中国南方红壤丘陵区植被净初级生产力空间分布及其与气候因子的关系——以江西省泰和县为例

doi:10.11821/dlyj201507003

地理研究 ›› 2015, Vol. 34 ›› Issue (7): 1222-1234.doi: 10.11821/dlyj201507003

中国南方红壤丘陵区植被净初级生产力空间分布及其与气候因子的关系——以江西省泰和县为例

戴尔阜^1,²(), 李双元³, 吴卓^1,^2,⁴, 闫浩文³, 赵东升^1,²

1. 中国科学院地理科学与资源研究所,北京 100101
2. 中国科学院陆地表层格局与模拟重点实验室,北京 100101
3. 兰州交通大学测绘与地理信息学院,兰州 730070
4. 中国科学院大学,北京 100049

收稿日期:2015-01-21 修回日期:2015-05-05 出版日期:2015-08-19 发布日期:2015-08-08
作者简介:
作者简介：戴尔阜（1972- ）,男,甘肃静宁人,博士,研究员,博士生导师,主要研究方向为自然地理综合研究、气候变化及其区域响应、土地利用变化模拟。E-mail: daief@igsnrr.ac.cn
基金资助:
国家重点基础研究发展计划（973计划）项目（2015CB452702,2012CB416906）;国家自然科学基金项目（41371196）;国家科技支撑计划项目（2013BAC03B04）

Spatial pattern of net primary productivity and its relationship with climatic factors in Hilly Red Soil Region of southern China: A case study in Taihe county, Jiangxi province

Erfu DAI^1,²(), Shuangyuan LI³, Zhuo WU^1,^2,⁴, Haowen YAN³, Dongsheng ZHAO^1,²

1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2. Key Laboratory of Land Surface Pattern and Simulation, CAS, Beijing 100101, China
3. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
4. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2015-01-21 Revised:2015-05-05 Online:2015-08-19 Published:2015-08-08

摘要/Abstract

摘要：

植被净初级生产力（NPP）对气候变化的响应研究是全球变化研究的核心内容之一。在区域尺度上研究NPP年际间的空间变化规律,探究气候因子与植被生长的关系,是应对气候变化区域响应、探讨区域生态过程的科学基础。基于SPOT VEGETATION NDVI 植被指数数据、气候和植被分类数据,利用光能利用率模型（CASA）估算了中国南方红壤丘陵区泰和县1998-2012年植被NPP,分析了NPP时空分布特征及其与气候因子的相关性。结果表明：① 1998-2012年泰和县植被年均NPP为762 g C/m²·a,不同植被类型差异明显,空间上表现出东西高、中间低的分布特征;② 1998-2012年泰和县植被NPP总体呈增长趋势,年际波动较大,平均值为2.21×10⁶ g C/a;③ 研究区NPP与年降水量呈不显著正相关关系,与年均气温呈显著负相关关系,表明温度是影响该地区植被NPP的主要气候因子。

关键词: CASA模型, 植被, 净初级生产力, 气候因子, 泰和县

Abstract:

Net primary productivity (NPP) and its responses to climate change stand one of the focuses of global change research. At the regional scale, it is significant to investigate the annual spatial variation and the impact of climatic factors on vegetation. Based on SPOT VEGETATION NDVI data, vegetation classification data and meteorological data, the spatio-temporal pattern on the NPP of Taihe county during 1988-2012 was simulated by CASA model. Then, the relationship between NPP and climatic factors was investigated deeply. The results showed that average annual NPP from 1988 to 2012 was 762 gC/m²·a in the study region. Spatial dimension is characterized by "high in the middle, but low in the east and west". There was a rising trend in the vegetation NPP during 1988-2012. The annual value fluctuated greatly. Mean NPP in the study area is 2.21×10⁶ g C/a. It can be found that vegetation NPP showed a weak positive correlation to annual precipitation, while it showed a significant negative correlation to annual average temperature. So, it can be concluded that temperature is the dominant climatic factor affecting vegetation NPP in the study region.

Key words: CASA model, vegetation, net primary productivity, climatic factors, Taihe county

戴尔阜, 李双元, 吴卓, 闫浩文, 赵东升. 中国南方红壤丘陵区植被净初级生产力空间分布及其与气候因子的关系——以江西省泰和县为例[J]. 地理研究, 2015, 34(7): 1222-1234.

Erfu DAI, Shuangyuan LI, Zhuo WU, Haowen YAN, Dongsheng ZHAO. Spatial pattern of net primary productivity and its relationship with climatic factors in Hilly Red Soil Region of southern China: A case study in Taihe county, Jiangxi province[J]. GEOGRAPHICAL RESEARCH, 2015, 34(7): 1222-1234.

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	常绿阔叶林	落叶阔叶林	针叶林	农田
丁庆福等^[22]	846.09	–	1091.38	767.2
孙睿等^[34]	972	460	529	–
刘明亮^[37]	945	928	587	752
陈雅敏等^[38]	484~1450	282~928	347~1180	212~897
陶波等^[39]	873	624	486	606
本研究	985	730	729	703

	R_p	R_t
人工湿地松林	-0.027	-0.3486
天然马尾松林	-0.0156	-0.3305
杉木林	0.0436	-0.2945
天然针叶混交林	-0.0414	-0.4211
人工落叶阔叶林	0.0239	-0.3113
天然落叶阔叶林	-0.0495	-0.2812
人工常绿阔叶林	0.1536	-0.4587
天然常绿阔叶林	0.0167	-0.2696
天然阔叶混交林	-0.0584	-0.1144
人工针阔混交林	-0.1477	-0.7316
天然针阔混交林	0.0167	-0.1944
天然竹林	0.0021	-0.2815
经济林	-0.0621	-0.1838
其他土地	-0.1123	-0.2883
农地	-0.0141	-0.3546

中国南方红壤丘陵区植被净初级生产力空间分布及其与气候因子的关系——以江西省泰和县为例

Spatial pattern of net primary productivity and its relationship with climatic factors in Hilly Red Soil Region of southern China: A case study in Taihe county, Jiangxi province

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