[Effects of anthropogenic organic matter inputs on stable carbon and nitrogen isotopes in organisms from microbial food chain in Taihu Lake].

Stable isotope analyses of carbon and nitrogen were used to evaluate autochthonous versus allochthonous contribution to the main microbial food loop components in the four sampling sites based on different trophic status in Taihu Lake. On average, the delta13 C and delta15 N values of organic matter (OM) sources (bacteria, cladocera, particulate and sedimentary organic matter) and the delta13 C of dissolved inorganic carbon (DIC), which are the main components in microbial food chain, showed the lowest values at estuary location compared with the other three sites, reflecting a strong influence by terrestrially derived nutrients and organic matter. The mean delta13 C value of dissolved organic matter (DOM) that we measured was close to the estimated terrestrial delta13 C - 26 per thousandd, suggesting an allochthonous-derived organic C pool. Particulate organic matter (POM) was supposed to be mainly dominated by algae under the assumption of a constant fractionation from DIC to phytoplankton of 22 per thousand. Cladocera had a lower delta13 C than the average delta13 C of POM (0.2 per thousand) and bacteria (2.5 per thousand), supposing a lipid accumulation or selective feeding a more delta13 C-depleted algal fraction (pico- and nano-plankton, < 50 microm) of POM. The contribution of autochthonous versus allochthonous carbon to the bacterial biomass was estimated by applying a two-member mixing model using a delta13 C of - 26 per thousand as the allochthonous end member. The bacterial biomass consisted of 61.2% allochthonous carbon at estuary point with large terrestrial effluents, while in the large open lake area, bacteria was mainly supported by autochthonous OM (58.5% - 92.9%). The results substantiate the finding that the analysis of carbon and nitrogen stable isotopes can help to elucidate sources and sinks of organic matter in Taihu Lake, which are characterized by a great spatial variability and complexity.