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Friday, October 25, 2024 at 09:08

How and why have high mountain biosphere reserves changed?

Photo: Ordesa. Author: Adrian Garcia Bruzon Photo: Ordesa. Author: Adrian Garcia Bruzon

A study carried out by researchers from the Research Group on Technologies for Landscape Analysis and Diagnosis (TADAT) has analysed the factors that imply the increase and decrease of vegetation in nature reserves such as Ordesa-Viñamala and Sierra Nevada, respectively. The results obtained could be used in conservation and sustainable development policies.

Irene Vega

Global warming is significantly affecting ecosystems, including high mountain biosphere reserves in Spain. The study of these protected areas using time series of indices is scarce and restricts existing knowledge on plant trends in these environments.

Scientists from the URJC's Research Group on Technologies for Landscape Analysis and Diagnosis (TADAT) have analysed the high mountain Biosphere Reserves in Spain (Ordesa-Viñamala and Sierra Nevada), between 2001 and 2016, using remote monitoring techniques, such as the Normalized Difference Vegetation Index (NDVI).

The results of the study, published in the journal Journal of Environmental Management, show significant differences in the vegetation index (NDVI) trends between both reserves. On the one hand, Ordesa-Viñamala presented a greater number of positive trends in vegetation, while in Sierra Nevada, on the contrary, negative NDVI trends predominated. “The positive trends in Ordesa-Viñamala are related to a moderate increase in temperatures, which favors plant growth. The increase in NDVI is especially noticeable in areas far from populated centers and at higher altitudes, suggesting that these areas are less impacted by human activities and more benefited by more stable climatic conditions,” explains Patricia Arrogante, researcher in the TADAT group and co-author of the study.

In the Sierra Nevada Biosphere Reserve, the results reveal that rising temperatures and decreasing precipitation have intensified droughts, which has negatively affected vegetation, especially in wetlands and agricultural areas. “The areas closest to population centres also show a greater decrease in vegetation, possibly due to increased human activity,” says Adrián García Bruzón, also a researcher in the TADAT group and co-author of the study. “These results are important because they underline how climate change is affecting these reserves differently, which could require different management strategies for each one,” he adds.

Furthermore, the study highlights the value of remote sensing tools and geographic information systems (GIS) for long-term monitoring, which is essential to prioritize conservation and sustainable development in these protected areas. “This study supports better management of natural resources and favors the creation of policies that can adapt to local realities in a climate change scenario,” concludes the URJC researcher.

New technologies to observe plant trends

To conduct this analysis, satellite images were first taken to measure vegetation health over time. These images were then processed with special software to clean the data and ensure it was accurate, removing errors or outliers that could distort the results.

Once the data was ready, the researchers wanted to know whether vegetation had increased or decreased in those reserves. To do so, they applied some statistical tests that helped them see if the observed changes were significant. They also calculated how much vegetation had changed in each area using the Normalized Vegetation Index (NDVI).

The study then focused on understanding why vegetation had changed. “To do this, we analysed different factors such as temperature, water availability, altitude of the areas and distance from urban centres. Using other statistical analyses, we checked whether these environmental factors were related to changes in vegetation,” explains Adrián García Bruzón.

Regarding the tools used, vegetation information came from high-resolution satellite images, while terrain and climate data were obtained from public databases and processed with a platform called Google Earth Engine, which facilitated the analysis of large amounts of climate and soil data.