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