Experimentally derived biochemical modelling parameters to improve understanding of aquaculture?s effect on marine food webs

To construct robust biogeochemical models for application to marine-based aquaculture settings, careful selec-tion of appropriate model parameters is necessary. This study used an experimental approach to establish bio-markers of farm and marine-derived organic matter, and to derive isotopic turnover rates, and trophic discrimination factors specific to aquaculture associated food webs. A shift towards a farm-derived resource base resulted in consumer tissues more depleted in the carbon-13 isotope (indicated by more negative delta C-13 values) and a higher proportion of oleic acid, linoleic acid, and alpha-linoleic acid in the fatty acid profile of consumers over time. Measured trophic discrimination factors between dietary sources and consumer tissues demonstrated high variability among species and tissue types, ranging from -0.25%o to 0.82%o for delta C-13 and from -0.77%o to 6.8%o for delta N-15. Stable isotope half-lives were also diverse among species and tissue types, ranging from < 7 days to 462 days. Results demonstrated that construction of robust models for tracing assimilation of farm-derived organic matter through marine food webs requires the use of taxa and tissue specific parameters. Turnover rates have applications for understanding assimilative capacity of communities and for managing populations within the ecological footprint of farms.

Automated summary

Careful selection of appropriate model parameters is necessary to construct robust biogeochemical models for marine-based aquaculture settings. This study used an experimental approach to establish biomarkers of organic matter from both farms and the marine environment, and derived isotopic turnover rates and trophic discrimination factors specific to aquaculture food webs. The results showed that construction of robust models requires the use of specific parameters for different species and tissue types, and turnover rates have applications in understanding assimilation capacity and managing populations.