Projecting environmental and krill fishery impacts on the Antarctic Peninsula food web in 2100

Testa, Giovanni; Neira, Sergio Peña; Giesecke, Ricardo; Piñones, Andrea

doi:10.1016/j.pocean.2022.102862

Cited by 7 publications

(1 citation statement)

References 124 publications

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“…For example, increased GCM resolution of 10 km has significantly decreased Spring SST bias in northwest Atlantic shelf waters (with zero bias in inner shelf waters in the Gulf of Maine and southern New England) (Saba et al 2016). Only recently have CMIP6 GCM output been used in fisheries projections (Fauchald et al 2021;Koul et al 2021;Testa et al 2022). Additionally, while previous fisheries models often include atmospheric forcing climate indices (e.g., ENSO and NAO) (Brunel and Boucher 2007;Caputi et al 2010;Muhling et al 2018), models rarely include direct measures of wind in projections, which have been shown to explain interannual recruitment variation (Churchill et al 2011;Hare et al 2015;Skagseth et al 2015) potentially due to larval transport and food supply mechanisms (Nakata et al 2000;Vikebø et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Using LASSO regularization to project recruitment under CMIP6 climate scenarios in a coastal fishery with spatial oceanographic gradients

Czaja

Hennen

Cerrato

et al. 2023

Can. J. Fish. Aquat. Sci.

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As climate change disrupts fisheries, scientists are interested in fisheries projections under climate change scenarios. However, projections that account for spatial oceanographic gradients, use increased variable selection power and output high spatial resolution climate data are needed to improve strategic fisheries management. This study uses the Least Absolute Squares and Selection Operator, a regularization technique, and improved, climate change projections from phase 6 of the Couple Model Intercomparison Project to relate Atlantic surfclam, Spisula solidissima solidissima, recruitment to climate variables. Results show a longitudinal gradient in New York State waters where western recruitment displays a negative relationship with sea surface temperature and eastern recruitment displays a negative relationship with eastward spring wind intensity. Models project recruitment in 2050 will decrease 100% in western waters and remain sporadic, but high, in eastern waters. This study provides insight regarding surfclam responses to climate change and considerations (methodological and statistical) for improved climate-based fisheries projections.

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