A synthetic control approach to estimate the effect of total allowable catches in the high seas |
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Authors: | Julia Margaret Lawson Conner Muir Smith |
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Institution: | Bren School of Environmental Science & Management, University of California, Santa Barbara, California, USA |
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Abstract: | Total allowable catch restrictions (hereafter referred to as catch quotas) play an important role in maintaining healthy fish stocks. While studies have identified a positive relationship between catch quota implementation and improved stock status, these methods are subject to selection bias as catch quotas are typically applied to stocks that are depleted. We address this challenge using the synthetic control method, which estimates the causal effect of catch quotas on fishing mortality and biomass by predicting a synthetic counterfactual outcome. We focus on high seas stocks (tunas, billfishes, and sharks) managed by tuna Regional Fisheries Management Organizations (tRFMOs), first providing an overview of stock status and current management measures in place. We find that implementation of catch quotas by tRFMOs has more than doubled over the past decade. Second, we predict the hypothetical fishing mortality and biomass trajectory for seven high seas quota-managed stocks in absence of a catch quota. These “synthetic non-quota stocks” are predicted using a weighted selection of high seas non-quota stocks. Credibility of the synthetic non-quota stocks is evaluated through diagnostic checks, and robustness tests assess sensitivity to study design. Five credible fishing mortality synthetic controls are predicted: three add support to the hypothesis that catch quotas successfully reduce fishing mortality, while two find that catch quotas increase fishing mortality. While our analysis is limited in scope, given that all seven quota-managed stocks are managed under a single tRFMO, we highlight the potential for the synthetic control method in fisheries management evaluation. |
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Keywords: | fisheries management high seas fisheries selection bias stock status synthetic control tRFMO |
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