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

doi:10.3969/j.issn.1000-2006.201812037

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2020, Vol. 44 ›› Issue (3): 163-170.doi: 10.3969/j.issn.1000-2006.201812037

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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 E-mail:2004honglan@163. com;zhlu856@ 163. com

Abstract

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

CLC Number:

S718

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, 2020, 44(3): 163-170.

Figures/Tables 8

Table 1

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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

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

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