不同草地类型净初级生产力(NPP)模拟及其敏感性分析

doi:10.12118/j.issn.1000–6060.2021.02.08

干旱区地理 ›› 2021, Vol. 44 ›› Issue (2): 369-378.doi: 10.12118/j.issn.1000–6060.2021.02.08

不同草地类型净初级生产力(NPP)模拟及其敏感性分析

张美玲¹(),陈全功²,蒋文兰^3,⁴

1.甘肃农业大学理学院/数量生物学研究中心,甘肃兰州 730070
2.兰州大学草地农业科技学院,甘肃兰州 730020
3.甘肃农业大学草业学院,甘肃兰州 730070
4.中国科学院寒区旱区环境与工程研究所,甘肃兰州 730000

收稿日期:2019-04-06 修回日期:2020-06-11 出版日期:2021-03-25 发布日期:2021-04-14
作者简介:张美玲（1978-）,女,博士,副教授,研究方向为草地生态学和数学模型. E-mail:zhangml@gsau.edu.cn
基金资助:
甘肃省高等学校创新能力提升项目(2019A-051);甘肃农业大学青年导师扶持基金(GAU-QDFC-2019-03);甘肃省自然科学基金项目(1606RJZA077);甘肃省自然科学基金项目(1308RJZA262);国家自然科学基金项目资助(30960264);国家自然科学基金项目资助(31160475)

Simulation and sensitivity analysis of net primary productivity(NPP) of different grassland types

ZHANG Meiling¹(),CHEN Quangong²,JIANG Wenlan^3,⁴

1. Center for Quantitative Biology, College of Science, Gansu Agricultural University, Lanzhou 730070, Gansu, China
2. College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, Gansu, China
3. College of Prataculture, Gansu Agricultural University, Lanzhou 730070, Gansu, China
4. Cold and Arid Regions Environments and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, Gansu, China

Received:2019-04-06 Revised:2020-06-11 Online:2021-03-25 Published:2021-04-14

摘要/Abstract

摘要：

气候变化问题作为人类社会可持续发展面临的重大挑战,受到国际社会越来越强烈的关注。全球气候变化深刻影响着草地生态系统,定量评估区域和不同类型草地生态系统的生产力,研究其对气候变化的敏感性可以为草地生态系统适应未来气候变化提供基础数据和理论依据。草原综合顺序分类系统（CSCS）将天然草原分为42类（其中中国包含41类）,并将其聚合为10个类组。研究利用改进Carnegie-Ames-Stanford Approach （CASA）模型模拟分析中国天然草地2004—2008年的净初级生产力（NPP）并进行系统聚类,分析了草地NPP与影响因子的相关性和敏感程度。结果表明：2004—2008年中国10个草地类组年均NPP均呈现增长趋势,其中亚热带森林草地增长最快,增长率达38.2%。温带湿润草地增长最慢,增长率为14.3%。通过聚类分析将中国41类草原的年均NPP分为3类：第1类NPP值较小,其湿润度级较低,而热量级较高;第2类NPP值较大,其热量级和湿润度级均较高,水热比适宜植被的生长;其余为第3类,其NPP值介于上述两者之间。可见,不同草地类型NPP分布规律与CSCS划分草地类型的湿润度级和热量级密切相关。草地年均NPP与>0 ℃年积温（Σθ）、降水量、湿润度（K）和NDVI的相关性强,与太阳辐射的相关性弱。草地类组NPP平均值对NDVI最敏感,其次为Σθ、K和降水量,敏感性最弱的为太阳辐射。草地NPP对CSCS量化分类的标准Σθ和K较为敏感,改进CASA模型在一定程度上实现了CSCS与草地生产力的耦合。

关键词: 净初级生产力（NPP）, 改进CASA模型, 草地类型, 聚类分析, 敏感性分析

Abstract:

As a major challenge to the sustainable development of human society, climate change has attracted increasing attention from the international community. Global climate change significantly affects grassland ecosystems. Quantitative assessment of regional and grassland ecosystem productivity and its sensitivity to climate change could provide basic data on and a theoretical basis for grassland ecosystems adapting to future climate change. The grassland integrated comprehensive sequential classification system (CSCS) divides the natural grassland into 42 classes and aggregates them into 10 super-classes. Using the improved Carnegie-Ames-Stanford Approach (CASA) model, we simulated the net primary productivity (NPP) of natural grasslands in China from 2004 to 2008. A system clustering analysis was also conducted based on the annual average NPP of grassland classes to analyze NPP correlation and sensitivity and its influencing factors. The results show that the NPP showed an increase from 2004 to 2008 for all grassland super-classes. The subtropical forest rapidly increased by 38.2%. The temperate humid grassland slowly increased by 14.3%. The 41 grassland classes of China were clustered into three groups. The NPP of group 1 was low for its low wetness level and high heat level. Group 2 had high NPP for its high wetness and heat level and a suitable moisture and temperature ratio. Others were in group 3. The results indicate that the grassland NPP distribution pattern is related to the wetness and heat level in CSCS. There exists a significant correlation between the annual NPP and annual accumulated temperature greater than zero (Σθ), annual precipitation, wetness (K), and normalized difference vegetation index (NDVI). The correlation between annual NPP and solar radiation was the weakest. NDVI was the most sensitive variable to grassland NPP in China, simulated by the improved CASA model in this study, followed by Σθ, K-values, precipitation, and solar radiation. K-values and Σθ were used for quantitative classification in CSCS, and these two parameters were sensitive to NPP. This study completed the coupling of CSCS and grassland NPP to a certain extent.

Key words: net primary productivity (NPP), improved CASA model, grassland types, clustering analysis, sensitivity analysis

张美玲,陈全功,蒋文兰. 不同草地类型净初级生产力(NPP)模拟及其敏感性分析[J]. 干旱区地理, 2021, 44(2): 369-378.

ZHANG Meiling,CHEN Quangong,JIANG Wenlan. Simulation and sensitivity analysis of net primary productivity(NPP) of different grassland types[J]. Arid Land Geography, 2021, 44(2): 369-378.

图/表 9

表1

CSCS草地类型和类组[8,9]"

类组号	草地类组	草地类型
1	冻原高山草地	寒冷极干寒带荒漠-高山荒漠类（IA1）,寒冷干旱寒带半荒漠-高山半荒漠类（IB8）,寒冷微干干燥冻原-高山草原类（IC15）,寒冷微润少雨冻原-高山草原草甸类（ID22）,寒冷湿润冻原-高山草甸类（IE29）,寒冷潮湿多雨冻原-高山草甸类（IF36）
2	冷荒漠草地	寒温极干山地荒漠类（IIA2）,微温极干温性荒漠类（IIIA3）,温暖极干暖温带荒漠类（IVA4）
3	热荒漠带草地	暖热极干亚热带荒漠类（VA5）,亚热极干亚热带荒漠类（VIA6）,炎热极干热带荒漠类（VIIA7）
4	半荒漠草地	寒温干旱山地半荒漠类（IIB9）,微温干旱湿带半荒漠类（IIIB10）,暖温干旱暖温带半荒漠类（IVB11）,暖热干旱亚热带半荒漠类（VB12）
5	斯太普草地	寒温微干山地草原类（IIC16）,微温微干温带典型草原类（IIIC17）,暖温微干暖温带典型草原类（IVC18）,暖热微干亚热带禾草-灌木草原类（VC19）
6	萨王纳草地	亚热干旱亚热带荒漠灌丛类（VIB13）,炎热干旱热带荒漠灌丛类（VIIB14）,亚热微干亚热带禾草-灌木草原类（VIC20）,炎热微干稀树草原类（VIIC21）,炎热微润干旱森林类（VIID28）
7	温带湿润草地	寒温微润山地草甸草原类（IID23）,微温微润草甸草原类（IIID24）,寒温湿润山地草甸类（IIE30）,微温湿润森林草原-落叶阔叶林类（IIIE31）
8	温带森林草地	暖温微润森林草原类（IVD25）,暖温湿润落叶阔叶林类（IVE32）,寒温潮湿寒温性针叶林类（IIF37）,微温潮湿针叶阔叶混交林类（IIIF38）,暖温潮湿落叶阔叶林类（IVF39）
9	亚热带森林草地	暖热微润落叶阔叶林类（VD26）,亚热微润硬叶类和灌丛类（VID27）,暖热湿润常绿-落叶阔叶林类（VE33）,亚热湿润常绿阔叶林类（VIE34）,暖热潮湿落叶-常绿阔叶林类（VF40）,亚热潮湿常绿阔叶林类（VIF41）
10	热带森林草地	炎热湿润季雨林类（VIIE35）,炎热潮湿雨林类（VIIF42）

表1

表2

图1

图2

图3

表3

图4

表4

草地NPP对影响因子的敏感度"

Σθ	降水量	$K$ 值	太阳辐射	NDVI
50.067	47.348	47.348	18.398	52.529

表4

图5

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月份	降水量	Σθ	K值	太阳辐射	NDVI
n	0.699*	0.100*	0.697**	-0.103*	0.472**
n-1	0.423*	0.068	0.353**	-0.327**	0.269**
n-2	0.391*	0.195**	0.290**	-0.313**	0.231**
n-3	0.323*	0.129**	0.066	-0.248**	0.228**
n-4	0.230*	0.073	0.062	0.022	-0.021

不同草地类型净初级生产力(NPP)模拟及其敏感性分析

Simulation and sensitivity analysis of net primary productivity(NPP) of different grassland types

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类组号	草地类组	年均NPP/g C·m^-2·a^-1
1	冻原高山草地	261.63
2	冷荒漠草地	141.26
3	热荒漠带草地	310.37
4	半荒漠草地	316.92
5	斯太普草地	424.67
6	萨王纳草地	640.29
7	温带湿润草地	452.88
8	温带森林草地	612.27
9	亚热带森林草地	784.26
10	热带森林草地	898.08

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