Chin J Plant Ecol ›› 2019, Vol. 43 ›› Issue (4): 273-283.doi: 10.17521/cjpe.2018.0237

• Reviews •     Next Articles

Research advances in modelling plant species distribution in China

LIU Xiao-Tong1,YUAN Quan1,NI Jian1,2,*()   

  1. 1 College of Chemistry and Life Sciences, Zhejiang Normal University, Jinhua, Zhejiang 321004, China
    2 Jinhua Mountain Observation and Research Station for Subtropical Forest Ecosystems, Jinhua, Zhejiang 321004, China
  • Received:2018-09-25 Revised:2019-03-20 Online:2019-04-23 Published:2019-04-20
  • Contact: NI Jian ORCID:0000-0001-6198-4849
  • Supported by:
    Supported by the National Natural Science Foundation of China(41471049)


Species distribution models (SDMs) have been extensively used in simulations of geographical distribution of animal and plant species during the past 20 years. Taking the simulation of plant species distribution as an example, we used both the digitized and library databases including the China National Knowledge Infrastructure (CNKI), the VIP Chinese Journal Database (VIP) and the Web of Science (WoS) to compile available literatures published from 2000 to 2018. The number of publications, SDMs used, target plant species, data sources, and the purpose of studies about using various SDMs to simulate plant species distribution in China was statistically investigated. In total 366 publications were collected. Further analysis and synthesis showed that the application of SDMs in simulating Chinese plant species distribution has developed rapidly since 2011, especially during the past five years. SDMs have been used in studies of ecology, Chinese traditional medicine, agriculture, and forestry. The Maximum Entropy Model (MaxEnt) is the most widely used model among 33 commonly used SDMs. A half of the studies use climate data only, and another half of the studies use both climate, soil and topography data. The source of both environmental data and plant distribution data are diverse, derived from international and domestic databases. In these studies, researchers have simulated the distribution of 562 plant species, in which 52.7% are woody species and 41.8% are herbaceous species, including a large number of Chinese medicinal plants, fruit trees, garden plants, and crops. Studies aim mainly on two aspects, i.e. the impact of climate change on plant species distribution and their predicted pattern in the past, present, and future climate scenarios, and the assessment of the potential distribution of plant species and biodiversity trends (including the risk of invasive species). In future studies, more attention should be paid to both the basic science on the modelling of potential distribution of plant species and the impact from climate change, and the applied science on the prediction of suitable distribution area of plant species in order to popularize their plantation. More applications of SDMs in multiple disciplines and in multiple industries such as ecology, forestry, crop science and Chinese traditional medicine should be further developed. Joint simulations and inter-comparisons using multiple plant species, more SDMs and multiple data sources of environmental data, as well as the development of new and mechanism SDMs are encouraged. The extension of model applications in new research fields is also needed.

Key words: species distribution models, climate change, biodiversity conservation, potential distribution area, Maximum Entropy Model

Fig. 1

Number of papers about the distribution of plant species simulated by species distribution models in China."

Table 1

Top journals publishing articles of plant distribution modelling from China (from 2001-01 to 2018-01)"

of papers published
1 中国中药杂志
China Journal of Chinese Materia Medica
2 植物生态学报 Chinese Journal of Plant Ecology 15
3 生态学报 Acta Ecologica Sinica 14
4 应用生态学报 Chinese Journal of Applied Ecology 13
5 生态学杂志 Chinese Journal of Ecology 12
7 林业科学 Scientia Silvae Sinica 7
8 中药材 Journal of Chinese Medicinal Materials 6
生物多样性 Biodiversity Science 6
9 生物安全学报 Journal of Biosafety 5
广东农业科学 Guangdong Agricultural Sciences 5
草业学报 Acta Prataculturae Sinica 5
Scientific Reports 5
10 广西植物 Guihaia 4
Ecology and Evolution 4
Polish Journal of Ecology 4

Table 2

Statistics of publications modeling plant species in China using species distribution models"

Number of
Number of
最大熵模型 Maximum Entropy Model (MaxEnt)
基于规则集的遗传算法 Genetic Algorithm for Rule-set
Prediction (GARP)
生物气候模型 BIOCLIM
广义线性模型 Generalized Linear Model (GLM)
广义相加模型 Generalized Additive Model (GAM)
随机森林 Random Forest (RF)
推进式回归树 Generalized Boosted Regression Models/Boosted Regression Tree (GBM/BRT)
多元适应回归样条函数 Multivariate Adaptive Regression Splines (MARS)
人工神经网络 Artificial Neural Network (ANN)
柔性判别分析 Flexibled Discriminant Analysis (FDA)
支持向量机 Support Vector Machine (SVM)
分类树分析 Classification Tree Analysis (CTA)
分类回归树 Classification and Regression Tree (CART)
表面分布区分室模型 Surface Range Envelope (SRE)
复合型广义相加模型运算系 Mixed GAM Computation
Vehicle (MGCV)



拟合神经网络 Fit Neural Networks (NNET)
循环分区回归树 Recursive Partitioning and Regression Trees (RPART)
Logistic回归模型 Logistic Regression (LR)
作物生态需求 Crop Ecological Requirements (ECOCROP)
农业生态区模型 Agriculture Ecological Zone Model (AEZ)
决策树模型 Classification Tree Model (CT)
生态位因子分析模型 Ecological Niche Factor Analysis (ENFA)
生境适生性模型 Habitat Suitability Model (HSM)
线性判别分析 Linear Discriminant Analysis (LDA)
马氏距离 Mahalanobis Distance (MAHAL)
迭代决策树算法 Multiple Additive Regression Tree (MART)
空间明晰物种组合模型 Spatially Explicit Species Assemblage Model (SESAM)
n维环境资源模型 n-Dimentional Environment and Resource Model
生态位模型 Niche model
随机预测模型 Random Predictive model




Fig. 2

Number of species distribution models used in modelling China’s plant species distribution. The small plot is the number of models with MaxEnt excluded. See Table 2 for models."

[1] Araújo MB, Peterson AT (2012). Uses and misuses of bioclimatic envelope modeling. Ecology, 93, 1527-1539.
[2] Busby J ( 1991). BIOCLIM—A bioclimate analysis and prediction system. Plant Protection Quarterly, 6, 8-9.
[3] Chen XM, Lei YC, Zhang XQ, Jia HY ( 2012). Effects of sample sizes on accuracy and stability of maximum entropy model in predicting species distribution. Scientia Silvae Sinicae, 48(1), 53-59.
doi: 10.11707/j.1001-7488.20120110
[ 陈新美, 雷渊才, 张雄清, 贾宏炎 ( 2012). 样本量对MaxEnt模型预测物种分布精度和稳定性的影响. 林业科学, 48(1), 53-59.]
doi: 10.11707/j.1001-7488.20120110
[4] Cui XQ, Ma HP, Huang GL, Hou M, Xu M, Zheng GQ, Cui BX, Zhuo L, Liao CZ ( 2016). Research on the land suitable for planting 6 major tree species in Qinghai Province. Forest Resources Management, ( 4), 74-78.
[ 崔雪晴, 马红萍, 黄桂林, 侯盟, 徐明, 郑国强, 崔北祥, 卓凌, 廖成章 ( 2016). 青海省6个主要树种适宜造林地研究. 林业资源管理, ( 4), 74-78.]
[5] Dai G, Yang J, Lu S, Huang C, Jin J, Jiang P, Yan P ( 2018). The potential impact of invasive woody oil plants on protected areas in China under future climate conditions. Scientific Reports, 8, 1041. DOI: 10.1038/s41598-018-‌19477-w.
[6] Elith J, Leathwick JR ( 2009). Species distribution models: Ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 40, 677-697.
[7] Fang JY, Wang ZH, Tang ZY (2011). Atlas of Woody Plants in China:Distribution and Climate. Higher Education Press, Beijing.
[ 方精云, 王志恒, 唐志尧 (2011). 中国木本植物分布图集. 高等教育出版社, 北京.]
[8] Gao B, Wei HY, Guo YL, Gu W ( 2015). Using GIS and MaxEnt to analyze the potential distribution of Abies chensiensis. Chinese Journal of Ecology, 34, 843-852.
[ 高蓓, 卫海燕, 郭彦龙, 顾蔚 (2015). 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, 34, 843-852.]
[9] Guisan A, Thuiller W ( 2005). Predicting species distribution: Offering more than simple habitat models. Ecology Letters, 8, 993-1009.
[10] Harris I, Jones PD, Osborn TJ, Lister DH ( 2014). Updated high-resolution grids of monthly climatic observations—‌The CRU TS3.10 Dataset. International Journal of Climatology, 34, 623-642.
[11] He Q, Zhou G ( 2012). The climatic suitability for maize cultivation in China. Chinese Science Bulletin, 57, 395-403.
[12] Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A ( 2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978.
[13] Huang MY, Kong XQ, Duan RY, Wu GL, Zhang ZX ( 2016). The basic principle of virtual species and its application to evaluations of species distribution models. Acta Ecologica Sinica, 36, 2460-2470.
[ 黄敏毅, 孔晓泉, 段仁燕, 吴甘霖, 张中信 ( 2016). 虚拟物种的基本原理及其在物种分布模型评估中的应用. 生态学报, 36, 2460-2470.]
[14] Jia X, Ma FF, Zhou WM, Zhou L, Yu DP, Qin J, Dai LM ( 2017). Impacts of climate change on the potential geographical distribution of broadleaved Korean pine (Pinus koraiensis) forests. Acta Ecologica Sinica, 37, 464-473.
[ 贾翔, 马芳芳, 周旺明, 周莉, 于大炮, 秦静, 代力民 ( 2017). 气候变化对阔叶红松林潜在地理分布区的影响. 生态学报, 37, 464-473.]
[15] Jiang X, Ni J ( 2005). Species-climate relationships of 10 desert plant species and their estimated potential distribution range in the arid lands of northwestern China. Acta Phytoecologica Sinica, 29, 98-107.
[ 蒋霞, 倪健 ( 2005). 西北干旱区10种荒漠植物地理分布与大气候的关系及其可能潜在分布区的估测. 植物生态学报, 29, 98-107.]
[16] Li GQ ( 2011). Evaluation the Ecological Niche Models and Predicting Species Potential Distribution Area. PhD dissertation, Institute of Botany, Chinese Academy of Sciences,Beijing.
[ 李国庆 ( 2011). 物种生态位模型的适用性评价和物种潜在分布区预测. 博士学位论文, 中国科学院植物研究所, 北京.]
[17] Li GQ, Liu CC, Liu YG, Yang J, Zhang XS, Guo K ( 2013). Advances in theoretical issues of species distribution models. Acta Ecologica Sinica, 33, 4827-4835.
[ 李国庆, 刘长成, 刘玉国, 杨军, 张新时, 郭柯 ( 2013). 物种分布模型理论研究进展. 生态学报, 33, 4827-4835.]
[18] Li Y, Yan HF, Ge XJ ( 2012). Phylogeographic analysis and environmental niche modeling of widespread shrub Rhododendron simsii in China reveals multiple glacial refugia during the last glacial maximum. Journal of Systematics and Evolution, 50, 362-373.
[19] Liu SJ, Zhou GS, Fang SB, Zhang JH ( 2015). Effects of future climate change on climatic suitability of rubber plantation in China. Chinese Journal of Applied Ecology, 26, 2083-2090.
[ 刘少军, 周广胜, 房世波, 张京红 ( 2015). 未来气候变化对中国天然橡胶种植气候适宜区的影响. 应用生态学报, 26, 2083-2090.]
[20] Luo M, Wang H, Lü Z ( 2017). Evaluating the performance of species distribution models Biomod2 and MaxEnt using the giant panda distribution data. Chinese Journal of Applied Ecology, 28, 4001-4006.
[ 罗玫, 王昊, 吕植 ( 2017). 使用大熊猫数据评估Biomod2和MaxEnt分布预测模型的表现. 应用生态学报, 28, 4001-4006.]
[21] Ma SM, Zhang ML, Zhang HX, Meng HH, Chen X ( 2010). Predicting potential geographical distributions and patterns of the relic plant Gymnocarpos przewalskii using Maximum Entropy and Genetic Algorithm for Rule-set Prediction. Chinese Journal of Plant Ecology, 34, 1327-1335.
[ 马松梅, 张明理, 张宏祥, 孟宏虎, 陈曦 ( 2010). 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, 34, 1327-1335.]
[22] Mao LH, Li Y, Liu C, Fang YM ( 2017). Predication of potential distribution of Haplocladium microphyllum in China based on MaxEnt model. Chinese Journal of Ecology, 36, 54-60.
[ 毛俐慧, 李垚, 刘畅, 方炎明 ( 2017). 基于MaxEnt模型预测细叶小羽藓在中国的潜在分布区. 生态学杂志, 36, 54-60.]
[23] New M, Lister D, Hulme M, Makin I ( 2002). A high-resolution data set of surface climate over global land areas. Climate Research, 21, 1-25.
[24] Ni J ( 2002). BIOME models: Main principles and applications. Acta Phytoecologica Sinica, 26, 481-488.
[ 倪健 ( 2002). BIOME系列模型: 主要原理与应用. 植物生态学报, 26, 481-488.]
[25] Ni J ( 2017). An introduction to bioclimatic factors in global change research. Quaternary Sciences, 37, 431-441.
[ 倪健 ( 2017). 全球变化研究中的生物气候指标. 第四纪研究, 37, 431-441.]
[26] Nix H, McMahon J, Mackenzie D , (1977). Potential areas of production and the future of pigeon pea and other grain legumes in Australia. In: Wallis ES, Whiteman PC eds. The Potential for Pigeon Pea in Australia: Proceedings of Pigeon Pea (Cajanus cajan (L.) Millsp.). University of Queensland,Queensland. 1-12.
[27] Peng SZ, Zhao CY, Xu ZL, Ashiq MW ( 2016). Restoration and conservation potential of destroyed Qinghai spruce (Picea crassifolia) forests in the Qilian Mountains of northwest China. Mitigation and Adaptation Strategies for Global Change, 21, 153-165.
[28] Peng SZ, Zhao CY, Xu ZL, Wang C, Liu YY ( 2011). Potential distribution of Qinghai spruce and assessment of its growth status in the upper reaches of the Heihe River in the Qilian Mountains of China. Chinese Journal of Plant Ecology, 35, 605-614.
[ 彭守璋, 赵传燕, 许仲林, 王超, 柳逸月 ( 2011). 黑河上游祁连山区青海云杉生长状况及其潜在分布区的模拟. 植物生态学报, 35, 605-614.]
[29] Phillips SJ, Anderson RP, Dudík M, Schapire RE, Blair ME ( 2017). Opening the black box: An open-source release of Maxent. Ecography, 40, 887-893.
[30] Phillips SJ, Anderson RP, Schapire RE ( 2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259.
[31] Svenning JC, Fløjgaard C, Marske KA, Nógues-Bravo D, Normand S ( 2011). Applications of species distribution modeling to paleobiology. Quaternary Science Reviews, 30, 2930-2947.
[32] Svenning JC, Skov F ( 2004). Limited filling of the potential range in European tree species. Ecology Letters, 7, 565-573.
[33] Wan JZ, Wang CJ, Han SJ, Yu JH ( 2014). Planning the priority protected areas of endangered orchid species in northeastern China. Biodiversity and Conservation, 23, 1395-1409.
[34] Wan JZ, Wang CJ, Yu FH ( 2017). Spatial conservation prioritization for dominant tree species of Chinese forest communities under climate change. Climatic Change, 144, 303-316.
[35] Wang C, Lin HL, Feng QS, Jin CY, Cao AC, He L ( 2017a). A new strategy for the prevention and control of Eupatorium adenophorum under climate change in China. Sustainability, 9, 2037. DOI: 10.3390/su9112037.
[36] Wang D, Wei HY, Yang Y, Shang ZH, Gu W ( 2017). MaxEnt and GIS for predicting the potential distribution of Bupleurum marginatum. Journal of Chinese Medicinal Materials, 40, 301-305.
[ 王丹, 卫海燕, 杨洋, 尚忠慧, 顾蔚 ( 2017). 基于MaxEnt和GIS的竹叶柴胡适生区分布预测. 中药材, 40, 301-305.]
[37] Wang J, Ni J ( 2006). Review of modelling the distribution of plant species. Journal of Plant Ecology (Chinese Version), 30, 1040-1053.
[ 王娟, 倪健 ( 2006). 植物种分布的模拟研究进展. 植物生态学报, 30, 1040-1053.]
[38] Wang LH, Yang JX, Xu XN ( 2015). Analysis of suitable bioclimatic characteristics of Pseudolarix amabilis by using MaxEnt model. Scientia Silvae Sinicae, 51(1), 127-131.
doi: 10.11707/j.1001-7488.20150115
[ 王雷宏, 杨俊仙, 徐小牛 ( 2015). 基于MaxEnt分析金钱松适生的生物气候特征. 林业科学, 51(1), 127-131.]
doi: 10.11707/j.1001-7488.20150115
[39] Wang R, Wan FH ( 2016). Predicting the potential invasive distribution and early-warning monitoring management of Solanum elaeagnifolium in China. Chinese Journal of Ecology, 35, 1697-1703.
[ 王瑞, 万方浩 ( 2016). 入侵植物银毛龙葵在中国的适生区预测与早期监测预警. 生态学杂志, 35, 1697-1703.]
[40] Wang SY, Xu XT, Shrestha N, Zimmermann NE, Tang ZY, Wang ZH ( 2017b). Response of spatial vegetation distribution in China to climate changes since the Last Glacial Maximum (LGM). PLOS ONE, 12, e0175742. DOI: 10.1371/journal.pone.0175742.
[41] Wang YH, Jiang WM, Comes HP, Hu FS, Qiu YX, Fu CX ( 2015). Molecular phylogeography and ecological niche modelling of a widespread herbaceous climber,Tetrastigma hemsleyanum(Vitaceae): Insights into Plio- Pleistocene range dynamics of evergreen forest in subtropical China. New Phytologist, 206, 852-867.
[42] Xing DL, Hao ZQ ( 2011). The principle of maximum entropy and its applications in ecology. Biodiversity Science, 19, 295-302.
[ 邢丁亮, 郝占庆 ( 2011). 最大熵原理及其在生态学研究中的应用. 生物多样性, 19, 295-302.]
[43] Xu ZL, Peng HH, Peng SZ ( 2015). The development and evaluation of species distribution models. Acta Ecologica Sinica, 35, 557-567.
[ 许仲林, 彭焕华, 彭守璋 ( 2015). 物种分布模型的发展及评价方法. 生态学报, 35, 557-567.]
[44] Xu ZL, Zhao CY, Feng ZD ( 2011). Species potential distribution models and evaluation based on dissimilarity index of variables of Qinghai spruce (Picea crassifolia) in Qilian mountains. Journal of Lanzhou University (Nature Sciences), 47, 55-63.
[ 许仲林, 赵传燕, 冯兆东 ( 2011). 祁连山青海云杉林物种分布模型与变量相异指数. 兰州大学学报(自然科学版), 47, 55-63.]
[45] Xu ZL, Zhao CY, Feng ZD ( 2012). Species distribution models to estimate the deforested area of Picea crassifolia in arid region recently protected: Qilian Mts. National Natural Reserve (China). Polish Journal of Ecology, 60, 515-524.
[46] Xu ZL, Zhao CY, Feng ZD, Peng HH, Wang C (2009). The impact of climate change on potential distribution of species in semi-arid region: A case study of Qinghai spruce (Picea crassifolia) in Qilian Mountain, Gansu Province, China. In: 2009 IEEE International Geoscience and Remote Sensing Symposium, Cape Town. 412-415.
[47] Yan HF, Zhang CY, Wang FY, Hu CM, Ge XJ, Hao G (2012). Population expanding with the phalanx model and lineages split by environmental heterogeneity: A case study of Primula obconica in subtropical China. PLOS ONE, 7, e41315. DOI: 10.1371/journal.pone.0041315.
[48] Ye YC, Zhou GS, Yin XJ ( 2016). Changes in distribution and productivity of steppe vegetation in Inner Mongolia during 1961 to 2010: Analysis based on MaxEnt model and synthetic model. Acta Ecologica Sinica, 36, 4718-4728.
[ 叶永昌, 周广胜, 殷晓洁 ( 2016). 1961-2010年内蒙古草原植被分布和生产力变化——基于MaxEnt模型和综合模型的模拟分析. 生态学报, 36, 4718-4728.]
[49] Zhang L ( 2015). Application of MaxEnt in predicting potential distribution of species. Bulletin of Biology, 50, 9-12.
[ 张路 ( 2015). MAXENT最大熵模型在预测物种潜在分布范围方面的应用. 生物学通报, 50, 9-12.]
[50] Zhang L, Liu SR, Sun PS, Wang TL, Wang GY, Zhang XD, Wang LL ( 2015). Consensus forecasting of species distributions: The effects of niche model performance and niche properties. PLOS ONE, 10, e0120056. DOI: 10.1371/ ‌journal.‌pone.0120056.
[51] Zhang MG, Slik JF, Ma KP ( 2017). Priority areas for the conservation of perennial plants in China. Biological Conservation, 210, 56-63.
[52] Zhang MG, Zhou ZK, Chen WY, Cannon CH, Raes N, Slik JF ( 2014). Major declines of woody plant species ranges under climate change in Yunnan, China. Diversity and Distributions, 20, 405-415.
[53] Zhang MG, Zhou ZK, Chen WY, Slik JF, Cannon CH, Raes N (2012). Using species distribution modeling to improve conservation and land use planning of Yunnan, China. Biological Conservation, 153, 257-264.
[54] Zhao ZF, Wei HY, Guo YL, Gu W (2016). Potential distribution of Panax ginseng and its predicted responses to climate change. Chinese Journal of Applied Ecology, 27, 3607-3615.
[ 赵泽芳, 卫海燕, 郭彦龙, 顾蔚 ( 2016). 人参潜在地理分布以及气候变化对其影响预测. 应用生态学报, 27, 3607-3615.]
[55] Zhong GP ( 2008). Predicting the Potential Distribution of Invasive Alien Weeds in China. Master degree dissertation, Southwest University, Chongqing.
[ 钟艮平 ( 2008). 几种外来入侵杂草在我国的潜在分布预测. 硕士学位论文, 西南大学, 重庆.]
[56] Zhou J, Li QY, Xiao L, Jiang JX, Yi ZL ( 2012). Potential distribution of Miscanthus sinensis and M. floridulus in China. Chinese Journal of Plant Ecology, 36, 504-510.
[ 周婧, 李巧云, 肖亮, 蒋建雄, 易自力 ( 2012). 芒和五节芒在中国的潜在分布. 植物生态学报, 36, 504-510.]
[57] Zhu GP, Liu GQ, Bu WJ, Gao YB ( 2013). Ecological niche modeling and its applications in biodiversity conservation. Biodiversity Science, 21, 90-98.
[ 朱耿平, 刘国卿, 卜文俊, 高玉葆 ( 2013). 生态位模型的基本原理及其在生物多样性保护中的应用. 生物多样性, 21, 90-98.]
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[3] . Changes of potential geographical distribution for Tsoongiodendron odorum since Last Glacial Maximum [J]. Chin J Plant Ecol, 2020, 44(1): 0-0.
[4] Xiaoyun Shi, Xiaogang Shi, Qiang Hu, Tianpei Guan, Qiang Fu, Jian Zhang, Meng Yao, Sheng Li. Evaluating the potential habitat overlap and predation risk between snow leopards and free-range yaks in the Qionglai Mountains, Sichuan [J]. Biodiv Sci, 2019, 27(9): 951-959.
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[13] Xiuwei Liu, Douglas Chesters, Chunsheng Wu, Qingsong Zhou, Chaodong Zhu. A horizon scan of the impacts of environmental change on wild bees in China [J]. Biodiv Sci, 2018, 26(7): 760-765.
[14] Xiangyu Jia,Bin Bai,Jieqing Zhang,Yi Huang. The effects of IPBES deliverables on global biodiversity conservation strategy—an analysis based on the U. S. pollinator protection policy [J]. Biodiv Sci, 2018, 26(5): 527-534.
[15] ZHOU Tong,CAO Ru-Yin,WANG Shao-Peng,CHEN Jin,TANG Yan-Hong. Responses of green-up dates of grasslands in China and woody plants in Europe to air temperature and precipitation: Empirical evidences based on survival analysis [J]. Chin J Plan Ecolo, 2018, 42(5): 526-538.
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[1] Kang Le. The Chemical Defenses of plants to phytophagous Insects[J]. Chin Bull Bot, 1995, 12(04): 22 -27 .
[2] HUANG Kai-Yao;GUO Hou-Liang and YI Ping. Effects of Salt Stress on Cell Structure and N2 Fixation in Blue-Green Alga Anabaena cylindrica[J]. Chin Bull Bot, 1998, 15(03): 54 -56 .
[3] Zhang Jing-tan. Abbreviations for Some Commonly Used Term[J]. Chin Bull Bot, 1985, 3(01): 57 -58 .
[4] DU Gui-Sen;ZANG Yu-Long and WANG Mei-Zhi. Study on Spore Morphology of 6 Species of The Family Pottiaceae in China[J]. Chin Bull Bot, 1998, 15(03): 57 -60 .
[5] TIAN Xin-Zhi. On Plant Illustration and Artistic Drawing and Painting[J]. Chin Bull Bot, 1999, 16(04): 470 -476 .
[6] LI Xiu-Lan WU Cheng DENG Xiao-Jian YANG Zhi-Rong. Plant Height Genes and Their Progress of Molecular Biology Research in Rice[J]. Chin Bull Bot, 2003, 20(03): 264 -269 .
[7] LIU Hong-Tao LI Bing ZHOU Ren-Gang. Calcium_calmodulin Signal Transduction Pathway and Environment Stimulation[J]. Chin Bull Bot, 2001, 18(05): 554 -559 .
[8] Renyi Gui;Yadi Liu;Xiaoqin Guo;Haibao Ji;Yue Jia;Mingzeng Yu;Wei Fang*. Effects of Dose of 137Cs-γ Irradiation on Chlorophyll Fluorescence Parameters for Leaves of Seedlings of Phyllostachys heterocycla ‘Pubescens’[J]. Chin Bull Bot, 2010, 45(01): 66 -72 .
[9] Sanxiong Fu;Cunkou Qi*. Identification of Genes Differentially Expressed in Seeds of Brassica napus Planted in Nanjing and Lhasa by Arabidopsis Microarray[J]. Chin Bull Bot, 2009, 44(02): 178 -184 .
[10] Xiaofen Sun;Yu Chen;Junsong Pan;Yuliang Wang;Kexing Sun;Kexuan Tang*;Run Cai*. Correlation and Path Analyses of Vindoline with Major Agronomic Traits in Catharanthus roseus[J]. Chin Bull Bot, 2009, 44(01): 96 -102 .