DOI: 10.5061/dryad.qfttdz0qn
title: Data for: Wolves in the borderland – changes in population and wolf diet in Romincka Forest, along the Polish-Russian-Lithuanian state borders

description: We assessed changes in the population size, density, and diet composition
 of wolves inhabiting the Romincka Forest (RF), an area of 480 km2 situated
 along the state border between Poland, Russian Federation (Kaliningrad),
 and Lithuania. We compared the results of our research in 2020-2021 with
 data from other projects conducted since 1999. We found that both packs
 living in RF had transboundary territories. The number of packs was stable
 over 21 years, the average pack size almost doubled (from 4-4.5 to 7.5-8
 wolves per pack), the total wolf number increased 1.8 times, reaching
 15-16 wolves, the density increased 1.5 times up to 3.1-3.3 wolves/100 km2
 in winter 2020/2021. Our analyses of 165 scats revealed that beavers
 Castor fiber made up 45.6% of food biomass in the wolf diet in 2020, which
 was 3.4 times more than in 1999-2004 (n=84 scats, 13.4%). Wild ungulates
 constituted 44.8% of the wolf food biomass in 2020, 1.6 times less than
 before (71.1%). In our study, among wild ungulates, wolves primarily
 consumed roe deer Capreolus capreolus (22.6% of food biomass),
 then wild boars Sus scrofa (13.7%) and red deer Cervus elaphus (5.0%),
 while moose Alces alces was eaten rarely (0.4%). We also recorded domestic
 dogs (4.9% of food biomass) and cattle (3.1%). The food niche breadth was
 wider (B=2.31) than in the earlier period (B=1.84), and the Pianka index
 showed moderate similarity in food composition between both periods
 (α=0.816). In November 2022, due to the migration crisis, a 199 km
 impermeable fence along the state border with Kaliningrad was erected,
 which blocked access to 48% of the RF area that was regularly used by the
 resident wolf packs. This may cause wolf numbers to decrease and isolation
 from the central part of the Baltic wolf population to which they belong,
 according to our DNA analyses.
description: <strong>Tracking</strong>. We tracked wolves by foot
 or by car, using the regular and dense network of dirt roads, routes, and
 other linear structures, and the plowed strip of soil along the
 borderline, across the whole Polish portion of RF, that wolves used for
 traveling and scent-marking. In snow-free seasons, we found tracks on mud
 or sand and followed them as far as were visible, usually at distances of
 100-300 m, while in winter, snow cover allowed us to follow wolf tracks up
 to 10 km. Species identification was based on the shape and size of tracks
 and evidence of animal behavior during scent-marking. Additionally, track
 identification was verified with genetic analysis of scat and urine
 samples collected during tracking. In winter, we estimated the number of
 wolves in the tracked group on snow by counting the number of individual
 trails when wolves split, which usually happened on road junctions and was
 associated with intense scent-marking. We measured the length of the
 footprint of the front paw with claws and the distance between the heels
 of subsequent footprints in the track to distinguish between adults and
 pups. To record adult wolves and pups, we used camera traps Browning Spec
 Ops Advantage and Browning Spec Ops Edge, USA, which were set up to
 register 30s-long videos with a 1s delay between recordings. Altogether,
 we set up camera traps in 28 locations, mostly on roads and road
 junctions, which were defined based on evidence of wolf presence (tracks
 and scent marks) found during tracking and wolf response to our howl
 stimulation. Cameras worked for 112 camera days.
 <strong>Genotyping</strong>. To distinguish between
 wolf family groups in RF, we applied genetic fingerprinting. Because our
 main goal was to genotype and distinguish between parental pairs and their
 relatives, which scent-mark the pack territory mostly on roads and
 junctions, we were looking for non-invasive samples (fresh scats and urine
 from snow) during wolf tracking on forest roads and trails within the
 whole forest tract. We put 3-4 cm long fragments of fresh wolf scats into
 plastic tubes (30 ml) fixed with 96% ethanol and stored at +4°C, while
 urine samples collected from snow, we mixed with two volumes of 96%
 ethanol and sodium acetate (100 mM final concentration) and kept at −20°C.
 All tubes with samples were described with date, GPS coordinates, and,
 whenever possible, the presumed status (breeder, subadult, male, or
 female) based on the behaviour of the tracked wolf. DNA isolation was
 performed in a separate cleanroom to avoid contamination. DNA from scats
 was isolated either with QIAamp DNA Stool Mini Kit (Qiagen) or Exgene™
 Stool DNA Mini kit (GeneAll Biotechnology), while precipitated urine
 samples were isolated with Exgene™ Tissue SV kit (GeneAll Biotechnology).
 Genetic fingerprinting was based on 13 polymorphic microsatellite loci:
 FH2001, FH2010, FH2017, FH2054, FH2087L, FH2088, FH2096, FH2137, FH2140,
 FH2161, vWF, PEZ17 and CPH5. Additionally, DBX intron 6 and DBY intron 7
 were used as sex markers. Details of laboratory analyses are described in
 the paper of Szewczyk et al. (2019. Sci. Rep.). Furthermore, we assigned
 the local wolves to the source population, comparing microsatellite
 genotypes from the study area with reference genotypes from the Central
 and Eastern European wolf populations (Baltic, Carpathian, and Central
 European Lowland). From each population, we selected 30 genotypes (from
 the dataset from Szewczyk et al. 2019, Sci. Rep.) and processed them
 together with genotypes from RF using STRUCTURE 2.3.4 software. Analyses
 were performed for a number of clusters (K) ranging from 1 to 10, with 10
 iterations per K. The Evanno method applied in STRUCTURE HARVESTER was
 used to infer the most likely number of clusters.
 <strong>Wolf diet. </strong>The diet composition was
 assessed by analyzing the content of wolf scats. Scats were collected
 opportunistically year-round on the dense grid of forest roads and other
 linear structures spanning the whole Polish RF and during long-distance
 tracking on snow. Each scat was placed in a paper envelope and described
 with date and GPS coordinates. Then scats were dried for a minimum of five
 days at 70°C in a laboratory drier to kill parasites. Socked scats were
 washed through a 0.5 mm-mesh sieve and then dried. The species eaten by
 wolves were identified based on hair, bones, teeth, and hooves found in
 scats using hair or osteological keys and reference material collected
 during earlier studies on the wolf foraging ecology. In cases where the
 identification of food items in the scat based on the hair and bones was
 inconclusive (n=19 samples), we determined the species based on the mtDNA
 isolated from the hair from each sample. We extracted DNA using Exgene™
 Genomic DNA micro kit (GeneAll Biotechnology) with modification of
 manufacturer protocol with the elongated time of first incubation (until
 complete dissolution, from 2.5 hours to overnight incubation), with the
 result of 50 ul of DNA extract. The PCR solution, reaction conditions, and
 further analyses were conducted as described in Szewczyk et al. (2019,
 Sci. Rep.) with primers L15995 (Taberlet and Bouvet 1994) and H16498
 (Fumagalli et al. 1996) proposed by Pun et al. (2009) for species
 identification from mixed samples.
description: # Dataset for paper: Wolves in the borderland – changes in population and
 wolf diet in Romincka Forest, along the Polish-Russian-Lithuanian state
 borders The dataset
 provides data to assess the wolf numbers and diet in the Romincka Forest
 in northern Poland. ## Description of the data and file structure Data are
 grouped into three files: **Nowak_Repository_genotyping.txt**. Results of
 genetic fingerprinting based on 13 DNA microsatellite markers for
 non-invasive samples found during the fieldwork in the Romincka Forest,
 along with reference samples from Baltic, Central European, and Carpathian
 wolf subpopulations. This is a TAB-separated file that contains the
 following columns: (1) ID - identification number of the sample; (2) sex -
 sex of the individual based on the analysis of DBX intron 6 and DBY intron
 7; Followed by columnes with numerical data for allele sizes of 13
 polymorphic microsatellite loci: FH2001, FH2010, FH2017, FH2054, FH2087L,
 FH2088, FH2096, FH2137, FH2140, FH2161, vWF, PEZ17 and CPH5.
 **Nowak_Repository_wolf_diet.txt**. Results of the analysis of wolf scats
 found in the Romincka Forest in 2020. This is a TAB-separated file with
 the following columns: (1) Region - name of the forest tract; (2) Year - a
 year when the sample was collected; (3) mass_(g) - dry mass (in grams) of
 the scat content after washing; And in the following columns with names of
 food items (hare, small_rodents, beaver, moose, wild_boar, red_deer,
 roe_deer, Cervide_indet, cattle, dog, plant_matter, artificial) is a dry
 mass of the scat content which refers to identified food items. Name of
 food items refers to: hare (Lepus europaeus), small_rodents (small
 rodents, &lt;50g, not identified to species), beaver (Castor fiber), moose
 (Alces alces), wild boar (Sus scrofa), red deer (Cervus elaphus), roe deer
 (Capreolus capreolus), Cervide indet. (cervids not identified to species
 level), cattle (domestic cattle Bos taurus), dog (Canis familiaris), plant
 matter (plant remains), artificial (artificial matter, e.g. plastic bags,
 etc.). **Nowak_Repository_tracking.txt**. List of tracks, videos from
 camera trapping, direct observations, scats, and urinations obtained
 during the study. This is a TAB-separated text file, divided into the
 following columns: (1) forest - with the name of the forest tract; (2)
 state_forest_division - with the name of the division of the Polish State
 Forest Service; (3) species - with the name of the studied species (grey
 wolf); (4) N - number of individuals (number of individuals is provided
 for tracking, direct observations, and camera trapping; in case of scats
 number of individuals could not be provided, thus there is NA); (5)
 age_category - two general age classes were provided: ad for adults or juv
 for juveniles; (6) season - it indicates a study season which begins on
 April 1st and finishes 31st March following year; (7) month; (8) type -
 type of data: direct observations, tracks, scats, video.