气候变化下西南地区12种常见针叶树种适宜分布区预测

doi:10.3969/j.issn.1000-2006.201808045

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南京林业大学学报（自然科学版） ›› 2019, Vol. 43 ›› Issue (6): 113-120.doi: 10.3969/j.issn.1000-2006.201808045

气候变化下西南地区12种常见针叶树种适宜分布区预测

陈禹衡¹(), 吕一维², 殷晓洁¹^,^*()

1.西南林业大学林学院,云南昆明 650224
2.东北林业大学林学院,黑龙江哈尔滨 150040

收稿日期:2018-08-24 修回日期:2019-09-08 出版日期:2019-11-30 发布日期:2019-11-30
通讯作者: 殷晓洁
基金资助:
国家自然科学基金项目(31700467);云南省高校优势特色重点学科(生态学)建设项目

Predicting habitat suitability of 12 coniferous forest tree species in southwest China based on climate change

CHEN Yuheng¹(), LÜ Yiwei², YIN Xiaojie¹^,^*()

1. College of Forestry, Southwest Forestry University, Kunming 650224, China
2. School of Forestry, Northeast Forestry University, Harbin 150040, China

Received:2018-08-24 Revised:2019-09-08 Online:2019-11-30 Published:2019-11-30
Contact: YIN Xiaojie

摘要/Abstract

摘要：

【目的】随气候变化加剧,未来西南地区针叶林分布存在诸多不确定性,进行未来气候下西南地区常见针叶树种适宜分布区研究,为该地区森林生态安全评估提供参考。【方法】基于最大熵模型(MaxEnt)模拟未来气候情景下西南地区常见的12种针叶树的气候适宜分布区。【结果】MaxEnt模型能够很好地模拟西南地区12个树种的潜在分布,AUC值均达0.9以上; 2070年MPI-ESM-LR模式RCP4.5情景下西南地区12种常见针叶树种气候适宜区面积分布变化显著,包括冷杉、三尖杉、杉木、干香柏、柏木、水杉、云南松、红豆杉和福建柏在内的9个树种气候适宜区与气候最适区面积增加11.1%~412.8%;银杉和油麦吊云杉的气候适宜区面积分别增加6.0%和32.8%,但气候最适区面积减少了0.8%和3.5%;云南油杉未来气候适宜区和气候最适区的面积则减少24.0%和29.1%。【结论】西南地区针叶林中广布树种的气候适宜区面积会得益于气候变化而扩大,但云南油杉和油麦吊云杉等一些西南特有乡土树种的气候适宜区面积则会因为气候变化而缩小,因此对特有乡土树种的保护应给予重视。

关键词: 针叶树, 适宜分布区, 气候变化, MaxEnt模型, 西南地区

Abstract:

【Objective】Coniferous forests in southwest China are important biodiversity hotspots, but they are under significant threat from ongoing climatic changes. In this study we explored the predicted changes in habitat suitability for 12 key tree species.【Method】We used MaxEnt models to predict habitat suitability for 12 coniferous tree species that are currently present in southwest China. 【Result】The AUC values (receiver operating characteristics, area under curve) of all 12 species were more than 0.9, suggesting our results are highly supported. We found that the climatically suitable area of all species under representative concentration pathways scenario 4.5 in 2070 will increase greatly. For 9 of the 12 species (Abies fabri, Cephalotaxus fortunei, Cunninghamia lanceolata, Cupressus duclouxiana, Metasequoia glyptostroboides, Pinus yunnanensis, Fokienia hodginsii, Taxus wallichiana var. chinensis and Cupressus funebris), both the total climatically suitable area and the area of optimal climate will increase 11.1% and 412.8% than the current areal, respectively. ForPicea brachytyla and Cathaya argyrophylla, the total climatically suitable area will increase by 6.0% and 32.8%, respectively, but the area of optimal conditions will decrease ( P. brachytyla by -0.8%; C. argyrophylla by -3.5%). However, for Keteleeria evelyniana, both the total climatically suitable area and the area of optimal climate area will respectively decrease by 24.0% and 29.1%.【Conclusion】Overall, our models show that climate change is expected to increase the range of various widely distributed coniferous tree species. However, for specialized coniferous species like Picea brachytyla and Keteleeria evelyniana, there will be a range decrease as conditions change. We suggest that more attention be paid to specialized forest conifer species, particularly in relation to expected climatic changes.

Key words: coniferous tree, ecological suitable area, climate change, MaxEnt model, southwest China

中图分类号:

Q948.5
S718

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.

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 (Natural Science Edition), 2019, 43(6): 113-120.DOI: 10.3969/j.issn.1000-2006.201808045.

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代号 code	中文名 Chinese name	学名 species name	样点数 records number
Af	冷杉	Abies fabri (Mast.) Craib	27
Ca	银杉	Cathaya argyrophylla Chun et Kuang	14
Cef	三尖杉	Cephalotaxus fortunei Hooker	297
Cl	杉木	Cunninghamia lanceolata (Lambert) Hooker	287
Cd	干香柏	Cupressus duclouxiana Hickel	61
Cuf	柏木	Cupressus funebris Endlicher	215
Fh	福建柏	Fokienia hodginsii (Dunn) Henry et Thomas	95
Ke	云南油杉	Keteleeria evelyniana Masters	57
Mg	水杉	Metasequoia glyptostroboides Hu et Cheng	47
Pb	油麦吊云杉	Picea brachytyla (Franchet) Pritzel	52
Py	云南松	Pinus yunnanensis Franchet	153
Tw	红豆杉	Taxus wallichiana var. chinensis (Pilger) Florin	81

气候因子(代号) climate scenario (code)	各因子在不同树种模型计算中的贡献占比/% contribution in models for every scenarios												贡献率/% contribution ratio
气候因子(代号) climate scenario (code)	Af	Ca	Cef	Cl	Cd	Cuf	Fh	Ke	Mg	Pb	Py	Tw	贡献率/% contribution ratio
年平均气温 (bio 1)	0	0	1.3	1.9	0.2	0.2	2	4.4	0	0	0.2	1.9	1.0
平均气温日较差 (bio 2)	0	10.5	1.8	1.4	0.1	0.9	0	0	0	0.1	1.2	0	1.3
等温性 (bio 3)	8.9	4.6	0.5	1	9.9	0.3	0.3	13.8	0.6	25.4	8.8	4.1	6.5
气温季节变动系数(bio 4)	23.4	3.4	2.2	0.7	39.7	2.4	3.3	50.5	2.9	15.4	45.7	9.1	16.6
最热月最高气温(bio 5)	0.1	0	0	0.5	2.5	0.1	0	0	0	0	0.3	0.2	0.3
最冷月最低气温(bio 6)	6.5	70.4	20.1	14.1	11.1	33.1	0.9	7.2	3.6	14.6	6.8	39.9	19.0
气温年较差(bio 7)	0	1.3	4.4	2.2	0	5	2.5	4	0	8.4	4	5.9	3.1
最湿季平均气温(bio 8)	0	1.1	2.2	2.8	1.4	1.6	4.9	1.3	0.9	0	0.2	2.1	1.5
最干季平均气温(bio 9)	0	0	0.4	0.2	0	0.1	0.2	0	0	0	1.9	0.4	0.3
最热季平均气温(bio 10)	0	0	3.6	1.9	6.6	1	1.5	0	9.5	15.3	5.1	0.4	3.7
最冷季平均气温(bio 11)	0	0	5.4	1.9	0.8	3.1	0.5	1	0	0	0.1	0.1	1.1
年降水量(bio 12)	38.4	0	33.1	42.8	20.3	45.3	4.2	15.4	0.9	19.8	23	27.7	22.6
最湿月降水量(bio 13)	0.3	0	0.9	0	0	0	0	0.5	0.5	0	0	0.8	0.3
最干月降水量(bio 14)	0	0	21.6	0	5.4	3.5	78.8	0	79.6	0.2	0.2	1	15.9
降水量季节性变化系数(bio 15)	16.6	8.6	0.8	0.4	0.2	0.8	0.6	0.1	0.6	0.1	0.3	0.6	2.5
最湿季降水量(bio 16)	0	0	0.1	0.1	0.6	0.1	0	0.2	0.5	0.6	0.1	0	0.2
最干季降水量(bio 17)	0.6	0	0.1	27	1.2	0	0.2	0.2	0.1	0	0	0	2.5
最热季降水量(bio 18)	0	0	0.9	0.1	0	0.1	0.1	1.3	0.1	0	1.6	0	0.4
最冷季降水量(bio 19)	5.2	0	0.7	1	0.1	2.4	0	0.3	0	0.1	0.5	5.8	1.3
AUC²	0.98	0.89	0.85	0.82	0.94	0.86	0.87	0.96	0.84	0.97	0.94	0.86

树种 species	适宜区面积 suitable climate habitat		最适区面积 the most suitable climate habitat
树种 species	当前 incurrent	2070 RCP4.5	当前 incurrent	2070 RCP4.5
冷杉	32.92	45.40	12.85	15.52
银杉	83.88	88.89	18.00	17.86
三尖杉	99.72	167.53	21.44	109.94
杉木	122.91	166.59	22.50	109.19
干香柏	37.86	65.25	15.80	38.36
柏木	111.77	156.61	21.47	87.00
福建柏	73.56	81.74	12.97	30.97
云南油杉	21.63	16.44	9.91	7.03
水杉	75.90	141.18	20.32	86.70
油麦吊云杉	21.41	28.44	9.74	9.40
云南松	40.56	70.53	17.53	47.41
红豆杉	69.98	126.18	17.91	54.49

气候变化下西南地区12种常见针叶树种适宜分布区预测

Predicting habitat suitability of 12 coniferous forest tree species in southwest China based on climate change

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