50 Spatial fishery dynamics

Fishing fleets are specified in the Ecopath model, along with landings, discards, discard mortality rates, discard fate and market values of each landed species and non-market price. When moving to Ecospace, it is important to enter the percentage of costs that are “sailing related” (e.g., fuel, crew) in Ecopath and then specify how the relative cost of fishing is expressed across the modeled area. With this information, Ecospace will distribute fishing effort spatially through a gravity model^{[1] [2]}, where the effort allocated to each spatial cell is based on the profitability of fishing estimated as the difference between expected income and costs of fishing in each cell^[3], thus proportional to the net benefits (profits-costs) gained from fishing in a given cell. When no cost or revenue information is entered, the fleets will gravitate to cells with the highest biomass of their target species. The cost of fishing can also be used to keep fleets from operating in certain areas, e.g., on the windward side of Caribbean islands or to keep fleets out of neighboring countries’ EEZ.

Ideally, expected income should be estimated with local economic and market data, otherwise it can be estimated using prices per functional groups from global price databases available based on average prices^[4], or even better, regional or local data if applications are regional.

There is an option on the Ecospace map to calculate the cost of fishing based on the assumption that it is proportional to the distance (km) from the nearest coast or port. This is done based on Euclidean distances from the nearest port for each fleet. The calculation is very rudimentary and does not calculate pathway lengths around land masses thus, more suitable data can be used when available.

Each fleet can be allowed to operate – or restricted from fishing – in one or more habitat types, and MPAs can be placed that exclude one or more fishing fleets during specified months. For a detailed description of fishing dynamics in Ecospace,^[5][6]. In addition, there is a new feature of the Ecospace model called the “MPA dynamic routine”. This routine allows one to study the spatial-temporal creations of MPAs, which can be allocated to fleet(s) at any moment in time during a simulation, and can be operative monthly or annually. This feature allows full control of MPA location or deletion in time and space^[7]. It can be a good idea to use environmental preference functions to distribute ecosystem groups spatially and habitats to distribute fishing effort.

Ideally, the emergent fishing effort distributions predicted by Ecospace should be compared to observed spatial effort patterns, such as those from logbook and vessel monitoring systems (VMS and/or AIS) data^[8], and parameters would be adjusted to improve agreement. However, this has rarely been done in practice^[9], due to a lack of spatial effort data in most modeled systems and difficulties in modeling fisher behavior and complex spatial management. Alternatively, one may attempt to force fishing effort using the spatial-temporal framework by either directly importing fleet-specific sailing cost maps that make it prohibitively expensive to fish in certain cells, or by designating an MPA or habitat for each fleet and loading time-varying maps of closed cells or habitat types. Additionally, habitat layers and MPAs can be used to impose administrative boundaries that prohibit fleets from operating in certain jurisdictions. While Ecospace contains great flexibility in representing spatial fishery dynamics, thus far little attention has been devoted to spatial effort dynamics^[10][11] compared to the biomass and ecological responses generated by Ecospace. This represents a component of the Ecospace that would benefit from simulation research, demonstration, and application.