Publications
Characteristics and driving mechanisms of understory plant diversity in different stand types in Lushan Mountain
A study on Lushan National Park reveals that mixed conifer-broadleaf forests exhibit the highest understory plant diversity, particularly in shrub layers, with 91 woody species and 45 herbaceous species, including four rare or endangered plants. This diversity surpasses that of other stand types, such as Japanese larch plantations and Japanese cypress plantations. The research, conducted across six typical forest stands, used random forest models to identify key drivers of understory plant diversity, finding that stand type, annual precipitation, elevation, and soil carbon-nitrogen ratio significantly influence plant composition and diversity. Shrub layer diversity consistently outperform herbaceous layers due to spatial resource competition advantages. These findings underscore the ecological value of mixed forests in maintaining biodiversity and conserving native species, offering valuable insights for forest optimization and afforestation practices.
Global meets local: co-constituting glocalisation at Mount Lushan
Mount Lushan exemplifies the dynamic interplay between global and local influences through four distinct phases of glocalisation: Formation (pre-late 15th century), Development (late 15th to 17th centuries), Transformation (1660s to late 1940s), and Regeneration (late 1940s to present). Each phase aligns with broader globalisation eras—classical, maritime, industrial, and information—and is driven by cultural reconstruction, power negotiation, and state-led brand shaping. The study challenges Eurocentric biases by highlighting the multi-directional nature of glocalisation, emphasizing local cultural autonomy in the Global South. Using primary data from field surveys, interviews, and secondary sources, it applies Roland Robertson’s theory to offer a nuanced understanding of how local cultures selectively engage with global influences.
Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
A groundbreaking study achieves high-precision prediction of deep-seated landslide displacements in Taiwan's Lushan National Park, with a mean absolute percentage error (MAPE) of just 2.81%. The research integrates convolutional neural networks (CNNs) and the Age of Exploration-Inspired Optimizer (AEIO), leveraging eight years of displacement, groundwater, and meteorological data to enhance geohazard risk assessment. This innovative framework, combining machine learning and time series deep learning, offers a robust tool for early warning systems, significantly improving the safety of road networks, construction projects, and infrastructure in vulnerable slope areas. The AEIO-MobileNet model's accuracy marks a substantial advancement in landslide prediction, addressing critical needs for environmental risk management amid changing climate patterns.
Topographic and Edaphic Drivers of Community Structure and Species Diversity in a Subtropical Deciduous Broad-Leaved Forest in Eastern China
Subtropical deciduous broad-leaved forests in eastern China, critical ecotones between temperate and subtropical biomes, exhibit complex vegetation-environment relationships that challenge conventional assumptions about biodiversity. A study in Lushan National Park revealed that high plant diversity does not always correlate with soil nutrient content; instead, topographic heterogeneity and soil conditions—particularly the carbon-to-nitrogen (C:N) ratio, altitude, pH, total phosphorus, and total carbon—jointly shape community structure and species diversity. The research surveyed a 25-hectare forest dynamics plot, analyzing woody plants with a diameter at breast height (DBH) ≥ 1 cm alongside detailed topographic and soil physicochemical data. Notably, tree-layer structural characteristics were negatively correlated with diversity, while shrub-layer density showed the opposite trend. Altitude and solar radiation aspect index (TRASP) emerged as key topographic drivers, influencing soil properties in ways that underscore the importance of integrating both factors into conservation strategies for these ecologically vital forests.
Ecological Risk Assessment of Forest Landscapes in Lushan National Nature Reserve in Jiangxi Province, China
A comprehensive ecological risk assessment of Lushan National Nature Reserve, China, reveals that 91.03% of the forest landscape exhibits low to medium risk, with the highest risks concentrated in the experimental and buffer zones rather than the core zone. The study identifies Cunninghamia lanceolata forests as the most vulnerable, while other forestry lands show minimal risk. Human factors, particularly proximity to roads and settlements, significantly influence ecological risk, often outweighing natural factors like temperature and humidity. Spatial analysis shows that ecological risks tend to cluster near human activities, emphasizing the need for stricter regulation of human interference to mitigate these risks.
Human–Land Coupling Relationship in Lushan National Park and Its Surrounding Areas: From an Integrated Ecological and Social Perspective
A significant increase in human activity intensity, rising from 6.02% to 16.41% over two decades, has been identified near Lushan National Park, with a spreading trend toward the core protected area. This study developed a four-quadrant model integrating human activity intensity (HAI) and landscape pattern index (LPI) to analyze spatial coupling characteristics from 2000 to 2020 in Lushan National Park and its surroundings (LNPSA). The findings reveal higher landscape fragmentation, diversity, and variation in the surrounding areas compared to the core park. Vegetation coverage and proximity to Lushan were found to be the most significant factors influencing this human-land relationship. Based on these insights, the study delineated four distinct zones—harmonious development, stable transformation, environmental regulation, and risk prevention—each requiring tailored optimization strategies. This research provides a comprehensive methodology for planning and managing natural protected areas under rapid urbanization.
Spatial planning constraints will mitigate the fragmentation trajectory of natural and semi-natural landscapes: a case of Lushan City, China
Spatial planning constraints significantly mitigate landscape fragmentation in Lushan National Park, China, preserving 15.61 km² of natural landscapes and reducing potential fragmentation areas by 7.74 km². The study used the Patch-generating Land Use Simulation (PLUS) model to compare two scenarios: one with planning constraints and another without, revealing that constraints prevent urban encroachment on 2.38 km² of cropland, forest, and grassland while shifting fragmentation risks away from sensitive northeastern regions. Despite these benefits, nearly a quarter of forest and grassland remains vulnerable. The research highlights the effectiveness of spatial planning in curbing anthropogenic impacts and offers critical insights for future habitat conservation strategies.
Land Cover Changing Pattern in Pre- and Post-Earthquake Affected Area from Remote Sensing Data: A Case of Lushan County, Sichuan Province
A significant improvement in land cover occurred in Lushan National Park, Sichuan Province, following the 2013 earthquake, driven by both artificial measures and natural restoration. The study, using remote sensing data from 2012 to 2020, revealed that cropland, forest, built-up areas, and bare land experienced notable changes during this period. Key ecological indicators such as patch density (PD) and landscape shape index (LSI) decreased, while the aggregation index (AI) increased, signaling a positive shift toward more stable and aggregated landscapes. This research provides critical insights for ecological management and long-term restoration planning in earthquake-affected regions.
Pollution Characteristics, Sources, and Health Risk Assessment of Heavy Metals in the Surface Soil of Lushan Scenic Area, Jiangxi Province, China
A study on Lushan National Park reveals that while heavy metal concentrations in surface soil do not exceed pollution thresholds, arsenic (As) poses significant carcinogenic health risks to residents. Using the Nemerow comprehensive pollution index and geo-accumulation index, researchers assessed seven metals (Pb, Cu, Cr, Zn, Ni, As, Mn), finding non-carcinogenic hazards below safety levels but carcinogenic risks at an 'acceptable' level due to high As contributions. Six pollutant sources were identified: soil parent material, altitude, organic matter accumulation, industrial dustfall, local human activities, and tourism. The findings underscore the need for continuous monitoring of As risks while providing a scientific basis for sustainable development strategies in the scenic area.
Joint development of cultural heritage protection and tourism: the case of Mount Lushan cultural landscape heritage site
A novel approach to balancing cultural heritage protection and sustainable tourism has been developed, offering a model for UNESCO World Heritage Sites. The study demonstrates that integrating digital technologies—such as oblique photography, 3D laser scanning, and panoramic imaging—with IoT-based monitoring can enhance both tourist experiences and heritage preservation. By creating a virtual tourism subsystem and a real-time environmental management system, researchers successfully optimized tourist flow while maintaining ecological health. This integrated platform also streamlined marketing efforts, providing a scalable solution for other sites facing similar challenges.
Seismic sentinel? An analysis of captive giant panda behavior in response to the Lushan earthquake in China
A study of four captive giant pandas in Lushan National Park found no evidence that they sensed or responded to precursor signals before the 2013 magnitude 7.0 Lushan earthquake in Sichuan, China. Despite their seismically active habitat, the pandas exhibited no significant behavioral changes three days prior to the quake nor startle responses upon tremor onset, suggesting they may not perceive pre-earthquake geophysical cues like electromagnetic fields. The research, published in Earthquake Science, challenges the notion that giant pandas—endemic to a seismically dynamic region—serve as seismic sentinels.
Tourism Economic Network Structural Characteristics of National Parks in the Central Region of China
National parks in Central China exhibit an unbalanced spatial distribution of tourism economic connections, forming a multi-core network where key sites like Lushan Mountain and Shaoshan act as critical hubs for regional tourism flow. A study applying the modified gravity model and social network analysis (SNA) reveals that while administrative divisions and cultural ties strengthen intra-provincial linkages, inter-regional integration remains limited. This research advances the understanding of how tourism economic networks function among UNESCO World Heritage Sites, highlighting structural inefficiencies in connectivity.
Recognising values of China’s scenic and historic interest areas as world heritage cultural landscapes: Lushan case study
Lushan National Park embodies cultural values intrinsic to China's Scenic and Historic Interest Areas, yet its management risks undermining these values due to a focus on natural conservation over traditional Chinese philosophy. A theoretical framework was developed and tested at Lushan using semi-structured interviews and questionnaires, revealing a disconnect between stakeholders' understanding of the site's Outstanding Universal Value (OUV) and its cultural landscape significance. The study highlights the need for supplementary advice on OUV to address this imbalance and preserve community values associated with these areas.
State-of-the-practice: Assessing community participation within Chinese cultural World Heritage properties
An assessment framework for community participation in cultural World Heritage management reveals significant variability in practices among Chinese UNESCO sites. While some, like the Honghe Hani Rice Terraces and Kulangsu, demonstrate high levels of engagement, most, including Lushan National Park, show minimal involvement. The framework, developed from heritage policies and literature, includes four criteria and 23 indicators, tested on 36 cultural properties inscribed between 1987 and 2018 using content analysis. This study highlights the need for improved community participation in heritage conservation globally.
Vascular plants in the tourist area of Lushan National Nature Reserve, China: status, threats and conservation
Lushan National Nature Reserve, a biodiversity hotspot, faces significant threats from human activities such as plant introduction, road construction, and tourism. A 2015–2016 survey identified 563 vascular plant species along its main tourism routes, including 157 endemic to China (three unique to Lushan), 26 threatened with extinction, and 15 ancient relic species. Notably, 131 introduced species—17 of which are invasive—have altered the native flora, particularly in shrub and herb layers. The study highlights the need for urgent conservation measures to protect this delicate ecosystem.
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