Modeling Climate‐Driven Vegetation Changes Under Contrasting Temperate and Arid Conditions in the Mediterranean Basin

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 1, 2025

ABSTRACT This study investigates climate change impacts on spontaneous vegetation, focusing the Mediterranean basin, a hotspot for climatic changes. Two case areas, Monti Sibillini (central Italy, temperate) and Sidi Makhlouf (Southern Tunisia, arid), were selected their contrasting climates vegetation. Using WorldClim's CMCC‐ESM2 model, future vegetation distribution was predicted 2050 2080 under SSP 245 (optimistic) 585 (pessimistic) scenarios. spectral indices, NDVI (temperate area) SAVI (arid area), served as proxies, classified into three classes using K‐means (NDVI: high = mainly associated with woodlands, medium shrublands, continuous grasslands crops, low discontinuous grasslands, bare soil, rocks; SAVI: woods, olive trees, shrublands sparse soil saline areas). Classes validated ESA WorldCover 2020 data sampled via 1390 presence‐only points. A set of 33 environmental variables (topography, bioclimatic) screened Pearson correlation matrices, predictive models built four algorithms: MaxEnt, Random Forest, XG Boost, Neural Network. Results revealed increasing temperatures declining precipitation in both regions, confirming trends. Vegetation changes varied by area: temperate area, woodlands stable, but expanded. In arid gained suitable habitat, while declined pessimistic scenario. Both areas showed an upward shift grasslands. The indicated significant shifts areal conditions, affecting habitat suitability ecosystem dynamics. MaxEnt emerged most reliable algorithm small datasets, effectively predicting suitability. findings highlight redistribution altered dynamics due to change, underscoring importance these planning ecological challenges.

Language: Английский

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Prediction and Influencing Factors of Precipitation in the Songliao River Basin, China: Insights from CMIP6

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 2297 - 2297

Published: March 6, 2025

The Songliao River Basin (SLRB) is a key agricultural region in China, and understanding precipitation variations can provide crucial support for water resource management sustainable development. This study used CN05.1 observational data the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate evaluate characteristics within SLRB. optimal model ensemble was selected future predictions. We analyzed historical SLRB projected under SSP126, SSP245, SSP585, while exploring driving factors influencing precipitation. results indicated that EC-Earth3-Veg (0.507) BCC-CSM2-MR (0.493) from MME2 effectively capture variations, with corrected more closely matching actual characteristics. From 1971 2014, showed an insignificant increasing trend, most concentrated between May September. Precipitation basin decreased southeast northwest. 2026 2100, trend became significant. of growth over time as follows: SSP126 < SSP245 SSP585. Future distribution resembled period, but area semiarid regions gradually humid increased, particularly long-term increase will become pronounced, significant expansion high-precipitation areas. In low-latitude, high-longitude areas, events were expected occur, impact altitude relatively weaker. response changes temperature shifts negative positive. Under this becomes average by 4.87% every 1 °C rise temperature.

Language: Английский

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A new statistical framework for future drought assessment – mutual information-based regional integrated standardized multicriteria decision for drought assessment

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(6)

Published: May 16, 2025

Language: Английский

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Climate model evaluation studies in ethiopia: a systematic review

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(6)

Published: June 1, 2025

Language: Английский

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Performance evaluation and ranking of CMIP6 global climate models over upper blue nile (abbay) basin of Ethiopia

Natural Hazards Research, Journal Year: 2024, Volume and Issue: unknown

Published: June 1, 2024

The use of Global Climate Models (GCMs) data is the most practical way to conduct studies on climate science. However, performance evaluation and selection appropriate GCMs are vital. In this research, effectiveness eight selected CMIP6 in simulating annual seasonal rainfall observed over Ethiopian Upper Blue Nile Basin from 1988 2014 was assessed. Five metrics (PMs) were used study: correlation coefficient, root mean square error, bias percentage, Kling-Gupta efficiency Nash-Sutcliffe efficiency. scores various PMs then combined into one, ranked using Compromised Programming (CP). findings CP verified a spatial, Taylor Diagram (TD), areal average evaluations. Even though produced some contradicting results, study exhibited that capable evaluate consistently. A regional relative revealed best-ranked by more accurately replicate rainfall. lowest-ranking found have either spatially overvalued or undervalued amount basin. best three for rainfall, according results method, BCC-CSM2-MR, MIROC6, NorESM2-MM; Kiremt season, GISS-E2-2-G, EC-Earth3. INM-CM5-0, MRI-ESM2-0 highest Bega EC-Earth3, Belg season. It recommended above-ranked predict characteristics UBNB. Furthermore, suggest be evaluated with range across whole temporal scales techniques such as identify best-performing GCMs.

Language: Английский

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Climate and Land Use Change Impacts on Groundwater Recharge in Prachinburi–Sakaeo Groundwater Basin by Integrating the CA–Markov Model with the WetSpass Model

Earth Systems and Environment, Journal Year: 2024, Volume and Issue: 8(4), P. 1179 - 1206

Published: Aug. 27, 2024

Language: Английский

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