Zhang Keliang, Liu Huina, Pan Haolei, Shi Wenhao, Zhao Yi, Li Silei, Liu Junchi, Tao Jun
Jiangsu Key Laboratory of Crop Genetics and Physiology College of Horticulture and Plant Protection Yangzhou University Yangzhou China.
Ecol Evol. 2020 Apr 6;10(11):4828-4837. doi: 10.1002/ece3.6236. eCollection 2020 Jun.
Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. is a common fast-growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of can provide reference for the development of forest management and protection strategies.
气候变化对生物多样性构成严重威胁。预测气候变化对物种栖息地分布的影响有助于人类应对可能改变物种范围和分布的潜在威胁。[具体树种名称]是一种常见的速生树种，常用于中国中部和东部河岸及高山森林的生态恢复。到目前为止，该物种栖息地分布的特征以及影响其适宜栖息地的环境因素都鲜为人知。在本研究中，通过选择236个已知出现地点和14个环境变量，利用最大熵建模（Maxent）算法和规则集生成遗传算法（GARP）建立了该物种潜在分布模型。结果表明，这两种模型都具有良好的预测能力。最冷月最低温度（Bio6）、最暖季平均温度（Bio10）、年降水量（Bio12）和最干月降水量（Bio14）是影响Maxent模型预测的重要环境变量。根据模型，中国东部的温带和亚热带地区对该物种具有较高的环境适宜性，该物种在这些地区有记录。在每种气候变化情景下，该物种现有分布范围的气候适宜性增加，其气候生态位在地理上向北和更高海拔扩展。GARP预测的扩展更为保守。[具体树种名称]预测的时空模式可为森林管理和保护策略的制定提供参考。
