Occurrence and Range-through database of functional diversity of marine ecosystems after the Late Permian mass extinction event

The Late Permian mass extinction event about 252 million years ago was the most severe biotic crisis of the past 500 million years and occurred during an episode of global warming. The loss of around two-thirds of marine genera is thought to have had substantial ecological effects, but the overall impacts on the functioning of marine ecosystems and the pattern of marine recovery are uncertain. Here we analyse the fossil occurrences of all known benthic marine invertebrate genera from the Permian and Triassic periods, and assign each to a functional group based on their inferred lifestyle. We show that despite the selective extinction of 62-74% of these genera, all but one functional group persisted through the crisis, indicating that there was no significant loss of functional diversity at the global scale. In addition, only one new mode of life originated in the extinction aftermath. We suggest that Early Triassic marine ecosystems were not as ecologically depauperate as widely assumed. Functional diversity was, however, reduced in particular regions and habitats, such as tropical reefs; at these smaller scales, recovery varied spatially and temporally, probably driven by migration of surviving groups. We find that marine ecosystems did not return to their pre-extinction state, and by the Middle Triassic greater functional evenness is recorded, resulting from the radiation of previously subordinate groups such as motile, epifaunal grazers.

Distribution models for mountain plant species: The value of elevation

The climatic conditions of mountain habitats are greatly influenced by topography. Large differences in microclimate occur with small changes in elevation, and this complex interaction is an important determinant of mountain plant distributions. In spite of this, elevation is not often considered as a relevant predictor in species distribution models (SDMs) for mountain plants. Here, we evaluated the importance of including elevation as a predictor in SDMs for mountain plant species. We generated two sets of SDMs for each of 73 plant species that occur in the Pacific Northwest of North America; one set of models included elevation as a predictor variable and the other set did not. AUC scores indicated that omitting elevation as a predictor resulted in a negligible reduction of model performance. However, further analysis revealed that the omission of elevation resulted in large over-predictions of species' niche breadths-this effect was most pronounced for species that occupy the highest elevations. In addition, the inclusion of elevation as a predictor constrained the effects of other predictors that superficially affected the outcome of the models generated without elevation. Our results demonstrate that the inclusion of elevation as a predictor variable improves the quality of SDMs for high-elevation plant species. Because of the negligible AUC score penalty for over-predicting niche breadth, our results support the notion that AUC scores alone should not be used as a measure of model quality. More generally, our results illustrate the importance of selecting biologically relevant predictor variables when constructing SDMs.