基于MaxEnt模型的三江源区草地濒危保护植物热点区识别

doi:10.17520/biods.2017188

生物多样性 ›› 2018, Vol. 26 ›› Issue (2): 138-148. DOI: 10.17520/biods.2017188

所属专题：青藏高原生物多样性与生态安全

基于MaxEnt模型的三江源区草地濒危保护植物热点区识别

武晓宇^1,², 董世魁^1,^*(), 刘世梁¹, 刘全儒³, 韩雨晖¹, 张晓蕾¹, 苏旭坤¹, 赵海迪¹, 冯憬¹

1 .北京师范大学环境学院, 北京 100875
2 .北京巧女公益基金会, 北京 100015
3 .北京师范大学生命科学学院, 北京 100875

收稿日期:2017-06-26 接受日期:2017-12-01 出版日期:2018-02-20 发布日期:2018-05-05
通讯作者: 董世魁
作者简介:# 共同第一作者
基金资助:
国家重点研发计划专项课题(2016YFC0501906)和水环境模拟国家重点实验室重点项目

Identifying priority areas for grassland endangered plant species in the Sanjiangyuan Nature Reserve based on the MaxEnt model

Xiaoyu Wu^1,², Shikui Dong^1,^*(), Shiliang Liu¹, Quanru Liu³, Yuhui Han¹, Xiaolei Zhang¹, Xukun Su¹, Haidi Zhao¹, Jing Feng¹

1 School of Environment, Beijing Normal University, Beijing 100875
2 Beijing Qiaonyu Foundation, Beijing 100015
3 College of Life Sciences, Beijing Normal University, Beijing 100875

Received:2017-06-26 Accepted:2017-12-01 Online:2018-02-20 Published:2018-05-05
Contact: Dong Shikui
About author:# Co-first authors

摘要/Abstract

摘要：

三江源地处全球生物多样性热点之一的青藏高原腹地, 是高寒草地生物多样性的集中分布区。但过去几十年中, 人为干扰和气候变化等因素导致高寒草地严重退化, 草地生物多样性受到极大威胁。本研究利用最大熵(MaxEnt)模型模拟了三江源区40种濒危保护植物当前及未来气候变化情景下的热点分布区。根据最大熵模型估计结果统计, 目前三江源濒危保护植物的热点区面积89,438 km², 主要分布于三江源东部和南部, 其中濒危物种大于30种的最热点地区面积485 km², 主要分布于囊谦县、玉树市、班玛县、久治县和河南县。未来在增温增湿的气候变化情景下, 最大熵模型模拟的三江源区草地濒危保护植物的热点区将向西北部扩大, 有利于植物多样性的维持和提升。然而, 模型模拟还发现, 在囊谦县、玉树市、班玛县、久治县和河南县等县市, 均有濒危保护植物大于25种以上的热点区域未被重点保护区覆盖, 总面积为4,423 km²。这一区域被划分为可开展畜牧生产活动的一般保护区, 受到人为干扰的可能性较大, 应予以更多关注与保护。

关键词: 生物多样性, 气候变化, 保护优先区, 最大熵模型

Abstract

Located in southern Qinghai Province in China, Sanjiangyuan is the source area for the Yangtze River, Yellow River, and Lancang River, and a worldwide biodiversity hotspot. Sanjiangyuan was degraded through human disturbance and climate change, which has led to a dramatic loss of the biodiversity of rangeland resources. We conducted field surveys based on species coordinates during 2014 and 2015. We used the MaxEnt model to predict distribution of 40 endangered plant species in Sanjiangyuan using the species coordinate data and bioclimatic data collected from the WorldClim database. From this, we obtained hotspots of endangered plant species in Sanjiangyuan under current and future climatic conditions. Results showed that hotspot areas of endangered plant species in Sanjiangyuan estimated using the MaxEnt model were approximately 89,438 km², and mainly located in the east and south of the reserve. Among these hotspots, those that included more than 30 endangered plant species totalled 485 km², and were mainly found in Nangqian County, Yushu City, Banma County, Jiuzhi County, and Henan County. The climate will become warmer and wetter in Sanjiangyuan in the future, which would benefit biodiversity and expand hotspot areas to the northwest. However, problems associated with planning the reserve remain. Nearly 4,423 km² of hotspot areas have not been protected in the key reserve, including in Nangqian County, Yushu City, Banma County, Jiuzhi County, and Henan County. In these areas grazing is permitted, which might lead to human disturbances. We suggest policy makers focus more attention on these areas and increase conservation efforts.

Key words: biodiversity, climate change, prior conservation area, MaxEnt model

武晓宇, 董世魁, 刘世梁, 刘全儒, 韩雨晖, 张晓蕾, 苏旭坤, 赵海迪, 冯憬 (2018) 基于MaxEnt模型的三江源区草地濒危保护植物热点区识别. 生物多样性, 26, 138-148. DOI: 10.17520/biods.2017188.

Xiaoyu Wu, Shikui Dong, Shiliang Liu, Quanru Liu, Yuhui Han, Xiaolei Zhang, Xukun Su, Haidi Zhao, Jing Feng (2018) Identifying priority areas for grassland endangered plant species in the Sanjiangyuan Nature Reserve based on the MaxEnt model. Biodiversity Science, 26, 138-148. DOI: 10.17520/biods.2017188.

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https://www.biodiversity-science.net/CN/Y2018/V26/I2/138

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变量 Variable	描述 Description
Bio1	年均温 Annual mean temperature
Bio2	平均温度日较差 Mean diurnal temperature range
Bio3	等温性 Isothermality
Bio4	温度季度变化 Temperature seasonality
Bio5	最热月最高温 Max temperature of warmest month
Bio6	最冷月最低温 Min temperature of coldest month
Bio7	年温度变化范围 Temperature annual range
Bio8	最湿季度均温 Mean temperature of wettest quarter
Bio9	最干季度均温 Mean temperature of driest quarter
Bio10	最暖季度均温 Mean temperature of warmest quarter
Bio11	最冷季度均温 Mean temperature of coldest quarter
Bio12	年平均降水量 Annual precipitation
Bio13	最湿月降水量 Precipitation of wettest month
Bio14	最干月降水量 Precipitation of driest month
Bio15	降水量变异系数 Precipitation seasonality (coefficient of variation)
Bio16	最湿季度降水量 Precipitation of wettest quarter
Bio17	最干季度降水量 Precipitation of driest quarter
Bio18	最暖季度降水量 Precipitation of warmest quarter
Bio19	最冷季度降水量 Precipitation of coldest quarter

变量 Variable	描述 Description
Bio1	年均温 Annual mean temperature
Bio2	平均温度日较差 Mean diurnal temperature range
Bio3	等温性 Isothermality
Bio4	温度季度变化 Temperature seasonality
Bio5	最热月最高温 Max temperature of warmest month
Bio6	最冷月最低温 Min temperature of coldest month
Bio7	年温度变化范围 Temperature annual range
Bio8	最湿季度均温 Mean temperature of wettest quarter
Bio9	最干季度均温 Mean temperature of driest quarter
Bio10	最暖季度均温 Mean temperature of warmest quarter
Bio11	最冷季度均温 Mean temperature of coldest quarter
Bio12	年平均降水量 Annual precipitation
Bio13	最湿月降水量 Precipitation of wettest month
Bio14	最干月降水量 Precipitation of driest month
Bio15	降水量变异系数 Precipitation seasonality (coefficient of variation)
Bio16	最湿季度降水量 Precipitation of wettest quarter
Bio17	最干季度降水量 Precipitation of driest quarter
Bio18	最暖季度降水量 Precipitation of warmest quarter
Bio19	最冷季度降水量 Precipitation of coldest quarter

物种 Species	AUC值 AUC value	物种 Species	AUC值 AUC value
褐紫乌头 Aconitum brunneum	0.969	广布红门兰 Orchis chusua	0.910
八宿雪灵芝 Arenaria baxoiensis	0.969	宽叶红门兰 Orchis latifolia	0.919
三刺草 Aristida triseta	0.978	河北红门兰 Orchis tschiliensis	0.995
华雀麦 Bromus sinensis	0.962	青海固沙草 Orinus kokonorica	0.982
凹舌兰 Coeloglossum viride	0.948	川赤芍 Paeonia veitchii	1.000
毛杓兰 Cypripedium franchetii	0.997	羽叶点地梅 Pomatosace filicula	0.833
黑紫披碱草 Elymus atratus	0.867	小丛红景天 Rhodiola dumulosa	0.992
短芒披碱草 Elymus breviaristatus	0.884	喜马红景天 Rhodiola himalensis	0.876
矮麻黄 Ephedra minuta	0.930	圆丛红景天 Rhodiola juparensis	0.830
单子麻黄 Ephedra monosperma	0.839	狭叶红景天 Rhodiola kirilowii	0.911
中华羊茅 Festuca sinensis	0.915	四裂红景天 Rhodiola quadrifida	0.844
南山龙胆 Gentiana grumii	0.880	粗茎红景天 Rhodiola wallichiana	0.844
西南手参 Gymnadenia orchidis	0.942	短颖鹅观草 Roegneria breviglumis	0.906
落地金钱 Habenaria aitchisonii	0.981	短柄鹅观草 Roegneria brevipes	0.953
裂瓣角盘兰 Herminium alaschanicum	0.984	青海鹅观草 Roegneria kokonorica	0.980
角盘兰 Herminium monorchis	0.981	云状雪兔子 Saussurea aster	0.818
沼兰 Malaxis monophyllos	0.983	苞叶雪莲 Saussurea obvallata	0.927
红花绿绒蒿 Meconopsis punicea	0.921	红叶雪兔子 Saussurea paxiana	0.855
颈果草 Metaeritrichium microuloides	0.873	羌塘雪兔子 Saussurea wellbyi	0.916
羌活 Notopterygium incisum	0.940	华福花 Sinadoxa corydalifolia	0.993

物种 Species	AUC值 AUC value	物种 Species	AUC值 AUC value
褐紫乌头 Aconitum brunneum	0.969	广布红门兰 Orchis chusua	0.910
八宿雪灵芝 Arenaria baxoiensis	0.969	宽叶红门兰 Orchis latifolia	0.919
三刺草 Aristida triseta	0.978	河北红门兰 Orchis tschiliensis	0.995
华雀麦 Bromus sinensis	0.962	青海固沙草 Orinus kokonorica	0.982
凹舌兰 Coeloglossum viride	0.948	川赤芍 Paeonia veitchii	1.000
毛杓兰 Cypripedium franchetii	0.997	羽叶点地梅 Pomatosace filicula	0.833
黑紫披碱草 Elymus atratus	0.867	小丛红景天 Rhodiola dumulosa	0.992
短芒披碱草 Elymus breviaristatus	0.884	喜马红景天 Rhodiola himalensis	0.876
矮麻黄 Ephedra minuta	0.930	圆丛红景天 Rhodiola juparensis	0.830
单子麻黄 Ephedra monosperma	0.839	狭叶红景天 Rhodiola kirilowii	0.911
中华羊茅 Festuca sinensis	0.915	四裂红景天 Rhodiola quadrifida	0.844
南山龙胆 Gentiana grumii	0.880	粗茎红景天 Rhodiola wallichiana	0.844
西南手参 Gymnadenia orchidis	0.942	短颖鹅观草 Roegneria breviglumis	0.906
落地金钱 Habenaria aitchisonii	0.981	短柄鹅观草 Roegneria brevipes	0.953
裂瓣角盘兰 Herminium alaschanicum	0.984	青海鹅观草 Roegneria kokonorica	0.980
角盘兰 Herminium monorchis	0.981	云状雪兔子 Saussurea aster	0.818
沼兰 Malaxis monophyllos	0.983	苞叶雪莲 Saussurea obvallata	0.927
红花绿绒蒿 Meconopsis punicea	0.921	红叶雪兔子 Saussurea paxiana	0.855
颈果草 Metaeritrichium microuloides	0.873	羌塘雪兔子 Saussurea wellbyi	0.916
羌活 Notopterygium incisum	0.940	华福花 Sinadoxa corydalifolia	0.993

基于MaxEnt模型的三江源区草地濒危保护植物热点区识别

Identifying priority areas for grassland endangered plant species in the Sanjiangyuan Nature Reserve based on the MaxEnt model

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