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Chinese Journal of Applied Ecology ›› 2010, Vol. 21 ›› Issue (05): 1315-1320.

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Application of niche theory in evaluation of main tourism scenic areas in Zhangjiajie City.

XIANG Yan-ping1,3;XIANG Chang-guo2;CHEN You-lian3   

  1. 1School of Life Science and Technology, Central South University of Forest and Technology, Changsha 410004, China;2College of Tourism, Jishou University, Zhangjiajie 427000, Hunan, China;3College of Business, Jishou University, Jishou 416000, Hunan, China
  • Online:2010-05-20 Published:2010-05-20

Abstract: Five tourism scenic areas in Zhangjiajie City were selected as research objects, and fifty kinds of resource conditions affecting the development of tourism scenic area were taken as evaluation indices. Through disposing and consolidating the indices level by level, an analysis was made on the niche breadth and niche overlap of the five tourism scenic areas at three levels (I, Ⅱ, and Ⅲ). In the five scenic areas, index level had significant effects on the niche breadth (F=10.278, P=0.006), but less effects on the relative niche breadth, suggesting that in the evaluation of the development potential of tourism scenic area, relative niche breadth was more reasonable than absolute niche breadth. From level Ⅲ to level I, the niche overlap of the five scenic areas was increasing, indicating that level choice would affect the evaluation of the actual niche overlap of the scenic areas. With the progressive refinement of the indices to certain level, and when the difference between observed and Monte Carlo-simulated Pianka indices achieved to significant level, this index level could be used as the minimum standard of the refinement, and the simulated niche overlap could be taken as an important reference in the competition evaluation of tourism scenic area.

Key words: niche breadth, niche overlap, ecological simulation, indices system, tourism competition, Yellow River Esturary, fish assemblage, spatial pattern, multivariate analysis, canonical correspondence analysis (CCA), environmental factors.