Plant Diversity ›› 2016, Vol. 38 ›› Issue (06): 264-270.DOI: 10.1016/j.pld.2016.12.001

• Articles • Previous Articles    

Mobilizing and integrating big data in studies of spatial and phylogenetic patterns of biodiversity

Douglas E. Soltisa,b,c, Pamela S. Soltisa,b   

  1. a. Florida Museum of Natural History, University of Florida, Gainesville, FL, USA;
    b. Genetics Institute, University of Florida, Gainesville, FL, USA;
    c. Department of Biology, University of Florida, Gainesville, FL, USA
  • Received:2016-10-24 Revised:2016-11-30 Published:2021-11-05
  • Contact: Douglas E. Soltis
  • Supported by:
    This work was supported in part by US NSF grants EF-1115210, DBI-1547229, DBI-1458640, DEB-1442280, and DEB-1208809.

Abstract: The current global challenges that threaten biodiversity are immense and rapidly growing. These biodiversity challenges demand approaches that meld bioinformatics, large-scale phylogeny reconstruction, use of digitized specimen data, and complex post-tree analyses (e.g. niche modeling, niche diversification, and other ecological analyses). Recent developments in phylogenetics coupled with emerging cyberinfrastructure and new data sources provide unparalleled opportunities for mobilizing and integrating massive amounts of biological data, driving the discovery of complex patterns and new hypotheses for further study. These developments are not trivial in that biodiversity data on the global scale now being collected and analyzed are inherently complex. The ongoing integration and maturation of biodiversity tools discussed here is transforming biodiversity science, enabling what we broadly term “next-generation” investigations in systematics, ecology, and evolution (i.e., “biodiversity science”). New training that integrates domain knowledge in biodiversity and data science skills is also needed to accelerate research in these areas. Integrative biodiversity science is crucial to the future of global biodiversity. We cannot simply react to continued threats to biodiversity, but via the use of an integrative, multifaceted, big data approach, researchers can now make biodiversity projections to provide crucial data not only for scientists, but also for the public, land managers, policy makers, urban planners, and agriculture.

Key words: Biodiversity, Big data, Niche modeling, Bioinformatics, Phylogeny