基于MaxEnt模型评估刺五加在东北地区的空间分布
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摘要
研究刺五加(Acanthopanax senticosus)在东北地区的潜在分布区及生态适宜性,针对267个刺五加分布样点数据和17个环境因子数据,应用最大熵模型(Maximum Entropy Model,简称MaxEnt)和地理信息系统(Geographic Information System,GIS)评估刺五加的地理分布。结果表明:最大熵模型的AUC值为0.929,模型预测结果的准确性可信度高,可以用来预测刺五加的地理分布。刺五加生态适宜区主要集中在长白山山脉及小兴安岭东南地区,分布面积约为22.12万km~2,存在概率最高的区域主要在辽宁省东部、吉林省东南部以及黑龙江省中部。影响刺五加地理分布的主要环境因子依次为:年均降水量、森林类型、极端低温、生长季降水量及海拔。耦合了大尺度环境数据、植被群落类型数据与刺五加分布之间的关系,预测了东北地区刺五加的生态适宜区及主导环境因子,为其种群恢复与开发利用提供了科学依据。
The maximum entropy model(MaxEnt) and geographic information system(GIS) were used to predict the suitable ecological region for A. senticosus based on 267 plots and 17 ecological factors. The results showed that the area under the receiver operator characteristic curve(AUC) reached 0.929. The accuracy of model prediction results was high and it can therefore be used to predict the geographical distribution of A. senticosus. The results suggested that the ecological adaptation area of A. senticosus was mainly concentrated in the Changbai mountains and the southeast part of Xiaoxing′anling mountains. The total area of the suitable regions was approximately 221200 km~2. The main environmental factors that affect the geographical distribution of A. senticosus were successive annual mean precipitation, forest type, extreme minimum temperature, growing season precipitation, and altitude. This paper, combined with large-scale environmental data, vegetation community types, and the distribution of A. senticosus, will enable the assessment of the ecological adaptation area of A. senticosus and the determination of the dominant environmental factors. These results will provide a scientific basis for population recovery and utilization of A. senticosus.
The maximum entropy model(MaxEnt) and geographic information system(GIS) were used to predict the suitable ecological region for A. senticosus based on 267 plots and 17 ecological factors. The results showed that the area under the receiver operator characteristic curve(AUC) reached 0.929. The accuracy of model prediction results was high and it can therefore be used to predict the geographical distribution of A. senticosus. The results suggested that the ecological adaptation area of A. senticosus was mainly concentrated in the Changbai mountains and the southeast part of Xiaoxing′anling mountains. The total area of the suitable regions was approximately 221200 km~2. The main environmental factors that affect the geographical distribution of A. senticosus were successive annual mean precipitation, forest type, extreme minimum temperature, growing season precipitation, and altitude. This paper, combined with large-scale environmental data, vegetation community types, and the distribution of A. senticosus, will enable the assessment of the ecological adaptation area of A. senticosus and the determination of the dominant environmental factors. These results will provide a scientific basis for population recovery and utilization of A. senticosus.
引文
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[12] 梁燕,刘爱军,邢旗,常书娟.反距离权重内插法在内蒙古天然草原植被盖度监测中的应用//2009中国草原发展论坛论文集.合肥:农业部草原监理中心,中国草学会,2009:6.
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[19] 高蓓,卫海燕,郭彦龙,顾蔚.应用GIS和最大熵模型分析秦岭冷杉潜在地理分布.生态学杂志,2015,34(3):843- 852.
[20] 杨文鹏,张立东,张俭峰,姜海洋,吕石佳,李新鹏,万太平.东北地区新开岭-科洛杂岩变形规律与成因[J/OL].地球科学,2018:1- 21.[2018-09- 17].http://kns.cnki.net/kcms/detail/42.1874.P.20180228.1312.004.html.
[21] 孟祥才,都晓伟,孙晖,王喜军,袁野,韩莹.野生刺五加分布规律调查.现代中药研究与实践,2009,23(4):6- 7.
[22] 晏寒冰,吴军,李建林,唐旭清.东北地区主要森林物种的分布区气候数据分析.生物数学学报,2016,31(1):118- 128.
[23] 徐燃,吴杰,董林林,徐江,陈平,刘淼,黄林芳,陈士林.刺五加全球产地生态适宜性及品质生态学研究.药学学报,2018,53(2):313- 320.
[24] 曹建国.刺五加生活史型特征及其形成机制的研究[D].哈尔滨:东北林业大学,2004.
[25] 金慧,尹航,赵莹,刘丽杰,代玉红,邴贵平,刘颖.长白山区野生刺五加种群结构与数量特征分析.吉林林业科技,2017,46(5):1- 5,16- 16.
[26] 唐策,文检,张雯,苏锦松,谢彩香,张艺.基于最大熵模型的藏药翼首草生态适宜性研究.中国中药杂志,2017,42(10):1871- 1876.
[2] 祝宁,王义弘.刺五加生殖生态学的研究(Ⅱ)——种子扩散、种子库及更新.东北林业大学学报,1992,20(5):12- 17.
[3] 刘德旺,谷彩梅,杨庆珍,黄林芳,谢彩香,蔡敏.内蒙古地区道地药材蒙古黄芪资源调查及产地适宜性.应用生态学报,2016,27(3):838- 844.
[4] Patterson B D.Contingency and determinism in mammalian biogeography:the role of history.Journal of Mammalogy,1999,80(2):345- 360.
[5] Peterson A T,Cohoon K P.Sensitivity of distributional prediction algorithms to geographic data completeness.Ecological Modelling,1999,117(1):159- 164.
[6] Underwood E C,Klinger R,Moore P E.Predicting patterns of non-native plant invasions in Yosemite National Park,California,USA.Diversity and Distributions,2004,10(5/6):447- 459.
[7] Li W J,Wang Z J,Ma Z J,Tang H X.A regression model for the spatial distribution of red-crown crane in Yancheng Biosphere Reserve,China.Ecological Modelling,1997,103(2/3):115- 121.
[8] 马松梅,张明理,张宏祥,孟宏虎,陈曦.利用最大熵模型和规则集遗传算法模型预测孑遗植物裸果木的潜在地理分布及格局.植物生态学报,2010,34(11):1327- 1335.
[9] 陈铁柱,刘建辉,周先建,张美,辜彬,廖述吉.基于MaxEnt和ArcGIS预测合欢潜在分布及适宜性评价.北方园艺,2017,41 (16):191- 195.
[10] 刘光孟,汪云甲,王允.反距离权重插值因子对插值误差影响分析.中国科技论文在线,2010,5(11):879- 884.
[11] 刘文岭,李伟,刘洋.空间插值法对渤海天津海域海水盐度分布的影响.盐业与化工,2010,39(2):43- 46.
[12] 梁燕,刘爱军,邢旗,常书娟.反距离权重内插法在内蒙古天然草原植被盖度监测中的应用//2009中国草原发展论坛论文集.合肥:农业部草原监理中心,中国草学会,2009:6.
[13] Swets J A.Measuring the accuracy of diagnostic systems.Science,1988,240(4857):1285- 1293.
[14] 徐军,曹博,白成科.基于MaxEnt濒危植物独叶草的中国潜在适生分布区预测.生态学杂志,2015,34(12):3354- 3359.
[15] 吴庆明,王磊,朱瑞萍,杨宇博,金洪阳,邹红菲.基于MAXENT模型的丹顶鹤营巢生境适宜性分析——以扎龙保护区为例.生态学报,2016,36(12)3758- 3764.
[16] 张飞,陈随清,王利丽,张涛,张小波,朱寿东.基于Maxent和ArcGIS的山茱萸生态适宜性区划研究.中国中药杂志,2017,42(16):3078- 3083.
[17] Phillips S J,Anderson R P,Schapire R E.Maximum entropy modeling of species geographic distributions.Ecological Modelling,2006,190(3/4):231- 259.
[18] 张东方,张琴,郭杰,孙成忠,吴杰,聂祥,谢彩香.基于MaxEnt模型的当归全球生态适宜区和生态特征研究.生态学报,2017,37(15):5111- 5120.
[19] 高蓓,卫海燕,郭彦龙,顾蔚.应用GIS和最大熵模型分析秦岭冷杉潜在地理分布.生态学杂志,2015,34(3):843- 852.
[20] 杨文鹏,张立东,张俭峰,姜海洋,吕石佳,李新鹏,万太平.东北地区新开岭-科洛杂岩变形规律与成因[J/OL].地球科学,2018:1- 21.[2018-09- 17].http://kns.cnki.net/kcms/detail/42.1874.P.20180228.1312.004.html.
[21] 孟祥才,都晓伟,孙晖,王喜军,袁野,韩莹.野生刺五加分布规律调查.现代中药研究与实践,2009,23(4):6- 7.
[22] 晏寒冰,吴军,李建林,唐旭清.东北地区主要森林物种的分布区气候数据分析.生物数学学报,2016,31(1):118- 128.
[23] 徐燃,吴杰,董林林,徐江,陈平,刘淼,黄林芳,陈士林.刺五加全球产地生态适宜性及品质生态学研究.药学学报,2018,53(2):313- 320.
[24] 曹建国.刺五加生活史型特征及其形成机制的研究[D].哈尔滨:东北林业大学,2004.
[25] 金慧,尹航,赵莹,刘丽杰,代玉红,邴贵平,刘颖.长白山区野生刺五加种群结构与数量特征分析.吉林林业科技,2017,46(5):1- 5,16- 16.
[26] 唐策,文检,张雯,苏锦松,谢彩香,张艺.基于最大熵模型的藏药翼首草生态适宜性研究.中国中药杂志,2017,42(10):1871- 1876.
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