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Russo, 2017 - Trends for trawling in the Adriatic Sea

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SFORZO DI PESCA E IMPATTI: TENDENZE IN
ATTO PER LA PESCA A STRASCICO DELLE SPECIE
DEMERSALI IN MAR ADRIATICO

Published in: Science
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Russo, 2017 - Trends for trawling in the Adriatic Sea

  1. 1. SFORZO DI PESCA E IMPATTI: TENDENZE IN ATTO PER LA PESCA A STRASCICO DELLE SPECIE DEMERSALI IN MAR ADRIATICO Tommaso Russo Laboratorio di Ecologia Sperimentale ed Acquacoltura Università degli Studi di Roma Tor Vergata
  2. 2. LO SCENARIO: LA PRODUZIONE §Lo sbarcato della flotta da pesca italiana è in sostanziale declino da decenni §Tra il 2009 e il 2015 la produzione nel Mare Adriatico per le specie demersali si è ridotta del 30% (-26% a livello nazionale) Fonte: EU - DCF
  3. 3. LO SCENARIO: LA FLOTTA §Lo sbarcato della flotta da pesca italiana è in sostanziale declino da decenni §Tra il 2009 e il 2015 la produzione nel Mare Adriatico per le specie demersali si è ridotta del 30% (-26% a livello nazionale) §Tra il 2009 e il 2015 la flotta a strascico Adriatica si è ridotta del 17% (-24% a livello nazionale) Fonte: EU - DCF
  4. 4. LO SCENARIO: LO SFORZO DI PESCA §Lo sbarcato della flotta da pesca italiana è in sostanziale declino da decenni §Tra il 2009 e il 2015 la produzione nel Mare Adriatico per le specie demersali si è ridotta del 30% (-26% a livello nazionale) §Tra il 2009 e il 2015 la flotta a strascico Adriatica si è ridotta del 17% (-24% a livello nazionale) §Tra il 2009 e il 2015 lo sforzo di pesca nominale nel Mare Adriatico si è ridotto del 35% (-15% a livello nazionale) Fonte: EU - DCF
  5. 5. TOMMASO RUSSO Ricercatore TDb presso il Laboratorio di Ecologia Sperimentale ed Acquacoltura dell’Università degli Studi di Roma Tor Vergata Sito web: www.tommasorusso.org Email: Tommaso.Russo@Uniroma2.it EU Data Collection Framework in the Fisheries Sector Programma Nazionale Raccolta Dati alieutici Modulo V: Indicatori 5-7. Valutazione degli effetti del settore della pesca sugli ecosistemi marini
  6. 6. VMS E AIS: UNA RIVOLUZIONE NELLE SCIENZE DELLA PESCA §La pesca è un gioco complesso che comprende vari “attori”: le risorse, l’ambiente, e l’uomo §Tradizionalmente, le scienze della pesca si sono concentrate sullo studio dell’ambiente e delle risorse §Gli aspetti dinamici della componente umana (le flotte) sono stati per lungo tempo non direttamente osservabili
  7. 7. VMS E AIS: UNA RIVOLUZIONE NELLE SCIENZE DELLA PESCA §Sistema di controllo dei pescherecci (VMS): Obbligatorio per i pescherecci di lunghezza superiore a 15 m (e dal 1° gennaio 2012 per quelli al di sopra di 12 m) §Sistema di identificazione automatica (AIS): Obbligatorio: §da giugno 2012 x tutti i pescherecci di lunghezza superiore a 24 §da giugno 2013 x tutti i pescherecci di lunghezza superiore a 18 §Da giugno 2014 x tutti i pescherecci di lunghezza superiore a 15 m.
  8. 8. LA VALUTAZIONE DEGLI EFFETTI DEL SETTORE DELLA PESCA SUGLI ECOSISTEMI MARINI §Stima dello sforzo di pesca nello spazio e nel tempo (la “pressione” da pesca) §Studio delle relazioni tra distribuzione dello sforzo di pesca e impatti sugli ecosistemi §Messa a punto di modelli per la gestione dello sforzo
  9. 9. VMS/AIS E ALTRI DATI ¡ Logbook Ø Associare le catture e gli sbarcati a specifiche aree (fishing grounds) e tempi Ø Indagare la relazione tra sforzo di pesca e impatto sulle risorse Ø Indagare le interazioni tra le flotte e le dinamiche che ne regolano l’attività ¡ VMS ¡ AIS
  10. 10. RAPPORTI CON LA POLITICA COMUNE PER LA PESCA: COSA Lo scopo principale della gestione della pesca nell’ambito della politica comune della pesca (PCP) è garantire livelli di catture elevati a lungo termine per tutti gli stock entro il 2015, ed al più tardi entro il 2020 (principio del rendimento massimo sostenibile - MSY).
  11. 11. RAPPORTI CON LA POLITICA COMUNE PER LA PESCA: COME? La gestione della pesca può assumere la forma di controllo dell’input o dell'output o una combinazione di entrambi. Il controllo dell'input comprende: §Norme sull'accesso alle acque per controllare chi pescherecci ha accesso a quali aree §Controlli sullo sforzo di pesca per limitare la capacità di pesca e lo sforzo §Misure tecniche per disciplinare l’uso delle attrezzature da pesca e i periodi di pesca
  12. 12. SPAZIO: ULTIMA FRONTIERA Controllare lo sforzo di pesca nello spazio (e nel tempo!) può essere un modo efficace di regolare la mortalità da pesca e proteggere alcuni stadi vitali (giovanili) PCP: ZONE CHIUSE E PERIODI DI FERMO DI PESCA
  13. 13. IL PROGETTO MANTIS EU, DG MARE - Agreement number – SI2 - 721911 MANTIS: Marine protected Areas Network Towards Sustainable fisheries in the Central Mediterranean
  14. 14. IL PROGETTO MANTIS EU, DG MARE - Agreement number – SI2 - 721911 MANTIS: Marine protected Areas Network Towards Sustainable fisheries in the Central Mediterranean Adriatico (GSA17-18) Stretto di Sicilia (GSA12-16)
  15. 15. IL PROGETTO MANTIS EU, DG MARE - Agreement number – SI2 - 721911 MANTIS: Marine protected Areas Network Towards Sustainable fisheries in the Central Mediterranean Principali obiettivi: • Rivedere le informazioni disponibili a proposito delle Marine Protected Areas (MPA) presenti nelle due aree di studio; • Studiarne la connettività rispetto alle aree di pesca • Indagare il possibile effetto di una rete di MPA (chiuse alla pesca per periodi definiti) sui principali stock sfruttati dalla pesca
  16. 16. MANTIS: STRUMENTI ISIS-FISH Due piattaforme per la simulazione di chiusure spaziali e temporali della pesca e per la previsione dei possibili effetti sulle risorse SMART
  17. 17. SMART SMART: A Spatially Explicit Bio-Economic Model for Assessing and Managing Demersal Fisheries, with an Application to Italian Trawlers in the Strait of Sicily Tommaso Russo1 *, Antonio Parisi2 , Germana Garofalo3 , Michele Gristina3 , Stefano Cataudella1 , Fabio Fiorentino3 1 Laboratory of Experimental Ecology and Aquaculture, Department of Biology, ‘‘Tor Vergata’’ University of Rome, via della Ricerca Scientifica s.n.c., Rome, Italy, 2 Department of Economics and Finance, Faculty of Economics, ‘‘Tor Vergata’’ University of Rome, Rome, Italy, 3 National Research Council (CNR), Institute for Coastal Marine Environment (IAMC), Mazara del Vallo, Italy Abstract Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of Sicily, also supporting sustainable economic returns for fishermen if not applied simultaneously for different species. Citation: Russo T, Parisi A, Garofalo G, Gristina M, Cataudella S, et al. (2014) SMART: A Spatially Explicit Bio-Economic Model for Assessing and Managing Demersal Fisheries, with an Application to Italian Trawlers in the Strait of Sicily. PLoS ONE 9(1): e86222. doi:10.1371/journal.pone.0086222 Editor: Brian R. MacKenzie, Technical University of Denmark, Denmark Received June 2, 2013; Accepted December 6, 2013; Published January 23, 2014 Copyright: ß 2014 Russo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by Flag project RITMARE (http://www.ritmare.it/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: Tommaso.Russo@Uniroma2.it Sforzo di pesca Dislocazione attuale Risorse Catture riferite allo spazio Aspetti economici Costi associati allo sforzo e ricavi dalle catture Simulazione sforzo Predizione catture Stima ricavi-costi = guadagni Valutazione effetti sulle risorse Valutazione effetti economici Schema FRA (aree chiuse alla pesca)
  18. 18. LO SPAZIO COME ARENA DELLA COMPETIZIONE PER LE RISORSE Lo studio della strategia utilizzata dai pescatori col metodo della “Volante” in Adriatico: La sfida è individuare le risorse sulla base delle proprie capacità, della propria esperienza e dell’osservazione degli altri (Chi sta pescando oggi? Dove? Chi non sta pescando? Dove?) Anchovy (Engraulis encrasicolus) Sardine (Sardina pilchardus)
  19. 19. Ecological Modelling 300 (2015) 102–113 Contents lists available at ScienceDirect Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel Modelling the strategy of mid-water trawlers targeting small pelagic fish in the Adriatic Sea and its drivers Tommaso Russoa,∗ , Jacopo Pulcinellaa , Antonio Parisib , Michela Martinellic , Andrea Belardinellic , Alberto Santojannic , Stefano Cataudellaa , Sabrina Colellac , Luca Anderlinid a Laboratory of Experimental Ecology and Aquaculture, Department of Biology, University of Rome Tor Vergata, Rome, Italy b Department of Economics and Finance, Faculty of Economics, University of Rome Tor Vergata, Rome, Italy c CNR, National Research Council of Italy, ISMAR, Marine Sciences Institute in Ancona, Italy d Department of Economics, Georgetown University, Washington, DC, USA a r t i c l e i n f o Article history: Received 15 July 2014 Received in revised form 28 November 2014 Accepted 1 December 2014 Keywords: Fisheries ecology VMS Pair trawl Mediterranean Sustainability a b s t r a c t Mid-water pair trawling (PTM) targeting small pelagic resources represents a key fishing activity in the Adriatic Sea. This fishery is experiencing a long period of crisis due to resource depletion and the lack of appropriate market strategies, and vessels spend most of the time searching for fishing schools. The searching strategy largely depends on the interaction between vessels: the captains of the PTM units take their decision also checking the position and the fishing status of other vessels. Understanding this strategy represents a key step towards a more effective resource management, since strategies directly determine the pattern of fishing effort. A Conditional Logit model has been devised to analyze fisher- men’s strategy as a non-cooperative game. This category of games is characterized by the existence of (at least) one equilibrium point – a Nash Equilibrium – in which each player plays his strategy, that is a Best Response to the strategies of the other players. This equilibrium point was estimated for the different scenarios defined by environmental (sea surface temperature and atmospheric pressure) and economic (fuel and fish prices at market) variables. Vessel Monitoring System data were used to capture fleet activ- ity, while different datasets were collected to reconstruct environmental and economic drivers. Results indicate a good predictive power of the model, and suggest that the equilibrium strategy that guides units’ behaviour is invariant with respect to environmental conditions, whereas it is largely influenced by economic factors. These latter, via strategies, may determine important consequences on the resources in terms of exploited areas and the impact of fishing activity. In particular, a low fuel price when fish price is high leads to higher values of CPUE, and then to a more efficient but also impacting fishing activity. © 2014 Elsevier B.V. All rights reserved. 1. Introduction ecosystem approach to fisheries underlying the new Common STRATEGIA: §dove si dirigono le varie coppie? §Quanto pesca ogni coppia? §Come agiscono i fattori economici (costo del carburante, prezzo delle risorse al mercato) sul comportamento delle coppie?
  20. 20. ANALISI DEI FLUSSI DALLE AREE DI PESCA AI PORTI Contents lists available at ScienceDirect Fisheries Research journal homepage: www.elsevier.com/locate/fishres Research Paper A model combining landings and VMS data to estimate landings by fishing ground and harbor T. Russoa,⁎,1 , E.B. Morellob,1 , A. Parisic , G. Scarcellab , S Angelinib , L. Labanchid , M. Martinellib , L. D’Andreaa , A Santojannib , E. Arnerib,e , S. Cataudellaa a University of Rome Tor Vergata, via della Ricerca Scientifica snc, 00133, Rome, Italy b CNR – Italian National Research Council, ISMAR – Institute of Marine Sciences, Largo Fiera della pesca 2, Ancona, 60125, Italy c Department of Economics and Finance, Faculty of Economics, University of Rome Tor Vergata, via Columbia, 00133, Rome, Italy d Società cooperativa MABLY, Via Vito Lembo 12, 84129, Salerno, Italy e FAO ADRIAMED and MEDSUDMED Projects, Via delle Terme di Caracalla, 00153, Rome, Italy A R T I C L E I N F O Handled by Dr. Bent Herrmann Keywords: Landings Vessel monitoring system Spatial management Adriatic sea A B S T R A C T At present, the assessment and management of Adriatic Sea fishery resources are based on data that do not fully account for the complex spatial patterns arising from fleet behavior and/or species’ behavior and biology, mainly because logbooks do not guarantee adequate coverage of the fishing activity exerted by the fleet. For data collection, the Adriatic Sea is divided into two management areas (namely FAO Geographical Sub-Areas–GSAs). To account for these spatial patterns while using the data available, we propose a method for estimating the monthly landings of Italian trawlers operating in the Adriatic Sea at a higher spatial resolution than the GSA. We use a stepwise approach based on the combined analysis of questionnaire-derived vessel-specific landings and the spatial activity of the vessels with respect to a set of fishing grounds. Thus, we sequentially 1) analyze the available vessel monitoring system data, 2) partition the study area into fishing grounds (the origin of the landings), 3) cross analyze vessel-specific fishing efforts with the available vessel-specific monthly landings to estimate the LPUE of each fishing ground, and 4) estimate the monthly landings (by vessel, fishing ground, and harbor) for the whole fleet and the monthly fluxes between fishing grounds (origin) and landing harbors (the destination of the landings). We apply the method to two species: the Norway lobster and the European hake. For both species, we find a few fishing grounds to be consistently more productive than others and the landings per harbor to vary greatly but with few harbors regularly receiving a significant share. In particular, the results suggest that the Pomo/Jabuka pit area represents a critical area for both species. Additional outcomes include a detailed characterization of the activity of the Adriatic bottom trawling fleet, highlighting the strengths and shortcomings of the official data available. We discuss the results in the context of the current management paradigm. Scampo (Nephrops norvegiucus)
  21. 21. ANALISI DEI FLUSSI DALLE AREE DI PESCA AI PORTI Contents lists available at ScienceDirect Fisheries Research journal homepage: www.elsevier.com/locate/fishres Research Paper A model combining landings and VMS data to estimate landings by fishing ground and harbor T. Russoa,⁎,1 , E.B. Morellob,1 , A. Parisic , G. Scarcellab , S Angelinib , L. Labanchid , M. Martinellib , L. D’Andreaa , A Santojannib , E. Arnerib,e , S. Cataudellaa a University of Rome Tor Vergata, via della Ricerca Scientifica snc, 00133, Rome, Italy b CNR – Italian National Research Council, ISMAR – Institute of Marine Sciences, Largo Fiera della pesca 2, Ancona, 60125, Italy c Department of Economics and Finance, Faculty of Economics, University of Rome Tor Vergata, via Columbia, 00133, Rome, Italy d Società cooperativa MABLY, Via Vito Lembo 12, 84129, Salerno, Italy e FAO ADRIAMED and MEDSUDMED Projects, Via delle Terme di Caracalla, 00153, Rome, Italy A R T I C L E I N F O Handled by Dr. Bent Herrmann Keywords: Landings Vessel monitoring system Spatial management Adriatic sea A B S T R A C T At present, the assessment and management of Adriatic Sea fishery resources are based on data that do not fully account for the complex spatial patterns arising from fleet behavior and/or species’ behavior and biology, mainly because logbooks do not guarantee adequate coverage of the fishing activity exerted by the fleet. For data collection, the Adriatic Sea is divided into two management areas (namely FAO Geographical Sub-Areas–GSAs). To account for these spatial patterns while using the data available, we propose a method for estimating the monthly landings of Italian trawlers operating in the Adriatic Sea at a higher spatial resolution than the GSA. We use a stepwise approach based on the combined analysis of questionnaire-derived vessel-specific landings and the spatial activity of the vessels with respect to a set of fishing grounds. Thus, we sequentially 1) analyze the available vessel monitoring system data, 2) partition the study area into fishing grounds (the origin of the landings), 3) cross analyze vessel-specific fishing efforts with the available vessel-specific monthly landings to estimate the LPUE of each fishing ground, and 4) estimate the monthly landings (by vessel, fishing ground, and harbor) for the whole fleet and the monthly fluxes between fishing grounds (origin) and landing harbors (the destination of the landings). We apply the method to two species: the Norway lobster and the European hake. For both species, we find a few fishing grounds to be consistently more productive than others and the landings per harbor to vary greatly but with few harbors regularly receiving a significant share. In particular, the results suggest that the Pomo/Jabuka pit area represents a critical area for both species. Additional outcomes include a detailed characterization of the activity of the Adriatic bottom trawling fleet, highlighting the strengths and shortcomings of the official data available. We discuss the results in the context of the current management paradigm. Nasello (Merluccius merluccius)
  22. 22. LA PRODUZIONE DELL’ADRIATICO: L’IMPORTANZA DELLE AREE DI PESCA L’analisi evidenzia il ruolo chiavi di alcune aree (es. La fossa di Pomo) Tonnellate/anno Nasello (Merluccius merluccius)Scampo (Nephrops norvegiucus)
  23. 23. RICADUTE APPLICATIVE: LA CHIUSURA DELLA PESCA NEL COMPLESSO DI POMO Attività di supporto scientifico nell’ambito del Progetto FAO ADRIAMED Annex 1 Geographical coordinates of the Jabuka/Pomo Pit FRA (Adriatic Sea)
  24. 24. GRAZIE PER L’ATTENZIONE Lunga vita e prosperità per l’Adriatico

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