Elita Baldridge

An amniote life‐history database to perform comparative analyses with birds, mammals, and reptiles

Studying life-history traits within and across taxonomic classifications has revealed many interesting and important patterns, but this approach to life history requires access to large compilations of data containing many different life-history parameters. Currently, life-history data for amniotes (birds, mammals, and reptiles) are split among a variety of publicly available databases, data tables embedded in individual papers and books, and species-specific studies by experts. Using data from this wide range of sources is a challenge for conducting macroecological studies because of a lack of standardization in taxonomic classifications, parameter values, and even in which parameters are reported. In order to facilitate comparative analyses between amniote life-history data, we created a database compiled from peer-reviewed studies on individual species, macroecological studies of multiple species, existing life-history databases, and other aggregated sources as well as published books and other compilations. First, we extracted and aggregated the raw data from the aforementioned sources. Next, we resolved spelling errors and other formatting inconsistencies in species names through a number of computational and manual methods. Once this was completed, subspecies-level data and species-level data were shared via a data-sharing algorithm to accommodate the variety of species transformations (taxonomic promotions, demotions, merges, divergences, etc.) that have occurred over time. Finally, in species where multiple raw data points were identified for a given parameter, we report the median value. Here, we report a normalized and consolidated database of up to 29 life-history parameters, containing at least one life-history parameter for 21 322 species of birds, mammals, and reptiles.

An extensive comparison of species-abundance distribution models

A number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD.