Publications

Displaying 21 - 40 of 63
By year of publication, then alphabetical by title
  1. Schore, Aiden I. G., et al. “Nitrogen Fixing Shrubs Advance the Pace of Tall-Shrub Expansion in Low-Arctic Tundra”. Communications Earth & Environment, vol. 4, 2023, https://doi.org/https://doi.org/10.1038/s43247-023-01098-5.
  2. Chang, Kuang‐Yu, et al. “Observational Constraints Reduce Model Spread But Not Uncertainty in Global Wetland Methane Emission Estimates”. Global Change Biology, vol. 29, no. 15, 2023, pp. 4298-12, https://doi.org/10.1111/gcb.16755.
  3. Del Vecchio, Joanmarie, et al. “Patterns and Rates of Soil Movement and Shallow Failures across Several Small Watersheds on the Seward Peninsula, Alaska”. Earth Surface Dynamics, vol. 11, no. 2, 2023, pp. 227-45, https://doi.org/10.5194/esurf-11-227-2023.
  4. Yang, Dedi, et al. “PiCAM: A Raspberry Pi-Based Open-Source, Low-Power Camera System for Monitoring Plant Phenology in Arctic Environments”. Methods in Ecology and Evolution, vol. 14, 2023, https://doi.org/10.1111/2041-210X.14231.
  5. Mevenkamp, Hannah, et al. “Reducing Uncertainty of High-Latitude Ecosystem Models through Identification of Key Parameters”. Environmental Research Letters, vol. 18, 2023, https://doi.org/10.1088/1748-9326/ace637.
  6. Tang, Jinyun, and William J. Riley. “Revising the Dynamic Energy Budget Theory With a New Reserve Mobilization Rule and Three Example Applications to Bacterial Growth”. Soil Biology and Biochemistry, vol. 178, 2023, p. 108954, https://doi.org/10.1016/j.soilbio.2023.108954.
  7. Wielandt, Stijn, et al. “TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring”. Journal of Signal Processing Systems, 2023, https://doi.org/10.1007/s11265-023-01834-2.
  8. Santos, Fernanda, et al. “The Eco-Evolutionary Role of Fire in Shaping Terrestrial Ecosystems”. Functional Ecology, vol. 37, no. 8, 2023, https://doi.org/https://doi.org/10.1111/1365-2435.14387.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. Wu, Yuxin, et al. “Electrical and Seismic Response of Saline Permafrost Soil During Freeze - Thaw Transition”. Journal of Applied Geophysics, vol. 146, 2017, pp. 16-26, https://doi.org/10.1016/j.jappgeo.2017.08.008.