Fisheries benefits of a marine protected area with endogenous fishing efforts – A bioeconomic analysis

Highlights

• A marine protected area (MPA) changes the fishing geography and redistribute effort.

• Fishers are forced into similar areas not directly adjacent to the MPA.

• High catch near the MPA arises due to reduced fishing effort as opposed to spillover.

• Fishers respond negatively to rising human risk and travel distance.

• Specific sites attributes and fishing behaviour are key in the design of MPA.

Abstract

The study assesses the conservation and fisheries benefits of the Blue Bay Marine Park in Mauritius. It addresses the question - are the higher catch rates near the Park a result of population spillovers or of reduced fishing effort in those waters due to site-specific attributes? There is no data on catches and fishing effort prior to the reserve's establishment; a bioeconomic model is used to separate the effects of spillover and effort redistribution on catch rates in waters next to the Marine Park. The area's fish populations are replicated using a dynamic age-structured model with a Beverton-Holt recruitment function, while fishing effort is predicted using a random utility model and Random Parameter Logit estimation. The bioeconomic model is characterised by two-way feedback loops between fish stocks and the geographic redistribution of fishing effort. A comparison of fish population, biomass, and catch rates in the fisheries with and without effort redistribution, suggests that the reduced fishing effort in waters near the Park, rather than spillover, is driving the increase in observed catch rates. Travel distance, variation in catch rates, depth of water and area status (lagoon vs. off-lagoon) explain the relocation of fishing effort away from the adjacent of the marine park. The study shows how site-specific characteristics affecting fisher behaviour are important in the design of marine reserves.

Introduction

Whilst Marine Protected Areas (MPAs) have often been proposed as means to support inshore ecosystems, many came into existence to protect areas of high amenity value. The Blue Bay Marine Park (BBMP) in Mauritius is one of these MPAs. Being small in size (353ha), it lies in the otherwise heavily fished lagoon area between the shoreline of Mauritius and the Island's fringing reef. Its main objectives are to protect the habitat for fish species and the diverse marine fauna and flora, to serve as a nursing ground for juvenile marine species, and to contribute to the stability of the marine environment (UNDP 2012). In addition to the amenity value, such MPAs can offer a range of potential ecological and economic benefits, which include the conservation of biodiversity, increased levels of biomass, improvements in fishery yield, and a buffer against environmental shocks and management failures (Sumaila, 1998; Hannesson, 1998; Sanchirico et al., 2006).

Many authors (e.g. Salas and Gaertner, 2004; Anderson et al., 2012; Benson and Stephenson, 2017) have commented that fisheries managers and reserve designers tend to focus on biological and ecological considerations whilst downplaying socio-economic issues. The biological factors, which influence the outcome of an MPA such as the BBMP, are multi-fold. They include the growth of fish populations inside the reserve, rates of recruitment, natural and fishing mortality, movement of fish, and dispersal of larvae to other areas (Polachek, 1990). These biological aspects are, however, also influenced by an important human factor, and one which should be considered in the design of MPAs, the spatial behaviour of fishers.

The importance of fishers’ behaviour after the establishment of a marine reserve has long been realized (Wilen, 1979; Smith et al., 2006). In more general terms, a reserve may redistribute effort unevenly if the costs of fishing are higher in some fishing grounds than others, or if some are riskier to fish. These issues are important because, if fish stocks increase inside the MPA and in the adjacent fishing areas, the question arises; are the higher catch rates in the vicinity of the MPA a result of spillovers and/or a reduction in the fishing effort due to site-specific attributes.

This study constructs a bioeconomic model to compare several metrics with and without effort redistribution following the establishment of the Marine Park. An advantage of the bioeconomic model is that it incorporates fishers’ behaviour and therefore it can correct for the effects of fishing effort relocation due to site-specific characteristics such as travel distance, variation in catch rates, depth of water, and area status (lagoon vs. off-lagoon). The study consequently separates the effects of spillover and the reduction in fishing effort in the adjacent sites of the Marine Park on the observed high catch rates.

The fish populations are modelled using a dynamic age-structured model characterised by two-way feedback loops between fish stocks and fishers' participation. Fishing effort is predicted using a random utility model (RUM). This is a utility theoretic model of fishers' fishing location choice, estimated through the Random Parameter Logit (RPL). The approach is to model fishers’ location choice and predict effort in different fishing areas, with and without the Marine Park. Similar approaches can be observed from Smith (2005) for the commercial sea urchin divers in California, Kahui and Alexander (2008) for the Marine Reserves at Stewart Island New Zealand, and Lee et al. (2017) for the groundfish fisheries of the North-eastern United States.

This paper distinguishes the benefits to the fisheries generated by spillovers from the Marine Park from those which arise when fishers relocate efforts driven by the Park. It also demonstrates how risk and travel distance from home ports mitigate effort redistribution to areas adjacent to the marine reserve. The likely effort redistribution is a key factor and should therefore be considered in assessing fisheries benefits of marine reserve.