Integrating multisource data for recreational ecological risk assessment in populous national park: A case study from Qianjiangyuan, China

Le résumé fourni par la source

• Develops a novel Source-Receptor-Response (SRR) model integrating multi-source data (statistics, RS, surveys, interviews) for spatial recreational ecological risk (RER) assessment in national parks. • Identifies high-risk RER areas (11.61% of park) near transport routes, residences, and recreational sites, correlated with human activity intensity. • Demonstrates recreational infrastructure (e.g., roads, lodges) and visitor density (67.52% combined source weight) as primary RER contributors, challenging “complete resident relocation” policies. • Proposes a three-tiered adaptive governance framework (geofenced controls, seasonal capacity models, eco-certification) for precise RER mitigation. • Validates GIS/RS-enabled multi-source data fusion overcomes single-source limitations, improving accuracy in mapping RER mechanisms. The burgeoning tension between anthropogenic pressures and ecological conservation in rapidly developing nations underscores the critical need for innovative frameworks to assess recreational ecological risk (RER) within national park systems. This study pioneers an analytical framework that synthesizes multi-source data streams, encompassing statistical analyses, remote sensing imagery, questionnaires, and interviews to advance ecological risk assessment theory beyond conventional methodologies. Through a novel hybrid model operationalizing the source, receptor and response, we systematically evaluate RER in Qianjiangyuan National Park (QJYNP). The results show that high-risk areas for recreational utilization zones are closely tied to human activities and are mainly located along transportation routes, residential areas, and designated recreational sites, accounting for 11.61% of the total area. Low-risk areas appear as strips or patches surrounding both the core protected zones and medium-to-high-risk regions. This indicates that even in densely populated settings, RER in national parks have strong spatial correlations with human activities. While large-scale conservation efforts are ongoing, it is essential to anticipate potential impacts from residents’ lifestyles and recreation pursuits effectively, such foresight will not hinder achieving ecological protection objectives for these parks. The proposed framework offers transformative potential for adaptive governance in Global South protected areas, providing a scalable methodology to reconcile biodiversity conservation with sustainable human use under escalating anthropogenic pressures.

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