Publications

Displaying 61 - 79 of 79
By year of publication, then alphabetical by title
  1. Schädel, Christina, et al. “Potential Carbon Emissions Dominated by Carbon Dioxide from Thawed Permafrost Soils”. Nature Climate Change, vol. 6, no. 10, 2016, pp. 950-3, https://doi.org/10.1038/nclimate3054.
  2. Dafflon, Baptiste, et al. “Quantification of Arctic Soil and Permafrost Properties Using Ground Penetrating Radar”. 2016 16th International Conference on Ground Penetrating Radar (GPR) , 2016, https://doi.org/10.1109/ICGPR.2016.7572663.
  3. Ghimire, Bardan, et al. “Representing Leaf and Root Physiological Traits in CLM Improves Global Carbon and Nitrogen Cycling Predictions”. Journal of Advances in Modeling Earth Systems, vol. 8, no. 2, 2016, pp. 598-13, https://doi.org/10.1002/2015MS000538.
  4. Xu, Xiaofeng, et al. “Reviews and Syntheses: Four Decades of Modeling Methane Cycling in Terrestrial Ecosystems”. Biogeosciences, vol. 13, no. 12, 2016, pp. 3735-5, https://doi.org/10.5194/bg-13-3735-2016.
  5. Zhu, Qing, et al. “Root Traits Explain Observed Tundra Vegetation Nitrogen Uptake Patterns: Implications for Trait-Based Land Models”. Journal of Geophysical Research: Biogeosciences, vol. 121, no. 12, 2016, pp. 3101-12, https://doi.org/10.1002/2016JG003554.
  6. Cable, William L., et al. “Scaling-up Permafrost Thermal Measurements in Western Alaska Using an Ecotype Approach”. The Cryosphere, vol. 10, no. 5, 2016, pp. 2517-32, https://doi.org/10.5194/tc-10-2517-2016.
  7. Farquharson, Louise M., et al. “Spatial Distribution of Thermokarst Terrain in Arctic Alaska”. Geomorphology, vol. 273, 2016, pp. 116-33, https://doi.org/10.1016/j.geomorph.2016.08.007.
  8. Tang, Jinyun Y., and William J. Riley. “Technical Note: A Generic Law-of-the-Minimum Flux Limiter for Simulating Substrate Limitation in Biogeochemical Models”. Biogeosciences, vol. 13, no. 3, 2016, pp. 723-35, https://doi.org/10.5194/bg-13-723-2016.
  9. Walker, Donald A., et al. “The Alaska Arctic Vegetation Archive (AVA-AK)”. Phytocoenologia, vol. 46, no. 2, 2016, pp. 221-9, https://doi.org/10.1127/phyto/2016/0128.
  10. Sjöberg, Ylva, et al. “Thermal Effects of Groundwater Flow through Subarctic Fens: A Case Study Based on Field Observations and Numerical Modeling”. Water Resources Research, vol. 52, no. 3, 2016, pp. 1591-06, https://doi.org/10.1002/2015WR017571.
  11. McGuire, David, et al. “Variability in the Sensitivity Among Model Simulations of Permafrost and Carbon Dynamics in the Permafrost Region Between 1960 and 2009”. Global Biogeochemical Cycles, vol. 30, no. 7, 2016, pp. 1015-37, https://doi.org/10.1002/2016GB005405.
  12. Yang, Ziming, et al. “Warming Increases Methylmercury Production in an Arctic Soil”. Environmental Pollution, vol. 214, 2016, pp. 504-9, https://doi.org/10.1016/j.envpol.2016.04.069.
  13. McGuire, David, et al. “An Assessment of the Carbon Balance of Arctic Tundra: Comparisons Among Observations, Process Models, and Atmospheric Inversions”. Biogeosciences, vol. 9, no. 8, 2012, pp. 3185-04, https://doi.org/10.5194/bg-9-3185-201210.5194/bg-9-3185-2012-supplement.
  14. Lewis, K. C., et al. “Drainage Subsidence Associated With Arctic Permafrost Degradation”. Journal of Geophysical Research, vol. 117, no. F4, 2012, https://doi.org/10.1029/2011JF002284.
  15. Lee, Hanna, et al. “Enhancing Terrestrial Ecosystem Sciences by Integrating Empirical Modeling Approaches”. Eos, Transactions, American Geophysical Union, vol. 93, no. 25, 2012, pp. 237-, https://doi.org/10.1029/2012EO250008.
  16. McCarthy, Heather R., et al. “Integrating Empirical-Modeling Approaches to Improve Understanding of Terrestrial Ecology Processes”. New Phytologist, vol. 195, no. 3, 2012, pp. 523-5, https://doi.org/10.1111/j.1469-8137.2012.04222.x.
  17. Graham, David E., et al. “Microbes in Thawing Permafrost: The Unknown Variable in the Climate Change Equation”. The ISME Journal, vol. 6, no. 4, 2012, pp. 709-12, https://doi.org/10.1038/ismej.2011.163.
  18. Xu, Chonggang, et al. “Toward a Mechanistic Modeling of Nitrogen Limitation on Vegetation Dynamics”. PLOS ONE, vol. 7, no. 5, 2012, p. e37914, https://doi.org/10.1371/journal.pone.0037914.
  19. Bouskill, Nicholas J., et al. “Trait-Based Representation of Biological Nitrification: Model Development, Testing, and Predicted Community Composition”. Frontiers in Microbiology, vol. 3, 2012, https://doi.org/10.3389/fmicb.2012.00364.