The history of life is filled with examples of one species diverging into several, even thousands, each with unique traits
geared to the demands of its ecological niche. In the textbook case of adaptive radiation, an ancestral finch species landed on the Galapagos Islands just a few million years ago, and evolved into 13 new species with specialized beaks adapted to exploiting the various seeds, nuts, insects, and other food sources on the island.
Adaptive radiations suggest that species
evolution follows the first rule of business: find a niche and fill it. But thats not what most models used to detect
evolutionary patterns of trait evolution assume. And in a new study, Robert Freckleton and Paul Harvey demonstrate the limitations of that choice. They also introduce a method to minimize those limitations by using a diagnostic tool that can detect evolutionary patterns that deviate from the standard models.
The complexity of evolutionary processes and spottiness of the fossil record calls for statistical modelswhose accuracy depends on their assumptionsto infer historical patterns of evolution. Traditional approaches to studying the evolution of traits (such as beak shape) typically compare populations, species, or higher taxa to identify adaptations and the corresponding evolutionary processes. With advances in molecular genomic techniques, comparative methods increasingly incorporate phylogenetic analyses, which compare gene or protein sequences to infer evolutionary relationships between taxa or traits.
These phylogenetic comparative methods often use a Brownian motion model of evolution, which assumes that more closely related species are more similar to each other and generate expected distributions of trait change among the species compared. Freckleton and Harvey suspected that the models could produce specious correlations, because they dont explicitly account for ecological processes. Such a modelwhich, the authors point out, has rarely been testedassumes (among other things) that traits evolve at a constant rate over time.
Freckleton and Harvey analyzed real and simulated data using a niche-filling model and a Brownian motion model and then applied two statistical tests as diagnostic tools to detect patterns of trait evolution that fall outside the assumptions of the Brownian motion. In the niche-filling model, niche space is initially empty (much like Darwins finches may have encountered), and new niches arise at a given rate, in random positions, and are instantly invaded by species with traits suited to exploiting that niche. Evolution occurs only when a new nichesuch as a novel seedappears and a species is under selection to exploit it. In contrast to Brownian models, for example, one would expect that as niches became filled with more species, the difference between the parent and offspring species would become smaller, because niches have a unique optimum value and trait values are constrained (by correlations between beak size and food size, for example). Likewise, with an adaptive radiation, one would expect ecological differences to arise with or shortly after speciation, rather than at a constant pace dependent only on time.
Speciation ratedefined as the rate at which new niches appear and are invaded in the niche-filling models and the rate at which lineages split in Brownian motion modelswas modeled using three different models: the probability of speciation is proportional to the number of species present, remains constant, or declines with the number present. Each scenario reflects a different process corresponding to the invasion of an empty niche.
The two diagnostic tests included a node height test, which assesses whether the rate of evolution of a particular trait occurs systematically within a phylogenetic tree, and a simple randomization test. (Node height refers to the distance between the ancestral species, or root, and the most recent common ancestor for a pai