基于MaxEnt模型的单花荠生境适宜性分析及其分布变化

doi:10.12302/j.issn.1000-2006.202302003

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南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (5): 173-180.doi: 10.12302/j.issn.1000-2006.202302003

基于MaxEnt模型的单花荠生境适宜性分析及其分布变化

李瑞兰¹(), 樊锦雅², 赵倩², 李廷菊², 王成辉¹, 丁荣², 古锐¹^,^*(), 钟世红³

1.成都中医药大学民族医药学院,四川成都 611137
2.成都中医药大学药学院,四川成都 611137
3.西南民族大学药学院,四川成都 610041

收稿日期:2023-02-03 修回日期:2023-05-19 出版日期:2024-09-30 发布日期:2024-10-03
通讯作者: * 古锐(664893924@qq.com),教授。
作者简介:
李瑞兰(2370403423@qq.com)。
基金资助:
国家重点研发计划(2019YFC1712302);国家重点研发计划(2019YFC1712305)

Estimation of habitat suitability and climatic distribution change of Pegaeophyton scapiflorum based on the MaxEnt model

LI Ruilan¹(), FAN Jinya², ZHAO Qian², LI Tingju², WANG Chenghui¹, DING Rong², GU Rui¹^,^*(), ZHONG Shihong³

1. College of Ethnic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
2. College of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
3. College of Pharmacy, Southwest Minzu University College, Chengdu 610041, China

Received:2023-02-03 Revised:2023-05-19 Online:2024-09-30 Published:2024-10-03

摘要/Abstract

摘要：

【目的】探讨影响单花荠(Pegaeophyton scapiflorum)分布的主导气候因子,模拟其潜在适宜分布区,为单花荠的野生资源调查与保护提供合理依据。【方法】基于单花荠在中国的88个分布点数据和8个环境因子数据,运用最大熵(MaxEnt)模型预测在当前气候模式和RCP 2.6、RCP 4.5和RCP 8.5等3种未来气候变化模式下到2050年和2070年我国单花荠潜在适生区的变化情况,综合分析影响单花荠分布的主要环境因子及其适宜范围。【结果】①模型精度较高,AUC值为0.887。预测显示当代单花荠潜在适生区主要分布在青藏高原地区,总适生区面积约310万km²,含高适生区约80.81万km²。②地形地貌、温度和降水是影响单花荠分布的主要环境因子,其中分别以海拔、等温性和年平均降水量的影响最大。③在不同气候变化模式下,到2050年和2070年我国单花荠的适生区面积相对当前缩减24%~28%,高适生区降级成中适生区或低适生区,将表现为明显缩减甚至面临消失,且分布重心有向西、向高海拔区域偏移的趋势。【结论】研究结果可为单花荠野生资源的保护与可持续开发利用及人工栽培提供重要的参考依据。

关键词: 野生植物资源, 单花荠, 最大熵(MaxEnt)模型, 潜在适生区, 青藏高原

Abstract:

【Objective】 Pegaeophyton scapiflorum can be found mainly in the high altitudes of the Qinghai-Xizang Plateau in China, and the traditional surveys are difficult to implement. This study explored the dominant climatic factors that limit the distribution of P. scapiflorum in China and simulated its suitable distribution areas. The goal was to provide a theoretical basis for the investigation and protection of wild resources of P. scapiflorum. 【Method】 This study was based on 88 distribution sites and eight environmental factor variables of P. scapiflorum in China. The MaxEnt model was employed to predict the changes in its potential habitat. Additionally, the possible influence of climatic change under the extremely pessimistic representative concentration pathways scenarios RCP 2.6, RCP 4.5 and RCP 8.5 for the 2050s and 2070s were estimated. A comprehensive analysis of the main environmental factors affecting the distribution of P. scapiflorum was conducted. 【Result】 (1) The prediction accuracy of the MaxEnt model was high, and the AUC was 0.887. The prediction showed that P. scapiflorum is mainly located in the Qinghai-Xizang Plateau currently. The highly suitable areas were mainly distributed in the Kailas Range, Himalayas, southern valley of Xizang, Qaidam Basin, Nyainqêntanglha Mountains, Tanggula Mountains, the southern section of the Aemye Ma-chhen Range, the northern part of the Songpan-Ganzi Plateau, and Hengduan Mountain. The total suitable area of the potential geographical distribution of P. scapiflorum was approximately 310 × 10⁴ km², including 80.81 × 10⁴ km² of highly suitable areas. (2) The main environmental factor variables affecting the potential geographical distribution of P. scapiflorum were geomorphology, temperature, and precipitation, among which dem, isothermality, and annual precipitation aere the key environmental factors. (3) Under different climate change models, the suitable habitat will be reduced by 24%-28% compared with the present situation by 2050s and 2070s. The highly suitable area would be downgraded to the medium or low suitable area to significantly reduce or even disappear, and the distribution center of P. scapiflorum tended to migrate to the westward and higher altitudes. 【Conclusion】 Study results are an important reference for the conservation, sustainable development, and utilization of wild resources and artificial cultivation of P. scapiflorum.

Key words: wild plant resources, Pegaeophyton scapiflorum, maximum entropy (MaxEnt) model, the potential distribution, Qihai-Xizang Plateau

中图分类号:

S718

李瑞兰,樊锦雅,赵倩,等. 基于MaxEnt模型的单花荠生境适宜性分析及其分布变化[J]. 南京林业大学学报（自然科学版）, 2024, 48(5): 173-180.

LI Ruilan, FAN Jinya, ZHAO Qian, LI Tingju, WANG Chenghui, DING Rong, GU Rui, ZHONG Shihong. Estimation of habitat suitability and climatic distribution change of Pegaeophyton scapiflorum based on the MaxEnt model[J].Journal of Nanjing Forestry University (Natural Science Edition), 2024, 48(5): 173-180.DOI: 10.12302/j.issn.1000-2006.202302003.

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编号 No.	地点 site	纬度(N) latitude	经度(E) longitude	海拔/m altitude	生境 habitat
A	青海称多县清水河镇	34°07'41.13″	97°39'42.45″	4 752	山坡、草甸、碎石滩、溪流(浅流水)
B	青海玛沁县下大武乡	34°53'26.69″	99°26'45.57″	4 446	山坡、碎石滩、浅流水、石隙
C	青海久治县雪山乡	34°34'38.24″	99°26'53.99″	4 704	山坡、碎石滩、干涸河床
D1&D2	青海玉树市格拉山	32°34'34.01″	97°12'39.70″	4 765	山坡、干涸河床、溪流、石隙
E	西藏山南市桑日县	29°36'0.04″	92°24'15.39″	4 627	山坡、溪流、流水滩、石隙
F	西藏当雄县纳木湖乡	30°40'14.33″	91°05'01.99″	5 115	山坡、碎石滩、干涸河床
G	西藏林芝市鲁朗镇色季拉山	29°36'34.56″	94°39'21.10″	4 478	山坡、溪流
H	四川阿坝州莲保叶则	33°03'49.05″	101°08'50.64″	4 292	多石浅水流、草甸、石隙
I	四川甘孜州乡城县格鲁柯	29°07'51.24″	100°03'05.76″	4 638	山坡、高山草甸、溪流石隙
J	云南德钦县岭乡永支村	28°05'38.38″	98°45'34.89″	—	山腰小溪溪水边、石隙

环境因子 environmental factor variables	变量描述 variable description	贡献率/% percent contribution	累积贡献率/% cumulative contribution rate	置换重要值 permutation importance
dem	海拔/m	60.2	60.2	42.3
bio_3	等温性(bio_2/bio_7 ×100)	17.9	78.1	27.7
bio_12	年均降水量/mm	8.3	86.4	5.2
geomor	地貌	3.8	90.2	9.3
bio_6	最冷月最低温/℃	3.0	93.2	6.7
srad_07	7月太阳辐射/(kJ·m^-2·d^-1)	2.8	96.0	2.1
soil_types	土壤类型	2.2	98.2	2.3
bio_17	最干季度降水量/mm	1.8	100.0	4.4

基于MaxEnt模型的单花荠生境适宜性分析及其分布变化

Estimation of habitat suitability and climatic distribution change of Pegaeophyton scapiflorum based on the MaxEnt model

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