deciduous forest. Int. J. Biometeorol. 42, 139–145. doi:10.1007/s004840050097
   PubMed Web of Science ®Google Scholar
• Wilczak, J. M., Oncley, S. P. and Stage, S. A. 2001. Sonic Anemometer tilt correction algorithms. Bound.-Layer Meteorol. 99, 127–150. doi:10.1023/A:1018966204465
   Web of Science ®Google Scholar
• Wohlfahrt, G., Fenstermaker, L. F. and Arone, J. A A. III. 2008. Large annual net ecosystem CO2 uptake of a Mojave Desert ecosystem. Global Change Biol. 14, 1475–1487. doi:10.1111/j.1365-2486.2008.01593.x
   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