Spatio-temporal analysis of litterfall load in the lower reaches of Qarqan and Tarim rivers using BP neural networks
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| Title: | Spatio-temporal analysis of litterfall load in the lower reaches of Qarqan and Tarim rivers using BP neural networks |
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| Authors: | Xu, Junyu, Eziz, Anwar, Kurban, Alishir, Halik, Ümüt, Shi, Zhiwen, Ullah, Saif, Fidelis, Gift Donu, Ma, Yingdong, Kibir, Ziwargul, Ahmed, Toqeer, Van de Voorde, Tim, Hujashim, Adil, Azadi, Hossein |
| Contributors: | NSCF - National Natural Science Foundation of China, Chinese Academy of Sciences |
| Source: | Sci Rep Scientific Reports, Vol 15, Iss 1, Pp 1-19 (2025) SCIENTIFIC REPORTS |
| Publisher Information: | Springer Science and Business Media LLC, 2025. |
| Publication Year: | 2025 |
| Subject Terms: | DYNAMICS, DECOMPOSITION, China, Science, BP neural network, Forests, FUEL, CHINA, Article, Spatio-Temporal Analysis, Rivers, Agriculture & agronomie, SURFACE-WATER, INDEX, Ecosystem, Multidisciplinary, Desert riparian forest, Litterfall load, FOREST, Agriculture & agronomy, Life sciences, Arid region, Plant Leaves, Earth and Environmental Sciences, Sciences du vivant, Medicine, VEGETATION, Neural Networks, Computer, Environmental Monitoring/methods, Environmental Monitoring |
| Description: | 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. |
| Document Type: | Article Other literature type |
| File Description: | application/pdf |
| Language: | English |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/s41598-024-82435-2 |
| Access URL: | https://pubmed.ncbi.nlm.nih.gov/39774011 https://doaj.org/article/3cad65f8518745648f88bd3d649196d5 http://hdl.handle.net/1854/LU-01JX303J3REQDT8CCA3EXWYDEC https://biblio.ugent.be/publication/01JX303J3REQDT8CCA3EXWYDEC/file/01JX30VPWNGWEJFVG43MZH74ZW https://biblio.ugent.be/publication/01JX303J3REQDT8CCA3EXWYDEC http://doi.org/10.1038/s41598-024-82435-2 |
| Rights: | CC BY NC ND |
| Accession Number: | edsair.doi.dedup.....462d18e053f4e12a878a3361d8788a06 |
| Database: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstract: | 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. |
|---|---|
| ISSN: | 20452322 |
| DOI: | 10.1038/s41598-024-82435-2 |