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Lingering legacies: Past growth and parental experience influence somatic growth in a fish population

Cite this dataset

Almeida, Leah; Ludsin, Stuart; Faust, Matthew; Marschall, Elizabeth (2024). Lingering legacies: Past growth and parental experience influence somatic growth in a fish population [Dataset]. Dryad. https://doi.org/10.5061/dryad.34tmpg4t6

Abstract

Body size and growth rate can influence individual and population success by mediating fitness. Understanding the factors that influence growth can be difficult to disentangle, however, because growth can be shaped by environmental conditions recently experienced, as well as legacy effects from conditions experienced earlier in life and by parents (via parental effects). To improve understanding of growth among annual cohorts (1982-2015) of Lake Erie Walleye (Sander vitreus), a species with life history and growth characteristics similar to many other long-lived, iteroparous fishes, we determined the role of the following hypothesized factors: H1) recent environmental conditions; H2) traits and experiences of the cohort, including growth, in the previous year; H3) early-life cohort density; H4) early-life body size; and H5) parental composition and environment. We evaluated the relative importance of these hypothesized factors using piecewise structural equation modeling in an information-theoretic framework. Our results indicated that cohort-specific growth of Lake Erie Walleye was most strongly influenced by traits (growth) and experiences of the cohort during the previous year (H2) and parental composition and environment (H5). The observed negative relationship with growth during the previous year may indicate that Walleye exhibits compensatory growth. The relationships with parental sizes and environments may mean that parental contributions to offspring affect cohorts into adulthood, with serious implications for the effects of climate change. Warm winters appear to negatively influence offspring growth performance for many years. Legacy effects had a stronger influence on cohort growth than recent environmental conditions, providing a new understanding of how somatic growth is regulated in Lake Erie’s Walleye population. Specifically, the parental composition and environment appear important via epigenetic and/or egg-provisioning legacies, with carryover effects modifying growth over the years. Ultimately, our findings demonstrate that understanding recent growth in animal populations similar to Lake Erie Walleye may require knowledge of past conditions, including those experienced by parents.

README: Lingering legacies: Past growth and parental experience influence somatic growth in a fish population

https://doi.org/10.5061/dryad.34tmpg4t6

The dataset contains an R script and data file used to produce figures and all of the piecewise structured equation models (SEM).

Description of the data and file structure

The R script file contains the code used to run the piecewise SEM analyses as well as to create related figures. The script contains additional information about analyses in comments throughout.

All of the data needed to conduct the analyses (predictor and response variables for piecewise SEMs) are compiled into the CSV file. Details about variable names are listed below. Within the dataset, each row represents a male or female annual cohort at ages 3, 4, or 5. Each cohort is represented by up to 6 rows in JAE_Almeida_et_al_compiled_data.csv - each sex (female and male) within the ages 3, 4, and 5.

Variables included in Almeida_et_al_compiled_data.csv

  • Cohort: The numeric year when the cohort within that row was born. Used as a random effect in component models.

  • Sex: A numeric indicator of the sex represented (1 = Female, 2 = Male). Used as a predictor variable for prop.mature (exogenous).

  • Age: The numeric age represented in years (ages 3 - 5 are included).

  • Residual.growth.lastyr: The residuals for the relationship between length and growth that also includes sex and age for the previous year. Used as a predictor variable in the analyses as well as a response variable in some component models (endogenous).

  • Year: The year that the cohort was sampled at that age. Used as a random effect in component models.

  • median.length: The median length of the cohort at that age for that sex (mm). Not directly used in analyses.

  • Residual.growth: The residuals for the relationship between length and growth that also includes sex and age. Only used as a response variable (endogenous).

  • CDD: The cumulative degree days over the past growing year (Oct-Sept). Used as a predictor variable (exogenous).

  • Adult.Abund: The estimated annual abundance of age 2 and older Walleye. Used to calculate Per.capta.prey and evaluated as a predictor variable (exogenous).

  • AvgPreyPerYear: Estimated annual prey fish density (catch-per-minute of trawling). Used to calculate Per.capta.prey and evaluated as a predictor variable (exogenous).

  • Per.capta.prey: Our index of prey incorporates prey densities across a range of Walleye prey fish types as well as an estimate of competition in the adult abundance. Used as a predictor variable (exogenous).

  • Age0.length: The median length (mm) of the cohort in August when they were Age-0. Used as a predictor variable (exogenous).

  • Age0.CPHA: Density (CPHA) of the cohort in August when they were Age-0. Used as a predictor variable (exogenous).

  • Percent.Ice: The percent of ice cover on Lake Erie during February and March of the year the cohort was born (i.e., before their hatching). Used as a predictor variable (exogenous).

  • prop.mature: The proportion of the cohort that was mature at that age for that sex. Used as a predictor variable in the analyses as well as a response variable in some component models (endogenous).

  • prop.mature.lastyr: The proportion of the cohort that was mature at that age for that sex in the previous year. Used as a predictor variable in the analyses (exogenous).

  • FMort: The estimated fishing mortality for that age in that year. Used as a predictor variable in the analyses (exogenous).

  • FMort.lastyr: The estimated fishing mortality for that age in the previous year. Used as a predictor variable in the analyses (exogenous).

  • Prop.sm: The proportion of mature adults during the year the cohort hatched that were smaller than the 1st quartile of lengths of mature fish of their respective sex for all years. Evaluated as a predictor variable (exogenous).

  • Prop.lg: The proportion of mature adults during the year the cohort hatched that were larger than the 3rd quartile of lengths of mature fish of their respective sex for all years. Evaluated as a predictor variable (exogenous).

  • Prop.sm.fm: The proportion of mature females during the year the cohort hatched that were smaller than the 1st quartile of lengths of mature females for all years. Evaluated as a predictor variable (exogenous).

  • Prop.lg.fm: The proportion of mature females during the year the cohort hatched that were larger than the 3rd quartile of lengths of mature females for all years. Used as a predictor variable (exogenous).

  • Prop.sm.m: The proportion of mature males during the year the cohort hatched that were smaller than the 1st quartile of lengths of mature males for all years. Used as a predictor variable (exogenous).

  • Prop.lg.m: The proportion of mature males during the year the cohort hatched that were larger than the 3rd quartile of lengths of mature males for all years. Evaluated as a predictor variable (exogenous).

Methods

Our evaluation of young adult growth was based on data collected annually during fall (i.e., September-November) surveys by the Ohio Department of Natural Resources-Division of Wildlife (ODNR-DOW). We tested different combinations of hypothesized ways in which past and recent environments can affect cohort-based growth in Walleye using model selection of these data within piecewise structured equation models. See the manuscript and appendix for further details.

Funding

United States Fish and Wildlife Service, Award: GRT00054578, F-69-P, Fish Management in Ohio

National Science Foundation, Award: 1333468, Graduate Research Fellowship

The Ohio State University

American Fisheries Society

International Association for Great Lakes Research