基于MaxEnt模型的黄河三角洲滨海湿地优势植物群落潜在分布模拟

doi:10.13287/j.1001-9332.201706.017

应用生态学报 ›› 2017, Vol. 28 ›› Issue (6): 1833-1842.doi: 10.13287/j.1001-9332.201706.017

基于MaxEnt模型的黄河三角洲滨海湿地优势植物群落潜在分布模拟

宗敏^1,2, 韩广轩^2*, 栗云召¹, 王光镇¹, 王安东³, 杨显基⁴

¹鲁东大学资源与环境工程学院, 山东烟台 264025
²中国科学院烟台海岸带研究所海岸带环境过程与生态修复重点实验室, 山东烟台 264003
³山东黄河三角洲国家级自然保护区管理局, 山东东营 257091
⁴中山大学地理科学与规划学院, 广州 510275

收稿日期:2016-10-18 发布日期:2017-06-18
通讯作者: *E-mail:gxhan@yic.ac.cn
作者简介:宗敏,女,1991年生,硕士研究生.主要从事湿地景观格局变化与景观生态研究.E-mail:zongminzm@163.com
基金资助:
本文由中国科学院科技服务网络计划项目(KFJ-EW-STS-127)和国家自然科学基金项目(41671089)资助

Predicting the potential distribution of dominant species of the coastal wetland in the Yellow River Delta, China using MaxEnt model

ZONG Min^1,2, HAN Guang-xuan^2*, LI Yun-zhao¹, WANG Guang-zhen¹, WANG An-dong³, YANG Xian-ji⁴

¹College of Resources and Environmental Engineering, Ludong University, Yantai 264025, Shandong, China
²Key Laboratory of Coastal Zone Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, Shandong, China
³Administration of the Yellow River Delta National Natural Reserve, Dongying 257091, Shandong, China
⁴School of Geo-graphy and Planning, Sun Yat-Sen University, Guangzhou, 510275, China

Received:2016-10-18 Published:2017-06-18
Contact: *E-mail:gxhan@yic.ac.cn
Supported by:
This work was supported by the Science and Technology Service Network Initiative (KFJ-EW-STS-127) and the National Natural Science Foundation of China (41671089)

摘要/Abstract

摘要： 采用千米网格的方法,对黄河三角洲滨海湿地进行土壤采样和植被群落调查,利用MaxEnt模型和GIS空间分析技术,模拟该地区优势物种的潜在分布,定量分析优势物种的主导环境影响因子及其生态位参数.结果表明: 黄河三角洲滨海湿地的优势物种为柽柳、芦苇和盐地碱蓬.影响柽柳、芦苇和盐地碱蓬潜在分布的主导环境因子分别为硝态氮、盐分、坡度、镁、海拔和铵态氮,硝态氮、盐分、全磷、pH、海拔和铵态氮,硝态氮、盐分和铵态氮.黄河三角洲滨海湿地优势物种的存在概率与盐分呈正相关,与其他主导环境影响因子呈负相关.黄河三角洲滨海湿地优势物种的潜在核心适生区主要分布在滨海地区,芦苇的分布范围较柽柳和盐地碱蓬更广泛.

Abstract: Soil and vegetation community were investigated using the method of kilometer grid sampling. In addition, using the maximum entropy (MaxEnt) and the GIS spatial analysis technique, the potential distribution of dominant species in the Yellow River Delta and their major environmental variables and ecological parameters were quantitatively analyzed. The results showed that the dominant species of the coastal wetland were Tamarix chinensis, Phragmites australis and Suaeda salsa in the Yellow River Delta. Among the environmental variables, six variables were significant contributors to the potential distribution model of T. chinensis: NO₃^--N, salt, slope, Mg, altitude and NH₄⁺-N. The environmental variables influencing the distribution of P. australis were NO₃^--N, salt, TP, pH, altitude and NH₄⁺-N. NO₃^--N, salt and NH₄⁺-N were the significant factors determining the potential distribution of S. salsa. The probability of presence of dominant species of the coastal wetland in the Yellow River Delta was positively correlated with salt, but it was negatively correlated with the other major environmental variables. The model predicted that the core potential distribution of dominant species in the Yellow River Delta was mainly in the coastal areas. In addition, P. australis had a wider range of distribution, compared with T. chinensis and S. salsa.

宗敏, 韩广轩, 栗云召, 王光镇, 王安东, 杨显基. 基于MaxEnt模型的黄河三角洲滨海湿地优势植物群落潜在分布模拟[J]. 应用生态学报, 2017, 28(6): 1833-1842.

ZONG Min, HAN Guang-xuan, LI Yun-zhao, WANG Guang-zhen, WANG An-dong, YANG Xian-ji. Predicting the potential distribution of dominant species of the coastal wetland in the Yellow River Delta, China using MaxEnt model[J]. Chinese Journal of Applied Ecology, 2017, 28(6): 1833-1842.

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基于MaxEnt模型的黄河三角洲滨海湿地优势植物群落潜在分布模拟

Predicting the potential distribution of dominant species of the coastal wetland in the Yellow River Delta, China using MaxEnt model

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