This readme.txt file was generated on 2023-12-15 by Thomas Gable Recommended citation for the data: Gable, Thomas D; Johnson-Bice, Sean M; Homkes, Austin T; Bump, Joseph K. (2023). Single visits to active wolf dens do not impact wolf pup recruitment or pack size. Retrieved from the Data Repository for the University of Minnesota. https://doi.org/10.13020/3555-3V87. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset: Single visits to active wolf dens do not impact wolf pup recruitment or pack size 2. Author Information Author Contact: Thomas D Gable (gable079@umn.edu) Name: Thomas D Gable Institution: University of Minnesota Email: gable079@umn.edu ORCID: 0000-0002-0917-8951 Name: Sean M Johnson-Bice Institution: University of Manitoba Email: s.johnsonbice@gmail.com ORCID: 0000-0001-7538-131X Name: Austin T Homkes Institution: University of Minnesota Email:austin.homkes@gmail.com ORCID: NA Name: Joseph K Bump Institution: University of Minnesota Email: bump@umn.edu ORCID: 0000-0002-4369-7990 3. Date published or finalized for release: 2023-12-14 4. Date of data collection (single date, range, approximate date): 2019-2023 5. Geographic location of data collection (where was data collected?): Greater Voyageurs Ecosystem, Minnesota. 6. Information about funding sources that supported the collection of the data: Foremost, we want to thank the National Park Service and their staff for efforts studying wolves in Voyageurs National Park since 1975. We also thank the Minnesota Environment and Natural Resources Trust Fund, the University of Minnesota, Northern Michigan University, the Van Sloun Foundation, Voyageurs Conservancy, Rainy Lake Conservancy, Wolf Conservation Center, International Wolf Center, The 06 Legacy, the National Wolfwatcher Coalition, Big Bad Project, Wildlife Science Center, Arc’teryx, NatureSpy, Vectronic-Aerospace, and 6,067 individual donors who have supported the work of the Voyageurs Wolf Project. 7. Overview of the data (abstract): Dataset for Gable et al. 2023 where the authors used a quasi-experimental approach (reference vs. treatment) to determine whether visiting wolf dens and marking wolf (Canis lupus) pups affects important wolf population metrics. Specifically, Gable et al. examined whether pup recruitment and pack size differed between packs where they visited dens and handled pups (‘disturbed packs’ = treatment group) and those where they did not visit dens (‘undisturbed packs’ = reference group). During 2019-2023, they studied 43 wolf packs and litters, 19 of which were disturbed packs and 24 of which were undisturbed. They found no difference in recruitment or pack size between disturbed and undisturbed wolf packs. However, they did observe substantial annual variation in recruitment and pack size, which indicated that other ecological factors (e.g., prey abundance) were likely responsible for annual changes in recruitment and pack size. Their findings are consistent with several other studies, and together this research indicates that wolf dens can be visited once and wolf pups handled briefly for research purposes without having a measurable effect on recruitment and pack size. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: CC0 1.0 Universal (http://creativecommons.org/publicdomain/zero/1.0/) 2. Links to publications that cite or use the data: Single visits to active wolf dens do not impact wolf pup recruitment or pack size. 2023. Wildlife Biology. 3. Was data derived from another source? No If yes, list source(s): 4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/drum/policies/#terms-of-use --------------------- DATA & FILE OVERVIEW --------------------- File List Filename: PupRecruitmentEstimates_2019-2022.xls Short description: Pup recruitment estimates Filename: PupRecruitmentEstimates_2019-2022_minus5litters.xls Short description: Pup recruitment estimates minus 5 litters Filename: PupRecruitment_Analysis_Revised.R Short description: R code -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: See publication for details on data. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: PupRecruitmentEstimates_2019-2022.csv ----------------------------------------- 1. Number of variables: 7 2. Number of cases/rows: 43 3. Missing data codes: no missing data 4. Variable List • pack: name of wolf pack • year: year examined (e.g., 2020 represented the time period from April 10, 2019 to April 9, 2020) • timespan: clarifying the timespan the data refers to. E.g., 2019-2020 means that data is associated with the time period April 10, 2019 to April 9, 2020. • type: whether the den of that pack in that year was disturbed by researchers visiting the den or not disturbed • recruited: minimum number of wolf pups recruited • max: maximum number of wolf pups recruited. In all but 5 instances, the minimum and maximum estimates of recruitment were the same. • packSize: number of wolves in a pack during winter of that year • comments: any relevant comments about the data in that row. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: PupRecruitmentEstimates_2019-2022_minus5litter.csv ----------------------------------------- • identical dataset to the one described above. However, we removed data on the 5 litters where the minimum and maximum estimates differed. 1. Number of variables: 7 2. Number of cases/rows: 38 R session information: R version 4.0.5 (2021-03-31) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: macOS Big Sur 10.16 Matrix products: default LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base loaded via a namespace (and not attached): [1] pillar_1.8.1 compiler_4.0.5 vipor_0.4.5 remotes_2.3.0 prettyunits_1.1.1 tools_4.0.5 testthat_3.0.2 pkgload_1.2.1 [9] pkgbuild_1.2.0 memoise_2.0.0 lifecycle_1.0.3 tibble_3.1.8 nlme_3.1-152 gtable_0.3.0 lattice_0.20-41 pkgconfig_2.0.3 [17] rlang_1.0.6 DBI_1.1.1 cli_3.5.0 rstudioapi_0.13 yaml_2.2.1 beeswarm_0.4.0 xfun_0.29 fastmap_1.1.0 [25] withr_2.5.0 dplyr_1.0.8 desc_1.3.0 generics_0.1.3 vctrs_0.5.1 fs_1.5.0 devtools_2.4.1 rprojroot_2.0.2 [33] grid_4.0.5 tidyselect_1.2.0 glue_1.6.2 R6_2.5.0 processx_3.5.2 fansi_0.4.2 ggbeeswarm_0.7.1 sessioninfo_1.1.1 [41] purrr_0.3.4 ggplot2_3.4.0 callr_3.7.0 magrittr_2.0.1 usethis_2.0.1 ps_1.6.0 scales_1.2.1 ellipsis_0.3.2 [49] assertthat_0.2.1 colorspace_2.0-1 utf8_1.2.1 tinytex_0.31 munsell_0.5.0 cachem_1.0.5 crayon_1.4.1