ABSTRACT
Intraspecific genetic diversity is a key aspect of biodiversity. Quaternary climatic change and glaciation influenced intraspecific genetic diversity by promoting range shifts and population size change. However, the extent to which glaciation affected genetic diversity on a global scale is not well established. Here we quantify nucleotide diversity, a common metric of intraspecific genetic diversity, in more than 38,000 plant and animal species using georeferenced DNA sequences from millions of samples. Results demonstrate that tropical species contain significantly more intraspecific genetic diversity than nontropical species. To explore potential evolutionary processes that may have contributed to this pattern, we calculated summary statistics that measure population demographic change and detected significant correlations between these statistics and latitude. We find that nontropical species are more likely to deviate from neutral expectations, indicating that they have historically experienced dramatic fluctuations in population size likely associated with Pleistocene glacial cycles. By analyzing the most comprehensive data set to date, our results imply that Quaternary climate perturbations may be more important as a process driving the latitudinal gradient in species richness than previously appreciated.
ABSTRACT
Patterns of genetic diversity within species contain information the history of that species, including how they have responded to historical climate change and how easily the organism is able to disperse across its habitat. More than 40,000 phylogeographic and population genetic investigations have been published to date, each collecting genetic data from hundreds of samples. Despite these millions of data points, meta-analyses are challenging because the synthesis of results across hundreds of studies, each using different methods and forms of analysis, is a daunting and time-consuming task. It is more efficient to proceed by repurposing existing data and using automated data analysis. To facilitate data repurposing, we created a database (phylogatR) that aggregates data from different sources and conducts automated multiple sequence alignments and data curation to provide users with nearly ready-to-analyse sets of data for thousands of species. Two types of scientific research will be made easier by phylogatR: large meta-analyses of thousands of species that can address classic questions in evolutionary biology and ecology, and student- or citizen- science based investigations that will introduce a broad range of people to the analysis of genetic data. phylogatR enhances the value of existing data via the creation of software and web-based tools that enable these data to be recycled and reanalysed and increase accessibility to big data for research laboratories and classroom instructors with limited computational expertise and resources.
Subject(s)
Data Aggregation , Ecology , Ecology/methods , Ecosystem , Humans , Phylogeography , SoftwareABSTRACT
SignificanceOnly an estimated 1 to 10% of Earth's species have been formally described. This discrepancy between the number of species with a formal taxonomic description and actual number of species (i.e., the Linnean shortfall) hampers research across the biological sciences. To explore whether the Linnean shortfall results from poor taxonomic practice or not enough taxonomic effort, we applied machine-learning techniques to build a predictive model to identify named species that are likely to contain hidden diversity. Results indicate that small-bodied species with large, climatically variable ranges are most likely to contain hidden species. These attributes generally match those identified in the taxonomic literature, indicating that the Linnean shortfall is caused by societal underinvestment in taxonomy rather than poor taxonomic practice.
