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<p><i>Quercus mongolica</i>, a vital species in temperate forests, is facing significant shifts in its range due to climate change. This study aims to model and project the potential distribution of <i>Q. mongolica</i> for past, present and future climate scenarios by using different climate models and shared socio-economic pathways (SSPs). Climate data from the Last Glacial Maximum (LGM) and future scenarios (RCPs 245 and 585) were used to develop an ensemble of species distribution models (SDMs). Four modelling algorithms—Random Forest, Boosted Regression Trees, Generalised Additive Model and Maximum Entropy—were used to create an ensemble SDM. These models assessed the effects of environmental variables on the distribution of <i>Q. mongolica</i>. The results show that the climatic niche of <i>Q. mongolica</i> has declined significantly since the current period, with a higher risk under more extreme gas emissions scenarios. The most important environmental factors influencing the distribution of <i>Q. mongolica</i> are the average temperature of the wettest quarter (bio8) and the rainfall of the wettest month (bio13). These variables consistently influenced habitat suitability in all models. The results emphasise the importance of climate-adapted conservation strategies, as continued habitat loss could endanger the species. By comparing different projected areas, the study provides important insights for conservation biology and emphasises the need for adaptive management to protect suitable climate-sensitive areas for species such as <i>Q. mongolica</i>.</p>

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Potential distribution and ecological niche of Quercus mongolica under different climate scenarios

  • 期刊论文

  • 发表日期：

    2025年5月2日

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  • David Kombi Kaviriri,
  • Tianyi Liu,
  • Ling Yang

摘要

Quercus mongolica, a vital species in temperate forests, is facing significant shifts in its range due to climate change. This study aims to model and project the potential distribution of Q. mongolica for past, present and future climate scenarios by using different climate models and shared socio-economic pathways (SSPs). Climate data from the Last Glacial Maximum (LGM) and future scenarios (RCPs 245 and 585) were used to develop an ensemble of species distribution models (SDMs). Four modelling algorithms—Random Forest, Boosted Regression Trees, Generalised Additive Model and Maximum Entropy—were used to create an ensemble SDM. These models assessed the effects of environmental variables on the distribution of Q. mongolica. The results show that the climatic niche of Q. mongolica has declined significantly since the current period, with a higher risk under more extreme gas emissions scenarios. The most important environmental factors influencing the distribution of Q. mongolica are the average temperature of the wettest quarter (bio8) and the rainfall of the wettest month (bio13). These variables consistently influenced habitat suitability in all models. The results emphasise the importance of climate-adapted conservation strategies, as continued habitat loss could endanger the species. By comparing different projected areas, the study provides important insights for conservation biology and emphasises the need for adaptive management to protect suitable climate-sensitive areas for species such as Q. mongolica.