Ecological Stress Assessment on Vegetation in the Al-Baha Highlands, Saudi Arabia (1991–2023)
Climate change significantly stresses cold-adapted and stenothermic plant species in high-altitude mountain ecosystems. The diverse plant species at elevations ranging from 1324 to 2527 m above mean sea level (AMSL) provide an ideal setting for investigating these impacts in the Al-Baha Highlands, Saudi Arabia. Therefore, this study has three aims: first, to estimate vegetation cover in 2023 and its relationship with environmental factors; second, to analyze long-term trends (1991–2023) in key spectral indices, including the normalized difference vegetation index (NDVI), normalized difference vegetation water index (NDWI), normalized difference open water index (NDWIw), and land surface temperature (LST), using the Kendall tau-b method; and third, to model ecological stress via a generalized additive model (GAM) and assess its impact on vegetation. We utilized Landsat 5/7/8 (C2 SR T1) for spectral indices and the Copernicus DEM for topographic and hydrological analysis. The results indicate significant roles of LST, elevation, and distance from seasonal streams in shaping vegetation patterns (p < 2 × 10−16). There were negative trends in the NDVI (91.66 km2), NDWI (138 km2), and NDWIw (804 km2) (p < 0.05), whereas the LST exhibited positive trends (116.15 km2) (p < 0.05). The GAM achieved high predictive accuracy (R2 = 0.979), capturing nonlinear relationships between the predictors and the stress score. Severe ecological stress occurred in high-altitude zones (>1700 m AMSL) on south-facing slopes due to increased LST and declining NDWI, impacting species such as Juniperus procera. Hypothesis testing was used to assess variations in the NDVI, its long-term trends, and ecological stress between highland and lower-elevation areas, revealing highly significant differences (p < 2.2 × 10−16). This study provides novel insights into ecological stress dynamics in relation to altitude and slope aspects, offering actionable recommendations for sustainable ecosystem management, including targeted reforestation and water resource optimization to mitigate stress and preserve biodiversity.
Authors
- Zubairul Islam (ORCID: https://orcid.org/0000-0002-6591-2241)
- Asma A. Al‐Huqail
Institutions
- King Saud University (SA)
- University of Abuja (NG)
Publication Details
- Journal
- Sustainability
- Published
- 2025-03-24
- DOI
- https://doi.org/10.3390/su17072854
- Citations
- 1
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 1.72
Funders
- Deanship of Scientific Research, King Saud University