Background

Multi-species fisheries and the interactions within them are complex and are not clearly understood. Despite being the focus of a considerable literature, no clearly defined management tools/strategies are currently available. Fishing effects on multi-species fish resources may be detected as changes in the relative abundance of species (species composition) in the stock, linked to fishing intensity, the relative catchabilities of the species, and the level of interaction (e.g. competition and predation) between them. Fishing removes top predators and is postulated to lead to increase in prey; however, observations supporting these predicted effects are limited. Understanding multispecies responses to fishing is necessary in order for managers to make informed decisions about appropriate resource assessment models, and to develop a suitable management strategy for them.

Approach

The project aimed to assess fishing effects, derive biological management guidelines, and describe minimum data requirements for demersal bank and deep slope reef fisheries - relatively simple multi-species examples but with widespread applicability.

To describe observed effects of fishing at the community level, data typically collected by developing country fisheries institutions from artisanal fisheries were analysed for case study fisheries in Tonga (deep slope) and the Indian Ocean (banks). Available local literature described the socio-economic context of each fishery.

To examine expected fishing effects and to develop guidelines for management, theoretical studies were performed using a Multispecies Interactive Dynamic Age Structured simulation model (MIDAS). Single and aggregate single species approaches, with length based methods were employed. Input parameters for modelling (e.g. abundance and population demographic estimates) were derived from case studies.

Findings

A Multispecies Interactive Dynamic Age Structured simulation model (MIDAS) was developed during the project, which simulates a number of stocks being fished by a number of gear types and will determine equilibrium and transient dynamics of the stocks.

No evidence for prey release or other multispecies interactions was found from either case-study or modelling analyses, but species composition changes due to technical interactions were significant. Prey release was only predicted from 5 years onwards into a fishery, but its magnitude was less than variation typically observed in available data indicating that it would be undetectable. These results suggest that single, and aggregate single species models were adequate to derive management advice and also that data need only be collected on the most important species and guilds of others. However, biological data collection on identified key species and improved data collection in relation to technological changes in the fishery were required.

Management simulations have resulted in guidelines for selecting a suitable target fishing mortality for species where length at maturity is unknown and length at first capture cannot be controlled. The guidelines suggest a means of selecting the most important and vulnerable species for analysis, and a method for setting overall effort limits for a multispecies fishery, taking into account different targeting practices and conservation trade-offs.