For Peru fi shing is a prime source of foreign exchange, second only to mining. The country’s anchovy fishing fleet, which seeks the Peruvian anchovy Engraulis ringens, is the world’s largest single-species fi shery, with an average of 8% of global landings.
For safety and monitoring purposes, vessels have the statutory obligation to be equipped with satellite geopositioning indicators, seeing that industrial-scale fi shing is prohibited within a band of 5 nautical miles (about 9 kilometres) from the coast.
This satellite device, the vessel monitoring system (VMS), gives the real-time position of the vessels to an accuracy of 100 m, communicated to bodies responsible for vessel movement recording and scientifi c monitoring of fi shing. Scientists from the IRD and the Peruvian Institute of the Sea (IMARPE) used this high-resolution spatial information to characterize vessel movement in campaigns targeting shoals of this anchovy species, a pelagic fi sh that usually lives and builds up off the coasts. These methods shed light on the spatial interactions between fi sh and fi shermen and enabled researchers to devise new tools that could improve monitoring and hence operational fi sh stock management.
The characteristics of movements traced between December 1999 and March 2003 by the 809 vessel fl eet were compared with those of theoretical movement models usually applied to study trajectories of animals (2).
The results showed that in their search for fi sh concentrations, the fi shermen adoptedmovement strategies similar to those described for natural predators, such as albatross or seals. Attributes considered as characteristically human, like the use of detection technologies (sonar, echo-sounding), communications (radio between vessels), and also economic motives or attachment to a port, did not produce a prey search strategy radically different from that of animal predators. Whether human or not, top predators of marine ecosystems must confront a degree of uncertainty as to the location of their prey. They therefore develop search strategies that enable them to manage this uncertainty while reducing “unproductive” movements to a minimum.
This convergence found between prey search by fi shermen and natural predators could change our general perception of human activity in marine ecosystems exploited for fi shing. Fishermen are not solely economic agents whose catches (i.e. removal of organisms) constitute a disturbance acting from outside the ecosystem.
They are part and parcel of it and their behaviour obeys the same laws as for other higher predators. Such results emphasize the importance of applying an ecosystembased approach to fi sheries management, integrating knowledge about the biotic, abiotic and human components of the marine ecosystems exploited, along with their interactions.
This study will moreover have immediate practical applications for fi sh stock management, as VMS data analysis provided an indication in real time of the fragility of the stock drawn upon. Off Peru, the anchovy are at the mercy of fi shermen particularly when climatic conditions force shoals to gather and stay very close to the coast.
The research team indeed showed that the spatial behaviour of fi shermen was a good indicator of the spatial distribution of fi sh.
Thus the grouping together of fi shing vessels near the coast can be an alarm signal showing high vulnerability of stock exploited and give clues as to possible management measures to relieve the fi shing pressure during these critical periods. This type of analysis, already used for monitoring the Peruvian anchovy stock, is being developed for application to European fi sheries by way of the European Project CEDER, initiated by the European Union as part of its Sixth Framework Programme (3).
(1) This research was conducted by scientists from IRD’s Centre de Recherche Halieutique Méditerranéenne et Tropicale, research unit UR097 ECO-UP in collaboration with researchers from IMARPE (Peru Institute of the Sea).
(2) The Levy random walk model, applied very recently in general ecology, proved to be the most appropriate model for describing the movement of vessels studied. This type of random walk is characterized by trajectories where there are many successive small movements (within the areas rich in prey) and occasional especially long movements (between two widely separated concentrations of prey).
(3) http://ceder.jrc.cec.eu.int/
Rédaction IRD : Céline Bézy / Marie Guillaume-Signoret
Translation : Nicholas Flay
Journal
Ecological Applications