SEAwise report on Carbon footprint, economic and social impacts of management strategies
Creators: name: Bitetto, Isabella
name: Spedicato, Maria-Teresa
name: Romagnoni, Giovanni
name: Lembo, Guiseppe
name: Halkos, Georgios
name: Plataniotis, Angelos
name: Koundouri, Phoebe
name: Andrés, Marga
name: Sánchez, Sonia
name: Garcia, Dorleta
name: Ibaibarriaga, Leire
name: Voss, Rudi
name: Liontakis, Angelos
name: Vassilopoulou, Celia
name: Giannoulaki, M.
name: Sgardeli, Vasiliki
name: Tsoukali, Stavroula
name: Sys, Klaas
name: Depestele, J. (Jochen)
name: Kühn, Bernhard
name: Taylor, Marc
name: Kempf, Alexander
name: Binch, Logan
name: Rindorf, Anna
Publisher: name: Technical University of Denmark
Year: 2024
Subjects: classificationCode: 380105
subject: Environment and resource economics

description: The SEAwise project works to deliver a fully operational tool that will allow fishers, managers, and policy makers to easily apply Ecosystem Based Fisheries Management (EBFM) in their fisheries. This report describes enhanced economic sub-models which can be used to predict economic impacts and Carbon footprint of potential fisheries management strategies. The work was conducted considering the different economic components (e.g. variable, fixed costs, etc.) and exploring different sub-models for each of them. In each case study specific key components were developed, mainly focusing on a better specification of metier specific fuel costs, and a more detailed fish price dynamic to overcome the assumption of constant price in the projections. In most cases the plausibility of the new configurations were tested through the management scenarios conducted in task 6.4 and 6.3.For the <b>Western Waters</b> three case studies were considered: two in the Bay of Biscay and one in the Celtic Sea.The first sub-case analysed the offshore demersal fleet operating in subarea 8abd. This is a multispecies and mixed fishery and there are two countries involved: Spain and France. The economic component of the model was parameterized, including prices and costs. Prices for the Spanish fleet were estimated at stock and metier level from the first sale notes, while the price for French fleet was estimated at fleet level. Costs were estimated from AER data for both countries, but the fleet segments used in the model does not always match with the AER segmentation, so assumptions about the compatibility had to be made. The fleet segments used were defined from ICES MIXFISH using Intercatch and Accessions. Additionally, variable costs are not disaggregated at metier level, and as a consequence the same variable costs were assumed for all the metiers of a given fleet segment. In some cases, the results of the simulations present negative economic results, possibly due to the fact that some species and catches from other areas are not included in the model.The second case study of the Bay of Biscay is the inshore pelagic fishery, a sequential and seasonal fishery. In this case study two countries are involved (Spain and France), but the economic component was analysed only for the Basque fleet. In this case study, the suitability of a new approach to model seasonal effort dynamics on a year basis model was analysed and compared with a status quo scenario. The new approach to model seasonal effort dynamics starts with a fleet and métier definition that captures the seasonal dynamics, and the definition of the metiers do not coincide with the definition of AER and AER data cannot be used. Therefore, regional statistics, logbooks and first sale notes were used to parameterize the economic component. The total effort exerted by each fleet segment and the effort allocation among métiers was calculated by maximizing the profits but constrained by: (i) the total eﬀort was constrained by the capacity of the ﬂeet; (ii) the catch quota by stock; (iii) the eﬀort share along métiers was restricted by an interval defined as the maximum and minimum effort that the fleet can allocate to a given métier. According to simulations, the new approach achieved better economic performance than the status quo scenario for almost all fleets, especially in the last years of the projected period.For the Celtic Sea, a preliminary FLBEIA model was developed by the ICES WGMIXFISH working group prior to the SEAwise project. However, this model was not yet operational and does not include any economic information on fleets, nor economic sub-models that drive the fishery. In SEAwise, the model was expanded in its modules, including all relevant information of costs structure and relevant indicators. The new economic configuration was tested by projecting a status quo scenario.The <b>North Sea</b> case study focused on updating the current economic parameterisation (costs and revenues of fleets) with data from the recent STECF Annual economic report 22-06 for the North Sea FLBEIA model. Additionally, we explored splitting of price information per age class for each stock and métier based on information from the EUMOFA database as well as testing various different price models within the current fleet conditioning in the North Sea FLBEIA model. A price model utilising lagged price and landings information as well as current years landings to inform current prices was the most suitable and will be explored in future simulations alongside the implementation of a static price model. Furthermore, a way to derive estimates of carbon emissions per fleet, based on FLBEIA effort output was presented.In the <b>Baltic Sea</b> case study the full set of economic data were updated, including new model fitting. The model was further enhanced by including the possibility of having a time trend in the cost function, mirroring technological progress. A major development is the inclusion of a demand system, i.e. an iso-elastic inverse demand function to specify producer as well as consumer surplus.For the <b>Mediterranean Sea</b> one new FLBEIA model and one enhanced BEMTOOL model are available.For the Eastern Mediterranean Sea case study, the FLBEIA analysis focused on the socioeconomic and carbon footprint of management strategies based on predetermined scenarios. The FLBEIA model was enhanced by the incorporation of additional indicators that are better adapted for the specific nature of the SSF fleet and the behaviour of the fishers, by taking into consideration the family-owned factors of production and especially the imputed value of family labour. In terms of these indicators, the ‘Fcomb’ scenario is better performing. In this scenario, the effort of the small scale fleet does not change while the large scale fleet effort is reduced by half, allowing the recovery of hake biomass and increase of biomass of all stocks, leading to an overall higher harvest. On the other hand, in Flw and PGY scenarios, the small scale fishery activity cannot be sustained as the Income becomes negative on average. Small and large scale fishing (and the total fleet) under all scenarios - excluding PGY for LSF- led to a lower carbon footprint.In addition, an analysis on the economic effect of the thermophilic species invasion in the Eastern Ionian Sea was conducted, with the case study on the economic effect of <i>Siganus</i> spp. invasion on the métier of <i>Sparisoma</i> <i>cretensis</i> utilizing trammel nets. The results suggests that the expected consequences of the thermophilic species expansion are significant and should be carefully taken into consideration in management planning and decision-making.For the Eastern Mediterranean Case Study (GSA 20, GFCM sensu) a time series analysis on the market price and landings of four target species (European hake, deep-water rose shrimp, red mullet and striped red mullet) was carried out, through MGARCH. Our objective was to determine how prices change and how elastic demand is with regards to these changes. The results show a price elasticity of demand of -0.1512 for hake, -0.9951 for red mullets, -1.67 for shrimps, and -1.224 for striped red mullets. The demand for hake seems to be quite inelastic, which means that small changes in price do not lead to big changes in demand. For red mullets, the demand is unitary elastic, which means that small changes in price lead to small changes in demand. Shrimp and stripped red mullets, on the other hand, have elastic demand, which means that small changes in price lead to big changes in demand. Possible factors that affect these estimates may include consumer preferences, consumer income, etc.For the Central Mediterranean Sea, a BEMTOOL model, previously developed in FAIRSEA project, was enhanced in SEAwise by disaggregating the trawlers fleet segments by fishing activity at metier level (OTB_DEF, OTB_DWS and OTB_MDD) in order to model possible effort re-allocation due to the implementation of the management measures (e.g. red shrimps catch limits) and/or to different fishing strategies as response to management (e.g. behavioural component). This disaggregation regarded the fuel costs and the fish price modelling.Finally, a set of socio-economic indicators was identified in line with AER to be used to evaluate the socio-economic impacts. Sub-models for carbon emissions estimates were also identified and applied.More information about the SEAwise project can be found at https://seawiseproject.org/<br>