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| Titel |
Mechanisms behind the estimation of photosynthesis traits from leaf reflectance observations |
| VerfasserIn |
Benjamin Dechant, Matthias Cuntz, Daniel Doktor, Michael Vohland |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250129230
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| Publikation (Nr.) |
 EGU/EGU2016-9308.pdf |
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| Zusammenfassung |
| Many studies have investigated the reflectance-based estimation of leaf chlorophyll, water
and dry matter contents of plants. Only few studies focused on photosynthesis traits, however.
The maximum potential uptake of carbon dioxide under given environmental conditions is
determined mainly by RuBisCO activity, limiting carboxylation, or the speed of
photosynthetic electron transport. These two main limitations are represented by the
maximum carboxylation capacity, V cmax,25, and the maximum electron transport rate,
Jmax,25. These traits were estimated from leaf reflectance before but the mechanisms
underlying the estimation remain rather speculative. The aim of this study was therefore
to reveal the mechanisms behind reflectance-based estimation of V cmax,25 and
Jmax,25.
Leaf reflectance, photosynthetic response curves as well as nitrogen content
per area, Narea, and leaf mass per area, LMA, were measured on 37 deciduous
tree species. V cmax,25 and Jmax,25 were determined from the response curves.
Partial Least Squares (PLS) regression models for the two photosynthesis traits
V cmax,25 and Jmax,25 as well as Narea and LMA were studied using a cross-validation
approach. Analyses of linear regression models based on Narea and other leaf traits
estimated via PROSPECT inversion, PLS regression coefficients and model residuals
were conducted in order to reveal the mechanisms behind the reflectance-based
estimation.
We found that V cmax,25 and Jmax,25 can be estimated from leaf reflectance with good to
moderate accuracy for a large number of species and different light conditions. The dominant
mechanism behind the estimations was the strong relationship between photosynthesis traits
and leaf nitrogen content. This was concluded from very strong relationships between PLS
regression coefficients, the model residuals as well as the prediction performance of Narea-
based linear regression models compared to PLS regression models. While the
PLS regression model for V cmax,25 was fully based on the correlation to Narea,
the PLS regression model for Jmax,25 was not entirely based on it. Analyses of
the contributions of different parts of the reflectance spectrum revealed that the
information contributing to the Jmax,25 PLS regression model in addition to the main
source of information, Narea, was mainly located in the visible part of the spectrum
(500-900 nm). Estimated chlorophyll content could be excluded as potential source
of this extra information. The PLS regression coefficients of the Jmax,25 model
indicated possible contributions from chlorophyll fluorescence and cytochrome f
content.
In summary, we found that the main mechanism behind the estimation of V cmax,25 and
Jmax,25 from leaf reflectance observations is the correlation to Narea but that there is
additional information related to Jmax,25 mainly in the visible part of the spectrum. |
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