Study on the Spatiotemporal Patterns and Driving Factors of Forest Vegetation Net Primary Productivity in the Central Yunnan Urban Agglomeration

doi:10.16258/j.cnki.1674-5906.2026.02.005

Ecology and Environmental Sciences ›› 2026, Vol. 35 ›› Issue (2): 209-222.DOI: 10.16258/j.cnki.1674-5906.2026.02.005

• Research Article [Ecology] • Previous Articles Next Articles

Study on the Spatiotemporal Patterns and Driving Factors of Forest Vegetation Net Primary Productivity in the Central Yunnan Urban Agglomeration

YU Yanju¹^,²^,³(), DING Xue¹^,²^,³^,^*()

1. Faculty of Geography, Yunnan Normal University, Kunming 650500, P. R. China
2. Yunnan Provincial Key Laboratory of Remote Sensing for Resources and Environment in Universities, Kunming 650500, P. R. China
3. Yunnan Provincial Engineering and Technology Research Center for Geospatial Information Technology, Kunming 650500, P. R. China

Received:2025-02-19 Revised:2025-11-12 Accepted:2025-11-19 Online:2026-02-18 Published:2026-02-09
Contact: DING Xue

滇中城市群森林植被净初级生产力时空变化特征及其影响因素研究

余燕鞠¹^,²^,³(), 丁雪¹^,²^,³^,^*()

1.云南师范大学地理学部，云南昆明 650500
2.云南省高校资源与环境遥感重点实验室，云南昆明 650500
3.云南省地理空间信息技术工程技术研究中心，云南昆明 650500

通讯作者: 丁雪
作者简介:余燕鞠（2002年生），女，硕士研究生，主要研究方向为土地利用模拟与碳储量估算。E-mail: 1690728905@qq.com
基金资助:
国家自然科学基金项目(42261073);国家自然科学基金项目(41971369);云南省基础研究专项计划面上项目(202401AT0701103)

Abstract

Abstract:

Revealing the carbon sink dynamics of forest ecosystems and their environmental response mechanisms in the Central Yunnan Urban Agglomeration provides crucial theoretical foundations for sustainable management of regional forest resources. Utilizing multi-source remote sensing data including MOD17A3H V6 NPP data, MCD12Q1 V6 land cover classification, ERA5 meteorological data, and SRTMGL1_003 elevation data, combined with multivariate statistical methods such as the Hurst index and partial derivative residual analysis, this study systematically investigated the spatiotemporal variation characteristics of forest net primary productivity (NPP) and its influencing factors in the Central Yunnan Urban Agglomeration from 2000 to 2020. The main findings include: 1) From 2000 to 2020, the total forest area in the Central Yunnan Urban Agglomeration was 1.77×104 km², of which broadleaf forests, coniferous forests, and mixed forests accounted for 0.34×104 km², 0.70×104 km² and 0.73×104 km², respectively. 2) The total NPP of forests increased by an average of C 2.01 Tg∙a⁻¹per year (an increase of 60.5%), with the highest average annual growth rate in mixed forests (C 1.71 Tg∙a⁻¹), followed by coniferous forests (C 1.66 Tg∙a⁻¹) and broadleaf forests (C 0.80 Tg∙a⁻¹). 3) In 55.8% of the forest areas, NPP showed an increasing trend, with 6.86% of the areas experiencing highly significant and significant increases. In contrast, 44.2% of the forest areas showed a decreasing trend, with 2.10% of the areas experiencing significant decreases. 4) The Hurst index was <0.5 in 78.0% of the areas, indicating that future NPP is likely to decrease gradually. 5) Topography had a significant impact, with NPP peaking at elevations of 2100‒2400 m and decreasing with increasing slope. The southern aspect had the highest NPP. 6) Human activities contributed to 99.3% of the changes, making them the dominant factor for NPP improvement (accounting for 33.7%). However, the combined effects of climate change and human activities were the main cause of NPP degradation (accounting for 30.6%). The findings can provide a scientific reference for forest carbon cycle research and sustainable forest resource management in the region.

Key words: forest, net primary productivity, spatiotemporal patterns, climate change, human activities, the Central Yunnan Urban Agglomeration

摘要：

揭示滇中城市群森林生态系统的碳汇动态及其环境响应机制，可为区域森林资源的可持续管理提供重要的理论依据。基于MOD17A3H V6 NPP数据、MCD12Q1 V6土地覆盖类型数据、ERA5气象数据和SRTMGL1_003高程数据等多源遥感数据，结合Hurst指数和偏导数残差法等多元统计方法，系统地研究了2000－2020年滇中城市群森林净初级生产力（NPP）的时空变化特征及其影响因素。研究结果表明，1）2000－2020年，滇中城市群森林总面积为1.77×10⁴ km²，其中阔叶林、针叶林和混交林分别为0.34×10⁴ km²、0.70×10⁴ km²和0.73×10⁴ km²。2）森林NPP总量年均增长C 2.01 Tg∙a⁻¹（增幅60.5%），混交林的年均增速最高（C 1.71 Tg∙a⁻¹），其次为针叶林（C 1.66 Tg∙a⁻¹）和阔叶林（C 0.80 Tg∙a⁻¹）。3）55.8%的区域森林NPP呈增加趋势，6.86%的区域为极显著和显著增加，44.2%的区域呈减少趋势，2.10%的区域显著减少。4）78.0%的区域Hurst指数<0.5，预示未来NPP将呈现逐步减少。5）地形影响显著，NPP在2100－2400 m达峰值，随坡度增加而降低，南坡向NPP最高。6）人类活动贡献率达99.3%，是NPP改善的主导因素（占33.7%），而气候变化和人类活动的共同作用则是导致NPP退化的主要原因（占30.6%）。研究结果可为该区域森林碳循环研究和森林资源可持续管理提供科学参考。

关键词: 森林, 净初级生产力（NPP）, 时空变化, 气候变化, 人类活动, 滇中城市群

CLC Number:

Q948
X173

YU Yanju, DING Xue. Study on the Spatiotemporal Patterns and Driving Factors of Forest Vegetation Net Primary Productivity in the Central Yunnan Urban Agglomeration[J]. Ecology and Environmental Sciences, 2026, 35(2): 209-222.

余燕鞠, 丁雪. 滇中城市群森林植被净初级生产力时空变化特征及其影响因素研究[J]. 生态环境学报, 2026, 35(2): 209-222.

Figures/Tables 18

Figure 1 Location of the Central Yunnan Urban Agglomeration

Table1 Data resources

数据类型	数据名称	空间分辨率	数据来源
森林净初级生产力	MOD17A3H V6	500 m	NASA（https://search.earthdata.nasa.gov/）
森林类型	MCD12Q1 V6	500 m	NASA（https://search.earthdata.nasa.gov/）
降水	ERA5	0.1°	ECMWF（https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5）
气温	ERA5	0.1°
高程	USGS/SRTMGL1_003	30 m	中科院地理空间数据云平台（http://www.gscloud.cn/）
坡度		30 m
坡向		30 m
气象站点数据			NOAA（https://www.ncei.noaa.gov/data/global-summary-of-the-day/archive/）

Figure 2 Scatter plots of the surface temperature from ERA5 dataset and station

Table 2 Classification of theil-sen median trend analysis change trend

N	Z	变化趋势
N>0	2.58<Z	极显著增加
	1.96<Z≤2.58	显著增加
	1.65<Z≤1.96	微显著增加
	0<Z≤1.65	不显著增加
N=0	Z=0	无变化
N<0	−1.65≤Z<0	不显著减少
	−1.96≤Z<−1.65	微显著减少
	−2.58≤Z<−1.96	显著减少
	Z<−2.58	极显著减少

Table 3 Different scenarios of contributions of climate change and human activities on forest NPP changes

情景	N	C	H	气候变化相对作用	人类活动相对作用	说明
植被改善	>0	>0	>0	K_c	K_h	气候变化和人类活动共同促进植被恢复
		>0	<0	100	0	气候变化促进植被恢复
		<0	>0	0	100	人类活动促进植被恢复
植被退化	<0	<0	<0	K_c	K_h	气候变化和人类活动共同促使植被退化
		<0	>0	100	0	气候变化促使植被退化
		>0	<0	0	100	人类活动促使植被退化

Figure 3 Variation in the annual total net primary productivity (NPP) of forest in the Central Yunnan Urban Agglomeration

Figure 4 Variation in the annual total NPP of different forest types in the Central Yunnan Urban Agglomeration

Figure 5 Variation in annual average NPP of forest in the Central Yunnan Urban Agglomeration

Figure 6 Variation in annual average NPP of different forest types in the Central Yunnan Urban Agglomeration

Figure 7 Forest NPP change trend of the the Central Yunnan Urban Agglomeration

Figure 8 Significance of forest NPP change trend of the Central Yunnan Urban Agglomeration

Figure 9 Hurst index of forest NPP in the Central Yunnan Urban Agglomeration

Figure 10 The impact of topographic factors on NPP

Figure 11 Variation of annual average temperature and cumulative precipitation in the Central Yunnan Urban Agglomeration

Figure 12 The contributions of temperature and precipitation to the changes in NPP in the Central Yunnan Urban Agglomeration

Figure 13 The contributions of climatic factors and human activities to the changes in NPP in the Central Yunnan Urban Agglomeration

Figure 14 The contribution proportions of climate changes and human activities to forest NPP in the Central Yunnan Urban Agglomeration

Figure 15 The dominant influence on the changes of forest NPP in the Central Yunnan Urban Agglomeration

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Study on the Spatiotemporal Patterns and Driving Factors of Forest Vegetation Net Primary Productivity in the Central Yunnan Urban Agglomeration

滇中城市群森林植被净初级生产力时空变化特征及其影响因素研究

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[3]	XU Da, GONG Chengcheng, ZHANG Zaiyong, RAN Bin, HU Yue, WANG Hanbing, CHEN Chen. The Spatiotemporal Variation Patterns of Vegetation Net Primary Productivity and Its Influencing Factors in the Mu Us Sandy Land [J]. Ecology and Environmental Sciences, 2025, 34(9): 1361-1372.
[4]	LI Dongyi, LI Tingting, XUE Wanyi, XIA Yongzhi, WANG Zhengxiang. Prediction and Analysis of Potential Habitat Distribution of Taxus wallichiana var. Chinensis under Climate Change: A Case Study of Hubei Province [J]. Ecology and Environmental Sciences, 2025, 34(9): 1398-1409.
[5]	LI Lin, ZHANG Chaoyang, CHU Xiaoxue, ZHOU Jinggang, WANG Xue, WEI Shiguang. Studies on Species Diversity and Functional Diversity of Different Types of Forests in Dinghu Mountains [J]. Ecology and Environmental Sciences, 2025, 34(8): 1219-1227.
[6]	ZHANG Shengbo, WU Zuohang, DANG Haofei, LIAO Kuo, LU Dengsheng, LI Dengqiu. The Response and Differences of Different Remote Sensing Vegetation Indices to Extreme Climate Events in the Wuyi Mountain Region over the Last 20 Years [J]. Ecology and Environmental Sciences, 2025, 34(8): 1240-1254.
[7]	QI Xun, FENG Xinxin, CHEN Yingjun, FENG Yanli, CHEN Tian, LI Jun, ZHANG Gan. Emission Characteristics and Influence Factors of NH₃ and Amines in Particulate Matter Emitted by Light-duty Gasoline Trucks [J]. Ecology and Environmental Sciences, 2025, 34(7): 997-1006.
[8]	LIU Zeyuan, WEI Youhai, YAN Xufa, CHENG Liang, HOU Lu, YAN Ziwei, GUO Liangzhi. Impact of Climate Change on the Potential Geographic Distribution of the Invasive Weed Sonchus asper [J]. Ecology and Environmental Sciences, 2025, 34(6): 845-852.
[9]	ZHOU Ruijiao, ZHANG Hong, QIAN Min. Spatial-Temporal Evolution of Ecosystem Service Flows in the Three Gorges Reservoir Area in the Past 30 Years and Influencing Factors [J]. Ecology and Environmental Sciences, 2025, 34(6): 876-887.
[10]	ZHANG Yali, HUANG Zhujun, TIAN Yichao, LIN Junliang, QIN Caihuan. Time-lag and Accumulation Responses of Fractional Vegetation Coverage Change to Extreme Climate in Southwestern China [J]. Ecology and Environmental Sciences, 2025, 34(5): 665-677.
[11]	XU Maohong. The Study on the Elevational Patterns and Underlying Influence Factors of Soil Microbial α Diversity in a Warm-temperate Forest [J]. Ecology and Environmental Sciences, 2025, 34(5): 678-687.
[12]	ZHANG Dandan, WU Zhenhai, WU Ke, BI Fang, LI Yunfeng, AN Cong, HAN Yixin, LIU Zhengyang, ZHU Ling, WANG Xuezhong. Characterization of Ozone Pollution and Influencing Factors Based on Different Types of Ozone Pollution Days: A Case Study in Bozhou City [J]. Ecology and Environmental Sciences, 2025, 34(5): 720-730.
[13]	DENG Pengfei, XIAO Yongyou, ZENG Changjin, GAO Yu, ZHANG Xiulan, CHEN Xingbin, XIAO Fuming, XU Xiaoniu. Characteristics of Community Structure and Species Diversity of a Long-term Abandoned Chinese Fir Plantation Forest [J]. Ecology and Environmental Sciences, 2025, 34(4): 511-520.
[14]	XU Fei, JIA Qinqi, GUO Na, HU Jiahao, FANG Shuangxi. The Impact of Litter Removal on Soil CO₂ and N₂O Fluxes in Typical Moso Bamboo Forests in the Yangtze River Delta, China [J]. Ecology and Environmental Sciences, 2025, 34(3): 380-390.
[15]	GUO Zhao, SHI Yun, LIU Tieming, ZHANG Yuxin, YAN Yongzhi. Analysis of Spatiotemporal Patterns and Driving Factors of NPP on the Northern Slope of the Qinling Mountains from 2001 to 2020 [J]. Ecology and Environmental Sciences, 2025, 34(3): 401-410.