未来气候变化对我国毛红椿适生区分布格局的影响预测

doi:10.3969/j.issn.1000-2006.201812037

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南京林业大学学报（自然科学版） ›› 2020, Vol. 44 ›› Issue (3): 163-170.doi: 10.3969/j.issn.1000-2006.201812037

未来气候变化对我国毛红椿适生区分布格局的影响预测

黄红兰¹^,³(), 钟沃谷², 衣德萍¹, 蔡军火³, 张露³()

^1.江西环境工程职业学院林业学院，江西赣州 341000
^2.复旦大学大气与海洋科学系，大气科学研究院, 上海 200438
^3.江西农业大学林学院，江西特色林木资源培育与利用2011协同创新中心，江西南昌 330045

收稿日期:2018-12-21 修回日期:2019-12-14 出版日期:2020-05-30 发布日期:2018-06-06
通讯作者: 张露
作者简介:黄红兰(2004honglan@163. com)，副教授，0RCID(0000-0001-6536-1200)。
基金资助:
江西省科技支撑重点项目(20151BBF60019);国家自然科学基金项目(31860202)

Predicting the impact of future climate change on the distribution patterns of Toona ciliata var. pubescens in China

HUANG Honglan¹^,³(), ZHONG Wogu², YI Deping¹, CAI Junhuo³, ZHANG Lu³()

^1.Forestry Institute, Jiangxi Environmental Engineering Vocational College, Ganzhou 341000, China
^2.Department of Atmospheric and Oceanic Sciences / Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
^3.2011 Collaborative Innovation Center of Jiangxi Typical Trees Cultivation and Utilization, College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China

Received:2018-12-21 Revised:2019-12-14 Online:2020-05-30 Published:2018-06-06
Contact: ZHANG Lu

摘要/Abstract

摘要： 目的

毛红椿(Toona ciliata var. pubescens)为楝科香椿属落叶乔木，被列为国家二级保护濒危物种。了解未来气候变化对中国毛红椿潜在适生区分布格局的影响，加强栖息地与环境因素间影响、适宜度等的评估，为其物种保护与生态恢复提供依据。

方法

基于来自中国江西、云南、安徽、浙江、湖南、广西、贵州、四川8 个省(区)的53个地理分布点，运用 MaxEnt 生态位模型，选取当前、未来 2040 s 和 2060 s 时段，于 RCP 2.6、RCP 4.5、RCP 8.5的3种温室气体排放情景下进行模拟预测，然后将分布模拟图经MapGIS 10.0识别、几何精校正与矢量化处理，进一步比较分析毛红椿未来分布格局的气候响应。

结果

本生态位模型的模拟效果理想，当前适生分布因东西向低纬度分布特征显著而呈形似狭长岛屿状分布，位于中国东部季风区，以雨热同期的亚热带季风气候为主，最热季平均降水量和气温决定毛红椿的适生分布区域，最冷月最低气温可能是其分布的主要限制气候因子。未来气候变化下，受未来分布区的降水量降低、冬季低温升高的气候变化影响，当前适生区可能发生华中分布区域以东的规模性消退，削减至当前规模的 31.90% ~63. 73% ；未来适生分布将随气候变化情景梯度向西迁移，其地理中心将移至云南省林区；较适生以上分布区域的分布格局波动将趋于集中，并将迁移至中国高海拔分布区的云南、四川、贵州等省境区域。

结论

总体上，未来气候可能对毛红椿的适宜程度、分布范围、分布规模与斑块状连续分布格局等产生负面影响，并形成较适生及以上区域的独岛状分布，进一步加剧毛红椿的濒危风险。建议加强对当前保护区内毛红椿不同地理居群的保护，将云南、四川、贵州等省列入未来气候变化监测的核心区域，分析毛红椿居群与气候环境波动，以及与地形小生境适应、变化的规律。

关键词: 气候变化, 气候因子, 地理分布, 适生区, MaxEnt模型, 毛红椿

Abstract: Objective

Toona ciliata var. pubescens, a deciduous broad-leaved plant, is a secondary endangered species under state protection in China. Understanding the impact of future climate change on the potential distribution patterns of T. ciliata var. pubescens in China and assessing the interaction between its habitat and environmental factors would contribute to its conservation and ecological restoration.

Method

The MaxEnt model was applied to the distribution data obtained from 53 locations spread across the Jiangxi, Yunnan, Anhui, Zhejiang, Hunan, Guangxi, Guizhou and Sichuan Provinces to estimate habitat suitability at present and in the future (by 2040s and 2060s) under three greenhouse gas emission scenarios of RCP 2.6, RCP 4.5 and RCP 8.5. The output data were processed using MapGIS 10.0 software, including identification, geometric correction and vectorization processing, and then used to analyze the response of T. ciliata var. pubescens to future climate change.

Result

The simulation results of the MaxEnt model were verified to be ideal. The current distribution pattern of T. ciliata var. pubescens was similar to a narrow island with its distinctive east-west features. This pattern was determined by the mean precipitation in the hottest quarter and temperature in a given year; the minimum air temperature of the coldest month may be the main limiting climatic factor for its distribution. The results illustrated that the suitable T. ciliata var. pubescens habitats will make a large-scale recession toward the east of central China under future climate change, mainly due to a decrease in rainfall and an increase in the minimum air temperature in winter. Under different greenhouse gas emission scenarios, the reduction rates in its habitable areas would vary from 31.90% to 63.73 %, and its geographic center would probably migrate into Yunnan Province. The distribution patterns in more suitable areas will become more concentrated and might migrate to the high-altitude areas of the Yunnan, Sichuan and Guizhou Provinces.

Conclusion

In brief, future climate change is likely to have negative effects on the suitability, distribution range, distribution scale, and patchy continuous distribution pattern of T. ciliata var. pubescens, and its distribution to higher suitability areas might be more concentrated. These combined effects will increase the degree of its future endangerment. We recommend strengthening the protection measures for T. ciliata var. pubescens not only in the currently protected areas but also in the sensitive areas of climate change, such as Yunnan, Sichuan, Guizhou and other Provinces. Further research should be focused on the relationship between the population fluctuation of T. ciliata var. pubescens and climate change as well as its adaptation to a particular ecological niche.

Key words: climate change, climatic factor, geographical distribution, suitable distribution area, MaxEnt model, Toona ciliata var. pubescens

中图分类号:

S718

黄红兰,钟沃谷,衣德萍,等. 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.

HUANG Honglan, ZHONG Wogu, YI Deping, CAI Junhuo, ZHANG Lu. Predicting the impact of future climate change on the distribution patterns of Toona ciliata var. pubescens in China[J].Journal of Nanjing Forestry University (Natural Science Edition), 2020, 44(3): 163-170.DOI: 10.3969/j.issn.1000-2006.201812037.

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变量 variable	变量编码 variable coding	变量 variable	变量编码 variable coding
年平均气温 mean annual air temperature	bio 1	最冷季平均气温 mean air temperature of the coldest quarter	bio 11
昼夜温差月均值mean of monthly (max.-min. air temperature)	bio 2	年均降水量 annual precipitation	bio 12
昼夜温差占年温差比 iso?thermality (bio 2×100/ bio 7)	bio 3	最湿月降水量 precipitation of the wettest month	bio 13
气温变化方差SD of air temperature change	bio 4	最干月降水量 precipitation of the driest month	bio 14
最热月最高气温 max. air temperature of the warmest month	bio 5	湿度变化方差SD of humidity seasonality	bio 15
最冷月最低气温min. air temperature of the coldest month	bio 6	最湿季降水量 precipitation of the wettest quarter	bio 16
年气温变化范围 air temperature annual range (bio 5-bio 6)	bio 7	最干季降水量 precipitation of the driest quarter	bio 17
最湿季平均气温 mean air temperature of the wettest quarter	bio 8	最热季平均降水量 mean precipitation of the warmest quarter	bio 18
最干季平均气温 mean air temperature of the driest quarter	bio 9	最冷季平均降水量 mean precipitation of the coldest quarter	bio 19
最热季平均气温 mean air temperature of the warmest quarter	bio 10

时期 period	气体排放情景 climate change	占比/% percentage of contemporary distribution	分布中心距离/ km distributed central distance
时期 period	气体排放情景 climate change	占比/% percentage of contemporary distribution	纬度方向latitude	经度方向longitude
当前潜在时段current potential period	current	100.00	3 530.21	1 046.87
2040 s	RCP 2.6	58.05	3 379.65	1 025.24
	RCP 4.5	63.73	3 378.21	1 027.01
	RCP 8.5	50.62	3 380.87	1 025.00
2060 s	RCP 2.6	58.96	3 379.37	1 025.19
	RCP 4.5	48.33	3 380.19	1 024.00
	RCP 8.5	31.90	3 381.33	1 024.98

2040 s			2060 s
变量 variable	贡献率/% contribution percent	随机分布重要值permutation importance	变量variable	贡献率/% contribution percent	随机分布重要值permutation importance
bio 18（RCP 2.6)	40.4	0.2	bio 18(RCP 2.6)	41.3	2.2
bio 6（RCP 2.6)	24.6	75.8	bio 6(RCP2.6)	23.1	72.3
bio19(RCP2.6)	9.4	3.2	bio 12(RCP 2.6)	10.0	0.0
bio10(RCP2.6)	8.5	5.8	bio 19(RCP 2.6)	9.5	3.8
bio 18（RCP 4.5)	42.6	3.0	bio 18(RCP4.5)	36.6	1.5
bio 6（RCP 4.5)	25.0	70.8	bio 6(RCP4.5)	20.2	78.0
bio19(RCP4.5)	9.5	5.3	bio 19(RCP4.5)	11.0	3.2
bio12(RCP4.5)	6.6	0.0	bio 10(RCP4.5)	9.4	3.1
bio 18（RCP 8.5)	40.2	2.4	bio 18(RCP 8.5)	40.4	2.7
bio 6（RCP 8.5)	24.3	79.7	bio 6(RCP 8.5)	23.2	66.1
bio19(RCP8.5)	9.5	4.3	bio 12(RCP 8.5)	10.2	0.0
bio12(RCP8.5)	8.9	0.0	bio 19(RCP 8.5)	9.1	3.7

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未来气候变化对我国毛红椿适生区分布格局的影响预测

Predicting the impact of future climate change on the distribution patterns of Toona ciliata var. pubescens in China

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