Collaborative Research: phyloregion, computational infrastructure for biogeographic regionalization and macroecology in the R computing environment

点击翻译按钮获取中文摘要

Establishing geographical comparisons based on shared biota is crucial to the study of biogeography and for managing biological diversity in the face of rapid warming of the Earth’s climate. However, the computational tools to analyze and manipulate the massive-scale species biogeography data has not been fully developed. Historically, classifications of biogeographic regions were based on descriptions of the ecology, taxonomic composition or vegetation features of regions. Recent approaches provided more quantitative, and objective classifications, but broadly recapitulated earlier efforts and overlooked the evolutionary implications captured by the shared phylogenetic relationships of species. Because the field of biogeography has traditionally developed as an observational science rather than an experimental one, developing replicable analytical tools for biogeography into reproducible workflows is critical. The R software package phyloregion – designed for biogeographic regionalization and macroecology – can overcome these computational challenges. It contains tools for biogeographical regionalization, macroecology, conservation, and visualization, and has potential application in various disciplines including evolution, microbial diversity, systematics, ecology, phylogenetics, and many others. In this project, the research team plans to substantially increase computational efficiency of functions in phyloregion, to add new functionality, and create a model for user-guided software development in biogeography.The project will develop and implement new tools in phyloregion for biome evolution and biogeographical investigations. Novel Grade of Membership model that represents sampling units as partial memberships in multiple groups will be established to analyze large biogeographic datasets. It will extend phyloregion with new tools to visualize patterns of biogeography, macroecology and evolution. Phyloregion will be enhanced to pass objects between R and RevBayes (a C++ tool for Bayesian phylogeography) for phylogeographic visualization through R. Finally, it will introduce new tools for conservation that reflect the key dimensions of phylogenetic diversity including richness, divergence and regularity. Phyloregion is already widely used and represents one of only a few biogeographical resources in R tailored for megaphylogenies and macroecological datasets. This research will create new, open-source, and freely distributed software tools with potential for transformative impact in biogeography and beyond. Workshops and conferences will be used for dissemination, and to provide introduction to intermediate R coding and implementation of biogeographical tools. Workshops will target a mix of faculty, postdocs, and especially graduate and undergraduate students, who will be trained on the use and application of phyloregion in their research, and to help develop their own novel biogeographic functions to assemble into an R package. The research team will work with existing diversity programs at Texas A&M University-Corpus Christi and Southeastern to recruit diverse undergraduate participants, and provide resources for them to learn about graduate school. All products from this project will be disseminated free and open-sourced through computer codes, publications, conferences, workshops and vignettes. Phyloregion vignettes will be used to create an upper-division course for undergraduate and early graduate students. The grant will support the mentoring of one postdoctoral researcher and a graduate student and many undergraduates. Women and traditionally underrepresented groups will be specifically encouraged to apply for the postdoctoral research position, as well as for the workshops. The phyloregion project can be accessed at https://CRAN.R-project.org/package=phyloregionThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.