DOI: 10.5061/dryad.rbnzs7hhx
title: Code and data for: Shining a light on elusive lynx: density estimation of three Eurasian lynx populations in Ukraine and Belarus

description: The Eurasian lynx is a large carnivore widely distributed across Eurasia.
 However, our understanding of population status is heterogeneous across
 their range, with some populations isolated that are at risk of reduced
 genetic variation and a complete lack of information about others. In many
 European countries, Eurasian lynx are monitored through demographic
 studies crucial for their conservation and management. Even so, there are
 only rough and fragmented population assessments from Ukraine and Belarus,
 despite strict protection in both countries and their importance for lynx
 connectivity across Europe. We monitored lynx from October 2020 to March
 2021 and used camera-trapping in combination with spatial
 capture-recapture (SCR) methods in a Bayesian Framework to provide the
 first SCR density estimation of three lynx populations across Ukraine and
 Belarus, including the Ukrainian Chornobyl Exclusion Zone, Southern
 Belarus, and the Ukrainian Carpathians. Our density estimates varied
 within our study areas ranging from 0.45 to 1.54 individuals/100
 km2. This work provides a substantial scientific component to the
 overall understanding of lynx conservation for a region where only broad
 information is available and opens the doors for further large-scale
 monitoring and trend assessments. The crucial information we provide can
 greatly enhance the range-wide assessments of the status of this protected
 species. We also discuss the implications for Eurasian lynx conservation,
 despite the geopolitical realities impacting species monitoring in the
 region. Our work serves as a baseline, not only for future conservation
 interventions but also to evaluate the effects of disturbance and threats
 to these protected populations.
description: Spatial capture-recapture (SCR) density estimation of Eurasian
 lynx from camera traps in three study areas in Europe (Ukrainian Chornobyl
 Exclusion Zone, Ukraine; Skolivski Beskydy National Park, Ukraine;
 Belarusian Pripyat-Polesia, Belarus). Camera traps were set up in a paired
 design to photograph the unique coat patterns of individuals during the
 winter period 2020-2021. Individual animals were then
 identified and capture histories were processed by Bayesian SCR models.
 Abundance and density were estimated for the state space area and the
 minimum convex polygon of camera traps.
description: Details for the R code are provided in the README file.
 R data software is required to re-run the analysis.
 <strong>Code included for the
 analysis:</strong> 1) Code for density estimation
 (Code for density estimation.R) which runs the analysis in the R software
 and follow the comments (#) guiding you through the code. 
 <strong>Files included for each study
 area:</strong> 1) capture file of Eurasian lynx
 events (edf.csv) 2) a list object for that study area
 (e.g. BPPlist.RData) that contains the number of individuals, occasions,
 and traps used to create the capture history object ("capthist")
 used by the <em>secr </em>package 3) two
 camera trap information files (tdf.csv and traps.txt), the .txt version of
 the file in required for the <em>secr </em>package in R to
 access the information on the camera traps to create the capture
 history <strong>Sharing/access
 Information:</strong> This code and data was
 generated through the hard work of park rangers and scientific staff in
 Ukraine and Belarus, and as part of student-led projects. Accreditation of
 the authors and data owners is greatly appreciated.
description: "Shining a light on elusive lynx: density estimation of three
 Eurasian lynx populations in Ukraine and Belarus" --- Stefano
 Palmero†\*, Adam F. Smith\*, Svitlana Kudrenko, Martin Gahbauer, Dominik
 Dachs, Kirsten Weingarth-Dachs, Irina Kashpei, Dmitry Shamovich, Denys
 Vyshnevskiy, Oleksandr Borsuk, Kateryna Korepanova, Andriy-Taras Bashta,
 Rostyslav Zhuravchak, Viktar Fenchuk, Marco Heurich ## Description of the
 Data and file structure **Experimental Context:** Spatial
 capture-recapture (SCR) density estimation of Eurasian lynx from camera
 traps in three study areas in Europe (Ukrainian Chornobyl Exclusion Zone,
 Ukraine; Skolivski Beskydy National Park, Ukraine; Belarusian
 Pripyat-Polesia, Belarus). Camera traps were set up in a paired design to
 photograph the unique coat patterns of individuals during the winter
 period 2020-2021. Individual animals were then identified and capture
 histories were processed by Bayesian SCR models. Abundance and density
 were estimated for the state space area and the minimum convex polygon of
 camera traps. **Abbreviations and variables:** SCR: Spatial capture
 recapture MCP: Minimum convex polygon UCEZ: Ukrainian Chornobyl Exclusion
 Zone SBNP: Skolivski Beskydy National Park BPP: Belarusian Pripyat-Polesia
 edf: Events data frame tdf: Traps data frame CH: Capture history
 ("capthist" object) nind: Number of individuals Yaug: Augmented
 capture history sst: Prior values for activity centers inits: Priors for
 the model post: Posterior distributions n.iter: Number of iterations
 n.burnin: Number of burn-ins n.chain: Number of chains J: Number of camera
 traps M: Number of augmented individuals K: Deployment information X:
 Coordinates of the camera traps MCMC: Markov Chain Monte Carlo mtx:
 Matrices kf: Spatial coordinates of MCP ACs: Activity centers <br>
 Each folder for the three study areas contains a capture file (edf.csv),
 two trap files (tdf.csv and traps.txt) and a list object (XYZlist.RData)
 for each study area used for the analysis. To run the analysis, open the
 file "Code for density estimation.R" in the R software and
 follow the comments (#) guiding you through the code. ## Sharing/access
 Information This code and data was generated through the hard work of park
 rangers and scientific staff in Ukraine and Belarus, and as part of
 student-led projects. Accreditation of the authors and data owners is
 greatly appreciated.