The co-regulation of nitrate and temperature on denitrification at the sediment-water interface in the algae-dominated ecosystem of Lake Taihu, China
Sediment denitrification is a dominant mechanism for nitrogen removal and can help to minimize lake eutrophication. However, the spatio-temporal variability of denitrification rates and its controlling factors in sediments of large shallow lakes are poorly understood. In this study, we investigated the controlling factors on the temporal and spatial variability of denitrification rates in Meiliang Bay in Taihu Lake, China, to determine the contribution of denitrification on the total lacustrine nitrogen budget.
Materials and methods
We collected 18 intact monthly sediment cores and an additional 36 seasonal sediment cores from January 2013 to January 2014. Cores were collected from the inner and outer sections of Meiliang Bay for analysis of denitrification rates and sediment properties. We also collected in situ surface water samples for water quality analysis. Denitrification rates at the sediment-water interface (SWI) were measured using acetylene inhibition techniques and intact sediment core incubation. We used a t test to determine the differences in water quality and sediment properties between the two sites and a one-way ANOVA to identify seasonal differences in denitrification rates, water quality, and sediment properties. We also applied Pearson’s correlation, distance-based redundancy analysis (db-RDA) and random forest model to identify the relationships between denitrification rates and environmental factors.
Results and discussion
Denitrification rates ranged from 0.76 to 40.94 μmol N m−2 h−1 and 0.13 to 52.55 μmol N m−2 h−1, with annual mean values of 19.97 and 17.15 μmol N m−2 h−1 for the Inner and Outer Bay, respectively. Sediment denitrification rates in the Inner and Outer Bay showed similar seasonal variability, with the highest values in spring and summer and the lowest values in autumn. Nitrate addition was shown to significantly increase denitrification rates in summer and autumn (P < 0.05); however, carbon addition showed no significant influence on denitrification rates in the four seasons. Our results imply that denitrification rates were nitrate-limited in summer and autumn. Distance-based redundancy analysis (db-RDA) and random forest model showed that denitrification rates were mainly determined by nitrate, temperature, and chlorophyll a (Chla), and that nitrate in the water column was the most important predictor of denitrification rates.
In general, denitrification rates showed significant seasonal variability in Meiliang Bay due to the co-regulation of both water temperature and nitrate concentrations. The dominance of each controlling factor on denitrification rates varied in different seasons. Based on our calculations, nitrogen removal by denitrification accounted for approximately 10.7% of the total nitrogen input to Taihu Lake. Therefore, we suggest the need for effective measures to reduce external nitrogen inputs of to Lake Taihu to prevent on-going eutrophication.
KeywordsDenitrification Eutrophication Lake Taihu Nitrogen budget Sediment-water interface
This work was funded by the National Natural Science Foundation of China (Grant Nos. 41371457 and 41771516). We would like to thank the Taihu Lake Laboratory of Ecosystem Research, Chinese Academy of Sciences (TLLER) for its logistic support. We would also like to thank the editor and anonymous reviewers for their constructive comments on improving the quality of our manuscript.
- Álvarez-Cobelas M, Piña-Ochoa E, Sánchez-Carrillo S, Delgado-Huertas A (2019) Spatial variability of denitrification along a nitrate-rich seepage chain of lakes (Ruidera Natural Park, Central Spain). Limnetica 38(2):607–621Google Scholar
- Feld CK, Segurado P, Gutierrez-Canovas C (2016) Analysing the impact of multiple stressors in aquatic biomonitoring data: A ‘cookbook’ with applications in R. SciTotal Environ 573:1320–1339Google Scholar
- Hedin LO, von Fischer JC, Ostrom NE, Kennedy BP, Brown MG, Robertson GP (1998) Thermodynamic constraints on nitrogen transformations and other biogeochemical processes at soil-stream interfaces. Ecology 79:684–703Google Scholar
- Ishwaran H, Kogalur U (2014) Random forests for survival, regression and classification (RF-SRC), R package version 1.6. URL. https://CRANR-projectorg/package=randomForestSRCGoogle Scholar
- Lu GH, Ma Q, Zhang JH (2011) Analysis of black water aggregation in Taihu Lake. Water Sci Eng 4:374–385Google Scholar
- Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O'hara R (2013) Package ‘vegan’. (Community ecology package, version 2)Google Scholar
- Seitzinger SP (1988) Denitrification in freshwater and coastal marine ecosystems: ecological and geochemical significance. Limnol Oceanogr 33:702–724Google Scholar
- Wang MR, Zhang HQ, Zhu X (2012) Innovation and practice of cyanobacteria control in Taihu Lake. China water resources and hydropower publishing press. Beijing, ChinaGoogle Scholar