Land Degradation & Development最新文献

{"title":"Forest Conversion Reduces Soil Water Retention in Tropical Rainforest","authors":"Qiaoyan Chen, Siyuan Cheng, Shuting Yu, Xiaowei Guo, Zhongyi Sun, Zhongmin Hu, Licong Dai","doi":"10.1002/ldr.70918","DOIUrl":"https://doi.org/10.1002/ldr.70918","url":null,"abstract":"Extensive primary forests are being converted to secondary forests and plantations owing to human activities in recent decades, which have substantial effects on soil hydrological processes. However, the potential impact of forest conversion on soil water retention remains poorly understood. In this study, tropical primary forests (PF), secondary forests (SF), and rubber monocultures (RM) converted from tropical primary forests were selected on Hainan Island to examine the variation in soil water retention across three forest types and their controlling factors. We found that the primary forests exhibited significantly greater water retention capacity than secondary forests and rubber monocultures. However, secondary forests showed higher water retention than rubber monocultures in shallow soils but lower in deep soils. Similarly, primary forests demonstrated significantly greater soil water storage capacity than secondary forests and rubber monocultures, but secondary forests and rubber monocultures had obvious seasonal variations, which showed that secondary forests had a higher water storage capacity than rubber monocultures in the rainy season and displayed an opposite pattern in the dry season. The saturated hydraulic conductivity in primary forests was higher than that in secondary forests and rubber monocultures. Furthermore, forest types influenced soil properties, with secondary forests and rubber monocultures showing higher bulk density but lower soil capillary porosity compared with primary forests. Among all factors, soil porosity emerged as the dominant controller of water retention, where total porosity and capillary porosity accounted for 31.49% and 30.61% of variation respectively, while soil bulk density contributed relatively less (12.46%). These findings indicate that the conversion of tropical primary forests to secondary forests and rubber monocultures is detrimental to soil water retention and storage. Our results can provide scientific insights for forest development and management in the tropical rainforest.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"11 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086865","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":"Effect of Stand Density on Soil Microbial Carbon and Nitrogen Use Efficiency in Robinia pseudoacacia Plantations in the Loess Hilly‐Gully Region, China","authors":"Yue Zhang, Yuchen Li, Yunming Chen, Min Zhao","doi":"10.1002/ldr.70912","DOIUrl":"https://doi.org/10.1002/ldr.70912","url":null,"abstract":"Soil microbial carbon (CUE) and nitrogen (NUE) use efficiency are critical for soil carbon (C) sequestration and nitrogen (N) availability. However, how microbial CUE and NUE respond to stand density is unclear. Furthermore, it remains unclear whether the response of microbial CUE and NUE to stand density could be mediated by soil depth. This study investigated the impact of stand density (low‐density, 625~1000; medium‐density, 1001~1625; high‐density, 1626~2100 trees ha <jats:sup>−1</jats:sup> ) on microbial CUE and NUE in topsoil (0–10 cm) and subsoil (10–20 cm) of <jats:styled-content style=\"fixed-case\"> <jats:italic>Robinia pseudoacacia</jats:italic> </jats:styled-content> plantations in the loess hilly‐gully region, China. In the 0–10 cm soil layer, microbial CUE decreased with increasing stand density. Specifically, microbial CUE under low‐density stands was significantly higher than that under medium‐ and high‐density stands, with increases of 4.9% and 7.1%, respectively. Microbial NUE in low‐density stands was significantly markedly lower than that in medium‐ and high‐density stands, with decreases of 19.9% and 27.8%, respectively. In the 10–20 cm layer, microbial CUE in medium‐density stands was 4.8% and 6.4% higher than that in low‐ and high‐density stands, respectively. In contrast, in the 10–20 cm layer, microbial NUE in medium‐density stands was 24.5% and 32.1% lower than that in low‐ and high‐density stands, respectively. Hierarchical partitioning analysis revealed that the relative importance of environmental factors on microbial CUE and NUE differed markedly across soil depths. Specifically, enzymatic C:N ratio and soil organic C:total N ratio explained the largest proportions of variation in microbial CUE and NUE at the 0–10 cm (19.2%) and 10–20 cm (19.5%), respectively. Results from multiple linear regression indicated that microbial metabolic limitation was the main driver of microbial CUE and NUE at the 0–10 cm layer; however, microbial biomass C:N ratio was the primary driver of microbial CUE and NUE at 10–20 cm soil layers. Overall, these results highlighted that stand density regulates microbial nutrient use efficiency by driving variations in nutrient limitation caused by the stoichiometric imbalances across soil depths.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"10 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086186","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":"Causal Linkages Between Forestation, Health Issues, and Sustainability Dimensions in the United States and China: A Climate Resilience Perspective","authors":"Jiyang Cheng, László Vasa, Wolanin Elżbieta, U. Shahzad, Ummara Razi","doi":"10.1002/ldr.70849","DOIUrl":"https://doi.org/10.1002/ldr.70849","url":null,"abstract":"Growing environmental pressures and climate‐related risks have intensified concerns regarding population health and sustainability. This study explores how the predictive relationship between public health and key sustainability indicators, such as agricultural emissions, forests, governance, digitalization, green energy, and climate outcomes, varies over time across the United States and China. For this, the study applied the Bootstrap rolling window Granger causality framework to identify whether health sustainability relationships remain stable or vary over time. The study uses the annual data from 1996 to 2023. The findings revealed different structural patterns. For instance, in the United States, causal flows from sustainability factors to health with episodic positive effects from forest, green energy, and climate outcomes, while digitalization exhibited weak health reinforcement. In contrast, for China, health exhibits stronger predictive effects on agricultural emissions, renewable energy transitions, and governance indicators. The results indicate distinct sustainability health pathways, with environmental conditions playing a more prominent role in health dynamics in the United States, while improvements in health are more closely associated with sustainability transition in China, which can be used to inform resilience‐oriented policy development.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"5 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086189","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":"From Trapped to Resilient Mountains: Diversified Coupling Pathways Linking Land Use Transition and Rural Revitalization for Mountain Sustainable Development","authors":"Luanyu Zhou, Yangbing Li, Yuluan Zhao, Guangjie Luo, Linyu Yang, Yuxuan Xie, Xiang Wu, Xue Ren, Yiyi Zhang, Juan Huang, Kunyan Rao","doi":"10.1002/ldr.70911","DOIUrl":"https://doi.org/10.1002/ldr.70911","url":null,"abstract":"The synergistic interplay among land use transition, rural revitalization, and sustainable development is critical for harmonizing human‐land‐economic systems. Understanding their diverse coupling pathways is key to resolving human‐land conflicts and advancing sustainable rural development in mountainous regions. However, existing research has not systematically elucidated their dynamic mechanisms or delineated context‐adaptive implementation pathways. This study establishes a theoretical framework of the “Land Use Transition‐Rural Revitalization‐Sustainability” (TRS) system. It also proposes a three‐stage evolutionary model, termed “Trapped‐Activating‐Resilient Mountains” (TAR), to understand it. This model characterizes a sequential developmental trajectory of mountain villages: starting from low‐level systemic lock‐in, transitioning via factor mobilization, and culminating in resilient human‐land symbiosis. This paper systematically unpacks the synergistic mechanisms and evolutionary pathways across the T, R, and S dimensions. It then verifies the theoretical framework via comparative case analysis. The core findings are as follows: (1) Land use transition acts as the spatial foundation and primary driver of the coupled TRS system. Rural revitalization serves as an intermediate carrier through diversified implementation pathways. Sustainable development sets the ultimate developmental goal and generates reverse feedback effects. Institutional innovation enables the coordinated co‐evolution of the three subsystems. (2) The three‐stage TAR evolution represents an upgrading process of the TRS system from “inefficient coupling” to “preliminary activation” and finally to “efficient synergy,” each exhibiting distinct characteristics. In the trapped mountain stage, inefficient coupling leads to low‐level development dilemmas. During the “activating mountain” stage, factor linkage and activation drive breakthroughs in pathways. In the resilient mountain stage, efficient TRS synergy forms a sustainable paradigm. (3) Based on the aforementioned theoretical discussions, comparative case evidence further verifies that disparities in regional resource endowments produce differentiated rural revitalization pathways under distinct driving modes, while all pathways follow the unified internal operating mechanisms of the TRS system. In conclusion, sustainable mountain development relies on localized adaptive governance, full exploitation of multifunctional land use transition potentials, and targeted adoption of context‐specific coupling pathways. This study provides a conceptual framework and an actionable roadmap, offering a resilient theoretical foundation for context‐specific implementations.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"60 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086187","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":"A Single Amendment With Flue Gas Desulfurization Gypsum Improves Saline‐Sodic Soil Quality: Evidence From a Decade‐Long Paddy Experiment","authors":"Ran Li, Jingzhe He, Wenchao Zhang, Bangyan Liu, Shujuan Wang, Jia Liu, Yan Li, Lizhen Xu, Jinbo Li, Yonggan Zhao","doi":"10.1002/ldr.70901","DOIUrl":"https://doi.org/10.1002/ldr.70901","url":null,"abstract":"Saline–sodic soils threaten global agriculture, and flue gas desulfurization (FGD) gypsum is a widely adopted reclamation practice. However, the associated long‐term (&gt; 10 years) legacy effects and temporal dynamics remain poorly understood. We quantified the decadal dynamics of soil quality following a one‐time application of FGD gypsum (40 t ha <jats:sup>−1</jats:sup> ) in a saline–sodic paddy field on the Songnen Plain. An in situ field experiment monitored key salinity‐sodicity and nutrient parameters in the 0–20 cm layer at 0, 3, 7, and 10 years post‐amendment. With the L <jats:sub>2</jats:sub> norm to establishing a minimum data set (MDS), the soil quality index (SQI) increased by 3.3‐, 4.2‐, and 4.8‐fold over the 3‐, 7‐, and 10‐year periods, respectively, representing full data set variability ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.98). This improvement was driven by reductions in soil pH (26.2%–28.4%), exchangeable sodium percentage (ESP, 58.5%–90.1%), water‐soluble sodium (Na <jats:sup>+</jats:sup> , 52.0%–87.7%), and dispersive charge (DC, 47.5%–86.5%), alongside a 2.6‐ to 4.5‐fold increase in available phosphorus (AP). Actual land productivity supported the theoretical SQI improvements, with rice yield exhibiting a highly significant positive response. A partial least squares path model (PLS‐PM) confirmed that the sustained exchange between water‐soluble calcium (Ca <jats:sup>2+</jats:sup> ) and exchangeable sodium (EX‐Na <jats:sup>+</jats:sup> ) mediated structural stabilization and drove SQI enhancement and crop yield. Soil quality and productivity benefits plateaued around the 7‐year mark. We demonstrate that a single FGD gypsum application can establish a decade‐long ameliorative legacy and present a robust, cost‐effective strategy for the sustainable management of saline–sodic paddy systems, particularly in rice‐growing regions facing similar soil constraints.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"20 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086188","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":"Linking Ecosystem Risk, Health, Services to Ecological Security Assessment in the Yellow River Basin: Spatiotemporal Dynamics and Nonlinear Driving Characteristics","authors":"Menghao Yang, Ming Wang, Haipeng Zhang, Zhihong Yao","doi":"10.1002/ldr.70896","DOIUrl":"https://doi.org/10.1002/ldr.70896","url":null,"abstract":"A scientific assessment of ecological security (ES) and its nonlinear mechanism for key driving factors in the Yellow River Basin (YRB) is of great significance for ecological protection and sustainable development. This study proposes an ES assessment framework, which links ecosystem risk (ER), ecosystem health (EH), and ecosystem services (ESS). We applied this framework to reveal the YRB's ES characteristics from 2000 to 2023, and explored the reliability of the assessment results. By coupling the XGBoost‐SHAP model, we identified the dominant driving factors of ES and quantified their nonlinear response relationships as well as key thresholds. The results indicated that under the comprehensive effect of significant decline in ER, overall improvement in EH and ESS in the YRB, the ES level showed a steady upward trend, with a stable pattern of high in the south and low in the north, and significant spatial positive correlation characteristics. The forest and grassland proportion, precipitation, vegetation coverage, and the construction land proportion are the dominant driving factors affecting ES, and each driving factor exhibited clear threshold characteristics in its impact on ES. Among them, the beneficial effects of the forest and grassland proportion, precipitation, and vegetation coverage on ES significantly increased when exceeding the thresholds of 49.6%, 512.2 mm, and 67.2%, respectively. The ecological impact of construction land proportion becomes negative when exceeding the threshold of 10.5%, showing a coercing effect. Our research not only provides key control objects and threshold basis for the ES management in the YRB, but also provides a robust framework for other similar regional ES research.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"3 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086261","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 Degradation Pathways of Open‐Pit and Underground Mining in Karst Regions: A Spatial Indicator Assessment","authors":"Xiaofu Chen, Jianchun Hu, Pushan Wen, Tao Wei, Wenrui Ran, Pan Wu","doi":"10.1002/ldr.70903","DOIUrl":"https://doi.org/10.1002/ldr.70903","url":null,"abstract":"Mining in the karst regions of southwest China threatens ecosystem stability and accelerates land degradation. Regional evaluation rarely distinguishes between degradation pathways in open‐pit and underground operations, due to spatial heterogeneity and geomorphological confounding effects. Using land use/land cover data from the China Land Cover Dataset (CLCD) for 2010, 2015, 2020 and 2025, we examined 4318 mines in Guizhou with a multiscale (0–4 km) distance‐decay model that applies local topological constraints to separate mining footprint changes from background landscape changes. We found that these two types of mining represent two distinct spatial disturbance regimes. For open‐pit operations, localized physical degradation was pronounced, with surficial stripping expansion peaking at a 2.0‐km radius and maintaining a sustained degradation footprint. Underground mining displayed a diffuse spatial signature. Rather than a sharp distance‐decay gradient, surrounding forest cover showed a uniform decline of 18.0 percentage points below the control baseline across the 4.0‐km study area. This non‐gradient degradation pattern implies a landscape‐scale response to alterations in subsurface hydrology rather than direct surface disturbances. These results emphasize the inadequacy of uniform buffer zones for managing regional environmental impacts. We recommend a 2.0‐km core management zone for prioritizing open‐pit mine rehabilitation, while addressing the impacts of underground mining requires transitioning from static spatial boundaries to broader landscape‐level hydro‐ecological management.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"6 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086190","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":"Manure Composting as a Strategy to Mitigate Antibiotic Resistance Dissemination in Agricultural Systems","authors":"Magdalena Urbaniak","doi":"10.1002/ldr.70909","DOIUrl":"https://doi.org/10.1002/ldr.70909","url":null,"abstract":"Livestock manure is a valuable agricultural resource but may introduce antibiotic residues and antibiotic resistance genes (ARGs) into the environment. This review critically evaluates the fate of antibiotics and ARGs during manure composting and identifies the principal factors controlling their attenuation. It integrates composting‐system configuration and phase‐specific operating conditions with antibiotic properties, microbial‐host succession, extracellular DNA, mobile genetic elements (MGEs), post‐application risks, and alternative manure‐treatment technologies. Composting can reduce many antibiotic residues by 80%–90% or more, although apparent removal may reflect degradation, transformation, sorption, or reduced extractability and remains strongly compound‐ and process‐dependent. ARG responses are more variable and often non‐linear. Sustained thermophilic conditions can reduce ARG‐carrying microorganisms and MGEs, but selected genes may persist or rebound during maturation because of microbial recolonization, residual selection pressure, extracellular DNA persistence, and horizontal gene transfer (HGT). Temperature and exposure duration, aeration, moisture, C:N ratio, bulking materials, biochar, and microbial inoculants are therefore key determinants of treatment performance. Composting substantially mitigates antimicrobial‐resistance risks but does not guarantee complete elimination of transmissible ARGs. Standardized monitoring, full‐scale validation, and long‐term assessment of soil and crop compartments are required to support safe agricultural use of composted manure.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"4 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149021227","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":"Explainable, Uncertainty‐Aware Machine Learning for Maize Land Suitability and Climate Resilience in Lorestan Province, Western Iran","authors":"Ahad Madani, Narges Shafaei Bajestani","doi":"10.1002/ldr.70910","DOIUrl":"https://doi.org/10.1002/ldr.70910","url":null,"abstract":"Maize ( <jats:styled-content style=\"fixed-case\"> <jats:italic>Zea mays</jats:italic> </jats:styled-content> L.) is strategically important in Iran, yet its cultivation in the semi‐arid Zagros is constrained by limited and variable water, heat stress and heterogeneous soils, while conventional suitability assessments are deterministic, rarely validated spatially and provide no measure of confidence. The aim of this study was to develop an explainable, uncertainty‐aware machine‐learning framework for maize land‐suitability mapping that is interpretable, spatially robust and climate‐aware and to demonstrate it in Lorestan Province (≈28,300 km <jats:sup>2</jats:sup> ), western Iran. The experimental material comprised harmonised multi‐source geospatial predictors—soil properties (SoilGrids 2.0), climate variables (Climate Hazards Group InfraRed Precipitation with Station data, CHIRPS; TerraClimate), moderate resolution imaging spectroradiometer (MODIS) vegetation indices and shuttle radar topography mission (SRTM) terrain—together with 520 reference sites labelled by applying the Food and Agriculture Organization (FAO) maximum‐limitation land‐evaluation procedure to explicitly documented land qualities. As the method of investigation, six classifiers (Elastic‐Net, support vector machine, multilayer perceptron, random forest, LightGBM and XGBoost) were trained and evaluated under spatial block cross‐validation; predictions were interpreted with SHapley Additive exPlanations (SHAP) and uncertainty was quantified using predictive entropy and between‐model ensemble variance and then validated against observed classification error. Data collection drew on openly available gridded products resampled to a 250 m grid, with Coupled Model Intercomparison Project Phase 6 (CMIP6) projections under two shared socioeconomic pathways (SSPs) used for climate scenarios. Gradient‐boosting models performed best, achieving a macro‐ <jats:italic>F</jats:italic> <jats:sub>1</jats:sub> ‐score of 0.79 under spatial block cross‐validation against 0.87 under random cross‐validation, confirming that random partitioning inflates apparent skill. Growing‐season precipitation, aridity, heat‐stress frequency, vegetation condition and root‐zone soil properties dominated, with pronounced thresholds; predictive entropy was inversely related to classification accuracy, confirming that the uncertainty surface is diagnostic of error rather than merely descriptive and the most suitable land was not necessarily the most climate‐resilient. We conclude that the framework offers a transparent, probabilistic and transferable alternative to deterministic suitability mapping for climate‐smart dryland agricultural planning.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"22 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149019891","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":"Energy Options to Reduce Deforestation Using EKC Model: A Region‐Based Longitudinal Approach","authors":"Krismanti Tri Wahyuni, Agung Purwanto, Bagus Sumargo, Robert Kurniawan","doi":"10.1002/ldr.70905","DOIUrl":"https://doi.org/10.1002/ldr.70905","url":null,"abstract":"Forests are carbon storage that can reduce carbon emissions, so deforestation (decrease in forest area) is a serious threat to environmental sustainability. Indonesia is a large carbon sink due to its large forests. However, deforestation is quite high due to economic activities that use fossil energy. In contrast to previous studies, this study uses deforestation per capita as a variable explained. The aim is to investigate the causes of deforestation in relation to economic variables with a focus on energy issues. Based on the EKC conceptual framework, control variables in the form of economic variables GRDP per capita and its square and technology in the form of proportion of internet usage. This study focuses on energy use, consisting of gas, electricity production, electricity consumption and fuel wood/charcoal/briquettes for cooking. The method is a longitudinal approach based on regional data for 8 years. The model used is dynamic panel data, which accommodates adjustments in deforestation per capita that are influenced by long‐term behavior and explores the diversity of data in the region. This study shows that the energy option that can reduce deforestation is currently gas. Indonesia has not yet reached the top of the Kuznet curve so the economy has not been able to improve environmental sustainability. The production and use of electrical energy in Indonesia is still not environmentally friendly and thus urgently requires investment in renewable energy and new technologies. In addition, the replacement of industrial machinery and household electrical appliances requires new technology to be more efficient.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"94 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009793","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}