Adaptive management in pelagic fisheries Background

Small pelagic species, like sardine and anchovy, are subject to large fluctuations in abundance from one year to the next. Currently many modelling scenarios looking at the effects of climate change on these species predict an increase in the size and frequency of these fluctuations. However, our knowledge of the relative importance of the factors that influence the recruitment of these short-lived species, including: environment, size of the parental stock, predator/prey relationships etc., is very limited. Conventional management aimed at maintaining some stability in fishing quotas or fishing effort is poorly adapted to these particular stocks. In unfavourable years it can lead to their collapse and in favourable years to underexploitation, exaggerating the natural variability in abundance. It is therefore essential to apply quasi-real time adaptive management tools to help ensure the susta inability of these fisheries.

Monitoring highly variable resources

Most short lived-species are never found in a state of equilibrium, and are affected by both a fluctuating environment and fisheries exploitation. The abundance of such species is highly variable and responds rapidly to many forcing factors such as changes in the physical environment (water temperature, currents), biological interactions (fluctuations in prey and predator abundance), fishing, etc. After many decades trying to predict patterns of abundance of these stocks with limited success, the scientific community is now concentrating its effort on developing fast and more accurate methods of estimating abundance, distribution, demographic structure and biological condition of the resource. In the case of the Peruvian small pelagic fishery this information is collected using a set of tools and approaches which include: - extended acoustic surveys, performed two to three times a year to estimate the abundance of the main fish species and their predators (birds and mammals); - when the abundance is very low, 48hr “Eureka” surveys performed by the commercial fleet, with boats running two transects perpendicular to the coastline each, to ascertain the status of the resource in real time (Figure 1); - plankton surveys, conducted as indicators of the availability of prey but also to estimate fish abundance based on eggs and larvae density; - oceanographic and plankton productivity information, obtained through in situ and satellite data monitoring and analysis; - fishery monitoring in quasi-real time, thanks to a satellite-based vessel monitoring system (VMS) and inspectors in all landing points. Furthermore, scientific observers are positioned onboard some fishing boats and communicate with the government laboratory using mobile phones; - biological information (fish condition, reproductive stage, feeding, etc), collected during all surveys and at landing points. Together these pieces of information allow the fishery to be monitored, and the catches per age classes in space and time to be adjusted and optimized as needed.

Here we present the example of the Peruvian purse-seine fishery of anchovy where innovative adaptive management (AM) is implemented.

Figure 1. Scientific acoustic survey (one research vessel) versus Eureka survey (27 commercial vessels). The main difference between both surveys is the time needed to complete a survey with scientific surveys (left) taking several weeks, while Eureka surveys (right) only 48hr.

July 2008

Fact Sheet 9.

Under these conditions, Adaptive Management (AM) can prevent stock collapse and subsequent closure of the fisheries with their disastrous social and economical consequences. It also prevents underexploitation during periods of high abundance in contrast with too conservative and static conventional management. Although the benefits of the implementation of this approach are immediate for all stakeholders, its success can only be measured by comparing average catches and gains of the fishery sector over a few decades with simulated performance under more unresponsive management. The costs for quasi real time monitoring are relatively high but largely covered by the increase in gain of the fishing sector compared to a too conservative or a too risky management strategy. This approach is fully compatible with, and complementary to, an Ecosystem Approach to Marine Resources (EAMR; see Fact Sheet 2) since both approaches make use of the same pieces of information. But combining them remains a challenge. Further research is required to integrate the different kinds of knowledge and uncertainty regarding the short-time impact on ecosystems of abrupt changes in forcing factors such as catches or oceanographic conditions known to greatly influence the stocks distribution and abundance (e.g. El Niños events). Advanced statistical techniques should improve the design and effectiveness of AM approaches. In Peru, there is still the need to formalise this approach and incorporate it in a management procedure. Furthermore, reducing the large overcapacity of the Peruvian pelagic fisheries should ease to the application of AM (Fact Sheet 10).

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Reproductive closure season

For most short-lived species, regardless of the regulatory mechanisms, it is almost impossible to estimate an “optimal catch” at any given time based on biological parameters. It is therefore essential to manage these fisheries in an adaptive, flexible and fast manner. This requires not only quasi-real time scientific information on the status of the stock, the ecosystem and the fisheries, but also a fast decision-making chain between scientists, managers and fishers. In Peru, this chain is Catch limit = final closure; if juveniles > 10% catch = provisional closure

Action steps towards the implement of Adaptive Management:

1. Set up tools of direct estimation of abundance and geographical distribution (e.g. acoustic, trawl, aerial or fish egg surveys) and schedule their use at frequent intervals (adapted to the length of the target species’ life cycle). 2. Monitor, also at frequent intervals, fish biological parameters and the abundance of their prey, predators and supporting environment through direct surveys and remote satellite techniques. 3. Monitor the fishery in quasi-real time (VMS, observers, inspectors on landing sites). 4. Design a rule-based management system that allows fast decisions on quota allocations, open/closure of fishing zones, size limits, etc) based on available scientific information (e.g. Figure 2). 5. Ensure stakeholder participation in the design and evaluation of the rules every 2-4 years. 6. Implement an efficient and fast process of decision making and enforcement. Although AM was implemented long ago in some countries, there is nowhere that all 6 of these actions have been fully implemented at the same time, and in nearly all fisheries efforts to merge AM and EAMR are needed. This Fact Sheet was jointly composed by scientists at Institut de Recherche pour le Développement in Sète, France and Instituto del Mar del Peru, Peru. For further information please contact, Pierre Fréon ([email protected]), Sophie Bertrand ([email protected]), Marilu Bouchon ([email protected]) and Miguel Ñiquen ([email protected]).

FactSheet Sheetby: by:EUR-OCEANS EUR-OCEANSKnowledge KnowledgeTransfer TransferUnit, Unit,hosted hostedbybythe theGLOBEC GLOBECIPO IPOatatPlymouth PlymouthMarine MarineLaboratory. Laboratory. Fact www.eur-oceans.org/KTU For further information contact, Jessica Heard: [email protected] or visit the Website: For further information contact, Jessica Heard: [email protected] or visit the Website: www.eur-oceans.org/KTU