Arid Zone Research ›› 2021, Vol. 38 ›› Issue (5): 1474-1483.doi: 10.13866/j.azr.2021.05.30

• Ecology and Environment • Previous Articles     Next Articles

Health assessment of plantations in Nursultan, capital of Kazakhstan

YAN Jinsheng1,2,3(),WANG Yongdong1,3(),LOU Boyuan1,2,3,Akida Askar1,2,3,XU Xinwen1,3   

  1. 1. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    2. University of Chinese Academy of Sciences, Beijing 101408, China
    3. National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Urumqi 830011, Xinjiang, China
  • Received:2021-02-23 Revised:2021-04-12 Online:2021-09-15 Published:2021-09-24
  • Contact: Yongdong WANG E-mail:761478224@qq.com;wangyd@ms.xjb.ac.cn

Abstract:

The study was performed in Nursultan and its surroundings. Its principal aims are to explore the methods of plantation health assessment, analyze different plantations, screen suitable assessment indexes of plantation health, and establish an evaluation model of plantation health, which would provide theoretical support for health assessment in the region. Twenty-five plantation plots and two natural forest plots were analyzed. Shannon-Wiener index (X1), Pielou index (X2), Simpson index (X3), stand spatial structure optimization object function(X4), soil organic matter content (X5), soil total nitrogen content (X6), soil total phosphorus content (X7), soil pH (X8), soil moisture (X9), mean tree height (X10), mean breast diameter (X11), mean height under branches (X12), mean canopy (X13), and forest regeneration (X14) were evaluated. Factor analysis, cluster analysis, discriminant analysis, and stepwise regression analysis were used to comprehensively assess the plantations. Fourteen single indicators were converted into four independent indicators through factor analysis. The contribution rates of the first four factors were 30.482%, 24.374%, 19.711%, and 8.646%, representing 83.212% of the original data variance. The health score value was calculated through the factor score coefficient matrix and the weight of each factor. Cluster analysis was performed on comprehensive health scores, and plots were divided into five categories: (Ⅰ) a high-quality type, (Ⅱ) a satisfied type, (Ⅲ) a moderate type, (Ⅳ) a vulnerable type, and (Ⅴ) an unhealthy type. The results of discriminant analysis and cluster analysis were similar. The accuracy of the self-verification and cross-validation were 100% and 85.185%. The optimal mathematical model for plantation health assessment was established as H=0+0.293X13+0.186X5+0.079X3+0.100X2+0.038X7(R2=0.987). Five indexes for plantation health assessment were selected: Mean canopy, soil organic matter content, Simpson index, Pielou index and soil total phosphorus content. Mean canopy, soil organic matter content, Simpson index, Pielou index, and soil total phosphorus content could be used to assess the health of plantations in the region. The comprehensive assessment value of the five indexes could be calculated to predict healthy conditions by measuring the five indexes under the same conditions.

Key words: plantations, factor analysis, cluster analysis, discriminant analysis, stepwise regression analysis, health assessment