Plant Structure-Function Relationships and Woody Tissue Respiration: Upscaling to Forests from Laser-Derived Measurements

  • Patrick MeirEmail author
  • Alexander Shenkin
  • Mathias Disney
  • Lucy Rowland
  • Yadvinder Malhi
  • Martin Herold
  • Antonio C. L. da Costa
Part of the Advances in Photosynthesis and Respiration book series (AIPH, volume 43)


Land surface processes dominate the observed global signal of large inter-annual variability in the global carbon cycle , and this signal is itself dominated by responses of tropical forests to climatic variation and extremes. However, our understanding of the functioning of these forests is poorly constrained, not least in terms of the size and climate-sensitivity of gross ecosystem respiratory CO2 emission. Woody tissue CO2 effluxes contribute substantially to gross ecosystem CO2 emissions, thereby influencing the net ecosystem exchange of carbon. Our ability to estimate this component of the forest respiration budget has been limited by our technical capacity to measure vegetation size and structure in sufficient detail and at sufficient scale. The outcome has been to leave large uncertainties in land-surface model performance and prediction. A key challenge in estimating woody tissue CO2 efflux for the ecosystem has been the scaling of measurements made with chambers from the level of an organ to the stand. Appropriate scalars such as woody tissue mass, surface area and volume all require accurate structural information on both size and pattern. For individual trees, pattern is dominated by branching structure and this fundamentally determines how trees partition resources to address the trade-offs inherent in the simultaneous maintenance of structural integrity and metabolism. The detailed structural information needed to address this challenge has until recently been extremely scarce because of the difficulty of acquiring it, even for a single large tree. Recent developments in terrestrial light detection and ranging (LiDAR) technology have made possible a step change in our ability to quantify and describe tree form for continuous forest, for example describing hundreds of adjacent trees at the hectare scale. Connecting this new capability with tree physiology and fundamental theories of plant structure and metabolism offers to change the way we understand plant functional biology and its variation with environment, biogeography and phylogeny.



PM gratefully acknowledges support from ARC DP170104091, LBA/457914/2013-0/MCTI/CNPq and NERC NE/J011002/1. We thank the Museu Paraense Emílio Goeldi in Belém, Pará, Brazil for generous long-term provision of field-site access (Fig. 5.4). Many thanks also to Jose Gonzalez’ for his contributions to TLS data analysis.


  1. Amthor JS (1989) Respiration and crop productivity. Springer-Verlag, BerlinCrossRefGoogle Scholar
  2. Anderegg WRL, Ballantyne AP, Smith WK, Majkut J, Rabin S, Beaulieu C et al (2015) Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink. Proc Natl Acad Sci U S A 12:15591–15596Google Scholar
  3. Anderson-Teixeira KJ, Wang MMH, McGarvey JC, LeBauer DS (2016) Carbon dynamics of mature and regrowth tropical forests derived from a pantropical database (TropForC-db). Glob Chang Biol 22:1690–1709CrossRefPubMedGoogle Scholar
  4. Angert A, Muhr J, Juarez RN, Muñoz WA, Kraemer G, Santillan JR et al (2012) Internal respiration of Amazon tree stems greatly exceeds external CO2 efflux. Biogeosciences 9:4979–4991CrossRefGoogle Scholar
  5. Atkin OK, Bloomfield KJ, Reich PB, Tjoelker MG, Asner GP, Bonal D et al (2015) Global variability in leaf respiration in relation to climate, plant functional types and leaf traits. New Phytol 206:614–636CrossRefPubMedGoogle Scholar
  6. Beer C, Reichstein M, Tomoelleri E, Ciais P, Jung M, Carvalhais N et al (2010) Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329:834–838CrossRefPubMedGoogle Scholar
  7. Bentley LP, Stegen JC, Savage VM, Smith DD, von Allmen E, Sperry JS, Reich PB, Enquist BJ (2013) An empirical assessment of tree branching networks and implications for plant allometric scaling models. Ecol Lett 16:1069–1078CrossRefPubMedGoogle Scholar
  8. Betts RA, Jones CD, Knight JR, Keeling RF, Kennedy JJ (2016) El Nino and a record CO2 rise. Nat Clim Chang 6:806–810CrossRefGoogle Scholar
  9. Brummer AB, Savage VM, Enquist BJ (2017) A general model for metabolic scaling in self-similar asymmetric networks. PLoS Comput Biol 13(3):e1005394CrossRefPubMedPubMedCentralGoogle Scholar
  10. Bužková R, Acosta M, Dařenová E, Pokorný R, Pavelka M (2015) Environmental factors influencing the relationship between stem CO2 efflux and sap flow. Trees 29:333–343CrossRefGoogle Scholar
  11. Calders K, Newnham G, Burt A, Murphy S, Raumonen P, Herold M et al (2015) Non-destructive estimates of above-ground biomass using terrestrial laser scanning. Methods Ecol Evol 6:198–208CrossRefGoogle Scholar
  12. Campioli M, Malhi Y, Vicca S, Luyssaert S, Papale D, Penuelas J et al (2016) Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests. Nat Commun 7:13717CrossRefPubMedPubMedCentralGoogle Scholar
  13. Carlquist S (2001) Comparative wood anatomy: systematic, ecological, and evolutionary aspects of dicotyledon wood, 2nd edn. Springer, Berlin/HeidelbergCrossRefGoogle Scholar
  14. Cavaleri MA, Oberbauer SF, Ryan MG (2006) Wood CO2 efflux in a primary tropical rain forest. Glob Chang Biol 12:2442–2458CrossRefGoogle Scholar
  15. Chambers JQ, Tribuzy ES, Toledo LC, Crispim BF, Higuchi N, dos Santos J et al (2004) Respiration from a tropical forest ecosystem: partitioning of sources and low carbon use efficiency. Ecol Appl 14:73–84CrossRefGoogle Scholar
  16. Chave J, Réjou-Méchain M, Burquez A, Chidumayo E, Colgan MS, Delitti WBC et al (2014) Improved allometric models to estimate the aboveground biomass of tropical trees. Glob Chang Biol 20:3177–3190CrossRefPubMedGoogle Scholar
  17. Cleveland CC, Taylor P, Chadwick KD, Dahlin K, Doughty CE, Malhi Y et al (2015) A comparison of plot-based satellite and Earth system model estimates of tropical forest net primary production. Glob Biogeochem Cycles 29:626–644CrossRefGoogle Scholar
  18. Corner EJH (1964) The life of plants. University of Chicago Press, ChicagoGoogle Scholar
  19. Da Costa ACL, Galbraith D, Almeida S, Portela BTT, da Costa M, Silva JD et al (2010) Effect of 7 years of experimental drought on vegetation dynamics and biomass storage of an eastern Amazonian rainforest. New Phytol 187:579–591CrossRefPubMedGoogle Scholar
  20. De Pury DGG, Farquhar GD (1997) Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models. Plant Cell Environ 20:537–557CrossRefGoogle Scholar
  21. Disney M, Burt A, Lewis S, Calders K, Armston, J, Bartholomeus H,…, Wilkes P (2017) Significant upward revision of tropical forest carbon stocks via new laser-based methods. Nature Communications, in reviewGoogle Scholar
  22. Domingues TF, Meir P, Feldpausch TR, Saiz G, Veenendaal EM, Schrodt F et al (2010) Co-limitation of photosynthetic capacity by nitrogen and phosphorus in West Africa woodlands. Plant Cell Environ 33:959–980CrossRefPubMedGoogle Scholar
  23. Doughty CE, Metcalfe DB, Girardin CAJ, Amezquita FF, Galiano D, Huaraca Huasco W et al (2015) Impact of drought on Amazonian carbon dynamics and fluxes. Nature 519:7541CrossRefGoogle Scholar
  24. Enquist BJ, Kerkhoff AJ, Stark SC, Swenson NG, McCarthy MC, Price CA (2007) A general integrative model for scaling plant growth, carbon flux, and functional trait spectra. Nature 449:218–222CrossRefPubMedGoogle Scholar
  25. Evans MR (2012) Modelling ecological systems in a changing world. Philos Trans R Soc B 367:181–190CrossRefGoogle Scholar
  26. Evans MR, Norris KJ, Benton TG (2012) Predictive ecology: systems approaches. Philos Trans R Soc B 367:163–169CrossRefGoogle Scholar
  27. Farnsworth KD, Niklas KJ (1995) Theories of optimisation, form and function in branching architecture in plants. Funct Ecol 9:355–363CrossRefGoogle Scholar
  28. Feldpausch TR, Banin L, Phillips OL, Baker TR, Lewis SL, Quesada CA et al (2010) Height-diameter allometry of tropical forest trees. Biogeosci Discuss 7:7727–7793CrossRefGoogle Scholar
  29. Field CB, Mooney HA (1986) The photosynthesis-nitrogen relationship in wild plants. In: Givnish TJ (ed) The economy of plant form and function. Cambridge University Press, Cambridge, pp 25–55Google Scholar
  30. Foote KC, Schaedle M (1978) The contribution of aspen bark photosynthesis to the energy balance of the stem. For Sci 24:569–573Google Scholar
  31. Gonzalez de Tanago GJ, Lau A, Bartholomeus H, Herold M, Avitabile V, Raumonen P, …, Calders K (2017) Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR. Method Ecol Evol (in Press)Google Scholar
  32. Goodman RC, Phillips OL, Baker TR (2014) The importance of crown dimensions to improve tropical tree biomass estimates. Ecol Appl 24:680–698CrossRefPubMedGoogle Scholar
  33. Hallé F, Oldeman RAA, Tomlinson PB (1978) Tropical trees and forests: an architectural analysis. Springer-Verlag, New YorkCrossRefGoogle Scholar
  34. Hollinger DY (1996) Optimality and nitrogen allocation in a tree canopy. Tree Physiol 16:627–634CrossRefPubMedGoogle Scholar
  35. Hutchinson GL, Livingston GP (1993) Use of chamber systems to measure trace gas fluxes. In: Harper LA, Mosier AR, Duxbury JM, Rolston DE (eds) Agricultural ecosystem effects on trace gases and global climate change. ASA Special Publication 55. Soil Science Society of America, Town, pp 63–78Google Scholar
  36. Huntingford C, Lowe JA, Booth BBB, Jones CD, Harris GR, Meir P (2009) Implications of thermal and carbon cycle uncertainty for future climate projections. Tellus Ser B Chem Phys Meteorol 61:355–360CrossRefGoogle Scholar
  37. Jung M, Reichstein M, Schwalm CR, Huntingford C, Sitch S, Ahlström A et al (2017) Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature 541:516–520CrossRefPubMedGoogle Scholar
  38. Katayama A, Kume T, Komatsu H, Ohashi M, Matsumoto K, Ichihashi R, Kumagai T, Otsuki K (2014) Vertical variations in wood CO2 efflux for live emergent trees in a Bornean tropical rainforest. Tree Physiol 34:503–512CrossRefPubMedGoogle Scholar
  39. Kramer PJ, Kozlowski TT (1979) Physiology of woody plants. Academic Press, Inc., New YorkGoogle Scholar
  40. Kull O, Broadmeadow M, Kruijt B, Meir P (1999) Light distribution and foliage structure in an oak canopy. Trees 14:55–64Google Scholar
  41. Kunert N, Edinger J (2015) Xylem sap flux affects conventional stem CO2 efflux measurements in tropical trees. Biotropica 47:650–653Google Scholar
  42. Le Quéré C, Peters GP, Andres RJ, Andrew RM, Boden TA, Ciais P et al (2014) Global Carbon Budget 2014. Earth Syst Sci Data 7:521–610CrossRefGoogle Scholar
  43. Levy PE, Jarvis PG (1998) Stem CO2 fluxes in two Sahelian shrub species (Guiera senegalensis and Combretum micranthum). Funct Ecol 12:107–116CrossRefGoogle Scholar
  44. Levy PE, Meir P, Allen SJ, Jarvis PG (1999) The effect of aqueous transport of CO2 in xylem sap on gas exchange in woody plants. Tree Physiol 19:53–59CrossRefPubMedGoogle Scholar
  45. Lin Y, Herold M (2016) Tree species classification based on explicit tree structure feature parameters derived from static terrestrial laser scanning data. Agric For Meteorol 216:105–114CrossRefGoogle Scholar
  46. Lloyd J, Patino S, Paiva RQ, Nardoto GB, Quesada CA, Santos AJB et al (2010) Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees. Biogeosciences 7:1833–1859CrossRefGoogle Scholar
  47. Malhi Y, Doughty CE, Goldsmith GR, Metcalfe DB, Girardin CAJ, Marthews TR et al (2015) The linkages between photosynthesis, productivity, growth and biomass in lowland Amazonian forests. Glob Chang Biol 21:2283–2295CrossRefPubMedGoogle Scholar
  48. McWilliam ALC, Roberts JM, Cabral OMR, Leitao MVBR, de Costa ACL, Maitelli GT, Zamparoni CAGP (1993) Leaf area index and above-ground biomass of terra firme rain forest and adjacent clearings in Amazonia. Funct Ecol 7:310–317CrossRefGoogle Scholar
  49. Medlyn BE, Zaehle S, De Kauwe MG, Walker AP, Dietze MC, Hanson PJ et al (2015) Using ecosystem experiments to improve vegetation models. Nat Clim Chang 5:528–534CrossRefGoogle Scholar
  50. Meir P, Grace J (2002) Scaling relationships for woody tissue respiration in two tropical rain forests. Plant Cell Environ 25:963–973CrossRefGoogle Scholar
  51. Meir P, Grace J, Miranda AC (2001) Leaf respiration in two tropical rain forests: constraints on physiology by phosphorus, nitrogen, and temperature. Funct Ecol 15:378–387CrossRefGoogle Scholar
  52. Meir P, Kruijt B, Broadmeadow M, Kull O, Carswell F, Nobre A, Jarvis PG (2002) Acclimation of photosynthetic capacity to irradiance in tree canopies in relation to leaf nitrogen concentration and leaf mass per unit area. Plant Cell Environ 25:343–357CrossRefGoogle Scholar
  53. Metcalfe DB, Meir P, Aragao L, Lobo-do-Vale R, Galbraith D, Fisher RA et al (2010) Shifts in plant respiration and carbon use efficiency at a large-scale drought experiment in the eastern Amazon. New Phytol 187:608–621CrossRefPubMedGoogle Scholar
  54. Mori S, Yamaji K, Ishida A, Prokushkin SG, Masyagina OV, Hagihara A et al (2010) Mixed-power scaling of whole-plant respiration from seedlings to giant trees. Proc Natl Acad Sci U S A 107:1447–1451CrossRefPubMedPubMedCentralGoogle Scholar
  55. Niklas KJ (1994) Size-dependent variations in plant growth rates and the “3/4-power rule”. Am J Bot 81:134–145CrossRefGoogle Scholar
  56. Ometto JP, Aguiar AP, Assis T, Soler L, Valle P, Tejada G, Lapola DM, Meir P (2014) Amazon forest biomass density maps: tackling the uncertainty in carbon emission estimates. Clim Chang 124:545–560CrossRefGoogle Scholar
  57. Patiño S, Lloyd J, Paiva R, Baker TR, Quesada CA, Mercado LM et al (2009) Branch xylem density variations across the Amazon Basin. Biogeosciences 6:545–568CrossRefGoogle Scholar
  58. Raumonen P, Kaasalainen M, Akerblom M, Kaasalainen S, Kaartinen H, Vastaranta M et al (2013) Fast automatic precision tree models from terrestrial laser scanner data from terrestrial laser scanner data. Remote Sens 5:491–520CrossRefGoogle Scholar
  59. Reich PB, Tjoelker MG, Machado JL, Oleksyn J (2006) Universal scaling of respiratory metabolism, size and nitrogen in plants. Nature 439:457–461CrossRefPubMedGoogle Scholar
  60. Rowland L, Zaragoza-Castells J, Bloomfield KJ, Turnbull MH, Bonal D, Burban B et al (2016) Scaling leaf respiration with nitrogen and phosphorus in tropical forests across two continents. New Phytol 214:1064–1077CrossRefPubMedPubMedCentralGoogle Scholar
  61. Ryan MG, Hubbard RM, Clark DA, Sanford RL (1994) Woody-tissue respiration for Simarouba amara and Minquartia guianensis, two tropical wet forest species with different growth habits. Oecologia 100:213–220CrossRefPubMedGoogle Scholar
  62. Ryan MG, Lavigne MB, Gower ST (1997) Annual carbon balance cost of autotrophic respiration in boreal forest ecosystemsin relation to species and climate. J Geophys Res 102:28871–28883CrossRefGoogle Scholar
  63. Sellers PJ, Berry JA, Collatz GJ, Field CB, Hall FG (1992) Canopy reflectance, photosynthesis, and transpiration. 3. A reanalysis using improved leaf models and a new canopy integration scheme. Remote Sens Environ 42:187–216CrossRefGoogle Scholar
  64. Sprugel DG (1990) Components of woody-tissue respiration in young Abies amabilis trees. Trees 4:88–98CrossRefGoogle Scholar
  65. Sprugel DG, Benecke U (1991) Measuring woody-tissue respiration and photosynthesis. In: Lassoie JP, Hinckley TM (eds) Techniques and approaches in forest tree ecophysiology. CRC Press, Berlin, pp 329–355Google Scholar
  66. Teskey RO, McGuire MA (2007) Measurement of stem respiration of sycamore (Platanus occidentalis L.) trees involves internal and external fluxes of CO2 and possible transport of CO2 from roots. Plant Cell Environ 30:570–579CrossRefPubMedGoogle Scholar
  67. Thompson DW (1917) On growth and form. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  68. Von Allmen EI, Sperry JS, Smith DD, Savage VM, Enquist BJ, Reich PB et al (2012) A species’ specific model of the hydraulic and metabolic allometry of trees II: testing predictions of water use and growth scaling in ring- and diffuse-porous species. Funct Ecol 26:1066–1076CrossRefGoogle Scholar
  69. Wang W, Ciais P, Nemani RR, Canadell JG, Piao S, Sitch S et al (2013) Variations in atmospheric CO2 growth rates coupled with tropical temperature. Proc Natl Acad Sci U S A 110:13061–13066CrossRefPubMedPubMedCentralGoogle Scholar
  70. West GB, Brown JH, Enquist BJ (1997) A general model for the origin of allometric scaling laws in biology. Science 276:122–126CrossRefPubMedGoogle Scholar
  71. Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F et al (2004) The worldwide leaf economics spectrum. Nature 428:821–827CrossRefPubMedGoogle Scholar
  72. Yoda K (1983) Community respiration in a lowland rain forest in Pasoh, peninsular Malaysia. Jpn J Ecol 33:183–197Google Scholar
  73. Yoda K, Shinozaki K, Ogawa H, Hozumi K, Kira T (1965) Estimation of the total amount of respiration in woody organs of trees and forest communities. J Biol Osaka City U 16:15–26Google Scholar
  74. Yoneda T (1993) Surface area of woody organs of an evergreen broadleaf forest tree in Japan Southeast Asia. J Plant Res 106:229–237CrossRefGoogle Scholar
  75. Zelawski W, Riech FP, Stanley RG (1970) Assimilation and release of internal carbon dioxide by woody plant shoots. Can J Bot 48:1351–1354CrossRefGoogle Scholar
  76. Ziemińska K, Butler DW, Gleason SM, Wright IJ, Westoby M (2013) Fibre wall and lumen fractions drive wood density variation across 24 Australian angiosperms. AoB Plants 5:plt046. CrossRefPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Patrick Meir
    • 1
    • 2
    Email author
  • Alexander Shenkin
    • 3
  • Mathias Disney
    • 4
    • 5
  • Lucy Rowland
    • 6
  • Yadvinder Malhi
    • 7
  • Martin Herold
    • 8
  • Antonio C. L. da Costa
    • 9
  1. 1.Research School of BiologyAustralian National UniversityCanberraAustralia
  2. 2.School of GeosciencesUniversity of EdinburghEdinburghUK
  3. 3.School of Geography and the EnvironmentUniversity of OxfordOxfordUK
  4. 4.Department of GeographyUniversity College LondonLondonUK
  5. 5.NERC National Centre for Earth ObservationLeicesterUK
  6. 6.Department of Geography, College of Life and Environmental SciencesUniversity of ExeterExeterUK
  7. 7.School of Geography and the EnvironmentUniversity of OxfordOxfordUK
  8. 8.Department of Environmental SciencesWageningen UniversityWageningenThe Netherlands
  9. 9.Instituto de GeociênciasFederal University of ParáBelémBrazil

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