The long-term series of geographic data and remote sensing data contain noise and perio-dic fluctuation. We used the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) to decompose the data of the normalized difference vegetation index (NDVI), precipitation, and temperature from 1982 to 2015 on per-pixels in the Loess Pla-teau to obtain residuals. Using the residual with less noise and periodic fluctuations, we examined the changes of NDVI and the relationship between NDVI and climatic factors. The results showed that the spatial change trend of NDVI was mainly increasing from 1982 to 2015 in the Loess Plateau. The significance of the change trend of residual NDVI (95.9%) was greater than the original NDVI (72.3%), with spatial variations. Temperature and precipitation could largely explain the changes in vegetation coverage. The proportions of areas with extremely significant positive and negative correlations between temperature and NDVI on the Loess Plateau were 83.7% and 13.9%, respectively, while that between precipitation and NDVI were 54.4% and 37.2%, respectively. There were obvious spatial variations in the responses of vegetation to climate change on the Loess Plateau. Different climatic factors had different effects on different types of vegetation. In general, temperature had stronger correlation with different vegetation than precipitation. Therefore, temperature was the main driving factor for the changes of vegetation cover in the Loess Plateau.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.13287/j.1001-9332.202106.011 | DOI Listing |
Front Plant Sci
January 2025
State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China.
The natural grassland in China is facing increasingly serious degradation. L., as an important native alpine grass, is widely used in the restoration and improvement of natural grassland.
View Article and Find Full Text PDFFront Neurol
January 2025
Graduate Development Office, Harbin Sport University, Harbin, China.
Objective: This study investigates the association between sedentary behavior and sleep quality among postmenopausal women residing in China's plateau regions. Particular attention is given to moderating effects of age, body mass index (BMI), and sleep environment. This study aims to identify modifiable risk factors influencing sleep quality in this high-altitude population.
View Article and Find Full Text PDFPest Manag Sci
January 2025
Key Laboratory of Plant Protection Resources and Pest Management of Ministry of Education, Key Laboratory of Integrated Pest Management on the Loess Plateau of Ministry of Agriculture and Rural Affairs, College of Plant Protection, Northwest A&F University, Yangling, China.
Background: In the realm of plant diseases, those caused by fungi and oomycetes are particularly challenging to manage, resulting in significant economic losses. There exist diverse active substances in natural products and developing them into fungicides holds great significance. At the initial phase of our research, we discovered that Syringa pinnatifolia extract demonstrates broad-spectrum inhibitory activity against phytopathogenic fungi.
View Article and Find Full Text PDFSci Rep
January 2025
Inner Mongolia Agricultural University, No. 275, XinJian East Street, Hohhot, 010019, China.
To address the problems of planting density and low soil nutrient content in maize cultivation and production in western Inner Mongolia. This study aims to elucidate the regulatory mechanism by which soil fertility augmentation affects maize yield formation under a variety of planting densities. In this study, nine soil fertility conditions were established by deep tillage, no-tillage and in situ straw return.
View Article and Find Full Text PDFGlob Chang Biol
January 2025
Department of Renewable Resources, University of Alberta, Edmonton, Canada.
Soil microorganisms transform plant-derived C (carbon) into particulate organic C (POC) and mineral-associated C (MAOC) pools. While microbial carbon use efficiency (CUE) is widely recognized in current biogeochemical models as a key predictor of soil organic carbon (SOC) storage, large-scale empirical evidence is limited. In this study, we proposed and experimentally tested two predictors of POC and MAOC pool formation: microbial necromass (using amino sugars as a proxy) and CUE (by O-HO approach).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!