中国草地峰值物候特征时空变化及其影响因素分析

doi:10.16258/j.cnki.1674-5906.2026.05.002

生态环境学报 ›› 2026, Vol. 35 ›› Issue (5): 679-690.DOI: 10.16258/j.cnki.1674-5906.2026.05.002

中国草地峰值物候特征时空变化及其影响因素分析

陈煖杏¹^,²^,³(), 向云燕¹^,²^,⁴, 廖敬¹^,²^,³, 杨元征¹^,², 俎佳星¹^,²^,^*()

¹ 南宁师范大学/北部湾环境演变与资源利用教育部重点实验室，广西南宁 530001
² 南宁师范大学/广西地表过程与智能模拟重点实验室，广西南宁 530001
³ 南宁师范大学自然资源与测绘学院，广西南宁 530001
⁴ 南宁师范大学地理科学与规划学院，广西南宁 530001

收稿日期:2025-09-06 修回日期:2026-02-14 接受日期:2026-03-15 出版日期:2026-05-18 发布日期:2026-05-08
通讯作者: *E-mail: zujiaxing@nnnu.edu.en
作者简介:陈煖杏（2001年生），女，硕士研究生，主要研究方向为遥感植被物候。E-mail: cxxfc123@163.com
基金资助:
国家自然科学基金项目(42001216)

Spatiotemporal Variation of Peak Phenology Metrics in China’s Grasslands and Analysis of Influencing Factors

CHEN Xuanxing¹^,²^,³(), XIANG Yunyan¹^,²^,⁴, LIAO Jing¹^,²^,³, YANG Yuanzheng¹^,², ZU Jiaxing¹^,²^,^*()

¹ Key laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education/Nanning Normal University, Nanning 530001, P. R. China
² Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation/Nanning Normal University, Nanning 530001, P. R. China
³ School of Natural Resources and Surveying and Mapping, Nanning Normal University, Nanning 530001, P. R. China
⁴ School of Geography Science and Planning, Nanning Normal University, Nanning 530001, P. R. China

Received:2025-09-06 Revised:2026-02-14 Accepted:2026-03-15 Online:2026-05-18 Published:2026-05-08

摘要/Abstract

摘要：

草地生态系统是中国陆地生态系统中至关重要的组成部分，在维持生态系统平衡和功能方面发挥着不可替代的作用。该研究以中国草地生态系统为研究对象，基于2000－2022年GOSIF GPP数据集，系统分析了中国草地植被生长季峰值物候（Peak of Growing Season，POS）和总初级生产力最大值（GPP_max）的时空演变规律，并深入探讨了其对春季物候（Start of Growing Season，SOS）及气候因子（温度和降水）的响应机制。研究结果表明：在研究时段内，整个研究区域的POS呈现不显著的提前趋势，变化速率为0.03 d⁻¹∙a⁻¹；而GPP_max则表现出显著的增加趋势，斜率为0.029 g∙m⁻²∙d⁻¹∙a⁻¹（以C计）。从空间上看，研究区约有55.84%的像元表现为POS提前的趋势（显著占比为22.40%），约有78.85%的区域表现出GPP_max增加的趋势（显著占比为33.31%）。就驱动因素而言，SOS在POS的变化趋势中起主导作用，其影响显著超过气候因素，这一发现凸显了植被自身节律的联动效应对植被后期生长的关键作用。GPP_max的主控因子呈现显著的区域分异特征：在西部干旱半干旱区主要受SOS调控，青藏高原则以温度为主导因子，而东部干旱区的GPP_max主要受降水控制。未来在研究全球碳循环与植被物候变化中，必须同时重视气候因素和生物节律的双重影响。

关键词: 草地生态系统, 植被物候, 总初级生产力最大值（GPP_max）, 时空变化, 驱动因子

Abstract:

Grassland ecosystems constitute a vital component of China's terrestrial ecosystems, playing an irreplaceable role in maintaining ecological balance and functionality. This study focuses on China's grassland ecosystems and systematically investigates the spatiotemporal evolution patterns of the Peak of Growing Season (POS) and maximum gross primary productivity (GPP_max), using the GOSIF GPP dataset from 2000 to 2022. Furthermore, we comprehensively examine their response mechanisms to the Start of Growing Season (SOS) and climatic factors (temperature and precipitation). The results demonstrated that during the study period, the entire study area exhibited a non-significant advancing trend in POS at a rate of 0.3 days/decade, while GPP_max showed a significant increasing trend with a slope of 0.029 g∙m⁻²∙d⁻¹ (in terms of carbon, the same below) per year. Spatially, approximately 55.84% of the pixels displayed an advancing POS trend (22.40% being statistically significant), and about 78.85% of the area exhibited increasing GPP_max trends (33.31% being statistically significant). Regarding the driving factors, SOS emerged as the dominant factor influencing POS trends, with its impact significantly surpassing that of climatic factors. This finding highlights the crucial role of vegetation's intrinsic rhythmic linkage effects on subsequent growth. The primary controlling factors of GPP_max exhibited distinct regional heterogeneity: SOS was the main regulator in western arid/semi-arid regions, temperature dominated on the Tibetan Plateau, while precipitation primarily controlled GPP_max in eastern arid regions. These findings underscore that future research on global carbon cycles and vegetation phenological changes must simultaneously consider the dual influences of climatic factors and biological rhythms.

Key words: grassland ecosystems, vegetation phenology, maximum gross primary productivity (GPP_max), spatiotemporal variation, driving factors

中图分类号:

Q948
X173

陈煖杏, 向云燕, 廖敬, 杨元征, 俎佳星. 中国草地峰值物候特征时空变化及其影响因素分析[J]. 生态环境学报, 2026, 35(5): 679-690.

CHEN Xuanxing, XIANG Yunyan, LIAO Jing, YANG Yuanzheng, ZU Jiaxing. Spatiotemporal Variation of Peak Phenology Metrics in China’s Grasslands and Analysis of Influencing Factors[J]. Ecology and Environmental Sciences, 2026, 35(5): 679-690.

图/表 9

图1 中国草地分布图根据Wang et al.（2020）的研究将研究区分为西部干旱半干旱区、青藏高原、东部干旱区。本图基于国家地理信息公共服务平台下载，审图号为GS（2024）0650号；底图边界无修改。下同

Figure 1 Distribution of grasslands in China

图2 基于GOSIF GPP时序物候提取示意图黑线表示基于logistic函数拟合后的GPP时序曲线，红线表示logistic函数拟合的GPP曲线导数；SOS表示春季物候，POS表示生长季峰值物候，GPP表示总初级生产力，POS对应的GPP为GPPmax。下同

Figure 2 Schematic diagram for phenological extraction of GOSIF GPP time series

图3 2000－2022年中国草地POS、GPPmax年际变化趋势

Figure 3 Interannual trends of POS and GPPmax in Chinese grasslands from 2000 to 2022

图4 2000－2022年中国草地POS、GPPmax均值空间分布

Figure 4 Spatial distribution of mean POS and GPPmax in Chinese grasslands from 2000 to 2022

图5 2000－2022年中国草地POS、GPPmax变化趋势图中百分数表示像元占比，下同

Figure 5 Trends in POS and GPPmax in Chinese grasslands from 2000 to 2022

图6 POS、GPPmax分别与影响因子（SOS、温度、降水）变化趋势的异同 PRE代表降水，TEM为温度；“+”表示正趋势，“?”表示负趋势

Figure 6 Similarities and differences in the trends of POS and GPPmax with influencing factors (SOS, temperature, precipitation)

图7 POS、GPPmax分别与影响因子（SOS、温度、降水）的偏相关空间格局

Figure 7 Partial Correlation Spatial Patterns of POS and GPPmax with influencing factors (SOS, temperature, precipitation)

图8 基于偏相关显著性水平识别出的POS与GPPmax的主控因子

Figure 8 The most significant factor controlling POS and GPPmax, according to the significance level of the partial correlation

图9 3个分区的主控因子

Figure 9 Dominant controlling factors in the three subregions

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中国草地峰值物候特征时空变化及其影响因素分析

Spatiotemporal Variation of Peak Phenology Metrics in China’s Grasslands and Analysis of Influencing Factors

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