Precision of Density Estimates from Fixed-Radius Plots Compared to N-Tree Distance Sampling
Abstract:We computed and compared the statistical properties of the estimators for the number of trees/ha (density) for fixed-radius plot and n-tree distance sampling. In forests with random spatial patterns, n-tree distance sampling density estimators are at least as precise as those of plot sampling if the fixed-radius plot size is less than the ratio of (n - 2) and the expected density, where n is the number of trees included at an n-tree location. A similar result holds for the clustered forest, where the ratio is multiplied by a factor involving a constant of heterogeneity. If the expected number of trees per plot and the plot sizes are the same for both the random and clustered spatial patterns, the variance of the plot sampling density estimator for the clustered pattern will always be greater than for that of the random spatial pattern. FOR. SCI. 48(1):1–6.
Keywords: Density-adapted sampling; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resource management; natural resources; spatial pattern
Document Type: Miscellaneous
Affiliations: 1: Associate Professor Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, 49931, Phone: (906) 487-3044 firstname.lastname@example.org 2: Professor School of Forestry and Wood Products, Michigan Technological University, Houghton, MI, 49931, Phone (906) 487-2886 email@example.com
Publication date: 2002-02-01
- 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.
2015 Impact Factor: 1.702
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