RT Journal Article
T1 What drives cultural ecosystem services in mountain protected areas? An AI-assisted answer using social media data
A1 Pérez-Girón, José Carlos
A1 Navarro, Carlos Javier
A1 Elghouat, Akram
A1 Khaldi, Rohaifa
A1 López-Pacheco, Domingo
A1 Arenas-Castro, Salvador
A1 Del Águila, Ana
A1 Moreno-Llorca, Ricardo
A1 Pistón, Nuria
A1 Romero-Gómez, Luis Felipe
A1 Vaz, Ana Sofía
A1 Tabik, Siham
A1 Martínez-López, Javier
A1 Alcaraz-Segura, Domingo
K1 Inteligencia artificial
K1 Ecosistemas - Gestión
AB Understanding how environmental and social factors shape the distribution of Cultural Ecosystem Services (CES) is essential for balancing biodiversity conservation and human well-being in protected landscapes. In this study, we integrate crowdsourced social media data, deep learning image classification (AI), and ecological niche models (ENMs) to map and compare the supply and demand of CES in mountain protected areas (PAs) across different biogeographical regions in southern Europe. Using geotagged photographs classified into eight CES types, we assessed model performance, identified key environmental and social predictors, explored CES bundles, and evaluated the influence of protection categories on CES suitability. Our models performed well across most CES types, confirming that social media data, when combined with AI and ENMs, provide a reliable and scalable approach for mapping human-nature interactions. The analysis revealed that while no universal set of predictors explains CES supply, some variables, particularly nighttime lights, distance to landmarks, and accessibility, consistently influenced multiple CES types. In contrast, nature-related CES such as Fauna & Flora and Nature & Landscape were mainly shaped by ecological and scenic features. We found that CES are generally clustered into two dominant bundles: one associated with cultural and heritage values and another linked to nature-based experiences. PAs showed higher overall CES suitability than unprotected zones, with Biosphere Reserves exhibiting particularly balanced outcomes between conservation and human use. This study shows how combining social media data, AI, and ecological modelling can reveal spatial drivers of CES, supporting sustainable management and fair distribution of nature’s cultural benefits in mountain PAs.
PB Elsevier
YR 2026
FD 2026-04-08
LK https://hdl.handle.net/10630/46341
UL https://hdl.handle.net/10630/46341
LA eng
NO José Carlos Pérez-Girón, Carlos Javier Navarro, Akram Elghouat, Rohaifa Khaldi, Domingo López-Pacheco, Salvador Arenas-Castro, Ana del Águila, Ricardo Moreno-Llorca, Nuria Pistón, Luis F. Romero, Ana Sofía Vaz, Siham Tabik, Javier Martínez-López, Domingo Alcaraz-Segura, What drives cultural ecosystem services in mountain protected areas? An AI-assisted answer using social media data, Ecosystem Services, Volume 79, 2026, 101848, ISSN 2212-0416, https://doi.org/10.1016/j.ecoser.2026.101848
NO https://openpolicyfinder.jisc.ac.uk/publication/21309?from=single_hit
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 4 may 2026