Nitrogen controls plant canopy light‐use efficiency in temperate and boreal ecosystems

Abstract

[1] Optimum daily light-use efficiency (LUE) and normalized canopy photosynthesis (GEE*) rate, a proxy for LUE, have been derived from eddy covariance CO 2 flux measurements obtained at a range of sites located in the mid to high latitudes. These two variables were analyzed with respect to environmental conditions, plant functional types (PFT) and leaf nitrogen concentration, in an attempt to characterize their variability and their potential drivers. LUE averaged 0.0182 mol/mol with a coefficient of variation of 37% (42% for GEE*). Foliar nitrogen N of the dominant plant species was found to explain 71% of LUE (n = 26) and 62% of GEE* (n = 44) variance, across all PFTs and sites. Mean Annual Temperature, MAT, explained 27% of LUE variance, and the two factors (MAT and N) combined in a simple linear model explain 80% of LUE and 76% GEE* variance. These results showed that plant canopies in the temperate, boreal and arctic zones fit into a general scheme closely related to the one, which had been established for plant leaves worldwide. The N-MAT-LUE relationships offer perspectives for LUE-based models of terrestrial photosynthesis based on remote sensing. On a continental scale, the decrease of LUE from the temperate to the arctic zone found in the data derived from flux measurements is not in line with LUE resulting from inversion of atmospheric CO 2 .

Modeling and Partitioning of Regional Evapotranspiration Using a Satellite-Driven Water-Carbon Coupling Model

“…For example, the slope coefficient in the Ball-Berry model (Equation (2)) was estimated as 7.5 to 10.3, consistent with the values in Community Land Model(CLM)4.0 [43]. The estimated maximum light-use efficiency values (0.0011 mg·CO 2 ·µmol −1 PPFD for forest and grassland and 0.0022 mg·CO 2 ·µmol −1 PPFD for cropland) are located in the middle range of ε max variations in the meta-analyses of Kergoat et al [44] and Garbulsky et al [45]. Note that we derived ε max using the NDVI data to estimate FPAR (Equation (3)).…”

Productivity, absorbed photosynthetically active radiation, and light use efficiency in crops: Implications for remote sensing of crop primary production

“…Recent studies have shown that LUE varies considerably within vegetation types, at different phenological stages, and under varying environmental conditions (Prince, 1991;Medlyn, 1998;Gower et al, 1999;Ruimy et al, 1999;Turner et al, 2003;Xu and Baldocchi, 2003;Houborg et al, 2011Houborg et al, , 2013. Analysis by Kergoat et al (2008) strongly supports the view that LUE varies significantly not only across and within biomes, but also among plant functional types. Thus, there is little doubt that the assumption of a constant LUE does not provide an accurate description of terrestrial ecosystems (Binkley et al, 2004;Bradford et al, 2005;Kergoat et al, 2008).…”

Using Different Regression Methods to Estimate Leaf Nitrogen Content in Rice by Fusing Hyperspectral LiDAR Data and Laser-Induced Chlorophyll Fluorescence Data

“…Apart from the fact that BP-NNs have a lower R 2 than SVMs and RBF-NNs, ANNs (BP-NNs and RBF-NNs) yield the same results which are consistent with SVMs when they are used for rice LNC estimation on the basis of fluorescence data in two stages. 1,2 Parameters in order to optimize the accuracy in SVM regression; 3 The LIF peaks at 450 nm, 510 nm, 685 nm and 740 nm; 4 The LIF indices developed with blue, red, and far-red bands using Equation (3); 5 The number of layers in BP-ANN analysis; 6 The spread of RBF in RBF-NN analysis; 7 The number of principal component (PCs) in PLSR analysis.…”