Multiscale remote sensing of plant physiology and carbon uptake
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Date
12//2/25/0Author
Atherton, Jon Mark
Metadata
Abstract
This study investigated the use of optical remote sensing for estimating leaf and
canopy scale light use efficiency (LUE) and carbon exchange. In addition, a new
leaf level model capable of predicting dynamic changes in apparent reflectance
due to chlorophyll fluorescence was developed.
A leaf level study was conducted to assess the applicability of passive remote
sensing as a tool to measure the reduction, and the subsequent recovery, of
photosynthetic efficiency during the weeks following transplantation. Spectral
data were collected on newly planted saplings for a period of 8 weeks, as well
as gas exchange measurements of LUE and PAM fluorescence measurements. A
set of spectral indices, including the Photochemical Reflectance Index (PRI),
were calculated from the reflectance measurements. A marked depression in
photosynthetic rate occurred in the weeks after outplanting followed by a gradual
increase, with recovery occurring in the later stages of the experimental period.
As with photosynthetic rate, there was a marked trend in PRI values over the
study period but no trend was observed in chlorophyll based indices. The study
demonstrated that hyperspectral remote sensing has the potential to be a useful
tool in the detection and monitoring of the dynamic effects of transplant shock. Relationships between hyperspectral reflectance indices, airborne carbon exchange
measurements and satellite observations of ground cover were then explored
across a heterogeneous Arctic landscape. Measurements were collected
during August 2008, using the University of Edinburgh’s research aircraft, from
an Arctic forest tundra zone in northern Finland as part of the Arctic Biosphere
Atmosphere Coupling at Multiple Scales (ABACUS) study. Surface fluxes of CO2
were calculated using the eddy covariance method from airborne data that were
collected from the same platform as hyperspectral reflectance measurements. Airborne
CO2 fluxes were compared to MODIS vegetation indices. In addition, LUE
was estimated from airborne flux data and compared to airborne measurements
of PRI. There were no significant relationships between MODIS vegetation indices
and airborne flux observations. There were weak to moderate (R2 = 0.4 in
both cases) correlations between PRI and LUE and between PRI and incident
radiation.
A new coupled physiological radiative transfer model that predicts changes in the
apparent reflectance of a leaf, due to chlorophyll fluorescence, was developed. The
model relates a physically observable quantity, chlorophyll fluorescence, to the sub
leaf level processes that cause the emission. An understanding of the dynamics
of the processes that control fluorescence emission on multiple timescales should
aid in the interpretation of this complex signal. A Markov Chain Monte Carlo
(MCMC) algorithm was used to optimise biochemical model parameters by fitting
model simulations of transient chlorophyll fluorescence to measured reflectance
spectra. The model was then validated against an independent data set. The
model was developed as a precursor to a full canopy scheme. To scale to
the canopy and to use the model on trans-seasonal time scales, the effects of
temperature and photoinhibition on the model biochemistry needs to be taken
into account, and a full canopy radiative transfer scheme, such as FluorMOD,
must be developed.
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