Estimating climate-driven phenology shifts and survey availability using fishery-dependent data

• Published in: Progress in Oceanography
• Main Authors: Olmos, Maxime, Ianelli, James, Ciannelli, Lorenzo, Spies, Ingrid, Mcgilliard, Carey, Thorson, James
• Other Authors: Dynamique et durabilité des écosystèmes : de la source à l’océan (DECOD), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Oregon State University (OSU), NOAA National Marine Fisheries Service (NMFS), National Oceanic and Atmospheric Administration (NOAA)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2023
• Subjects: Movement phenology; Climate-driven phenology shifts; Seasonal spatiotemporal model; Fishery-dependent data; Spatial availability; Catchability; Yellowfin sole; [SDE]Environmental Sciences; [SDE.BE]Environmental Sciences/Biodiversity and Ecology; Bering Sea
• Online Access: https://hal.inrae.fr/hal-04150632; https://doi.org/10.1016/j.pocean.2023.103035

International audience Environmental changes are predicted to impact fish ecology; specifically, the phenology of spawning and larval settlement, resulting adult and larval movement, and ultimately seasonal habitat utilization. Hence, warm or cold environmental conditions may cause early or late seasonal movement among habitats. However, resource surveys are typically designed to occur at approximately the same time each year, and this mismatch in timing between survey sampling and fish movement can cause a different proportion of population biomass to be available to the survey in different years. In this study, we demonstrate an application to minimize such impacts using yellowfin sole (Limanda aspera) in the eastern Bering Sea as a case study. We employed fishery-dependent catch-and-effort (also called catch per unit effort (CPUE)) data collected by observers on commercial vessels, which covered the months of March-October (whereas survey data were limited to June-August). We built a seasonal spatio-temporal model so that seasonal distribution could be used to better explain summer survey availability and movement timing as impacted by interannual temperature changes. Our results highlight (i) spawning movement phenology occurs earlier during warm years than cold years, (ii) spatial distribution is more constrained and biomass is lower during cold years than warm years, (iii) fish were more available to the summer survey during warm years than cold years, and (iv) phenology differed by sex with males staying longer on the spawning grounds than females. Finally, we computed an overlap index between the survey area and fishery CPUE data to be used as a catchability covariate within the yellowfin sole stock assessment. This index confirmed the changes in relative availability of this species by year as presently used in the assessment.