西北植被净初级生产力时空变化及其驱动因素
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摘要
利用CASA模型模拟了西北植被净初级生产力(NPP)值,并结合地统计学理论,利用趋势分析及相关性分析研究了西北地区2000—2013年植被NPP时空变化特征,并结合气象数据探究了其对气候变化的响应。结果表明:(1)西北地区植被NPP在研究年限内呈现波动增加趋势,线性增加趋势达到极显著水平(p<0.01)。(2)植被NPP分布具有明显的空间异质性,整体呈现由东向西递减的趋势,除新疆外,其余省份也总体上表现为南高北低的分布格局。植被NPP呈现增加趋势的面积占总面积的85.97%,主要集中在陕西北部、宁夏南部、甘肃东部、青海的东部及南部和新疆西部部分地区,呈现减少趋势主要集中在新疆西部;不同植被类型NPP的均值呈现明显的差异,具体表现为:草地[262.16 g C/(m~2·a)]>灌丛[66.51 g C/(m~2·a)]>农田[45.90 g C/(m~2·a)]>森林[14.36 g C/(m~2·a)]。2000—2013年草地、农田及灌丛的NPP均呈现极显著增加趋势(p<0.01),而森林NPP的增加趋势不显著(p>0.05)。(3)总体上,西北地区植被NPP与气温、降水呈正相关,其对降水响应较为敏感,降水是限制西北地区植被NPP增加的主要因素。
Based on the Carnegie-Ames-Stanford approach(CASA) model, the temporal and spatial variations of vegetation NPP in northwest China during the period 2000—2013 were analyzed by combining with geo-statistics theory and using trend and correlation analysis. Meanwhile, the relationships between vegetation NPP and climate change were also examined by using the meteorological data. The results showed that:(1) The vegetation NPP in northwest China presented the fluctuating increase trend which reached an extremely significant level(p<0.01);(2) The distribution of vegetation NPP had obvious spatial heterogeneity, which generally presented the decreasing trend from east to west; Except for Xinjiang, the other provinces also showed the low state in the north; the area with increasing vegetation NPP accounted for 85.97% of the total area, and mainly distributed in northern Shaanxi, southern Ningxia, eastern Gansu, eastern and southern parts of Qinghai, and parts of western Xinjiang, while the NPP presented the decreasing trend in west of Xinjiang; The average NPP values of different vegetation types showed significant differences, and followed an order of: grassland [262.16 g C/(m~2·a)]>shrub [66.51 g C/(m~2·a)]>farmland [45.90 g C/(m~2·a)]>forest [14.36 g C/(m~2·a)]; The NPP of grassland, farmland, and shrub all showed the extremely significant increase(p<0.01), but the increase of forests was not obvious(p>0.05);(3) In general, vegetation NPP was positively correlated with temperature and precipitation, and was more sensitive to precipitation; Therefore, precipitation was the main factor limiting the increase of vegetation NPP in this area.
Based on the Carnegie-Ames-Stanford approach(CASA) model, the temporal and spatial variations of vegetation NPP in northwest China during the period 2000—2013 were analyzed by combining with geo-statistics theory and using trend and correlation analysis. Meanwhile, the relationships between vegetation NPP and climate change were also examined by using the meteorological data. The results showed that:(1) The vegetation NPP in northwest China presented the fluctuating increase trend which reached an extremely significant level(p<0.01);(2) The distribution of vegetation NPP had obvious spatial heterogeneity, which generally presented the decreasing trend from east to west; Except for Xinjiang, the other provinces also showed the low state in the north; the area with increasing vegetation NPP accounted for 85.97% of the total area, and mainly distributed in northern Shaanxi, southern Ningxia, eastern Gansu, eastern and southern parts of Qinghai, and parts of western Xinjiang, while the NPP presented the decreasing trend in west of Xinjiang; The average NPP values of different vegetation types showed significant differences, and followed an order of: grassland [262.16 g C/(m~2·a)]>shrub [66.51 g C/(m~2·a)]>farmland [45.90 g C/(m~2·a)]>forest [14.36 g C/(m~2·a)]; The NPP of grassland, farmland, and shrub all showed the extremely significant increase(p<0.01), but the increase of forests was not obvious(p>0.05);(3) In general, vegetation NPP was positively correlated with temperature and precipitation, and was more sensitive to precipitation; Therefore, precipitation was the main factor limiting the increase of vegetation NPP in this area.
引文
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[3] 刘征,赵旭阳,米林迪.基于3S技术的河北省山区植被净初级生产力估算及空间格局研究[J].水土保持研究,2014,21(4):143-147.
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[5] 张永领,郝成元.基于遥感和CASA模型的西江流域NPP时空分布特征研究[J].水土保持研究,2010,17(5):101-104.
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[8] 周梦甜,李军,朱康文.西北地区NDVI变化与气候因子的响应关系研究[J].水土保持研究,2015,22(3):182-187.
[9] 王钊,李登科.2000—2015年陕西植被净初级生产力时空分布特征及其驱动因素[J].应用生态学报,2018,29(6):1876-1884.
[10] 冯益明,姚爱冬,姜丽娜.CASA模型的改进及在干旱区生态系统NPP估算中的应用[J].干旱区资源与环境,2014,28(8):39-43.
[11] 汪青春,秦宁生,唐红玉,等.青海高原近44年来气候变化的事实及其特征[J].干旱区研究,2007,24(2):234-239.
[12] 王云霓,熊伟,王彦辉,等.宁夏六盘山3种针叶林初级净生产力年际变化及其气象因子响应[J].生态学报,2013,33(13):4002-4010.
[13] 张仁平.新疆地区草地NPP和物候对气候变化的响应研究[D].兰州:兰州大学,2017.
[14] 丁文广,魏银丽,牛贺文.西北干旱区植被恢复的土壤养分效应[J].生态环境学报,2010,19(11):2568-2573.
[15] 穆少杰,周可新,齐杨,等.内蒙古植被降水利用效率的时空格局及其驱动因素[J].植物生态学报,2014,38(1):1-16.
[16] 穆少杰,李建龙,周伟,等.2001—2010年内蒙古植被净初级生产力的时空格局及其与气候的关系[J].生态学报,2013,33(12):3752-3764.
[17] 朱文泉,陈云浩,徐丹,等.陆地植被净初级生产力计算模型研究进展[J].生态学杂志,2005,24(3):296-300.
[18] 周伟,刚成诚,李建龙,等.1982—2010年中国草地覆盖度的时空动态及其对气候变化的响应[J].地理学报,2014,69(1):15-30.
[19] 刘海江,尹思阳,孙聪,等.2000—2010年锡林郭勒草原NPP时空变化及其气候响应[J].草业科学,2015,32(11):1709-1720.
[20] 阿多,赵文吉,宫兆宁,等.1981—2013华北平原气候时空变化及其对植被覆盖度的影响[J].生态学报,2017,37(2):576-592.
[21] 焦伟,陈亚宁,李稚.西北干旱区植被净初级生产力的遥感估算及时空差异原因[J].生态学杂志,2017,36(1):181-189.
[22] 彭珂珊,王继军.中国退耕还林(草)的发展历史阶段与对策探讨[J].水土保持研究,2004,11(1):106-109.
[23] Iersel M W V.Carbon use efficiency depends on growth respiration,maintenance respiration,and relative growth rate:A case study with lettuce[J].Plant Cell & Environment,2010,26(9):1441-1449.
[24] 王耀斌,赵永华,韩磊,等.2000—2015年秦巴山区植被净初级生产力时空变化及其趋动因子[J].应用生态学报,2018,29(7):2373-2381.
[25] 仲晓春,陈雯,刘涛,等.2001—2010年中国植被NPP的时空变化及其与气候的关系[J].中国农业资源与区划,2016,37(9):16-22.
[26] Guo R,Wang X K,Ouyang Z Y,et al.Spatial and temporal relationships between precipitation and ANPP of four types of grasslands in northern China[J].Journal of Environmental Sciences,2006,18(5):1024-1030.
[2] 李登科,王钊.基于MOD17A3的中国陆地植被NPP变化特征分析[J].生态环境学报,2018,27(3):397-405.
[3] 刘征,赵旭阳,米林迪.基于3S技术的河北省山区植被净初级生产力估算及空间格局研究[J].水土保持研究,2014,21(4):143-147.
[4] Alexandrov G A,Oikawa T,Yamagata Y.The scheme for globalization of a process-based model explaining gradations in terrestrial NPP and its application[J].Ecological Modelling,2002,148(3):293-306.
[5] 张永领,郝成元.基于遥感和CASA模型的西江流域NPP时空分布特征研究[J].水土保持研究,2010,17(5):101-104.
[6] Gang C,Zhou W,Wang Z,et al.Comparative assessment of grassland NPP dynamics in response to climate change in china,North America,Europe and Australia from 1981 to 2010[J].Journal of Agronomy & Crop Science,2015,201(1):57-68.
[7] 刘刚,孙睿,肖志强,等.2001—2014年中国植被净初级生产力时空变化及其与气象因素的关系[J].生态学报,2017,37(15):4936-4945.
[8] 周梦甜,李军,朱康文.西北地区NDVI变化与气候因子的响应关系研究[J].水土保持研究,2015,22(3):182-187.
[9] 王钊,李登科.2000—2015年陕西植被净初级生产力时空分布特征及其驱动因素[J].应用生态学报,2018,29(6):1876-1884.
[10] 冯益明,姚爱冬,姜丽娜.CASA模型的改进及在干旱区生态系统NPP估算中的应用[J].干旱区资源与环境,2014,28(8):39-43.
[11] 汪青春,秦宁生,唐红玉,等.青海高原近44年来气候变化的事实及其特征[J].干旱区研究,2007,24(2):234-239.
[12] 王云霓,熊伟,王彦辉,等.宁夏六盘山3种针叶林初级净生产力年际变化及其气象因子响应[J].生态学报,2013,33(13):4002-4010.
[13] 张仁平.新疆地区草地NPP和物候对气候变化的响应研究[D].兰州:兰州大学,2017.
[14] 丁文广,魏银丽,牛贺文.西北干旱区植被恢复的土壤养分效应[J].生态环境学报,2010,19(11):2568-2573.
[15] 穆少杰,周可新,齐杨,等.内蒙古植被降水利用效率的时空格局及其驱动因素[J].植物生态学报,2014,38(1):1-16.
[16] 穆少杰,李建龙,周伟,等.2001—2010年内蒙古植被净初级生产力的时空格局及其与气候的关系[J].生态学报,2013,33(12):3752-3764.
[17] 朱文泉,陈云浩,徐丹,等.陆地植被净初级生产力计算模型研究进展[J].生态学杂志,2005,24(3):296-300.
[18] 周伟,刚成诚,李建龙,等.1982—2010年中国草地覆盖度的时空动态及其对气候变化的响应[J].地理学报,2014,69(1):15-30.
[19] 刘海江,尹思阳,孙聪,等.2000—2010年锡林郭勒草原NPP时空变化及其气候响应[J].草业科学,2015,32(11):1709-1720.
[20] 阿多,赵文吉,宫兆宁,等.1981—2013华北平原气候时空变化及其对植被覆盖度的影响[J].生态学报,2017,37(2):576-592.
[21] 焦伟,陈亚宁,李稚.西北干旱区植被净初级生产力的遥感估算及时空差异原因[J].生态学杂志,2017,36(1):181-189.
[22] 彭珂珊,王继军.中国退耕还林(草)的发展历史阶段与对策探讨[J].水土保持研究,2004,11(1):106-109.
[23] Iersel M W V.Carbon use efficiency depends on growth respiration,maintenance respiration,and relative growth rate:A case study with lettuce[J].Plant Cell & Environment,2010,26(9):1441-1449.
[24] 王耀斌,赵永华,韩磊,等.2000—2015年秦巴山区植被净初级生产力时空变化及其趋动因子[J].应用生态学报,2018,29(7):2373-2381.
[25] 仲晓春,陈雯,刘涛,等.2001—2010年中国植被NPP的时空变化及其与气候的关系[J].中国农业资源与区划,2016,37(9):16-22.
[26] Guo R,Wang X K,Ouyang Z Y,et al.Spatial and temporal relationships between precipitation and ANPP of four types of grasslands in northern China[J].Journal of Environmental Sciences,2006,18(5):1024-1030.
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