A Bayesian Approach to Carrying Capacity Estimate: The Case of Greek Coastal Cage Aquaculture

The estimation of the carrying capacity (CC) is a fundamental process in integrated environmental management, policy making, and decision making. Aquaculture carrying capacity has been studied since the 1960s to allow estimation of the production limits of aquaculture projects and, hence, their maximum economic performance within sustainable limits for the local environment. One major drawback of these approaches is that they can provide CC estimates after a fish farm is installed and operates in a certain location (ex post approaches). This paper approaches the estimation of CC using a Bayesian/CHAID model of profiling information on the environmental quality, geomorphology, and human activities on the adjacent coastal area (land side) using as an indicator the trophic state of the marine area in terms of chlorophyll-a concentration (upper mesotrophic). This way, having the above information for a certain site, it is possible to calculate the maximum annual production of a cage fish farm so that the trophic state of the area will not exceed the environmental goal of the upper mesotrophic level. We examined the effects of 27 different physical, chemical, social and geomorphological parameters on CC (in fish biomass terms). CC was found to be correlated by particulate nitrogen (PN), silicates (Si-SiO4), salinity, and suspended particulate matter (SPM). The overall relationship found is: Biomassat CC level = +473.762[Chl-a] − 6856.64[PN] + 9.302[Salinity] − 473.5[Si-SiO4] + 341.864[SPM] − 207.046. The analysis performed allowed us to estimate the maximum levels for each factor to maintain a eutrophication status up to the upper mesotrophic level: particulate nitrogen < 0.018 mg/L, silicates < 0.137 mg/L, salinity > 38 PSU and SPM > 0.815 mg/L. Finally, the current fish farm licensing legislation in Greece concerning the CC estimation algorithm is discussed

A Bayesian Approach to Carrying Capacity Estimate: The Case of Greek Coastal Cage Aquaculture

The estimation of the carrying capacity (CC) is a fundamental process in integrated environmental management, policy making, and decision making. Aquaculture carrying capacity has been studied since the 1960s to allow estimation of the production limits of aquaculture projects and, hence, their maximum economic performance within sustainable limits for the local environment. One major drawback of these approaches is that they can provide CC estimates after a fish farm is installed and operates in a certain location (ex post approaches). This paper approaches the estimation of CC using a Bayesian/CHAID model of profiling information on the environmental quality, geomorphology, and human activities on the adjacent coastal area (land side) using as an indicator the trophic state of the marine area in terms of chlorophyll-a concentration (upper mesotrophic). This way, having the above information for a certain site, it is possible to calculate the maximum annual production of a cage fish farm so that the trophic state of the area will not exceed the environmental goal of the upper mesotrophic level. We examined the effects of 27 different physical, chemical, social and geomorphological parameters on CC (in fish biomass terms). CC was found to be correlated by particulate nitrogen (PN), silicates (Si-SiO4), salinity, and suspended particulate matter (SPM). The overall relationship found is: Biomassat CC level = +473.762[Chl-a] − 6856.64[PN] + 9.302[Salinity] − 473.5[Si-SiO4] + 341.864[SPM] − 207.046. The analysis performed allowed us to estimate the maximum levels for each factor to maintain a eutrophication status up to the upper mesotrophic level: particulate nitrogen 38 PSU and SPM > 0.815 mg/L. Finally, the current fish farm licensing legislation in Greece concerning the CC estimation algorithm is discussed

Growth Performance and Environmental Quality Indices and Biomarkers in a Co-Culture of the European Sea Bass with Filter and Deposit Feeders: A Case Study of an IMTA System

This study aimed to evaluate the efficiency of an integrated multi-trophic aquaculture (IMTA) system comprising co-cultured fed fish and organic extractive species representing three distinct trophic levels as well as the impact and potential utilization of two commercially available fish feeds made up of 35% fish meal (FM) and 20% fish meal (LFM) ingredients, using a multi-indicator assessment approach. Significant alterations were observed in growth performance indicators (GPIs), water and sediment quality indices, toxicity tests and biomarkers within the IMTA system. The fish survival, weight gain (WG), and specific growth rate (SGR) were higher in the IMTA system with significantly lower feed conversion ratios (FCRs) and higher feed efficiency (FE) in comparison to the fed fish monoculture system. Yet, organic filter feeders displayed 100% survival, and increased shell growth, while deposit feeders exhibited successful survival and significant weight gain. In the comparison between FM-IMTA and LFM-IMTA, fed fish in FM-IMTA showed higher WG, SGR, and FE with lower FCR. Environmental parameters like temperature, oxygen, and nutrient concentrations fluctuated but generally improved in the IMTA system, indicating lower mesotrophic conditions. Sediment fatty acid profiles differed between systems and toxicity assessments, which suggested a lower impact in IMTA and FM-IMTA systems. The sediment microbial community displayed high similarity within IMTA systems and between FM-IMTA and LFM-IMTA. These findings underscore the potential of IMTA systems for sustainable aquaculture, emphasizing improved growth performance and reduced environmental impact, particularly when using fish meal feeds