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生态学杂志 ›› 2020, Vol. 39 ›› Issue (11): 3785-3794.doi: 10.13292/j.1000-4890.202011.009

• 研究报告 • 上一篇    下一篇

基于MaxEnt模型的广东省红树林潜在适生区和保护空缺分析

晁碧霄1,胡文佳2,3,陈彬2,3,张典2,陈光程2,3,俞炜炜2,3,马志远2,3,雷光春1,王玉玉1*   

  1. 1北京林业大学生态与自然保护学院, 北京 100083; 2自然资源部第三海洋研究所, 福建厦门 361005;3福建省海洋生态保护与修复重点实验室, 福建厦门 361005)
  • 出版日期:2020-11-11 发布日期:2021-05-10

Potential suitable habitat of mangroves and conservation gap analysis in Guangdong Province with MaxEnt Modeling.

CHAO Bi-xiao1, HU Wen-jia2,3, CHEN Bin2,3, ZHANG Dian2, CHEN Guang-cheng2,3, YU Wei-wei2,3, MA Zhi-yuan2,3, LEI Guang-chun1, WANG Yu-yu1*#br#   

  1. (1Beijing Forestry University, School of Ecology and Nature Conservation, Beijing 100083, China; 2Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, Fujian, China; 3Fujian Provincial Key Laboratory of Marine Ecological Conservation and Restoration, Xiamen 361005, Fujian, China).
  • Online:2020-11-11 Published:2021-05-10

摘要: 红树林是分布在热带、亚热带海岸潮间带的木本群落,具有重要的生态功能。广东省是中国红树林分布面积最大的省份,在红树林保护方面具有重要地位。最大熵(MaxEnt)模型是以生态位理论为基础的物种分布模型,目前被广泛应用于物种潜在适生区预测。本研究应用MaxEnt模型,根据广东省红树林分布数据和环境变量数据,预测了该省红树林的潜在适生区分布,分析了影响红树林分布的关键环境变量及其适生区间,识别了广东省红树林保护与修复空缺区域。结果表明,在气候、地形、底质类型、海表盐度、海表温度5组变量中,影响广东省红树林分布的最主要环境变量为气温、海表温度和降水。关键环境变量的最佳适生区间为年平均温度22.37~23.58 ℃、最冷季平均海表温度23.15~23.34 ℃、年平均降水量1647.14~1809.61 mm、最干月降水量23.6~27.2 mm。广东省红树林的高适生区域主要集中于珠江口大亚湾沿岸和雷州半岛阳江沿岸,保护空缺主要出现在阳江港、镇海湾、珠江口、红海湾等地。本研究结果可为今后广东省红树林保护和修复行动与规划的空间布局提供科学依据。

关键词: 物种分布模型, 保护空缺, 适宜生境, 潜在分布, 限制因子

Abstract: Mangrove forest is a woody community occurring in the intertidal zone of tropical and subtropical coasts, with important ecological functions. Guangdong Province has the largest area of mangrove in China, and thus is critical for mangrove protection. Maximum entropy model (MaxEnt), a species distribution model, is extensively applied in biodiversity conservation. This study compiled a dataset of mangrove distribution and key environmental variables in Guangdong Province. With this dataset, a mangrove MaxEnt was built, which was used to predict the potential suitable zones of mangroves in Guangdong Province and to identify the key environmental variables influencing mangrove distribution. Outcomes of the modeling were further used to assess conservation gaps. The results showed that the most important environmental variables affecting mangrove distribution were temperature, sea surface temperature, and precipitation. The suitable range for annual mean temperature was 22.37-23.58 ℃, for mean sea surface temperature of the coldest quarter was 23.15-23.34 ℃, for annual precipitation was 1647.14-1809.61 mm, and for precipitation of driest month was 23.6-27.2 mm. The most suitable areas for mangrove in Guangdong were mainly concentrated in Pearl River Estuary to Daya Bay coast, and Leizhou Peninsula to Yangjiang coast. Conservation gaps of mangrove were mainly located in Yangjiang Port, Zhenhai Bay, Pearl River Estuary, and Red Bay. Our findings could provide a scientific basis for improving and advancing the spatial layout of mangrove protection and restoration in Guangdong Province.

Key words: species distribution model, conservation gap, suitable area, potential distribution, restricting factor.