Simulation and analyses of ecological characteristics of Cerasus conradinae adaptability area

doi:10.12302/j.issn.1000-2006.202101024

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2022, Vol. 46 ›› Issue (3): 213-221.doi: 10.12302/j.issn.1000-2006.202101024

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Simulation and analyses of ecological characteristics of Cerasus conradinae adaptability area

DONG Jingjing(), CHEN Jie, YANG Hong, LI Meng, WANG Xianrong, YI Xiangui^*()

Co-Innovation Center for Sustainable Forestry in Southern China,College of Biology and Environment, Cerasus Research Center, Nanjing Forestry University, Nanjing 210037,China.

Received:2021-01-19 Accepted:2021-04-12 Online:2022-05-30 Published:2022-06-10
Contact: YI Xiangui E-mail:2657438134@qq.com;yixiangui@njfu.edu.cn

Abstract

Abstract:

【Objective】Cerasus conradinae is a endemic plant resource in China, with high ornamental value and utilization prospects. The impacts of climate change on its geographical distribution in the present and future (2050s, 2070s) were analyzed to provide a theoretical basis for the protection and utilization of C. conradinae.【Method】Based on data from 201 geographical distribution points for C. conradinae combined with climate characteristics, the MaxEnt model and ArcGIS software were used to predict its potential adaptive area in China. The contribution rate, knife cutting test, response curve drawing, principal component analysis and correlation analysis were used to make qualitative and quantitative analyses of the leading environmental factors.【Result】 The MaxEnt model precision detection is very reliable, with a regularized training gain of 0.945, and a test gain of 0.949, The potential adaptive area of C. conradinae is mainly in southwest, central and east China. The two core adaptive areas are concentrated in Chongqing and the area from the Sichuan Basin to the west, Wuling Mountain to the east, the Dalou Mountains to the south and Daba Mountain to the north, as well as the eastern Yunnan-Guizhou Plateau, the Miao Mountain range and the western edge of the Xuefeng Mountain range long strip area. The main environmental factors affecting its distributions were the wettest quarterly precipitation (bio 16), annual precipitation (bio 12), seasonal variation in temperature (bio 4) and the annual temperature difference (bio 7). Under the change of the 2050s future climate (CCSM4) scenario, the total adaptive area decreased compared with the contemporary area, but increased in the 2070s, and the extremely adaptive area spreading to the high latitude in a northeasterly direction, while the highly adaptive area spread in the low latitude direction.【Conclusion】The MaxEnt model can accurately predict the potential adaptive area of C. conradinae. The normal distribution area of C. conradinae is continuous and widespread, and the core area of germplasm resources protection and use is southwest, central and east China. This paper has laid an important foundation for further research on germplasm protection, phylogeography and resource use of Cerasus conradinae.

Key words: Cerasus conradinae, MaxEnt, geographical distribution, dominant environmental factor

CLC Number:

S717

DONG Jingjing, CHEN Jie, YANG Hong, LI Meng, WANG Xianrong, YI Xiangui. Simulation and analyses of ecological characteristics of Cerasus conradinae adaptability area[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2022, 46(3): 213-221.

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References 32

[1]	文志, 郑华, 欧阳志云. 生物多样性与生态系统服务关系研究进展[J]. 应用生态学报, 2020, 31(1):340-348.
	WEN Z, ZHENG H, OUYANG Z Y. Research progress on the relationship between biodiversity and ecosystem services[J]. Chin J Appl Ecol, 2020, 31(1):340-348.DOI: 10.13287/j.1001-9332.202001.003. doi: 10.13287/j.1001-9332.202001.003
[2]	郭佳, 张宝林, 高聚林, 等. 气候变化对中国农业气候资源及农业生产影响的研究进展[J]. 北方农业学报, 2019, 47(1):105-113.
	GUO J, ZHANG B L, GAO J L, et al. Advances on the impacts of climate change on agro-climatic resources and agricultural production in China[J]. Inn Mong Agric Sci Technol, 2019, 47(1):105-113.DOI: 10.3969/j.issn.2096-1197.2019.01.18. doi: 10.3969/j.issn.2096-1197.2019.01.18
[3]	BEBBER D P, RAMOTOWSKI M A T, GURR S J. Crop pests and pathogens move polewards in a warming world[J]. Nat Clim Chang, 2013, 3(11):985-988. DOI: 10.1038/nclimate1990. doi: 10.1038/nclimate1990
[4]	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]. Biodivers Sci, 2013, 21(1):90-98.DOI: 10.3724/SP.J.1003.2013.09106. doi: 10.3724/SP.J.1003.2013.09106
[5]	许仲林, 彭焕华, 彭守璋. 物种分布模型的发展及评价方法[J]. 生态学报, 2015, 35(2):557-567.
	XU Z L, PENG H H, PENG S Z. The development and evaluation of species distribution models[J]. Acta Ecol Sin, 2015, 35(2):557-567.DOI: 10.5846/stxb201304030600. doi: 10.5846/stxb201304030600
[6]	NAGAI S, MORIMPTE H, SAITOH T M. A simpler way to predict flowering and full bloom dates of cherry blossoms by self-organizing maps[J]. Ecol Informatics, 2019, 56:101040. DOI: 10.1016/j.ecoinf.2019.101040. doi: 10.1016/j.ecoinf.2019.101040
[7]	PHILLIPS S, DUDIK M, SCHAPIRE R. A maximum entropy approach to species distribution modeling, 2004[C]. ACM, 2004. DOI: 10.1145/1015330.1015412. doi: 10.1145/1015330.1015412
[8]	中国植物志编辑委员会. 中国植物志[M]. 北京: 科学出版社, 1986.
[9]	王贤荣, 黄国富. 中国樱花类植物资源及其开发利用[J]. 林业科技开发, 2001, 15(6):3-6.
	WANG X R, HUANG G F. Resources and exploitation of Chinese cherries[J]. China For Sci Technol, 2001, 15(6):3-6.DOI: 10.3969/j.issn.1000-8101.2001.06.001. doi: 10.3969/j.issn.1000-8101.2001.06.001
[10]	禹霖, 李建挥, 柏文富, 等. 湖南大熊山野生樱花资源调查与利用评价[J]. 林业与环境科学, 2019, 35(6):38-43.
	YU L, LI J H, BAI W F, et al. Investigation and utilization evaluation of wild Cerasus resources in daxiong mountain of Hunan Province[J]. Guangdong For Sci Technol, 2019, 35(6):38-43.DOI: 10.3969/j.issn.1006-4427.2019.06.007. doi: 10.3969/j.issn.1006-4427.2019.06.007
[11]	柏文富, 禹霖, 李建挥, 等. 大围山樱属植物资源调查[J]. 湖南林业科技, 2019, 46(6):85-90.
	BAI W F, YU L, LI J H, et al. Investigation of Cerasus resources on Dawei Mountain[J]. Hunan For Sci Technol, 2019, 46(6):85-90.DOI: 10.3969/j.issn.1003-5710.2019.06.013. doi: 10.3969/j.issn.1003-5710.2019.06.013
[12]	付涛, 严春风, 林乐静, 等. 我国南方野生樱属植物的SSR亲缘关系分析[J]. 核农学报, 2018, 32(10):1949-1959.
	FU T, YAN C F, LIN L J, et al. Analysis of genetic relationship of wild Cerasus in south China with SSR markers[J]. J Nucl Agric Sci, 2018, 32(10):1949-1959.DOI: 10.11869/j.issn.100-8551.2018.10.1949. doi: 10.11869/j.issn.100-8551.2018.10.1949
[13]	伊贤贵. 武夷山樱属资源调查及开发利用研究[D]. 南京: 南京林业大学, 2007.
	YI X G. Studies on investigation and exploitation of the resources of Cerasus Mill.in Wuyi Mountain[D]. Nanjing: Nanjing Forestry University, 2007.
[14]	黎录松. 武夷山华中樱群落物种组成与结构特征[J]. 安徽农业科学, 2010, 38(6):3234-3237.
	LI L S. Community composition and structure characteristics of Cerasus cordnaria in Wuyishan National Nature Reserve of Fujian[J]. J Anhui Agric Sci, 2010, 38(6):3234-3237.DOI: 10.13989/j.cnki.0517-6611.2010.06.132. doi: 10.13989/j.cnki.0517-6611.2010.06.132
[15]	陈法志, 徐冬云, 蒋细旺, 等. 武汉市刘家山野生樱花资源调查及分析[J]. 江汉大学学报(自然科学版), 2017, 45(1):72-76.
	CHEN F Z, XU D Y, JIANG X W, et al. Investigation and analysis of wild cherry blossom resources in Liujiashan area of Wuhan[J]. J Jianghan Univ Nat Sci Ed, 2017, 45(1):72-76.DOI: 10.16389/j.cnki.cn42-1737/n.2017.01.012. doi: 10.16389/j.cnki.cn42-1737/n.2017.01.012
[16]	邱靖, 朱弘, 陈昕, 等. 基于DIVA-GIS的水榆花楸适生区模拟及生态特征[J]. 北京林业大学学报, 2018, 40(9):25-32.
	QIU J, ZHU H, CHEN X, et al. Modeling the suitable areas and ecological characteristics of Sorbus alnifolia using DIVA-GIS software[J]. J Beijing For Univ, 2018, 40(9):25-32.DOI: 10.13332/j.1000-1522.20180162. doi: 10.13332/j.1000-1522.20180162
[17]	邱浩杰, 孙杰杰, 徐达, 等. 基于MaxEnt模型预测鹅掌楸在中国的潜在分布区[J]. 浙江农林大学学报, 2020, 37(1):1-8.
	QIU H J, SUN J J, XU D, et al. MaxEnt model-based prediction of potential distribution of Liriodendron chinense in China[J]. J Zhejiang A&F Univ, 2020, 37(1):1-8.DOI: 10.11833/j.issn.2095-0756.2020.01.001. doi: 10.11833/j.issn.2095-0756.2020.01.001
[18]	赵儒楠, 何倩倩, 褚晓洁, 等. 气候变化下千金榆在我国潜在分布区预测[J]. 应用生态学报, 2019, 30(11):3833-3843.
	ZHAO R N, HE Q Q, CHU X J, et al. Prediction of potential distribution of Carpinus cordata in China under climate change[J]. Chin J Appl Ecol, 2019, 30(11):3833-3843.DOI: 10.13287/j.1001-9332.201911.020. doi: 10.13287/j.1001-9332.201911.020
[19]	田聪, 穆尼热, 朱忠艳, 等. 基于DIVA-GIS快速获取气候信息的方法[J]. 农学学报, 2015, 5(5):109-113.
	TIAN C, MU N R, ZHU Z Y, et al. Method for the rapid obtaining of climate data based on DIVA-GIS[J]. J Agric, 2015, 5(5):109-113.
[20]	朱弘, 尤禄祥, 李涌福, 等. 浙闽樱桃地理分布模拟及气候限制因子分析[J]. 热带亚热带植物学报, 2017, 25(4):315-322.
	ZHU H, YOU L X, LI Y F, et al. Modeling the geographical distribution pattern and climatic limited factors of Cerasus schneideriana[J]. J Trop Subtrop Bot, 2017, 25(4):315-322.DOI: 10.11926/jtsb.3702. doi: 10.11926/jtsb.3702
[21]	孙李勇, 蒋政, 刘晨妮, 等. 基于DIVA-GIS的紫玉兰地理分布及适生性分析[J]. 植物科学学报, 2018, 36(6):804-811.
	SUN L Y, JIANG Z, LIU C N, et al. Analysis of the adaptive and geographical distribution of Yulania liliiflora based on DIVA-GIS[J]. Plant Sci J, 2018, 36(6):804-811.DOI: 10.11913/PSJ.2095-0837.2018.60804. doi: 10.11913/PSJ.2095-0837.2018.60804
[22]	李璇, 李垚, 方炎明. 基于优化的Maxent模型预测白栎在中国的潜在分布区[J]. 林业科学, 2018, 54(8):153-164.
	LI X, LI Y, FANG Y M. Prediction of potential suitable distribution areas of Quercus fabri in China based on an optimized maxent model[J]. Sci Silvae Sin, 2018, 54(8):153-164.DOI: 10.11707/j.1001-7488.20180817. doi: 10.11707/j.1001-7488.20180817
[23]	GARAH K, BENTOUATI A. Using the MaxEnt model for assessing the impact of climate change on the Aurasian Aleppo pine distribution in Algeria[J]. Afr J Ecol, 2019, 57(4):500-511.DOI: 10.1111/aje.12630. doi: 10.1111/aje.12630
[24]	VANAGAS G. Receiver operating characteristic curves and comparison of cardiac surgery risk stratification systems[J]. Interact Cardiovasc Thorac Surg, 2004, 3(2):319-322.DOI: 10.1016/j.icvts.2004.01.008. doi: 10.1016/j.icvts.2004.01.008
[25]	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. doi: 10.3321/j.issn:1005-0094.2007.04.005
[26]	符潮, 万春, 戴利燕, 等. 江西樱属物种多样性分析[J]. 北方园艺, 2016(20):71-76.
	FU C, WAN C, DAI L Y, et al. Diversity of species analysis of Jiangxi Cerasus[J]. North Hortic, 2016(20):71-76.DOI: 10.11937/bfyy.201620020. doi: 10.11937/bfyy.201620020
[27]	王华辰, 朱弘, 李涌福, 等. 中国特有植物雪落樱桃潜在分布及其生态特征[J]. 热带亚热带植物学报, 2020, 28(2):136-144.
	WANG H C, ZHU H, LI Y F, et al. Potential distribution and ecological characteristic of Chinese endemic species Cerasus xueluoensis[J]. J Trop Subtrop Bot, 2020, 28(2):136-144.DOI: 10.11926/jtsb.4102. doi: 10.11926/jtsb.4102
[28]	NAN C H, WANG X R, TANG G G, et al. Cerasus xueluoensis(Rosaceae),a new species from China[J]. Ann Bot Fenn, 2013, 50(1/2):79-82.DOI: 10.5735/085.050.0114. doi: 10.5735/085.050.0114
[29]	朱淑霞, 朱弘, 程琳, 等. 高盆樱桃与钟花樱桃的地理分布模拟及生态特征比较分析[J]. 广西植物, 2019, 39(10):1398-1406.
	ZHU S X, ZHU H, CHENG L, et al. Modeling geographical distribution pattern and comparison of ecological characteristics between Cerasus cerasoides and C.campanulata[J]. Guihaia, 2019, 39(10):1398-1406.DOI: 10.11931/guihaia.gxzw201809004. doi: 10.11931/guihaia.gxzw201809004
[30]	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):31-41.
	ZHANG X W, LI Y, XIE Y P, et al. Effect of climate change on potential geographical distribution of Sorbus amabilis[J]. J Plant Resour Environ, 2018, 27(4):31-41.DOI: 10.3969/j.issn.1674-7895.2018.04.04. doi: 10.3969/j.issn.1674-7895.2018.04.04
[31]	江志红, 张霞, 王冀. IPCC-AR4模式对中国21世纪气候变化的情景预估[J]. 地理研究, 2008, 27(4):787-799.
	JIANG Z H, ZHANG X, WANG J. Projection of climate change in China in the 21st century by IPCC-AR4 models[J]. Geogr Res, 2008, 27(4):787-799.DOI: 10.3321/j.issn:1000-0585.2008.04.007. doi: 10.3321/j.issn:1000-0585.2008.04.007
[32]	姜大膀, 王会军, 郎咸梅. 全球变暖背景下东亚气候变化的最新情景预测[J]. 地球物理学报, 2004, 47(4):590-596.
	JIANG D P, WANG H J, LANG X M. East Asian climate change trend under global warming background[J]. Chin J Geophys, 2004, 47(4):590-596.DOI: 10.3321/j.issn:0001-5733.2004.04.007. doi: 10.3321/j.issn:0001-5733.2004.04.007

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变量序号 variable number	变量描述 description of variables	贡献率/% percent contribution	置换重要值/% permutation importance	变量序号 variable number	变量描述 description of variables	贡献率/% percent contribution	置换重要值/% permutation importance
bio 12	年均降水量annual mean precipitation	50.4	31.6	bio 3	等温性isothermality	0.7	2.0
bio 7	温度年较差 temperature annual range	14.7	0.5	bio 19	最冷季降水量precipitation in the coldest season	0.6	5.4
bio 4	温度季节变化方差variance of temperature seasonal change	8.0	28.4	bio 14	最干月降水量driest monthly precipitation	0.4	0.2
bio 17	最干季降水量precipitation in the driest season	6.1	2.3	bio 15	季节降水量变异系数variation coefficient of seasonal precipitation	0.2	1.1
bio 6	极端最低温extreme minimum temperature	5.0	1.8	bio 16	最湿季降水量precipitation in the wettest season	0.2	1.2
bio 1	年均温annual mean temperature	3.8	1.3	bio 8	最湿季均温mean temperature in the wettest season	0.2	0.8
bio 9	最干季均温mean temperature in the driest season	3.2	13.1	bio 5	极端最高温extreme maximum temperature	0.2	5.1
bio 2	平均日温差mean temperature diurnal range	2.4	0.3	bio 18	最暖季降水量precipitation in the warmest season	0.1	1.8
bio 10	最暖季均温mean temperature in the warmest season	2.1	1.1	bio 13	最湿月降水量wettest monthly precipitation	0.1	1.7
bio 11	最冷季均温mean temperature in the coldest season	1.8	0.2

主成分 principal component	特征值 eigenvalue	方差贡献率/% variance contribution rate	累计贡献率/% cumulative contribution rate
1	4.52	45.22	45.22
2	3.07	30.68	75.90
3	1.64	16.38	92.27

气候因子 climatic factors	主成分principal component
气候因子 climatic factors	PC1	PC2	PC3
bio 4	0.02	0.83	0.40
bio 6	0.73	-0.33	0.55
bio 7	-0.33	0.82	0.29
bio 9	0.80	-0.36	0.44
bio 11	0.70	-0.49	0.50
bio 12	0.83	0.46	-0.26
bio 16	0.85	0.03	-0.46
bio 17	0.67	0.69	-0.01
bio 18	0.63	-0.33	-0.60
bio 19	0.70	0.66	-0.05

参数 parameter	bio 7	bio 16	bio 4	bio 12	海拔 altitude	经度 longitude
bio 16	-0.331^**	-
bio 4	0.806^**	-0.112	-
bio 12	0.007	0.820^**	0.315^**	-
海拔altitude	-0.211^**	-0.259^**	-0.601^**	-0.467^**	-
经度longitude	0.460^**	0.377^**	0.685^**	0.756^**	-0.588^**	-
纬度latitude	0.601^**	-0.516^**	0.455^**	-0.383^**	0.115	-0.041

时期 period	气候情境 climatic scenario	适生区面积/万km² permissive area				面积合计/万km² total area
时期 period	气候情境 climatic scenario	低low	中middle	高high	极高extremely high	面积合计/万km² total area
当代contemporary		74.79	65.32	28.43	1.46	170.00
2050s	RCP 2.6	83.29	53.57	28.49	2.85	168.20
	RCP 4.5	71.53	60.26	38.97	4.68	175.44
	RCP 6.0	76.79	50.55	36.90	4.45	168.69
	RCP 8.5	74.15	55.71	35.18	3.33	168.37
2070s	RCP 2.6	78.19	66.16	32.50	2.41	179.26
	RCP 4.5	77.78	57.44	29.76	2.02	167.00
	RCP 6.0	84.30	54.86	34.59	6.28	180.03
	RCP 8.5	68.82	63.03	40.89	4.70	177.44

Simulation and analyses of ecological characteristics of Cerasus conradinae adaptability area

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[10]	CHEN Yuheng, LÜ Yiwei, YIN Xiaojie. Predicting habitat suitability of 12 coniferous forest tree species in southwest China based on climate change [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(6): 113-120.
[11]	MA Qingjiang, SUN Caowen, ZHANG Leying, HU Ziheng, ZHANG Shijiao, FU Xiangxiang. Identification of potential distribution region for East Asian dogwoods (Cornus) in China [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(5): 135-140.
[12]	JIANG Yifan,LI Mingyang,LIU Yanan,LIU Fei. Impact of climate change on suitable habitats of Pinus massoniana in Hunan Province [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2019, 43(04): 94-100.
[13]	WANG Lu, WU Xiuping, LI Yao, XU Xiaogang. Prediction of suitable cultivation area for Halesia carolina L. in China [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2018, 42(05): 10-16.
[14]	LIU Qingliang, LI Yao^{1, 3}, FANG Shengzuo^{1, 2}. MaxEnt model-based identification of potential Cyclocarya paliurus* cultivation regions [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2017, 41(04): 25-29.
[15]	WU Xiankun, NAN Chenhui, TANG Gengguo, LI Yao, MAO Lijun, ZHANG Zhicheng. Impact of climate change on potential distribution range and spatial pattern of Phoebe chekiangensis [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2016, 40(06): 85-91.