Long-term vegetation dynamics in Spain's National Park Network: insights from remote sensing data

Understanding long-term vegetation dynamics in protected areas is crucial for assessing ecosystem resilience and informing adaptive management strategies. This study presents a comprehensive analysis of vegetation trends across Spain’s National Park Network from 1984 to 2023, using Landsat imagery processed in Google Earth Engine. Twelve national parks, representing diverse biogeographical regions and ecosystems, were analyzed using vegetation indices such as NDVI, SAVI, kNDVI, and NDMI. The Mann–Kendall test and Theil-Sen slope estimator were employed to detect monotonic trends and quantify their magnitudes, respectively. Our results reveal a predominant increase in vegetation activity across most parks over the past four decades, though with notable spatial and seasonal variations influenced by topographic gradients, bioclimatic zones, and vegetation types. High-altitude parks exhibited strong seasonal dynamics, with positive trends concentrated during the growing season, whereas Mediterranean parks showed more consistent trends throughout the year. Conversely, wetland parks like Las Tablas de Daimiel displayed concerning negative trends, highlighting ecosystem vulnerabilities associated with hydrological stress. These findings underscore the importance of integrating high-resolution remote sensing data into long-term ecological monitoring programs to track ecosystem functioning and assess management practices in protected areas. Combining remote sensing with field observations is essential to support evidence-based conservation strategies in response to climate change and other anthropogenic pressures.

Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research has been supported by the CUVACLI project (2857/2022) financed by the Spanish National Organism of National Parks. Magí Franquesa has been supported by the Grant JDC2022-048710-I funded by MCIN/AEI/https://doi.org/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR.

Peer reviewed