On the Match-Mismatch dynamics of North Sea herring

The Match-Mismatch Hypothesis (MMH) has been a fundamental concept to understand fish recruitment variation for decades (see post). With climate change this hypothesis developed in 1969 by David Cushing  has been revived in many predator-prey studies (see post, and post,  Durant et al. 2013, Ferreira et al. 2020).

Our study published in ICES journal of Marine Science, focuses on the overlap between herring (Clupea harengus) larvae, zooplankton (Temora longicornis, Oithona sp., Pseudocalanus spp., and Acartia spp.), and phytoplankton in the North Sea from 1982 to 2017. We found that MMH explained 23% of recruitment of North Sea autumn-spawning herring and that value was consistent across different trophic levels. Additionally, the study found a spatial pattern in both the overlap and the negative relationship between the overlap and recruitment, which was similar to the variation of habitat use of North Sea herring (Fig 1).

The methodology used in this study involves the analysis of North Sea herring larvae data gathered from the ICES eggs and larvae database, which were collected using Gulf III and Gulf VII samplers with a 280 or 300μm mesh size net. The data were collected within the International Herring Larvae Survey from 1982 to 2017(Gröger et al. 2001, ICES 2010). The study focuses on the western North Sea, which is also where the North Sea autumn-spawning herring stock spawns. The data were restricted to fish with a length equal to or above 6 mm to include only feeding larvae. The survival measure used in this study is the recruitment of North Sea autumn-spawning herring at 0 winter rings (wr), which corresponds to 1-year-old autumn spawning herring. Zooplankton and phytoplankton data were gathered from the Continuous Plankton Recorder database from the Sir Alister Hardy Foundation for Ocean Science (Johns 2020b, a), while SST data were downloaded from the National Oceanic and Atmospheric Administration (Reynolds et al. 2002).

The analyses were performed with Generalized Additive Models (GAMs) to smooth and fill in the spatiotemporal gaps in the data set. The spatio-temporal overlap metric was used to quantify the degree of overlap between different trophic levels, and was calculated based on the minimum integral of the areas of overlap under the curves of predator-prey pairs of the three trophic levels. The relationship between the overlap index and recruitment of herring was assessed using a linear model.

Our findings are crucial because they highlight the importance of understanding predator-prey dynamics and spatiotemporal variability in fish recruitment and population dynamics. This study thus suggests that sustainable fishery practices require accurate predictions of fish recruitment, which can be achieved by considering the impacts of MMH on different trophic levels. The study also has significant implications for future research, as we noted that there are still unexplained variation in the relationship between predator-prey dynamics and recruitment. Further studies can build on this research by exploring the mechanisms that drive this variation and how it can be accounted for in fishery management practices.

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References

Durant JM, Hjermann DØ, Falkenhaug T, Gifford DJ, Naustvoll L-J, Sullivan BK, Beaugrand G, Stenseth NC (2013) Extension of the match-mismatch hypothesis to predator-controlled systems. Marine Ecology Progress Series 474:43-52

Ferreira ASA, Neuheimer AB, Durant JM (2023) Impacts of the match-mismatch hypothesis across three trophic levels—a case study in the North Sea. ICES Journal of Marine Science: 80(2) 308–316, DOI: 10.1093/icesjms/fsac237

Ferreira ASA, Stige LC, Neuheimer AB, Bogstad B, Yaragina N, Prokopchuk I, Durant JM (2020) Match-mismatch dynamics in the Norwegian-Barents Sea system. Marine Ecology Progress Series 650: 81-94

Cushing DH (1969) The regularity of the spawning season of some fishes. J Cons Int Explor Mer 33:81–92

Gröger J, Schnack D, Rohlf N (2001) Optimisation of survey design and calculation procedure for the international herring larvae survey in the North Sea. Archive of Fishery and Marine Research 49:103-116

ICES C (2010) Report of the Working Group for International Pelagic Surveys (WGIPS), 19‐22 January 2010. ICES CM 2010/SSGESST:03, Galway, Ireland

Johns D (2020a) Monthly averaged data for Temora longicornis, Oithona sp., Pseudocalanus elongates, and Acartia spp. (35N to 65N, 75W to 15E) 1958-2018 as recorded by the Continuous Plankton Recorder. Sir Alister Hardy Foundation for Ocean Science, Plymouth

Johns D (2020b) Monthly averaged data for the Phytoplankton Colour Index, PCI (35N to 65N, 75W to 15E) 1958-2018 as recorded by the Continuous Plankton Recorder. Sir Alister Hardy Foundation for Ocean Science, Plymouth

Payne MR (2010) Mind the gaps: a state-space model for analysing the dynamics of North Sea herring spawning components. ICES Journal of Marine Science 67:1939-1947

Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. Journal of Climate 15:1609-1625