Dataset DOI: 10.5061/dryad.d2547d8ht

Description of the data and file structure

These data were gathered by the Alaska Department of Fish and Game (ADF&G) as part of their hunter reporting and sealing requirements as well as non-harvest mortality data from 1995-2021. These data contain records for both black and brown bears in Southeast Alaska, ADF&G Region 1. Records include relevant demographic data such as age, sex, and species.

Files and variables

Spatial Analysis

Files: The data and shapefile for this analysis is legally protected from public reporting at this spatial scale. The code has been included for anyone hoping to apply this analysis to their own data. However, for inquiries about the the original data used in the analysis contact Anthony Crupi (anthony.crupi@alaska.gov) with the Alaska Department of Fish and Game.

Age-at-harvest State-space Analysis

Files: StateSpace_[species][GMU][sex]_95-21.csv

Description: These files contain the empirical number of individuals harvested in each age class in each year of the study. They are species-specific, brown bear (uarct) or black bear (uamer), GMU-specific (1C or 1D), and sex-specific (male or female). The files with "total" in the name are the total counts of males and females in a given year regardless of age-class. The rows are the study year while the columns are the age-classes 1-10.

File: StateSpace_[Species]_[GMU]_State_Space_Results.csv

Description: These files contain the results of the age-at-harvest state-space model. The variable is in the variable column. The columns c1, c2, and c3 represent the year, sex, and age-class values. If there are values in each of these columns in the same row, they are year, sex, and age-class. If there are two values they are sex and age-class. If there is one value it is year. No values in these columns indicate that the varaible was not year, sex, or age-specific. For these files the year value starts at 1 and counts up rather than the actual calendar year.

Variables

• Var: The variable
• c1: year or sex
• c2: sex or age-class
• c3: age-class
• Mean: The mean of the variable estimates across simulations.
• SD: The standard deviation of the variable estimates across simulations.
• LCL95: The lower 95 percent confidence interval for the variable estimates across simulations.
• UCL95: The upper 95 percent confidence interval for the variable estimates across simulations.

Harvest Effort Analysis

File: Harvest_Effort_[Species]_GMU1CD.csv

Description: These files contain the harvest effort data for both GMUs.

Variables

• Year: 1995-2021 for brown bears and 2009-2021 for black bears
• Unsuccessful_[GMU]: Number of unsuccessful hunters in the GMU
• Successful_[GMU]: Number of successful hunters in the GMU
• Total_[GMU]: Total number or reported hunts in the GMU
• Percent_Success_[GMU]: The successful hunts divided by the total
• Avg_Effort_Success_[GMU]: The average number of days for a successful hunt

File: Harvest_Effort_[Species]_mort.csv

Description: These files contain the mortality data for each of the records. Each row is a record.

Variables

• regyear: 1995-2021
• season: Spring (S) or Fall (F)
• species: Brown bear (B) or Black bear (L)
• gmu: 1C or 1D
• Mortality: Harvest or Non-Harvest

Code/software

Spatial Analysis

File: Spatial_Analysis.R

The analyses was performed using R version 4.4.2 in the RStudio environment (version 2024.12.0+467) with loaded packages: sf 1.0-19, terra 1.8-5, spatstat 3.3-2, spdep 1.3-11, RColorBrewer 1.1-3, ggplot2 3.5.1, ggmap4.0.0, ggpubr 0.6.3, and dplyr 1.1.4.

Description: Geographic Data- The R code first reads in the shapefile and projects it in the section.

Moran's I analysis for centroids- In this section we found the centroids for each minor subunit and then calculated Moran's I for the subunit areas. The centroids were used in the following section.

Weighted sliding average centroid- Using the centroids from the previous section we created a function that calculates the average latitude and longitude for all of the records in the five-year windows and output the centroid locations for plotting in ArcGIS.

Species data- The code in this section filters and prepares the species data for input into the cross-k analysis by grouping by species and years. The count_and_merge funtion combines the species data with the minor subunits as a count per minor subunit.

Data Cross K- The functions in this section took the filtered species data and performed the simulations for the empirical hunt counts per year-group at the minor subunit level, running the cross-k analysis on each.

Random Cross K- The functions in this section take the empirical number of harvesets and simulate them within the entire study area to create a random process with which to compare the empirical simulations to.

Plotting Cross K- We used this code to combine the empirical and random simulation data making the empirical simulations specific colors and the simulations gray like the published figures.

Age-at-harvest State-space Analysis

These files were adapted directly from:

Allen, M. L., A. S. Norton, G. Stauffer, N. M. Roberts, Y. Luo, Q. Li, D. MacFarland, and T. R. Van Deelen. 2018. A Bayesian State-Space Model Using Age-at-Harvest Data for Estimating the Population of Black Bears (Ursus americanus) in Wisconsin. Scientific Reports 8 (1): 12440.

The analyses was performed using R version 4.4.2 in the RStudio environment (version 2024.12.0+467) with loaded packages: abind 1.4-8, R2jags 0.8-9, rjags 4-17, gdata 3.0.1, ggplot2 3.5.1, tidyr 1.3.1, and dplyr 1.1.4. Input and results files contain the StateSpace_ prefix.

File: StateSpace_[Species]_JAGS_Model.R

Description: These files create the JAGS functions for the model and calculate summary statistics.

File: StateSpace_Figure_Functions.R

Description: This file contains the code to pull variables out of the output files and create figures for each of them.

File: StateSpace_[Species]_StateSpace_Inputs_and_Parameters.R

Description: The code in these files read in the data, specify the parameters, and then use the functions in the JAGS_Model.R files as well as the Figure_Functions.R file to both run the model.

File: State_Space_Pop_estimation.R

Description: We used this code to create the population estimation figures and perform the qualitative estimate of the of the population trends.

Harvest Effort Analysis

The analyses was performed using R version 4.4.2 in the RStudio environment (version 2024.12.0+467) with loaded packages: ggplot2 3.5.1, tidyverse 2.0.0, and dplyr 1.1.4. Input files contain the Harvest_Effort prefix.

File: Harvest_Effort.R

Description: We used this code to run the statistical analyses on the harvest data as well as make the figures for the harvest effort analyses.

Access information

Data was derived from the following sources:

• Alaska Department of Fish and Game harvest records