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Dr. Christine Chang
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 Education

2010 - 2016 Ph.D. in Plant Physiology, University of Toronto, Mississauga, ON, Canada
2005 - 2009 B.A. in Biology, Barnard College, Columbia University, New York, NY, USA

 

Professional Experience

2021- Present Research Plant Physiologist, USDA-ARS, Adaptive Cropping Systems Laboratory, Beltsville, MD
2010 -2021 Research Associate, Cornell University, Ithaca, NY
2018 - 2020 USDA-NIFA Postdoctoral Fellow, Cornell University, Ithaca, NY
2017 - 2018 Postdoctoral Associate, Cornell University, Ithaca, NY
2010 - 2016 Graduate Research Assistant, Department of Biology, University of Toronto Mississauga, Mississauga, ON, Canada
2009 Research Intern, Finnish Forestry Research Institute, Punkaharju, Finland
2007 Amgen Undergraduate Research Fellow,  Barnard College, New York, NY
2005 - 2009 Undergraduate Research Assistant,  Barnard College, New York, NY

 

Refereed Publications

  1. Näthe P., Julitta T., Chang C. Y., Burkart A., Migliavacca M., Rascher U. A Partial Least Square Regression approach for the retrieval of red and far-red fluorescence. Agriculture and Forest Meteorology (under review).

  2. Jain P., Liu W., Zhu S., Melkonian J., Pauli D., Riha S. J., Chang C. Y., Sun Y., Gore M. A., Stroock A. D. (2021) A minimally disruptive method for measuring water potential in-planta using hydrogel nanoreporters. Proceedings of the National Academy of Sciences of the United States of America (accepted).

  3. Zhang Y., Yang W., Sun Y., Chang C. Y., Yu J., Zhang W. Fusion of multispectral aerial imagery and vegetation indices for machine learning-based ground classification. Remote Sens., 13: 1411. doi: 10.3390/rs13081411

  4. Bendig J., Wang N., Chang C. Y., Atherton J., Malenovsky Z., Muller O., Rascher U. Measuring solar-induced fluorescence from unmanned aircraft systems for operational use in plant phenotyping and precision farming. IEEE IGARSS 2021 (accepted).

  5. Kira O., Chang C. Y., Gu L., Wen J., Hong Z., Sun Y. (2021) Partitioning net ecosystem exchange (NEE) of CO2 using solar-induced chlorophyll fluorescence (SIF). Geophys. Res. Lett., 48: e2020GL091247. doi: 10.1029/2020GL091247

  6. Chang C. Y., Zhou R., Kira O., Marri S., Skovira J., Gu L., Sun Y. (2020) An Unmanned Aerial System (UAS) for concurrent measurements of sun-induced chlorophyll fluorescence and hyperspectral reflectance to improve crop monitoring and stress detection. Agr. For. Meteorol., 294: 108145. doi: 10.1016/j.agrformet.2020.108145

  7. Chang C. Y., Bräutigam K., Hüner N. P. A., Ensminger I. (2020) How Evergreen Conifers Overwinter: Ecophysiology and Molecular Regulation. New Phytol., 229: 675-691. doi: 10.1111/nph.16904

  8. Chang C. Y., Guanter L., Frankenberg C., Köhler P., Gu L., Magney, T. S., Grossmann, K., Sun Y. (2020) Systematic assessment of retrieval methods for ground solar-induced chlorophyll fluorescence (SIF) using high-frequency automated field spectroscopy. J. Geophys. Res: Biogeosciences, 125: e2019JG005533. doi: 10.1029/2019JG005533

  9. Fréchette E., Chang C. Y., Ensminger I. (2020) Variation in the phenology of photosynthesis among eastern white pine provenances in response to warming. Global Change Biology, 26: 5217-5234. doi: 10.1111/gcb.15150

  10. Wen J., Köhler P., Duveiller G., Parazoo N. C., Yu L., Chang C. Y., Sun Y. (2020) Generating a long-term record of high-resolution global solar-induced chlorophyll fluorescence (SIF) by harmonizing multiple satellite instruments: A case study for fusing GOME-2 and SCIAMACHY. Remote Sens. Environ. 239: 111644. doi: 10.1016/j.rse.2020.111644

  11. Gu L., Han J., Wood J. D., Chang C. Y., Sun Y. (2019) Sun-Induced Chl fluorescence and its importance for biophysical modeling of photosynthesis based on light reactions. New Phytol. 223: 1179-1191. doi: 10.1111/nph.15796

  12. Yu L., Wen J., Chang C. Y., Frankenberg C., Sun Y. (2019) High-resolution global contiguous SIF of OCO-2. Geophys. Res. Lett. 46: 1449-1458. doi: 10.1029/2018GL081109

  13. Gu L., Wood J. D., Chang C. Y., Sun Y., Riggs J. S. (2018) Advancing Terrestrial Ecosystem Science with a Novel Automated Measurement System for Sun-Induced Chlorophyll Fluorescence for Integration with Eddy Covariance Flux Networks. J. Geophys. Res. Biogeosciences 124: 127-146. doi: 10.1029/2018JG004742

  14. Chang C. Y., Fréchette E., Unda F., Mansfield S. D., Ensminger I. (2016) Elevated temperature and CO2 stimulate late-season photosynthesis but impair cold hardening in pine. Plant Physiol. 172: 802-818. doi: 10.​1104/​pp.​16.​00753

  15. Fréchette E., Chang C. Y., Ensminger I. (2016) Photoperiod and temperature constraints on the relationship between the photochemical reflectance index and the light use efficiency of photosynthesis in Pinus strobus. Tree Physiol. 36: 311-324. doi: 10.1093/treephys/tpv143

  16. Chang C. Y., Unda F., Zubilewich A., Mansfield S. D., Ensminger I. (2015) Sensitivity of cold acclimation to elevated autumn temperature in field-grown Pinus strobus seedlings. Front. Plant Sci., 6: 165. doi: 10.3389/fpls.2015.00165

  17. Fréchette E., Wong C. Y. S., Junker L. V., Chang C. Y., Ensminger I. (2015) Zeaxanthin-independent energy quenching and alternative electron sinks cause a decoupling of the relation between the photochemical reflectance index (PRI) and photosynthesis in an evergreen conifer during spring. J. Exp. Bot. 66: 7309-7323. doi: 10.1093/jxb/erv427

  18. Ensminger I., Chang C. Y., Bräutigam K. (2015) Tree responses to environmental cues. In: A.-F. Adam-Blondon, C. Plomion (volume eds.), J.-P. Jacquot, & P. Gadal (serial eds.), Advances in Botanical Research Vol. 74 (p. 229-264), London: Elsevier Ltd. doi: 10.1016/bs.abr.2015.05.003