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Title: Influence of tree spatial pattern and sample plot type and size on inventory

Author: Berrill, John-Pascall; O'Hara, Kevin L.;

Date: 2012

Source: In: Standiford, Richard B.; Weller, Theodore J.; Piirto, Douglas D.; Stuart, John D., tech. coords. Proceedings of coast redwood forests in a changing California: a symposium for scientists and managers. Gen. Tech. Rep. PSW-GTR-238. Albany, CA: Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture: 485-497

Publication Series: General Technical Report (GTR)

   Note: This article is part of a larger document. View the larger document

Description: Sampling with different plot types and sizes was simulated using tree location maps and data collected in three even-aged coast redwood (Sequoia sempervirens) stands selected to represent uniform, random, and clumped spatial patterns of tree locations. Fixed-radius circular plots, belt transects, and variable-radius plots were installed by simulation. Bootstrap sample means, coefficient of variation (CV), and 95 percent confidence intervals were calculated for sample estimates of eight important stand parameters. Percent CV models depicted sample precision and enable calculation of minimum sample size for forest inventories. Precision differed between stand parameters e.g., dominant height and mean top height estimates were most precise; in many cases four times as precise as density estimates. Precision was affected more by spatial pattern than plot type, and generally ranked: uniform > random >> clumped. Density, average diameter, and average height estimate precision was especially sensitive to spatial pattern, and generally poorer in variable-radius plots. However, variable-radius plots generally produced the most precise estimates of basal area, volume, and leaf area index. Quantitative descriptions of sample stand structure and spatial pattern provide a basis for comparison or application of results to other forests with similar characteristics.

Keywords: bootstrap confidence intervals, coefficient of variation, precision, Ripley's K, sampling simulation, Sequoia sempervirens

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Berrill, John-Pascall; O'Hara, Kevin L. 2012. Influence of tree spatial pattern and sample plot type and size on inventory. In: Standiford, Richard B.; Weller, Theodore J.; Piirto, Douglas D.; Stuart, John D., tech. coords. Proceedings of coast redwood forests in a changing California: a symposium for scientists and managers. Gen. Tech. Rep. PSW-GTR-238. Albany, CA: Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture: 485-497.

 


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