Xin Zhang, Shihang Zhang, Hongjin Chen, Jian-rong FAN
{"title":"青藏高原植被和气候对冻土碳的控制","authors":"Xin Zhang, Shihang Zhang, Hongjin Chen, Jian-rong FAN","doi":"10.1007/s12665-025-12325-x","DOIUrl":null,"url":null,"abstract":"<div><p>Soil organic carbon (SOC) in the active layer (0–2 m) of the Tibetan Plateau (TP) permafrost region is sensitive to climate change, with significant implications for the global carbon cycle. Environmental factors—including parent material, climate, vegetation, topography, soil, and human activities—inevitably drive SOC variations. However, vegetation and climate are likely the two most influential factors impacting SOC variations. To test this hypothesis, we conducted experiments using 31 environmental variables combined with the recursive feature elimination (RFE) algorithm. These experiments showed that RFE retained all vegetation variables [Land cover types (LCT), normalized difference vegetation index (NDVI), leaf area index (LAI), and gross primary productivity (GPP)] as well as two climate variables [Moisture index (MI) and drought index (DI)], supporting our hypothesis. We then analyzed the relationship between SOC and the retained vegetation and climate variables using random forest (RF), Shapley additive explanations (SHAP), and GeoDetector models to quantify the independent and interactive drivers of SOC distribution and to identify the optimal conditions for SOC accumulation. The RF model explained 68% and 42% of the spatial variability in SOC at depths of 0–1 m and 1–2 m, respectively, with SOC stocks higher in the southeast and lower in the northwest. Additionally, SOC stock at 0–1 m was significantly higher (<i>p</i> < 0.05) than at 1–2 m in alpine meadows, alpine wet meadows, and swamp meadows. Conversely, SOC stock in alpine deserts, steppe meadows, and barren land did not differ significantly between the two depths (<i>p</i> > 0.05). Spearman correlation coefficients results indicated that NDVI, LAI, GPP, and MI had highly significant positive correlations with SOC (<i>p</i> < 0.01), whereas DI had a highly significant negative correlation with SOC (<i>p</i> < 0.01). SHAP analysis revealed environmental thresholds for SOC variations, with notable shifts at NDVI (0.40), LAI (7), GPP (250 g C m⁻² year⁻¹), MI (0.40), and DI (0.50). The spatial distribution of these thresholds aligns with the 400 mm equivalent precipitation line. Additionally, GeoDetector results emphasized that interactions between climate and vegetation factors enhance the explanatory power of individual variables on SOC variations. The swamp meadow type, with an NDVI range of 0.73–0.84, LAI range of 11.06–15.94, and MI range of 0.46–0.56, was identified as the most favorable environment for SOC accumulation. These findings are essential for balancing vegetation and climate conditions to sustain SOC levels and mitigate climate change-driven carbon release.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Permafrost carbon controlled by vegetation and climate in the Tibetan Plateau\",\"authors\":\"Xin Zhang, Shihang Zhang, Hongjin Chen, Jian-rong FAN\",\"doi\":\"10.1007/s12665-025-12325-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Soil organic carbon (SOC) in the active layer (0–2 m) of the Tibetan Plateau (TP) permafrost region is sensitive to climate change, with significant implications for the global carbon cycle. Environmental factors—including parent material, climate, vegetation, topography, soil, and human activities—inevitably drive SOC variations. However, vegetation and climate are likely the two most influential factors impacting SOC variations. To test this hypothesis, we conducted experiments using 31 environmental variables combined with the recursive feature elimination (RFE) algorithm. These experiments showed that RFE retained all vegetation variables [Land cover types (LCT), normalized difference vegetation index (NDVI), leaf area index (LAI), and gross primary productivity (GPP)] as well as two climate variables [Moisture index (MI) and drought index (DI)], supporting our hypothesis. We then analyzed the relationship between SOC and the retained vegetation and climate variables using random forest (RF), Shapley additive explanations (SHAP), and GeoDetector models to quantify the independent and interactive drivers of SOC distribution and to identify the optimal conditions for SOC accumulation. The RF model explained 68% and 42% of the spatial variability in SOC at depths of 0–1 m and 1–2 m, respectively, with SOC stocks higher in the southeast and lower in the northwest. Additionally, SOC stock at 0–1 m was significantly higher (<i>p</i> < 0.05) than at 1–2 m in alpine meadows, alpine wet meadows, and swamp meadows. Conversely, SOC stock in alpine deserts, steppe meadows, and barren land did not differ significantly between the two depths (<i>p</i> > 0.05). Spearman correlation coefficients results indicated that NDVI, LAI, GPP, and MI had highly significant positive correlations with SOC (<i>p</i> < 0.01), whereas DI had a highly significant negative correlation with SOC (<i>p</i> < 0.01). SHAP analysis revealed environmental thresholds for SOC variations, with notable shifts at NDVI (0.40), LAI (7), GPP (250 g C m⁻² year⁻¹), MI (0.40), and DI (0.50). The spatial distribution of these thresholds aligns with the 400 mm equivalent precipitation line. Additionally, GeoDetector results emphasized that interactions between climate and vegetation factors enhance the explanatory power of individual variables on SOC variations. The swamp meadow type, with an NDVI range of 0.73–0.84, LAI range of 11.06–15.94, and MI range of 0.46–0.56, was identified as the most favorable environment for SOC accumulation. These findings are essential for balancing vegetation and climate conditions to sustain SOC levels and mitigate climate change-driven carbon release.</p></div>\",\"PeriodicalId\":542,\"journal\":{\"name\":\"Environmental Earth Sciences\",\"volume\":\"84 12\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Earth Sciences\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12665-025-12325-x\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Earth Sciences","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s12665-025-12325-x","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
青藏高原多年冻土区活动层(0 ~ 2 m)土壤有机碳(SOC)对气候变化敏感,对全球碳循环具有重要影响。环境因素——包括母质、气候、植被、地形、土壤和人类活动——不可避免地驱动着有机碳的变化。然而,植被和气候可能是影响有机碳变化的两个最重要因素。为了验证这一假设,我们使用31个环境变量结合递归特征消除(RFE)算法进行了实验。实验结果表明,RFE保留了所有植被变量[土地覆盖类型(LCT)、归一化植被指数(NDVI)、叶面积指数(LAI)和总初级生产力(GPP)]以及两个气候变量[湿度指数(MI)和干旱指数(DI)],支持了我们的假设。利用随机森林(RF)、Shapley加性解释(SHAP)和GeoDetector模型分析了土壤有机碳与保留植被和气候变量之间的关系,量化了土壤有机碳分布的独立驱动因素和交互驱动因素,并确定了土壤有机碳积累的最佳条件。RF模型分别解释了0 ~ 1 m和1 ~ 2 m土壤有机碳空间变异的68%和42%,土壤有机碳储量呈现东南高西北低的趋势。高寒草甸、高寒湿草甸和沼泽草甸0 ~ 1 m土壤有机碳储量显著高于1 ~ 2 m (p < 0.05)。相反,高寒荒漠、草原草甸和荒地的SOC储量在两个深度之间没有显著差异(p > 0.05)。Spearman相关系数结果显示,NDVI、LAI、GPP和MI与SOC呈极显著正相关(p < 0.01),而DI与SOC呈极显著负相关(p < 0.01)。SHAP分析揭示了SOC变化的环境阈值,在NDVI (0.40), LAI (7), GPP (250 g C m - 2年毒血症),MI(0.40)和DI(0.50)上有显著的变化。这些阈值的空间分布与400mm等效降水量线一致。此外,GeoDetector研究结果强调,气候与植被因子之间的相互作用增强了个体变量对土壤有机碳变化的解释能力。沼泽草甸类型的NDVI范围为0.73 ~ 0.84,LAI范围为11.06 ~ 15.94,MI范围为0.46 ~ 0.56,是最有利于有机碳积累的环境。这些发现对于平衡植被和气候条件以维持有机碳水平和减轻气候变化驱动的碳释放至关重要。
Permafrost carbon controlled by vegetation and climate in the Tibetan Plateau
Soil organic carbon (SOC) in the active layer (0–2 m) of the Tibetan Plateau (TP) permafrost region is sensitive to climate change, with significant implications for the global carbon cycle. Environmental factors—including parent material, climate, vegetation, topography, soil, and human activities—inevitably drive SOC variations. However, vegetation and climate are likely the two most influential factors impacting SOC variations. To test this hypothesis, we conducted experiments using 31 environmental variables combined with the recursive feature elimination (RFE) algorithm. These experiments showed that RFE retained all vegetation variables [Land cover types (LCT), normalized difference vegetation index (NDVI), leaf area index (LAI), and gross primary productivity (GPP)] as well as two climate variables [Moisture index (MI) and drought index (DI)], supporting our hypothesis. We then analyzed the relationship between SOC and the retained vegetation and climate variables using random forest (RF), Shapley additive explanations (SHAP), and GeoDetector models to quantify the independent and interactive drivers of SOC distribution and to identify the optimal conditions for SOC accumulation. The RF model explained 68% and 42% of the spatial variability in SOC at depths of 0–1 m and 1–2 m, respectively, with SOC stocks higher in the southeast and lower in the northwest. Additionally, SOC stock at 0–1 m was significantly higher (p < 0.05) than at 1–2 m in alpine meadows, alpine wet meadows, and swamp meadows. Conversely, SOC stock in alpine deserts, steppe meadows, and barren land did not differ significantly between the two depths (p > 0.05). Spearman correlation coefficients results indicated that NDVI, LAI, GPP, and MI had highly significant positive correlations with SOC (p < 0.01), whereas DI had a highly significant negative correlation with SOC (p < 0.01). SHAP analysis revealed environmental thresholds for SOC variations, with notable shifts at NDVI (0.40), LAI (7), GPP (250 g C m⁻² year⁻¹), MI (0.40), and DI (0.50). The spatial distribution of these thresholds aligns with the 400 mm equivalent precipitation line. Additionally, GeoDetector results emphasized that interactions between climate and vegetation factors enhance the explanatory power of individual variables on SOC variations. The swamp meadow type, with an NDVI range of 0.73–0.84, LAI range of 11.06–15.94, and MI range of 0.46–0.56, was identified as the most favorable environment for SOC accumulation. These findings are essential for balancing vegetation and climate conditions to sustain SOC levels and mitigate climate change-driven carbon release.
期刊介绍:
Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth:
Water and soil contamination caused by waste management and disposal practices
Environmental problems associated with transportation by land, air, or water
Geological processes that may impact biosystems or humans
Man-made or naturally occurring geological or hydrological hazards
Environmental problems associated with the recovery of materials from the earth
Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources
Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials
Management of environmental data and information in data banks and information systems
Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment
In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.