Discovering the rules of plant biogeography using a trait-based approach

Abstract

Lineage-specific traits determine how plants interact with their surrounding environment. As different species may find similar phenotypic solutions through evolution to tolerate, persist in and invade environments with certain characteristics, some traits may become more common in certain types of habitats. These general patterns of geographical trait distribution point towards the existence of some rules in how plants diversify in space over time. Trait-environment correlation analyses are ways to discover general rules in plant biogeography by quantifying to what extent unrelated lineages have similar evolutionary responses to a given type of habitat. In this synthesis, I give a short historical overview on trait-environment correlation analyses, from some key observations from classic naturalists to modern approaches using trait evolution models, large phylogenies, and massive datasets of traits and distributions. I discuss some limitations of modern approaches, including the need for more realistic models, the lack of data from tropical areas, and the necessary focus on trait scoring that goes beyond macro-morphology. Overcoming these limitations will allow the field to explore new questions related to trait lability and niche evolution and to better set apart rules and exceptions in how plants diversify in space over time.

Long-term responses of life-history strategies to climatic variability in flowering plants

“…For example, in comparative biology, studies examining large phylogenies usually have little power to determine specific mechanisms underpinning evolutionary patterns (Donoghue and Edwards 2019), while small-scale studies of specific clades, for various reasons, are often limited in their ability to explain broad evolutionary patterns (Beaulieu and O’Meara 2018, 2019). The multi-clade approach we used for this work, which allowed us to examine broad patterns as well as make inferences about the causes of clade-specific patterns, aims to combine the advantages of both large- and small-scale studies (Vasconcelos 2022). Due to their advantages, multi-clade studies have recently become popular in comparative biology (e.g., Mayrose et al 2011, 2015; Vasconcelos et al 2020, 2021; Miller et al 2021).…”

The global distribution of angiosperm genome size is shaped by climate

“…We compiled the largest genome size dataset to date, encompassing > 5% of known angiosperm species (Dataset S1). Large datasets of phylogenetic representation and traits, including genome size data, are latitudinally biased, with northern latitudes being more thoroughly sampled (Vasconcelos, 2022). To check how this may have affected our data, we compared the across-TDWG latitudinal distribution of range sizes of all angiosperms in the WCVP to that of the taxa in our genome size dataset.…”