Volume 11, Issue 40 (summer 2007)                   JWSS 2007, 11(40): 483-495 | Back to browse issues page

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M. Mousaei Sanjerehei, M. Bassiri. Comparison and Evaluation of Indices of Dispersion Patterns of Plants on Artemisia Sieberi Shrublands in Yazd Province. JWSS. 2007; 11 (40) :483-495
URL: http://jstnar.iut.ac.ir/article-1-721-en.html
Abstract:   (17714 Views)
Selection of efficient indices is very important for detecting and measuring random, uniform and clumped distribution patterns of plants in different plant communities. To compare and evaluate indices of dispersion patterns of plants, three stands were selected in Nodushan, Yazd. A (50m*100m) area was selected within each stand for sampling. Sampling was randomly systematicly conducted. Measurements and counts were made at 50 points and (1 and 2m2) quadrats which were randomly selected along four 100m transects within each sampling area. Indices of dispersion using quadrate studied in this survey include: Standardized index of Morisita, Morisita's index, Green's index, Dispersion (variance/mean ratio) index , Lloyd's index of patchiness and distance indices of dispersion including Pielou, Hopkines, T square, Eberhardt , Hines, Johnson and Zimer and Holgate indices. Results showed that T square and Holgate indices were more powerful than the other indices for detecting intensity of small-scale and tightly clumped pattern of shrubs because the two indices could distinguish between single individuals and the individuals on the edges of dense and small clumps. Johnson and Zimer index and Standardized index of Morisita (in shrublands with plant cover greater than 5%) were more efficient than the other indices for determining spatial pattern of these small clumps and single individuals. Among studied indices of dispersion, Green's index had the highest precision and with the exception of this index, distance indices were more precise than the quadrate indices.
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Type of Study: Research | Subject: Ggeneral
Received: 2008/01/9 | Accepted: 2017/10/31 | Published: 2017/10/31

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