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Abstract
This PhD thesis aimed to assess the status of common sole, one of the main commercial stocks in the Adriatic Sea, using a mix of conventional and innovative techniques to provide more reliable estimates of stock status compared to past advice. First, a meta-analysis was carried out using data-poor assessment model to analyze the whole catch assemblage of rapido fishery. The outcomes were used to estimate rebuilding time and forecast catches under different harvest control rule scenarios, with a reduction of 20% of fishing effort being suggested as a way to allow most of the species to recover to sustainable levels. Secondly, an ensemble of data-rich assessment models was developed to better incorporate uncertainty by using alternative hypotheses of main parameters. This was the first time an ensemble of models has been used in the Mediterranean to provide management advice. Consistent with data-poor analysis results, the ensemble outcomes indicated that the common sole stock was showing a recovering trend probably due to the effective management actions underway in the area rather than the moderate effort reduction according to the actual management plan. Moreover, back-calculation measurements were used to fit and compare monophasic and biphasic growth curves through the use of non-linear mixed effects models. The analyses revealed that the fitting of the biphasic curve was superior, confirming the theory that growth in size would decrease as a consequence of reproductive effort. A stock assessment simulation showed how the use of the monophasic pattern would result in a critical overestimation of biomass that could lead to a greater risk of overfishing. As a final step, a simulation-testing procedure was applied to determine the best performing reference points using stock-specific characteristic. The procedure could be routinely adopted to increase transparency in reference points calculation enhancing the credibility of scientific advice.
Abstract
This PhD thesis aimed to assess the status of common sole, one of the main commercial stocks in the Adriatic Sea, using a mix of conventional and innovative techniques to provide more reliable estimates of stock status compared to past advice. First, a meta-analysis was carried out using data-poor assessment model to analyze the whole catch assemblage of rapido fishery. The outcomes were used to estimate rebuilding time and forecast catches under different harvest control rule scenarios, with a reduction of 20% of fishing effort being suggested as a way to allow most of the species to recover to sustainable levels. Secondly, an ensemble of data-rich assessment models was developed to better incorporate uncertainty by using alternative hypotheses of main parameters. This was the first time an ensemble of models has been used in the Mediterranean to provide management advice. Consistent with data-poor analysis results, the ensemble outcomes indicated that the common sole stock was showing a recovering trend probably due to the effective management actions underway in the area rather than the moderate effort reduction according to the actual management plan. Moreover, back-calculation measurements were used to fit and compare monophasic and biphasic growth curves through the use of non-linear mixed effects models. The analyses revealed that the fitting of the biphasic curve was superior, confirming the theory that growth in size would decrease as a consequence of reproductive effort. A stock assessment simulation showed how the use of the monophasic pattern would result in a critical overestimation of biomass that could lead to a greater risk of overfishing. As a final step, a simulation-testing procedure was applied to determine the best performing reference points using stock-specific characteristic. The procedure could be routinely adopted to increase transparency in reference points calculation enhancing the credibility of scientific advice.
Tipologia del documento
Tesi di dottorato
Autore
Masnadi, Francesco
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
35
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
common sole, rapido fishery, stock assessment, management, data-poor, ensemble approach, forecast, mixed effect model, back-calculation, growth curve, reference points, shortcut MSE, CMSY, SS3, diagnostic tool
URN:NBN
DOI
10.48676/unibo/amsdottorato/10759
Data di discussione
16 Giugno 2023
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Masnadi, Francesco
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
35
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
common sole, rapido fishery, stock assessment, management, data-poor, ensemble approach, forecast, mixed effect model, back-calculation, growth curve, reference points, shortcut MSE, CMSY, SS3, diagnostic tool
URN:NBN
DOI
10.48676/unibo/amsdottorato/10759
Data di discussione
16 Giugno 2023
URI
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