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The elevation gradient has long been known to be vital in shaping the structure and function of terrestrial ecosystems, but little is known about the elevation-dependent pattern of net CO uptake, denoted by net ecosystem productivity (NEP). Here, by analyzing data from 203 eddy covariance sites across China, we report a negative linear elevation-dependent pattern of NEP, collectively shaped by varying hydrothermal factors, nutrient supply, and ecosystem types. Furthermore, the NEP shows a higher temperature sensitivity in high-elevation environments (3000-5000 m) compared with the lower-elevation environments (<3000 m). Model ensemble and satellite-based observations consistently reveal more rapid relative changes in NEP in high-elevation environments during the last four decades. Machine learning also predicts a stronger relative increase in high-elevation environments, whereas less change is expected at lower elevations. We therefore conclude a varying elevation-dependent pattern of the NEP of terrestrial ecosystems in China, although there is significant uncertainty involved.
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http://dx.doi.org/10.1038/s41467-024-46930-4 | DOI Listing |
J Environ Manage
August 2025
College of Geographical Sciences, Faculty of Geographical Science and Engineering, Henan University, Zhengzhou, 450046, China.
This study analyzed daily temperature data from 114 meteorological stations in the Qinling-Daba Mountains from 1980 to 2017, focusing on core zones (CE I ≥ 2274 m, CE II 1321-2274 m) and peripheral zones (PE I 668-1321 m, PE II < 668 m). Using 15 extreme temperature indices computed with RClimDex, we assessed the spatiotemporal patterns, trends, and response to climate warming of extreme temperature events across different elevation zones. The Mann-Kendall test and Sen's slope estimator were employed to quantify trends, and the driving mechanisms of extreme temperature indices in different altitudinal zones were explored through Random Forest models and Pearson correlation analysis.
View Article and Find Full Text PDFPeerJ
July 2025
College of Life Science, Chian West Normal University, Nanchong, China.
Background: Natural regeneration is pivotal for sustaining evolutionary processes in plant species. Identifying determinants that shape recruitment dynamics could elucidate key factors governing this critical biological process. However, the relationship between environmental variables and recruitment patterns in remains uninvestigated, despite its dual significance as a species endemic to China and a National Grade II Protected Plant.
View Article and Find Full Text PDFPhysiol Plant
July 2025
Department of Biotechnology, School of Biosciences and Biotechnology, BGSB, University, Rajouri, India.
Understanding the molecular basis of how species adapt to varying elevations can advance our knowledge regarding forecasting and regulating the consequences of climate change on plants. Here, we investigate the variation in gene expression patterns of Rhododendron anthopogon D.Don along an elevation gradient (3200-3900 m) in Kashmir Himalaya, India, based on comparative transcriptomics.
View Article and Find Full Text PDFJ Environ Manage
September 2025
College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210024, China.
While vertical hydrological connectivity (VHC) plays a critical role in material exchange and ecosystem functionality of intertidal wetlands, it remains poorly understood compared to horizontal connectivity. This knowledge gap hinders the development of effective restoration strategies for degraded coastal wetlands. Here, we used isotopic tracers (δH and δO) to characterize VHC patterns in an intertidal wetland of the Yellow River Delta, China.
View Article and Find Full Text PDFFront Microbiol
July 2025
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, China.
Introduction: Alpine meadows provide a critical natural laboratory for investigating interactions between ecosystem degradation and biogeochemical processes across elevational gradients.
Methods: This study examines how degradation states and elevation (3,700 m vs. 4,300 m) influence soil fungal community composition, diversity, and network architecture in Qinghai-Tibetan Plateau grasslands.