Dr. Thomas L. Kieft is an environmental microbiologist who investigates the ecology and biogeochemistry of microbes in extreme environments. He is a professor of Biology at New Mexico Institute of Mining and Technology.
Dr. Kieft completed a master's degree in Biology at New Mexico Highlands University in 1978 and a PhD in Biology at University of New Mexico in 1983. He went on to be a visiting assistant research microbiologist in the Department of Plant and Soil Biology at the University of California, Berkeley from 1983 – 1985 before joining the faculty at New Mexico Institute of Mining and Technology.[1] He is a member of the Deep Life Scientific Steering Committee for the Deep Carbon Observatory (DCO).[2]
In his research, Kieft has investigated the deep biosphere in South African gold mines[3] and developed new methods for detecting pathogenic microorganisms and microbial toxins.[4] Recent work focuses on uncovering relationships between the abundance and diversity of microbes that live in association with animals, and an animal's mass.[5]
References edit
- ^ "Homepage of Dr. Thomas L. Kieft". infohost.nmt.edu. Retrieved 2017-07-19.
- ^ "DCO Scientific Steering Committees | Deep Carbon Observatory Portal". deepcarbon.net. Archived from the original on 2017-08-02. Retrieved 2017-07-19.
- ^ Kieft, Thomas L.; McCuddy, Sean M.; Onstott, T. C.; Davidson, Mark; Lin, Li-Hung; Mislowack, Bianca; Pratt, Lisa; Boice, Erik; Lollar, Barbara Sherwood (2005-09-01). "Geochemically Generated, Energy-Rich Substrates and Indigenous Microorganisms in Deep, Ancient Groundwater". Geomicrobiology Journal. 22 (6): 325–335. doi:10.1080/01490450500184876. ISSN 0149-0451. S2CID 140561776.
- ^ Allen, Rebekah C.; Rogelj, Snezna; Cordova, Susan E.; Kieft, Thomas L. (2006-01-20). "An immuno-PCR method for detecting Bacillus thuringiensis Cry1Ac toxin". Journal of Immunological Methods. 308 (1): 109–115. doi:10.1016/j.jim.2005.10.006. PMID 16337224.
- ^ Kieft, Thomas L. (2017-06-01). "New Allometric Scaling Laws Revealed for Microorganisms". Trends in Ecology & Evolution. 32 (6): 400–402. doi:10.1016/j.tree.2017.02.017. ISSN 0169-5347. PMID 28285792.
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