Available budgets for the inventory of non-commercial woodlands are small. Therefore, there has been increased interest in using distance methods, such as k-tree sampling, which are faster than fixed plot sampling. In low-density woodlands, large search areas for k nearest trees contradict any practical advantage over sampling with fixed area plots. Here, a modification of a k-tree sample plot with an empirical approach to estimating the number of trees per unit area in low-density woodlands is presented. The standard and modified k-tree sample plots have been tested in one actual and three simulated forests with different spatial patterns. The modified method was superior to other combinations of methods in terms of relative bias and relative efficiency. Considering statistical and practical aspects of sampling for tree density, the modified method is more promising than is the standard one.
Batcheler C.L., Craib D.G. (1985): A variable area plot method of assessment of forest condition and trend. New Zealand Journal of Forestry Science, 8: 83–95.
Byth Karen (1982): On Robust Distance-Based Intensity Estimators. Biometrics, 38, 127-
https://doi.org/10.2307/2530295
DIGGLE PETER J. (1977): A note on robust density estimation for spatial point patterns. Biometrika, 64, 91-95
https://doi.org/10.1093/biomet/64.1.91
Eberhardt L. L. (1967): Some Developments in 'Distance Sampling'. Biometrics, 23, 207-
https://doi.org/10.2307/2528156
Engeman Richard M., Sugihara Robert T., Pank Larry F., Dusenberry William E. (1994): A Comparison of Plotless Density Estimators Using Monte Carlo Simulation. Ecology, 75, 1769-1779
https://doi.org/10.2307/1939636
Haxtema Zane, Temesgen Hailemariam, Marquardt Theresa (2012): Evaluation of <I>n</I>-Tree Distance Sampling for Inventory of Headwater Riparian Forests of Western Oregon. Western Journal of Applied Forestry, 27, 109-117
https://doi.org/10.5849/wjaf.10-035
Kleinn C., Vilčko F. (2006a): A new empirical approach for estimation in k-tree sampling. Forest Ecology and Management, 237: 522–533.
Kleinn C., Vilčko F. (2006b): Design-unbiased estimation for point-to-tree distance sampling. Canadian Journal of Forest Research, 36: 1407–1414.
Lessard V.C., Drummer T.D., Reed D.D. (2002): Precision of density estimates from fixed-radius plots compared to
n-tree distance sampling. Forest Science, 48: 1–6.
Lynch Ann M (2003): Comparison of fixed-area plot designs for estimating stand characteristics and western spruce budworm damage in southwestern U.S.A. forests. Canadian Journal of Forest Research, 33, 1245-1255
https://doi.org/10.1139/x03-044
Magnussen S. (2016): A fixed count sampling estimator of stem density based on a survival function. Journal of Forest Science, 61, 485-495
https://doi.org/10.17221/46/2015-JFS
Magnussen Steen, Fehrman Lutz, Platt William J. (2012): An adaptive composite density estimator for k-tree sampling. European Journal of Forest Research, 131, 307-320
https://doi.org/10.1007/s10342-011-0502-8
Morisita M. (1957): A new method for the estimation of density by the spacing method applicable to non-randomly distributed populations. Physiology and Ecology Japan, 7: 134–144. (in Japanese)
Nothdurft Arne, Saborowski Joachim, Nuske Robert S., Stoyan Dietrich (2010): Density estimation based on
k -tree sampling and point pattern reconstruction. Canadian Journal of Forest Research, 40, 953-967
https://doi.org/10.1139/X10-046
Patil S. A., Kovner J. L., Burnham K. P. (1982): Optimum Nonparametric Estimation of Population Density Based on Ordered Distances. Biometrics, 38, 243-
https://doi.org/10.2307/2530307
Prodan M. (1968): Punktstichprobe für die Forsteinrichtung. Forst- und Holzwirt, 23: 225–226.
Sheil D., Ducey M.J., Sidiyasa K., Samsoedin I. (2003): A new type of sample unit for the efficient assessment of diverse tree communities in complex forest landscapes. Journal of Tropical Forest Science, 15: 117–135.
Stoyan D. (2006): Computer program STG 4.1: Stochastic geometry for Windows. Available at http://www.mathe.tu-freiberg.de/Stoyan/e-programm.html (accessed May 1, 2015).
Wiegert Richard G. (1962): The Selection of an Optimum Quadrat Size for Sampling the Standing Crop of Grasses and Forbs. Ecology, 43, 125-129
https://doi.org/10.2307/1932047
Zhang Li-Chun, Chambers Raymond L. (2004): Small area estimates for cross-classifications. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66, 479-496
https://doi.org/10.1111/j.1369-7412.2004.05266.x
