This readme.txt file was generated on 2025-12-26 by Andrea Hynes Recommended citation for the data: Hynes, A; Gable, Thomas D; Homkes, Austin T; Bump, Joseph K; Bruggink, John G. (2026). Dataset supporting Pack and Population Level Estimates of Wolf Pup Survival in the Greater Voyageurs Ecosystem. Retrieved from the Data Repository for the University of Minnesota. https://doi.org/10.13020/3p7c-mp48. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset: Dataset supporting Pack and population level estimates of wolf pup survival in the Greater Voyageurs Ecosystem 2. Author Information Author Contact: Andrea Hynes (ahynes073@gmail.com) Name: Andrea Hynes Institution: Northern Michigan University Email: ahynes073@gmail.com ORCID: 0009-0003-8851-3061 Name: Thomas D Gable Institution: University of Minnesota Email: gable079@umn.edu ORCID: 0000-0002-0917-8951 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 Name: John G Bruggink Institution: Northern Michigan University Email: jbruggin@nmu.edu ORCID: 0009-0002-3536-9791 3. Date published or finalized for release: 2026 4. Date of data collection (single date, range, approximate date): 2019-2025 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, Rainy Lake Conservancy, the Van Sloun Foundation, Manitou Fund, Voyageurs Conservancy, International Wolf Center, the National Wolfwatcher Coalition, Wildlife Science Center, Arc’teryx, NatureSpy, Vectronic-Aerospace, and >8,700 individual donors who have supported the work of the Voyageurs Wolf Project. 7. Overview of the data (abstract): Dataset for Hynes et al. 2026 where the authors used a combination of pup counts at dens and remote camera observations to estimate annual survival and recruitment of wolf pups (Canis lupus) in the Greater Voyageurs Ecosystem, Minnesota, USA, from 2019 to 2025. They estimated recruitment for 33 packs over 92 pack-years and survival for 23 litters from 13 packs. Mean annual pup recruitment was 1.27 pups per pack, and mean annual pup survival was 0.29. They observed that annual wolf pup recruitment and survival rates varied substantially among years and packs, which was likely a result of differences in food availability and the ability of breeding animals to acquire sufficient prey to provision dependent pups. They found that pup survival was negatively related to litter size. Although most (71%) wolf pups born during the study did not survive their first biological year, the population remained relatively stable, suggesting that recruitment rates were sufficient to sustain the high-density wolf population over time. These data underscore the potential of integrative monitoring approaches to advance the understanding of wolf reproductive ecology. -------------------------- 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: Pack and population level estimates of wolf pup survival in the Greater Voyageurs Ecosystem. 2026. 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: PupSurvivalandRecruitmentEstimates_2019to2025.xls Short description: Pup survival and recruitment estimates Filename: LitterSizeRegressionData.csv Short description: Litter size and recruitment data Filename: Pup Survival&Recruitment Analysis.txt 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: PupSurvivalandRecruitmentEstimates_2019to2025.csv ----------------------------------------- 1. Number of variables: 5 2. Number of cases/rows: 93 3. Missing data codes: no missing data 4. Variable List • Pack: name of wolf pack • Litter_Size: number of pups in the litter • Recruitment: minimum number of wolf pups recruited • Survival: minimum number of wolf pups that survived • Year: biological year examined ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: LitterSizeRegressionData.csv ----------------------------------------- 1. Number of variables: 2 2. Number of cases/rows: 26 3. Missing data codes: no missing data 4. Variable List • Littersize: number of pups in the litter • Pups_Recruited: minimum number of wolf pups recruited Information for R code: R version 4.4.1 (2024-06-14 ucrt) Platform: x86_64-w64-mingw32/x64 Running under: Windows 11 x64 (build 26100) Matrix products: default locale: [1] LC_COLLATE=English_United States.utf8 [2] LC_CTYPE=English_United States.utf8 [3] LC_MONETARY=English_United States.utf8 [4] LC_NUMERIC=C [5] LC_TIME=English_United States.utf8 time zone: America/Denver tzcode source: internal attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] tidytext_0.4.2 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 [5] dplyr_1.1.4 purrr_1.0.2 readr_2.1.5 tidyr_1.3.1 [9] tibble_3.2.1 tidyverse_2.0.0 ggplot2_4.0.1 Rmisc_1.5.1 [13] plyr_1.8.9 lattice_0.22-6 loaded via a namespace (and not attached): [1] Matrix_1.7-0 bit_4.5.0 gtable_0.3.6 [4] janeaustenr_1.0.0 compiler_4.4.1 crayon_1.5.3 [7] tidyselect_1.2.1 Rcpp_1.0.13 parallel_4.4.1 [10] systemfonts_1.1.0 scales_1.4.0 textshaping_0.4.0 [13] R6_2.5.1 SnowballC_0.7.1 labeling_0.4.3 [16] generics_0.1.3 pillar_1.9.0 RColorBrewer_1.1-3 [19] tzdb_0.4.0 tokenizers_0.3.0 rlang_1.1.4 [22] utf8_1.2.4 stringi_1.8.4 S7_0.2.1 [25] bit64_4.5.2 timechange_0.3.0 cli_3.6.3 [28] withr_3.0.1 magrittr_2.0.3 grid_4.4.1 [31] vroom_1.6.5 rstudioapi_0.16.0 hms_1.1.3 [34] lifecycle_1.0.4 vctrs_0.6.5 glue_1.8.0 [37] farver_2.1.2 ragg_1.3.3 fansi_1.0.6 [40] tools_4.4.1 pkgconfig_2.0.3