四种气候变化情景下中国樱桃的潜在适生区预测

doi:10.12302/j.issn.1000-2006.202212007

国家林草科技领军期刊
中国精品科技期刊
中国高校百佳科技期刊
江苏省新闻出版政府奖期刊奖
RCCSE林学权威期刊（A+）
CSCD核心期刊
Scopus数据库收录期刊
中文核心期刊
SCD核心期刊

作者加群：102861116

微信公众号：南京林业大学学报

高级检索

南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (4): 235-242.doi: 10.12302/j.issn.1000-2006.202212007

四种气候变化情景下中国樱桃的潜在适生区预测

付陈龙(), 李蒙^*(), 田昌芬, 宋炎峰, 伊贤贵, 王贤荣

南京林业大学,南方现代林业协同创新中心,江苏南京 210037

收稿日期:2022-12-04 修回日期:2023-08-22 出版日期:2024-07-30 发布日期:2024-08-05
通讯作者: *李蒙(limeng@njfu.edu.cn),副教授。
作者简介:
付陈龙(15955152808@163.com)。
基金资助:
江苏省科学技术厅现代农业重点项目(BE2020343)

Prediction of potential suitable regions of Prunus pseudocerasus based on MaxEnt model under climate change

FU Chenlong(), LI Meng^*(), TIAN Changfen, SONG Yanfeng, YI Xiangui, WANG Xianrong

Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China

Received:2022-12-04 Revised:2023-08-22 Online:2024-07-30 Published:2024-08-05

摘要/Abstract

摘要：

【目的】中国樱桃(Prunus pseudocerasus)是我国古老的栽培果树之一。分析当前和未来气候变化情景下中国樱桃潜在适生区的变化趋势,为深入认识中国樱桃生长习性以及合理栽培和资源保护提供参考。【方法】基于中国樱桃现实地理分布数据和环境气候因子数据,使用MaxEnt模型模拟中国樱桃当前、未来2050年代和2070年代4种气候变化情景(SSP126、SSP245、SSP370和SSP585)下的潜在适生区分布,评估影响中国樱桃适生区分布的重要环境气候因子并分析其潜在适生区的变化趋势。【结果】采用ROC曲线法检验预测结果精度为0.936,说明预测结果可信度高。影响中国樱桃潜在适生区范围的关键因子为最冷月最低温、年降水量和最热季平均气温,土壤因子对中国樱桃适生区的限制不明显;现代气候条件下中国樱桃的潜在地理分布区主要集中于华东、华中以及西南地区,其中高适生区主要位于山东中东部和陕西南部;未来气候变化条件下,中国樱桃原本适生区范围收缩,西藏中部、吉林东部出现新的适生区。【结论】未来气候变化情景下,中国樱桃的潜在适生区将持续缩小,呈零星化、碎片化分布,并逐渐向高纬度、高海拔地区移动,这一结果可为中国樱桃种质资源的保护和产业规划提供理论依据。

关键词: 中国樱桃, 潜在适生区, 种质资源保护, MaxEnt模型

Abstract:

【Objective】Prunus pseudocerasus, one of the oldest cultivated species in China, is the focus of this study which predicts its suitable growth regions currently and in the future. This serves as a reference for understanding its growth habits and enhancing its cultivation.【Method】The MaxEnt model simulated the distribution of potential suitable areas for P. pseudocerasus under four climate scenarios (SSP126,SSP245,SSP370 and SSP585) at different times. This was based on geographic and environmental climate data. Important climatic variables influencing these areas were identified, and changes in potential suitable regions were analyzed.【Result】The accuracy of the predictions was validated using ROC analysis, achieving a high score of 0.936. Key climatic factors included annual precipitation, minimum temperature of the coldest month, and mean temperature of the warmest quarter. Soil factors did not significantly limit the distribution of P. pseudocerasus. Currently, suitable areas are primarily in the eastern, central and southwest China, with highly suitable regions in central and eastern Shandong, and southern Shaanxi. Climate change is expected to reduce these areas while creating new suitable regions in central Xizang and eastern Jilin.【Conclusion】Under future climate change scenarios, the potential suitable areas for P. pseudocerasus will become fragmented and shift towards higher latitudes and altitudes. These findings provide a theoretical basis for the conservation and industrial development of P. pseudocerasus in China.

Key words: Prunus pseudocerasus, potential suitable regions, protection of germplasm resources, MaxEnt model

中图分类号:

S718

付陈龙,李蒙,田昌芬,等. 四种气候变化情景下中国樱桃的潜在适生区预测[J]. 南京林业大学学报（自然科学版）, 2024, 48(4): 235-242.

FU Chenlong, LI Meng, TIAN Changfen, SONG Yanfeng, YI Xiangui, WANG Xianrong. Prediction of potential suitable regions of Prunus pseudocerasus based on MaxEnt model under climate change[J].Journal of Nanjing Forestry University (Natural Science Edition), 2024, 48(4): 235-242.DOI: 10.12302/j.issn.1000-2006.202212007.

图/表 7

图1

表1

图2

图3

表2

图4

图5

参考文献 35

[1]	World Meteorological Organization. State of the global climate 2020, provisional report[R]. Geneva: World Meteorological Organization, 2020.
[2]	中国科学院中国植物志编辑委员会. 中国植物志:第38卷[M]. 北京: 科学出版社, 1986:52.
	Editorial Committee of Chinese Flora, Chinese Academy of Sciences. Flora of China: Volume 38[M]. Beijing: Science Press, 1986:52.
[3]	刘长江, 刘美州. 山西侯马铸铜遗址种子类遗物的鉴定[M]. 北京: 文物出版社, 1993:65-71.
	LIU C J, LIU M Z. The seed identification of therelics from the HouMa Copper-Casting site in Shanxi, China[M]. Beijing: Cultural Relics Publishing House, 1993:65-71.
[4]	董渭雪. 樱桃黄酮组分及降尿酸作用研究[D]. 汉中: 陕西理工大学, 2020.
	DONG W X. Study on the flavonoids in cherries and the effect of reducing uric acid[D]. Hanzhong: Shaanxi University of Technology, 2020.
[5]	王月华. 江苏省栽培果树品种资源特征与生态适应性分析[D]. 南京: 南京农业大学, 2009.
	WANG Y H. Study on the characteristics and development strategies of the variety resources of fruit trees in Jiangsu Province[D]. Nanjing: Nanjing Agricultural University, 2009.
[6]	陈涛, 李良, 张静, 等. 中国樱桃种质资源的考察、收集和评价[J]. 果树学报, 2016, 33(8):917-933.
	CHEN T, LI L, ZHANG J, et al. Investigation,collection and preliminary evaluation of genetic resources of Chinese cherry[Cerasus pseudocerasus(Lindl.) G. Don][J]. J Fruit Sci, 2016, 33(8):917-933.DOI: 10.13925/j.cnki.gsxb.20150549.
[7]	刘针杉, 何文, 王燕, 等. 中国樱桃‘黑珍珠’离体的培养技术[J]. 分子植物育种, 2019, 17(24):8215-8220.
	LIU Z S, HE W, WANG Y, et al. In vitro culture technique of ‘Heizhenzhu’ [Cerasus pseudocerasus(Lindl.) G. Don][J]. Mol Plant Breed, 2019, 17(24):8215-8220.DOI: 10.13271/j.mpb.017.008215.
[8]	沈均波. 浙江省中国樱桃控根栽培技术[J]. 现代农业科技, 2021(22):55-56,64.
	SHEN J B. Cultivation techniques of cherry root control in China,Zhejiang Province[J]. Mod Agric Sci Technol, 2021(22):55-56, 64.DOI: 10.3969/j.issn.1007-5739.2021.22.024.
[9]	王建华. 中国樱桃‘黑珍珠’大棚矮冠栽培表现及技术[J]. 中国果树, 2020(4):85-87,142.
	WANG J H. Cultivation performance and techniques of dwarf crown of ‘Heizhenzhu’ Cerasus pseudocerasus in greenhouse[J]. China Fruits, 2020(4):85-87, 142.DOI: 10.16626/j.cnki.issn1000-8047.2020.04.023.
[10]	徐养诚, 刘孝贤, 王婷, 等. 基于MaxEnt模型的菜豆象全球潜在适生区预测[J]. 生物安全学报, 2021, 30(3):213-219.
	XU Y C, LIU X X, WANG T, et al. Potential suitable distribution of Acanthoscelides obtectus (Say) based on the MaxEnt model[J]. J Biosaf, 2021, 30(3):213-219.DOI: 10.3969/j.issn.2095-1787.2021.03.010.
[11]	王文婷, 杨婷婷, 金磊, 等. 未来气候变化下两种红景天植物的脆弱性[J]. 生物多样性, 2021, 29(12):1620-1628.
	WANG W T, YANG T T, JIN L, et al. Vulnerability of two Rhodiola species under climate change in the future[J]. Biodivers Sci, 2021, 29(12):1620-1628.DOI: 10.17520/biods.2021209.
[12]	高健, 赵辉. 基于MaxEnt模型评估槭属鸡爪槭组物种的空间分布[J]. 西北林学院学报, 2021, 36(1):163-167,265.
	GAO J, ZHAO H. Prediction of potentially suitable distribution of section palmata (Acer) in east Asia based on MaxEnt[J]. J Northwest For Univ, 2021, 36(1):163-167,265.DOI: 10.3969/j.issn.1001-7461.2021.01.23.
[13]	林丽, 晋玲, 王振恒, 等. 气候变化背景下藏药黑果枸杞的潜在适生区分布预测[J]. 中国中药杂志, 2017, 42(14):2659-2669.
	LIN L, JIN L, WANG Z H, et al. Prediction of the potential distribution of Tibetan medicinal Lycium ruthenicum in context of climate change[J]. China J Chin Mater Med, 2017, 42(14):2659-2669.DOI: 10.19540/j.cnki.cjcmm.2017.0117.
[14]	杨宏, 董京京, 吴桐, 等. 基于MaxEnt模型的迎春樱桃潜在适生区预测[J]. 南京林业大学学报(自然科学版), 2023, 47(4):131-138.
	YANG H, DONG J J, WU T, et al. Prediction of potential suitable areas of Cerasus discoidea in China based on the MaxEnt model[J]. J Nanjing Fore Univ (NatSci Ed), 2023, 47(4):131-138.DOI: 10.12302/j.issn.1000-2006.202108014.
[15]	周佩, 钱增强, 陈克克, 等. 气候变化背景下费菜在中国适生区分布预测[J]. 中药材, 2015, 38(7):1379-1383.
	ZHOU P, QIAN Z Q, CHEN K K, et al. Prediction on the distribution of Potamogeton esculentum in suitable areas of China under the background of climate change[J]. J Chin Med Mater, 2015, 38(7):1379-1383.DOI: 10.13863/j.issn1001-4454.2015.07.011.
[16]	RONG Z L, ZHAO C Y, LIU J J, et al. Modeling the effect of climate change on the potential distribution of Qinghai spruce (Picea crassifolia Kom.) in Qilian Mountains[J]. Forests, 2019, 10(1):62.DOI: 10.3390/f10010062.
[17]	张丽霞, 陈晓龙, 辛晓歌. CMIP6情景模式比较计划(ScenarioMIP)概况与评述[J]. 气候变化研究进展, 2019, 15(5):519-525.
	ZHANG L X, CHEN X L, XIN X G. Short commentary on CMIP6 scenario model intercomparison project(ScenarioMIP)[J]. Clim Change Res, 2019, 15(5):519-525.DOI: 10.12006/j.issn.1673-1719.2019.082.
[18]	姜彤, 吕嫣冉, 黄金龙, 等. CMIP6模式新情景(SSP-RCP)概述及其在淮河流域的应用[J]. 气象科技进展, 2020, 10(5):102-109.
	JIANG T, LÜ Y R, HUANG J L, et al. New scenarios of CMIP6 model (SSP-RCP) and its application in the Huaihe River basin[J]. Adv Meteorol Sci Technol, 2020, 10(5):102-109.DOI: 10.3969/j.issn.2095-1973.2020.05.016.
[19]	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.
	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]. Biodivers Sci, 2007, 15(4):365-372.DOI: 10.3321/j.issn:1005-0094.2007.04.005.
[20]	吴晓萌, 叶冬梅, 白玉娥, 等. 基于MaxEnt模型的中国白杄分布格局及未来变化[J]. 西北植物学报, 2022, 42(1):162-172.
	WU X M, YE D M, BAI Y, et al. Distribution pattern and future change of Picea meyeri in China based on MaxEnt model[J]. Acta Bot Boreali Occidentalia Sin, 2022, 42(1):162-172.DOI: 10.7606/j.issn.1000-4025.2022.01.0162.
[21]	麻亚鸿. 基于最大熵模型(MaxEnt)和地理信息系统(ArcGIS)预测藓类植物的地理分布范围:以广西花坪自然保护区为例[D]. 上海: 上海师范大学, 2013.
	MA Y H. Applying maxent and arcgis to predict mosses geographic distirbution range[D]. Shanghai: Shanghai Normal University, 2013.
[22]	CHEN T, CHEN Q, ZHANG J, et al. Phylogeography of 912 cherry accessions insight into independent origins of fruiting cherries and domestication footprints of cultivated Chinese cherry (Prunus pseudocerasus Lindl.)[J]. Plants, 2023, 12(12):2258.DOI: 10.3390/plants12122258.
[23]	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]. J Biogeogr, 2007, 34(1):102-117.
[24]	孔维尧, 李欣海, 邹红菲. 最大熵模型在物种分布预测中的优化[J]. 应用生态学报, 2019, 30(6):2116-2128.
	KONG W Y, LI X H, ZOU H F. Optimizing MaxEnt model in the prediction of species distribution[J]. Chin J Appl Ecol, 2019, 30(6):2116-2128.DOI: 10.13287/j.1001-9332.201906.029.
[25]	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.
	ZHU G P, QIAO H J. Effect of the MaxEnt model’s complexity on the prediction of species potential distributions[J]. Biodivers Sci, 2016, 24(10):1189-1196.DOI: 10.17520/biods.2016265.
[26]	童晓利, 韩金龙, 唐冬兰, 等. 南京地区中国樱桃发展现状与栽培建议[J]. 江苏农业科学, 2019, 47(8):165-167.
	DONG X L, HAN J L, TANG D L, et al. Current situation and cultivation suggestions of Chinese cherry(Prunus pseudocerasus L.) in Nanjing area[J]. Jiangsu Agric Sci, 2019, 47(8):165-167.DOI: 10.15889/j.issn.1002-1302.2019.08.037.
[27]	曹福祥, 徐庆军, 曹受金, 等. 全球变暖对物种分布的影响研究进展[J]. 中南林业科技大学学报, 2008, 28(6):86-89.
	CAO F X, XU Q J, CAO S J, et al. Advances of global warming impact on species distribution[J]. J Cent South Univ For Technol, 2008, 28(6):86-89.DOI: 10.3969/j.issn.1673-923X.2008.06.019.
[28]	吴建国, 吕佳佳. 气候变化对我国干旱区分布及其范围的潜在影响[J]. 环境科学研究, 2009, 22(2):199-206.
	WU J G, LÜ J J. Potential effect of climate change on the distribution and range of arid regions[J]. Res Environ Sci, 2009, 22(2):199-206.DOI: 10.13198/j.res.2009.02.77.wujg.004.
[29]	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.
	ZHANG X W, LI Y, FANG Y M. Geographical distribution and prediction of potential ranges of Quercus acutissima in China[J]. Acta Bot Boreali Occidentalia Sin, 2014, 34(8):1685-1692.DOI: 10.7606/j.issn.1000-4025.2014.08.1685.
[30]	袁峰. 冬虫夏草居群谱系地理与适生区分布研究[D]. 昆明: 云南大学, 2015.
	YUAN F. Study on phylogeography and suitable distribution of Ophiocordyceps sinensis populations[D]. Kunming: Yunnan University, 2015.
[31]	李垚, 张兴旺, 方炎明. 小叶栎分布格局对末次盛冰期以来气候变化的响应[J]. 植物生态学报, 2016, 40(11):1164-1178.
	LI Y, ZHANG X W, FANG Y M. Responses of the distribution pattern of Quercus chenii to climate change following the Last Glacial Maximum[J]. Chin J Plant Ecol, 2016, 40(11):1164-1178.
[32]	韩金龙, 童晓利, 曹荣祥, 等. 中国樱桃品种在南京地区的引种试验[J]. 安徽农业科学, 2022, 50(3):53-55.
	HAN J L, TONG X L, CAO R X, et al. Introduction experiment of Chinese cherry varieties in Nanjing region[J]. J Anhui Agric Sci, 2022, 50(3):53-55.DOI: 10.3969/j.issn.0517-6611.2022.03.014.
[33]	吴延军, 陈锦宇, 赵新军, 等. 中国樱桃新品种‘紫晶’[J]. 园艺学报, 2020, 47(S2):2894-2895.
	WU Y J, CHEN J Y, ZHAO X J, et al. A new Chinese cherry cultivar ‘Zijing’[J]. Acta Hortic Sin, 2020, 47(S2):2894-2895. DOI: 10.16420/j.issn.0513-353x.2020-0661.
[34]	刘珠琴, 汪国云, 汪国武, 等. 中国樱桃新品种梁弄红的选育[J]. 果树学报, 2022, 39(11):2201-2204.
	LIU Z Q, WANG G Y, WANG G W, et al. Breeding report of a new Chinese cherry cultivar Liangnonghong[J]. J Fruit Sci, 2022, 39(11):2201-2204.DOI: 10.13925/j.cnki.gsxb.20220141.
[35]	WANG Y, LIU Z S, YANG X Q, et al. Inheritance analysis of fruit-related traits in Chinese cherry[Cerasus pseudocerasus (Lindl.) G. Don] breeding progenies[J]. Sci Hortic, 2023, 307:111519.DOI: 10.1016/j.scienta.2022.111519.

变量 variable	贡献率/% percent contribution	置换重要值/% permutation importance
Bio12	38.4	12.1
Bio6	30.6	29.9
Bio10	7.6	6.3
Bio4	5.7	11.5
Bio3	3.4	1.4
Bio2	2.5	5.8
AWC_CLASS	2.0
Bio19	1.6	2.7
Bio15	1.2	2.3
T_CACO₃	1.2	3.0
T_CLAY	1.2	10.1
T_GRAVEL	1.0	1.2
T_TEB	0.9	1.6
T_SILT	0.6	1.3
T_PH_H₂O	0.6	0.3
Bio16	0.4	9.8
T_SAND	0.4	1.8
T_OC	0.3	0.6
T_ESP	0.3	1

气候情景 climatic scenario	时期 period	非适生区面积 area of non-suitable area	低适生区面积 area of low fitness area	中适生区面积 area of meso-suitable area	高适生区面积 area of high suitable area
SSP126	2050s	1.644	3.411	-2.681	-2.374
	2070s	1.061	4.450	-3.010	-2.501
SSP245	2050s	29.700	3.969	-2.209	-2.057
	2070s	2.834	3.988	-4.114	-2.707
SSP370	2050s	2.579	3.061	-3.239	-2.400
	2070s	4.349	2.746	-4.547	-2.549
SSP585	2050s	-66.800	3.501	-29.700	-2.536
	2070s	-18.400	7.247	-4.158	-2.905

四种气候变化情景下中国樱桃的潜在适生区预测

Prediction of potential suitable regions of Prunus pseudocerasus based on MaxEnt model under climate change

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 35

相关文章 13

编辑推荐

Metrics

本文评价

作者

读者

审稿

[1]	杨宏, 董京京, 吴桐, 周华近, 陈洁, 李蒙, 王贤荣, 伊贤贵. 基于MaxEnt模型的迎春樱桃潜在适生区预测[J]. 南京林业大学学报（自然科学版）, 2023, 47(4): 131-138.
[2]	韩淑敏, 闫伟, 杨雪栋, 胡博, 于凤强, 高润红. 白榆在我国的潜在分布格局及未来变化[J]. 南京林业大学学报（自然科学版）, 2023, 47(3): 103-110.
[3]	董京京, 陈洁, 杨宏, 李蒙, 王贤荣, 伊贤贵. 华中樱桃适生区模拟和生态特征分析[J]. 南京林业大学学报（自然科学版）, 2022, 46(3): 213-221.
[4]	龚茂佳, 王娟, 付小勇, 寇卫利, 鲁宁, 王秋华, 赖虹燕. 云南广西蒜头果适生区预测及环境影响因子[J]. 南京林业大学学报（自然科学版）, 2022, 46(2): 44-52.
[5]	吴帆, 朱沛煌, 季孔庶. 马尾松分布格局对未来气候变化的响应[J]. 南京林业大学学报（自然科学版）, 2022, 46(2): 196-204.
[6]	缪菁, 王勇, 王璐, 许晓岗. 基于MaxEnt模型的苦槠潜在地理分布格局变迁预测[J]. 南京林业大学学报（自然科学版）, 2021, 45(3): 193-198.
[7]	黄红兰, 钟沃谷, 衣德萍, 蔡军火, 张露. 未来气候变化对我国毛红椿适生区分布格局的影响预测[J]. 南京林业大学学报（自然科学版）, 2020, 44(3): 163-170.
[8]	陈禹衡, 吕一维, 殷晓洁. 气候变化下西南地区12种常见针叶树种适宜分布区预测[J]. 南京林业大学学报（自然科学版）, 2019, 43(6): 113-120.
[9]	马青江, 孙操稳, 张乐英, 胡梓恒, 张仕娇, 洑香香. 东亚四照花群体中国潜在适生区预测研究[J]. 南京林业大学学报（自然科学版）, 2019, 43(5): 135-140.
[10]	江一帆,李明阳,刘雅楠,刘菲. 气候变化对湖南省马尾松适宜生境影响分析[J]. 南京林业大学学报（自然科学版）, 2019, 43(04): 94-100.
[11]	刘清亮,李垚1,3,方升佐1,2*. 基于MaxEnt模型的青钱柳潜在适宜栽培区预测[J]. 南京林业大学学报（自然科学版）, 2017, 41(04): 25-29.
[12]	吴显坤,南程慧,汤庚国,李垚,毛丽君,张志成. 气候变化对浙江楠潜在分布范围及空间格局的影响[J]. 南京林业大学学报（自然科学版）, 2016, 40(06): 85-91.
[13]	李勤文,李永和,刘建宏,杨松,马明友,佘光辉. 基于Maxent模型的细梢小卷蛾云南潜在分布区预测[J]. 南京林业大学学报（自然科学版）, 2013, 37(06): 37-40.