Ontogenetic trait variation and metacommunity effects influence species relative abundances during tree community assembly

作者：He, Yun-Yun; Srisombut, Kwansupa; Xing, Ding-Liang; Swenson, Nanthan G.; Asefa, Mengesha; Cao, Min; Song, Xiao-Yang; Wen, Han-Dong; Yang, Jie^*

来源：Plant Diversity, 2022, 44(4): 360-368.

DOI：10.1016/j.pld.2021.09.002

• Metacommunity
• Maximum entropy
• Ontogenetic trait variation
• Community assembly
• Trait-selected process

Predicting species abundance is one of the most fundamental pursuits of ecology. Combining the in-formation encoded in functional traits and metacommunities provides a new perspective to predict the abundance of species in communities. We applied a community assembly via trait selection model to predict quadrat-scale species abundances using functional trait variation on ontogenetic stages and metacommunity information for over 490 plant species in a subtropical forest and a lowland tropical forest in Yunnan, China. The relative importance of trait-based selection, mass effects, and stochasticity in shaping local species abundances is evaluated using different null models. We found both mass effects and trait selection contribute to local abundance patterns. Trait selection was detectable at all studied spatial scales (0.04-1 ha), with its strength stronger at larger scales and in the subtropical forest. In contrast, the importance of stochasticity decreased with spatial scale. A significant mass effect of the metacommunity was observed at small spatial scales. Our results indicate that tree community assembly is primarily driven by ontogenetic traits and metacommunity effects. Our findings also demonstrate that including ontogenetic trait variation into predictive frameworks allows ecologists to infer ecological mechanisms operating in community assembly at the individual level.Copyright (c) 2021 Kunming Institute of Botany, Chinese Academy of Sciences. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY -NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

• 单位
  中国科学院研究生院