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Publications by Author

Last Name

Authors who are active project participants

  • Amy L. Breen

    2024

    • Wang, Chen, et al. “Local-Scale Heterogeneity of Soil Thermal Dynamics and Controlling Factors in a Discontinuous Permafrost Region”. Environmental Research Letters, vol. 19, 2024, https://doi.org/10.1088/1748-9326/ad27bb .
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    2021

    • Mekonnen, Zelalem A., et al. “Arctic Tundra Shrubification: A Review of Mechanisms and Impacts on Ecosystem Carbon Balance”. Environmental Research Letters, vol. 16, no. 5, 2021, p. 053001, https://doi.org/10.1088/1748-9326/abf28b.
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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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    • Yang, Dedi, et al. “Landscape-Scale Characterization of Arctic Tundra Vegetation Composition, Structure, and Function With a Multi-Sensor Unoccupied Aerial System”. Environmental Research Letters, vol. 16, no. 8, 2021, p. 085005, https://doi.org/10.1088/1748-9326/ac1291.
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    • Kropp, Heather, et al. “Shallow Soils Are Warmer under Trees and Tall Shrubs across Arctic and Boreal Ecosystems”. Environmental Research Letters, vol. 16, no. 1, 2021, p. 015001, https://doi.org/10.1088/1748-9326/abc994.
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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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    2020

    • Yang, Dedi, et al. “A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra”. Remote Sensing, vol. 12, no. 16, 2020, p. 2638, https://doi.org/10.3390/rs12162638.
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    • Euskirchen, Eugénie S., et al. “Co‐producing Knowledge: The Integrated Ecosystem Model for Resource Management in Arctic Alaska”. Frontiers in Ecology and the Environment, vol. 18, no. 1, 2020, pp. 447-55, https://doi.org/10.1002/fee.2176.
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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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    2016

    • Euskirchen, Eugénie S., et al. “Consequences of Changes in Vegetation and Snow Cover for Climate Feedbacks in Alaska and Northwest Canada”. Environmental Research Letters, vol. 11, no. 10, 2016, https://doi.org/10.1088/1748-9326/11/10/105003.
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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

    • 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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  • Susan L. Heinz

    2020

    • Krassovski, Misha B., et al. “Hybrid-Energy Module for Remote Environmental Observations, Instruments, and Communications”. Advances in Polar Science , vol. 31, no. 3, 2020, pp. 156-6, https://doi.org/10.13679/j.advps.2020.0008.
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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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