Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments
• Collected 564 samples of non-structural carbohydrate (NSC) from 81 subplots across multiple deserts spanning 75°E to 115°E. • Constructed a novel SAFESCAN analysis platform by integrating remote sensing and ensemble learning techniques into plant ecology field. • Revealed the macro-scale species distribution patterns and local individual distribution patterns of the dominant desert shrub Haloxylon ammodendron. • Generated high-precision NSC content maps, revealing the carbon spatial patterns of desert shrubs. • Provided clear insights into desert shrubs adaptation to environmental changes, aiding desertification management and plant conservation strategies. Arid regions occupy 40% of the Earth's land surface and play a significant role in the global carbon budget. Dominant desert shrub Haloxylon ammodendron , which thrives under extreme climatic conditions, contributes substantially to the stability of desert ecosystems. However, its species distribution patterns and carbon spatial dynamics in deserts remain unknown. Based on our newly development “Satellite-Airborne-Field” Ensemble learning platform for Systematic plant CArbohydrate estimation in Nature (SAFESCAN), we accurately estimated the spatial patterns of non-structural carbohydrate (NSC) content in leaves (LNSC) and branches (BNSC), with R ² values of 0.83 and 0.72, respectively. This analysis incorporated 51 environmental variables and 564 samples collected from 81 subplots across multiple temperate deserts between 75°E and 115°E. The results identified the northern Gurbantunggut Desert and western edges of the Taklamakan Desert in Xinjiang as primary distribution areas for H. ammodendron , with northern Inner Mongolia and northern Qinghai also suitable for its survival. LNSC showed a west-to-east decreasing trend, while BNSC exhibited an increasing trend. The SAFESCAN platform demonstrated strong predictive capacity for shrub-dominated arid regions but may overestimate the relationship between NSC content and certain environmental variables. By integrating macro-scale species distribution patterns and local individual patterns of H. ammodendron , SAFESCAN provides NSC content maps, laying the foundation for future efforts in desert plant conservation and cultivation.
Authors
- Yuankai Zhou (ORCID: https://orcid.org/0000-0001-7909-5011)
- Lan Peng (ORCID: https://orcid.org/0000-0003-3849-1426)
- Benfeng Yin (ORCID: https://orcid.org/0000-0002-5992-8861)
- Yanfeng Di (ORCID: https://orcid.org/0000-0002-3874-2355)
- Jing Zhang (ORCID: https://orcid.org/0000-0002-5009-7707)
- Yuanming Zhang (ORCID: https://orcid.org/0000-0002-0100-0219)
- Hongwei Zheng (ORCID: https://orcid.org/0000-0001-5366-5936)
- Lingyue Wang (ORCID: https://orcid.org/0000-0002-7616-5042)
- Xiaobing Zhou (ORCID: https://orcid.org/0009-0000-6599-3822)
- Weiyi Zhou
Institutions
- Institute of Ecology and Geography (MD)
- Xinjiang Institute of Ecology and Geography (CN)
- University of Chinese Academy of Sciences (CN)
- Goldsmiths University of London (GB)
- Xinjiang University (CN)
Publication Details
- Journal
- Plant Stress
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1016/j.stress.2025.100790
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00