Nitrogen and Phosphorus Effect on Sun-Induced Fluorescence and Gross Primary Productivity in Mediterranean Grassland
"> Figure 1
<p>Energy partitioning at the leaf and canopy level representing the processes involved in the photosynthetic light use efficiency model (GPP = APAR x LUE<sub>p</sub>) and fluorescence light use efficiency model (F<sub>760</sub> = APAR *LUE<sub>f</sub> * Fesc) are represented with solid arrows. Dotted arrows represent the hypothesized relationship between leaf traits, canopy structure and the various processes related to the allocation of energy and transfer of SIF within the canopy. Photosynthetic active radiation (PAR); absorbed (by vegetation) photosynthetic active radiation (APAR); PAR absorbed by chlorophyll a and b molecules (APAR<sub>green</sub>), represented as the green bar in the equations on both sides of the figure; gross primary production (GPP); sun-induced fluorescence emitted by all leaves at 760 nm (F<sub>760leaf</sub>); sun-induced fluorescence at 760 nm observed at top of canopy (F<sub>760</sub>); nitrogen concentration on a mass basis (N%); chlorophyll a and b on a mass basis (Cab); leaf mass per area (LMA); maximum carboxylation rate (Vcmax); leaf area index (LAI); leaf angle distribution (LAD).</p> "> Figure 2
<p>Bar graphs representing differences among treatments (control treatment, C; nitrogen treatment, N; nitrogen and phosphorus treatment, NP; and control treatment, C) of Gross Primary Production (GPP) in 2014 (<b>a</b>) and 2015 (<b>b</b>); light use efficiency of photosynthesis (LUE<sub>p</sub>) in 2014 (<b>c</b>) and 2015 (<b>d</b>); Fluorescence at 760 nm (F<sub>760</sub>) in 2014 (<b>e</b>) and 2015 (<b>f</b>); light use efficiency of fluorescence emission at 760 nm (LUE<sub>f</sub>) in 2014 (<b>g</b>) and 2015 (<b>h</b>); and fraction of F<sub>760</sub> that escapes the canopy (Fesc<sub>fw</sub>) in 2014 (<b>i</b>) and 2015 (<b>l</b>). Data are divided among campaigns. Bar graphs represent means and error bars represent 1 standard error. Group differences in (<b>a</b>–<b>h</b>) were analyzed with ANOVA test and individual differences among groups were evaluated with Tukey HSD post hoc test. Group differences in (<b>i</b>,<b>l</b>) were analyzed with ANOVA with the Welch correction and individual differences among groups were evaluated with the Games–Howell post hoc test. “*” refers to a significant difference from the control treatment with <span class="html-italic">p</span> value < 0.05 and “**” refers to a significant difference from the control treatment with <span class="html-italic">p</span> value < 0.01.</p> "> Figure 3
<p>Bar graph representing differences among treatments (control treatment, C; nitrogen treatment, N; nitrogen and phosphorus treatment, NP; and control treatment, C) of Canopy nitrogen content (N%) in 2014 (<b>a</b>) and 2015 (<b>b</b>); absorbed photosynthetic active radiation (APAR) in 2014 (<b>c</b>) and 2015 (<b>d</b>); Albedo<sub>400–900</sub> in 2014 (<b>e</b>) and 2015 (<b>f</b>); Surface Temperature (Ts) in 2014 (<b>g</b>) and 2015 (<b>h</b>); and graminoids relative abundance (%graminoids) in 2014 (<b>i</b>) and 2015 (<b>l</b>). Data are divided among campaigns. Bar graphs represent means and error bars represent 1 standard error. Group differences in (<b>e</b>–<b>h</b>) were analyzed with ANOVA test and individual differences among groups were evaluated with Tukey HSD post hoc test. Group differences in (<b>a</b>,<b>b</b>,<b>i</b>,<b>l</b>) were analyzed with ANOVA with the Welch correction and individual differences among groups were evaluated with the Games–Howell post hoc test. “*” refers to a significant difference from the control treatment with <span class="html-italic">p</span> value < 0.05 and “**” refers to a significant difference from the control treatment with <span class="html-italic">p</span> value < 0.01.</p> "> Figure 4
<p>Scatterplot of observed fluorescence at 760 nm from top of canopy (F<sub>760</sub>) vs. Gross Primary Production (GPP) for 2014 (<b>a</b>) and for 2015 (<b>c</b>); and directional fluorescence emitted by all leaves at 760 nm calculated from forward SCOPE runs (F<sub>760leaf,fw</sub>) vs. GPP for 2014 (<b>b</b>) and for 2015 (<b>d</b>). Data are divided for the four treatments; control (C), nitrogen addition (N), nitrogen and phosphorus addition (NP) and phosphorus addition (P). P values of the interaction treatment with independent variable (in comparison with the control treatment, C) from an analysis of covariance (ANCOVA) are reported in the bottom-right of each panel. Colored lines represent the regression from the ordinary least square regression.</p> "> Figure 5
<p>Relative importance analysis with “lmg”(Lindeman, Merenda and Gold) method of Light use efficiency of photosynthesis (LUE<sub>p</sub>), Light use efficiency of fluorescence emission at 760 nm (LUE<sub>f</sub>) and escape probability of sun-induced fluorescence at 760 nm obtained from forward runs of SCOPE (Fesc<sub>fw</sub>). Predictors included in the analysis are: soil moisture, Shannon biodiversity index (H), canopy nitrogen content (N%), surface temperature (Ts), relative abundance of legumes (%legumes), relative abundance of graminoids (%graminoids) and leaf area index (LAI). Error bars (1 SE) are calculated through bootstrapping (<span class="html-italic">n</span> = 1000), but are not shown in the figure. They are however reported in the result section.</p> "> Figure 6
<p>Path analysis displays the role of canopy nitrogen content (Canopy N) and relative graminoids abundance (%graminoids) on the energy partitioning at the leaf and canopy level. Photosynthetic active radiation (PAR); absorbed by vegetation photosynthetic active radiation (APAR); fluorescence emission by all leaves at 760 nm calculated by forward runs of SCOPE (F<sub>760leaf,fw</sub>); gross primary production (GPP); surface temperature (Ts); and observed fluorescence at 760 nm (F<sub>760</sub>). The strength of the relationship among variables is expressed by the standardized coefficient (β) of the path analysis. Each standardized coefficient has a standard error obtained from bootstrapping (<span class="html-italic">n</span> = 100 times). The width of the arrows is proportional to their standardized coefficient (β). Colored lines (both solid or dotted) represent direct relationships between variables, whereas gray double-headed arrows represent the covariance among variables. Solid and dotted lines indicate significant (<span class="html-italic">p</span> < 0.05) and non-significant relationships, respectively. The width of the arrows is proportional to their standardized coefficient (β). The different colors are introduced to increase readability of the standardized path coefficients. The fit by the overall model is measured by means of Chi-squared (χ2), comparative fit index (CFI) and standardized root mean square of residual (SRMR).</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Site
2.2. Nutrient Manipulation Experiment, Gross Primary Production and Ancillary Data
2.3. Transpiration Estimates
2.4. Field Spectroscopy, Retrieval of Sun-Induced Fluorescence and Biophysical Properties
2.5. SCOPE Model Simulations
2.6. Calculation of the Light Use Efficiency of Photosynthesis (LUEp), Light use Efficiency of Fluorescence Emission (LUEf) and Escape Probability of F760 (Fesc)
2.7. Statistical Analysis
3. Results
3.1. Description of Fertilization Effects on Fluxes, Optical Data, and Vegetation Characteristics
3.2. Temporal Variability of GPP–F760 and GPP–F760leaf.fw Relationship among Treatments
3.3. Factors Controlling the Parameters of Light Use Efficiency Equation (LUEp, LUEf and Fesc)
3.4. Mechanisms behind the Treatment Effect on GPP and F760 at Leaf and Canopy Scale
4. Discussion
4.1. Treatment Effect on LUEp, LUEf, Fescfw
4.2. Predictors of the Terms of the Light Use Efficiency Equation
4.3. Mechanisms behind the Treatment Effect on GPP and F760 at Leaf and Canopy Scale
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Date | Campaign | Fertilization | PAR μmol s−1 m−2 | VPD hPa | Ta °C | SWC % | SZA ° |
---|---|---|---|---|---|---|---|
20-03-2014 | 1 | No | 1604.82 ± 11.33 | 12.59 ± 0.38 | 24.2 ± 0.2 | 19.01 ± 0.27 | 41.86 ± 0.23 |
15-04-2014 | 2 | Yes | 1842.92 ± 32.63 | 15.12 ± 0.59 | 30.09 ± 0.55 | 22.58 ± 0.58 | 31.83 ± 0.85 |
7-05-2014 | 3 | Yes | 1342.1 ± 93.73 | 22.4 ± 1.98 | 32.1 ± 0.91 | 4.78 ± 0.09 | 25.69 ± 0.6 |
27-05-2014 | 4 | Yes | 1417.15 ± 104.4 | 15.83 ± 1.2 | 27.89 ± 0.47 | 6.57 ± 0.09 | 21.4 ± 0.82 |
04-03-2015 | 5 | Yes | 1411.29 ± 18.05 | 7.01 ± 0.36 | 23.9 ± 0.48 | 21.49 ± 1.91 | 49.66 ± 0.49 |
23-04-2015 | 6 | Yes | 1842.64 ± 25.23 | 16.38 ± 0.84 | 29.98 ± 0.37 | 6.7 ± 0.11 | 31.21 ± 0.98 |
27-05-2015 | 7 | Yes | 1955.21 ± 35.25 | 23.2 ± 1.56 | 36.33 ± 0.73 | 1.14 ± 0.02 | 24.26 ± 1.87 |
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Martini, D.; Pacheco-Labrador, J.; Perez-Priego, O.; van der Tol, C.; El-Madany, T.S.; Julitta, T.; Rossini, M.; Reichstein, M.; Christiansen, R.; Rascher, U.; et al. Nitrogen and Phosphorus Effect on Sun-Induced Fluorescence and Gross Primary Productivity in Mediterranean Grassland. Remote Sens. 2019, 11, 2562. https://doi.org/10.3390/rs11212562
Martini D, Pacheco-Labrador J, Perez-Priego O, van der Tol C, El-Madany TS, Julitta T, Rossini M, Reichstein M, Christiansen R, Rascher U, et al. Nitrogen and Phosphorus Effect on Sun-Induced Fluorescence and Gross Primary Productivity in Mediterranean Grassland. Remote Sensing. 2019; 11(21):2562. https://doi.org/10.3390/rs11212562
Chicago/Turabian StyleMartini, David, Javier Pacheco-Labrador, Oscar Perez-Priego, Christiaan van der Tol, Tarek S. El-Madany, Tommaso Julitta, Micol Rossini, Markus Reichstein, Rune Christiansen, Uwe Rascher, and et al. 2019. "Nitrogen and Phosphorus Effect on Sun-Induced Fluorescence and Gross Primary Productivity in Mediterranean Grassland" Remote Sensing 11, no. 21: 2562. https://doi.org/10.3390/rs11212562