Scaling of Biodiversity

Deciphering patterns of biodiversity is particularly challenging because: 1) the drivers of diversity change with spatial scale (McGlinn and Palmer 2011, McGlinn and Hurlbert 2012) and, 2) similar patterns of diversity can result from very different components of community structure: the spatial structure, relative abundance, and density of each species (McGlinn and Palmer 2009, McGlinn and Palmer 2010).

To address these problems, our lab has helped to develop the Measurement of Biodiversity (MoB) framework which is a suite of new statistical tools (R packages mobr and mobsim) that quantify and simulate how changes in community structure drive multiscale changes in diversity (McGlinn et al. 2018, Chase et al. 2018, May et al. 2018., Blowes et al. in review, software archive). This work is critical because it provides a means of more directly connecting changes in diversity back to mechanisms that influence community structure.

We are working to extend the MoB framework to analyze microbial diversity, continuous diversity gradients (e.g., elevation, latitude), species covariance, and trait and phylogenetic diversity.