Pandey Bikram, Khatiwada Janak R, Zhang Lin, Pan Kaiwen, Dakhil Mohammed A, Xiong Qinli, Yadav Ram Kailash P, Siwakoti Mohan, Tariq Akash, Olatunji Olusanya Abiodun, Justine Meta Francis, Wu Xiaogang, Sun Xiaoming, Liao Ziyan, Negesse Zebene Tadesse
CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration Biodiversity Conservation Key Laboratory of Sichuan Province Chengdu Institute of Biology Chinese Academy of Sciences Chengdu China.
University of Chinese Academy of Sciences Beijing China.
Ecol Evol. 2020 Aug 8;10(17):9474-9485. doi: 10.1002/ece3.6639. eCollection 2020 Sep.
Studying the pattern of species richness is crucial in understanding the diversity and distribution of organisms in the earth. Climate and human influences are the major driving factors that directly influence the large-scale distributions of plant species, including gymnosperms. Understanding how gymnosperms respond to climate, topography, and human-induced changes is useful in predicting the impacts of global change. Here, we attempt to evaluate how climatic and human-induced processes could affect the spatial richness patterns of gymnosperms in China. Initially, we divided a map of the country into grid cells of 50 × 50 km spatial resolution and plotted the geographical coordinate distribution occurrence of 236 native gymnosperm taxa. The gymnosperm taxa were separated into three response variables: (a) all species, (b) endemic species, and (c) nonendemic species, based on their distribution. The species richness patterns of these response variables to four predictor sets were also evaluated: (a) energy-water, (b) climatic seasonality, (c) habitat heterogeneity, and (d) human influences. We performed generalized linear models (GLMs) and variation partitioning analyses to determine the effect of predictors on spatial richness patterns. The results showed that the distribution pattern of species richness was highest in the southwestern mountainous area and Taiwan in China. We found a significant relationship between the predictor variable set and species richness pattern. Further, our findings provide evidence that climatic seasonality is the most important factor in explaining distinct fractions of variations in the species richness patterns of all studied response variables. Moreover, it was found that energy-water was the best predictor set to determine the richness pattern of all species and endemic species, while habitat heterogeneity has a better influence on nonendemic species. Therefore, we conclude that with the current climate fluctuations as a result of climate change and increasing human activities, gymnosperms might face a high risk of extinction.
研究物种丰富度模式对于理解地球上生物的多样性和分布至关重要。气候和人类影响是直接影响植物物种(包括裸子植物)大规模分布的主要驱动因素。了解裸子植物如何应对气候、地形和人为引起的变化,有助于预测全球变化的影响。在此,我们试图评估气候和人为过程如何影响中国裸子植物的空间丰富度模式。首先,我们将中国地图划分为空间分辨率为50×50千米的网格单元,并绘制了236种本土裸子植物分类群的地理坐标分布情况。根据裸子植物分类群的分布,将其分为三个响应变量:(a)所有物种,(b)特有物种,(c)非特有物种。还评估了这些响应变量对四组预测因子的物种丰富度模式:(a)能量 - 水分,(b)气候季节性,(c)生境异质性,(d)人类影响。我们进行了广义线性模型(GLMs)和变异分解分析,以确定预测因子对空间丰富度模式的影响。结果表明,物种丰富度的分布模式在中国西南部山区和台湾地区最高。我们发现预测变量集与物种丰富度模式之间存在显著关系。此外,我们的研究结果表明,气候季节性是解释所有研究响应变量物种丰富度模式中不同变异部分的最重要因素。此外,发现能量 - 水分是确定所有物种和特有物种丰富度模式的最佳预测因子集,而生境异质性对非特有物种有更好的影响。因此,我们得出结论,由于气候变化导致的当前气候波动以及人类活动的增加,裸子植物可能面临高度灭绝风险。