内蒙古NPP时空特征分析及多情景下的预测研究

doi:10.12118/j.issn.1000-6060.2025.250

Abstract

Abstract:

Global warming caused by climate change currently exerts a profound impact on terrestrial ecosystem productivity. As a core indicator of the carbon sequestration capacity of vegetation, spatiotemporal changes in net primary productivity (NPP) directly influence regional carbon-sink functions and ecosystem stability. As an important ecological security barrier in northern China, Inner Mongolia encompasses diverse ecosystems, such as grasslands, forests, and deserts. Its NPP is particularly sensitive to climate change, and any abnormal fluctuations may significantly compromise regional ecological balance and carbon cycling. This study integrated multimodel Coupled Model Intercomparison Project Phase 6 (CMIP6) projections, the MOD17A3 NPP dataset, and ERA5-Land reanalysis temperature and precipitation data to systematically analyze spatiotemporal NPP patterns in Inner Mongolia (2001—2024), projecting trends (2025—2100) under four shared socioeconomic pathway (SSP) scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. We employed Sen’s trend analysis to quantify historical changes and utilized the Delta downscaling method to enhance the accuracy and spatial resolution of CMIP6 climate projections. We also applied Lasso regression to construct a robust multivariate NPP, namely the meteorological relationship model. Taylor diagram analysis was used to identify EC-Earth3-Veg-LR as the best-performing CMIP6 model for the region; this model was subsequently used to drive Lasso-based projections. Results indicated that the annual average NPP between 2001 and 2024 was 277.4 g C·m^-2, exhibiting a distinct spatial pattern characterized by a “northwest-high, southwest-low” spatial gradient. NPP increased significantly (P<0.05) or extremely significantly (P<0.01) across 20.7% of the region, driven mainly by climatic warming and humidification, particularly in eastern grasslands. Critically, Delta downscaling significantly resolved CMIP6 projections for regional-scale analysis. Additionally, our projections revealed an oscillatory increase in regional NPP across all four SSP scenarios, although with notable magnitude and spatial heterogeneity differences. The SSP1-2.6 (sustainability) pathway projected the highest average NPP increase and the most balanced spatial growth across the region. The SSP2-4.5 (middle of the road) scenario also showed substantial gains, albeit these were less uniformly distributed. The SSP3-7.0 (regional rivalry) scenario exhibited the smallest area of significant NPP change, dominated primarily by fluctuation rather than strong upward trends. While the SSP5-8.5 (fossil-fueled development) scenario projected an overall NPP increase, it was characterized by the most pronounced spatial disparities, potentially threatening regional ecosystem stability by exacerbating imbalances. This study quantifies NPP evolutionary trends, providing reliable scenario-prediction results based on climate-projection data, offering an important scientific basis for formulating climate-adaptive ecological management strategies, carbon sequestration planning, and related policies in this ecologically sensitive and strategically significant region.

Key words: CMIP6, NPP, climate projection, Inner Mongolia

QU Xuebin, WU Nier, ZHAO Yuechen, NIU Dong, WANG Yaying, LIU Xin. Spatiotemporal analysis and multi-scenario projections of NPP in Inner Mongolia[J].Arid Land Geography, 2026, 49(6): 1180-1191.

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序号	气候模式	研究机构	国家	分辨率/(°)
1	ACCESS-CM2	ACCESS	澳大利亚	1.875×1.250
2	AWI-CM-1-1-MR	AWI	德国	0.938×0.938
3	BCC-CSM2-MR	BCC、CMA	中国	1.125×1.125
4	CESM2	NCAR	美国	1.250×0.938
5	CNRM-CM6-1-HR	CNRM	法国	0.500×0.500
6	EC-Earth3-Veg-LR	EC-Earth	瑞典	1.125×1.125
7	FGOALS-f3-L	CAS-IAP	中国	2.250×1.875
8	GFDL-ESM4	GFDL	美国	1.250×1.000
9	MIROC6	MIROC	日本	1.406×1.406
10	MRI-ESM2-0	MRI	日本	1.125×1.125
11	NorESM2-MM	NCC	挪威	1.250×0.938

要素	1月	2月	3月	4月	5月	6月	7月	8月	9月	10月	11月	12月
气温	0.173	0.236	0.394^*	0.340^*	0.248	0.403^*	0.305	0.438^*	0.250	0.203	0.211	0.235
降水	0.307	0.183	0.261	0.256	0.346^*	0.390^*	0.472^*	0.355^*	0.328	0.302	0.309	0.303

Spatiotemporal analysis and multi-scenario projections of NPP in Inner Mongolia

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