基于植被动态模式预估中国植被净初级生产力变化格局

doi:10.11821/dlxb202207017

Abstract

Abstract:

Six vegetation dynamic models, provided by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), are selected and verified for net primary productivity (NPP) in China based on remote sensing retrials. Then the goodness of fit of each model is used as the weight to synthesize a new sequence to estimate the future change pattern of China's NPP under the RCP2.6 and RCP6.0 scenarios. This study aims to solve inaccuracy of the estimation on the change pattern of China's NPP due to differences in data and methods. The results show that the single model has a poor fitting effect on NPP in most regions of China (R²< 0.4), the average NPP is 33%-97% higher than the remotely sensed value, but it can well reflect the decreasing trend from southeast to northwest China. The overall goodness of fit of the proposed NPP data is 0.85, and the goodness of fit in most vegetation zones is basically greater than 0.3. In the future 30 years, China's average NPP will continue to decrease from southeast to northwest, and the average value will show a fluctuating growth, which is expected to reach 8.8 μg/(m² s) in 2035 and 9.7 μg/(m² s) in 2050. With the elaspe of time, the main growth area under the RCP2.6 scenario will shift from southern to northern China. This is reflected in the fact that NPP in north China will increase significantly at a rate greater than 0.15 μg/(m² s) per year, but the growth rate will slow down and the area of significant growth will decrease in the southwestern and central-south regions. Under the RCP6.0 scenario, the main growth areas will retreat to the northeastern, southeastern and western regions, and the growth in the central and eastern regions will become insignificant. The high emission scenario will promote the growth of NPP before 2035 and inhibit the growth after 2035. The NPP will be extremely distributed under the RCP 6.0 scenario. For instance, the alpine desert grassland, temperate desert, shrub and semi-shrub desert in the northwest of Qinghai-Tibet Plateau will grow slowly or even stop growing.

Key words: net primary productivity, ISI-MIP, climate change, change pattern

MA Zhongxue, CUI Huijuan, GE Quansheng. Prediction of net primary productivity change pattern in China based on vegetation dynamic models[J].Acta Geographica Sinica, 2022, 77(7): 1821-1836.

Figures/Tables 10

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References 41

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一级植被区	二级植被区	代码	一级植被区	二级植被区	代码
寒温带针叶林区域	南寒温带针叶林地带	Ⅰi		温带北部荒漠草原亚区	ⅥAic
温带针叶阔叶混交林区域	温带北部针叶阔叶混交林地带	Ⅱi		温带南部森林(草甸)草原	ⅥAiia
温带针叶阔叶混交林区域	温带南部针叶阔叶混交林地带	Ⅱii		温带南部荒漠草原亚区	ⅥAiic
暖温带落叶阔叶林区域	暖温带北部落叶栎林地带	Ⅲi		温带南部典型草原亚区	ⅥAiib
暖温带落叶阔叶林区域	暖温带南部落叶栎林地带	Ⅲii		温带北部荒漠草原亚区	ⅥBia
亚热带常绿阔叶林区域	北亚热带常绿、落叶混交林地带	ⅣAi	温带荒漠区域	温带半灌木、矮乔木荒漠地带	ⅦAi
	中亚热带常绿阔叶林北部亚区	ⅣAiia		温带半灌木、灌木荒漠地带	ⅦBi
	中亚热带常绿阔叶林南部亚区	ⅣAiib		温带灌木、禾草半荒漠亚区	ⅦBia
	南亚热带季风常绿阔叶林地带	ⅣAiii		温带灌木、半灌木荒漠亚区	ⅦBib
	中亚热带常绿阔叶林地带	ⅣBi		暖温带灌木半灌木荒漠亚区	ⅦBiia
	南亚热带季风常绿阔叶林地带	ⅣBii		暖温带灌木半灌木、裸露地带	ⅦBiib
	亚热带山地寒温性针叶林地带	ⅣBiii	青藏高原高寒植被区域	高寒灌丛、草甸地带	ⅧAi
热带季雨林、雨林区域	北热带半常绿季雨林、湿润雨林地带	ⅤAi		高寒草甸地带	ⅧAii
	南热带季雨林、湿润雨林地带	ⅤAii		高寒草原地带	ⅧBi
	北热带季节雨林、半常绿季雨林地带	ⅤBi		温性草原地带	ⅧBii
温带草原区域	温带北部草甸草原亚区	ⅥAia		高寒荒漠地带	ⅧCi
温带草原区域	温带北部典型草原亚区	ⅥAib		温性荒漠地带	ⅧCii

	动态植被	氮限制	热应激	生根深度	多年冻土	能量平衡	土—水—热耦合	潜热	显热
ORCHIDEE	是	否	是	是	是	是	是	是	是
DLEM	否	是	是	否	是	否	是	是	否
LPJ-GUESS	是	是	是	是	否	否	否	否	否
VISIT	否	否	是	是	否	否	否	是	否
LPJML	是	否	是	否	否	是	是	是	是
CLM4.5	否	是	否	是	否	是	是	是	是

	寒温带针叶林	温带针阔叶混交林	暖温带落叶阔叶林	亚热带常绿阔叶林	热带季雨林、雨林	温带草原	温带荒漠	青藏高寒区	全国
DLEM	12.5	12.5	13.9	15.9	21.8	8.2	1.1	2.7	8.5
ORCHIDEE	14.6	18.9	15.3	18.3	23.8	10.9	1.2	5.8	10.4
VISIT	12.0	19.7	15.8	25.4	33.4	4.2	1.5	13.6	12.6
LPJ-GUESS	17.4	18.8	15.1	15.4	19.9	13.3	4.0	2.8	10.5
LPJML	15.4	16.8	15.7	19.6	23.0	10.8	2.5	9.6	11.7
CLM4.5	12.4	18.0	9.8	18.2	21.9	6.6	0.7	4.8	8.8
遥感反演值	8.5	9.5	7.7	9.9	12.5	6.2	2.4	3.4	6.4

Prediction of net primary productivity change pattern in China based on vegetation dynamic models

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