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 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.publishedVersio

Is oxygen limitation in warming waters a valid mechanism to explain decreased body sizes in aquatic ectotherms?

The authors would like to acknowledge funding from Australian Research Council (grant No. DP170104240) and the Kone Foundation (to AA), Horizon 2020 European research projects ClimeFish (grant No. 677039) (to ARB) and Australian Academy of Science (to JRM)Peer reviewedPostprintPostprin

Growth portfolios buffer climate-linked environmental change in marine systems

Large-scale, climate-induced synchrony in the productivity of fish populations is becoming more pronounced in the world's oceans. As synchrony increases, a population's “portfolio” of responses can be diminished, in turn reducing its resilience to strong perturbation. Here we argue that the costs and benefits of trait synchronization, such as the expression of growth rate, are context dependent. Contrary to prevailing views, synchrony among individuals could actually be beneficial for populations if growth synchrony increases during favorable conditions, and then declines under poor conditions when a broader portfolio of responses could be useful. Importantly, growth synchrony among individuals within populations has seldom been measured, despite well-documented evidence of synchrony across populations. Here, we used century-scale time series of annual otolith growth to test for changes in growth synchronization among individuals within multiple populations of a marine keystone species (Atlantic cod, Gadus morhua). On the basis of 74,662 annual growth increments recorded in 13,749 otoliths, we detected a rising conformity in long-term growth rates within five northeast Atlantic cod populations in response to both favorable growth conditions and a large-scale, multidecadal mode of climate variability similar to the East Atlantic Pattern. The within-population synchrony was distinct from the across-population synchrony commonly reported for large-scale environmental drivers. Climate-linked, among-individual growth synchrony was also identified in other Northeast Atlantic pelagic, deep-sea and bivalve species. We hypothesize that growth synchrony in good years and growth asynchrony in poorer years reflects adaptive trait optimization and bet hedging, respectively, that could confer an unexpected, but pervasive and stabilizing, impact on marine population productivity in response to large-scale environmental change.publishedVersio

Fundamental questions and applications of sclerochronology: Community-defined research priorities.

Horizon scanning is an increasingly common strategy to identify key research needs and frame future agendas in science. Here, we present the results of the first such exercise for the field of sclerochronology, thereby providing an overview of persistent and emergent research questions that should be addressed by future studies. Through online correspondence following the 5th International Sclerochronology Conference in 2019, participants submitted and rated questions that addressed either knowledge gaps or promising applications of sclerochronology. An initial list of 130 questions was compiled based on contributions of conference attendees and reviewed by expert panels formed during the conference. Herein, we present and discuss the 50 questions rated to be of the highest priority, determined through an online survey distributed to sclerochronology community members post the conference. The final list (1) includes important questions related to mechanisms of biological control over biomineralization, (2) highlights state of the art applications of sclerochronological methods and data for solving long-standing questions in other fields such as climate science and ecology, and (3) emphasizesthe need for common standards for data management and analysis. Although research priorities are continually reassessed, our list provides a roadmap that can be used to motivate research efforts and advance sclerochronology towardnew, and more powerful, applications.N/

Fundamental questions and applications of sclerochronology: Community-defined research priorities

Horizon scanning is an increasingly common strategy to identify key research needs and frame future agendas in science. Here, we present the results of the first such exercise for the field of sclerochronology, thereby providing an overview of persistent and emergent research questions that should be addressed by future studies. Through online correspondence following the 5th International Sclerochronology Conference in 2019, participants submitted and rated questions that addressed either knowledge gaps or promising applications of sclerochronology. An initial list of 130 questions was compiled based on contributions of conference attendees and reviewed by expert panels formed during the conference. Herein, we present and discuss the 50 questions rated to be of the highest priority, determined through an online survey distributed to sclerochronology community members post the conference. The final list: (1) includes important questions related to mechanisms of biological control over biomineralization; (2) highlights state of the art applications of sclerochronological methods and data for solving long-standing questions in other fields such as climate science and ecology: and (3) emphasizes the need for common standards for data management and analysis. Although research priorities are continually reassessed, our list provides a roadmap that can be used to motivate research efforts and advance sclerochronology toward new, and more powerful, applications

Data from: A statistical framework to explore ontogenetic growth variation among individuals and populations: a marine fish example

Growth is a fundamental biological process, driven by a multitude of intrinsic (within-individual) and extrinsic (environmental) factors, that underpins individual fitness and population demographics. Focussing on the comprehensive information stored in aquatic and terrestrial organism hard parts, we develop a series of increasingly complex hierarchical models to explore spatial and temporal sources of growth variation, ranging in resolution from within individuals to across a species. We apply this modelling framework to an extensive data set of otolith increment measurements from tiger flathead (Platycephalus richardsoni), a demersal commercially exploited fish that inhabits the warming waters of south-east Australia. We recreated growth histories (biochronology) up to four decades in length from seven fishing areas spanning this species' range. The dominant pattern in annual growth was an age-dependent, allometric decline that varied amongst individuals, sexes, fishing areas, years and cohorts. We found evidence for among-area differences in growth rate selectivity whereby younger fish at capture were generally faster growers. Temporal growth variation was partitioned into two main sources: extrinsic year-to-year annual fluctuations in environmental conditions and persistent cohort-specific growth differences, reflecting density dependence and/or juvenile experience. Despite low levels of among-individual growth synchrony within areas, we detected a regionally coherent signal of increasing average growth rate through time, a trend related to oceanic warming. At the southerly (poleward) range limit, growth was only weakly related to temperature, but further north in warmer waters this relationship strengthened until at the species' equatorward range limit, growth declined with increasing temperatures. We partitioned these species-wide and area-specific phenotypic responses into within and among-individual components using a reaction norm approach. Individual tiger flathead likely possess sufficient growth plasticity to successfully adapt to warming waters across much of their range, but increased future warming in the north will continue to depress growth, affecting individual fitness and even population persistence. Our modelling framework is directly applicable to other long-term, individual-based, data sets such as those derived from tree rings, corals, and tag-recapture studies, and provides an unprecedented level of resolution into the drivers of growth variation and the ecological and evolutionary implications of environmental and climatic change

environmental data

Environmental covariates used in the analysis of inter-annual growth variation. Year: 1 Jan – 31 Dec. Area: fishing area (see figure 1). Centlat: central latitude of fishing area. Centlong: central longitude of fishing area. Bottomtemp: annual average bottom temperature (oC) for each fishing area based on SynTS and HadISST data sets. See appendix B for methodological details. CPUE: annual average catch per unit effort (CPUE) for each fishing area. See appendix B for methodological details

increment averages

Table of otolith increment measurements averaged by age and year for each fishing area. Area: fishing area. Year: 1 Jan – 31 Dec. Age1- Age18: fish ages

tiger flathead biochronologies

Sheet 1: Estimated annual average growth tiger flathead for each fishing area (figure 4a-g & figure 5). Sheet 2: estimated cohort specific growth for each fishing area (figure 4h-n). Year: 1 Jan – 31 Dec. Area: fishing area (see figure 1). Bottomtemp: annual average bottom temperature (oC) for each fishing area. See appendix B for methodological details. annualgrowth: estimate of annual average growth (in mm) derived from model BLUPs. cohortgrowth: estimate of cohort-specific growth (in mm) derived from model BLUPs. SE: standard error

incrmement measurements

Raw increment measurements and biological data for 4318 (of 6143) fish from fishing areas EBS and ETAS. This subset represents ~74% of increment data used in analyses. The full data set has not been published as it underpins commercially sensitive stock assessments and is held by CSIRO in confidence on behalf of AFMA. Requests for the full data set will be considered on a case by case basis and must be directed to Dr David Smith, Research Director Marine Resources & Industries, CSIRO Oceans & Atmosphere Flagship. David(dot)C(dot)Smith(at)csiro(dot)au. Area: fishing area; FishID: unique identifier for each individual; Sex: M or F; Gear:otter trawl (OT), Danish seine (DS) or unknown; Capyear: capture year; Capmonth: capture month; Floorlength: fish length (cm) rounded down to the nearest whole number; AdjAge: adjusted fish age, based on increment count, otolith edge type, date of capture and the species’ nominal birthday (1 Jan). This is the age-at-capture variable in the paper, and is a fish’s age in whole years; DeciAge: decimal age based on date of capture in relation to birth date; Radius: otolith radius along measuring transect in mm; YOB: year of birth, or year class. Year: calendar year in which a given increment was deposited; Age: age in years corresponding to a given increment; Increment: width of otolith annuli in m