4.7 Article

Technological creep masks continued decline in a lobster (Homarus gammarus) fishery over a century

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SCIENTIFIC REPORTS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-022-07293-2

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  1. Institute of Marine Research through the Coastal Area Program

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Fishery-dependent data are crucial for management decisions, but technological creep can lead to biased inferences. This study examines the impact of trap improvement on a European lobster fishery, revealing a significant decline in lobster abundance over nine decades. The findings highlight the importance of standardization, including technological development, when using commercial data for monitoring and managing data-limited fisheries.
Fishery-dependent data are frequently used to inform management decisions. However, inferences about stock development based on commercial data such as Catch-Per-Unit-Effort (CPUE) can be severely biased due to a phenomenon known as technological creep, where fishing technology improves over time. Here we show how trap improvement over nine decades has driven technological creep in a European lobster (Homarus gammarus) fishery. We combined fishing data, experimental fishing with contemporary and older trap types, and information on depletion effects during fishing seasons. The resulting standardized CPUE time series indicates a 92% decline in lobster abundance between 1928 and 2019 compared to 70% if technological creep is not corrected for. Differences are most pronounced within the last 40 years when the most substantial shift in gear technology occurred: an uncorrected CPUE index suggests an 8% increase in lobster abundance during this period, while the corrected CPUE index declined by 57%. We conclude that technological creep has masked a continuous stock decline, particularly in recent decades and largely driven by the shift from one- to two-chambered traps, as well as the ability of newer trap designs to capture larger lobsters. Our study confirms the importance of adequate standardization, including technological development, when using fishery dependent CPUE for monitoring and management of data-limited fisheries.

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