Accounting for spatial sampling patterns in Bayesian phylogeography

Statistical phylogeography provides useful tools to characterize and quantify the spread of organisms during the course of evolution. Analyzing georeferenced genetic data often relies on the assumption that samples are preferentially collected in densely populated areas of the habitat. Deviation from this assumption negatively impacts the inference of the spatial and demographic dynamics. This issue is pervasive in phylogeography. It affects analyses that approximate the habitat as a set of discrete demes as well as those that treat it as a continuum. The present study introduces a Bayesian modeling approach that explicitly accommodates for spatial sampling strategies. An original inference technique, based on recent advances in statistical computing, is then described that is most suited to modeling data where sequences are preferentially collected at certain locations, independently of the outcome of the evolutionary process. The analysis of georeferenced genetic sequences from the West Nile virus in North America along with simulated data shows how assumptions about spatial sampling may impact our understanding of the forces shaping biodiversity across time and space.

Uneven spatial sampling distorts reconstructions of Phanerozoic seawater temperature

Paleotemperature proxy records are widely used to reconstruct the global climate throughout the Phanerozoic and to test macroevolutionary hypotheses. However, the spatial distribution of these records varies through time. This is problematic because heat is unevenly distributed across Earth’s surface. Consequently, heterogeneous spatial sampling of proxy data has the potential to bias reconstructed temperature curves. We evaluated the spatiotemporal evolution of sampling using a compilation of Phanerozoic δ18O data. We tested the influence of variable spatial coverage on global estimates of paleotemperature by sampling a steep “modern-type” latitudinal temperature gradient and a flattened “Eocene-type” gradient, based on the spatial distribution of δ18O samples. We show that global paleotemperature is overestimated in ~70% of Phanerozoic stages. Perceived climatic trends for some intervals might be artifactually induced by shifts in paleolatitudinal sampling, with equatorward shifts in sampling concurring with warming trends, and poleward shifts concurring with cooling trends. Yet, the magnitude of some climatic perturbations might also be underestimated. For example, the observed Ordovician cooling trend may be underestimated due to an equatorward shift in sampling. Our findings suggest that while proxy records are vital for reconstructing Earth’s paleotemperature in deep time, consideration of the spatial nature of these data is crucial to improving these reconstructions.

Supplemental Material: Uneven spatial sampling distorts reconstructions of Phanerozoic seawater temperature

Additional information regarding data preparation, analysis, and study limitations.<br>

Supplemental Material: Uneven spatial sampling distorts reconstructions of Phanerozoic seawater temperature

Additional information regarding data preparation, analysis, and study limitations.<br>