Net primary production (NPP) was strongly influenced by the flooding stress, which is closely related to carbon (C), nitrogen (N) and phosphorus (P) allocation in plant aboveground (leaf-stem) and belowground (root) biomass. However, the relationship of NPP with the C:N:P stoichiometric ratio in plant tissues remains unknown, especially in the riparian zone of the Three Gorges Reservoir (TGR). In this study, the leaf-stem and root C, N, P content and biomass of Cynodon dactylon (Linn.) Pers. (C. dactylon) were investigated at the 145-155m, 155-165m and 165-175m altitudes of the riparian zone in TGR tributary-Pengxi River. The results showed that the biomass and NPP of C. dactylon had a similar trend along the riparian zone altitudes. The root showed much lower N and P content, but much higher N and P use efficiency with higher C:N and C:P ratio than that of leaf-stem under N limitation condition. Hydrological and C:N:P stoichiometric variables could predict 68% of the NPP variance. NPP was positively directly correlated to C:N in the stem-leaf to root ratio (C:N_{stem-leaf/root}) and C:P ratio in the root (C:P_root ratio ), thus could be regarded as the indicators of NPP in the riparian zone of the TGR.

DATA COLLECTION

The distribution of C. dactylon on the riparian zone at two hydrological sections of Qukou (QK) and Shuangjiang (SJ) were investigated in Pengxi River, July 2017. Three sampling plots (1m×1m) were established at each altitude of 145-155 m, 155-165 m, 165-175 m. The leaf-stem and root of C. dactylon were collected, bagged separately and brought back to the laboratory for 65 ^oC dry for 48h, and weight.

The C and N content were analyzed in plants on an Elemental Analyzer (Euro Vector EA3000, Italy) equipped with Callidus software. The total phosphorus (TP) was determined in plant samples by the alkali fusion-Mo-Sb anti-spectrophotometric method.

Net primary production was determined from plant biomass (W) change over a given time interval

(Lin et al., 2020, https://doi.org/10.1002/ece3.6409).

The submerging time was extracted from hydrological data from 2013 to 2018 at Wanzhou Hydrological Station in the Yangtze Riverby GetData (V2.20) software.