Recruitment regime shifts and nonstationarity are widespread phenomena in harvestable stocks experiencing pronounced climate fluctuations

Abstract

Methods to reliably identify jump discontinuities in biological time series and to assess the specific contribution of various covariates are rapidly progressing. Here, we took advantage of these statistical improvements as well as those seen in complementary, down‐scaled climate and biogeochemical models to investigate causes of the substantial interannual variability observed in recruitment strength in hindcast analyses. This systematic meta‐analysis included 23 data‐rich, commercially valuable, warm‐ and cold‐temperate stocks in the North, Norwegian and Barents Seas. Since this study focuses on recruitment strength variability, we have used the term “recruitment regime shift” to distinguish from the concept of ecosystem regime shift. The breakpoint analysis revealed that the former criterion applied to more than half of the time series, mainly with respect to North Sea stocks but also to those in the Norwegian Sea. The exploratory analysis using vcGAM indicated that 1–3 shifts per stock were real, when using five drivers spanning spawning stock biomass to large‐scale climatic processes. Thus, non‐stationary relationships were extensively prevalent, indicating that each stock is uniquely adapted to its locally varying conditions. Outputs from the stationary GAM resembled those from the vcGAM but not after the threshold year. In‐depth case studies showed that the proxy of a given driver for the process which was to be included should be critically considered in a spatiotemporal context. Furthermore, the stock‐specific uncertainty associated with the given recruitment figures as such should also be an in‐built component of the model construct and thereby in the evaluation of the output.

Northeast Atlantic fish stock productivity hindcasts and forecasts from a Bayesian framework reveal pronounced climate‐induced dynamics

“…A non-stationary pattern also existed between the recruitment of Norwegian spring-spawning herring and GSP, reiterating the ambiguous relationship between productivity and this driver (Ma, Huse, et al, 2024). For the North Sea autumn-spawning herring, additional warming should also be regarded as negative for its productivity, agreeing with expert scorings (Kjesbu et al, 2022), as well as with the hypothesized cause and effect behind its recruitment failure in the 2000s (Corten, 2013;Payne et al, 2009).…”

“…However, these benefits might be counteracted by greater energetic costs due to the larger distances for spawning migrations (Kjesbu et al, 2023). In the recent decade, the Northeast Arctic cod has shown high-level catches and SSB, while its recruitment (Ma, Huse, et al, 2024), as well as its productivity, as assessed in our study, have shifted to relatively low productivity. This species is cannibalistic (Bogstad et al, 2016) the resultant recruitment levels is further complicated compared with many other species.…”

“…The Atlantic cod, represented in this study by four stocks, has attracted considerable attention from the scientific (and public) community due to its high commercial value, significant ecological role and notable population dynamics (Link et al, 2009;Myers et al, 1996;Sguotti et al, 2020). A general, near-negative effect of ocean warming on Atlantic cod stocks occurred, supported by recruitment of non-linear, non-stationary models (Ma, Huse, et al, 2024). For the high-latitude Northeast Arctic cod, expert scorings have instead implied a positive directional effect but then restricted this assessment to the 2050s (Kjesbu et al, 2022), that is, near or at the typical interception point, if present, for the three SSPbased production curves.…”

“…tolerance limits (Kerby et al, 2013b). In addition, the recruitment of this stock seems positively affected by temperature, particularly before the mid-1990s (Ma, Huse, et al, 2024). In the case of North Sea sprat, a dome-shaped relationship with temperature has been revealed both for body growth (Lindegren et al, 2020) and recruitment (Ma, Huse, et al, 2024).…”

“…One of the key strengths of this sort of surplus production model is the absence of assumptions regarding the stock-recruitment relationship, which often exhibits non-linearity and non-stationarity (e.g. Ma, Huse, et al, 2024;Munch et al, 2018;Szuwalski et al, 2015).…”