Otolith chemistry has gained increasing attention as a tool for analyzing various aspects of fish biology, such as stock dynamics, migration patterns, hypoxia and pollution exposure, and connectivity between habitats. While these studies often assume otolith elemental concentrations reflect environmental conditions, physiological processes are increasingly recognized as a modulating and/or controlling factor. In particular, biomineralization—the complex, enzyme-regulated construction of CaCO3 crystals scaffolded by proteins—is believed to play a critical role in governing otolith chemical patterns. This review aims to summarize the knowledge on otolith composition and biophysical drivers of biomineralization, present hypotheses on how biomineralization should affect element incorporation, and test the validity thereof with selected case studies. Tracers of environmental history are assumed to be dominated by elements that substitute for Ca during crystal growth or that occur randomly trapped within the crystal lattice. Strontium (Sr) and barium (Ba) largely comply with the biomineralization-based hypotheses that otolith element patterns reflect environmental concentrations, without additional effects of salinity, but can be influenced by physiological processes, typically exhibiting decreasing incorporation with increasing growth. Conversely, tracers of physiology are assumed to be elements under physiological control and primarily occur protein-bound in the otolith’s organic matrix. Physiological tracers are hypothesized to reflect feedingmore »
"So, where do you come from?" The impact of assumed spatial population structure on estimates of recruitment
Understanding population dynamics is essential for achieving sustainable and productive fisheries. However, estimating recruitment in a stock assessment model involves the challenging task of identifying a self-sustaining population, which often includes representing complex geographic structure. A review of several case studies demonstrated that alternative stock assessment models can influence estimates of recruitment. Incorporating spatial population structure and connectivity into stock assessment models changed the perception of recruit- ment events for a wide diversity of fisheries, but the degree to which estimates were impacted depended on movement rates and relative stock sizes. For multiple population components, estimates of strong recruitment events and the productivity of smaller population units were often more sensitive to connectivity assumptions. Simulation testing, conditioned on these case studies, suggested that accurately accounting for population structure, either in management unit definitions or stock assessment model structure, improved recruitment estimates. An understanding of movement dynamics improved estimation of connected sub-populations. The challenge of representing geographic structure in stock assessment emphasizes the importance of defining self- sustaining management units to justify a unit-stock assumption.
- Award ID(s):
- 1841435
- Publication Date:
- NSF-PAR ID:
- 10137080
- Journal Name:
- Fisheries research
- Volume:
- 217
- Page Range or eLocation-ID:
- 156-186
- ISSN:
- 1872-6763
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Publisher's Version of Record
- https://doi.org/https://doi:10.1016/j.fishres.2018.11.030
