A five‑dimension paradigm for grassland LDN: XGBoost–SHAP evidence on thresholds and governance in the Ebinur Lake Basin

A five‑dimension paradigm for grassland LDN: XGBoost–SHAP evidence on thresholds and governance in the Ebinur Lake Basin | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 27 August 2025 V1 Latest version Share on A five‑dimension paradigm for grassland LDN: XGBoost–SHAP evidence on thresholds and governance in the Ebinur Lake Basin Authors : Denghui Xu , Jiani Li , Caifang Xu , Tongsheng Fan , Yao Wang , and Zhonglin Xu 0000-0003-0524-7662 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175628008.82433638/v1 131 views 82 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract To overcome the limited ability of the UNCCD “three‑indicator” set to detect ecosystem‑service change and management thresholds in arid grasslands, we develop an explicit–implicit–supply, five‑dimension framework and apply it to the Ebinur Lake Basin (2000–2020). Explicit shifts are mapped with a LULC transition atlas (code = A × 10 + B) and a cumulative trend index (Dex). Pixel‑wise linear slopes of NPP, NEP, SC and GS are tested with Mann–Kendall; an “OOAO + LfL” rule yields the LDN status. A Bayesian‑optimised XGBoost classifier, explained with SHAP, quantifies the marginal and interactive impacts of 15 natural and anthropogenic factors. Grassland change is dominated by degradation—69.42 % (20160.62 km 2 ) versus 30.57 % recovery (8878.85 km 2 ) and 0.01 % stability (2.79 km 2 ); explicit net loss totals 1786.77 km 2 and the centroid migrates ~11.1 km. Implicit functions improve overall: NPP rises across 77.58 % (22529.90 km 2 ) and NEP across 76.35 % (22174.16 km 2 ); SC is bipolar (45.40 % gain, 42.57 % loss); GS increases over 64.48 %. In improving pixels, 78.7 % show synchronous enhancement of all four implicit metrics, whereas 56.3 % of degraded pixels exhibit decline in only one metric; SHAP ranks human‑activity intensity (HAI = 0.706) above precipitation (0.438), elevation (0.297), temperature (0.243) and road density (0.217). Optimal windows emerge at 260–280 mm rainfall, 2000–2500 m elevation and HAI 2000–4000, while road density > 1 km km -2 exerts growing negative effects. The coupled control of human pressure and hydro- topography governs degradation–recovery patterns. The five‑dimension index set, combined with explainable machine learning, markedly enhances the accuracy and actionability of LDN assessments, informing avoid–reduce–reverse zoning in China’s Three‑North shelterbelt and grazing- to- grass initiatives. Supplementary Material File (manuscript_0826.docx) Download 6.59 MB Information & Authors Information Version history V1 Version 1 27 August 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords ebinur lake basin grassland land degradation neutrality threshold effect xgboost Authors Affiliations Denghui Xu Xinjiang University College of Ecology and Environment View all articles by this author Jiani Li Xinjiang University College of Ecology and Environment View all articles by this author Caifang Xu Xinjiang University College of Ecology and Environment View all articles by this author Tongsheng Fan Nanning Normal University View all articles by this author Yao Wang Xinjiang University College of Ecology and Environment View all articles by this author Zhonglin Xu 0000-0003-0524-7662 [email protected] Xinjiang University College of Ecology and Environment View all articles by this author Metrics & Citations Metrics Article Usage 131 views 82 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Denghui Xu, Jiani Li, Caifang Xu, et al. A five‑dimension paradigm for grassland LDN: XGBoost–SHAP evidence on thresholds and governance in the Ebinur Lake Basin. Authorea . 27 August 2025. DOI: https://doi.org/10.22541/au.175628008.82433638/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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