Evaluating the Robustness of Process-Pattern Links Using Phylogenies—Insights from a Comparison of Eight Simulation Models
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2026
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Abstract
Abstract Macroevolutionary studies have shown that the shape of phylogenetic trees differs in space, time, and between taxa. It is commonly assumed that these differences in tree shape reflect variability in the underlying ecological and evolutionary processes that produced them, and mechanistic eco-evolutionary models are increasingly used to explore this link. A concern in this context is whether conclusions drawn from such mechanistic models are robust to idiosyncrasies in how eco-evolutionary processes are formalized in the models. Here, we use eight mechanistic macroevolutionary models to study how 52 metrics of phylogenetic tree shape respond to variation in the strength of five fundamental processes: competition, dispersal, environmental filtering, niche conservatism, and speciation. We find that models agree on how some tree metrics respond to changes in these processes, in particular dispersal and speciation. However, no tree metric uniquely correlated with a single process, suggesting that single tree metrics have limited utility as shortcuts for inferring the underlying eco-evolutionary processes. Moreover, while it was possible to infer the underlying processes if the data-generating model was known, inference was not consistent across the different models. We conclude that the relationship between phylogenetic patterns and eco-evolutionary processes in macroevolutionary analysis is likely sensitive to the structural and mechanistic details of how a given process is implemented within models.
| Reference Key |
openalex_W7167924911
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| Authors | Allen H. Hurlbert, Juliano Sarmento Cabral, Rampal S. Etienne, Oskar Hagen, Shan Huang, Yun-Ting Jang, Thijs Janzen, Antonín Macháč, Pedro Santos Neves, Mikael Pontarp, David Storch, Liang Xu, Florian Hartig |
| Journal | systematic biology |
| Year | 2026 |
| DOI |
10.1093/sysbio/syag050
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| URL | |
| Keywords | Keywords not found |
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