[en] Litterfall load is crucial in maintaining ecosystem health, controlling wildfires, and estimating carbon stock in arid regions. However, there is a lack of spatiotemporal analysis of litterfall in arid riparian forests. This study aims to estimate Litterfall load using a BP neural network based on vegetation indices from Landsat 5 and 8 satellite images, litterfall inventory data, slope, and distance to major river tributaries. It also aims to analyze the spatiotemporal distribution pattern of litter in the research area by estimating and analyzing the spatiotemporal pattern of litterfall along the desert riparian forests of the lower Qarqan and Tarim Rivers from 2001 to 2021. The results show that the initiation of the ecological water transfer project has facilitated the decomposition of litterfall, leading to an initial decline. Subsequently, the vegetation gradually recovered, leading to an increase in leaf litter input. Since 2001, litterfall initially decreased until reaching its lowest value of 4.39 × 109 kg in 2005, followed by a subsequent increase, reaching its highest value of 12.5 × 109 kg in 2021. The study concludes that ecological water conveyance promotes both the decomposition and increase of litterfall. Initially, it accelerates litterfall decomposition, while later stages foster an increase in Litterfall load. Meanwhile, due to the ecological water transfer project and the higher vegetation cover along the Tarim River compared to the Qarqan River, the Tarim River basin experiences higher average Litterfall load and variation.
Disciplines :
Agriculture & agronomy
Author, co-author :
Xu, Junyu; College of Ecology and Environment, Xinjiang University, Urumqi, 830046, Xinjiang, China ; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China ; Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, 830011, China
Eziz, Anwar; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China. anwareziz@ms.xjb.ac.cn ; Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, 830011, China. anwareziz@ms.xjb.ac.cn
Kurban, Alishir; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China ; Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, 830011, China
Halik, Ümüt; College of Ecology and Environment, Xinjiang University, Urumqi, 830046, Xinjiang, China. halik@xju.edu.cn
Shi, Zhiwen; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China
Ullah, Saif; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China ; Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, 830011, China
Fidelis, Gift Donu; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China ; Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, 830011, China
Ma, Yingdong; College of Ecology and Environment, Xinjiang University, Urumqi, 830046, Xinjiang, China
Kibir, Ziwargul; College of Ecology and Environment, Xinjiang University, Urumqi, 830046, Xinjiang, China ; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China
Ahmed, Toqeer; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China ; Centre for Climate Research and Development (CCRD), COMSATS University Islamabad, Tarlai Kalan, Park Road, Islamabad, 45550, Pakistan
Van de Voorde, Tim; Department of Geography, Ghent University, Krijgslaan 281 S8, 9000, Ghent, Belgium
Hujashim, Adil; Forestry and Grassland Bureau of Ruoqiang County, Ruoqiang, 841800, China
Azadi, Hossein ; Université de Liège - ULiège > TERRA Research Centre > Modélisation et développement ; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China ; Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, 830011, China ; Department of Geography, Ghent University, Krijgslaan 281 S8, 9000, Ghent, Belgium
NSCF - National Natural Science Foundation of China Chinese Academy of Sciences
Funding text :
The authors extend their sincere gratitude to their esteemed colleagues, Nuria Abduwayit and Abduaini Maimaiti, for their invaluable assistance during the fieldwork. Furthermore, the authors wish to express profound appreciation to the personnel at the Xinjiang Institute of Ecological Geography for their unwavering technical support and selfless dedication to the collection of field data for this project. Additionally, the authors extend their heartfelt thanks to my colleagues for them invaluable assistance in enhancing the language of the manuscript. Finally, the authors would like to convey their gratitude to the staff of the Forestry Department in Qiemo (Charchen) and Ruoqiang (Charqiliq)\u00A0for their selfless contributions during the sample collection phase of this research endeavor.This work was jointly funded by the National Natural Science Foundation of China (Grant No. 32071655; 32260285), Tianchi talent (young scientist) fund (E335030101), Chinese Academy of Sciences President\u2019s International Fellowship Initiative (PIFI, 2021VCA0004, 2024PVA0101, 2024PVB0064). and the Project for Cultivating High-Level Talent of Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences (Grant No. E450030101).
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