Analysis of wood density profiles of tree stems: incorporating vertical variations to optimize wood sampling strategies for density and biomass estimations
- 582 Downloads
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.
KeywordsWood density Biomass estimation Sampling strategy Wiemann approximation Subtropical China Approximation point
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.
- Akca A, van Laar A (2007) Forest Mensuration. Springer, BerlinGoogle 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 20:165–169Google Scholar
- Guo WF (2009) An analysis of relationship between growth and site condition of Mytilaria laosensis plantation. For Res 22:835–839Google 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 2007–02Google Scholar
- 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 4:150Google 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 40:673Google Scholar
- Reyes G, Brown S, Chapman J, Lugo AE (1992) Wood densities of tropical tree species. USDA For Serv GTR-S0-88Google Scholar
- 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 87–117Google Scholar
- Sein CC, Mitlöhner R (2011) Erythrophleum fordii Oliver: ecology and silviculture. CIFOR, BogorGoogle Scholar
- Wiemann MC, Williamson GB (1988) Extreme Radial Changes in Wood Specific Gravity in Some Tropical Pioneers. Wood Fiber Sci 20:344–349Google Scholar
- Wiemann MC, Williamson GB (2012) Testing a novel method to approximate wood specific gravity of trees. For Sci 58:577–591Google Scholar
- Wiemann MC, Williamson GB (2013) Biomass determination using wood specific gravity from increment cores. USDA For Serv FPL-GTR-225Google 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: http://hdl.handle.net/10255/dryad.235
- 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 6:387–394Google Scholar