Sampling Strategies for Efficient Estimation of Tree Foliage Biomass
Conifer crowns can be highly variable both within and between trees, particularly with respect to foliage biomass and leaf area. A variety of sampling schemes have been used to estimate biomass and leaf area at the individual tree and stand scales. Rarely has the effectiveness of these sampling schemes been compared across stands or even across species. In addition, sample size estimates for achieving a certain level of precision have rarely been given. This simulation study used extensive branch and tree foliage biomass data sets for Douglas-fir (
menziesii var. menziesii [Mirb.] Franco) and ponderosa pine ( Pinus ponderosa Dougl ex. Laws.) to compare alternative sampling schemes and sample sizes. The use of auxiliary information at the estimation
phase resulted in a more cost-efficient sampling scheme than when auxiliary information was used at the design phase. However, using auxiliary information at the design phase resulted in more precise estimates than using the same at the estimation phase for the same sample size. For both species,
systematic sampling with ratio estimation provided the most efficient estimate of individual tree foliage biomass. In Douglas-fir, stratifying by branch type (i.e., whorl versus interwhorl) resulted in a marginal gain in precision. For Douglas-fir, on average, root mean square error decreased
by 43.1% when sample size increased from 6 to 12 branches per tree, with a further decrease of 24.3% when sample size increased from 12 to 18 branches per tree. For ponderosa pine, on average, the root mean square error decreased by 44.4 and 23.9% when the sample size was increased from 6
to 12 and from 12 to 18 branches per tree, respectively. Additional work is needed to understand the appropriate sampling techniques for older conifer tree crowns and sampling multileader deciduous crowns.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
Document Type: Research Article
Publication date: 2011-04-01
More about this publication?
- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2016 Impact Factor: 1.782 (Rank 17/64 in forestry)
Average time from submission to first decision: 62.5 days*
June 1, 2016 to Feb. 28, 2017
Also published by SAF:
Journal of Forestry
Other SAF Publications
- Submit a Paper
- Membership Information
- Author Guidelines
- Ingenta Connect is not responsible for the content or availability of external websites