Screening of seaweed species for cultivation associated with land-based aquaculture.

Aires M. Duarte1,2, Isabel Sousa Pinto1,2, Isabel Costa1,2

1Interdisciplinary Centre of Marine and Environmental Research (CIIMAR),

Matosinhos, Portugal

2Faculty of Sciences of University of Porto, University of Porto, Portugal

 

Fish-farms produce as by-products nutrients–nitrogen and phosphorus–that can be used

by seaweeds to grow and, consequently, produce biomass that can be valorised in different applications. We aim to find specific seaweeds to grow in a fish farm effluent that has specific traits such as low salinity (~23%), moderate temperature (~19ᵒC), high and low levels of nitrates and ammonium, respectively. The seaweed species selected for this experiment were Chondrus crispus, Gracilaria multipartita, Mastocarpus stellatus, Osmundea pinnatifida, Porphyra sp. and Ulva sp. Seaweeds from North Coast of Portugal were collected, acclimated for seven days and exposed to this effluent for three weeks under the following conditions: 5gL-1 of density, 19ᵒC of temperature, 23% of salinity, 150µmolphotons∙m-2.s-1 and a neutral photoperiod of 12h:12h (L:D). Part of the effluent was adjusted to 33% salinity to determine whether salinity was a limiting factor. Every week the effluent was exchanged and water samples were collected for nutrient uptake, pulseamplitude modulation (PAM) for photosynthetic activity and fresh weight for relative

growth rate (RGR). Gracilaria multipartita was affected by salinity. The adjustment of salinity to 33% allowed to reach higher growth rates (22%:3.76±1.34%d-1, 33%:5.67±1.54%d-1). The remaining seaweeds were not affected by salinity. The seaweeds that showed best growth rates on the original effluent were G. multipartite (3.76±1.34%d-1), O. pinnatifida (2.09±0.72%d-1), Ulva sp. (1.59±1.14%d-1), C. crispus (1.33±0.86 %d-1), and M. stellatus (0.88±0.46%d-1), The best performing seaweed will be grown in a pilot scale seaweed cultivation system associated with the fish farm to assess productivity at real-life conditions.