Data_Sheet_3_Potential Consequences of Climate and Management Scenarios for the Northeast Atlantic Mackerel Fishery.csv

• Main Authors: Robin Boyd, Robert Thorpe, Kieran Hyder, Shovonlal Roy, Nicola Walker, Richard Sibly
• Format: Dataset
• Language: unknown
• Published: 2020
• Subjects: Oceanography; Marine Biology; Marine Geoscience; Biological Oceanography; Chemical Oceanography; Physical Oceanography; Marine Engineering; Atlantic mackerel; climate change; fisheries management; earth system models; individual-based model; approximate Bayesian computation; Northeast Atlantic; Ocean acidification
• Online Access: https://doi.org/10.3389/fmars.2020.00639.s003; https://figshare.com/articles/dataset/Data_Sheet_3_Potential_Consequences_of_Climate_and_Management_Scenarios_for_the_Northeast_Atlantic_Mackerel_Fishery_csv/12763139

Climate change and fishing represent two of the most important stressors facing fish stocks. Forecasting the consequences of fishing scenarios has long been a central part of fisheries management. More recently, the effects of changing climate have been simulated alongside the effects of fishing to project their combined consequences for fish stocks. Here, we use an ecological individual-based model (IBM) to make predictions about how the Northeast Atlantic mackerel (NEAM) stock may respond to various fishing and climate scenarios out to 2050. Inputs to the IBM include Sea Surface Temperature (SST), chlorophyll concentration (as a proxy for prey availability) and rates of fishing mortality F at age. The climate scenarios comprise projections of SST and chlorophyll from an earth system model GFDL-ESM-2M under assumptions of high (RCP 2.6) and low (RCP 8.5) climate change mitigation action. Management scenarios comprise different levels of F, ranging from no fishing to rate F lim which represents an undesirable situation for management. In addition to these simple management scenarios, we also implement a hypothetical area closure in the North Sea, with different assumptions about how much fishing mortality is relocated elsewhere when it is closed. Our results suggest that, over the range of scenarios considered, fishing mortality has a larger effect than climate out to 2050. This result is evident in terms of stock size and spatial distribution in the summer months. We then show that the effects of area closures are highly sensitive to assumptions about how fishing mortality is relocated elsewhere after area closures. Going forward it would be useful to incorporate: (1) fishing fleet dynamics so that the behavioral response of fishers to area closures, and to the stock’s spatial distribution, can be better accounted for; and (2) additional climate-related stressors such as ocean acidification, deoxygenation and changes in prey composition.