Assessing climate change impacts on the geographical distribution of Cupressus sempervirens in the Mediterranean region.

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Název: Assessing climate change impacts on the geographical distribution of Cupressus sempervirens in the Mediterranean region.
Autoři: Behroozian, Maryam, Amini, Tayebeh, Zare, Habib, Ejtehadi, Hamid
Zdroj: Scientific Reports; 11/17/2025, Vol. 15 Issue 1, p1-12, 12p
Témata: CLIMATE change, ECOLOGICAL niche, SOCIOECONOMIC factors, CUPRESSACEAE, HISTORY of the Mediterranean Region, HABITAT selection, SPATIAL analysis (Statistics), CONSERVATION projects (Natural resources)
Geografický termín: MEDITERRANEAN Sea
Abstrakt: Cupressus sempervirens L., a long-lived conifer of the Cupressaceae family, plays a vital ecological, medicinal, and economic role in the Mediterranean basin. Due to the species' sensitivity to climatic fluctuations, particularly temperature and precipitation regimes, understanding its potential distributional shifts under climate change is critical. This study employs ecological niche modeling to quantify the current and future potential geographic distribution of C. sempervirens under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) for the mid-twenty-first century (2041–2060). Model outputs identified mean diurnal range (bio2), precipitation seasonality (bio15), and annual precipitation (bio12) as key determinants of habitat suitability. Presently, suitable habitats are concentrated throughout the Mediterranean region, with moderate suitability extending into the Euro-Siberian and Irano-Turanian domains. Future climate projections indicated an expansion of climatically suitable areas, most consistently within the Mediterranean basin, where predictions showed higher reliability, whereas additional gains in northern regions (e.g., around the Caspian and Black seas) were associated with greater model uncertainty, reflecting overall increases in suitable habitat of 14.7% under SSP2-4.5 and 16.4% under SSP5-8.5. These findings provide critical insights for developing effective monitoring frameworks and conservation strategies to enhance the resilience and adaptive capacity of C. sempervirens populations amid ongoing climate change. [ABSTRACT FROM AUTHOR]
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  Data: Assessing climate change impacts on the geographical distribution of Cupressus sempervirens in the Mediterranean region.
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  Data: Cupressus sempervirens L., a long-lived conifer of the Cupressaceae family, plays a vital ecological, medicinal, and economic role in the Mediterranean basin. Due to the species' sensitivity to climatic fluctuations, particularly temperature and precipitation regimes, understanding its potential distributional shifts under climate change is critical. This study employs ecological niche modeling to quantify the current and future potential geographic distribution of C. sempervirens under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) for the mid-twenty-first century (2041–2060). Model outputs identified mean diurnal range (bio2), precipitation seasonality (bio15), and annual precipitation (bio12) as key determinants of habitat suitability. Presently, suitable habitats are concentrated throughout the Mediterranean region, with moderate suitability extending into the Euro-Siberian and Irano-Turanian domains. Future climate projections indicated an expansion of climatically suitable areas, most consistently within the Mediterranean basin, where predictions showed higher reliability, whereas additional gains in northern regions (e.g., around the Caspian and Black seas) were associated with greater model uncertainty, reflecting overall increases in suitable habitat of 14.7% under SSP2-4.5 and 16.4% under SSP5-8.5. These findings provide critical insights for developing effective monitoring frameworks and conservation strategies to enhance the resilience and adaptive capacity of C. sempervirens populations amid ongoing climate change. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Scientific Reports is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 11/17/2025
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