Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments
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 distr...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Plant Stress |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667064X25000557 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849774380235620352 |
|---|---|
| author | Weiyi Zhou Jing Zhang Benfeng Yin Lan Peng Lingyue Wang Xiaobing Zhou Yaoli Zhou Yanfeng Di Hongwei Zheng Yuanming Zhang |
| author_facet | Weiyi Zhou Jing Zhang Benfeng Yin Lan Peng Lingyue Wang Xiaobing Zhou Yaoli Zhou Yanfeng Di Hongwei Zheng Yuanming Zhang |
| author_sort | Weiyi Zhou |
| collection | DOAJ |
| description | 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 R² 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. |
| format | Article |
| id | doaj-art-49decbd78a5c48959c0efea6830c2247 |
| institution | DOAJ |
| issn | 2667-064X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Plant Stress |
| spelling | doaj-art-49decbd78a5c48959c0efea6830c22472025-08-20T03:01:42ZengElsevierPlant Stress2667-064X2025-03-011510079010.1016/j.stress.2025.100790Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environmentsWeiyi Zhou0Jing Zhang1Benfeng Yin2Lan Peng3Lingyue Wang4Xiaobing Zhou5Yaoli Zhou6Yanfeng Di7Hongwei Zheng8Yuanming Zhang9National Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, ChinaNational Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, ChinaNational Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, ChinaNational Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; College of Resource and Environment Sciences, Xinjiang University, Urumqi 830017, ChinaNational Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, ChinaNational Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, ChinaGoldsmiths University of London, London, United KingdomNational Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, ChinaNational Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, China; Corresponding authors at: National Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.National Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing, China; Corresponding authors at: National Key Laboratory of Ecological Security and Sustainable Development in Arid Region, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.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 R² 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.http://www.sciencedirect.com/science/article/pii/S2667064X25000557Desert shrubEnsemble machine learningSpatial patternEnvironmental drivers |
| spellingShingle | Weiyi Zhou Jing Zhang Benfeng Yin Lan Peng Lingyue Wang Xiaobing Zhou Yaoli Zhou Yanfeng Di Hongwei Zheng Yuanming Zhang Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments Plant Stress Desert shrub Ensemble machine learning Spatial pattern Environmental drivers |
| title | Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments |
| title_full | Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments |
| title_fullStr | Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments |
| title_full_unstemmed | Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments |
| title_short | Mapping spatial heterogeneity of non-structural carbohydrates in Haloxylon ammodendron using remote sensing in extreme desert environments |
| title_sort | mapping spatial heterogeneity of non structural carbohydrates in haloxylon ammodendron using remote sensing in extreme desert environments |
| topic | Desert shrub Ensemble machine learning Spatial pattern Environmental drivers |
| url | http://www.sciencedirect.com/science/article/pii/S2667064X25000557 |
| work_keys_str_mv | AT weiyizhou mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT jingzhang mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT benfengyin mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT lanpeng mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT lingyuewang mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT xiaobingzhou mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT yaolizhou mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT yanfengdi mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT hongweizheng mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments AT yuanmingzhang mappingspatialheterogeneityofnonstructuralcarbohydratesinhaloxylonammodendronusingremotesensinginextremedesertenvironments |