McMurdo LTER Publications
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Characterizing hyporheic exchange processes using high-frequency electrical conductivity-discharge relationships on subhourly to interannual timescales. Water Resources Research. 2017;53(5):4124 - 4141. doi:10.1002/wrcr.v53.510.1002/2016WR019739.
A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551. doi:10.1038/nature24621.
A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551. doi:10.1038/nature24621.
A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551. doi:10.1038/nature24621.
. Comparing the Weathering Environment of Permian and Modern Antarctic Proglacial Lake Sediments: Mineralogical and Geochemical Study. . School of Earth Sciences. 2017;B.S. Available at: http://hdl.handle.net/1811/80763.
Decadal ecosystem response to an anomalous melt season in a polar desert in Antarctica. Nature Ecology & Evolution. 2017;1(9):1334-1338. doi:10.1038/s41559-017-0253-0.
. Decoupled responses of soil bacteria and their invertebrate consumer to warming, but not freeze-thaw cycles, in the Antarctic Dry Valleys. Ecology Letters. 2017;20(10):1242-1249. doi:10.1111/ele.12819.
. Early diverging lineages within Cryptomycota and Chytridiomycota dominate the fungal communities in ice-covered lakes of the McMurdo Dry Valleys, Antarctica. Scientific Reports. 2017;7(1). doi:10.1038/s41598-017-15598-w.
. Life cycle size dynamics in Didymosphenia geminata (Bacillariophyceae). Journal of Phycology. 2017;53(3):652 - 663. doi:10.1111/jpy.2017.53.issue-310.1111/jpy.12528.
. Primary productivity as a control over soil microbial diversity along environmental gradients in a polar desert ecosystem. PeerJ. 2017;5(10):e3377. doi:10.7717/peerj.3377.
. A simulation-based approach to understand how metacommunity characteristics influence emergent biodiversity patterns. Oikos. 2017;126(5):723-737. doi:10.1111/oik.03690.
. A simulation-based approach to understand how metacommunity characteristics influence emergent biodiversity patterns. Oikos. 2017;126(5):723-737. doi:10.1111/oik.03690.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography. 2018;27(7):760-786. doi:10.1111/geb.12729.
