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LI Ying, ZHANG Jie, GUO Dong-Gang, SHANGGUAN Tie-Liang. Geostatistical Analysis of Pinus tabulaeformis Population Spatial Patterns Based on Large Plots[J]. Plant Science Journal, 2015, 33(2): 158-164. DOI: 10.11913/PSJ.2095-0837.2015.20158
Citation: LI Ying, ZHANG Jie, GUO Dong-Gang, SHANGGUAN Tie-Liang. Geostatistical Analysis of Pinus tabulaeformis Population Spatial Patterns Based on Large Plots[J]. Plant Science Journal, 2015, 33(2): 158-164. DOI: 10.11913/PSJ.2095-0837.2015.20158

Geostatistical Analysis of Pinus tabulaeformis Population Spatial Patterns Based on Large Plots

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  • Received Date: July 28, 2014
  • Available Online: October 31, 2022
  • Published Date: April 27, 2015
  • The distribution patterns of the Pinus tabulaeformis population in the National Nature Reserve of Lingkong Mountain in Shanxi Province were studied using geostatistics. According to the data of 4 hm2 sample plots, the semivariances of the P. tabulaeformis diameter grades were calculated, semivariogram models were simulated, and Kriging interpolation was performed to draw Kriging maps showing different diameter grades. Results showed that the semivariograms of diameter gradesⅠ, Ⅲ and Ⅳ well fit the exponential model, while diameter grade Ⅱ fit the spherical model, suggesting aggregated spatial distribution patterns in all four diameter grades. In addition, all diameter grades exhibited medium spatial correlation with the range of spatial autocorrelation of 23.4 m, 15.2 m, 11.1 m and 24.9 m, respectively, and the fractal dimensions were ranked as: diameter grade Ⅱ (1.999) > diameter grade Ⅲ (1.995) > diameter grade Ⅳ (1.973) > diameter grade Ⅰ (1.969). The semivariances of height were basically the same as the semivariances of diameter at breast height (DBH), which further verified the accuracy of our analysis. The Kriging map drawn by the Surfer software demonstrated the patch aggregation of the P. tabulaeformis population. The semivariance analysis and Kriging interpolation methods filled the loopholes of traditional population spatial distribution analyses, and were advantageous in revealing the changes in spatial pattern and aggregate intensity for more precise studies of plant patterns in the landscape.
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