Spatial–Temporal Variation Characteristics and Driving Factors of Net Primary Production in the Yellow River Basin over Multiple Time Scales
-
Published:2023-11-07
Issue:22
Volume:15
Page:5273
-
ISSN:2072-4292
-
Container-title:Remote Sensing
-
language:en
-
Short-container-title:Remote Sensing
Author:
Lin Ziqi1, Liu Yangyang1, Wen Zhongming12ORCID, Chen Xu3, Han Peidong1, Zheng Cheng1, Yao Hongbin1, Wang Zijun4, Shi Haijing2
Affiliation:
1. College of Grassland Agriculture, Northwest A&F University, Yangling, Xianyang 712100, China 2. State Key Laboratory of Soil Erosion and Dryland Farming on Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Xianyang 712100, China 3. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Xianyang 712100, China 4. College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Xianyang 712100, China
Abstract
Vegetation net primary productivity (NPP) serves as a crucial and intuitive indicator for assessing ecosystem health. However, the nonlinear dynamics and influencing factors operating at various time scales are not yet fully understood. Here, the ensemble empirical mode decomposition (EEMD) method was used to analyze the spatiotemporal patterns of NPP and its association with hydrothermal factors and anthropogenic activities across different temporal scales for the Yellow River Basin (YRB) from 2000 to 2020. The results indicate that: (1) the annual average NPP was 236.37 g C/m2 in the YRB and increased at rates of 4.64 g C/m2/a1 (R2 = 0.86, p < 0.01) during 2000 to 2020. Spatially, nonlinear analysis indicates that 72.77% of the study area exhibits a predominantly increasing trend in NPP, while 25.17% exhibits a reversing trend. (2) On a 3-year time scale, warming has resulted in an increase in NPP in the majority of areas of the study area (69.49%). As the time scale widens, the response of vegetation to climate change becomes more prominent; especially under the long-term trend, the percentage areas of the correlation between vegetation and precipitation and temperature increased with significance, reaching 48.21% and 11.57%, respectively. (3) Through comprehensive time analysis and multivariate regression analysis, it was confirmed that both human activities and climate factors had comparable impacts on vegetation growth. Among different vegetation types, climate was still the main factor affecting grassland NPP, and only 15.74% of grassland was affected by human activities. For shrubland, forest, and farmland, human activity was a dominating factor for vegetation NPP change. There are still few studies on vegetation change using nonlinear methods in the Yellow River Basin, and most studies have not considered the effect of time scale on vegetation evolution. The findings highlight the significance of multi-time scale analysis in understanding the vegetation dynamics and providing scientific guidance for future vegetation restoration and conservation efforts.
Subject
General Earth and Planetary Sciences
Reference66 articles.
1. IPCC, 2021: Climate change 2021-the physical science basis;Legg;Interaction,2021 2. Chang, J., Liu, Q., Wang, S., and Huang, C. (2022). Vegetation Dynamics and Their Influencing Factors in China from 1998 to 2019. Remote Sens., 14. 3. Jian, S.Q., Zhang, Q.K., and Wang, H.L. (2022). Spatial-Temporal Trends in and Attribution Analysis of Vegetation Change in the Yellow River Basin, China. Remote Sens., 14. 4. Zhou, X., Peng, B., Zhou, Y., Yu, F., and Wang, X.-C. (2022). Quantifying the Influence of Climate Change and Anthropogenic Activities on the Net Primary Productivity of China’s Grasslands. Remote Sens., 14. 5. Relationship between net primary production and climate change in different vegetation zones based on EEMD detrending—A case study of Northwest China;Liu;Ecol. Indic.,2021
|
|