Chin J Plan Ecolo ›› 2007, Vol. 31 ›› Issue (6): 1079-1091.doi: 10.17521/cjpe.2007.0136

• Research Articles • Previous Articles     Next Articles


ZHANG Zhi-Dong1,2; ZANG Run-Guo1*   

  1. 1 Key Laboratory of Forest Ecology and Environment, the State Forestry Administration, Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China; 2 Yantai Institute of Coastal Zone Research for Sustainable Development, Chinese Academy of Sciences, Yantai , Shandong 264003, China
  • Online:2007-11-30 Published:2007-11-30
  • Contact: ZANG Run-Guo

Abstract: Aims Our major objectives were to 1) identify keystone species within the context of functional groups, 2) develop potential
distributional predict ions for keystone species using ecological niche model, 3) confirm factors determining potential
distributions of keystone species, and 4) test if the performances of ecological niche model are better than those of a
random model and differ in predicting different keystone species.
Methods Based on the investigation of 135 plots in a natural tropical forest landscape, we classified woody plant functional
groups based on successional status and potential maximum height. Keystone species within each functional group we re
identified using a dominance index (DI). We used the genetic algorithm for rule-set prediction (GARP) to estimate the
keystone species’ potential distribution and then used the receiver operating characteristics to evaluate predictive
performance. Applying multiple linear regression analysis, we identified major factors determining potential distributions of
keystone species.
Important findings Identification of keystone species within pioneer species, climax shrub and emergent tree functional
groups was clearer than within climax subcanopy and climax canopy tree functional groups. Generally, among the eight keystone
species, pioneer species Melastoma sanquiueum, Aporosa chinensis and Liquidambar formosana (but not Adinandra hainanensis)
have high probability of occurrence in the north, west and southwest regions of Bawangling. However, climax species
Psychotria rubra, Ardisia quinquegona and Castanopsis hainanensis (but not Pinus merkusii) have high probability of
occurrence in the central, southeast and south regions. Minimum and maximum temperature, mean annual temperature and
precipitation, aspect and altitude were the key factors determining potential distributions of keystone species. Evaluation
of GARP model’s performance indicated excellent predictive ability of all eight keystone species’ distribution. This study
suggests the DI method is more suitable to identify keystone species with in woody plant functional groups in which a single
or a few species are dominant. Findings will assist decision makers in planning conservation and management policies in
tropical rainforest areas.

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