Publications

Displaying 181 - 200 of 334
By year of publication, then alphabetical by title
  1. Chen, Hongmei, et al. “Molecular Insights into Arctic Soil Organic Matter Degradation under Warming”. Environmental Science & Technology, vol. 52, no. 8, 2018, pp. 4555-64, https://doi.org/10.1021/acs.est.7b05469.
  2. Bjorkman, Anne D., et al. “Plant Functional Trait Change across a Warming Tundra Biome”. Nature, vol. 562, no. 7725, 2018, pp. 57-62, https://doi.org/10.1038/s41586-018-0563-7.
  3. Vaughn, Lydia J. S., and Margaret S. Torn. “Radiocarbon Measurements of Ecosystem Respiration and Soil Pore-Space Carbon Dioxide in Utqiaġvik (Barrow), Alaska”. Earth System Science Data, vol. 10, no. 4, 2018, pp. 1943-57, https://doi.org/10.5194/essd-10-1943-2018.
  4. Lara, Mark J., et al. “Reduced Arctic Tundra Productivity Linked With Landform and Climate Change Interactions”. Scientific Reports, vol. 8, no. 1, 2018, https://doi.org/10.1038/s41598-018-20692-8.
  5. Tran, Anh Phuong, et al. “Spatial and Temporal Variations of Thaw Layer Thickness and Its Controlling Factors Identified Using Time-Lapse Electrical Resistivity Tomography and Hydro-Thermal Modeling”. Journal of Hydrology, vol. 561, 2018, pp. 751-63, https://doi.org/10.1016/j.jhydrol.2018.04.028.
  6. Lombardozzi, Danica L., et al. “Triose Phosphate Limitation in Photosynthesis Models Reduces Leaf Photosynthesis and Global Terrestrial Carbon Storage”. Environmental Research Letters, vol. 13, no. 7, 2018, p. 074025, https://doi.org/10.1088/1748-9326/aacf68.
  7. Lara, Mark J., et al. “Tundra Landform and Vegetation Productivity Trend Maps for the Arctic Coastal Plain of Northern Alaska”. Scientific Data, vol. 5, 2018, p. 180058, https://doi.org/10.1038/sdata.2018.58.
  8. Mekonnen, Zelalem A., et al. “Twenty-First Century Tundra Shrubification Could Enhance Net Carbon Uptake of North America Arctic Tundra under an RCP_8.5 Climate Trajectory”. Environmental Research Letters, vol. 13, no. 5, 2018, p. 054029, https://doi.org/10.1088/1748-9326/aabf28.
  9. Langford, Zachary, et al. “Wildfire Mapping in Interior Alaska Using Deep Neural Networks on Imbalanced Datasets”. 2018 IEEE International Conference on Data Mining Workshops (ICDMW), IEEE, 2018, https://doi.org/10.1109/icdmw.2018.00116.
  10. Ghimire, Bardan, et al. “A Global Trait-Based Approach to Estimate Leaf Nitrogen Functional Allocation from Observations”. Ecological Applications, vol. 27, no. 5, 2017, pp. 1421-34, https://doi.org/10.1002/eap.1542.
  11. Zhu, Qing, et al. “A New Theory of Plant-Microbe Nutrient Competition Resolves Inconsistencies Between Observations and Model Predictions”. Ecological Applications, vol. 27, no. 3, 2017, pp. 875-86, https://doi.org/10.1002/eap.1490.
  12. Rogers, Alistair, et al. “A Roadmap for Improving the Representation of Photosynthesis in Earth System Models”. New Phytologist, vol. 213, no. 1, 2017, pp. 22-42, https://doi.org/10.1111/nph.14283.
  13. Lewin, Keith F., et al. “A Zero-Power Warming Chamber for Investigating Plant Responses to Rising Temperature”. Biogeosciences, vol. 14, no. 18, 2017, pp. 4071-83, https://doi.org/10.5194/bg-14-4071-2017.
  14. Dou, Shan, et al. “An Effective-Medium Model for P-Wave Velocities of Saturated, Unconsolidated Saline Permafrost”. GEOPHYSICS, vol. 82, no. 3, 2017, https://doi.org/10.1190/geo2016-0474.1.
  15. Nicolsky, Dmitry J., et al. “Applicability of the Ecosystem Type Approach to Model Permafrost Dynamics across the Alaska North Slope”. Journal of Geophysical Research: Earth Surface, vol. 122, no. 1, 2017, pp. 50-75, https://doi.org/10.1002/2016JF003852.
  16. Dafflon, Baptiste, et al. “Coincident Aboveground and Belowground Autonomous Monitoring to Quantify Covariability in Permafrost, Soil, and Vegetation Properties in Arctic Tundra”. Journal of Geophysical Research: Biogeosciences, vol. 122, no. 6, 2017, pp. 1321-42, https://doi.org/10.1002/2016JG003724.
  17. Wang, Kang, et al. “Continuously Amplified Warming in the Alaskan Arctic: Implications for Estimating Global Warming Hiatus”. Geophysical Research Letters, vol. 44, no. 17, 2017, pp. 9029-38, https://doi.org/10.1002/2017GL074232.
  18. Langford, Zachary L., et al. “Convolutional Neural Network Approach for Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion”. 2017 IEEE International Conference on Data Mining Workshops (ICDMW)2017 IEEE International Conference on Data Mining Workshops (ICDMW), IEEE, 2017, https://doi.org/10.1109/ICDMW.2017.48.
  19. Tran, Anh Phuong, et al. “Coupled Land Surface-Subsurface Hydrogeophysical Inverse Modeling to Estimate Soil Organic Content and Explore Associated Hydrological and Thermal Dynamics in an Arctic Tundra”. The Cryosphere, vol. 11, 2017, pp. 2089-0, https://doi.org/10.5194/tc-11-2089-2017.
  20. Strauss, Jens, et al. “Deep Yedoma Permafrost: A Synthesis of Depositional Characteristics and Carbon Vulnerability”. Earth-Science Reviews, vol. 172, 2017, pp. 75-86, https://doi.org/10.1016/j.earscirev.2017.07.007.