Direct versus indirect effects of human activities on dissolved organic matter in highly impacted lakes.
Sci Total Environ
; 752: 141839, 2021 Jan 15.
Article
em En
| MEDLINE
| ID: mdl-32889275
ABSTRACT
Human activities can alter dissolved organic matter (DOM) in lakes through both direct (i.e., exporting DOM of anthropogenic sources) and indirect effects (i.e., enhancing the autochthonous production of DOM via nutrient loading). Distinguishing between the direct and indirect effects is important to better understand human impacts on aquatic systems, but it remains highly challenging due to the interdependence of associated environmental variables. Here, we demonstrated that disentangling the direct and indirect effects can be achieved through combining large-scale environmental monitoring with the Partial Least Squares Path Modeling (PLS-PM). We presented DOM data from 61 lakes within the floodplain of the Yangtze River (Lakes-YR), China, a region that has been subjected to intense anthropogenic disturbances. We analyzed the amount and composition of DOM through dissolved organic carbon (DOC), chromophoric DOM (CDOM), and fluorescent DOM (FDOM). Four fluorescence components were identified, including one tyrosine-like component, one tryptophan-like component, and two humic-like components. Most of the lakes were dominated by freshly produced DOM with small molecular weights and low humification. Results from the PLS-PM models showed that the autochthonous production was more important than anthropogenic inputs in mediating DOC and CDOM. In contrast, FDOM parameters in lakes were more sensitive to the direct, anthropogenic sources, including treated domestic, industrial wastewater, and the effluents of aquaculture. These sources can be identified by elevated FDOM content per DOC (FDOM DOC ratio) relative to autochthonous DOM, suggesting the potential of using FDOM as a tracer to identify and monitor the contribution of anthropogenic organic matter to inland waters.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Sci Total Environ
Ano de publicação:
2021
Tipo de documento:
Article