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Procedures to Handle Inventory Cluster Plots that Straddle Two or More Conditions

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We review the relative merits and field procedures for four basic plot designs to handle forest inventory plots that straddle two or more conditions, given that subplots will not be moved. A cluster design is recommended that combines fixed-area subplots and variable-radius plot (VRP) sampling. Each subplot in a cluster consists of a large fixed-area subplot for estimating area and tallying large trees, a microplot (small fixed-area subplot) for tallying small trees, and a variable-radius plot for tallying intermediate size trees. Subplots are assigned a condition class based on a classification algorithm. For subplots that straddle conditions, boundaries are mapped for area estimation, and the condition class of each tree is recorded. For some straddler subplots, there may be insufficient trees for specific conditions to allow unambiguous classification by computer algorithm. We discuss several possible solutions for this problem. For. Sci. Monogr. 31:12-25.

Keywords: Forest Inventory and Analysis; cluster sample; edge effect; forest survey; national forest inventories

Document Type: Journal Article

Affiliations: Research Forester, USDA Forest Service Southern Forest Experiment Station, Asheville, NC

Publication date: August 1, 1995

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.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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