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Publications by Author

Last Name

Authors who are active project participants

  • Colleen M. Iversen

    2022

    • Bennett, Katrina E., et al. “Spatial Patterns of Snow Distribution for Improved Earth System Modelling in the Arctic”. The Cryosphere, 2022, https://doi.org/https://doi.org/10.5194/tc-2021-341.
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    2021

    • Euskirchen, Eugénie S., et al. “Assessing Dynamic Vegetation Model Parameter Uncertainty across Alaskan Arctic Tundra Plant Communities”. Ecological Applications, 2021, https://doi.org/10.1002/eap.2499.
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    • Sulman, Benjamin N., et al. “Integrating Arctic Plant Functional Types in a Land Surface Model Using Above‐ and Belowground Field Observations”. Journal of Advances in Modeling Earth Systems, vol. 13, no. 4, 2021, https://doi.org/10.1029/2020MS002396.
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    • Mekonnen, Zelalem A., et al. “Topographical Controls on Hillslope‐Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska”. Journal of Geophysical Research: Biogeosciences, vol. 126, no. 2, 2021, https://doi.org/10.1029/2020JG005823.
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    • Ladd, Mallory P., et al. “Untargeted Exometabolomics Provides a Powerful Approach to Investigate Biogeochemical Hotspots With Vegetation and Polygon Type in Arctic Tundra Soils”. Soil Systems, vol. 5, no. 1, 2021, p. 10, https://doi.org/10.3390/soilsystems5010010.
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    2020

    • Zhu, Qing, et al. “Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model”. Journal of Advances in Modeling Earth Systems, 2020, https://doi.org/10.1029/2019MS001841.
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    • Iversen, Colleen M., et al. “Building a Culture of Safety and Trust in Team Science”. Eos, vol. 101, 2020, https://doi.org/10.1029/2020EO143064.
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    • Lara, Mark J., et al. “Local-Scale Arctic Tundra Heterogeneity Affects Regional-Scale Carbon Dynamics”. Nature Communications, vol. 11, no. 1, 2020, https://doi.org/10.1038/s41467-020-18768-z.
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    • Gallagher, Rachael V., et al. “Open Science Principles for Accelerating Trait-Based Science across the Tree of Life”. Nature Ecology & Evolution, vol. 4, no. 3, 2020, pp. 294-03, https://doi.org/10.1038/s41559-020-1109-6.
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    • Bergmann, Joana, et al. “The Fungal Collaboration Gradient Dominates the Root Economics Space in Plants”. Science Advances, vol. 6, no. 27, 2020, https://doi.org/10.1126/sciadv.aba3756.
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    2019

    • Salmon, Verity G., et al. “Alder Distribution and Expansion across a Tundra Hillslope: Implications for Local N Cycling”. Frontiers in Plant Science, vol. 10, 2019, https://doi.org/10.3389/fpls.2019.01099.
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    • Langford, Zachary L., et al. “Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks”. Remote Sensing, vol. 11, no. 1, 2019, p. 69, https://doi.org/10.3390/rs11010069.
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    • Norby, Richard J., et al. “Controls on Fine-Scale Spatial and Temporal Variability of Plant-Available Inorganic Nitrogen in a Polygonal Tundra Landscape”. Ecosystems, vol. 22, 2019, pp. 528–543, https://doi.org/10.1007/s10021-018-0285-6.
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    2016

    • Langford, Zachary L., et al. “Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets”. Remote Sensing, vol. 8, no. 9, 2016, p. 733, https://doi.org/10.3390/rs8090733.
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    • Kumar, Jitendra, et al. “Modeling the Spatiotemporal Variability in Subsurface Thermal Regimes across a Low-Relief Polygonal Tundra Landscape”. The Cryosphere, vol. 10, no. 5, 2016, pp. 2241-74, https://doi.org/10.5194/tc-10-2241-2016.
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    • 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.
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    • 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.
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    • 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.
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    • 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.
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    2015

    • Treat, Claire C., et al. “A Pan-Arctic Synthesis of Methane and Carbon Dioxide Production from Anoxic Soil Incubations”. Global Change Biology, vol. 21, no. 7, 2015, pp. 2787-03, https://doi.org/10.1111/gcb.12875.
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    • Wullschleger, Stan D., et al. “Genomics in a Changing Arctic: Critical Questions Await the Molecular Ecologist”. Molecular Ecology, vol. 24, no. 10, 2015, pp. 2301-9, https://doi.org/10.1111/mec.13166.
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    • Heikoop, Jeffrey Martin, et al. “Isotopic Identification of Soil and Permafrost Nitrate Sources in an Arctic Tundra Ecosystem”. Journal of Geophysical Research: Biogeosciences, vol. 120, no. 6, 2015, pp. 1000-17, https://doi.org/10.1002/2014JG002883.
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    • Warren, Jeffery M., et al. “Root Structural and Functional Dynamics in Terrestrial Biosphere Models - Evaluation and Recommendations”. New Phytologist, vol. 205, no. 1, 2015, pp. 59-78, https://doi.org/10.1111/nph.13034.
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    • Iversen, Colleen M., et al. “The Unseen Iceberg: Plant Roots in Arctic Tundra”. New Phytologist, vol. 205, no. 1, 2015, pp. 34-58, https://doi.org/10.1111/nph.13003.
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    2014

    • Wullschleger, Stan D., et al. “Plant Functional Types in Earth System Models: Past Experiences and Future Directions for Application of Dynamic Vegetation Models in High-Latitude Ecosystems”. Annals of Botany, vol. 114, no. 1, 2014, pp. 1-16, https://doi.org/10.1093/aob/mcu077.
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  • Charles E. Miller

    2021

    • Cawse-Nicholson, Kerry, et al. “NASA’s Surface Biology and Geology Designated Observable: A Perspective on Surface Imaging Algorithms”. Remote Sensing of Environment, vol. 257, 2021, p. 112349, https://doi.org/10.1016/j.rse.2021.112349.
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    2018

    • Parazoo, Nicholas C., et al. “Detecting the Permafrost Carbon Feedback: Talik Formation and Increased Cold-Seasonrespiration As Precursors to Sink-to-Source Transitions”. The Cryosphere Discussions, 2018, pp. 1-44, https://doi.org/10.5194/tc-2017-18910.5194/tc-2017-189-RC110.5194/tc-2017-189-RC210.5194/tc-2017-189-AC110.5194/tc-2017-189-AC2.
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    • Fisher, Joshua B., et al. “Missing Pieces to Modeling the Arctic-Boreal Puzzle”. Environmental Research Letters, vol. 13, no. 2, 2018, p. 020202, https://doi.org/10.1088/1748-9326/aa9d9a.
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    2016

    • Xu, Xiyan, et al. “A Multi-Scale Comparison of Modeled and Observed Seasonal Methane Emissions in Northern Wetlands”. Biogeosciences, vol. 13, no. 17, 2016, pp. 5043-56, https://doi.org/10.5194/bg-13-5043-201610.5194/bg-13-5043-2016-supplement.
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    • Parazoo, Nicholas C., et al. “Detecting Regional Patterns of Changing CO <sub>2< Sub> Flux in Alaska”. Proceedings of the National Academy of Sciences, vol. 113, no. 28, 2016, pp. 7733-8, https://doi.org/10.1073/pnas.1601085113.
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  • Alistair Rogers

    2022

    • Lamour, Julien, et al. “New Calculations for Photosynthesis Measurement Systems: What’s the Impact for Physiologists and Modelers?”. New Phytologist, vol. 233, no. 2, 2022, pp. 592-8, https://doi.org/https://doi.org/10.1111/nph.17762.
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    • Rogers, Alistair, et al. “Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation”. Global Change Biology, vol. 28, no. 4, 2022, pp. 1222-47, https://doi.org/https://doi.org/10.1111/gcb.15958 .
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    2021

    • Burnett, Angela C., et al. “A Best-Practice Guide to Predicting Plant Traits from Leaf-Level Hyperspectral Data Using Partial Least Squares Regression”. Journal of Experimental Botany, vol. 72, no. 18, 2021, pp. 6175-89, https://doi.org/10.1093/jxb/erab295.
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    • Ely, Kim S., et al. “A Reporting Format for Leaf-Level Gas Exchange Data and Metadata”. Ecological Informatics, vol. 61, 2021, p. 101232, https://doi.org/10.1016/j.ecoinf.2021.101232.
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    • Rogers, Alistair, et al. “Triose Phosphate Utilization Limitation: An Unnecessary Complexity in Terrestrial Biosphere Model Representation of Photosynthesis”. New Phytologist, 2021, https://doi.org/10.1111/nph.17092.
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    2020

    • Iversen, Colleen M., et al. “Building a Culture of Safety and Trust in Team Science”. Eos, vol. 101, 2020, https://doi.org/10.1029/2020EO143064.
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    2019

    • Serbin, Shawn P., et al. “From the Arctic to the Tropics: Multibiome Prediction of Leaf Mass Per Area Using Leaf Reflectance”. New Phytologist, vol. 224, 2019, pp. 1557-68, https://doi.org/10.1111/nph.16123.
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    • Kumarathunge, Dushan P., et al. “No Evidence for Triose Phosphate Limitation of light‐saturated Leaf Photosynthesis under Current Atmospheric Carbon Dioxide Concentration”. Plant, Cell & Environment, vol. 42, no. 12, 2019, pp. 3241-52, https://doi.org/10.1111/pce.13639.
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    • Rogers, Alistair, et al. “Terrestrial Biosphere Models May Overestimate Arctic Carbon Dioxide Assimilation If They Do Not Account for Decreased Quantum Yield and Convexity at Low Temperature”. New Phytologist, vol. 223, no. 223, 2019, pp. 167-79, https://doi.org/10.1111/nph.15750.
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    • Burnett, Angela C., et al. “The ‘one‐point method’ for Estimating Maximum Carboxylation Capacity of Photosynthesis: A Cautionary Tale”. Plant, Cell & Environment, vol. 42, no. 8, 2019, pp. 2472-81, https://doi.org/10.1111/pce.13574.
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    2018

    • 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.
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    2017

    • 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.
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    • 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.
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    • 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.
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    • Rogers, Alistair, et al. “Terrestrial Biosphere Models Underestimate Photosynthetic Capacity and Carbon Dioxide Assimilation in the Arctic”. New Phytologist, vol. 216: 1090-1103, no. 4, 2017, pp. 1090-03, https://doi.org/10.1111/nph.14740.
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    2016

    • Ali, Ashehad A., et al. “A Global Scale Mechanistic Model of Photosynthetic Capacity (LUNA V1.0)”. Geoscientific Model Development, vol. 9, no. 2, 2016, pp. 587-06, https://doi.org/10.5194/gmd-9-587-201610.5194/gmd-9-587-2016-supplement.
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    • De Kauwe, Martin G., et al. “A Test of the ‘one-Point method’ for Estimating Maximum Carboxylation Capacity from Field-Measured, Light-Saturated Photosynthesis”. New Phytologist, no. 3, 2016, pp. 1130-44, https://doi.org/10.1111/nph.13815.
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    2015

    • Ali, Ashehad A., et al. “Global-Scale Environmental Control of Plant Photosynthetic Capacity”. Ecological Applications, vol. 25, no. 8, 2015, pp. 2349-65, https://doi.org/10.1890/14-2111.110.1890/14-2111.1.sm.
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    • Lin, Yan-Shih, et al. “Optimal Stomatal Behaviour Around the World”. Nature Climate Change, vol. 5, no. 5, 2015, pp. 459-64, https://doi.org/10.1038/nclimate2550.
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    2014

    • Rogers, Alistair, et al. “Improving Representation of Photosynthesis in Earth System Models”. New Phytologist, vol. 204, no. 1, 2014, pp. 12-14, https://doi.org/10.1111/nph.12972.
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    • Rogers, Alistair. “The Use and Misuse of Vc,max in Earth System Models”. Photosynthesis Research, vol. 119, no. 1-2, 2014, pp. 15-29, https://doi.org/10.1007/s11120-013-9818-1.
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  • Terri Velliquette

    2015

    • Devarakonda, Ranjeet, et al. “Use of a Metadata Documentation and Search Tool for Large Data Volumes: The NGEE Arctic Example”. 2015 IEEE International Conference on Big Data (Big Data), 2015, https://doi.org/10.1109/BigData.2015.7364086.
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