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M. Vedriš,A. Jazbec, M. Frntić, M. Božić, E. Goršić: PRECIZNOST PROCJENE STRUKTURNIH ... Šumarski list br. 7–8, CXXXIII (2009), 369-379 Iles,K., 2003:ASampler of InventoryTopics. Atex-Pranjić, A., 1987: Pouzdanost rezultata izmjere tbook on forest inventory. Second edition. Kim šuma. Glasnik za šumske pokuse, Posebno izda- Iles andAssociates, 869 str., Nanaimo, B.C. Ca-nje3, 161–176, Zagreb. nada. Pranjić,A., N.Lukić,1997:Izmjera šuma. ŠumarIndir, K., 2004: Optimalni načini prikupljanja i ski fakultet, 210 str., Zagreb. obrade podataka kontrolnom metodom u inven- Schreuder, H.T.,T. G.Gregoire, G.B Wood, turi šuma. Magisterij. Šumarski fakultet, Sveuči 1993: Sampling methods for multiresource folište u Zagrebu. rest inventory. John Wiley & Sons, 446 str., New Johnson, E. W., 2000: Forest sampling desk refe- York. rence. CRC Press, 1008 str.,Boca Raton, Florida. Schreuder, H. T., R. Ernst, H. Ramirez-MalKoprivica, M., 2006:Varijabilitet i preciznost pro donado, 2004: Statistical techniques for samcjene taksacionih elemenata visokih sastojina pling and monitoring natural resources. General bukve u Jablaničkom šumskom području. Glas- Technical Report RMRS-GTR-126, U.S. Departnik Šumarskog fakulteta Univerziteta u Banjoj ment of Agriculture, Forest Service, Rocky Luci 6, 49–60. Mountain Research Station, 111 str., Fort Collins. Sokal, R. R., F. J. Rohlf, 1995:Biometry, (Third mjenom uzoraka promjenljive vjerojatnosti se Lukić,N., 1984:Izmjera jednodobnih sastojina priedition). Freeman and Company, 880 str., New York. lekcije. Glasnik za šumske pokuse 22, 333–377, Zagreb. StatSoft, Inc., 2006:STATISTICA(data analysis software system), version 7.1. www.statsoft.com. Pranjić,A., 1966:Interpolirane Šurićeve jednoulazne tablice za jelu – smreku i bukvu. Šumarski *** Pravilnik o uređivanju šuma, Narodne novine, list 90 (3–4), 185–212, Zagreb. 111/06i 141/08. SUMMARY: Stand structure estimate is based on data from sample plots. The aim of this research was to compare the stand structure estimates based on sample of circular plots with different radii. Through this influence of plot size on structure estimate and efficiency of stand measurement was also indirectly assessed. Measurements were made in beech-fir selection stand in the Educational and experimental forest site “Zalesina” in Gorski kotar region, Croatia. Stand size is 20,63 ha, it is situated from 790 to 850 m above sea level, and belongs to site class II. Stand exposition is south to east, terrain slope is 5–10°. Tree breast height diameters (DBH) were measured on systematic sample of 17 concentric circular sample plots. Tree location from plot centre was recorded by azimuth and distance. All trees of DBH 10 cm or more were measured on 13 meter radius plot, trees of DBH 30 cm and more were measured on 19 m radius plot and trees of DBH 50 cm and more on 26 m radius plot. Computer programme CirCon for calculation of stand parameters based on measured plots and simulated plots, with radii different from measured ones, has been developed. Plots based on real measurements were simulated according to ones used in forest management practice (singular and concentric circle plots). We simulated 8 methods: K7,98 (7.98 m radius plots), K9,77 (9.77 m radius plots), K11,28 (11.28 m radius plots), K12,62 (12.62 m radius plots); K5-12 (concentric circle plots with radii 5 and 12 m), K7-13 (concentric plots with radii 7 and 13 m), K7-13-20 (concentric plots with radii 7, 13 and 20 m) and K13-19-26 (three concentric circles of 13, 19 and 26 m radius). Calculated estimates for number of trees, basal area and volume on the same standing points differed between methods depending on spatial tree distribution and size of plots. Descriptive statistics (arithmetic mean, standard deviation, standard error) was made for each variable (number of trees, basal area and volume) on stand level. Sample error with 95 % confidence (SE/mean*t0.05,) was also calculated to express the precision of estimates. Different estimates by methods depending on plot size were compared by re |