Eddy Covariance Measurements over Forests

Chapter
Part of the Springer Atmospheric Sciences book series (SPRINGERATMO)

Abstract

In the 1970s, scientists met with difficulties in estimating fluxes over tall vegetation, like forests, using flux-gradient relationship (Raupach 1979). The roughness of the exchanging surface drive to efficient turbulent mixing reducing the concentration gradient and invalidating Monin-Obukhov similarity theory (Lenschow 1995). In the 1990s, the eddy covariance (EC) method was developed and turned out to be very promising for CO2, latent, and sensible heat exchange quantification over these tall ecosystems. When the first networks of EC measurements were implemented (EuroFlux, Valentini et al. 2000; Ameriflux, Running et al. 1999), they included then a majority of forest sites. The other reasons for this historical forest leading position were their large terrestrial cover (FAO 2005 report) and their potentiality to store carbon over long periods (Valentini 2003).

Keywords

Leaf Area Index Eddy Covariance Biomass Increment Stem Flow Footprint Area 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Andre F, Jonard M, Jonard F, Ponette Q (2011) Spatial and temporal patterns of throughfall volume in a deciduous mixed-species stand. J Hydrol 400(1–2):244–254CrossRefGoogle Scholar
  2. Aubinet M, Berbigier P, Bernhofer CH et al (2005) Comparing CO2 storage and advection conditions at night at different CarboEuroflux sites. Bound Layer Meteorol 116:63–94CrossRefGoogle Scholar
  3. Bréda N (2003) Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. J Exp Bot 54(392):2403–2417CrossRefGoogle Scholar
  4. Čermák J, Kučera J, Bauerle WL et al (2007) Tree water storage and its diurnal dynamics related to sap flow and changes in stem volume in old-growth Douglas-fir trees. Tree Physiol 27:181–198CrossRefGoogle Scholar
  5. FAO (2005) Chapter 2: Extent of forest resources. In: Global forest resources assessment 2005, progress towards sustainable forest management. FAO, Rome, pp 11–12Google Scholar
  6. Flechard CR, Neftel A, Jocher M et al (2007) Temporal changes in soil pore space CO2 concentration and storage under permanent grassland. Agric For Meteorol 142:66–84CrossRefGoogle Scholar
  7. Göckede M, Foken T, Aubinet M et al (2008) Quality control of CarboEurope flux data – part 1: coupling footprint analyses with flux data quality assessment to evaluate sites in forest ecosystems. Biogeosciences 5:433–450CrossRefGoogle Scholar
  8. Grace J, Nichol C, Disney M et al (2007) Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence? Glob Chang Biol 13:1484–1497CrossRefGoogle Scholar
  9. Granier A, Biron P, Köstner B et al (1996) Comparison of xylem sap flow and water vapour flux at the stand level and derivation of the canopy conductance for Scots Pine. Theor Appl Climatol 53:115–122CrossRefGoogle Scholar
  10. Granier A, Breda N, Reichstein M et al (2007) Evidence for soil water control on carbon and water dynamics in European forests during the extremely dry year: 2003. Agric For Meteorol 143:123–145CrossRefGoogle Scholar
  11. Granier A, Breda N, Longdoz B et al (2008) Ten years of fluxes and stand growth in a young beech forest at Hesse, North-eastern France. Ann For Sci 64:704–726CrossRefGoogle Scholar
  12. Gut A, Blatter A, Fahrni M et al (1998) A new membrane tube technique (METT) for continuous gas measurements in soils. Plant Soil 198:79–88CrossRefGoogle Scholar
  13. Hendricks Franssena HJ, Stöcklid R, Lehner I et al (2010) Energy balance closure of eddy-covariance data: a multisite analysis for European FLUXNET stations. Agric For Meteorol 150:1553–1567CrossRefGoogle Scholar
  14. Jassal R, Black A, Novak M et al (2005) Relationship between soil CO2 efflux concentrations and forest-floor CO2 effluxes. Agric For Meteorol 130:176–192CrossRefGoogle Scholar
  15. Kutsch WL, Bahn M, Heinemeyer A (2010) Integrated methodology on soil carbon flux measurements. Cambridge University Press, CambridgeGoogle Scholar
  16. Lenschow DH (1995) Micrometeorological techniques for measuring biosphere-atmosphere trace gas exchange. In: Matson PA, Harriss RC (eds) Biogenic trace gas: measuring emissions from soil and water. Blackwell, London, pp 126–163, Great-BritainGoogle Scholar
  17. Levia DF Jr, Frost EE (2003) A review and evaluation of stemflow literature in the hydrologic and biogeochemical cycles of forested and agricultural ecosystems. J Hydrol 274:1–29CrossRefGoogle Scholar
  18. Longdoz B, Gross P, Granier A (2008) Multiple quality tests for analysing CO2 fluxes in a beech temperate forest. Biogeosciences 5:719–729CrossRefGoogle Scholar
  19. Lu P, Urban L, Zhao P (2004) Granier’s Thermal Dissipation Probe (TDP) method for measuring Sap flow in trees: theory and practice. Acta Botanica Sin 46(6):631–646Google Scholar
  20. Mayocchi CL, Bristow KL (1995) Soil surface heat flux: some general questions and comments on measurements. Agric For Meteorol 75:43–50CrossRefGoogle Scholar
  21. Papale D, Reichstein M, Aubinet M et al (2006) Towards a standardized processing of Net ecosystem exchange measured with eddy covariance technique: algorithms and uncertainty estimation. Biogeosciences 3:571–583CrossRefGoogle Scholar
  22. Peichl M, Arain MA (2007) Allometry and partitioning of above and below ground tree biomass in an age-sequence of white pine forests. For Ecol Manag 253:68–80CrossRefGoogle Scholar
  23. Prichard TL Document.~Soil moisture measurement technology. http://ceeldorado.ucdavis.edu/files/45069.pdf
  24. Raupach MR (1979) Anomalies in flux-gradient relationships over forests. Bound Layer Meteorol 16:467–486CrossRefGoogle Scholar
  25. Risk D, Kellman L, Beltrami H (2002) Carbon dioxide in soil profiles: production and temperature dependence. Geophys Res Lett 29(6):1029–2001CrossRefGoogle Scholar
  26. Running SW, Baldocchi DD, Turner D et al (1999) A global terrestrial monitoring network, scaling tower fluxes with ecosystem modelling and EOS satellite data. Remote Sens Environ 70:108–127CrossRefGoogle Scholar
  27. Tang J, Baldocchi DD, Qi Y et al (2003) Assessing soil CO2 efflux using continuous measurements of CO2 profiles in soils with small solid-state sensors. Agric For Meteorol 118:207–220CrossRefGoogle Scholar
  28. Valentini R (2003) An integrated network for studying the long-term responses of biospheric exchanges of carbon, water and energy of European forests. Ecol Stud 163:1–8Google Scholar
  29. Valentini R, Matteucci G, Dolman AJ et al (2000) Respiration as the main determinant of carbon balance in European forests. Nature 404:861–864CrossRefGoogle Scholar
  30. Van Laar A, Akça A (2007) Tree volume tables and equation. In: Managing forest ecosystems, forest mensuration. Springer Edition, DordrechtGoogle Scholar
  31. Wang W-M, Li Z-L, Su H-B (2007) Comparison of leaf angle distribution functions: effects on extinction coefficient and fraction of sunlit foliage. Agric For Meteorol 143(1–2):106–122CrossRefGoogle Scholar
  32. Widlowski J-L (2010) On the bias of instantaneous FAPAR estimates in open-canopy forests. Agric For Meteorol 150:1501–15022CrossRefGoogle Scholar
  33. Xu L-K, Matista AA, Hsiao TC (1999) A technique for measuring CO2 and water vapour profiles within and above plant canopies over short periods. Agric For Meteorol 94:1–12CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.INRA, UMR1137 Ecologie et Ecophysiologie Forestières, Centre de NancyChampenouxFrance

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