Advances in modelling the effectiveness of Marine Protected Areas (MPAs) to enhance conservation management of mobile fish stocks.

Marine Protected Areas (MPAs) have been proposed as beneficial for conservation of fish species and as fisheries management tools. However, there is lack of consensus about the benefit of MPAs for mobile species, which are under-represented in the literature. Empirical data in this field are lacking for mobile species so mathematical models are useful tools to explore the design and effectiveness of MPAs. A spatio-temporal, age-structured mathematical model was developed to determine whether MPAs could be used to protect biomass and sustain yield of mobile commercial stocks. It is demonstrated that the temporal resolution of models can affect the reliability of model predictions and therefore must be at an appropriate scale, appropriate to biological processes. The model is applied to a two-species fishery of mobile stocks. It is shown that stock mobility can impact the effectiveness of an MPA, potentially preventing conservation aims and fisheries goals both being met. The model is developed to examine the effect of density-dependence in the stock recruitment relationship within the model: this is found to be a key factor which affects the reliability of predictions of MPA models. The model is also used to compare the potential benefits of MPAs to seasonal closures and it is shown that while MPAs can protect more of the stock biomass, effort control over and above either type of closure can give similar management outcomes. The model is used in a case-study of the North Sea herring (Clupea harengus) fishery. The case-study demonstrates the need for real-world data to be used in simulations for effective MPA planning. The outcomes from each model application emphasise the need for stock mobility, life-histories and stock status to be incorporated in MPA simulations. Doing so will improve reliability of simulation predictions and aid MPA planning.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of Essex

Year dc:date.issued

2020

Author dc:creator

• Watson, Fiona Mary

Language dc:language

en