• 论文与研究报告 •

### 基于最大熵模型的吉林省主要天然林潜在分布适宜性

1. 中国林业科学研究院资源信息研究所 国家林业与草原局森林经营与生长模拟重点实验室 北京 100091
• 收稿日期:2018-02-05 修回日期:2018-05-19 出版日期:2018-07-25 发布日期:2018-08-11
• 基金资助:
林业公益性行业科研专项"我国主要林区林地立地质量和生产力评价研究"（201504303）。

### The Suitability of Potential Geographic Distribution of Natural Forest Types in Jilin Province Based on Maximum Entropy Models

Liu Dan, Li Yutang, Hong Lingxia, Guo Hong, Xie Yangsheng, Zhang Zhuoli, Lei Xiangdong, Tang Shouzheng

1. Key Laborabory of Forest Management and Growth Modelling, State Forestry and Grassland Administration Research Institute of Forest Resource Information Techniques, CAF Beijing 100091
• Received:2018-02-05 Revised:2018-05-19 Online:2018-07-25 Published:2018-08-11

Abstract: [Objective]This study aims to investigate the method of distribution suitability of natural forests based on species distribution models, to examine the dominant environmental factors affecting the distribution of forest types and to generate the distribution suitability maps of major forest types. The results will provide the reference for natural forest restoration and structural adjustment in the region.[Method]Maximum entropy models were used for predicting potential distribution suitability for 11 natural forest types (including 7 mixed-species forests) in Jilin Province, northeast China. Data with tree species presence were obtained from permanent sample plots from the 8th Chinese national forest inventory (NFI) with natural origins collected in Jilin Province. Totally, 19 bioclimatic, 33 soil and 3 terrain environmental variables were included. Model accuracy was evaluated by AUC (area under the receiver operating characteristics curves) values, and the Jackknife test showed the importance of different variables which determined dominant variables affecting the distribution of forest types. Distribution suitability maps of 11 forest types were generated with five levels.[Result]The maximum entropy models were successful at discriminating between suitable and unsuitable habitat at the local scale for all 11 forest types, the AUC values were from 0.687 2 to 0.946 9 for calibration and test data. Among the values, one forest type showed "excellent", 7 forest types showed "very good", 2 forest types showed "good" and 1 forest type showed "fair". Therefore, the prediction results of the potential distribution of the 11 forest types in Jilin Province by the maximum entropy model were reliable. The environmental factors affecting the distribution of forest types were ranked as max temperature of the warmest month(for 10 forest types), elevation(for 8 forest types), mean temperature of the warmest quarter (for 7 forest types), and annual mean temperature(for 6 forest types) in terms of their importance to the distribution of the specific forest types. Therefore, temperature and elevation were the most important factors to the distribution of the specific forest types in the region. Potential distribution suitability mapping for 11 forest types were completed.[Conclusion]The maximum entropy model could reliably simulate the potential distribution area of forest types in Jilin Province. The dominant environment variables selected by the model were reasonable. The distribution suitability maps for 11 forest types could be as a reference for natural forest restoration and quality improvement in northeast China.