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

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. IL PROGETTO MANTIS
EU, DG MARE - Agreement number – SI2 - 721911
MANTIS: Marine protected Areas
Network Towards Sustainable
fisheries in the Central
Mediterranean

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. GRAZIE PER L’ATTENZIONE
Lunga vita e prosperità
per l’Adriatico