2000-2015年黄河流域植被净初级生产力时空变化特征及其驱动因子
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摘要
黄河流域区域性差异显著,生态系统环境脆弱敏感,研究植被NPP对其生态环境生产能力的了解具有重要意义。基于MOD17A3 NPP数据、气象数据和土地利用/覆盖类型数据,采用偏差分析、趋势分析、相关性分析及马尔科夫转移模型对黄河流域2000—2015年植被NPP的时空格局、变化趋势及驱动因子进行了研究。结果表明:(1) 2000—2015年黄河流域植被年NPP均值为228.2 g C/(m~2·a),变化范围为179.6～258.1 g C/(m~2·a),整体上呈现微小波动增加趋势,植被NPP偏差值呈现先减少后增加的趋势;上中下游植被NPP年均值呈明显的梯度分布,即上游<中游<下游,说明中上游区域生态环境相对脆弱。(2)黄河流域植被NPP具有较强的空间分异性,呈南向北带状递减分布;上中下游植被NPP总量差异显著,其中中上游植被NPP总量约占整个流域的96%,可见中上游对整个黄河流域生态环境的影响举足轻重,故加强对中上游区域生态环境建设与保护至关重要;流域大部分地区植被NPP以增加为主要趋势。(3)流域植被NPP受气候因素中降雨影响较大,以气候因素强驱动的区域主要分布在川西高原、鄂尔多斯高原及华北平原等地区。农用地转建设用地及草地转荒漠是黄河流域植被NPP损失的主要方式,可见城市加速扩张以及过度开垦、放牧等人类活动是植被NPP损失的主要驱动力,近几年林地、草地面积有所增加,植被NPP整体上损失程度有所减小,可见实施退耕还林还草政策已见成效。
The regional differences are significant and the ecological environment is fragile and sensitive in Yellow River Basin. It is of great significance to study the vegetation net primary productivity(NPP) and to understand the production capacity of ecological environment. We used MOD17 A3 NPP data, meteorological data, and land use/cover type data to investigate the spatiotemporal pattern, change trends, and driving factors of vegetation NPP in Yellow River Basin from 2000 to 2015. The data were analyzed using bias analysis, trend analysis, correlation analysis, and Markov transition model. The results showed that:(1) from 2000 to 2015, the average annual vegetation NPP for Yellow River Basin was 228.2 g C/(m~2·a), ranging from 179.6 to 258.1 g C/(m~2·a), showing the slightly volatile increase; the bias value of vegetation NPP showed the decreasing trend first and then the increasing trend. The average annual NPP decreased in the order: downstream>midstream>upstream, indicating that the ecological environment in the upper and middle reaches was relatively fragile;(2) vegetation NPP had a strong spatial variability in Yellow River Basin, showing a decreasing distribution from south to north; the total amounts NPP in different reaches varied significantly, decreasing in the order: midstream>upstream>downstream, so, it was crucial to strengthen the construction and protection of the ecological environment in the upper and middle reaches: vegetation NPP increased in most areas of the basin;(3) vegetation NPP was most affected by rainfall among the climatic factors. The regions strongly driven by climate factors mainly distributed in the western Sichuan Plateau, the Ordos Plateau, and the North China Plain; conversion of croplands to construction land and conversion of grasslands to desert were the main modes of losses of vegetation NPP in Yellow River Basin; it can be seen that the accelerated expansion of cities and human activities such as excessive reclamation and grazing were the main drivers of vegetation NPP losses. In the recent years, the areas of forests and grasslands have increased, and the overall NPP losses have been reduced. It can be seen that the implementation of Grain for Green Project has obtained initial success.
The regional differences are significant and the ecological environment is fragile and sensitive in Yellow River Basin. It is of great significance to study the vegetation net primary productivity(NPP) and to understand the production capacity of ecological environment. We used MOD17 A3 NPP data, meteorological data, and land use/cover type data to investigate the spatiotemporal pattern, change trends, and driving factors of vegetation NPP in Yellow River Basin from 2000 to 2015. The data were analyzed using bias analysis, trend analysis, correlation analysis, and Markov transition model. The results showed that:(1) from 2000 to 2015, the average annual vegetation NPP for Yellow River Basin was 228.2 g C/(m~2·a), ranging from 179.6 to 258.1 g C/(m~2·a), showing the slightly volatile increase; the bias value of vegetation NPP showed the decreasing trend first and then the increasing trend. The average annual NPP decreased in the order: downstream>midstream>upstream, indicating that the ecological environment in the upper and middle reaches was relatively fragile;(2) vegetation NPP had a strong spatial variability in Yellow River Basin, showing a decreasing distribution from south to north; the total amounts NPP in different reaches varied significantly, decreasing in the order: midstream>upstream>downstream, so, it was crucial to strengthen the construction and protection of the ecological environment in the upper and middle reaches: vegetation NPP increased in most areas of the basin;(3) vegetation NPP was most affected by rainfall among the climatic factors. The regions strongly driven by climate factors mainly distributed in the western Sichuan Plateau, the Ordos Plateau, and the North China Plain; conversion of croplands to construction land and conversion of grasslands to desert were the main modes of losses of vegetation NPP in Yellow River Basin; it can be seen that the accelerated expansion of cities and human activities such as excessive reclamation and grazing were the main drivers of vegetation NPP losses. In the recent years, the areas of forests and grasslands have increased, and the overall NPP losses have been reduced. It can be seen that the implementation of Grain for Green Project has obtained initial success.
引文
[1]王强,张廷斌,易桂花,等.横断山区2004—2014年植被NPP时空变化及其驱动因子[J].生态学报,2017,37(9):3084-3095.
[2]王新闯,王世东,张合兵.基于MOD17A3的河南省NPP时空格局[J].生态学杂志,2013,32(10):2797-2805.
[3]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.
[4]姜春,吴志峰,程炯,等.广东省土地覆盖变化对植被净初级生产力的影响分析[J].自然资源学报,2016,31(6):961-972.
[5]Zhu W, Pan Y, Liu X, et al. Spatio-temporal distribution of net primary productivity along the northeast China transect and its response to climatic change[J]. Journal of Forestry Research, 2006, 17(2): 93-98.
[6]郭连发,来全,伊博力,等.2000—2014年呼伦贝尔沙地河流湿地植被NPP时空变化及驱动力分析[J].水土保持研究,2017,24(6):267-272.
[7]姚玉璧,杨金虎,王润元,等.50年长江源区域植被净初级生产力及其影响因素变化特征[J].生态环境学报,2010,19(11):2521-2528.
[8]崔林丽,杜华强,史军,等.中国东南部植被NPP的时空格局变化及其与气候的关系研究[J].地理科学,2016,36(5):787-793.
[9]陈探,刘淼,胡远满,等.沈阳经济区土地利用和净初级生产力变化[J].生态学报,2015,35(24):8231-8240.
[10]张峰,周广胜,王玉辉.基于CASA模型的内蒙古典型草原植被净初级生产力动态模拟[J].植物生态学报,2008,32(4):786-797.
[11]Piao S L, Fang J Y, Chen A P. Seasonal dynamics of terrestrial net primary production in response to climate changes in China [J]. Acta Botanica Sinica, 2003,45(3):269-275.
[12]宋艺,李小军,江涛.2008—2014年植被覆盖变化对黑河流域净初级生产力的影响研究[J].水土保持研究,2017,24(4):204-209,218.
[13]赵国帅,王军邦,范文义,等.2000—2008年中国东北地区植被净初级生产力的模拟及季节变化[J].应用生态学报,2011,22(3):621-630.
[14]王芳,汪左,张运.2000—2015年安徽省植被净初级生产力时空分布特征及其驱动因素[J].生态学报,2018,38(8):1-13.
[15]陈强,陈云浩,王萌杰,等.2001—2010年黄河流域生态系统植被净第一性生产力变化及气候因素驱动分析[J].应用生态学报,2014,25(10):2811-2818.
[16]毛德华,王宗明,韩佶兴,等.1982—2010年中国东北地区植被NPP时空格局及驱动因子分析[J].地理科学,2012,32(9):1106-1111.
[17]张强,高歌.我国近50年旱涝灾害时空变化及监测预警服务[J].科技导报,2004(7):21-24.
[18]杨荆安,闵爱荣,廖移山.2011年4—10月我国主要暴雨天气过程简述[J].暴雨灾害,2012,31(1):87-95.
[2]王新闯,王世东,张合兵.基于MOD17A3的河南省NPP时空格局[J].生态学杂志,2013,32(10):2797-2805.
[3]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.
[4]姜春,吴志峰,程炯,等.广东省土地覆盖变化对植被净初级生产力的影响分析[J].自然资源学报,2016,31(6):961-972.
[5]Zhu W, Pan Y, Liu X, et al. Spatio-temporal distribution of net primary productivity along the northeast China transect and its response to climatic change[J]. Journal of Forestry Research, 2006, 17(2): 93-98.
[6]郭连发,来全,伊博力,等.2000—2014年呼伦贝尔沙地河流湿地植被NPP时空变化及驱动力分析[J].水土保持研究,2017,24(6):267-272.
[7]姚玉璧,杨金虎,王润元,等.50年长江源区域植被净初级生产力及其影响因素变化特征[J].生态环境学报,2010,19(11):2521-2528.
[8]崔林丽,杜华强,史军,等.中国东南部植被NPP的时空格局变化及其与气候的关系研究[J].地理科学,2016,36(5):787-793.
[9]陈探,刘淼,胡远满,等.沈阳经济区土地利用和净初级生产力变化[J].生态学报,2015,35(24):8231-8240.
[10]张峰,周广胜,王玉辉.基于CASA模型的内蒙古典型草原植被净初级生产力动态模拟[J].植物生态学报,2008,32(4):786-797.
[11]Piao S L, Fang J Y, Chen A P. Seasonal dynamics of terrestrial net primary production in response to climate changes in China [J]. Acta Botanica Sinica, 2003,45(3):269-275.
[12]宋艺,李小军,江涛.2008—2014年植被覆盖变化对黑河流域净初级生产力的影响研究[J].水土保持研究,2017,24(4):204-209,218.
[13]赵国帅,王军邦,范文义,等.2000—2008年中国东北地区植被净初级生产力的模拟及季节变化[J].应用生态学报,2011,22(3):621-630.
[14]王芳,汪左,张运.2000—2015年安徽省植被净初级生产力时空分布特征及其驱动因素[J].生态学报,2018,38(8):1-13.
[15]陈强,陈云浩,王萌杰,等.2001—2010年黄河流域生态系统植被净第一性生产力变化及气候因素驱动分析[J].应用生态学报,2014,25(10):2811-2818.
[16]毛德华,王宗明,韩佶兴,等.1982—2010年中国东北地区植被NPP时空格局及驱动因子分析[J].地理科学,2012,32(9):1106-1111.
[17]张强,高歌.我国近50年旱涝灾害时空变化及监测预警服务[J].科技导报,2004(7):21-24.
[18]杨荆安,闵爱荣,廖移山.2011年4—10月我国主要暴雨天气过程简述[J].暴雨灾害,2012,31(1):87-95.
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