Metagenomics Offers a Big-Picture View of the Diversity and Distribution of Marine Viruses

The history of life is fi lled 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 fi nch 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 fi rst rule of business: fi nd a niche and fi ll it. But that's 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 models— whose accuracy depends on their assumptions—to 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 don't explicitly account for ecological processes. Such a model— which, the authors point out, has rarely been tested—assumes (among other things) that traits evolve at a constant rate over time. Freckleton and Harvey analyzed real and simulated data using a niche-fi lling 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-fi lling model, niche space is initially empty (much like Darwin's fi nches 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 …