Data for: Multi-generational fitness effects of natural immigration indicate strong heterosis and epistatic breakdown in a wild bird population
Data files
Nov 03, 2023 version files 615.94 KB
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annual_data.csv
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egg_data.csv
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juvenile_data.csv
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lrs.data.csv
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README.md
Abstract
The fitness of immigrants and their descendants produced within recipient populations fundamentally underpins the genetic and population dynamic consequences of immigration. Immigrants can in principle induce contrasting genetic effects on fitness across generations, reflecting multi-faceted additive, dominance, and epistatic effects. Yet, full multi-generational and sex-specific fitness effects of regular immigration have not been quantified within naturally structured systems, precluding inference on underlying genetic architectures and population outcomes. We used four decades of song sparrow (Melospiza melodia) life-history and pedigree data to quantify fitness of natural immigrants, natives, and their F1, F2, and backcross descendants, and test for evidence of non-additive genetic effects. Values of key fitness components (including adult lifetime reproductive success and zygote survival) of F1 offspring of immigrant-native matings substantially exceeded their parent mean, indicating strong heterosis. Meanwhile, F2 offspring of F1-F1 matings had notably low values, indicating surprisingly strong epistatic breakdown. Further, magnitudes of effects varied among fitness components, and differed between females and males descendants. These results demonstrate that strong non-additive genetic effects on fitness can arise within weakly structured and fragmented populations experiencing frequent natural immigration. Such effects will substantially affect the net degree of effective gene flow and resulting local genetic introgression and adaptation.
README: Data for: Multi-generational fitness effects of natural immigration indicate strong heterosis and epistatic breakdown in a wild bird population
This file is associated with the manuscript "Multi-generational fitness effects of natural immigration indicate strong heterosis and epistatic breakdown in a wild bird population" (Submitted to American Naturalist in March, 2023)
Authors: Lisa Dickel, Peter Arcese, Lukas F. Keller, Pirmin Nietlisbach, Debora Goedert, Henrik Jensen, Jane M. Reid
Study population: Song sparrow (Melospiza melodia) of XOX DEL (English name Mandarte island), British Columbia, Canada, (latitude 48.6329, longitude 123.2859, 0.06 km)
All code was written by Lisa Dickel and Jane M. Reid
Data collection was planned and overseen by P. Arcese, and P. Nietlisbach, L. F. Keller and J. M. Reid contributed to fieldwork.
Study summary
Data used come from a long-term study of song sparrows on Mandarte Island.
In these analyses we tested for fitness differences in different groups of immigrants and natives and their descendants.
Data and analysis structure
We analysed 5 different fitness components, namely:
- Lifetime reproductive success (LRS)
- Annual survival
- Annual reproductive success (ARS)
- Juvenile survival
- Zygote survival
These analyses relied on 4 different data sets, comprising:
- Lrs.data.csv (for Lifetime reproductive success, LRS)
- Annual_data.csv (for Annual survival and Annual reproductive success, ARS)
- Juvenile_data.csv (for juvenile survival)
- egg_data (for zygote survival)
There is one script for each of the 5 fitness component analysis, plus one script for overall fitness approximation.
One additional script contains the functions used to process model outputs.
Below, each fitness component is listed with the data set and coding script.
This is a Bayesian analysis, using Monte Carlo sampling. Therefore there is some sampling variance (i.e. Monte Carlo Error) in the results. This typically affects the second, and therefore due to rounding, sometimes the first decimal when re-running these models.
These models take up to 30 minutes to run on a standard comuputer.
The folder for these analyses contains two empty sub-folders to save model outputs and figures when the analyses are run, and the main folder (location of all R scripts) is set as the working directory.
Lifetime reproductive success
R script: LRS_analysis.Rmd
lrs_data: Data used to analyze lifetime reproductive success with the following variables (columns)
- ninecode: Individual identifyer for each bird (factor)
- natalyr2: Hatch year for each individual (integer)
- lrs.use: Count of banded offspring produced over the entire lifetime by an individual (integer)
- f.coef: Inbreeding coefficient pedigree f (numeric)
- sex.fac: Sex of each individual (factor)
- status_mother_father2: Status of both parents before reducing the levels, i.e. the "Other" group found in the "parent_status" column is still split into different sub grups (factor)
- parent_status: Filial group membership of both parents combined, equivalent grouping as in "names" which is created in the scripts (factor)
- pair_ID: Combined ID of both parents of each individual (factor) Annual adult fitness components i.e. annual reproductive success (ARS) and annual adult survival
R scripts: AnnualSurvival_analysis.Rmd
ARS_analysis.Rmd
Data: annual_data.csv Data
With the following variables (columns):
- ninecode: Individual identifyer for each bird (factor)
- syear: Observation year for annual traits (ARS and annual survival)
- natalyr2: Hatch year for each individual (integer)
- f.coef: Inbreeding coefficient pedigree f (numeric)
- ars: Annual reproductive success counted as number of banded offspring (integer)
- sex.fac: Sex of each individual (factor)
- age.cat: Category of young, middle, or old age (factor)
- parent_status: Filial group membership of both parents combined, equivalent grouping as in "names" which is created in the scripts (factor)
- pair_ID: Combined ID of both parents of each individual (factor)
- surv: Annual survival from April to April (binary) Juvenile survival
R script: JuvenileSurvival_analysis.Rmd
Data: juvenile_data.csv
With the following variables (columns)
- ninecode: Individual identifyer for each bird (factor)
- natalyr: Hatch year for each individual (integer)
- f.coef: Inbreeding coefficient pedigree f (numeric)
- surv.band.ad: Survival to banding at ~6 days of age
- nestrec: Nest ID identifying each group of nestlings raised in the same nest
- status_mother_father2: Status of both parents before reducing the levels, i.e. the "Other" group found in the "parent_status" column is still split into different sub grups (factor)
- sex.use: Sex of each individual (factor)
- parent_status: Filial group membership of both parents combined, equivalent grouping as in "names" which is created in the scripts (factor)
- pair_ID: Combined ID of both parents of each individual (factor)Zygote (i.e. egg) survival
R script: ZygoteSurvival_analysis.Rmd
Data: egg_data
- Year: Year of egg laid and observed to hatch (or not) (integer)
- parent_status: Filial group membership of both parents combined, equivalent grouping as in "names" which is created in the scripts (factor)
- nestrec: Nest ID identifying each group of nestlings raised in the same nest (factor)
- band: Count of eggs banded (integer)
- eggs_not_banded: Count of eggs not banded (integer)
- eggs: Total number of eggs counted in the clutch (integer)
- f.coef: Inbreeding coefficient pedigree f (numeric)
- status_offspring_par: Status of both parents before reducing the levels, i.e. the "Other" group found in the "parent_status" column is still split into different sub grups (factor)
- pair_ID: Combined ID of both parents of each individual (factor)
############### R session info ####################################3
R version 4.2.2 Patched (2022-11-10 r83330)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.5 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale:
[1] LC_CTYPE=en_US.UTF-8[2] LC_NUMERIC=C[3] LC_TIME=nb_NO.UTF-8[4] LC_COLLATE=en_US.UTF-8[5] LC_MONETARY=nb_NO.UTF-8[6] LC_MESSAGES=en_US.UTF-8[7] LC_PAPER=nb_NO.UTF-8[8] LC_NAME=C[9] LC_ADDRESS=C[10] LC_TELEPHONE=C[11] LC_MEASUREMENT=nb_NO.UTF-8
[12] LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils[5] datasets methods base
other attached packages:
[1] ggdist_3.2.1 cowplot_1.1.1[3] ggpubr_0.6.0 scales_1.2.1[5] qwraps2_0.5.2 tidybayes_3.0.3
[7] bayesplot_1.10.0 MCMCglmm_2.34[9] ape_5.7 coda_0.19-4[11] Matrix_1.5-3 egg_0.4.5[13] gridExtra_2.3 forcats_1.0.0[15] stringr_1.5.0 dplyr_1.1.0[17] purrr_1.0.1 readr_2.1.4[19] tidyr_1.3.0 tibble_3.1.8[21] ggplot2_3.4.1 tidyverse_1.3.1
loaded via a namespace (and not attached):
[1] nlme_3.1-162 fs_1.6.1[3] bit64_4.0.5 lubridate_1.9.2[5] webshot_0.5.4 httr_1.4.4[7] tensorA_0.36.2 tools_4.2.2[9] backports_1.4.1 utf8_1.2.3[11] R6_2.5.1 DBI_1.1.3[13] colorspace_2.1-0 withr_2.5.0[15] tidyselect_1.2.0 bit_4.0.4[17] compiler_4.2.2 cli_3.6.0[19] rvest_1.0.3 arrayhelpers_1.1-0[21] xml2_1.3.3 labeling_0.4.2[23] posterior_1.3.1 checkmate_2.1.0[25] systemfonts_1.0.4 digest_0.6.31[27] rmarkdown_2.20 svglite_2.1.1[29] pkgconfig_2.0.3 htmltools_0.5.4[31] dbplyr_2.3.1 fastmap_1.1.0[33] rlang_1.0.6 readxl_1.4.2[35] rstudioapi_0.14 farver_2.1.1[37] generics_0.1.2 svUnit_1.0.6[39] jsonlite_1.8.4 vroom_1.6.1[41] car_3.1-1 distributional_0.3.1
[43] magrittr_2.0.3 kableExtra_1.3.4[45] Rcpp_1.0.10 munsell_0.5.0[47] fansi_1.0.4 abind_1.4-5[49] lifecycle_1.0.3 stringi_1.7.12[51] yaml_2.3.7 carData_3.0-5[53] grid_4.2.2 parallel_4.2.2[55] crayon_1.5.2 lattice_0.20-45[57] haven_2.5.2 hms_1.1.2[59] knitr_1.42 pillar_1.8.1[61] boot_1.3-28 cubature_2.0.4.6[63] ggsignif_0.6.4 corpcor_1.6.10[65] reprex_2.0.2 glue_1.6.2[67] evaluate_0.20 modelr_0.1.10[69] vctrs_0.5.2 tzdb_0.3.0[71] cellranger_1.1.0 gtable_0.3.1[73] xfun_0.37 broom_1.0.3[75] rstatix_0.7.2 viridisLite_0.4.1[77] timechange_0.2.0 ellipsis_0.3.2
Methods
These data come from the long-term song sparrow field study on Mandarte Island, BC, Canada (latitude 48.6329°, longitude -123.2859°). The data provided here are sufficient to replicate the analyses presented in the above paper, and are therefore a restricted subset of the full Mandarte dataset.