基于遥感-过程耦合模型的1988~2004年青海三江源区净初级生产力模拟

doi:10.3773/j.issn.1005-264x.2009.02.003

摘要/Abstract

摘要：

三江源区不仅是地处青藏高原的全球气候变化的敏感区, 也是我国甚至亚洲最重要河流的上游关键源区。作为提供物质基础的植被净初级生产力(Net primary production, NPP), 是评价生态系统状况的重要指标。该文应用已在碳通量观测塔验证, 扩展到区域水平的遥感-过程耦合模型GLOPEM-CEVSA, 以空间插值的气象数据和1 km分辨率的AVHRR遥感反演的FPAR数据为模型主要输入, 模拟并分析了1988~2004年该区NPP时空格局及其控制机制。结果表明, 该区植被平均NPP为143.17 gC·m^-2·a^-1, 呈自东南向西北逐渐降低的空间格局, 其中, 以森林NPP最高(267.90 gC·m^-2·a^-1), 其次为农田(222.94 gC·m^-2·a^-1)、草地(160.90 gC·m^-2·a^-1)和湿地(161.36 gC·m^-2·a^-1), 荒漠最低(36.13 gC·m^-2·a^-1)。其年际变化趋势在空间上呈现出明显的差异, 西部地区NPP表现为增加趋势, 每10 a增加7.8~28.8 gC·m^-2; 而中、东部表现为降低趋势, 每10 a降低13.1~42.8 gC·m^-2。根据显著性检验, NPP呈增加趋势(趋势斜率b>0), 显著性水平高于99%和95%的区域占研究区总面积的13.43%和20.34%, 主要分布在西部地区;NPP呈降低趋势(趋势斜率b<0), 显著性水平高于99%和95%的区域占研究区面积的0.75%和3.77%, 主要分布在中、东部地区, 尤以该区长江和黄河等沿线区分布更为集中, 变化显著性也更高。三江源NPP的年际变化趋势的气候驱动力分析表明, 整个区域水平上该地区植被生产力受气候变化的主导, 西部地区暖湿化趋势, 造成了该地区生产力较为明显的、大范围的增加趋势; 但东、中部地区则主要受人类活动的影响, 特别是长江、黄河等河流沿线, 是人类居住活动密集的地区, 造成这些地区放牧压力较大、草地退化严重, 而该地区暖干化趋势加剧了这一过程。

关键词: 青海, 三江源, 净初级生产力, 遥感-过程模型

Abstract:

Aims The “Three-River Headwaters” Region, as the headwaters of important rivers and an area sensitive to global climate change, has become a recent research focus. Our objective is to model and assess the spatial-temporal pattern of net primary production ( NPP) and its control mechanisms.

Methods We applied the GLOPEM-CEVSA model, which has been validated with carbon flux observation in forest, grassland and cropland. The main inputs are spatially interpolated meteorological data and fraction of photosynthetically active radiation absorbed by vegetation canopy, using 1 km resolution of the Advanced Very High Resolution Radiometer of the National Oceanic and Atmospheric Administration in 1988-2004.

Important findings Modeled NPP ranged from 36.13 gC·m^-2·a^-1 for desert to 267.90 gC·m^-2·a^-1 for forest, and the mean was 143.17 gC·m^-2·a^-1. Spatially, NPP decreased from southeast to northwest, as influenced by geography and climate. Variability of NPP was the largest in desert (41.75%), was similar for cropland (25.93%), grassland (22.31%) and wetland (24.72%) and was the smallest in forest (20.79%). During 1988-2004, NPP increased at the rate of 7.8-28.8 gC·m^-2 per 10 years in the western area, but decreased 13.1-42.8 gC·m^-2 per 10 years in the central and eastern areas. At 99 and 95% significance levels, the area with NPP increasing (regression slope b > 0) was 13.43% and 20.34%, respectively, of the whole area, and mainly distributed in the western region, while the area with NPP decreasing (b < 0) was 0.75% and 3.77%, respectively, of the whole area and distributed in the central and western areas and was more concentrated near the main rivers at higher significance levels. Increases of NPP in the western area may have been affected by increasing temperature and precipitation, while central and eastern areas may have been impacted by human activities, especially along the Yangtze, Yellow and other rivers with intensive human habitation and where the warmer and drier climate has led to more serious grassland degradation. The effects of human activities on NPP were not analyzed because data on human activity were unavailable and spatial interpolation of the impact is difficult.

Key words: “Three-River Headwaters” Region, Qinghai, net primary productivity, GLOPEM-CEVSA

王军邦, 刘纪远, 邵全琴, 刘荣高, 樊江文, 陈卓奇. 基于遥感-过程耦合模型的1988~2004年青海三江源区净初级生产力模拟. 植物生态学报, 2009, 33(2): 254-269. DOI: 10.3773/j.issn.1005-264x.2009.02.003

WANG Jun-Bang, LIU Ji-Yuan, SHAO Quan-Qin, LIU Rong-Gao, FAN Jiang-Wen, CHEN Zhuo-Qi. SPATIAL-TEMPORAL PATTERNS OF NET PRIMARY PRODUCTIVITY FOR 1988-2004 BASED ON GLOPEM-CEVSA MODEL IN THE “THREE-RIVER HEADWATERS” REGION OF QINGHAI PROVINCE, CHINA. Chinese Journal of Plant Ecology, 2009, 33(2): 254-269. DOI: 10.3773/j.issn.1005-264x.2009.02.003

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图/表 9

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变量 Variable	描述 Description	单位 Unit	缺省值 Default	常绿针叶林ENF	落叶针叶林DNF	混交林MF	常绿阔叶林EBF	落叶阔叶林DBF	草地Grass	灌丛Shrub	荒漠Desert	农田Crop
b19	叶维持性呼吸系数 Leaf maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.000 8	0.002	0.002	0.006	0.009	0.009	0.002	0.002	0.002	0.002
b20	枝干维持性呼吸系数 Stem maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.001 0	0.001	0.001	0.003	0.004	0.004	0.001	0.001	0.001	0.001
b21	粗根维持性呼吸系数 Coarse root maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.001 5	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001
b22	细根维持性呼吸系数 Fine root maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.003 0	0.003	0.003	0.003	0.003	0.003	0.003	0.003	0.003	0.003
b29	叶生物量分配系数 Leaf carbon allocation fraction	-	0.3	0.01	0.02	0.01	0.01	0.01	0.2	0.6	0.2	0.2
b30	枝干生物量分配系数 Stem carbon allocation fraction	-	0.2	0.90	0.90	0.93	0.90	0.93	0.2	0.2	0.2	0.2
b31	根生物量分配系数 Root carbon allocation fraction	-	0.5	0.09	0.08	0.06	0.09	0.06	0.6	0.2	0.6	0.6
b32	叶周转时间 Leaf litter C turnover fraction	a	1	2	2	1	2	1	1	1	1	1
b33	枝干周转时间 Stem litter C turnover fraction	a	1	90	50	90	90	100	1	10	1	1
b34	根周转时间 Root litter C turnover fraction	a	1	45	30	50	50	50	1	5	1	1

变量 Variable	描述 Description	单位 Unit	缺省值 Default	常绿针叶林ENF	落叶针叶林DNF	混交林MF	常绿阔叶林EBF	落叶阔叶林DBF	草地Grass	灌丛Shrub	荒漠Desert	农田Crop
b19	叶维持性呼吸系数 Leaf maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.000 8	0.002	0.002	0.006	0.009	0.009	0.002	0.002	0.002	0.002
b20	枝干维持性呼吸系数 Stem maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.001 0	0.001	0.001	0.003	0.004	0.004	0.001	0.001	0.001	0.001
b21	粗根维持性呼吸系数 Coarse root maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.001 5	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001
b22	细根维持性呼吸系数 Fine root maintenance respiration co.	kgC^-1·d^-1·kg^-1	0.003 0	0.003	0.003	0.003	0.003	0.003	0.003	0.003	0.003	0.003
b29	叶生物量分配系数 Leaf carbon allocation fraction	-	0.3	0.01	0.02	0.01	0.01	0.01	0.2	0.6	0.2	0.2
b30	枝干生物量分配系数 Stem carbon allocation fraction	-	0.2	0.90	0.90	0.93	0.90	0.93	0.2	0.2	0.2	0.2
b31	根生物量分配系数 Root carbon allocation fraction	-	0.5	0.09	0.08	0.06	0.09	0.06	0.6	0.2	0.6	0.6
b32	叶周转时间 Leaf litter C turnover fraction	a	1	2	2	1	2	1	1	1	1	1
b33	枝干周转时间 Stem litter C turnover fraction	a	1	90	50	90	90	100	1	10	1	1
b34	根周转时间 Root litter C turnover fraction	a	1	45	30	50	50	50	1	5	1	1

生态系统 Ecosystem	平均值 Mean	标准偏差 SD	变异系数 CV (%)	朴世龙和方精云(2002) Piao & Fang ( 2002)
农田 Crop	222.94	68.25	30.61	175
森林 Forest	267.90	58.81	21.95	297
草地 Grass	160.90	93.01	57.80	121
荒漠 Desert	36.13	31.16	86.26	42
湿地 Wet land	161.36	70.18	43.49
其它 Other	106.10	78.13	73.64
全区 Whole area	143.17	98.21	68.60

生态系统 Ecosystem	平均值 Mean	标准偏差 SD	变异系数 CV (%)	朴世龙和方精云(2002) Piao & Fang ( 2002)
农田 Crop	222.94	68.25	30.61	175
森林 Forest	267.90	58.81	21.95	297
草地 Grass	160.90	93.01	57.80	121
荒漠 Desert	36.13	31.16	86.26	42
湿地 Wet land	161.36	70.18	43.49
其它 Other	106.10	78.13	73.64
全区 Whole area	143.17	98.21	68.60

草地类型 Grass type	模拟产草量 Modeled	80年代草调产草量 Surveyed in the 1980s	2004年监测产草量 Surveyed in 2004	2005年监测产草量 Surveyed in 2005
草地 Grass	461.54	666.50	537.50	668.50
荒漠 Desert	187.00	162.00
湿地 Wet land	859.75	961.50