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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
引用本文: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[J].植物生态学报,2010,34(11):1327-1335.
作者姓名:马松梅  张明理  张宏祥  孟宏虎  陈曦
作者单位:中国科学院干旱区生物地理与生物资源重点实验室, 中国科学院新疆生态与地理研究所
中国科学院研究生院
中国科学院植物研究所
新疆遥感与地理信息系统应用实验室, 中国科学院新疆生态与地理研究所
基金项目:中国科学院新疆生态与地理研究所"百人计划"项目资助
摘    要:利用野外调查的16个居群分布点和7个环境因子图层,选择最大熵模型(MAXENT)和规则集遗传算法模型(GARP),在地理和环境空间上模拟了第三纪孑遗植物裸果木(Gymnocarpos przewalskii)在中国西北地区的潜在分布。结果表明:(1)裸果木的潜在适生区全部集中在西北荒漠区,其中最佳适生区主要集中在3个区域,一是河西走廊中部和玉门以西、宁夏北部及内蒙古乌拉特后旗;二是塔里木盆地西北缘;三是柴达木盆地西北缘两片极小的高度适生区。裸果木的生态位被确定在一个较广的干旱环境空间:适生区极端最高气温基本上在29.2–36.8℃之间,极端最低气温在–18.3至–13.4℃之间;年平均降水量40–200mm;潜在蒸发率在3–15之间。(2)MAXENT和GARP模型都较好地预测了裸果木的潜在分布,但GARP产生了相对较大、较连续的潜在分布区,部分过预测了破碎化生境;而MAXENT预测到的潜在分布区,在不同区域具有不同的环境适生性指数,而且成功地排除了不合理的破碎化分布,从而更直观地展示了裸果木的潜在分布格局和生态位要求。

关 键 词:规则集遗传算法模型  裸果木  留一法  最大熵模型  潜在分布区
收稿时间:2010-05-19
修稿时间:2010-08-11

Predicting potential geographical distributions and patterns of the relic plant Gymnocarpos przewalskii using Maximum Entropy and Genetic Algorithm for Rule-set Prediction
MA Song-Mei,ZHANG Ming-Li,ZHANG Hong-Xiang,MENG Hong-Hu,CHEN Xi.Predicting potential geographical distributions and patterns of the relic plant Gymnocarpos przewalskii using Maximum Entropy and Genetic Algorithm for Rule-set Prediction[J].Acta Phytoecologica Sinica,2010,34(11):1327-1335.
Authors:MA Song-Mei  ZHANG Ming-Li  ZHANG Hong-Xiang  MENG Hong-Hu  CHEN Xi
Affiliation:Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences

Graduate University of Chinese Academy of Sciences

Institute of Botany, Chinese Academy of Sciences

Xinjiang Laboratory of Geographic Information System and Remote Sensing Application, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences
Abstract:Aims Understanding the geographical distribution and patterns of endemic species is critical to biodiversity conservation and biogeographical history reconstruction of the area occupied by the species. The ecological niche models (ENMs) are useful techniques to explore the links between the species distribution and the environmental data. The displayed potential habitats for the species, in turn can enable the examination of the predictive abilities of various ENMs. We attempt to determine the potential geographic distributions of the Tertiary relic plant Gymnocarpos przewalskii based on the model of maximum entropy (MAXENT) and genetic algorithm for rule-set prediction (GARP). Methods Based on sixteen sampled localities and seven environmental layers (isothermality, maximum temperature, minimum temperature, annual precipitation, potential evapotranspiration ratio (PER), altitude and soil types), we conducted predictions of G. przewalskii using MAXENT and GARP models. The spatial distribution maps of G. przewalskii with the different environmental suitable values (MAXENT) or overlap index (GARP) displayed the distribution patterns clearly. Important findings The potential distributions of G. przewalskii with the highest environment suitability are predicted at first in the middle of Hexi corridor and the western Yumen of Gansu Province, the north of Ningxia-Hui Autonomous Region, and the part of the Wulate banner of Inner Mongolia in China. The others are mainly in northwestern Tarim Basin and small isolated areas in northwestern Qaidam Basin. Both MAXENT and GARP produced good predictions for G. przewalskii. However, GARP predicted larger and more continuous suitable habitats around the species’ locations and some isolated and fragmented spatial predictions where the species has never been found or collected before. MAXENT predicted a distribution that is a logical proportion of the study area and removed most of the unlikely isolated habitats.
Keywords:Genetic Algorithm for Rule-set Prediction (GARP)  Gymnocarpos przewalskii  leave one out  Maximum Entropy (MAXENT)  potential geographic distribution
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