中国东北落叶松属3种植物潜在分布对气候变化的敏感性分析

doi:10.17521/cjpe.2007.0104

摘要/Abstract

摘要：

该文在东北地区多年平均的年均温、年降水分布图,海拔高程图、坡度图、坡向图和植被图的基础上,使用地理信息系统和Logistic回归模型的结合,预测3种落叶松(Larix sp.)的“气候-地形”潜在分布区。预测精度用敏感性、指定度和总正确率进行评价,3个树种的敏感性为61%~88%,指定度为80%~99.8%,总正确率为80%~99.8%。年均温、年降水和海拔是控制3种落叶松分布的主要环境因子。采用5种气温变化方案(+1 ℃、+2 ℃、+3 ℃、+4 ℃和+5 ℃)和6种降水变化方案(-30%、-20%、-10%、+10%、+20%和+30%),预测气候变化对各个树种潜在分布的影响,探索不同的树种对气候因子的敏感性。结果表明,气温每上升1 ℃,兴安落叶松(Larix gmelinii)将减少12%;长白落叶松(Larix olgensis var. changpaiensis)将增加23%;华北落叶松(Larix principis-rupprecntii)将增加500%。降水每增加10%,兴安落叶松将减少12.5%;长白落叶松将增加64%;华北落叶松将减少15%;随气候的“暖干化"(+5 ℃,-30%),兴安落叶松将向西北方退缩100 km左右;长白落叶松向西北方扩展100 km左右;华北落叶松将向东北方扩展800 km左右。随气候的“暖湿化"(+5 ℃,+30%),兴安落叶松将向西北退缩400 km左右;长白落叶松将向西北方扩展550 km;华北落叶松将向东北方扩展320 km左右。

关键词: 兴安落叶松, 长白落叶松, 华北落叶松, 潜在分布, 气候变化, 敏感性

Abstract:

Aims Prediction of potential distribution of tree species and their responses to climate change is an increasingly important field of global change. Larix are important tree species in northeastern China. In this study we predict the potential distribution of three Larix species based on “climatic-topographic" relationships. Our aims are to determine: 1) the dominant factors that control the distributions of the three Larix species and 2) the sensitivities of the species to climate change.

Methods Spatial overlap analysis was used to sample the distribution information of the three Larix species and corresponding environmental factors. A logistic regression model was used to explore the quantitative relationships between environmental factors and Larix species. A map calculator method was used to transform the results of the logistic regression model to a prediction map in ArcGIS. Three indices (sensitivity, specificity and percentage of correctness) were used to assess the prediction accuracy of the logistic regression models. Five temperature change scenarios (+1 ℃, +2 ℃, +3 ℃, +4 ℃, and +5 ℃) and six precipitation change scenarios (-30%, -20%, -10%, +10%, +20%, and +30%) were used to explore the impacts of climate change on the distributions of the three Larix and the sensitivities of the species to climate factors.

Important findings Mean annual temperature, annual precipitation and elevation were found to be dominant factors controlling the distributions of the Larix species. The sensitivity of the species changed from 61% to 88%, the specificity changed from 80% to 99.8% and the percentage of correctness changed from 80% to 99.8%. Larix gmelinii decreases by 12% and L. olgensis var. changpaiensis and L. principis-rupprechtii increase by 23% and 500%, respectively, with the temperature increase 1 ℃. L. olgensis var. changpaiensis increases by 64% and L. gmelinii and L. principis-rupprecntii decrease by 12.5% and 15%, respectively, with the precipitation increasing 10%. With climate change to “warm and dry" (+5 ℃, -30%), L. gmelinii shifts northwestward by about 100 km, L. olgensis var. changpaiensis expands northwestward by about 100 km and L. principis-rupprecntii expands northeastward by about 800 km. With climate change to “warm and wet" (+5 ℃, +30%), L. gmelinii shifts northwestward by about 400 km, L. olgensis var. changpaiensis expands northwestward by about 550 km and L. principis-rupprecntii expands northeastward by about 320 km. All three species are sensitive to climate change; therefore, future climate change in northeastern China may greatly impact their distributions.

Key words: Larix gmelinii, Larix olgensis var. changpaiensis, Larix principis-rupprecntii, potential distribution, climate change, sensitivity

冷文芳, 贺红士, 布仁仓, 胡远满. 中国东北落叶松属3种植物潜在分布对气候变化的敏感性分析. 植物生态学报, 2007, 31(5): 825-833. DOI: 10.17521/cjpe.2007.0104

LENG Wen-Fang, HE Hong-Shi, BU Ren-Cang, HU Yuan-Man. SENSITIVITY ANALYSIS OF THE IMPACTS OF CLIMATE CHANGE ON POTENTIAL DISTRIBUTION OF THREE LARCH (LARIX) SPECIES IN NORTHEASTERN CHINA. Chinese Journal of Plant Ecology, 2007, 31(5): 825-833. DOI: 10.17521/cjpe.2007.0104

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2007.0104

https://www.plant-ecology.com/CN/Y2007/V31/I5/825

图/表 6

参考文献 19

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数据集 Data sets	数据来源 Data sources	空间分辨率 Resolution
兴安落叶松分布图The distribution map of Lg	中国1∶100万植被图1∶1×10⁶ vegetation map of China	100 m
长白落叶松分布图The distribution map of Loc	中国1∶100万植被图1∶1×10⁶ vegetation map of China
华北落叶松分布图The distribution map of Lpr	中国1∶100万植被图1∶1×10⁶ vegetation map of China
数字高程图Digital elevation model(DEM)	东北1∶25万地形图1∶2.5×10⁵ contour map of northeastern China
温度分布图Annual average temperature map	东北台站数据与DEM Weather station data of northeastern China
降水分布图Annual precipitation map	东北台站数据与DEM Weather station data of northeastern China
坡度分布图Slope map	海拔数字高程图 Digital elevation model
坡向分布图Transition aspect map (TRASP)	海拔数字高程图 Digital elevation model

数据集 Data sets	数据来源 Data sources	空间分辨率 Resolution
兴安落叶松分布图The distribution map of Lg	中国1∶100万植被图1∶1×10⁶ vegetation map of China	100 m
长白落叶松分布图The distribution map of Loc	中国1∶100万植被图1∶1×10⁶ vegetation map of China
华北落叶松分布图The distribution map of Lpr	中国1∶100万植被图1∶1×10⁶ vegetation map of China
数字高程图Digital elevation model(DEM)	东北1∶25万地形图1∶2.5×10⁵ contour map of northeastern China
温度分布图Annual average temperature map	东北台站数据与DEM Weather station data of northeastern China
降水分布图Annual precipitation map	东北台站数据与DEM Weather station data of northeastern China
坡度分布图Slope map	海拔数字高程图 Digital elevation model
坡向分布图Transition aspect map (TRASP)	海拔数字高程图 Digital elevation model

		观测值 Observed value		列和i Column sum
		1	0
预测值 Predicted value	1	a₁₁	a₁₂	A_1·
	0	a₂₁	a₂₂	A_2·
行和r Row sum		A_·1	A_·2	A_sum

		观测值 Observed value		列和i Column sum
		1	0
预测值 Predicted value	1	a₁₁	a₁₂	A_1·
	0	a₂₁	a₂₂	A_2·
行和r Row sum		A_·1	A_·2	A_sum

	系数 Coefficient			值域 Value range		新值域 New value range
	Lg	Loc	Lpr	极小Min	极大Max	Lg	Loc	Lpr
温度Temperature	-51.00	56.00	141.00	-6.87	11.26	(350,-574)	(-385,631)	(-969, 1 588)
降水Precipitation	-1.54	1.16	-1.51	219	880	(-337,-1 355)	(-254,1 021)	(-331, -1 329)
海拔Elevation	-0.14	-	0.89	-118	2 644	(17,-370)	(-,-)	(-105, 235 3)
坡度Slope	5.12	-4.60	-4.30	0	75	(0,384)	(0,-345)	(0, -323)
坡向Aspect	-7.04	-14.00	5.05	0	1	(0, -7)	(0,-14)	(0,5)
常数Intercept	880.00	-941.00	-555.00	-	-	880	-941	-555