Gorgan University Of Agricultural Sciences and Natural Resources Journal of Wood and Forest Science and Technology 2322-2077 24 2 2017 08 23 Evaluation of homogeneity of tree spatial distribution in a mixed mesquite (Prosopis cineraria) stand in Barchah protected area, Hormozgan province Evaluation of homogeneity of tree spatial distribution in a mixed mesquite (Prosopis cineraria) stand in Barchah protected area, Hormozgan province 47 58 3659 10.22069/jwfst.2017.12497.1652 FA Elaheh Khosravi Yousef Erfanifard Shiraz University Journal Article 2017 01 04 Background and objectives: Spatial pattern of trees in a stand is the outcome of different processes such as their interactions, seed dispersal, and environmental heterogeneity. In consequence, knowledge of spatial pattern of plant species is important for deeper understanding of different hypotheses in ecology. Considering the importance, unbiased recognition of spatial pattern of plant species using reliable techniques is essential in ecology. Summary statistics used in point pattern analysis to explore spatial pattern of plants are based on the null model of homogeneous Poisson process (Complete spatial randomness: CSR). So it seems necessary to investigate homogeneity of tree spatial distribution before analyzing their spatial pattern. Considering this issue, this study was aimed to evaluate the homogeneity of tree spatial distribution in a mixed mesquite stand in Khalij-Omanian vegetation zone using two methods. Moreover, it was also aimed to investigate the impact of ignoring the CSR null model on spatial pattern analysis of trees in the plot. <br /> Materials and methods: A 49-ha study plot (700 m × 700 m) was selected in a mixed mesquite stand in Barchah protected area in Hormozgand province. The spatial location of all tree and shrubs with height > 0.5 m was registered and their height and crown area were measured. Furthermore, another plot with similar number of plants and environmental conditions was simulated with homogeneous spatial distribution and clustered spatial pattern of plants. Two methods of Chi-squared test based on quadrat accompanied with Pearson residuals and Kolmogorov-Smirnov test were applied to explore homogeneity of tree spatial distribution. Moreover, homogeneous and inhomogeneous pair correlation functions were used to analyze spatial patterns in two plots. <br /> Results: The study plot was covered by 498 trees and shrubs including 149 mesquites, 248 umbrella thorns (Acacia tortilis), and 101 desert thorns (Lycium shawii). The results showed that Chi-squared test only with 4 × 4 quadrats could recognize homogeneity of the simulated plot. Mean of Pearson residuals also did not characterize the homogeneity difference of two plots. While Kolmogorov-Smirnov test explored the difference between tree spatial distribution of the real plot (p-value Conclusion: In general, it was concluded that Kolmogorov-Smirnov test is a reliable method to assess homogeneity of plant spatial distribution in the study area. Moreover, it was revealed that efficiency of g(r) in spatial pattern recognition of plants was influenced by homogeneity of their spatial distribution and application of inappropriate form of g(r) resulted in biased spatial pattern analysis in the study site. Background and objectives: Spatial pattern of trees in a stand is the outcome of different processes such as their interactions, seed dispersal, and environmental heterogeneity. In consequence, knowledge of spatial pattern of plant species is important for deeper understanding of different hypotheses in ecology. Considering the importance, unbiased recognition of spatial pattern of plant species using reliable techniques is essential in ecology. Summary statistics used in point pattern analysis to explore spatial pattern of plants are based on the null model of homogeneous Poisson process (Complete spatial randomness: CSR). So it seems necessary to investigate homogeneity of tree spatial distribution before analyzing their spatial pattern. Considering this issue, this study was aimed to evaluate the homogeneity of tree spatial distribution in a mixed mesquite stand in Khalij-Omanian vegetation zone using two methods. Moreover, it was also aimed to investigate the impact of ignoring the CSR null model on spatial pattern analysis of trees in the plot. <br /> Materials and methods: A 49-ha study plot (700 m × 700 m) was selected in a mixed mesquite stand in Barchah protected area in Hormozgand province. The spatial location of all tree and shrubs with height > 0.5 m was registered and their height and crown area were measured. Furthermore, another plot with similar number of plants and environmental conditions was simulated with homogeneous spatial distribution and clustered spatial pattern of plants. Two methods of Chi-squared test based on quadrat accompanied with Pearson residuals and Kolmogorov-Smirnov test were applied to explore homogeneity of tree spatial distribution. Moreover, homogeneous and inhomogeneous pair correlation functions were used to analyze spatial patterns in two plots. <br /> Results: The study plot was covered by 498 trees and shrubs including 149 mesquites, 248 umbrella thorns (Acacia tortilis), and 101 desert thorns (Lycium shawii). The results showed that Chi-squared test only with 4 × 4 quadrats could recognize homogeneity of the simulated plot. Mean of Pearson residuals also did not characterize the homogeneity difference of two plots. While Kolmogorov-Smirnov test explored the difference between tree spatial distribution of the real plot (p-value Conclusion: In general, it was concluded that Kolmogorov-Smirnov test is a reliable method to assess homogeneity of plant spatial distribution in the study area. Moreover, it was revealed that efficiency of g(r) in spatial pattern recognition of plants was influenced by homogeneity of their spatial distribution and application of inappropriate form of g(r) resulted in biased spatial pattern analysis in the study site. https://jwfst.gau.ac.ir/article_3659_e8b20074ebc48ebd8aad0eaa0ccfa2d6.pdf