Welcome to the Gamon Lab website

Dr. Gamon studies the "breathing of the planet" - the exchanges of carbon and water vapour between the biosphere and the atmosphere that affect ecosystem productivity and help regulate our atmosphere and climate.

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Research Topics

· Disturbance effects on ecosystem function
· Climate change impacts in northern latitude ecosystems
· Optical tools for sampling terrestrial ecosystems
· Detecting plant biochemical responses with non-contact optical methods
· Stress-related plant ecophysiology and photosynthesis changes
· Eco-informatics and Cyberinfrastructure for ecosystem monitoring

Research Topics

What is a spectral laboratory?

Dr. Gamon's Spectral Laboratory focuses on the use of optical remote sensing to evaluate vegetation productivity. Dr. Gamon founded SpecNet toward this goal and developed of a number of spectral reflectance tools (uni-spec, multi-spec) that can be used in analyzing field, airborne and spacecraft data.


Join us!

Do you want to understand reflectance and global productivity at a deeper level? Apply online to join Gamon Lab as a Post-Doctoral Fellow, Ph.D. or Master's student.

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"I welcome inquiries from applicants interested in ecology (ecophysiology, ecosystems ecology), remote sensing, ecosystem modeling and eco-informatics and cyberinfrastructure. Please complete an online application."

Current Projects

  • “Evaluating growing season length and productivity across the ABoVE Domain using novel satellite indices and a ground sensor network”(ABoVE Program, NASA, USA)

    How are growing season length and primary productivity changing in the boreal and arctic regions of Alaska and western Canada and what drives these changes?  Using satellite remote sensing and ground measurements (optical sensors and eddy covariance), this project investigates patterns of “greening” and “browning” detected in satellite time series data, and seeks to resolve the underlying causes, including disturbance, climate variation, and climate change leading to altered temperatures and hydrology.  Key tools will include the light-use efficiency model and novel satellite-derived pigment indices that detect invisible photosynthetic activity in evergreen vegetation.  This 3-year project is part of a 9-year NASA ABoVE program, and is funded through the University of Nebraska.
  • “The functional significance of plant optical diversity: a multi-scale analysis” (NSERC, Canada)
    This project applies new optical sampling methods to study biodiversity, gas exchange (the breathing of the planet), and ecosystem feedbacks to the atmosphere and climate.  The central theme is “optical diversity” – variation in vegetation optical patterns in time and space – because optical variation reveals useful information about underlying species richness, functional diversity, and ecosystem processes. 
  • “Quantifiying the carbon balance of Mattheis Ranch” (Rangeland Research Institute, U. Alberta).
    This project measures net carbon uptake at Mattheis Ranch using eddy covariance and remote sensing methods, validated by independent ground sampling. This work can provide a basis for improved rangeland management that optimizes carbon sequestration, ecosystem productivity and biodiversity. 
  • “Imaging Spectrometry & Cyberinfrastructure for Biospheric Carbon Monitoring” (AITF)
    This project uses novel field sensors and remote sensing to monitor patterns of ecosystem-atmosphere carbon exchange (the “breathing of the planet”).  A key focus is the integration of optical remote sensing with gas flux measurements, with the goal of developing improved optical methods of monitoring ecosystem function.
  • "Linking remotely sensed optical diversity to genetic, phylogenetic and functional diversity to predict ecosystem processes."  (Collaborative Research, US NSF & NASA)
  • Funded by the US National Science Foundation (NSF) and the National Aeronautic and Space Administration (NASA), this project will explore the ability of remote sensing to detect biodiversity at many levels. In particular, we will test the Optical Diversity and Surrogacy hypotheses using experimental studies at Cedar Creek Reserve and other sites in the US Midwest. Interested applicants should also consider applying directly to partner universities, which include the University of Nebraska and the University of Minnesota. Click here to read the project ABSTRACT.
  • "Ecological Spectral Information System (ESIS): Integration of Spectral Data with Measurements of Vegetation Functional Traits" (Collaborative Research, NASA)
  • Funded by the US National Aeronautic and Space Administration (NASA), this project is developing spectral data systems (databases and related software tools for processing, analyzing, visualizing and archiving spectral data) for ecological questions. Project PI: Phil Townsend (University of Wisconsin). Opportunities for this project are funded through partner institutions, including the University of Wisconsin, the University of Nebraska, and SpecNet. Interested applicants should consider applying through one of these institutions. Click here to read the project Overview & Synopsis.
    Links to Related Projects:
  • SpecNet – Spectral Network
  • Research Opportunities

    Positions available for motivated postdoctoral fellows, graduate students and undergraduate students

    Postdoc Positions :

    1. “Quantifying rangeland carbon balance” (Alberta, Canada).
    2. "Evaluating growing season length and productivity across the ABoVE Domain" (Lincoln, Nebraska, USA)
    3. "Remote Sensing of Biodiversity" (Lincoln, Nebraska, USA).

    Student Positions: Graduate and undergraduate research opportunities are available (University of Alberta and Universty of Nebraska)

    Technical Positions: Technical support opportunites are available (University of Alberta and Universty of Nebraska)

    Funding sources: NASA (US), NSF (US), AITF (Alberta), Rangeland Research Institute (U. Alberta), NSERC (Canada), SpecNet and Decagon Inc. (Pullman WA, USA).

    Duties vary with topic and level of experience & training.

    Applicants should submit a preliminary application via this website, or contact John Gamon (jgamon@gmail.com).


    Latest News

    Congratulations to recent lab graduates:
    Chris Wong
    Olga Kovalchuk
    Evan DeLancey
    Saulo Castro
    Don Wehlage

    Craig Emmerton

    Welcome to new labmembers Ran Wang, Kyle Springer, and
    Shayna Harris

    Recent Publications

    1. Emmerton CA, St. Louis VL, Humphreys ER, Barker JD, Gamon JA, Pastorello GZ (2015) The net ecosystem exchange of rapidly changing high Arctic landscapes and potential for upscaling.  Global Change Biology.  First published online: DOI: 10.1111/gcb.13064 

    2. Flanagan LB, Sharp EJ, Gamon JA (2015)Application of the photosynthetic light-use efficiency model in a northern Great Plains grassland.  Remote Sensing of Environment. 168:239-251.   

    3. Gamon JA (2015)Optical sampling of the flux tower footprint.  Biogeosciences 12: 4509-4523.  doi:10.5194/bg-12-4509-2015 (EuroSpec Special Issue

    4. Gamon JA, Kovalchuk O, Wong CYS, Harris A, Garrity SR (2015). Monitoring seasonal and diurnal changes in photosynthetic pigments with automated PRI and NDVI sensors.  Biogeosciences 12: 4149-4159.  doi:10.5194/bg-12-4149-2015

    5. Wong CYS, Gamon JA (2015) The Photochemical Reflectance Index (PRI) provides an optical indicator of spring photosynthetic activation in conifers   New Phytologist. 206: 196–208, doi: 10.1111/nph.13251    

    6. Wong, CYS, Gamon JA (2015) Three causes of variation in the Photochemical Reflectance Index (PRI) in evergreen conifers.  New Phytologist  206: 187–195, doi: 10.1111/nph.13159   

    7. Gitelson A, Gamon  JA (2015) The need for a common basis for defining light-use efficiency: implications for productivity estimation.  Remote Sensing of Environment 156:196-201.

    8. Harris A., Gamon JA., Pastorello G.Z., *Wong CYS (2014) Retrieval of the photochemical reflectance index for assessing xanthophyll cycle activity: a comparison of near-surface optical sensors, Biogeosciences

    9. Williamson SN, Hik DS, Gamon JA, Kavanaugh JL, Flowers GE (2014) Estimating mean surface air temperature from MODIS Land Surface Temperature observations in a sub-Arctic alpine environment.  Remote Sensing 6(2):946-963. DOI: 10.3390/rs6020946. 

    Click here for a more complete list of Dr. Gamon's papers.