8. Plot size, shape and point sampling

Anon. 1997. Area Sampling Frame Pilot Activity in Malawi- Final Report. Agricultural Assessments International Corporation. (available at http://ag.arizona.edu/OALS/malawi/Reports/ARIZFIN_252.html.)
Azuma- D.L.; Bednar L. 2002. A Method for Evaluating Fixed-Radius Plot Size When Sampling Western Juniper Seedlings and Saplings. In Western Journal of Applied Forestry, 17(4), 207-208. (available at Abstract: http://www.ingenta.com/isis/searching/ExpandTOC/ingenta?issue=infobike://saf/wjaf/2002/00000017/00000004&index=6&WebLogicSession=PhBjPgLHx0OMCKHVip11|4114063964735006182/-1052814329/6/7051/7051/7052/7052/7051/-1.)

This note outlines a method for evaluating plot size selection for an inventory of western juniper woodlands in eastern Oregon. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service in Portland, Oregon, used this method to evaluate several plot sizes to measure seedlings and saplings in the 1998 inventory of eastern Oregon. By choosing a 5 m radius plot, the probability of tallying no seedlings or saplings on four subplots is less than 10% for the three sample densities (0.01, 0.02, and 0.03 trees/m2) used (from Abstract)

Clark, Patrick E. & Seyfried, Mark S. 2001. Point Sampling for leaf area index in sagebrush steppe communities. In Journal of Range Management, 54, 589-594. (available at http://uvalde.tamu.edu/jrm/sep01/clark.htm.)

Leaf area index estimates obtained using different sampling pin inclinations or combinations of pin inclinations were evaluated in Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle and Young), low sagebrush (Artemisia arbuscula Nutt.), and mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana [Rydb.] Beetle) communities within the Reynolds Creek Experimental Watershed near Boise, Ida.

Gambill, Charles W.; Wiant, Harry V. & Yandle, David O. 1985. Optimum Plot Size and BAF. In Forest Science, the Society of American Foresters, Journal of Forest Science, 31 (3), 587-594.

A method is presented for determining the plot size or basal area factor (BAF) which minimizes total cruising time to provide estimates within a stated level of accuracy. Factors affecting the optimization of plot size or BAF are discussed

Gove, Jeffrey H. et al. 1999. Point Relascope Sampling of Downed Coarse Woody Debris. In Canadian Journal of Forest Research, 29 (11), 1718-1726. (available at Abstract: http://pubs.nrc-cnrc.gc.ca/cgi-bin/rp/rp2_abst_e?cjfr_x99-119_29_ns_nf_cjfr11-99.)

This paper presents a method based on angle-gauge sampling useful for inventorying downed coarse woody material in forest stands. The method is closely related to transect Relascope sampling, except that sample points are used rather than line transects. The estimators for the total and per unit area are given along with the estimators of their variances. Methods for handling both borderline material and boundary overlap situations are also presented.

Hahn, Jerold T.; MacLean, Colin d.; Arner, Stanford L. & Bechtold, William A. 1995. Procedures to Handle Inventory Cluster Plots that Straddle Two or More Conditions. In Supplement to Forest Science, Volume 41 (3). A publication of the Society of American Foresters, USA, 12-25.

It reviews the relative merits and field procedures for four basic plot designs to handle forest inventory plots that straddle two or more conditions. Given that sub-plots will not be moved. A cluster design is recommended that combines fixed-area subplots and area sub-plot for estimating area and tallying large tree, a microplot (small fixed-area subplot) for tallying small trees, and a variable-radius plot for tallying intermediate size subplots trees. Several possible solutions for the problem of straddling are discussed.

Lund, H. Gyde. 1982. Point sampling--the role in in-place resource inventories. In: Brann, Thomas B; House, Louis O.; Lund, H. Gyde, tech. coords. In-place resource inventories: principles and practices. Proceedings of a national workshop; 9-14 August 1981; Orono, ME. SAF 82-02. Bethesda, MD: Society of American Foresters; 79-84. Contributed paper. (available at http://greeningaustralia.org.au/tech_advice/tech_monitoring.html.)

Comment: Point sampling is quite frequently used as a means of obtaining area estimates and/or as a procedure for defining plot locations. The role point sampling plays in in-place resource inventories is not always fully understood, acknowledged, or appreciated.

Moisen, Gretchen G.; Stage, Albert R. & Born J. David. 1995. Point Sampling With Disjunct Support Near Population Boundaries. In Forest Science, Supplement to Volume 41 (3), A publication of the Journal of Forest Science, 62-82.

It�s dealt with the bias produced due to point substitution, and discusses about a rule which is developed for reshaping the pattern of support points that resolves the dilemma for single, straight boundaries. Simulations to evaluate the rule show that it produces a uniform density of points with respect to distance from the boundary while maintaining a compact region of support for the principal point.

Potts, Matthew D.; Plotkin, Joshua B.; Lee, Hua Seng; Manokaran, N; Ashton, Peter S. & Bossert, William H. 2001. Sampling Biodiversity: Effects of Plot Shape. In The Malaysian Forester, 64, 29-34.

This paper has concluded that for small plot sizes, plot shape and aspect ratio have no effect on biodiversity sampled. For large plot sizes (except for extreme aspect ratios) rectangular plots contains more species than L-shaped plots.

Ranneby, Bo. 1979. Model Studies of Shapes and Sizes of Tracts in Forest Survey. Department of Biometry and Forest Management, Swedish University of Agricultural Sciences, Sweden.

Analyze the results of some model studies of shape and sizes of tracts and the number of sample plots in the tracts.

Rennie, J.C.; Wood, G.B.; Schreuder, H.T. & Lund, H.G. 1991. Point-Model Based Sampling in Forestry: Principles and Practices. In Southern Journal of Applied Forestry, 15(3), 109-113. Peer reviewed.

Information needs, data collection technology, and public interest in management of federal lands are changing. As a result, federal agencies need to reexamine their resource inventories to see if they should take advantages of these new opportunities. Changes in information needs, technology, and public awareness are presented along with recommendations for future inventories.

Scott, Charles T. 1993. Optimal Design of a Plot Cluster for Monitoring. The optimal design of forest experiments and forest surveys, Sept 10-14. pp 233-242, School of Math, Statistics and Computing. Univ. of Greenwich, London.

The cost of traveling to sample location in extensive forest surveys makes cluster sampling a cost effective alternative. A method of determining the optimal cluster design when different method requires cost and variance relationship in order to develop an optimal design.

Spetich, Martin A. & Parker- George R. 1998. Plot Size Recommendations for Biomass Estimation in a Midwestern Old-Growth Forest. In Northern Journal of Applied Forestry, 15 (4), 165-168. (available at Abstract: http://www.safnet.org/pubs/northern/highlights98.htm#dec98.)

The relationship between disturbance regime and plot size for woody biomass estimation is examined in a Midwestern old-growth deciduous forest from 1926 to 1992.

Wang, Guangxing; Gertner, George; Xiao, Xiangyun; Wente, Steven & Anderson, Alan B. 2001. Appropriate Plot Size and Spatial Resolution for Mapping multiple Vegetation Types. In Photogrammetric Engineering & Remote Sensing, 67 (5), 575-584.

This paper presents a method to determine appropriate plot size and spatial resolution for mapping multiple vegetation types using remote sensing data for a large area. This method is based field data and geostatistics theory.

Zeide, Boris. 1980. Plot Size Optimization. In Forest Science, Vol. 26, No.2 Society of American Foresters, USA, 251-257.

The relationship between measurement time, travel time, and plot size are examined for simple random sampling and systematic sampling on a square lattice. The total time to estimate a stand variable within a desired level of accuracy is shown to be minimal if plot size is calculated from the formula P*=p(t/m)2

Zeide, Boris and Troxell, John K. 1979. Plot Versus Point Sampling. Forest Resource Inventories. Workshop Proceedings. Colorado State University, Fort Collins, July23-26, 1979. Volume II. 923-929pp, Colorado State University, Fort Collins.

This article aims to compare the times required to obtain the same accuracy in basal area with plot and point sampling. Though this problem has been widely discussed, the specific idea of the approach is a separate consideration of tow thing which are sometimes not distinguished in other studies 1) sampling efficiency and 2) time spent per tree.

Zeide, Boris; Troxell, John K. & Hag, David. 1979. Field Instruction in Point Sampling. Forest Resource Inventories. Workshop Proceedings. Colorado State University, Fort Collins, July23-26, 1979. Volume, II. 917-922pp, Colorado State University, Fort Collins.

This article describes the training method and field procedures of the point sampling.

last updated:  Monday, November 15, 2004