| Abstrakt: |
Submerged macrophytes are important indicators of the state of shallow freshwater ecosystems. Reconstruction long‐term changes in submerged macrophytes remains a challenge in paleoecology. Here, the relative biomass (mass weight) of different plants to sedimentary organic matter in a shallow lake in central China was estimated using a Bayesian multi‐source mixing model with concentrations and δ13C of n‐alkanes extracted from surface lake sediments. The spatial distribution of submerged macrophytes biomass estimated by the model correlates with water transparency, water depth, and total nitrogen. The correlation patterns are consistent with previously established patterns of submerged macrophyte growth and water conditions, which supports the utility of the Bayesian approach in shallow freshwater lakes. In comparison, Paq, proportion of mid‐chain length (C23, C25) to long‐chain length (C29, C31) homologs, underestimated the contribution of submerged macrophytes, especially in samples with moderate Paq values (0.3 < Paq < 0.4). On the other hand, some discrepancies between the model output and the satellite imagery estimated macrophyte coverage are present, which suggests that ground‐truthing is needed to further evaluate this approach. Our study demonstrates that the Bayesian mixing model combining the abundance and isotopes of n‐alkanes makes a reasonable estimation of the relative biomass of submerged macrophytes in the sediments. This approach provides new insights into reconstructing long‐term variations in submerged macrophytes for paleoecological studies, which is valuable for the restoration and conservation of shallow freshwater lakes when long‐term limnological monitoring is lacking. Plain Language Summary: Long‐term records of submerged macrophytes are critical for studies of lake ecology and climate of the past, as well as the restoration of freshwater bodies at risk of algal bloom. By combining the organic chemistry and carbon isotopes of plant wax lipid biomarkers with a modeling framework, we estimate the relative biomass of submerged macrophytes in surface sediments of a shallow freshwater lake in the Yangtze floodplain, central China. Our estimates are in agreement with the results from satellite images, supporting the validity of the method. We found that water transparency, water depth, and nutrients in the lake correlate with the abundance of submerged macrophytes. Our results support the utility of the modeling framework in studies of lake ecology and climate of the past. The abundance of submerged macrophytes may also provide guidelines for the restoration and conservation of shallow freshwater lakes. Key Points: A Bayesian model incorporating concentrations and δ13C of n‐alkanes was used to quantify the contribution of submerged macrophytesThe model estimated distribution of submerged macrophytes agrees with the growing condition and PaqDiscrepancy between satellite imagery and model output suggest ground‐truthing is needed for future applications [ABSTRACT FROM AUTHOR] |
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