Townsend, Philip (Phil): University of Wisconsin (Project Lead)
Project Funding:
2012 - 2016
NRA: 2011 NASA: HyspIRI Preparatory Airborne Activities and Associated Science and Applications
Funded by NASA
Abstract:
Using the California transects for the proposed HyspIRI field campaign in 2013-2014, we will comprehensively assess the potential to make spatially explicit estimates of two important parameters characterizing leaf and canopy photosynthetic capacity: the maximum rate of CO2 carboxylation by RuBisCo (Vcmax), and the maximum rate of electron transport required for the regeneration of RuBP needed in Calvin Cycle processes (Jmax). These variables are typically determined using measures of leaf gas exchange, but we have identified an approach to estimate Vcmax and Jmax using spectroscopy (Serbin et al., 2012). It follows that estimation of these variables from remotely sensed hyperspectral+thermal data will facilitate prediction of seasonal canopy assimilation across large areas using similar data from the anticipated HyspIRI mission. Our proposed work relies on the simultaneous acquisition of hyperspectral and thermal infrared imagery, as estimates of canopy temperature will be crucial for an accurate characterization of Vcmax and Jmax . The research will be conducted across two climate-elevation gradients in California, and will span a vegetation gradient from coastal sage and chaparral to oak woodlands and closed-canopy conifer forests. For two years, combined hyperspectral and thermal infrared imagery will be collected at key intervals during the growing season along each climate-elevation gradient. The resulting estimates of Vcmax and Jmax will be evaluated against those derived from eddy flux-based observations of canopy gas exchange, and will be used to generate high-resolution spatio-temporal estimates of gross primary productivity (GPP) that will then be compared to concurrent measures of plot-level productivity. Specifically, we propose to:
1. Calibrate leaf-level values of Vcmax and Jmax, derived from photosynthetic CO2-responses (using the LI-6400 Portable Photosynthesis system) measured across a range of temperatures and vegetation types, to leaf-level spectroscopy using partial least-squares regression.
2. Use the 4SAIL2 radiative transfer model (Verhoef et al., 2007) to scale Vcmax and Jmax to AVIRIS via radiative transfer modeling, using ground-based measurements of canopy structure. MASTER data will be used to retrieve canopy temperature and generate temperature-normalized values of metabolic properties for each canopy (e.g. Vcmax,Jmax at 25 deg C) from the instantaneous values.
3. We will then compare our measurements of Vcmax and Jmax to estimates derived from ten eddy covariance flux towers located within the proposed footprints of the aerial campaign, using a simple ecosystem model and Bayesian parameter estimation.
4. Finally, we will apply a Farquhar-von Caemmerer-Berry (FvCB) photosynthesis model to convert airborne estimates of photosynthetic parameters and associated canopy traits to pixel-level GPP values, and compare those to vegetation productivity measured in a set of plots located near each of the ten flux towers.
If successful, this activity will demonstrate a unique capacity of the proposed HyspIRI mission, which will make comparable measurements to what we are proposing for an airborne system, but at a global scale at a 19-day repeat interval.
This research specifically addresses three HyspIRI science questions: VQ2. Ecosystem Function, Physiology and Seasonal Activity; VQ3. Biogeochemical Cycles; and especially CQ4. Ecosystem Function and Diversity. Our team includes expertise in imaging spectroscopy (Townsend and Serbin), data assimilation (Serbin and Desai), plant physiology (Kruger), and eddy covariance techniques and modeling (Desai and Goulden).
Publications:
Cavender-Bares, J., Meireles, J., Couture, J., Kaproth, M., Kingdon, C., Singh, A., Serbin, S., Center, A., Zuniga, E., Pilz, G., Townsend, P. 2016. Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity. Remote Sensing. 8(3), 221. DOI: 10.3390/rs8030221
Christian, B., Joshi, N., Saini, M., Mehta, N., Goroshi, S., Nidamanuri, R. R., Thenkabail, P., Desai, A. R., Krishnayya, N. S. R. 2015. Seasonal variations in phenology and productivity of a tropical dry deciduous forest from MODIS and Hyperion. Agricultural and Forest Meteorology. 214-215, 91-105. DOI: 10.1016/j.agrformet.2015.08.246
DuBois, S., Desai, A. R., Singh, A., Serbin, S. P., Goulden, M. L., Baldocchi, D. D., Ma, S., Oechel, W. C., Wharton, S., Kruger, E. L., Townsend, P. A. 2018. Using imaging spectroscopy to detect variation in terrestrial ecosystem productivity across a water-stressed landscape. Ecological Applications. 28(5), 1313-1324. DOI: 10.1002/eap.1733
Serbin, S. P., Singh, A., Desai, A. R., Dubois, S. G., Jablonski, A. D., Kingdon, C. C., Kruger, E. L., Townsend, P. A. 2015. Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy. Remote Sensing of Environment. 167, 78-87. DOI: 10.1016/j.rse.2015.05.024
Serbin, S. P., Wu, J., Ely, K. S., Kruger, E. L., Townsend, P. A., Meng, R., Wolfe, B. T., Chlus, A., Wang, Z., Rogers, A. 2019. From the Arctic to the tropics: multibiome prediction of leaf mass per area using leaf reflectance. New Phytologist. 224(4), 1557-1568. DOI: 10.1111/nph.16123
More details may be found in the following project profile(s):
