Abstract

Shellfish hatcheries have become an increasingly important component of aquaculture production in the United States. Although the industry has been advancing technologically over time to stabilize production and supply, many hatcheries suffer regularly from bouts of stalled or failed production, termed crashes. Crashes are widely acknowledged to occur and are considered a persistent problem in the industry but also an understudied phenomenon in the field of shellfish aquaculture that warrants greater investigation. Furthermore, there are few thorough reports on production variability from established hatcheries. To help fill the data gap and initiate a broader discussion on the causes of hatchery crashes, we provide testimonials from research hatchery managers across the Atlantic Coast about their experiences with crashes. As a case study, we report on long-term production trends (2011−2020) at Horn Point Laboratory's oyster hatchery, which included persistent production failure during the 2019 season. During the 2019 season, larval assays were conducted to determine drivers of production failure; however, no clear culprits were identified. Machine learning was used to help characterize production variability and hindcast the specific conditions when the hatchery's production was most efficient. Microbial community structure of larval associated microorganisms was shown to differ between a crash and non-crash time-point. We highlight the ubiquity of hatchery crashes along the Atlantic Coast of the US, the range of severity at which crashes can occur, and the difficulty of identifying the underlying causes of crashes, even at world-class research facilities. Collectively, we conclude that more research, data sharing, and cross-institution collaboration are needed to prevent crashes, and to develop mitigation strategies to maintain high levels of consistent shellfish aquaculture production.

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