Bo Dong, Jianwei Li, Jie Lin, Feilong Zhang. Predication of Potential Distribution of Toxicodendron vernicifluum in China Based on MaxEnt Model[J]. Journal of Southwest Forestry University, 2020, 40(2): 79-85. DOI: 10.11929/j.swfu.201902069
Citation: Bo Dong, Jianwei Li, Jie Lin, Feilong Zhang. Predication of Potential Distribution of Toxicodendron vernicifluum in China Based on MaxEnt Model[J]. Journal of Southwest Forestry University, 2020, 40(2): 79-85. DOI: 10.11929/j.swfu.201902069

Predication of Potential Distribution of Toxicodendron vernicifluum in China Based on MaxEnt Model

More Information
  • Received Date: February 23, 2019
  • Revised Date: December 15, 2019
  • Available Online: January 20, 2020
  • Published Date: February 29, 2020
  • Based on the 206 modern geographical distribution records and 9 environmental factor variables of Toxicodendron vernicifluum, the MaxEnt model was used to simulate the suitable distribution area of T. vernicifluum in China. Combined with the variable contributions, jackknife tests and response curves analyzes the dominant factors affecting the distribution of the T. vernicifluum. The results show that the MaxEnt model has high prediction accuracy and the average AUC value is 0.941; the annual average precipitation, altitude, annual average temperature and temperature variation variance are the dominant environmental factors affecting the geographical distribution of the T. vernicifluum. The current suitable area of T. vernicifluum is mainly concentrated in Qinba Mountain, Hengduan Mountains, Yunnan-Guizhou Plateau and Sichuan Basin in Southwestern China. The research results have certain reference value for the rational planting and scientific division of China's T. vernicifluum plantations.
  • Gaston K J. The structure and dynamics of geographic ranges[M]. New York: Oxford University Press, 2003.
    朱耿平, 刘国卿, 卜文俊, 等. 生态位模型的基本原理及其在生物多样性保护中的应用 [J]. 生物多样性, 2013, 21(1): 90−98.
    王婧, 王少波, 康宏樟, 等. 东亚地区栓皮栎的地理分布格局及其气候特征 [J]. 上海交通大学学报(农业科学版), 2009, 27(3): 235−241.
    李颖, 姜小龙, 邓敏, 等. 乌冈栎的潜在分布模拟及分析 [J]. 生态学杂志, 2017, 36(10): 2971−2978.
    McCormack J E, Zellmer A J, Knowles L L. Does niche divergence accompany allopatric divergence inaphelocomajays as predicted under ecological speciation?: insights from tests with niche models [J]. Evolution, 2009, 64(5): 1231−1244.
    Kumar S, Stohlgren T J. Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia [J]. Journal of Ecology and Natural Environment, 2009, 1(4): 94−98.
    孙文涛, 刘雅婷. 生物入侵风险分析的研究进展 [J]. 中国农学通报, 2010, 26(7): 233−236.
    胡秀, 吴福川, 郭微, 等. 基于MaxEnt生态学模型的檀香在中国的潜在种植区预测 [J]. 林业科学, 2014, 50(5): 27−33. DOI: 10.11707/j.1001-7488.20140504
    Phillips S J, Dudík M, Schapire R E. A maximum entropy approach to species distribution modeling[C]//Proceeding of the twenty-first international conference on Machine learning-ICML'04, New York: ACM Press, 2004: 83.
    魏朔南, 陈振峰. 秦巴山的漆树资源及其可持续发展 [J]. 经济林研究, 2004, 22(3): 68−73. DOI: 10.3969/j.issn.1003-8981.2004.03.021
    张飞龙, 张武桥, 魏朔南. 中国漆树资源研究及精细化应用 [J]. 中国生漆, 2007, 26(2): 36−50, 60. DOI: 10.3969/j.issn.1000-7067.2007.02.005
    魏朔南, 陈振峰. 陕西秦巴山区漆树分布特征研究 [J]. 西北林学院学报, 2005, 20(4): 31−35. DOI: 10.3969/j.issn.1001-7461.2005.04.008
    斯龙燕. 中国漆树资源与品种现状及产业发展前景 [J]. 绿色科技, 2016(1): 18, 20.
    张兴旺, 李垚, 方炎明. 麻栎在中国的地理分布及潜在分布区预测 [J]. 西北植物学报, 2014, 34(8): 1685−1692.
    王雷宏, 杨俊仙, 郑玉红, 等. 苹果属山荆子地理分布模拟 [J]. 北京林业大学学报, 2011, 33(3): 70−74.
    谢春平. 基于DIVA-GIS生物地理分布图的绘制 [J]. 湖北农业科学, 2011, 50(11): 2345−2348. DOI: 10.3969/j.issn.0439-8114.2011.11.056
    Yang X Q, Kushwaha S P S, Saran S, et al. Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills [J]. Ecological Engineering, 2013, 51: 83−87. DOI: 10.1016/j.ecoleng.2012.12.004
    肖育檀. 中国漆树生态地理分布的初步研究 [J]. 陕西林业科技, 1980(2): 32−41.
    幸亨泰, 梁万福, 郭建魁, 等. 甘肃漆树分布规律及品种的研究 [J]. 中国生漆, 1982, 1(3): 11−15.
    罗值贤, 罗玉友. 大方县漆树生长气候条件分析 [J]. 贵州气象, 2009, 33(S1): 72−73.
    Warren D L, Wright A N, Seifert S N, et al. Incorporating model complexity and spatial sampling Bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concern [J]. Diversity and Distributions, 2014, 20(3): 334−343. DOI: 10.1111/ddi.12160
    宋晓猛, 张建云, 占车生, 等. 基于DEM的数字流域特征提取研究进展 [J]. 地理科学进展, 2013, 32(1): 31−40. DOI: 10.11820/dlkxjz.2013.01.003
    Peterson A T, Soberón J. Species distribution modeling and ecological niche modeling: getting the concepts right [J]. Natureza & Conservação, 2012, 10(2): 102−107.
    Pouteau R, Meyer J Y, Larrue S. Using range filling rather than prevalence of invasive plant species for management prioritisation: the case of Spathodea campanulata in the Society Islands (South Pacific) [J]. Ecological Indicators, 2015, 54: 87−95. DOI: 10.1016/j.ecolind.2015.02.017
    Hernandez P A, Graham C H, Master L L, et al. The effect of sample size and species characteristics on performance of different species distribution modeling methods [J]. Ecography, 2006, 29(5): 773−785. DOI: 10.1111/j.0906-7590.2006.04700.x
    褚建民, 李毅夫, 张雷, 等. 濒危物种长柄扁桃的潜在分布与保护策略 [J]. 生物多样性, 2017, 25(8): 799−806. DOI: 10.17520/biods.2015218
  • Related Articles

    [1]Tang Jimin, Xuan Zhan, Yin Xiaojie, Yu Yanan, Yan Shuang, Li Hongqin, Huang Xunchao. Simulation of Geographical Distribution and Identification of Priority Protected Areas of the Extremely Small Populations of Oyama sinensis[J]. Journal of Southwest Forestry University. DOI: 10.11929/j.swfu.202407027
    [2]Li Rui, Yang Jianxin, Ma Changle, Guo Shuailong, Yang Lixing, Wang Lijuan. Habitat Suitability Evaluation of National Key Protected Birds in Kunming Based on MaxEnt Model[J]. Journal of Southwest Forestry University, 2024, 44(5): 165-175. DOI: 10.11929/j.swfu.202310063
    [3]He Lanjun, Li Linxia, Ou Guanglong. Prediction on the Potential Distribution of Vegetation and Climate Interpretation Based on the Distribution of Indicative Species in Ailao Mountain[J]. Journal of Southwest Forestry University, 2024, 44(3): 52-60. DOI: 10.11929/j.swfu.202303072
    [4]Zhou Limao, Wu Haiyang, Tian Bin. Dynamic Simulation Analysis of Potential Suitable Regions in the Different Periods for Lonicera maackii Using the MaxEnt Optimization Model[J]. Journal of Southwest Forestry University, 2024, 44(3): 43-51. DOI: 10.11929/j.swfu.202305048
    [5]Kang Zhen, Yan Zhaoyu, He Qiuxiang, Tian Bin. Prediction of Suitable Areas for 3 Species of Ilex Under Climate Change[J]. Journal of Southwest Forestry University, 2024, 44(2): 27-35. DOI: 10.11929/j.swfu.202211076
    [6]Dongxu Ma, Yi Zhou, Shuangfei Lu, Xiaojie Yin, Siyi Zhou. Study on Climate Suitability of 11 Species of Common Broad-leaved Trees in Yunnan Based on MaxEnt Model[J]. Journal of Southwest Forestry University, 2020, 40(5): 64-72. DOI: 10.11929/j.swfu.201906003
    [7]ZHOU Wei, ZHAO Heng, YANG Xi. Prediction of Potential Geographic Distribution Areas for Rana catesbiana and Mikania micrantha in China Using GARP Modeling System[J]. Journal of Southwest Forestry University, 2012, 32(1): 51-55. DOI: 10.3969/j.issn.2095-1914.2012.01.011
    [8]LI Yingang1, LIU Xinhong1, ZHAO Xun1, XU Liang1, YANG Zhiguo2. Climate Characteristics of the Geographic Distribution Areas of Styrax tonkinensis in China[J]. Journal of Southwest Forestry University, 2011, 31(1): 5-10. DOI: 10.3969/j.issn.2095-1914.2011.01.002
    [9]A STUDY ON THE SPECIES OF AFIDENTULA KAPUR 1955 AND THEIR GEOGRAPHICAL DISTRIBUTION[J]. Journal of Southwest Forestry University, 1992, 12(2): 174-179. DOI: 10.11929/j.issn.2095-1914.1992.02.008
    [10]THE COLOUR PATTERNS AND GEOGRAPHIC DISTRIBUTION OF COCCINELLA LUTEOPICTA (MULSANT). (COLEOPERA: COCCINELLIDAE)[J]. Journal of Southwest Forestry University, 1991, 11(2): 214-217. DOI: 10.11929/j.issn.2095-1914.1991.02.016
  • Cited by

    Periodical cited type(10)

    1. 刘华,管兰华,黄光体,曹健,杨寒,胡超,鲍汉民. 基于MaxEnt的湖北省鹅掌楸属树种适宜生态分布区预测. 湖北林业科技. 2023(02): 9-15 .
    2. 杜超群,吴昊,袁慧,许业洲. 湖北主要造林树种生态区划研究. 西南林业大学学报(自然科学). 2023(06): 1-7 .
    3. 潘浪波,段伟,黄有军. 基于MaxEnt模型预测薄壳山核桃在中国的种植区. 浙江农林大学学报. 2022(01): 76-83 .
    4. 张春华,雷晨雨,王储,冯德枫,孙永玉. 珍贵用材树种红椿4个变种栽培的潜在气候适生区预测. 云南农业大学学报(自然科学). 2022(02): 294-301 .
    5. 许斌,钟悦,张焱. 基于物种分布模型的画稿溪国家级自然保护区桫椤保护现状及影响因素. 西部林业科学. 2022(06): 53-61 .
    6. 辜云杰,李晓清,杨汉波. 基于MaxEnt生态位模型预测桢楠在中国的潜在适宜栽培区. 西北林学院学报. 2021(02): 136-141 .
    7. 陈豪杰,聂艳,刘新华,刘斌,张辉. 基于MaxEnt模型的胡杨潜在适生区预测研究. 中国农业信息. 2021(01): 46-55 .
    8. 张春华,雷晨雨,田瑞杰,冯德枫,孙永玉. 用材树种高山栲潜在适生区分布区及影响因子. 西部林业科学. 2021(03): 28-33 .
    9. 唐兴港,袁颖丹,张星,张金池. 板栗树种在中国水土流失区的分布及其环境因子. 水土保持通报. 2021(02): 345-352 .
    10. 郭文雨,郝蕾,张国盛,黄海广,宁静,李娅翔. 基于最大熵模型(MaxEnt)预测北沙柳潜在地理分布. 内蒙古林业科技. 2020(03): 1-7 .

    Other cited types(4)

Catalog

    Article views (1021) PDF downloads (39) Cited by(14)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return