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<p>Habitat suitability models are widely used to estimate the potential distribution of species under current and future environmental conditions. In this study, the IPSL-CM6A-LR model and climate scenarios from the CMIP6 were employed to simulate future climate conditions. Using MaxEnt modeling, the future distributions of five dominant tree species (<i>Pinus nigra</i>,<i> Abies nordmanniana</i>,<i> Fagus orientalis</i>,<i> Quercus</i> spp., and <i>Pinus sylvestris</i>) in the Western Black Sea region were projected for the years 2030, 2050, 2070, and 2090 under the Shared Socioeconomic Pathways SSP 2-4.5 and SSP 5-8.5. Results under the SSP 2-4.5 scenario indicated a general loss of suitable habitats for all species, with <i>Quercus</i> spp. showing the highest reduction (6.1%), whereas very suitable zones increased for most species except <i>Pinus nigra</i>, which declined by 4.3%. Under the SSP 5-8.5 scenario, only <i>Abies nordmanniana</i> exhibited an increase (5%) in suitable habitat, while other species experienced contractions, resulting in a net loss of 12.3%; nevertheless, very suitable areas increased overall by 7.3%. In addition, this study assessed both current and future potential species mixtures by identifying stand-type combinations derived from overlapping suitable habitats. While <i>Fagus orientalis</i> and <i>Quercus</i> spp. currently dominate mixed stands, future projections suggest increasing overlap between <i>Abies nordmanniana</i> and <i>Pinus sylvestris</i>, particularly under SSP 5-8.5. Overall, species exhibited distinct and contrasting responses to future climate conditions across both scenarios. Variable importance analyses revealed that temperature seasonality, precipitation of the driest month, and isothermality were the primary environmental drivers shaping the current and future distributions of the studied tree species. Such analysis of dynamic species associations has not been previously addressed in the literature at this scale. By integrating spatial species distribution modeling with forest stand-type composition analysis, this study provides novel insights into how climate change may reshape forest structure and biodiversity, offering critical guidance for adaptive forest planning, conservation strategies, and the sustainable management of forest ecosystems under changing climatic conditions.</p>

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Projected future distributions of dominant tree species in the Western Black Sea region under climate change scenarios

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  • 发表日期：

    2026年3月25日

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  • Ahmet Salih Değermenci

摘要

Habitat suitability models are widely used to estimate the potential distribution of species under current and future environmental conditions. In this study, the IPSL-CM6A-LR model and climate scenarios from the CMIP6 were employed to simulate future climate conditions. Using MaxEnt modeling, the future distributions of five dominant tree species (Pinus nigra, Abies nordmanniana, Fagus orientalis, Quercus spp., and Pinus sylvestris) in the Western Black Sea region were projected for the years 2030, 2050, 2070, and 2090 under the Shared Socioeconomic Pathways SSP 2-4.5 and SSP 5-8.5. Results under the SSP 2-4.5 scenario indicated a general loss of suitable habitats for all species, with Quercus spp. showing the highest reduction (6.1%), whereas very suitable zones increased for most species except Pinus nigra, which declined by 4.3%. Under the SSP 5-8.5 scenario, only Abies nordmanniana exhibited an increase (5%) in suitable habitat, while other species experienced contractions, resulting in a net loss of 12.3%; nevertheless, very suitable areas increased overall by 7.3%. In addition, this study assessed both current and future potential species mixtures by identifying stand-type combinations derived from overlapping suitable habitats. While Fagus orientalis and Quercus spp. currently dominate mixed stands, future projections suggest increasing overlap between Abies nordmanniana and Pinus sylvestris, particularly under SSP 5-8.5. Overall, species exhibited distinct and contrasting responses to future climate conditions across both scenarios. Variable importance analyses revealed that temperature seasonality, precipitation of the driest month, and isothermality were the primary environmental drivers shaping the current and future distributions of the studied tree species. Such analysis of dynamic species associations has not been previously addressed in the literature at this scale. By integrating spatial species distribution modeling with forest stand-type composition analysis, this study provides novel insights into how climate change may reshape forest structure and biodiversity, offering critical guidance for adaptive forest planning, conservation strategies, and the sustainable management of forest ecosystems under changing climatic conditions.