Skip to main content
Log in

Analysis of wood density profiles of tree stems: incorporating vertical variations to optimize wood sampling strategies for density and biomass estimations

  • Original Paper
  • Published:
Trees Aims and scope Submit manuscript


Key message

Strategies for sampling trees for wood density must consider within-tree variations of density; theoretically and empirically developed sampling strategies can lead to accurate estimations of mean density.


Wood density is a highly variable functional trait of trees with large differences occurring between species as well as between and within trees of a given species, which is a potential source of uncertainty in forest biomass estimations. Because of the within-tree variation, sampling trees for density in certain locations within the bole (e.g., breast height) can be biased. This study is an attempt to develop and test sampling strategies that yield more representative estimates of whole-tree density by incorporating information on radial and vertical density variations. In this study, 76 trees of 6 tree species from China and Germany were destructively sampled and analyzed for radial and vertical density profiles. The species exhibit different patterns and magnitudes in their density variations. Theoretical approximation points for linear radial and vertical density trends were derived mathematically. The best sampling position was found to be at 1/3 of the tree height and at 2/3 of the radial distance from pith to bark (“strategy 2”). Different sampling strategies as estimators for the mean wood density of the species were simulated, tested and compared. Strategy 2 yielded the best estimates of wood density, while BH (breast height) increment core density at 2/3 radial distance (Wiemann approximation) and BH increment core mean density were slightly less accurate. Sampling-based estimates reduced uncertainty about 5 % relative to database estimates. As a more feasible alternative to strategy 2, adapted sampling strategies based on increment cores at breast height could be developed empirically for the six species.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others


  • Akca A, van Laar A (2007) Forest Mensuration. Springer, Berlin

    Google Scholar 

  • Cai DX, Jia HY, Lu LH, Guo WF, Zhang W (2007) On large-size timber plantation forestry of valuable hardwood species in warm sub-tropical areas of China. For Res 20:165–169

    Google Scholar 

  • Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D et al (2005) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145:87–99

    Article  CAS  PubMed  Google Scholar 

  • Deng XW, Zhang LY, Lei PF, Xiang WH, Yan WD (2014) Variations of wood basic density with tree age and social classes in the axial direction within Pinus massoniana stems in Southern China. Ann For Sci 71:1–12

    Article  Google Scholar 

  • Edmonds JM, Staniforth M (1998) Plate 348. Toona sinensis. Curtis’s Bot Mag 15:186–193. doi:10.1111/1467-8748.00169

    Article  Google Scholar 

  • Guo WF (2009) An analysis of relationship between growth and site condition of Mytilaria laosensis plantation. For Res 22:835–839

    Google Scholar 

  • Hacke U, Sperry J, Pockman W, Davis S, McCulloh K (2001) Trends in wood density and structure are linked to prevention of xylem implosion by negative pressure. Oecologia 126:457–461. doi:10.1007/s004420100628

    Article  Google Scholar 

  • Henry M, Besnard A, Asante WA, Eshun J, Adu-Bredu S, Valentini R, Bernoux M, Saint-André L (2010) Wood density, phytomass variations within and among trees, and allometric equations in a tropical rainforest of Africa. For Ecol Manag 260:1375–1388

    Article  Google Scholar 

  • Ketterings QM, Coe R, van Noordwijk M, Ambagau Y, Palm CA (2001) Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For Ecol Manag 146:199–209

    Article  Google Scholar 

  • Liu SS, Ye YC, Zhu JY, Lu HR, Li NS, Mo ZQ (2007) Early growth performance of 17 broadleaved tree species in degraded Pinus massoniana forest. Guangdong For Sci Technol 2007–02

  • Maniatis D, Saint André L, Temmerman M, Malhi Y, Beeckman H (2011) The potential of using xylarium wood samples for wood density calculations: a comparison of approaches for volume measurement. iForest 4:150

  • Niklas K, Spatz H (2010) Worldwide correlations of mechanical properties and green wood density. Am J Bot 97:1587–1594. doi:10.3732/ajb.1000150

    Article  PubMed  Google Scholar 

  • Nogueira E, Nelson B, Fearnside P (2005) Wood density in dense forest in central Amazonia, Brazil. For Ecol Manag 208:261–286. doi:10.1016/j.foreco.2004.12.007

    Article  Google Scholar 

  • Nogueira E, Fearnside P, Nelson B (2008) Normalization of wood density in biomass estimates of Amazon forests. For Ecol Manag 256:990–996. doi:10.1016/j.foreco.2008.06.001

    Article  Google Scholar 

  • Poorter L, Wright SJ, Paz H, Ackerly DD, Condit R et al (2008) Are functional traits good predictors of demographic rates? Evidence from five Neotropical forests. Ecology 89:1908–1920

    Article  CAS  PubMed  Google Scholar 

  • Raymond CA, MacDonald AC (1998) Where to shoot your pilodyn: within tree variation in basic density in plantation Eucalyptus globulus and E. nitens in Tasmania. New For 15:205–221

    Article  Google Scholar 

  • Raymond CA, Muneri A (2001) Non-destructive sampling of Eucalyptus globulus and E. nitens for wood properties. I. Basic density. Wood Sci Technol 35:27–39

    Article  CAS  Google Scholar 

  • Repola J (2006) Models for vertical wood density of Scots pine, Norway spruce and birch stems, and their application to determine average wood density. Silva Fenn 40:673

    Google Scholar 

  • Reyes G, Brown S, Chapman J, Lugo AE (1992) Wood densities of tropical tree species. USDA For Serv GTR-S0-88

  • Saranpää P (2003) Wood density and growth. In: Barnett JR, Jeronimidis G (eds) Wood quality and its biological basis. Blackwell Publishing and CRC Press, Oxford, pp 87–117

    Google Scholar 

  • Schinker M, Hansen N, Spiecker H (2003) High-frequency densitometry—a new method for the rapid evaluation of wood density variations. IAWA J 24:231–239

    Article  Google Scholar 

  • Sein CC, Mitlöhner R (2011) Erythrophleum fordii Oliver: ecology and silviculture. CIFOR, Bogor

    Google Scholar 

  • Wassenberg M, Montwé D, Kahle HP, Spiecker H (2014) Exploring High Frequency densitometry calibration functions for different tree species. Dendrochronologia 32:273–281. doi:10.1016/j.dendro.2014.07.001

    Article  Google Scholar 

  • Wiemann MC, Williamson GB (1988) Extreme Radial Changes in Wood Specific Gravity in Some Tropical Pioneers. Wood Fiber Sci 20:344–349

    Google Scholar 

  • Wiemann MC, Williamson GB (2012) Testing a novel method to approximate wood specific gravity of trees. For Sci 58:577–591

    Google Scholar 

  • Wiemann MC, Williamson GB (2013) Biomass determination using wood specific gravity from increment cores. USDA For Serv FPL-GTR-225

  • Williamson GB, Wiemann MC (2010) Measuring wood specific gravity… Correctly. Am J Bot 97:519–524. doi:10.3732/ajb.0900243

    Article  PubMed  Google Scholar 

  • Williamson GB, Wiemann MC (2011) Age versus size determination of radial variation in wood specific gravity: lessons from eccentrics. Trees Struct Funct 25:585–591

    Article  Google Scholar 

  • Woodcock D, Shier A (2002) Wood specific gravity and its radial variations: the many ways to make a tree. Trees Struct Funct 16:437–443. doi:10.1007/s00468.002.0173.7

    Article  Google Scholar 

  • Zanne AE, Lopez-Gonzalez G, Coomes DA, Ilic J, Jansen S, Lewis SL, Miller RB, Swenson NG, Wiemann MC, Chave J (2009) Global wood density database. Dryad. Identifier:

  • Zhang X, Zhao Y, Ashton MS, Lee X (2012a) Measuring Carbon in Forests. In: Ashton MS, Tyrrell ML, Spalding D, Gentry H (eds) Managing forest carbon in a changing climate. Springer, Berlin, pp 139–164

    Chapter  Google Scholar 

  • Zhang LY, Deng XW, Lei XD, Xiang WH, Peng CH, Lei PF, Yan WD (2012b) Determining stem biomass of Pinus massoniana L. through variations in basic density. Forestry 85:601–609. doi:10.1093/forestry/cps069

    Article  Google Scholar 

  • Zhou GX, Zhang BG, Lin L, Zhu Q, Guo L, Pu YY, Cao X (2010) Study on the relationship between Toona sinensis Roem stand productivity and site conditions in Sichuan Basin. Ecol Econ 6:387–394

    Google Scholar 

  • Zobel B, van Buijtenen J (1989) Wood variation. Its causes and control, Springer

    Book  Google Scholar 

Download references

Author contribution statement

MW wrote the manuscript with help and advice from HS, WG and HC, based on a pilot study done by HC. Data analysis was done by MW based on the work of HC. Field and lab work was mainly carried out by MW and HC with major support from WG. The study was conceived and planned by MW with help and advice from HS and WG.


The authors want to thank Ruyao Zhu, Felix Baab and Clemens Koch for their help with lab work, Andreas Dörr and Christopher Morhart for providing stem discs of 35 trees, and Dongjing Sun, Thaiza Pereira, Si Luo, Jan Hackenberg and Stephan Hoffmann for their help with field work. Special thanks go to Shirong Liu, Daoxiong Cai, Burkhard Steckel and Bastian Allmosloechner for making the field work possible. The comments of two anonymous reviewers helped to improve an earlier version of this manuscript. This research was supported by the Federal Ministry of Education and Research (BMBF), Germany, within the Sino-German project Lin2Value (No. 033L049A).

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Marc Wassenberg.

Additional information

Communicated by Y. Sano.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wassenberg, M., Chiu, HS., Guo, W. et al. Analysis of wood density profiles of tree stems: incorporating vertical variations to optimize wood sampling strategies for density and biomass estimations. Trees 29, 551–561 (2015).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: