植物生态学报 ›› 2007, Vol. 31 ›› Issue (5): 825-833.DOI: 10.17521/cjpe.2007.0104
收稿日期:
2005-12-13
接受日期:
2006-05-31
出版日期:
2007-12-13
发布日期:
2007-09-30
作者简介:
E-mail: nnlwf1999@gmail.com
基金资助:
LENG Wen-Fang1,2(), HE Hong-Shi1,3, BU Ren-Cang1, HU Yuan-Man1
Received:
2005-12-13
Accepted:
2006-05-31
Online:
2007-12-13
Published:
2007-09-30
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。
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
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 | 100 m | ||||||||||||||||
长白落叶松分布图The distribution map of Loc | 中国1∶100万植被 | |||||||||||||||||
华北落叶松分布图The distribution map of Lpr | 中国1∶100万植被 | |||||||||||||||||
数字高程图Digital elevation model(DEM) | 东北1∶25万地形 | |||||||||||||||||
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 |
表1 空间数据集
Table 1 The spatial datasets
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 | 100 m | ||||||||||||||||
长白落叶松分布图The distribution map of Loc | 中国1∶100万植被 | |||||||||||||||||
华北落叶松分布图The distribution map of Lpr | 中国1∶100万植被 | |||||||||||||||||
数字高程图Digital elevation model(DEM) | 东北1∶25万地形 | |||||||||||||||||
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 | A1· |
0 | a21 | a22 | A2· | |
行和r Row sum | A·1 | A·2 | Asum |
表2 观测值与预测值的列联表
Table 2 The contingency table of observed value and predicted value
观测值 Observed value | 列和i Column sum | |||
---|---|---|---|---|
1 | 0 | |||
预测值 Predicted value | 1 | a11 | a12 | A1· |
0 | a21 | a22 | A2· | |
行和r Row sum | A·1 | A·2 | Asum |
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 |
表3 Logistic回归模型的系数*
Table 3 The coefficients of Logistic regression model*
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 |
敏感性 Sensitivity | 指定度 Specificity | 总正确率 PerC | 概率阈值 Cutoff value | |
---|---|---|---|---|
兴安落叶松 Lg | 88 | 86 | 86 | 0.85 |
长白落叶松 Loc | 78 | 80 | 80 | 0.60 |
华北落叶松 Lpr | 61 | 99.8 | 99.8 | 0.70 |
表4 Logistic模型的预测精度
Table 4 The prediction precision of Logistic regression model
敏感性 Sensitivity | 指定度 Specificity | 总正确率 PerC | 概率阈值 Cutoff value | |
---|---|---|---|---|
兴安落叶松 Lg | 88 | 86 | 86 | 0.85 |
长白落叶松 Loc | 78 | 80 | 80 | 0.60 |
华北落叶松 Lpr | 61 | 99.8 | 99.8 | 0.70 |
图1 各气候变化方案下落叶松属的预测面积大小 tem0~tem5: 分别代表气温增加0~5 ℃ Represent the temperature increase 0~5 ℃ d10~d30:分别代表降水减少10%~30% Represent the precipitatiion decrease 10%-30%, respectively pre0:代表降水不变 Represent the precipitation does not change i10~i30:分别代表降水增加10%~30% Represent the precipitation increase 10%-30%, respectively
Fig.1 Prediction area of Larix genus under climate changing scenarios
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