From α-to β-diversity: Understanding the historical, present, and future diversity patterns of Fagaceae in Southwestern China
Year: 2024
Type: article
Abstract: 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 ( α ) and beta ( β ) 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 α - and β -diversity of 120 species. We modeled the α -diversity via stacking prediction using an individual species distribution model at 50 km × 50 km grid cells. We used Sørensen dissimilarity to quantify total β -diversity and its components - turnover ( β SIM ) and nestedness ( β NES ). 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 α - and β -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 β SIM is a driving factor of differing species composition during the past and present periods, while β NES will be a dominant factor in the future. Similarly, climatic and topographic factors significantly influenced the α- diversity and the β -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.
Source: Heliyon
Authors: Bikram Pandey, Fengying Zhang, Basu Dev Poudel, Rong Li, Mohammed A. Dakhil, Bishal Gurung, Zhaxi Luobu, Yawen Gan, Ziyan Liao, Lin Zhang
Language: English
Subfield: Ecological Modeling
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $2,100
Awards: G2951890624, G5002046385, G56370659, G821667392
OpenAlex ID: W4405961998
