Matthews, T. J. | Search bioRxiv

bioRxiv2024

The biogeography of evolutionary radiations on oceanic archipelagos

Evolutionary radiations on oceanic archipelagos (ROAs) have long served as models for understanding evolutionary and ecological processes underlying species diversification. Yet, diversity patterns emerging from ROAs have received relatively little attention from biogeographers, even though characterizing the effect of key geo-environmental factors on island clades species distribution could be important for unraveling diversification dynamics. In this study, we conducted a comparative analysis using island-specific species richness values for approximately one hundred ROAs across major oceanic archipelagos (mostly Hawaii, Canary Islands, Galapagos and Fiji) and taxa (vascular plants, invertebrates and vertebrates). Our aim was to determine whether (1) ROA species richness patterns scale as a function of key geo-environmental factors including island area, geological age, environmental heterogeneity (elevation and topographic complexity) and inter-island isolation, and (2) whether the magnitude of the effects of these factors varies across archipelagos and taxa. Our results identified elevation as a key driver of ROA species richness patterns on islands, supporting existing theoretical and empirical work that highlighted the central role of environmental heterogeneity in driving diversification on oceanic islands. As importantly, we found that the influence of geo-environmental factors varies across archipelagos and taxa, suggesting that unique archipelagic dynamics and biological traits together shape diversification differently. Our findings emphasize the value of applying biogeographical modeling at the resolution of individual radiations to improve our understanding of evolutionary processes on oceanic archipelagos.

evolutionary biology↗

bioRxiv2024

The what, how and why of trait-based analyses in ecology

Functional diversity is increasingly used alongside taxonomic diversity to describe populations and communities in ecology. Indeed, functional diversity metrics allow researchers to summarize complex occupancy patterns in space and/or time (what is changing?) that lead to changes in communities and/or populations (the process; how is it changing?) in response to some stressors (the mechanism; why is it changing?). However, as the diversity of functional diversity metrics and methods increases, it is often not directly clear which metric is more readily appropriate for which question. We studied the ability of different functional diversity metrics to recover patterns and signals from different processes linked to common assembly mechanisms (environmental filtering, competitive exclusion, equalizing fitness, and facilitation) in community ecology. Using both simulated data and an empirical dataset affected by more complex and nuanced mechanisms, we tested the effectiveness of different space occupancy metrics to recover the simulated or empirical changes. We show that different metrics perform better for different tasks, emphasizing the importance of not using a one-size-fits-all metric. Instead, researchers should carefully consider and test whether a particular metric will be effective in capturing a pattern of interest.

ecology↗