Life history is a key driver of temporal fluctuations in tropical tree abundances

• 成果类型: Article
• 署名作者: Jops, Kenneth; Dalling, James W.; O'Dwyer, James P.
• 署名单位: University of Illinois System; University of Illinois Urbana-Champaign; Smithsonian Institution; Smithsonian Tropical Research Institute; University of Illinois System; University of Illinois Urbana-Champaign
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-10384
• DOI: 10.1073/pnas.2422348122
• 发表日期: 2025-01-24
• 关键词: relative species abundance; within-generation variance; neutral theory; environmental stochasticity; forest biodiversity; functional traits; natural-selection; beta-diversity; CLIMATE-CHANGE; patterns

摘要

The question of what mechanisms maintain tropical biodiversity is a critical frontier in ecology, intensified by the heightened risk of biodiversity loss faced in tropical regions. Ecological theory has shed light on multiple mechanisms that could lead to the high levels of biodiversity in tropical forests. But variation in species abundances over time may be just as important as overall biodiversity, with a more immediate connection to the risk of extirpation and biodiversity loss. Despite the urgency, our understanding of the primary mechanisms driving fluctuations in species abundances has not been clearly established. Here, we introduce a theoretical framework based around life history; the schedule of birth, growth, and mortality over a lifespan, and its systematic variation across species. We develop a mean field model to predict expected fluctuations in abundance for a focal species in a larger community, and we quantify empirical life history variation among 90 tropical forest species in a 50 ha plot in Panama. Putting theory and data together, we show that life history provides a critical piece of this puzzle, allowing us to explain patterns of abundance fluctuations more accurately than previous models incorporating demographic stochasticity without life history variation, and without introducing unobserved couplings between species and their environment. This framework provides a starting point for more general models that incorporate multiple factors in addition to life history variation, and suggests the potential for a fine-grained assessment of extirpation risk based on the impacts of anthropogenic change on demographic rates across life stages.