Land Degradation & Development最新文献

{"title":"Effects of Park Utilization Disturbance on Plant Diversity in Karst Urban Remnant Mountain Habitats","authors":"Shujun Liu, Gilbert Kumilamba, Zhijie Wang, Yixin Li, Yuan Su","doi":"10.1002/ldr.5650","DOIUrl":"https://doi.org/10.1002/ldr.5650","url":null,"abstract":"Urban remnant habitats, which are crucial biodiversity hotspots, are facing severe threats from urban expansion and infrastructure development. However, the impact of park utilization on plant diversity in these habitats remains underexplored. This study focused on eight urban remnant mountain parks (URMP) in Guiyang City, China, a karst mountain region, and a comprehensive evaluation system for park utilization disturbances was established using 11 indicators across four dimensions. We analyzed plant diversity responses to different disturbance types and intensities, identified dominant disturbance factors, and explored the relationship between habitat patch area and plant diversity. The results indicated that plant diversity in green patches under severe and moderate park utilization disturbance was higher than in areas with slight disturbance. Habitat fragmentation and tourist capacity were the primary disturbance factors. Larger habitat patches were associated with higher plant diversity, showing a clear area effect of habitat patches. Additionally, maintaining plant diversity in URMP had an area threshold effect. The minimum habitat patch area required to maintain plant diversity varied: 1.5 hm<jats:sup>2</jats:sup> for community‐level richness, 1.0 hm<jats:sup>2</jats:sup> for arbor, shrub, and herb layers, and 0.5 hm<jats:sup>2</jats:sup> for the Shannon–Wiener index at all levels and the Simpson index at the arbor layer. Threshold‐driven management strategies should prioritize maintaining core habitats &gt; 1.5 hm<jats:sup>2</jats:sup>, implementing visitor flow controls during peak periods, and preserving connectivity between habitat patches. This study significantly contributes to the theoretical understanding of the interplay between disturbance and biodiversity and offers valuable insights into the conservation and utilization of urban biodiversity in urban remnant habitats.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"4 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Dynamic Monitoring and Precision Analysis of Soil Salinity in Cotton Fields Using CNN‐Attention and UAV Multispectral Imaging Integration","authors":"Jiao Tan, Jianli Ding, Jiangtao Li, Lijing Han, Kuangda Cui, Yongkang Li, Xiao Wang, Yanhong Hong, Zhe Zhang","doi":"10.1002/ldr.5578","DOIUrl":"https://doi.org/10.1002/ldr.5578","url":null,"abstract":"Accurate and timely estimates of crop exposure to salt stress are essential for monitoring crop growth and implementing effective management practices. However, most contemporary research has focused on single‐period soil salinity estimations and relied on traditional machine learning methods, which struggle to account for the temporal dynamics of soil salinity. This study proposed a modeling framework that combined multi‐temporal UAV multispectral imagery and measured soil salinity data to estimate agricultural soil salinity. Key growth stages in soil preparation, squaring stage, flowering stage, and boll opening stage were evaluated and combined with field‐measured soil salinity values. Based on different combinations of inputs of indices, textures, and spectral reflectance, recursive feature cancelation cross‐validation (REFCV), Elastic Net, and XGBoost were used for selection of features extracted from multispectral imagery. The selected features were used to train and test random forest (RF) and Convolutional Neural Network‐Attention (CNN‐Attention) models. The results of the study show that (1) the REFCV algorithm is stable in feature selection, the EN algorithm is more prominent in the squaring stage and flowering stage, and XGBoost results are optimal. (2) After incorporating texture features, the model's <jats:italic>R</jats:italic><jats:sup>2</jats:sup> showed varying degrees of improvement. the <jats:italic>R</jats:italic><jats:sup>2</jats:sup> value of the RF model in Saline‐alkaline farmland increased to 0.912 and the RMSE decreased to 0.207, while in high standard farmland, the <jats:italic>R</jats:italic><jats:sup>2</jats:sup> reached 0.891 and the RMSE decreased to 0.255, with a significant improvement in model accuracy. (3) Overall, the CNN‐Attention model demonstrated a higher prediction accuracy at all time points and feature combinations. (4) In different scenarios, the RF model is suitable for long‐term stable monitoring tasks, and the CNN‐Attention model has significant advantages in complex feature extraction and dynamic change capture.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"60 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143979593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strengthening Climate Change Adaptation in Indian Agriculture: Policy Insights for Building Resilience","authors":"Srishty Kasana, Amarnath Tripathi, Yamini Gupt","doi":"10.1002/ldr.5624","DOIUrl":"https://doi.org/10.1002/ldr.5624","url":null,"abstract":"India's agricultural sector is under pressure from changing climatic conditions, placing the livelihoods of millions of farmers at great risk. Protecting this sector from these risks is essential to ensuring food security, reducing poverty, and sustaining rural livelihoods. Adaptation is a crucial strategy for achieving these goals. Based on the literature, there is a priori expectation that farmers with favorable socio-economic characteristics (higher income, education, awareness, large farm size, etc.) and institutional support should respond to climate change through adaptation. This premise remains underexplored in the literature. With a view to fill this gap, we have studied three villages in the National Capital Region (NCR) of India: Gadhi Kalanjari, Siroli, and Dharipur. Research based on mixed methods, the Mann–Kendall test, and logistic regression analysis reveals that farmers with stronger socio-economic and institutional support often either do not adopt adaptation measures or do so primarily to sustain their income, with little concern for long-term sustainability. This is evident from the fact that only 13% of surveyed farmers reported adopting any measures to mitigate the adverse effects of climate change. However, 97% of them acknowledged a decline in farm income due to extreme climate events. Furthermore, farmers with better market access are more likely to adapt, as the findings indicate that a 1% reduction in distance from the market increases the probability of adaptation by 11% points. Important suggestions for policy include improvement in extension, agromet services, community services; conducting evaluations of existing schemes in this sector to improve their effectiveness, and increasing investment in infrastructure.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"14 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144000644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of Urban Agglomeration Ecological Network Based on Multi‐Scale and Multi‐Method: A Case Study of Yangtze River Delta Urban Agglomeration, China","authors":"Kai Li, Wei Wu, Shiqi Tian, Linjuan Li, Zhe Li, Yue Cao, Yufan Wu, Weidong Xiao","doi":"10.1002/ldr.5649","DOIUrl":"https://doi.org/10.1002/ldr.5649","url":null,"abstract":"Ecological networks (ENs) are vital for maintaining regional ecological security and preserving biodiversity. While various methods exist for constructing ENs, their effectiveness across different spatial scales, particularly in urban agglomerations, has not been thoroughly investigated. This study focuses on the Yangtze River Delta urban agglomeration (YRDUA), constructing ENs at three scales: urban agglomeration, metropolitan area, and city. Two methods were employed at each step, and the outcomes were evaluated and ranked using specific indicators. The results indicate: (1) For ecological source identification, the spatial distribution of ecological sources identified by different methods is consistent at the same scale, with the number of ecological sources identified at the three scales being around 600, 140, and 160, respectively. (2) For resistance surface construction, although there are differences between the two methods, the final resistance value shows relatively small changes. (3) Regarding the number of corridors, the quantities of the three scales are around 1470, 380, and 410, respectively. For specific indicators, <jats:italic>α</jats:italic> values of the three scales are around 0.71, 0.85, and 0.81, respectively; <jats:italic>β</jats:italic> values are around 2.42, 2.68, and 2.61, respectively; <jats:italic>γ</jats:italic> values are around 0.81, 0.90, and 0.88, respectively; Cr values are around 0.88, 0.80, and 0.68, respectively. Comparing and ranking all indicators can yield: at the urban agglomeration scale, ecological sources identified by the MSPA method, resistance surfaces constructed by Spatial Principal Component Analysis (SPCA), and corridors extracted by Linkage Mapper yielded optimal results. At the metropolitan and city scales, ecological sources identified by the MSPA method, resistance surfaces constructed by the Analytical Hierarchy Process (AHP), and corridors extracted by Graphab yielded optimal results. These findings provide methodological guidance for constructing ENs across different scales and offer new insights for landscape planning at multiple levels.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"116 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Divergent Responses of Microbial Diversity and Extracellular Enzymatic Activities to Straw Addition in Reclaiming Salt‐Affected Soil","authors":"Xiangdong Li, Feifei Dang, Changkun Ma, Na Mao, Chong Liu, Xiaorong Wei, Ming'an Shao","doi":"10.1002/ldr.5644","DOIUrl":"https://doi.org/10.1002/ldr.5644","url":null,"abstract":"Soil salinization threatens food security and ecosystem functions, particularly in arid and semi‐arid regions. Besides degrading soil structure and nutrient availability, salinization also disrupts microbial functionality. Although irrigation and organic amendments are widely used to alleviate salinity, their combined effects on microbial diversity and nutrient metabolism remain unclear. Through a 120‐day microcosm experiment, the results demonstrated that intermittent leaching (320.0 mm) significantly reduced soil saltness by 29.3%–36.9% (<jats:italic>p</jats:italic> &lt; 0.05). Although straw addition (6.5 t/ha) did not directly reduce salt content, it improved leaching efficiency by 7.6% (<jats:italic>p</jats:italic> &gt; 0.05). Both straw and leaching decreased nitrate nitrogen contents (<jats:italic>p</jats:italic> &lt; 0.05). Straw addition reduced microbial diversity due to the disproportionate growth of dominant taxa, and the decreased fungal diversity was partially alleviated by lower salinity under leaching. Straw addition also significantly increased the activities of β‐glucosidase and N‐acetylglucosaminidase by 94.6%–161.2% and 187.3%–210.9% (<jats:italic>p</jats:italic> &lt; 0.05), respectively, while the activities of β‐cellobiosidase, leucine aminopeptidase, and alkaline phosphatase remained unaffected (<jats:italic>p</jats:italic> &gt; 0.05). Ecoenzymatic vector analysis indicated vector length generally below 0.3, with straw increasing it by 44.9%–64.4%. Leaching indirectly reduced microbial carbon limitation by alleviating salinity stress (<jats:italic>p</jats:italic> &lt; 0.05). The soils were primarily nitrogen‐limited (vector angles &lt; 55°), with straw addition and leaching exerting indirect effects through fungal diversity. These findings indicate that the proposed vector length threshold of 0.61 may underestimate soil microbial carbon limitation in extreme conditions like salt‐affected soils. Given that straw addition improves salt leaching efficiency and nutrient metabolism, combining optimized irrigation with organic amendments could be an effective strategy for reclaiming salt‐affected soils.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"10 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land Use‐Induced Changes in Nutrient Accumulation and Bacterial Diversity Shift Stoichiometry of Soil Enzyme Activity","authors":"Quan Zhou, Quanchao Zeng, Lianhao Zhou, Man Hu","doi":"10.1002/ldr.5651","DOIUrl":"https://doi.org/10.1002/ldr.5651","url":null,"abstract":"Soil enzymes are the rate‐limiting steps in the catalytic breakdown of organic matter, governing the process and efficiency of nutrient cycling in soil. Despite their crucial role in agricultural management and climate change mitigation, our understanding of the enzyme‐mediated mechanisms by which soil microorganisms regulate nutrient cycling in agricultural soils remains limited. This study investigated patterns of extracellular enzyme activities related to carbon (C), nitrogen (N), and phosphorus (P) cycling, along with their driving factors, in both agricultural and natural ecosystems. Our results indicated that citrus cultivation significantly reduced soil bacterial community diversity. Compared with natural forest soils, citrus‐planted soils exhibited markedly higher levels of available nitrogen and phosphorus, which correspond with decreased activities of C‐ and P‐acquiring enzymes and increased activity of N‐acquiring enzymes. Regression analyses revealed that the activities of soil C‐ and P‐acquiring enzymes were positively correlated with bacterial diversity, whereas N‐acquiring enzyme activity was negatively associated with bacterial diversity. In contrast, N‐acquiring enzyme activity was positively correlated with the availability of soil N and P, while C‐ and P‐acquiring enzyme activities showed negative correlations. These findings suggested that extracellular enzyme activities are highly responsive to variations in soil nutrient availability and microbial diversity. Enzyme vector analysis further indicated that as soil bacterial diversity decreased, microbial nutrient limitation shifted from phosphorus to nitrogen. This transition is primarily driven by citrus‐induced decline in bacterial diversity, resulting in enhanced microbial nitrogen limitation. The shift in microbial nutrient limitation, influenced by soil pH, available phosphorus, and bacterial diversity, has significant implications for soil fertility management, particularly in enhancing soil enzyme activity to reduce chemical fertilizer use and support climate‐smart agriculture in the face of global environmental challenges.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"10 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Are the Main Drivers of Ecological Vulnerability in Typical Arid Zones Natural or Anthropogenic? An Analysis From an Evolutionary Process Framework","authors":"Kexin Yang, Kang Hou, Lixia Ma, Ruochen Mei, Yujie Zhu, Xuxiang Li","doi":"10.1002/ldr.5638","DOIUrl":"https://doi.org/10.1002/ldr.5638","url":null,"abstract":"As a key indicator of regional sustainable development, in‐depth study of ecological vulnerability (EV) is conducive to the realization of precise ecological protection. However, the complexity of the regional environment causes the driving mechanism of EV to be difficult to clarify, particularly for areas with special natural climates. This study developed a comprehensive natural‐social‐economic‐pollution‐environmental (NSEPE) index system and analytical framework for typical arid areas, revealing EV's spatiotemporal heterogeneity and driving factors. Based on structural equation modeling, the spatial driving mechanism of the dominant factors was clarified. Finally, the spatial heterogeneity of EV in 2035 under different scenarios was predicted using the CA‐Markov model. The results indicated that: (1) Ecological vulnerability grades exhibited a southeast‐northwest increasing trend (2000–2020), with 9.6% areas transitioning from high to low vulnerability. (2) The three factors of precipitation, farmers' income, and Normalized Difference Vegetation Index (NDVI) were the most important factors causing EV in the study area. (3) Sustainable development scenarios better support ecological protection and human‐nature harmony by predicting for 2035. This study can quantitatively identify the law of spatial heterogeneity of EV and its influencing factors, and also provides a feasible idea for EV evolution in areas with complex natural environments and frequent human activities.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"51 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Urbanization and Urban Water Security in China: Challenges for Sustainable Development Under SDGs Framework","authors":"Ziheng Shangguan","doi":"10.1002/ldr.5646","DOIUrl":"https://doi.org/10.1002/ldr.5646","url":null,"abstract":"China's rapid population urbanization over recent decades has posed significant challenges to sustainable urban development, particularly in ensuring water resource security. Within the sustainable development goals (SDGs) framework, this study explores the multidimensional mechanisms underlying population urbanization and water resource security by integrating spatial and econometric analyses. Spatial kernel density estimation and obstacle degree model were employed to assess the dynamic trends of population urbanization and water resource security across China. Subsequently, econometric analyses using random effects models, difference‐in‐differences models, and spatial durbin models were conducted to evaluate causal relationships and spatial dependencies. Empirical results demonstrate that China's population urbanization enhances water resource security largely due to the agglomeration effect of population density and improved water infrastructure development. However, regional economic growth often occurs at the expense of environmental quality, highlighting the critical need for strengthened protection of wetlands and forests and enhanced regulation of industrial wastewater discharge. Further analysis confirms that: (1) the impact of population urbanization on water resource security remains consistent with the benchmark regression results in both short‐term and long‐term effects; (2) population density and years of education positively moderate the relationship between population urbanization and water resource security; (3) spatial heterogeneity is evident, showing negative externalities from population urbanization in eastern and central provinces on neighboring regions' water resource security, whereas population urbanization in western provinces significantly improved local water resource security without significant externalities. Based on these insights, this study proposes targeted management strategies to mitigate negative spillovers, enhance regional cooperation, and integrate water resource governance into sustainable urban planning.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"54 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Priority Areas for Ecological Restoration in the Three Gorges Reservoir Area, China: The Systemic and Targeted Perspectives","authors":"Chunhua Peng, Yanhui Wang, Junwu Dong, Chong Huang, Mengqin Yang","doi":"10.1002/ldr.5630","DOIUrl":"https://doi.org/10.1002/ldr.5630","url":null,"abstract":"This study focuses on precisely identifying ecological restoration priorities within territorial spaces, aiming to safeguard ecological security and accelerate the implementation of differentiated restoration strategies. An innovative “area‐to‐point” framework is developed by integrating systematic ecological conservation and targeted restoration perspectives to accurately determine the priorities of ecological restoration work in territorial space. Taking the Three Gorges Reservoir Area (TGRA) as a case study, a dual—evaluation method combining the ecosystem service importance index and the ecological problem index is adopted to quantitatively identify the restoration “areas.” Then, from the targeted restoration perspective, the ecological security pattern construction method is applied to identify the restoration “points.” Finally, spatial overlay techniques are utilized to determine the restoration priorities and formulate strategies for different intervention levels. The results convincingly demonstrate the validity and practicality of the proposed framework. A total of 300.63 km<jats:sup>2</jats:sup> of ecological restoration areas are identified, categorized into three priority levels: Level I (75.69 km<jats:sup>2</jats:sup>), Level II (88.94 km<jats:sup>2</jats:sup>), and Level III (136.00 km<jats:sup>2</jats:sup>). These areas are primarily located along critical ecological corridors in the northwestern and northern parts of TGRA. Although these areas exhibit high ecological value, some face significant ecological challenges, with land use predominantly consisting of arable and forestland. The study recommends comprehensive improvements in arable land management, artificial afforestation, greening construction, and enhanced ecological environment monitoring to prevent the loss of ecological land. The findings not only provide scientific guidance for ecological restoration in TGRA but also offer new insights for ecological restoration research in other regions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"24 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143920178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combined Application of Humic Acid and Attapulgite Improves Physical Structure and Nutrients in Coastal Saline-Alkali Soils","authors":"Weibin Zhao, Shufeng Wang, Li Tang, Jiang Xiao, Guangcai Chen","doi":"10.1002/ldr.5643","DOIUrl":"https://doi.org/10.1002/ldr.5643","url":null,"abstract":"Coastal soils are subject to salinization, a process that degrades soil structure, exacerbates nutrient leaching, and depletes soil organic matter. Both organic fertilizers and clay amendments have been shown to play a key role in soil structure, nutrient availability, and soil health. The different dosages (0%, 3%, and 6%) of humic acid (HA3 and HA6) and attapulgite (AT3 and AT6) alone or in combined application (HAT3 and HAT6) on the quality of coastal saline-alkali soil were studied. The results showed that in terms of soil physiochemical properties, the combination of HA and AT (HAT) significantly (<i>p</i> &lt; 0.05) improved soil moisture content and soil CEC by 4.01%–5.25% and 53.45%–401%, and significantly (<i>p</i> &lt; 0.05) reduced soil salinity and soil Na⁺ content by 25.38%–45.18% and 27.57%–38.16%, compared to the control. In terms of soil nutrient content, HAT treatments significantly (<i>p</i> &lt; 0.05) improved the contents of soil TN, AP, and SOC by 15.25%–26.88%, 19.67%–32.11%, and 73.71%–99.25%, compared to the control, respectively. Furthermore, the soil quality indexes (SQI) constructed based on PCA analysis indicated that the improvement effect of each treatment on soil quality ranked as HAT6 &gt; HA6 &gt; HAT3 &gt; HA3 &gt; AT6 &gt; AT3 &gt; Control. In short, HAT treatment can produce larger surface area and more elements (e.g., N, P, and Ca) content through the combination of HA and AT, accelerate salt leaching, and increase soil nutrient content by promoting soil aggregate formation and ion exchange capacity, thereby improving soil quality more than the single application of HA and AT. These results offer valuable insights for the formulation of ecological restoration strategies targeting large-scale coastal saline-alkali terrains.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"20 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143926943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}