Identification of optimal filtration conditions for the management of eutrophic waters by freshwater mussels using response surface methodology
The substantial filtration capacity of freshwater mussels makes them attractive tools for environmental management. In this study, we applied a central composite design to estimate independent variables and establish optimal conditions of filtration rate and faeces production that enhance filtration...
Gespeichert in:
Veröffentlicht in: | Water and environment journal : WEJ 2019-05, Vol.33 (2), p.292-299 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The substantial filtration capacity of freshwater mussels makes them attractive tools for environmental management. In this study, we applied a central composite design to estimate independent variables and establish optimal conditions of filtration rate and faeces production that enhance filtration of suspended organic matter by the freshwater mussel Sinanodonta woodiana. The results indicated that statistical design methodology offers an efficient and feasible approach for identifying optimal conditions for high filtration and low faeces production, using just a small number (30) of individuals. The proposed model equation takes into account the quantitative effect of variables and also the influence of interactions among variables on mussel filtration rate. Under the optimal experimental conditions (mussel size, 13.0 ± 0.2 cm; flow rate, 17.5 L/h), the experimental filtration rate of 4.47 ± 1.82 L/mussel/h showed a degree of correspondence with the predicted value of 8.4 L/mussel/h, which verified the practicability of this optimum strategy. Our findings contribute to our understanding of the context‐specific ecosystem engineering provided by mussels in natural systems, and also provides a framework for optimizing conditions for the applied use of mussels as biological filters. |
---|---|
ISSN: | 1747-6585 1747-6593 |
DOI: | 10.1111/wej.12409 |