11 research outputs found

    environmental data

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    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

    tiger flathead biochronologies

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    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

    increment averages

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    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

    incrmement measurements

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    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

    Appendix G. Within vs. among individual supplementary results: result descriptions.

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    Within vs. among individual supplementary results: result descriptions

    Supplement 1. Detailed worked tutorials of analyses performed in this paper, including R code for mixed effects models and example data.

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    <h2>File List</h2><div> <p><a href="S1_tutorial.pdf">S1_tutorial.pdf</a> (MD5: b9ce89e5e69463afbfc055a2943824e6)  --  worked examples for the analysis of growth variation within and among individuals and populations</p> <p><a href="S2_R_code.txt">S2_R_code.txt</a> (MD5: 6028e6cddbdf1473a4eef0faa8bd310a)  --  R code to perform analyses in S1</p> <p><a href="S3_within_zone_example_data.csv">S3_within_zone_example_data.csv</a> (MD5: ab86c1dd8ca7bcd2115f23a14b746bd8)  --  within-zone fish growth data</p> <p><a href="S4_among_zone_example_data.csv">S4_among_zone_example_data.csv</a> (MD5: d601bea4192d1f1c4c513fac34e39306)  --  among-zone fish growth data</p> <p><a href="S5_example_temperature.csv">S5_example_temperature.csv</a> (MD5: f7ae18b64af07ec4b4d7ff94966bbf46)  --  temperature data used in among-zone analyses</p> </div><h2>Description</h2><div> <p>These supplements are designed to assist the reader to implement hierarchical growth models using the statistical software R. The first supplement (S1_tutorial.pdf) provides detailed model descriptions, formulations and analytical steps used in the paper, complementing models presented in Table 3. The second supplement (S2_R_code.txt) provides executable R code for analyses in S1. The third, fourth, and fifth supplements (S3_within_zone_example_data.csv, S4_among_zone_example_data.csv, and S5_example_temperature.csv) are example data sets. </p> <p>Our analyses rely heavily on the R packages lme4, AICcmodavg, effects, lattice and plyr, all available on the comprehensive R archive network (CRAN; cran.r-project.org). </p> <p>Each row in S3_within_zone_example_data.csv and S4_among_zone_example_data.csv represents a measurement of growth in mm (Increment). These observations are associated with an Age (in years) and belong to a fish (FishID) of a given sex (M or F). Each fish has an age-at-capture (ACC, in years). Associated with each Increment is its year of deposition (Year) and the annual bottom temperature (Temp) experienced by the individual at this time. In addition, the S4_among_zone_example_data.csv and S5_example_temperature.csv files contain a variable called zone that assigns each fish to a fictitious fishing area. See Table 2 for additional descriptions of these parameters.</p> </div

    Appendix B. Supplementary methods and results: Estimation of spatially resolved annual bottom temperature from SynTS and the HadISST1 modelled products.

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    Supplementary methods and results: Estimation of spatially resolved annual bottom temperature from SynTS and the HadISST1 modelled products

    Appendix A. Supplementary results: Age-class specific fish length ~ otolith radius relationships.

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    Supplementary results: Age-class specific fish length ~ otolith radius relationships

    Appendix D. Intraclass correlation coefficient (ICC) and R2 equations for mixed models.

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    Intraclass correlation coefficient (ICC) and R2 equations for mixed models

    Appendix C. Supplementary methods and results: Calculation of relative abundance indices using fishery-derived CPUE estimates.

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    Supplementary methods and results: Calculation of relative abundance indices using fishery-derived CPUE estimates
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