Abstract

Nitrogen (N) is a vital macronutrient in plant growth and development that plays a crucial role in the regulation of numerous physiological processes. The Tibetan Plateau is among the most species-diverse vegetation zones in the world, and is sensitive to climate change; however, research on vegetation N in the region remains limited. This study used field grid-sampling of 2040 plant communities to investigate the spatial variation and driving factors of vegetation N on the Tibetan Plateau. The results yielded an average N content, density and storage in vegetation of 8.48 mg g−1, 27.02 g m−2, and 29.84Tg, respectively. The ratio-based optimal partitioning hypothesis appears to be more suitable than the isometric allocation hypothesis to explain variation in vegetation N on the Tibetan Plateau. Variation in vegetation N density, was influenced by several environmental factors of which the most significant was radiation. Based on these results, a Random Forest model was used to predict a N density distribution map at 1 km resolution, achieving an accuracy (R2) of 0.72 (aboveground N density), 0.61 (belowground N density), and 0.69 (total vegetation N density). Trends for high densities were predicted in the southeast and low densities in the northwest of the region. Our findings and maps could be used to provide key N cycle parameters, contributing to future remote sensing, radar analyses, modeling and ecological management.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.