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Classification of Woody Plant Functional Groups in A Tropical Natural Forest Landscape of Bawangling, Hainan Island and Their Potential Distribution

海南岛霸王岭热带天然林景观中木本植物功能群划分及其潜在分布*


为了解热带天然林景观中木本植物功能群及其基本分布规律,在对研究区进行千米网格样方调查和环境因子收集的基础上,采用演替地位和最大潜在高度2个指标将579种木本植物划分为8个功能群; 采用生态位模型对这些功能群的地理分布进行预测,并应用受试者工作特征分析进行模型精度验证; 应用多元线性回归对影响各功能群分布的主要因子进行分析。结果表明: 生态位模型对8个功能群的潜在分布预测都达到70%以上; 相对于顶极类功能群,先锋类功能群具有较高的最大潜在分布面积和较低的最适分布面积,同时呈现出较为分散的格局,反映了两大类功能群个体生态学特性和对环境适应的差异; 在选择的10个环境因子中,有7个因子(极端最低温、年均温、极端最高温、年均相对湿度、年均降水量、海拔和坡向)对木本植物功能群的潜在分布影响显著。

Nowadays, plant functional groups (PFGs) have been recognized as a promising tool in management and restoration of degraded species-rich ecosystems. However, their potential distribution, especially in a tropical forest landscape, is rarely studied. Based on an investigation of 135 plots in a tropical natural forest landscape of Bawangling, Hainan Island, South China, the PFGs were classified by employing two criteria of successional status and potential maximum height. In this study the genetic algorithm for rule-set prediction (GARP) was used to estimate the potential distribution of the PFGs and then the receiver operating characteristics (ROC) was used to evaluate the predictive performance. Multiple linear regression analysis was applied in order to find out the major factors determining potential distributions of the PFGs. Results showed that the predictive accuracies for the eight PFGs were all over 70%. Compared with the climax functional groups, the pioneer functional groups had higher potential maximum distributional range, smaller maximum suitable range and presented more dispersed distribution pattern. This indicated there were different in autecological characteristics and responses to environment between pioneer and climax species. The analysis of correlation revealed that minimum temperature, annual mean temperature, maximum temperature, annual mean relative humidity, annual mean precipitation, aspect and elevation were the key factors determining potential distributions of PFGs. The results further also demonstrate that the GARP ecological niche model using presence-only data and large-scale environmental variables is a powerful tool for predicting species‘ geographic range.


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