Returning neighbors: Eastern wild turkey (Meleagris gallopavo silvestris) occupancy in an urban landscape
Data files
Aug 19, 2025 version files 1.03 MB
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JWM_TurkeyAutOccu_2025.zip
1.03 MB
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README.md
3 KB
Abstract
Once extirpated from most of its range due to overharvest and habitat loss in the early 1900s, the eastern wild turkey (Meleagris gallopavo silvestris) has been recolonizing landscapes in the eastern United States due to restoration and reintroduction efforts. Wild turkey populations have rebounded in the last 50 years so much so that wild turkey is seen as one of the most successful conservation efforts in the US. More recently, wild turkeys have begun to expand into cities across the US. While this can be seen as a successful return of a once extirpated species, it has also given rise to human-wildlife conflict in highly populated areas. Given the ecological differences between urban and rural ecosystems, it is important for conservation and management efforts to understand how wild turkey use urban landscapes. We used cameras deployed at 75 long-term study sites across the Washington, D.C. region to assess occupancy and habitat use of urban wild turkey at multiple scales. We found that wild turkey occupancy was positively correlated with the distance to roadways and the proportion of natural vegetation cover within 1 km, while occupancy was negatively correlated with the distance to the nearest water source and mean canopy height within 4 km. Our findings add to the understanding of how wild turkeys are returning and using novel urban ecosystems and can inform future management needs, contribute to conservation initiatives, and help reduce negative human-wildlife interactions.
Returning Neighbors: Eastern Wild Turkey (Meleagris gallopavo silvestris) Occupancy in an Urban Landscape
Authors
Merri Collins, Katherine Edwards, Scott Bates, and Travis Gallo
File Descriptions
Scripts:
Scripts/TurkeyMultiOccu_package_load.R - run this script to download and
load all scripts needed in this analysis
Scripts/2025-07-21_landscape_variables.R - this script will calculate and
scale all covariates used in the autologistic occupancy model. Note: there
are many publically GIS layers needed in this analysis. We have not included these
data, but have included relevant urls (active at the creation of this repository)
within this script.
Scripts/2025-07-21_fit_JAGS.R - this script will format turkey observations
into detection histories, calculate an observation covariate, fit and run
diagnostics on the autologistic occupancy JAGS model.
Scripts/2025-07-21_summarize_plot.R - creates Figure 2
Scripts/2025-07-21_summarize_results.R - calculates summary statistics of
observation data and odds ratios, variable inclusion probabilities, and Tables 2
and 3 from model results.
Scripts/2025-07-21_lasso_model_jags.R - JAGS model script for multi-season
autologistic occupancy model
Scripts/2025-07-21_reduced_lasso_model_jags.R - JAGS model script for
multi-season autologistic occupancy model using only the 11 variables that remained
after the variable selection procedure
Directories and Data Files:
Data/TurkeyOccupancyReport.csv - Detection data of wild turkey in Washington, D.C.
This data is read into Scripts/2025-07-21_landscape_variables.R and
Scripts/2025-07-21_fit_JAGS.R.
This data has 51 columns
| Column header | Data type | Description | |
|---|---|---|---|
| Species | character | The name of the species | |
| Season | character | The season for which observation was collected | |
| Site | character | The name of the camera location | |
| Latitude | numeric | Latitude coordinates (WGS84) | |
| Longitude | numeric | Longitude coordinates (WGS84) | |
| Day_1-Day_45 | numeric | Detection (1 detected or 0 not detected) |
GIS/ - empty directory to save GIS layers. To line up with the current working
directory, this folder must exist and GIS layers must be saved in this directory.
See scripts for sub-directory labels.
Results/ - empty directory to save results and figure to
Note: All of these files must be within your working directory for
the analysis to work. Analyses were done in parallel. Therefore,
you will need to adjust the settings accordingly.
