GOVERNMENT
Less diversity on Earth according to Cornell data analyses
The total number of microbial species on the planet Earth is two orders of magnitude smaller than the consensus estimate, according to a data analyses performed by John Bunge, chair of social statistics and associate professor of statistical science at Cornell University.
Bunge and his research colleagues collaborated with database consultants at the Cornell Center for Advanced Computing (CAC) and used their high-performance database servers to create a more accurate estimate of the biodiversity of microbial populations.
Bunge used a combination of statistical techniques – parametric and nonparametric, frequentist and Bayesian, and abundance- and incidence-based – to generate this new insight. Typically diversity is defined as the number of taxonomic groups such as species or genera, but the same statistical techniques can be used to estimate the number of individuals within a population.
Bunge’s research team investigates microbial diversity, both in specific environments – such as sub-oceanic hydrothermal vents, Arctic ice melt, and beach sands – and over the entire biosphere. “CAC deals with this scenario very well,” according to Linda Woodard, a research specialist focused on the simulation modeling of ecological systems and database design. “Each run is independent and can be done in parallel. While researchers can only run one data set at a time on a desktop computer, we can process multiple data sets simultaneously with our high-performance database servers.”
Bunge estimates that the total number of microbial species on planet Earth, defined as groups sharing 97% of their ribosomal gene identity, is 150,000. This is roughly 2 orders of magnitude smaller than the impressionistic consensus – the average guess – of microbiologists. His latest findings are published in Biometrical Journalism, BMC Biology, and Microbiology Monographs. Bunge’s data analysis software is available to the scientific community.
The Cornell Center for Advanced Computing receives support from the Cornell University, the National Science Foundation, DOD, USDA, and members of its corporate program, including Pfizer, Boeing, Corning, and Northrop Grumman.
Bunge and his research colleagues collaborated with database consultants at the Cornell Center for Advanced Computing (CAC) and used their high-performance database servers to create a more accurate estimate of the biodiversity of microbial populations.
Bunge used a combination of statistical techniques – parametric and nonparametric, frequentist and Bayesian, and abundance- and incidence-based – to generate this new insight. Typically diversity is defined as the number of taxonomic groups such as species or genera, but the same statistical techniques can be used to estimate the number of individuals within a population.
Bunge’s research team investigates microbial diversity, both in specific environments – such as sub-oceanic hydrothermal vents, Arctic ice melt, and beach sands – and over the entire biosphere. “CAC deals with this scenario very well,” according to Linda Woodard, a research specialist focused on the simulation modeling of ecological systems and database design. “Each run is independent and can be done in parallel. While researchers can only run one data set at a time on a desktop computer, we can process multiple data sets simultaneously with our high-performance database servers.”
Bunge estimates that the total number of microbial species on planet Earth, defined as groups sharing 97% of their ribosomal gene identity, is 150,000. This is roughly 2 orders of magnitude smaller than the impressionistic consensus – the average guess – of microbiologists. His latest findings are published in Biometrical Journalism, BMC Biology, and Microbiology Monographs. Bunge’s data analysis software is available to the scientific community.
The Cornell Center for Advanced Computing receives support from the Cornell University, the National Science Foundation, DOD, USDA, and members of its corporate program, including Pfizer, Boeing, Corning, and Northrop Grumman.