Prediction of suitable distribution area of the endangered plant <i>Acer catalpifolium</i> under the background of climate change in China

Huang Ruizhi; Yu Tao; Zhao Hui; Zhang Shengkai; Jing Yang; Li Junqing

doi:10.12171/j.1000-1522.20200254

Journal of Beijing Forestry University > 2021 > 43(5): 33-43. > DOI: 10.12171/j.1000-1522.20200254

Huang Ruizhi, Yu Tao, Zhao Hui, Zhang Shengkai, Jing Yang, Li Junqing. Prediction of suitable distribution area of the endangered plant Acer catalpifolium under the background of climate change in China[J]. Journal of Beijing Forestry University, 2021, 43(5): 33-43. DOI: 10.12171/j.1000-1522.20200254

Citation:

PDF (1035 KB)

Prediction of suitable distribution area of the endangered plant Acer catalpifolium under the background of climate change in China

1.
Beijing Key Laboratory of Forest Resources Ecosystem Process, Beijing Forestry University, Beijing 100083, China
2.
Henan Academy of Forestry Sciences, Zhengzhou 450008, Henan, China
3.
Comprehensive Agricultural Service Center of Daliuxing Town, Penglai City, Yantai 265615, Shandong, China

More Information

Received Date: August 17, 2020
Revised Date: October 14, 2020
Available Online: March 19, 2021
Published Date: May 26, 2021

Graphical Abstract

Abstract

Abstract

Objective This paper aims to analyze the potential distribution areas of extremely small population of endangered plant Acer catalpifolium in China today and in the future, reveal the distribution dynamics of A. catalpifolium under future climate change.
Method Taking A. catalpifolium as the research object, based on the existing A. catalpifolium distribution sites, climate data and altitude data, using the MaxEnt model and GIS technology to simulate the current, 2050s (2041−2060) and 2090s (2081−2100) (SSP126, SSP245, SSP370 and SSP585) distribution pattern of A. catalpifolium under climate scenarios, classify the fitness level and use the area under the receiver operating characteristic curve (ROC) (AUC) to evaluate the accuracy of simulation, analyze the contribution rate of climate variables with the knife-cut method to find out the dominant climate variables that restrict the distribution of A. catalpifolium; compare the geographic distribution of A. catalpifolium under different climatic conditions based on the distribution area ratio (N_a) and the degree of habitat change (N_e) dynamic.
Result The main suitable areas for A. catalpifolium were distributed in southwestern China. The AUC values of the training set and the test set under the nine climatic scenarios were both greater than 0.995, indicating that the model simulation accuracy was extremely high. The warmest season rainfall, temperature seasonal variation standard deviation and altitude had the highest contribution rates, which were 56.1%, 18.2% and 10.9%, respectively.
Conclusion Under the background of climate change, A. catalpifolium will lose a large number of highly suitable areas, and the habitat fragmentation will be more serious than the trend. The medium-to-high intensity emission scenario SSP370 has little impact on the potential distribution area of A. catalpifolium. This study can provide a basis for the in-situ and ex-situ conservation of the endangered species of A. catalpifolium.
- Acer catalpifolium,
- MaxEnt,
- potential distribution area,
- climate factor

FullText(HTML)

References (42)

References

[1]	蒋霞, 倪健. 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[J]. 植物生态学报, 2005, 29(1):98−107. Jiang X, Ni J. Species-climate relationships of 10 desert plant species and their estimated potential distribution range in the arid lands of northwestern China[J]. Acta Phytoecologica Sinica, 2005, 29(1): 98−107.
[2]	王娟, 倪健. 植物种分布的模拟研究进展[J]. 植物生态学报, 2006, 30(6):1040−1053. doi: 10.17521/cjpe.2006.0133 Wang J, Ni J. Review of modelling the distribution of plant species[J]. Journal of Plant Ecology, 2006, 30(6): 1040−1053. doi: 10.17521/cjpe.2006.0133
[3]	Intergovernmental Panel on Climate Change. Fifth assessment report (AR5) [EB/OL]. (2013−06−07) [2018−07−08]. http://www.ipcc.ch/assessment-report/ar5/.
[4]	Sharma E, Chettri N, Tsering K, et al. Climate change impacts and vulnerability in the eastern himalayas[M]. Kathmandu: International Centre for Integrated Mountain Development, 2009.
[5]	Thomas C D, Cameron A, Green R E, et al. Extinction risk from climate change[J]. Nature, 2004, 427: 145−148. doi: 10.1038/nature02121
[6]	王运生, 谢丙炎, 万方浩, 等. ROC曲线分析在评价入侵物种分布模型中的应用[J]. 生物多样性, 2007, 15(4):365−372. doi: 10.1360/biodiv.060280 Wang Y S, Xie B Y, Wan F H, et al. Application of ROC curve analysis in evaluating the performance of alien species’ potential distribution models[J]. Biodiversity Science, 2007, 15(4): 365−372. doi: 10.1360/biodiv.060280
[7]	周海涛, 那晓东, 臧淑英, 等. 最大熵(Maxent)模型在物种栖息地研究中的应用[J]. 环境科学与管理, 2016, 41(3):149−151. Zhou H T, Na X D, Zang S Y, et al. Applications of maximum entropy (Maxent) model in species habitat study[J]. Environmental Science and Management, 2016, 41(3): 149−151.
[8]	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. doi: 10.3724/SP.J.1003.2013.09106 Zhu G P, Liu G Q, Bu W J, et al. Ecological niche modeling and its applications in biodiversity conservation[J]. Biodiversity Science, 2013, 21(1): 90−98. doi: 10.3724/SP.J.1003.2013.09106
[9]	艾科拜尔·木哈塔尔, 热木图拉·阿卜杜克热木, 马合木提·哈力克. 基于生态位模型的艾比湖国家级自然保护区马鹿生境评价[J]. 生态学报, 2017, 37(11):3919−3925. Ekbar M, Rahmutulla A, Mahmut H. Assessing habitat suitability for cervuselaphus in the Ebinur Lake National Nature Reserve[J]. Acta Ecologica Sinica, 2017, 37(11): 3919−3925.
[10]	苏旭坤, 董世魁, 刘世梁, 等. 阿尔金山自然保护区土地利用/覆被变化对藏野驴栖息地的影响[J]. 生态学杂志, 2014, 33(1):141−148. Su X K, Dong S K, Liu S L, et al. Effects of land use/land cover change (LUCC) on habitats of Tibetan wild donkey in Aerjin Mountain National Nature Reserve[J]. Chinese Journal of Ecology, 2014, 33(1): 141−148.
[11]	Basille M, Calenge C, Marboutin C, et al. Assessing habitat selection using multivariate statistics: some refinements of the ecological-niche factor analysis[J]. Ecological Modelling, 2008, 211(1): 233−240.
[12]	Niven R K. Jaynes’ MaxEnt, steady state flow systems and the maximum entropy production principle[J]. AIP Conference Proceedings, 2009, 1193: 397−404.
[13]	Gotway C A, Stroup W W. A generalized linear model approach to spatial data analysis and prediction[J]. Journal of Agricultural Biological and Environmental Stats, 1997, 2(2): 157−178. doi: 10.2307/1400401
[14]	David R B S, Lan N R. Induction of sets of rules from animal distribution data: a robust and informative method of data analysis[J]. Mathematics & Computers in Simulation, 1992, 33(5−6): 385−390.
[15]	曹雪萍, 王婧如, 鲁松松, 等. 气候变化情景下基于最大熵模型的青海云杉潜在分布格局模拟[J]. 生态学报, 2019, 39(14):5232−5240. Cao X P, Wang J R, Lu S S, et al. Simulation of the potential distribution patterns of Picea crassifolia in climate change scenarios based on the maximum entropy (Maxent) model[J]. Acta Ecologica Sinica, 2019, 39(14): 5232−5240.
[16]	季乾昭, 王荣兴, 黄志旁, 等. 样本量与研究范围变化对MaxEnt模型准确度的影响:以黑白仰鼻猴为例[J]. 兽类学报, 2019, 39(2):126−133. Ji Q Z, Wang R X, Huang Z P, et al. Effects of sample size and study range on accuracy of MaxEnt in predicting species distribution: a case study of the black-and-white snub-nosed monkey[J]. Acta Theriologica Sinica, 2019, 39(2): 126−133.
[17]	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[J]. 生态学杂志, 2015, 34(12):3354−3359. Xu J, Cao B, Bai C K. Prediction of potential suitable distribution of endangered plant Kingdonia uniflora in China with MaxEnt[J]. Chinese Journal of Ecology, 2015, 34(12): 3354−3359.
[18]	马松梅, 聂迎彬, 耿庆龙, 等. 气候变化对蒙古扁桃适宜分布范围和空间格局的影响[J]. 植物生态学报, 2014, 38(3):262−269. doi: 10.3724/SP.J.1258.2014.00023 Ma S M, Nie Y B, Geng Q L, et al. Impact of climate change on suitable distribution range and spatial pattern in Amygdalus mongolica[J]. Chinese Journal of Plant Ecology, 2014, 38(3): 262−269. doi: 10.3724/SP.J.1258.2014.00023
[19]	吴志华, 詹妮, 尚秀华, 等. 我国黄槿气候特征及适生区分析[J]. 桉树科技, 2020, 37(2):45−52. Wu Z H, Zan N, Shang X H, et al. Climatic characteristics analysis of Hibiscus tiliaceus and prediction of its suitable range in China[J]. Eucalypt Science & Technology, 2020, 37(2): 45−52.
[20]	Adhikari D, Barik S, Upadhaya K. Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically endangered tree species of northeastern India[J]. Ecological Engineering, 2012, 40: 37−43. doi: 10.1016/j.ecoleng.2011.12.004
[21]	Sunil K, Thomas J S. Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia[J]. Journal of Ecology Environment, 2009, 1(4): 94−98.
[22]	张宇阳, 马文宝, 于涛, 等. 梓叶槭的种群结构和群落特征[J]. 应用与环境生物学报, 2018, 24(4):697−703. Zhang Y Y, Ma W B, Yu T, et al. Population structure and community characteristics of Acer catalpifolium Rehd[J]. Chinese Journal of Applied & Environmental Biology, 2018, 24(4): 697−703.
[23]	Muscarella R, Galante P J, Soley-Guardia M, et al. ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models[J]. Methods in Ecology & Evolution, 2015, 5(11): 1198−1205.
[24]	朱耿平, 乔慧捷. Maxent模型复杂度对物种潜在分布区预测的影响[J]. 生物多样性, 2016, 24(10):1189−1196. doi: 10.17520/biods.2016265 Zhu G P, Qiao H J. Effect of the Maxent model’s complexity on the prediction of species potential distributions[J]. Biodiversity Science, 2016, 24(10): 1189−1196. doi: 10.17520/biods.2016265
[25]	Akaike H. Information theory and an extension of the maximum likelihood principle[C]. Budapest: the Committee of Second International Symposium on Information Theory, 1973.
[26]	Warren D L, Seifert S N. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria[J]. Ecological Applications, 2011, 21(2): 335−342. doi: 10.1890/10-1171.1
[27]	Pearson R G, Raxworthy C J, Nakamura M, et al. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar[J]. Journal of Biogeography, 2007, 34(1): 102−117.
[28]	Lobo J M. AUC: a misleading measure of the performance of predictive distribution models[J]. Global Ecology & Biogeography, 2010, 17(2): 145−151.
[29]	冉巧, 卫海燕, 赵泽芳, 等. 气候变化对孑遗植物银杉的潜在分布及生境破碎度的影响[J]. 生态学报, 2019, 39(7):2481−2492. Ran Q, Wei H Y, Zhao Z F, et al. Impact of climate change on the potential distribution and habitat fragmentation of the relict plant Cathaya argyrophylla Chun et Kuang[J]. Acta Ecologica Sinica, 2019, 39(7): 2481−2492.
[30]	郭飞龙, 徐刚标, 牟虹霖, 等. 伯乐树潜在地理分布时空格局模拟[J]. 植物科学学报, 2020, 38(2):185−194. Guo F L, Xu G B, Mu H L, et al. Simulation of potential spatiotemporal population dynamics of Bretschneidera sinensis Hemsl. based on MaxEnt model[J]. Plant Science Journal, 2020, 38(2): 185−194.
[31]	邢丁亮, 郝占庆. 最大熵原理及其在生态学研究中的应用[J]. 生物多样性, 2011, 19(3):295−302. doi: 10.3724/SP.J.1003.2011.08318 Xing D L, Hao Z Q. The principle of maximum entropy and its applications in ecology[J]. Biodiversity Science, 2011, 19(3): 295−302. doi: 10.3724/SP.J.1003.2011.08318
[32]	Phillips S J, Dudík M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation[J]. Ecography, 2008, 31(2): 161−175. doi: 10.1111/j.0906-7590.2008.5203.x
[33]	孟艺宏, 徐璕, 姜小龙, 等. 双花木属植物潜在分布区模拟与分析[J]. 生态学报, 2019, 39(8):2816−2825. Meng Y H, Xu X, Jiang X L, et al. Potential distribution modeling and analysis of Disanthus Maxim.[J]. Acta Ecologica Sinica, 2019, 39(8): 2816−2825.
[34]	吴建国. 气候变化对7种荒漠植物分布的潜在影响[J]. 应用与环境生物学报, 2010, 16(5):650−661. Wu J G. Effects of climate changes on distribution of seven desert plants in China[J]. Chinese Journal of Applied & Environmental Biology, 2010, 16(5): 650−661.
[35]	Bezeng S B, Morales-Castilla I, Bank M V D, et al. Climate change may reduce the spread of non-native species[J]. Ecosphere, 2017, 8(3): 1−14.
[36]	Mckenney D W, Pedlar J H, Lawrence K, et al. Potential impacts of climate change on the distribution of North American trees[J]. BioScience, 2007, 57(11): 939−948. doi: 10.1641/B571106
[37]	Lenoir J, Gegout J C, Marquet P A, et al. A significant upward shift in plant species optimum elevation during the 20th century[J]. Science, 2008, 320: 1768−1771. doi: 10.1126/science.1156831
[38]	冯建孟. 中国种子植物物种多样性的大尺度分布格局及其气候解释[J]. 生物多样性, 2008, 16(5):470−476. doi: 10.3724/SP.J.1003.2008.08027 Feng J M. Spatial patterns of species diversity of seed plants in China and their climatic explanation[J]. Biodiversity Science, 2008, 16(5): 470−476. doi: 10.3724/SP.J.1003.2008.08027
[39]	张兴旺, 李垚, 谢艳萍, 等. 气候变化对黄山花楸潜在地理分布的影响[J]. 植物资源与环境学报, 2018, 27(4):33−43. Zhang X W, Li Y, Xie Y P, et al. Effect of climate change on potential geographical distribution of Sorbus amabilis[J]. Journal of Plant Resources and Environment, 2018, 27(4): 33−43.
[40]	贾翔, 王超, 金慧, 等. 基于优化的MaxEnt模型评价红松适宜分布区[J]. 生态学杂志, 2019, 38(8):2570−2576. Jia X, Wang C, Jin H, et al. Assessing the suitable distribution area of Pinus koraiensis based on an optimized MaxEnt model[J]. Chinese Journal of Ecology, 2019, 38(8): 2570−2576.
[41]	苏维词. 贵州喀斯特地区珍稀濒危植物及其保护[J]. 长江流域资源与环境, 2002, 11(2):111−116. Su W C. Rare and endangered plants in Guizhou karst regions with the consideration of their conservation[J]. Resources and Environment in the Yangtze Basin, 2002, 11(2): 111−116.
[42]	Austin M P, Niel K P V. Improving species distribution models for climate change studies: variable selection and scale[J]. Journal of Biogeography, 2011, 38(1): 1−8. doi: 10.1111/j.1365-2699.2010.02416.x

[1]	Feng Xuejing, Ma Ling, Yang Shuang, Bo Wenhao, Chen Xuexun, Pang Xiaoming. Construction of genetic transformation system of ‘Jingzao 39’ callus[J]. Journal of Beijing Forestry University, 2024, 46(10): 74-80. DOI: 10.12171/j.1000-1522.20240055
[2]	PANG Hong-dong, XIANG Lin, ZHAO Kai-ge, LI Xiang, YANG Nan, CHEN Long-qing. Genetic transformation and functional characterization of Chimonanthus praecox SAMT gene in tobacco[J]. Journal of Beijing Forestry University, 2014, 36(5): 117-122. DOI: 10.13332/j.cnki.jbfu.2014.05.019
[3]	LI Yan, ZHAO De-gang. Ipt gene promoting shoot regeneration in genetic transformation of Eucommia ulmoides Oliv[J]. Journal of Beijing Forestry University, 2011, 33(6): 90-93.
[4]	ZENG Xiao-fang, ZHAO De-gang. Factors affecting transformation of Zanthoxylum piperitum DC. var. inerme Makino via Agrobacterium tumefaciens.[J]. Journal of Beijing Forestry University, 2011, 33(6): 80-85.
[5]	ZHAO Ling-li, SHI Shao-chuan, SUN Jia-qi, ZHANG Qi-xiang, GAO Yi-ke. Transformation of ground-cover Chrysanthemum with HsfA2 gene isolated from Arabidopsis thaliana[J]. Journal of Beijing Forestry University, 2011, 33(5): 97-102.
[6]	LONG Cui, PANG Xiao-ming, CAO Guan-lin, LIU Ying, ZHANG Zhi-yi. A study on the efficient protocol for transforming MdSPDS1 gene into Populus tomentosa Carr.[J]. Journal of Beijing Forestry University, 2010, 32(5): 21-26.
[7]	YU Lai, AN Xin-min, CAO Guan-lin, CHEN Zhong, ZHANG Zhi-yi. Genetic transformation of Populus tomentosa Carr. with sterility construct of PtAP3[J]. Journal of Beijing Forestry University, 2010, 32(5): 15-20.
[8]	QIN Ai-guang, LUO Xiao-fang. Transformation of transcription factor DREB1C gene into the fast-growing black locust mediated with Agrobacterium tumefaciens[J]. Journal of Beijing Forestry University, 2007, 29(6): 29-34. DOI: 10.13332/j.1000-1522.2007.06.011
[9]	LI Hui, CHEN Xiao-yang, LI Yun, LI Wei, DING Xia. Optimization of antibiotic concentration in genetic transformation of Populus alba[J]. Journal of Beijing Forestry University, 2005, 27(5): 118-121.
[10]	GAO Li-ping, BAO Man-zhu. Optimization of Agrobacterium-mediated transformation of Rosa hybrida[J]. Journal of Beijing Forestry University, 2005, 27(4): 60-64.

Cited By

Cited by

Periodical cited type(8)

1.	罗茂，关志华，颜幼春，柴莹莹，刘佳琪，张佳敏，王忠红. 模拟根际生境下青甘韭生长与品质的差异分析. 高原农业. 2025(01): 65-72+132 .
2.	黄小辉，吴焦焦，王玉书，冯大兰，孙向阳. 不同供氮水平的核桃幼苗生长及叶绿素荧光特性. 南京林业大学学报(自然科学版). 2022(02): 119-126 .
3.	郑伟，师筝，龙美，廖允成. 黄绿叶突变体冀麦5265yg的光合生理特性分析. 中国农业科学. 2021(21): 4539-4551 .
4.	王佳敏，宋海燕，陈金艺，张静，李素慧，陶建平，刘锦春. 多年生黑麦草对干旱胁迫下喀斯特异质生境的生长响应策略. 生态学报. 2020(13): 4566-4572 .
5.	王生云，陶永明，司剑华. 不同配方轻基质对鳞皮云杉生长及光合参数的影响. 浙江林业科技. 2019(02): 50-55 .
6.	乐佳兴，田秋玲，吴焦焦，高岚，张文，刘芸. 无患子幼苗的生长和光合特性对重庆低山丘陵区不同生境的响应. 北京林业大学学报. 2019(06): 75-85 . 本站查看
7.	戴前莉，黄小辉，黄馨，唐龙波，朱恒星. 不同生境条件下凤丹生长及光合特性比较. 西南大学学报(自然科学版). 2018(09): 53-58 .
8.	陶永明，司剑华. 不同轻基质配方对川西云杉幼苗生长的影响. 浙江林业科技. 2017(04): 66-70 .

Other cited types(5)

Get Citation

PDF

XML

Article views (2298) PDF downloads (189) Cited by(13)

Turn off MathJax

Article Contents

Abstract

References

Prediction of suitable distribution area of the endangered plant Acer catalpifolium under the background of climate change in China