1.西安科技大学测绘科学与技术学院,西安 710054
2.西安科技大学国土空间研究所,西安 710054
3.陕西国图信息技术有限公司,西安 710034
杨梅焕(1982—),女,博士,副教授,主要从事沙漠化生态过程研究。E-mail: ymh8307024@163.com
王涛(1984—),男,博士,副教授,主要从事区域环境变化研究。E-mail: wht432@163.com
收稿:2025-08-06,
修回:2025-09-22,
录用:2025-09-29,
网络首发:2025-11-21,
纸质出版:2026-04-01
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杨梅焕,陶冰玉,王涛,等.黄土高原植被NEP时空变化及对气温降水和退耕还林(草)的响应[J].水土保持学报,2026,40(2):405-416.
YANG Meihuan, TAO Bingyu, WANG Tao, et al. Spatiotemporal variation of vegetation NEP on Loess Plateau and its responses to temperature, precipitation, and grain-for-green program[J]. Journal of Soil and Water Conservation, 2026, 40(2):405-416.
杨梅焕,陶冰玉,王涛,等.黄土高原植被NEP时空变化及对气温降水和退耕还林(草)的响应[J].水土保持学报,2026,40(2):405-416. DOI: 10.13870/j.cnki.stbcxb.2026.02.005. CSTR: 32310.14.stbcxb.2026.02.005.
YANG Meihuan, TAO Bingyu, WANG Tao, et al. Spatiotemporal variation of vegetation NEP on Loess Plateau and its responses to temperature, precipitation, and grain-for-green program[J]. Journal of Soil and Water Conservation, 2026, 40(2):405-416. DOI: 10.13870/j.cnki.stbcxb.2026.02.005. CSTR: 32310.14.stbcxb.2026.02.005.
目的
2
净生态系统生产力(net ecosystem productivity, NEP)是衡量陆地生态系统碳收支的重要指标,定量评估净生态系统生产力及其影响因素,对于深入理解区域碳循环及其驱动机制具有重要意义。
方法
2
以黄土高原为研究区,基于MOD13A1 NDVI和MOD17A3 NPP数据产品、气温、降水量、DEM和土地覆盖等数据,利用Carnegie-Ames-Stanford-Approach(CASA)模型、Theil-Sen趋势分析、Mann-Kendall显著性检验和相关性分析等方法,分析2001—2022年黄土高原植被NEP时空分布变化特征,并探讨其对气温、降水量和退耕还林(草)工程实施的响应。
结果
2
1)2001—2022年黄土高原植被NEP多年平均值为327.06 g/m²(以C计),总体呈显著增加趋势,增加速率为7.51 g/(m²·a) (
p
<
0.05)。其中,草地的增速最快。2)空间上,黄土高原植被NEP以增加趋势为主,其中显著增加区域占77.38%,主要分布在黄土高塬沟壑区的中部和黄土丘陵沟壑区的中部;显著减少区域占比仅为0.98%,主要分布在土石山区及河谷平原区的西部、沙地和农灌区的西南部及黄土高塬沟壑区的西部。不同分区中,黄土丘陵沟壑区植被NEP呈显著增加趋势的区域面积占比最高,占该分区面积的93.00%。3)黄土高原植被NEP与年平均气温、年降水量均呈正相关为主,其中呈显著正相关的区域分别占区域总面积的6.28%和26.38%,前者集中分布在黄土高塬沟壑区南部,后者集中分布在黄土高塬沟壑区的北部和黄土丘陵沟壑区东部、沙地和农灌区中部、东北部、土石山区及河谷平原区东北部;呈显著负相关的区域分别占1.38%和0.13%,分别集中在黄土高塬沟壑区西部和西北部。不同分区中农业植被、森林和草地植被NEP与年降水量呈显著正相关的面积比例高于年平均气温,且沙地和农灌区植被NEP与年降水量关系最为明显。4)黄土高原坡度
>
25°的区域中
,耕地转为林地和草地区域的植被NEP增速,高于耕地保持不变的区域。
结论
2
退耕还林(草)工程的实施及气候暖湿化对黄土高原植被NEP增加起到重要作用。
Objective
2
Net ecosystem productivity (NEP) is a key indicator for measuring the carbon budget of terrestrial ecosystems. Quantitatively assessing NEP and its influencing factors is of great importance for deeply understanding the regional carbon cycle and its driving mechanisms.
Methods
2
Taking the Loess Plateau as the study area, the research used data products such as MOD13A1 NDVI, MOD17A3 NPP, climate data (temperature and precipitation), digital elevation model (DEM), and land cover data. The Carnegie-Ames-Stanford-Approach (CASA) model, Theil-Sen trend analysis, Mann-Kendall significance test, and correlation analysis were employed to analyze the spatiotemporal distribution changes of vegetation NEP on the Loess Plateau from 2001 to 2022 and to explore its responses to temperature, precipitation, and the implementation of the Grain-for-Green Program.
Results
2
1) From 2001 to 2022, the multi-year mean vegetation NEP on the Loess Plateau was 327.06 g/m² (in terms of C), showing a significant increasing trend at a rate of 7.51 g/(m²·a) (
p
<
0.05). Among land cover types, grassland had the fastest growth rate. 2) Spatially, vegetation NEP on the Loess Plateau mainly exhibited an increasing trend. Significantly increasing areas accounted for 77.38% of the total, primarily distributed in the central part of the loess tableland gully region and the central part of the loess hilly gully region. Significantly decreasing areas accounted for only 0.98%, primarily located in the western part of the rocky mountainous and river valley plain region, the southwestern part of the sandy land and agricultural irrigation region, and the western part of the loess tableland gully region. Among the subregions, the loess hilly gully region had the highes
t proportion of areas where vegetation NEP showed a significant increasing trend, accounting for 93.00% of its total area. 3) Vegetation NEP on the Loess Plateau was overall positively correlated with both mean annual temperature and annual precipitation. Areas showing significant positive correlation accounted for 6.28% and 26.38% of the total area, respectively. The former concentrated in the southern part of the loess tableland gully region, while the latter was mainly distributed in the northern part of the loess tableland gully region and the eastern part of the loess hilly gully region, the central and northeastern parts of the sandy land and agricultural irrigation region, and the northeastern part of the rocky mountainous and river valley plain region. Areas showing significant negative correlation accounted for 1.38% and 0.13%, respectively, and were primarily distributed in the western and northwestern parts of the loess plateau gully region. Among different subregions, the proportion of areas where the vegetation NEP of cropland, forest, and grassland showed a significant positive correlation with annual precipitation was higher than that with mean annual temperature. The relationship between vegetation NEP and annual precipitation was most pronounced in the sandy land and agricultural irrigation region. 4) In areas of the Loess Plateau with slopes greater than 25°, the increase rate in vegetation NEP was higher in areas where cropland had been converted to forest or grassland than in areas where cropland remained unchanged.
Conclusion
2
The implementation of the Grain-for-Green Program and the warming-wetting climate play critical roles in increasing vegetation NEP on the Loess Plateau.
SHI L J , FENG P Y , WANG B , et al . Quantifying future drought change and associated uncertainty in southeastern Australia with multiple potential evapotranspiration models [J]. Journal of Hydrology , 2020 , 590 : e125394 .
翟涌光 , 王晓妮 , 郝蕾 , 等 . 2001—2020年内蒙古净生态系统生产力格局多时间尺度分析 [J]. 生态环境学报 , 2024 , 33 ( 2 ): 167 - 179 .
ZHAI Y G , WANG X N , HAO L , et al . Multi-time scale analysis of net ecosystem productivity pattern in Inner Mongolia from 2001 to 2020 [J]. Ecology and Environmental Sciences , 2024 , 33 ( 2 ): 167 - 179 .
周怡婷 , 严俊霞 , 刘菊 , 等 . 2000—2021年黄土高原生态分区NEP时空变化及其驱动因子 [J]. 环境科学 , 2024 , 45 ( 5 ): 2806 - 2816 .
ZHOU Y T , YAN J X , LIU J , et al . Spatio-temporal variation in NEP in ecological zoning on the Loess Plateau and its driving factors from 2000 to 2021 [J]. Environmental Science , 2024 , 45 ( 5 ): 2806 - 2816 .
裴宏泽 , 赵亚超 , 张廷龙 . 2000—2020年黄土高原NEP时空格局与驱动力 [J]. 干旱区研究 , 2023 , 40 ( 11 ): 1833 - 1844 .
PEI H Z , ZHAO Y C , ZHANG T L . Analysis of spatial and temporal patterns and drivers of local regional NEP in the Loess Plateau from 2000 to 2020 [J]. Arid Zone Research , 2023 , 40 ( 11 ): 1833 - 1844 .
张怡 , 王志慧 , 卢小平 , 等 . 黄土高原生态系统碳汇时空变化及其影响因素 [J]. 水土保持研究 , 2025 , 32 ( 1 ): 266 - 274 .
ZHANG Y , WANG Z H , LU X P , et al . Evolution of ecosystem carbon sink and its driving factors in the Loess Plateau [J]. Research of Soil and Water Conservation , 2025 , 32 ( 1 ): 266 - 274 .
刘文利 , 姜亮亮 , 刘冰 , 等 . 中国植被碳源/汇时空演变特征及其驱动因素 [J]. 生态学报 , 2024 , 44 ( 4 ): 1456 - 1467 .
LIU W L , JIANG L L , LIU B , et al . Spatio-temporal evolution characteristics and driving factors analysis of vegetation carbon sources/sinks in China [J]. Acta Ecologica Sinica , 2024 , 44 ( 4 ): 1456 - 1467 .
ZHANG K , ZHU C M , MA X D , et al . Spatiotemporal variation characteristics and dynamic persistence analysis of carbon sources/sinks in the Yellow River basin [J]. Remote Sensing , 2023 , 15 ( 2 ): e323 .
侯金龙 , 马志强 , 杨澄 , 等 . 京津冀地区植被碳源/汇的时空变化特征及影响因素分析 [J]. 生态环境学报 , 2024 , 33 ( 9 ): 1329 - 1338 .
HOU J L , MA Z Q , YANG C , et al . Analysis of spatio-temporal variation of vegetation carbon sources and sinks in the Beijing-Tianjin-Hebei region and influencing factors [J]. Ecology and Environmental Sciences , 2024 , 33 ( 9 ): 1329 - 1338 .
管亚兵 , 王军 , 覃莉 , 等 . 黄土高原植被碳源/汇估算及其对土地利用变化的响应:以延河流域为例 [J]. 环境科学 , 2025 , 46 ( 3 ): 1657 - 1665 .
GUAN Y B , WANG J , TAN Li , et al . Estimation of vegetation carbon source/sink and its response to land use change in the Loess Plateau: A case study of Yanhe River basin [J]. Environmental Science , 2025 , 46 ( 3 ): 1657 - 1665 .
WANG C , ZHAO W Z , ZHANG Y Y . The change in net ecosystem productivity and its driving mechanism in a mountain ecosystem of arid regions, northwest China [J]. Remote Sensing , 2022 , 14 ( 16 ): e4046 .
GUO D , SONG X N , HU R H , et al . Grassland type-dependent spatiotemporal characteristics of productivity in Inner Mongolia and its response to climate factors [J]. Science of the Total Environment , 2021 , 775 : e145644 .
PEI Z Y , OUYANG H , ZHOU C P , et al . Carbon balance in an alpine steppe in the Qinghai-Tibet Plateau [J]. Journal of Integrative Plant Biology , 2009 , 51 ( 5 ): 521 - 526 .
宋双双 , 秦世姣 , 孙彭成 , 等 . 基于多源遥感数据的汾河流域植被碳汇量估算及预测 [J]. 生态环境学报 , 2025 , 34 ( 3 ): 345 - 357 .
SONG S S , QIN S J , SUN P C , et al . Estimation and prediction of vegetation carbon sinks in Fenhe River basin based on multi-source remote sensing data [J]. Ecology and Environmental Sciences , 2025 , 34 ( 3 ): 345 - 357 .
干靓 , 朱佩露 , 杨颖 . 陆地生态系统碳汇能力估算及空间分布特征:以嘉兴西南三县为例 [J]. 生态学杂志 , 2025 , 44 ( 4 ): 1393 - 1408 .
GAN J , ZHU P L , YANG Y . Estimation and spatial distribution of carbon sink capacity in terrestrial ecosystems: A case study of three counties in southwest Jiaxing [J]. Chinese Journal of Ecology , 2025 , 44 ( 4 ): 1393 - 1408 .
周姝含 , 曹永强 , 么嘉棋 , 等 . 东北三省碳源/汇和碳盈亏时空分布与影响因素 [J]. 生态学报 , 2023 , 43 ( 22 ): 9266 - 9280 .
ZHOU S H , CAO Y Q , YAO J Q , et al . Spatio-temporal distribution and influencing factors of carbon source/sink, carbon surplus and deficit in three northeast provinces [J]. Acta Ecologica Sinica , 2023 , 43 ( 22 ): 9266 - 9280 .
周日平 . 黄土高原典型区土壤保持服务效应研究 [J]. 国土资源遥感 , 2019 , 31 ( 2 ): 131 - 139 .
ZHOU R P . Assessing the soil erosion control service in the typical area of Loess Plateau [J]. Remote Sensing for Land and Resources , 2019 , 31 ( 2 ): 131 - 139 .
杨梅焕 , 王添晴 , 李扬 , 等 . 黄土高原植被水分利用效率时空变化及其对不同影响因子的响应强度 [J]. 水土保持研究 , 2025 , 32 ( 3 ): 159 - 169 .
YANG M H , WANG T Q , LI Y , et al . Spatiotemporal variation of vegetation water use efficiency on the Loess Plateau and its response intensity to different influencing factors [J]. Research of Soil and Water Conservation , 2025 , 32 ( 3 ): 159 - 169 .
刘凤 , 曾永年 . 2000—2015年青海高原植被碳源/汇时空格局及变化 [J]. 生态学报 , 2021 , 41 ( 14 ): 5792 - 5803 .
LIU F , ZENG Y N . Analysis of the spatio-temporal variation of vegetation carbon source/sink in Qinghai Plateau from 2000—2015 [J]. Acta Ecologica Sinica , 2021 , 41 ( 14 ): 5792 - 5803 .
SHAO Y K , ZHU Q , FENG Z K , et al . Temporal and spatial assessment of carbon flux dynamics: Evaluating emissions and sequestration in the three northern protection forest project areas supported by google earth engine [J]. Remote Sensing , 2024 , 16 ( 5 ): e777 .
黄琪 , 彭立 , 李赛男 , 等 . 基于GAM的喀斯特植被覆盖与驱动因素非线性关系分析 [J]. 中国环境科学 , 2023 , 43 ( 5 ): 2489 - 2496 .
HUANG Q , PENG L , LI S N , et al . Analysis of the nonlinear relationship between karst vegetation cover and driving factors based on GAM [J]. China Environmental Science , 2023 , 43 ( 5 ): 2489 - 2496 .
赖金林 , 齐实 , 廖瑞恩 , 等 . 2000—2019年西南高山峡谷区植被变化对气候变化和人类活动的响应 [J]. 农业工程学报 , 2023 , 39 ( 14 ): 155 - 163 .
LAI J L , QI S , LIAO R E , et al . Vegetation change responses to climate change and human activities in southwest alpine canyon areas of China from 2000 to 2019 [J]. Transactions of the Chinese Society of Agricultural Engineering , 2023 , 39 ( 14 ): 155 - 163 .
高萌萌 , 李小磊 , 杨楠 , 等 . 黄河流域植被时空变化及其与土壤湿度的相关性分析 [J]. 水文地质工程地质 , 2023 , 50 ( 3 ): 172 - 181 .
GAO M M , LI X L , YANG N , et al . Spatio-temporal variation of vegetation and its correlation with soil moisture in the Yellow River basin [J]. Hydrogeology and Engineering Geology , 2023 , 50 ( 3 ): 172 - 181 .
谢艳玲 , 夏正清 , 王涛 , 等 . 黄河流域植被NPP时空变化及其对水热条件和退耕还林还草工程实施的响应 [J]. 测绘通报 , 2023 ( 2 ): 15 - 20 .
XIE Y L , XIA Z Q , WANG T , et al . Temporal and spatial variation of vegetation net primary product and its response to hydrothermal conditions and grain for green project in the Yellow River basin [J]. Bulletin of Surveying and Mapping , 2023 ( 2 ): 15 - 20 .
张雪纯 , 马毅 , 张靖宇 , 等 . 基于分段自适应算法的浅海水深遥感反演融合模型研究 [J]. 海洋科学 , 2020 , 44 ( 6 ): 1 - 11 .
ZHANG X C , MA Y , ZHANG J Y , et al . Research on the remote sensing inversion fusion model of shallow water depth based on the piecewise adaptive algorithm [J]. Marine Sciences , 2020 , 44 ( 6 ): 1 - 11 .
徐勇 , 黄雯婷 , 郭振东 , 等 . 2000—2020年我国西南地区植被NEP时空变化及其驱动因素的相对贡献 [J]. 环境科学研究 , 2023 , 36 ( 3 ): 557 - 570 .
XU Y , HUANG W T , GUO Z D , et al . Spatio-temporal variation of vegetation net ecosystem productivity and relative contribution of driving forces in southwest China from 2000 to 2020 [J]. Research of Environmental Sciences , 2023 , 36 ( 3 ): 557 - 570 .
LI Z , CHEN Y N , ZHANG Q F , et al . Spatial patterns of vegetation carbon sinks and sources under water constraint in Central Asia [J]. Journal of Hydrology , 2020 , 590 : e125355 .
王江涛 , 杨永崇 , 杨梅焕 . 基于地理探测器的黄土高原NPP时空变化及驱动力研究 [J]. 西安理工大学学报 , 2023 , 39 ( 1 ): 12 - 20 .
WANG J T , YANG Y C , YANG M H . Spatial and temporal variation and driving forces of NPP on the Loess Plateau based on Geodetector [J]. Journal of Xi´an University of Technology , 2023 , 39 ( 1 ): 12 - 20 .
HUANG Y T , WANG F , ZHENG L J , et al . Corrigendum: Changes and net ecosystem productivity of terrestrial ecosystems and their influencing factors in China from 2000 to 2019 [J]. Frontiers in Plant Science , 2023 , 14 : e259137 .
白萌 , 莫淑红 , 莫兴国 , 等 . 退耕还林背景下黄土高原蒸散量时空演变特征及归因 [J]. 生态学报 , 2023 , 43 ( 20 ): 8344 - 8358 .
BAI M , MO S H , MO X G , et al . Spatio-temporal variation of evapotranspiration and its attribution over the Loess Plateau since the implementation of the Grain for Green Project [J]. Acta Ecologica Sinica , 2023 , 43 ( 20 ): 8344 - 8358 .
HE H L , WANG S Q , ZHANG L , et al . Altered trends in carbon uptake in China´s terrestrial ecosystems under the enhanced summer monsoon and warming hiatus [J]. National Science Review , 2019 , 6 ( 3 ): 505 - 514 .
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