DOI: 10.5061/dryad.fj6q57417
title: Data for: Multi-generational fitness effects of natural immigration indicate strong heterosis and epistatic breakdown in a wild bird population

description: 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.
description: 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.
description: # 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
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 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
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