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Divergent responses of forest dominant trees species to the manipulated canopy and understory nitrogen additions in terms of foliage stoichiometric, economic and hydraulic traits

Cite this dataset

Zhang, Zhenzhen et al. (2021). Divergent responses of forest dominant trees species to the manipulated canopy and understory nitrogen additions in terms of foliage stoichiometric, economic and hydraulic traits [Dataset]. Dryad. https://doi.org/10.5061/dryad.bzkh1895f

Abstract

Nitrogen (N) deposition effects on the stoichiometric balance and photosynthetic and  hydraulic couplings in subtropical forests has drawn wide attentions. The previously adopted understory application of N fertilization is criticized because it might ignore foliar N retention for different species. This paper reports a fertilizing application from the canopy (CAN) and under the canopy (UAN) in a phosphorus (P) limited ecosystemFoliage stoichiometric, photosynthetic and hydraulic traits of six dominant species were measured and analyzedBoth treatments equally enhanced foliage N and N/P, but not foliage P, who was highly species-specific depending on tree height, which implied enhanced P limitation. Decreased isotope abundance of 15N (δ15N) that approaching to the level in the urea fertilizer under CAN suggested the existence of canopy retention of N. Besides, N response sensitivity  of  N, P and δ15that positively related to tree height (H) under CAN indicated different exposure to the added N, which promoted stoichiometric imbalance  among  species. The photosynthetic traits represented by net photosynthesis (An) increased under both treatments. A divergent foliar photosynthetic and hydraulic traits varations was identified by signifcant decreased stomatal conductance (gs) and An /gs for CAN treatments, which induced the elevated isotope abundance of 13C (δ13C). Correspondingly, foliage hydraulic traits that shifted to water use efficiency axis were identified only under CAN in principal component analysis. Overall, our results proved that the canopy obsorbtion and species heterogeneity should be considered regarding foliar safety vs efficiency trade-off in response to nitrogen additions in the future.

Methods

1. Foliage photosynthetic and hydraulic traits

The maximum net photosynthetic rate (An) and stomatal conductance (gs) were measured with a Li-Cor LI-6400XT portable photosynthesis system (Li-Cor Inc., Lincoln, NE, USA) on three trees from each species in the different treatments. Three leaves from different separate branches on the top of each tree were chosen for measurement from 9:00-17:00 on sunny days in October 2014 and 2015. The saturating photon flux density was set at 1,500 μmol m-2 s-1, and the air temperature and the CO2 concentration in the leaf chamber were maintained at 20°C and 400±20 μmol mol-1, respectively. The leaves of each branch from each species were collected after measurements, classified according to their treatments, then brought to the laboratory, and carefully kept in a refrigerator for further experiments.

Fresh leaves from each treatment were chopped into 0.2 g samples (0.2 cm × 1.0 cm) excluding leaf veins before being immersed in solutions of 80% acetone and 95% ethanol (2:1) for 24 h. Then, the optical density of the solutions at both 645 nm and 663 nm was determined with a TU-1221 ultraviolet-visible spectrophotometer (Beijing Purkinje General Instrument Co., Beijing, China). The determination of the chlorophyll-a (Ca), chlorophyll-b (Cb), and total leaf chlorophyll (Chl) concentration followed the method described in Zhang et al. (2017a). Finally, the ratio of Ca and Cb (a/b) was calculated.

Some fresh leaves were scanned by using a portable scanner (LI-3000C, LI-COR Inc. USA) to determine the leaf area (al). Then, the leaf samples was oven-dried at 65°C for 48 h to a constant mass (md). The specific leaf area (SLA, cm2 g-1) was calculated as the ratio of al/md.

The leaf stomatal morphology was measured on fully expanded leaves. With the aid of transparent nail varnish, we obtained epidermal impressions from the midsection of the abaxial and adaxial leaf surfaces. The dried layers of nail varnish were peeled off from the leaf surface. We captured three images at 20× magnification by using a digital camera mounted on a compound light microscope. The stomatal density (sd) was calculated based on the number of stomas per image area averaged across both sides of the leaf surfaces. The stomatal size (ss) was measured from 10 - 30 well-defined stomata on each leaf surface and averaged on glass slides.

2. Foliage, soil, and urea fertilizer stoichiometry

The portion of the dried leaves used to determine the SLA were crushed into powder to determine the leaf stoichiometric compositions. We measured the C, N, and relative isotope abundances (R) of 13C / 12C   and 15N / 14by using a stable isotope ratio mass spectrometer (Iso-prime 100 IRMS, Isoprime Co., UK) with a precision of 13C<0.1‰. The R for the 13C / 12of the plant tissue is expressed as the relative deviation from the international standards (V-PDB) by using the delta (δ) notation, i.e., δ13=((Rsample/Rstandard)-1) ×1000. The total P was measured with the Mo-SB calorimetric method via a standard Kjeldahl digestion procedure (Yuan & Lavkulich, 1995). About 55 mg of ground leaf material was digested in 3 mL of sulfuric acid (H2SO4) and 2 mL of hydrogen peroxide (H2O2) for 45 min using a microwave digester (Speedwave 4, Berghof Products GmbH, Eningen, Germany). Soil samples were taken from three profiles at a depth of 0-30 cm in the CK, CAN, UAN treatment, and dried at 65 °C. The fertilizer samples were sampled five times. The soil and fertilizer samples were ground and analyzed for 15N abundance (δ15N). The δ15N in the soil and fertilizer was (0.13±0.02) ‰ and (-2.58±0.03) ‰, respectively.

3. Data analysis

Linear mixed-effects models were constructed with SPSS 20 (IBM inc., USA) to test the fixed effects of N addition, the species and their interactions (N treatments × species) for all variables. Considering the tree size variance for each individual, the DBH was divided into four classes (0-10 cm, 10-20 cm, 20-30 cm, and >30 cm). In the linear mixed-effects models, the DBH class was defined as the random effects. To verify the homogeneity of variance, we checked the plots of the residuals compared with the predicted values from each model with SPSS 20 to ensure that the residuals were normally distributed around 0 and that the variance in the residuals did not vary with the changes in the predicted value. If significant (sig. < 0.05) interactions (N treatments × species) were observed, then we predicted that the treatment effects were interrupted by the differences among the species.

To assess the treatment effects on this forest, the species mean N response ratios [i.e. the mean (N treatments)/mean (CK)] were also calculated for each trait, and expressed as “traitr. When analyzing the specific leaf traits of the six species, we calculated the mean values of each trait and the coefficient of variation. We excluded the Ca / Cb in the figure since all six species did not experience a significant variation in Ca / Cb in response to the fertilization.

We also conducted an analysis of variance (ANOVA) to assess the trait variances among the different species. Before the analysis, a homogeneity test of variance was conducted to test the data homogeneity. The mean of each traits was then calculated and compared with the Tukey method.

In addition, by arranging the species based on their scores on the first two principal components in each N treatment, multiple-trait relationships were analyzed by principal component analysis (PCA) in OriginLab (version 9.0, OriginLab, USA). All trait data were standardized by adopting the zero-mean approach before the PCA analysis. OriginPro (version 9.0, OriginLab, USA) was used to draw graphs.

Funding

National Natural Science Foundation of China, Award: 41630752,41701226

Zhejiang Province Public Welfare Technology Application Research Project, Award: LGF19C030002

Jinhua Technology Research Project, Award: 2019-4-163

Jinhua Technology Research Project, Award: 2019-4-163