Pandey Bikram, Nepal Nirdesh, Tripathi Salina, Pan Kaiwen, Dakhil Mohammed A, Timilsina Arbindra, Justine Meta F, Koirala Saroj, Nepali Kamal B
CAS Key Laboratory of Mountain Ecological Restoration and Bio-Resource Utilization and Ecological Restoration Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Plants (Basel). 2020 May 14;9(5):625. doi: 10.3390/plants9050625.
Understanding the pattern of species distribution and the underlying mechanism is essential for conservation planning. Several climatic variables determine the species diversity, and the dependency of species on climate motivates ecologists and bio-geographers to explain the richness patterns along with elevation and environmental correlates. We used interpolated elevational distribution data to examine the relative importance of climatic variables in determining the species richness pattern of 26 species of gymnosperms in the longest elevation gradients in the world. Thirteen environmental variables were divided into three predictors set representing each hypothesis model (energy-water, physical-tolerance, and climatic-seasonality); to explain the species richness pattern of gymnosperms along the elevational gradient. We performed generalized linear models and variation partitioning to evaluate the relevant role of environmental variables on species richness patterns. Our findings showed that the gymnosperms' richness formed a hump-shaped distribution pattern. The individual effect of energy-water predictor set was identified as the primary determinant of species richness. While, the joint effects of energy-water and physical-tolerance predictors have explained highest variations in gymnosperm distribution. The multiple environmental indicators are essential drivers of species distribution and have direct implications in understanding the effect of climate change on the species richness pattern.
了解物种分布模式及其潜在机制对于保护规划至关重要。几个气候变量决定了物种多样性，物种对气候的依赖性促使生态学家和生物地理学家解释物种丰富度模式以及海拔和环境相关性。我们使用插值海拔分布数据来检验气候变量在确定世界上最长海拔梯度上26种裸子植物物种丰富度模式中的相对重要性。13个环境变量被分为三个预测变量集，分别代表每个假设模型（能量 - 水分、物理耐受性和气候季节性）；以解释裸子植物沿海拔梯度的物种丰富度模式。我们进行了广义线性模型和变异分解，以评估环境变量对物种丰富度模式的相关作用。我们的研究结果表明，裸子植物的丰富度形成了驼峰状分布模式。能量 - 水分预测变量集的个体效应被确定为物种丰富度的主要决定因素。同时，能量 - 水分和物理耐受性预测变量的联合效应解释了裸子植物分布中最高的变异。多个环境指标是物种分布的重要驱动因素，对理解气候变化对物种丰富度模式的影响具有直接意义。
