基于Biome-BGC模型的青藏高原五道梁地区NPP变化及情景模拟

doi:10.13249/j.cnki.sgs.2019.08.015

摘要/Abstract

摘要：

以“气候变暖”为标志的全球气候变化对青藏高原生态系统产生强烈影响,利用参数本地化的生物地球化学模型（Biome-BGC）对五道梁地区草地生态系统进行模拟,研究了该区域1961~2015年净初级生产力（net primary productivity,NPP）的变化,并进行了情景模拟。结果表明:五道梁地区近55 a草地年均NPP为67.94 g/(m ²·a),呈显著上升趋势,主要是由生长季延长以及9月份生物量快速增长造成。在该地区,温度是草地NPP的主导因子,降水变化在40%以内对生产力影响不显著;温度和降水交互影响NPP,对单一影响有放大作用,暖湿条件下NPP对气候变化响应更加明显。

关键词: 草地生态系统, 生物地球化学模型, 气候变暖, 参数本地化

Abstract:

The Tibetan Plateau is the largest plateau in China and the highest altitude in the world. Due to its unique natural conditions, this area not only directly affects the climate change in East Asia, but also has a great impact on the northern hemisphere. However, the Wudaoliang site on this Plateau has not been studied independently. The purpose of this study is to use Biome-BGC model to simulate NPP changes in Wudaoliang from 1961 to 2015. In addition, scenario simulation is also conducted to explore the response of NPP to climate change under different scenarios. Biome-BGC model has strong rationality and systematicness. It is a biogeochemical model in daily for studying the physiological processes and interactions of vegetation and soil energy, water, carbon and nitrogen in regional and global scale ecosystems. The input data of the model are meteorological data, initialized file data, atmospheric CO₂ concentration data for many years, vegetation parameter data. The model has been widely applied. In order to improve the accuracy, some parameters, such as leaf C/N ratio and soil particle size, were also measured. In August 2017, the measured samples of grassland vegetation in the flourishing season were validated by directly converting the measured samples into biomass, and compared with previous studies. The verification results showed that the simulated NPP is acceptable and applicable to this area. NPP of Wudaoliang alpine grassland ranged from 57.6 to 79.8 g/(m ²·a), with an average of 67.94 g/(m ²·a), showing an overall growth trend (P<0.01), with an average annual growth rate of 0.18%/a. According to the criterion of Odum ecosystem productivity, the study area is the lowest productivity ecosystem. NPP increased by 5.9%, 11.77%, 17.57% and 23.32% respectively along with the temperature increased by 0.5℃, 1℃, 1.5℃ and 2℃ than the normal scenario. The greater the temperature rise, the more obvious the increase of NPP. In the scenarios of precipitation increasing and decreasing by 20% and 40%, the average NPP changed by 1.13%, 2.14%, 1.19% and -2.45% than normal scenarios. Increasing precipitation could promote the growth of NPP, but decreasing precipitation showed inhibition effect. The combined scenarios of T₂W₂₀₊, T₂W₄₀₊, T₂W_20- and T₂W_40- increased by 24.54%, 25.68%, 21.79% and 19.94% respectively than normal scenarios. Under the combined scenarios, the NPP increase is higher than that of a single increase in moderate precipitation scenarios. Biome-BGC model with localized parameters can better simulate the net primary productivity of grassland in Wudaoliang area of Tibetan Plateau. In the past 55 years, the net primary productivity of Wudaoliang grassland showed a significant upward trend, which was mainly caused by the extension of growing season and the rapid growth of biomass in September. In this area, temperature increase is beneficial to productivity increase. Precipitation increase is beneficial to productivity acceleration. Precipitation decrease inhibits NPP accumulation. Precipitation change within 40% has no significant effect on productivity. Temperature and precipitation interact with NPP and have an amplifying effect on a single effect.

Key words: grassland ecosystem, Biogeochemical model, climate warming, localized parameters

中图分类号:

Q948

李传华,韩海燕,范也平,曹红娟,王玉涛,孙皓. 基于Biome-BGC模型的青藏高原五道梁地区NPP变化及情景模拟[J]. 地理科学, 2019, 39(8): 1330-1339.

Li Chuanhua,Han Haiyan,Fan Yeping,Cao Hongjuan,Wang Yutao,Sun Hao. NPP Change and Scenario Simulation in Wudaoliang Area of the Tibetan Plateau Based on Biome-BGC Model[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(8): 1330-1339.

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参数	值	单位	来源	参数	值	单位	来源
土壤深度	0.75	m	实测	站点高程	4605.3	m	实测
土壤沙土含量	62	%	实测	站点纬度	92.922	^°	实测
土壤粉土含量	36	%	实测	坡度	13.202	^°	实测
土壤黏土含量	2	%	实测	坡向	340.27	-	实测

参数	值	单位	参数	值	单位
开始新生长的天数	120^[18]	d	叶凋落物中易分解物质比例	0.39	无
落叶分解的天数	290^[9]	d	叶凋落物中纤维素比例	0.44	无
转移生长占生长季的比例	1	无	叶凋落物中木质素比例	0.17	无
凋落过程占生长季的比例	1	无	细根中易分解物质比例	0.3	无
年火灾死亡率	0.001^[17]	a^-¹	细根中纤维素比例	0.45	无
新细根与新叶碳分配比例	1.18^**	无	细根中木质素比例	0.25	无
新根与新茎碳分配比例	0	无	死立木中纤维素比例	0.76	无
生长与贮存碳分配比例	0.5	无	死立木木质素比例	0.24	无
叶片碳氮比	12.47^**	无	冠层截水系数	0.021^[18]	LAI/d
凋落后碳氮比	45^**	无	冠层消光系数	0.48	无
细根碳氮比	37.29^**	无	阴生叶与阴生叶比叶面积比例	2	无
活立木碳氮比	0	无	Rubisco酶活叶氮量	0.21	无
平均比叶面积	23.85^**	m²/kg	气孔开始缩小时饱和水汽压差	930	Pa
叶表面积与投影叶面积比例	2^[18]	无	气孔完全闭合时饱和水汽压差	4100	Pa

情景	情景变化情况	情景	情景变化情况	情景	情景变化情况
T₀W₀	正常条件	T_0.5W₀	增温0.5℃降水不变	T₂W₂₀₊	增温2.0℃降水增加20%
T₀W₂₀_-	温度不变降水减少20%	T₁W₀	增温4.0℃降水不变	T₂W_20-	增温2.0℃降水减少20%
T₀W₂₀₊	温度不变降水增加20%	T_1.5W₀	增温1.5℃降水不变	T₂W₄₀₊	增温2.0℃降水增加40%
T₀W₄₀_-	温度不变降水减少40%	T₂W₀	增温2.0℃降水不变	T₂W_40-	增温2.0℃降水减少40%
T₀W₄₀₊	温度不变降水增加40%	--	--	--	--

研究时段	方法及模型	模拟均值 g/(m²·a)	参考文献
1982~1999年	CASA	80	朴世龙等^[23]
2000~2002年	TEM	63.95	周才平等^[20]
1981~2004年	CASA	48.1	高清竹等^[21]
1981~2000年	AVIM	50	黄玫等^[22]
2005~2008年	GLO-PEM	70	陈卓奇等^[6]
1982~2009年	CASA	55.9	Zhang Y等^[24]
2013~2015年	BIOME-BGC	74.37	本研究

	5月	6月	7月	8月	9月	10月
NPP平均值[g/(m²·a)]	5.25	12.91	16.42	16.59	12.71	4.06
月均增长率（%/a）	0.22	0.07	0.03	0.06	0.64	0.52