However, data for how these smaller operations effect ecosystems is limited, and ineffective enforcement of these endeavours can allow for continued environmental degradation from overexploitation of local fish stocks.
To combat this, we used spatial planning to design an enforcement strategy that considers multiple factors including climate variability, existing seasonal fishing closures, conservation targets, and enforcement costs. Since these priorities vary season to season, a dynamic enforcement strategy offers the best solution.
Figure 1: Spatial priorities for enforcement of artisanal fisheries in the Patos Lagoon estuary when ignoring El Niño Southern Oscillation (ENSO) intensities (Group 1) and when incorporating spatial distribution of species during distinct ENSO intensities as conservation features (Group 3). Selection frequency is how often a planning unit is selected across 100 runs under each scenario. Here, the cost layer used was the estimated enforcement cost by the government.
This is one of the first studies to consider how environmental variability within spatial planning can be used to efficiently optimise enforcement to meet multiple conservation actions.
Most fisheries management in Brazil has focused on control of catch, fish size restrictions, and restricted seasonal areas, enforced by patrols that detect and prosecute illegal activities. With limited enforcement resources, there is an opportunity to use modelling to increase the chance enforcement reduces poaching at a minimum cost.
Combining fisheries data with conservation planning and considering seasonal change, we applied spatial planning tool Marxan, while shifting enforcement from governments to local communities, to design an optimum strategy over space and time for Patos Lagoon estuary in Brazil. We aimed to protect 25% of each of our main species considered in the seasonal fishing closure and 10% of the remaining estuarine biodiversity for each scenario tested.
Figure 2: Mean cost and area selected to enforce the artisanal fishery in the Patos Lagoon estuary. Results displayed in this graph represent scenarios from Group 1, 2 and 3: A) El Niño and B) La Niña, C) enforcement by environmental agency and D) enforcement by fishers.