Potential sources of bias in the climate sensitivities of fish otolith biochronologies

Analysis of growth increments in the hard parts of animals (e.g., fish otoliths) can be used to assess how organisms respond to variability in environmental conditions. In this study, mixed-effects models were applied to otolith data simulated for two hypothetical fish populations with assumed biolo...

Full description

Saved in:
Bibliographic Details
Published in:Canadian journal of fisheries and aquatic sciences 2020-09, Vol.77 (9), p.1552-1563
Main Authors: Smoliński, Szymon, Morrongiello, John, van der Sleen, Peter, Black, Bryan A, Campana, Steven E
Format: Article
Language:English
Subjects:
Age determination
Aging
Analysis
Climate change
Computer simulation
Environmental changes
Environmental conditions
Environmental effects
Environmental factors
Evaluation
Fish
Fish populations
Fishes
Gadus morhua
Growth
Marine
Modelling
Otolith reading
Otoliths
Populations
Robustness
Sensitivity analysis
Time series
Variability
Variation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Analysis of growth increments in the hard parts of animals (e.g., fish otoliths) can be used to assess how organisms respond to variability in environmental conditions. In this study, mixed-effects models were applied to otolith data simulated for two hypothetical fish populations with assumed biological parameters and known growth response to environmental variability. Our objective was to assess the sensitivity of environment–growth relationships derived from otolith biochronologies when challenged with a range of realistic ageing errors and sampling regimes. We found that the development of a robust biochronology and the precision of environmental effect estimates can be seriously hampered by insufficient sample size. Moreover, the introduction of even moderate ageing error into the data can cause substantial underestimation of environmental sources of growth variation. This underestimation diminished our capacity to correctly quantify the known environment–growth relationship and more generally will lead to overly conservative conclusions concerning the growth response to environmental change. Careful study design, reduction of ageing errors, and large sample sizes are critical prerequisites if robust inferences are to be made from biochronological data.
ISSN:0706-652X
1205-7533
DOI:10.1139/cjfas-2019-0450