# Net Primary Production Predicted by the Proportion of C:N:P Stoichiometric Ratio in the Leaf-Stem and Root of Cynodon Dactylon (Linn.) in the Riparian Zone of the Three Gorges Reservoir

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## Abstract

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_{stem-leaf/root}) and C:P ratio in the root (C:P

_{root}ratio). Hydrological and C:N:P stoichiometric variables could predict 68% of the NPP variance, and thus could be regarded as the main predictor of NPP in the riparian zone of the TGR.

## 1. Introduction

^{2}[1]. Thus, it is believed to be the most fragile ecological zone along the Yangtze River [2]. Periodic flooding also causes various adverse consequences for the riparian habitat, such as a lower plant richness and diversity, due to scarce revegetation of non-annual plants through seed banks [3,4]. Thus, the dominant riparian perennial herbs have to rapidly recover from its unique root system during the limited growing season [5].

## 2. Materials and Methods

#### 2.1. Study Areas

^{2}in the Pengxi River, accounting for 15.9% of the total riparian zone area of TGR, and its slope gradient is <15° [19]. The annual average rainfall in this region is about 1200 mm [20]. The mean humidity was 65.58–95.11%, while the mean temperature was 22.16–30.52 °C on a daily basis in the sampling period in July 2017.

#### 2.2. Sampling

#### 2.3. Laboratory Analyses

#### 2.4. Data Processing

^{2}). The model is satisfying when non-significant χ

^{2}test (p > 0.05), χ

^{2}/df within 0–2 and low values of χ

^{2}, akaike information criterion (AIC), and root mean square error of approximation (RMSEA) [21], and indicate that there is an acceptable difference between the modeled and observed values. Net primary production was determined from plant biomass (W) change over a given time interval [22]. Plant biomass production per unit of nitrogen uptake can represent N use efficiency, which was indicated by the C:N ratio in plant tissues in this study [23]. All data were tested for normality using the Kolmogorov–Smirnov test, and log-transformed non-normal data (e.g., C:P ratio in root). Structure equation modeling (SEM) was performed by IBM SPSS Amos 24 (IBM Corp., 2016).

#### 2.5. Statistical Analysis

## 3. Results

#### 3.1. Flooding Time and Net Primary Production (NPP)

#### 3.2. C, N, and P in Leaf-Stem and Root

#### 3.3. Leaf-Stem and Root C:N:P Stoichiometry with NPP

_{leaf-stem/root}(Figure 5(b3)), while positively correlated to C:N

_{leaf-stem/root}(Figure 5d3) at p < 0.05. No significant correlation of the NPP was found with C

_{leaf-stem/root}, P

_{leaf/root}, C:P

_{leaf/root}and N:P

_{leaf/root}(p > 0.05) (Figure 5).

#### 3.4. Exploring the Indicators of NPP

_{root}) and the proportion of C:N ratio in leaf-stem and root (C:N

_{leaf-stem/root}) had a direct effect, while submerging stress and the proportion of N in leaf-stem and root (N

_{leaf-stem/root}) exerted an indirect effect on the NPP. All of these variables predicted 68% of the variance in the NPP (Figure 6a). Specifically, flooding stress had a direct negative effect on the C:P

_{root}ratio and C:N

_{leaf-stem/root}ratio. The C:P

_{root}ratio had a direct positive effect on the NPP or indirectly negatively affected C:N

_{leaf-stem/root}ratio, which further had a direct positive effect on NPP by mediating N

_{leaf-stem/root}ratio. Taking the total effect of direct and indirect effects into account, the C:N

_{leaf-stem/root}and C:P

_{root}ratios could be regarded as the most critical predictors shaping the NPP variation along the riparian zone altitudes (Figure 6b).

## 4. Discussion

#### 4.1. Flooding Stress and NPP

#### 4.2. Nutrient Allocation and NPP

_{root}ratio and C:N

_{leaf-stem/root}ratio were the most critical indicators of the NPP (Figure 6a), which supported our second hypothesis. The nutrient allocation among plant tissues is essential for regulating plant growth [27,28]. A plant may take different survival strategies by allocating C, N, and P in the above- and below-ground tissues to maintain C:N:P stoichiometric balance [29].

_{stem-leaf/root}(proportion of N in stem-leaf and root) (Figure 5b3), but by contrast positively correlated with C:N

_{leaf-stem/root}ratio (proportion of C:N ratio in stem-leaf and root) in the riparian zone (p < 0.05) (Figure 5d3). Thus, C. dactylon might preferentially allocate energy and resources in the aboveground to raise N use efficiency in the leaf-stem (higher C:N

_{leaf-stem/root}ratio) to enhance the NPP under periodic flooding stress [35]. Furthermore, the NPP was tightly coupled with the C:N

_{leaf-stem/root}ratio among riparian zone altitudes (Figure 4). Thus, N is a critical limit factor for NPP of C. dactylon, while the C:N

_{leaf-stem/root}ratio and root C:P ratio can be regarded as the main predictors of the NPP in the riparian zone.

## 5. Conclusions

_{leaf-stem/root}ratio and root C:P ratio can be regarded as the main predictors of the NPP in the riparian zone under periodic water level fluctuation. Therefore, this can provide an essential scientific basis for establishing vegetation restoration technology based on C:N:P stoichiometry in the riparian zone ecosystem. Further research needs to pay attention to the coupling relationship between C:N:P stoichiometry and the above- and underground distribution mechanism of NPP in the riparian zone ecosystem.

## Author Contributions

## Funding

## Conflicts of Interest

## Abbreviations

_{root}—C:P ratio in the root; C:N

_{leaf-stem/root}—C:N in the leaf-stem to root ratio; N

_{leaf-stem/root}—N in the leaf-stem to root ratio.

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**Figure 2.**Water level fluctuation (

**a**) and submerging time (

**b**) from 2013 to 2018. The sampling was conducted in July 2017.

**Figure 3.**Net primary production (NPP) (

**a**) and biomass (

**b**) of C. dactylon among the riparian zone altitudes.

**Figure 4.**C:N:P stoichiometry in the leaf-stem to root ratio among the riparian zone altitudes. Different lowercase letters of a, b, c indicate significant differences among riparian zone altitudes at p < 0.05.

**Figure 6.**Structure equation modeling (SEM) with variables (boxes) and potential causal relationships (arrows) for NPP (

**a**) and standardized total effects (direct effect plus indirect effect) on NPP derived from SEM (

**b**). The black-headed arrows indicate that the hypothesized direction of causation is a positive relationship; on the contrary, the red-headed arrows represent a negative relationship. Arrow width is proportional to the strength of path coefficients. Standardized path coefficients (numbers) can reflect the importance of the variables within the model [24]. The model for NPP had χ

^{2}= 2.660, df = 3, p = 0.447, RMSEA = 0.000, AIC = 50.66.

**Table 1.**Leaf-stem and root C:N:P stoichiometric ratio among riparian zone altitudes and results from linear mixed model.

Riparian Zone Altitude (masl) | Tissue | Replicate | C (%) | N (%) | P (%) | C:N | C:P | N:P |
---|---|---|---|---|---|---|---|---|

145–155 | leaf-stem | 6 | 39.46 | 1.77 | 0.28 | 22.37 | 143.93 | 6.41 |

root | 6 | 39.71 | 0.97 | 0.18 | 40.67 | 220.55 | 5.41 | |

155–165 | leaf-stem | 6 | 41.20 | 1.38 | 0.23 | 30.06 | 187.69 | 6.30 |

root | 6 | 43.45 | 0.82 | 0.16 | 53.18 | 278.87 | 5.35 | |

165–175 | leaf-stem | 6 | 41.35 | 2.16 | 0.27 | 35.16 | 220.61 | 7.49 |

root | 6 | 40.43 | 0.86 | 0.17 | 52.62 | 311.79 | 5.33 | |

Results from linear mixed models | ANOVA P-values | |||||||

Main effect | Altitude | 0.076 | 0.424 | 0.259 | 0.064 | 0.008 | 0.819 | |

Tissue | 0.579 | 0.002 | 0.000 | 0.000 | 0.000 | 0.100 | ||

Interaction effect | Altitude × Tissue | 0.392 | 0.495 | 0.720 | 0.851 | 0.945 | 0.792 |

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**MDPI and ACS Style**

Liu, D.; He, L.; Yu, Z.; Liu, Z.; Lin, J.
Net Primary Production Predicted by the Proportion of C:N:P Stoichiometric Ratio in the Leaf-Stem and Root of *Cynodon Dactylon* (*Linn.*) in the Riparian Zone of the Three Gorges Reservoir. *Water* **2020**, *12*, 3279.
https://doi.org/10.3390/w12113279

**AMA Style**

Liu D, He L, Yu Z, Liu Z, Lin J.
Net Primary Production Predicted by the Proportion of C:N:P Stoichiometric Ratio in the Leaf-Stem and Root of *Cynodon Dactylon* (*Linn.*) in the Riparian Zone of the Three Gorges Reservoir. *Water*. 2020; 12(11):3279.
https://doi.org/10.3390/w12113279

**Chicago/Turabian Style**

Liu, Dan, Liping He, Zhiguo Yu, Zhengxue Liu, and Junjie Lin.
2020. "Net Primary Production Predicted by the Proportion of C:N:P Stoichiometric Ratio in the Leaf-Stem and Root of *Cynodon Dactylon* (*Linn.*) in the Riparian Zone of the Three Gorges Reservoir" *Water* 12, no. 11: 3279.
https://doi.org/10.3390/w12113279