Pandey Bikram, Zhang Fengying, Poudel Basu Dev, Li Rong, Dakhil Mohammed A, Gurung Bishal, Luobu Zhaxi, Gan Yawen, Liao Ziyan, Zhang Lin
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, Sichuan, China.
CAS Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, Yunnan, China.
Heliyon. 2024 Dec 31;11(2):e41474. doi: 10.1016/j.heliyon.2024.e41474. eCollection 2025 Jan 30.
Macroecological research aims to understand factors influencing species composition and diversity. Understanding the distribution patterns of species is essential for prioritizing areas for conservation. This study investigates the alpha () and beta () diversity facets of Fagaceae across past (historical), present, and future timelines in Southwestern China. We used over 11,000 geographical observations to predict the spatial patterns of the - and -diversity of 120 species. We modeled the -diversity via stacking prediction using an individual species distribution model at 50 km × 50 km grid cells. We used Sørensen dissimilarity to quantify total -diversity and its components - turnover ( ) and nestedness ( ). We integrated climate variables along with topographic and plant trait predictors to understand the species diversity. Finally, simultaneous autoregression (SAR) model was used to evaluate the effects of predictor variables on the - and -diversity patterns. Our results indicate a projected decline in α-diversity and an increase in β-diversity in the future. The findings underscore that the species is a driving factor of differing species composition during the past and present periods, while will be a dominant factor in the future. Similarly, climatic and topographic factors significantly influenced the diversity and the -diversity. In the future, climatic variables will play a significant role in determining the diversity patterns. By closely studying how various species respond and adapt to these changes, we can gain valuable insights into the dynamics of ecosystems and the potential threats to biodiversity.
宏观生态研究旨在了解影响物种组成和多样性的因素。了解物种的分布模式对于确定保护区域的优先级至关重要。本研究调查了中国西南地区过去(历史时期)、现在和未来时间线内壳斗科的α多样性和β多样性方面。我们使用了超过11000个地理观测数据来预测120个物种的α多样性和β多样性的空间模式。我们通过在50千米×50千米的网格单元上使用单个物种分布模型进行堆叠预测来模拟β多样性。我们使用 Sørensen 相异度来量化总β多样性及其组成部分——周转率(β turnover)和嵌套性(nestedness)。我们整合了气候变量以及地形和植物性状预测因子来了解物种多样性。最后,使用同步自回归(SAR)模型来评估预测变量对α多样性和β多样性模式的影响。我们的结果表明,未来α多样性预计会下降,β多样性会增加。研究结果强调,物种更替在过去和现在时期是导致物种组成差异的驱动因素,而在未来,环境过滤将成为主导因素。同样,气候和地形因素对α多样性和β多样性有显著影响。在未来,气候变量将在决定多样性模式方面发挥重要作用。通过密切研究各种物种如何对这些变化做出反应和适应,我们可以深入了解生态系统的动态以及生物多样性面临的潜在威胁。