Environmental drivers of herring growth and how the perception shifts with time series length

Type Article
Date 2022-08
Language English
Author(s) Claireaux Marion1, 2, Zimmermann Fabian3, Ernande BrunoORCID4, 5, Heino Mikko5, 6, 7, Enberg Katja8
Affiliation(s) 1 : Institute of Marine Research Tromso, 235118, Tromso, Norway
2 : University of Bergen, 1658, Department of Biological Sciences, Bergen, Norway;
3 : Institute of Marine Research Tromso, 235118, Tromso, Norway;
4 : IFREMER, MARBEC, Univ. Montpellier, Montpellier, France
5 : IIASA, 31362, Laxenburg, Austria;
6 : University of Bergen, 1658, Department of Biological Sciences, Bergen, Norway
7 : Institute of Marine Research, Bergen, Norway
8 : University of Bergen, 1658, Department of Biological Sciences, Bergen, Norway, 5020;
Source Canadian Journal of Fisheries and Aquatic Sciences (0706-652X) (Canadian Science Publishing), 2022-08 , Vol. 79 , N. 8 , P. 1282-1290
DOI 10.1139/cjfas-2021-0176
Keyword(s) somatic growth, density dependence, environmental drivers, SST, NAO, scale chronology, sclerochronology
Abstract

Growth is a key component of population dynamics and, thus, fisheries management, yet drivers of its variations are often poorly understood. Using individual data collected over 80 years, we explored how environmental drivers affect growth in a major population of Atlantic herring (Clupea harengus). The results confirm that intrinsic factors (age and maturation) determine growth to a large degree but also that extrinsic factors such as temperature have some influence. While the role of intrinsic factors was independent of time series length, the importance of extrinsic drivers vary strongly with the analysed time period. It remains unclear whether this is caused by data inconsistencies back in time, spurious correlations appearing in shorter time series, shifts in population dynamics, or dynamic interactions between variables that cannot be determined with current data. Generally, environmental effects on growth became less clear and relevant with increasing time series length. What drives variation in growth may therefore change over time, potentially due to impacts such as fishing or climate change. It also underlines that seemingly clear correlations can break down or change their sign over time, hence caution is advised when interpreting results from time series of 20-40 years.

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