Biodiversity Data Journal 11: e99036 (oo @)
doi: 10.3897/BDJ.11.e99036 open access

Data Paper

Records of common species of amphibians and
reptiles widespread in northern, central, western
and southern Ukraine

Oksana Nekrasova?, Oleksii Marushchak*

$ I. |. Schmalhausen Institute of Zoology of National Academy of Sciences of Ukraine, Kyiv, Ukraine

Corresponding author: Oleksii Marushchak (ecopelobates@gmail.com)

Academic editor: Dmitry Schigel

Received: 20 Dec 2022 | Accepted: 26 Jan 2023 | Published: 31 Jan 2023

Citation: Nekrasova O, Marushchak O (2023) Records of common species of amphibians and reptiles

widespread in northern, central, western and southern Ukraine. Biodiversity Data Journal 11: e99036.
https://doi.org/10.3897/BDJ.11.e99036

Abstract
Background

The dataset includes records of amphibian and reptile species from northern, central,
western and southern Ukraine made by Ukrainian herpetologist O. D. Nekrasova during
her field trips in the period from 1996 to 2022. Chosen species were not included in the
latest published edition of the Red Data Book of Ukraine (2009) and in the latest lists of
such species prepared in 2019. The species mentioned in this dataset are characterised by
wide range within the country, covering more than 70% of its territory according to spatial
distribution modelling (GIS-modelling) made with the help of Maxent software.

New information

The dataset highlights records of eight common species of herpetofauna of Ukraine
collected by the first author for the last 26 years. Within the period from 1996 to 2022, O.
D. Nekrasova collected and studied information and material on the herpetofauna of the
northern, central, western and southern parts of Ukraine from a total of 3960 cadastral

© Nekrasova O, Marushchak O. This is an open access article distributed under the terms of the Creative Commons Attribution
License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author
and source are credited.

2 Nekrasova O, Marushchak O

points (1707 - for three species of reptiles and 2253 - for five species of amphibians).
These records, being now available for the international scientific community, will fill the
gap in updated records of the mentioned species, being potentially useful for GIS-
modelling, distribution modelling, clarification of conservation lists of national and local
importance, further assessment of impact of the war on native biota etc.

Keywords

Common species, amphibians, reptiles, Ukraine, herpetofauna, GIS-modelling

Introduction

The main part of the herpetofauna of Ukraine consists of the so-called "common species",
occupying more than 70% of the studied area and numerically prevailing in different
biotopes compared to their other classes (Sillero et al. 2014). They tend to be very
important parts of many trophic chains in ecosystems, maintaining their energy balance, its
flow, keeping a stable state. Simultaneously, the structural and functional state of common
species' populations (age composition, sex ratio, morphological and genetic features of
these animals) can be used for bioindication, since it reflects the state of the environment
as a whole (Yablokov 1987, Akulenko et al. 2019). Amphibian and reptile species, even
those treated as common ones, are extremely sensitive to the state of the environment
(biotopes and habitats) and, therefore, require development of special conservation
measures now, based on the long-term trends and probabilistic models of environmental
change (Gibbons et al. 2000, Howard and Bickford 2014, Catenazzi 2015, Greenberg and
Palen 2021). Anthropogenic processes demanding such urgent needs include pollution of
the environment (e.g. with pecticides, insecticides etc.), degradation, fragmentation and
direct destruction of suitable habitats (e.g. as a result of military actions, shelling, using
chemical weapons etc.) (Vasyliuk et al. 2022), emergence and expansion of alien invasive
species and harmful agents (viruses, microorganisms and parasites) (Kopecky et al. 2013,
Garcia-Diaz et al. 2016, Demkowska-Kutrzepa et al. 2018) and, of course, global climate
change (Lindenmayer et al. 2011, Vasyliuk et al. 2015, Tytar et al. 2018, Nekrasova et al.
2019). Common species are usually ecologically flexible and occur both in urbo- and
agrocenoses, surviving even in heavily anthropogenically transformed areas (Nekrasova
2002). At the same time, they are characterised by a large number of different
morphological and genetic forms and, sometimes in the population, a large number of
individuals with anomalies are observed, which have recently increased significantly
(Nekrasova 2002, Nekrasova 2008, Nekrasova 2014, Nekrasova and Kuibida 2018, Tytar
et al. 2018, Marushchak et al. 2021).

Amongst the 24 species of reptiles in Ukraine, we have chosen only three "common"
species (12.5% of all reptile species inhabiting the country): sand lizard Lacerta agilis
Linnaeus, 1758; European pond turtle Emys orbicularis (Linnaeus, 1758) and grass snake
Natrix natrix (Linnaeus, 1758). This group does not include species that are widespread,
but are rare and relatively few in numbers or listed in the Red Data Book of Ukraine

Records of common species of amphibians and reptiles widespread in northern, ... 3

(Akimov 2009), for example, the smooth snake Coronella austriaca Laurenti, 1768 (74.1%)
(Nekrasova 2014). Amongst 22 species of amphibians in Ukraine, we chose five species of
anurans (22.7% of all amphibian species inhabiting Ukraine): semi-aquatic and widespread
(https://www.gbif.org/uk/dataset/1 48bc5c8-0408-424c-84d2-d491ea2e234d) European
green toad Bufotes viridis (Laurenti, 1768); the most ecologically flexible and numerous
marsh frog Pelophylax ridibundus (Pallas, 1771); oriental tree frog Hyla orientalis
(Bedriaga, 1890); European fire-bellied toad Bombina bombina (Linnaeus, 1761)

widespread in small water bodies and the most vulnerable forest species - common toad
Bufo bufo (Linnaeus, 1758) (Smirnov 2014, Shabanova et al. 2017, Palamarenko 2021)
(Table 1, Figs 1, 2).

Table 1.

A list of the studied amphibians and reptiles of Ukrainian herpetofauna.

AMPHIBIA Conservation status N % of the territory of
f Ukraine
Number Family Species
1. Bombinatoridae Bombina bombina (Linnaeus, IUCN (LC), BC (2) 532 76.7
1761)
2. Bufonidae Bufo bufo (Linnaeus, 1758) IUCN (LC), BC (3) 210 70.4
3. Bufonidae Bufo viridis Laurenti, 1768 IUCN (LC), BC (2) 354 97.1
4. Hylidae Hyla orientalis (Bedriaga, 1890) IUCN (LC),BC (2) 312 78.0
5. Ranidae Pelophylax ridibundus (Pallas, IUCN (LC), BC (3) 845 = 96.1
1771)
Total: 2253
REPTILIA
6. Emydidae Emys orbicularis (Linnaeus, IUCN (NT), BC (2) 583 78.0
1758)
7. Lacertidae Lacerta agilis Linnaeus, 1758 IUCN (LC), BC (2) 615 98.3
8. Colubridae Natrix natrix (Linnaeus, 1758) IUCN (LR/LC),BC 509 75.0
(3)
Total: 1707

The published dataset highlights information on widespread amphibian and reptile species,
records on the distribution of which in Ukraine has been poorly represented and only
available for the scientific community for the last 26 years. The problem is that information
on actual records is mainly collected on rare species (listed in national Red Lists of
protected species, such as the Red Book of Ukraine) (Akimov 2009). On the contrary, data
on common species is usually copied from old publications to the new ones without any
real changes (Kuzmin 1999, Pysanets 2007) and, therefore, possible trends, especially
negative ones when a common species suddenly becomes rare, can be missed. Tracking
and constant updating the evidence on all species (publishing updated bases of records),
regardless of their status, is necessary to respond adequately and in a timely manner to
their needs and possible population decline. At the very least, the regular publication of

4 Nekrasova O, Marushchak O

such data helps to make adequate changes to the lists of protected species and their
status, based on real data (Nekrasova et al. 2019), rather than personal feelings of
particular scientists or working groups. Only recently, thanks to the initiatives of the NGO
"Ukrainian Nature Conservation Group" on the preparation of the Shadow List of the
Emerald Network in Ukraine - newly-proposed territories aimed at the conservation of
specific species and habitats mentioned in Resolutions 4 and 6 of the Bern Convention
(Vasyliuk et al. 2022) and the initiative of our colleagues to create the National Ukrainian
Network UkrBin (UkrBIN 2017) to collect information on the distribution of various species
of fauna and flora in Ukraine, this problem started to get solved. Currently, GBIF is one of
the most unified international open access databases, which helps to collect and distribute
information, including information about common species.

y m Reptilia
: Fs e Amphibia

Figure 1. EES
Map of records of studied representatives of herpetofauna (amphians - Amphibia; reptiles -
Reptilia) on the territory of Ukraine.

General description

Purpose: The dataset consists of records of Amphibia and Reptilia representatives from
northern, central, western and southern Ukraine made in the period from 1996 to 2022
(Nekrasova and Marushchak 2022). The species are chosen as those not included in the
latest published edition of Red Data Book of Ukraine (Akimov 2009) and in the latest lists
of such species prepared in 2019. The species mentioned in this dataset are characterised
by wide range within the country, covering more than 70% of its territory according to
spatial distribution modelling (GlS-modelling) made with the help of Maxent software. The
purpose of the dataset publication is to make the data on common species of herpetofauna
of Ukraine available for the scientific community. These data, collected and identified by
the first author, are important for tracking of the changes in herpetofauna distribution and
population trends in terms of habitat changes induced by climate change, military actions,
agriculture intensification and their side effects.

Records of common species of amphibians and reptiles widespread in northern, ... 5

| a

re]

. viridis —97 1%

% >
Z. orientalis — 78,0%

3 » “ 40 23
E. orbicularis —78,0 % N. natrix —75,0 %

Figure 2. EES

Results of the analysis (Binomial test) of climatically suitable territory of Ukraine (distribution)
for the studied amphibian and reptile species.

Sampling methods

Description: Animals were caught manually during the peaks of activity of amphibians or
reptiles (mainly from 7:00 to 11:00 am and from 5:00 to 11:00 pm). Both groups of
vertebrates were caught mainly by hands. In particular cases for catching amphibians, we
used a net or fishing rod, while in cases of catching grass snakes, a hook was used for
picking them up. In the vast majority of cases, the animals were simply caught by hand
(Pupins et al. 2022). Animals killed on the road by vehicles were taken into account if the
identification to specific level was possible. For visualising the records (points) and for
further use in GlS-modelling, the points of herpetofauna registrations were collected (with
the indication of latitude 00.00000 N and longitude 00.00000 E) using the field off-line

6 Nekrasova O, Marushchak O

orientation programme MAPS.ME (version 12.0.1-Google) and Google Earth Pro (Earth
version 7.3.3). Visualisation of records and creation of maps was carried out in the QGIS
programme (v.2.181, QGIS Development Team (2016). QGIS Geographic Information
System. Open Source Geospatial Foundation. URL hitp://qgis.org). The species
identification was carried out using methodological materials (Bannikov et al. 1977,
Nekrasova et al. 2005, Kuzmin 2012).

Sampling description: The animals were detected using route methods, artificially
constructed channels, with the help of special equipment. Animal species were diagnosed
by studying larvae and adult individuals and remnants (moulted skin, dead bodies) using
morphological methods (Nekrasova 2002, Nekrasova et al. 2005, Nekrasova 2015,
Nekrasova et al. 2019), as well as by acoustic data depending on season. Spatial data was
used for GlS-analysis, and visualisation of spatial project models and modelling were done
using QGIS and DivaGis software (BIOCLIM, DOMAIN algorithms). To account for
potential sampling bias, we used the nearest-neighbour distance (‘ntbox' package in R)
method (Osorio-Olvera et al. 2020) to thin the data: to avoid spatial autocorrelation,
occurrence points < 0.1 units (meaning approximately the spatial resolution of the climate
factors’ database (.tiff map file, 2.5’ (or approximately 5 km) spatial resolution) used for the
research) away from each other were removed. We used 19 bioclimatic indicators (Table 2)
from the database from the CliMond dataset (Kriticos et al. 2014) https:/Avww.climond.org/
(accessed 27 December 2020), A1B scenario). Species distribution modelling (SDM)
methods (Anderson et al. 2003, Araujo et al. 2019) have been employed to explore the
potential climatically suitable territories for the studied species within the territory of
Ukraine. Binomial test was used for building distribution maps when choosing the species
for study. It helps to make a significance estimation of a niche model by using the
cumulative binomial probability of success of predicting an occurrence given the validation
data and the proportional area predicted as present in the niche model (Anderson et al.
2003). The modelling was done in the Maxent v.3.4.4 software (Phillips et al. 2006,
Peterson et al. 2008) with default settings. This software was chosen as Maxent, which,
unlike other distributional modelling techniques, uses only presence and background data
instead of presence and absence data. Visualisation of the models was carried out using
programmes - SAGA GIS and QGis (Nekrasova et al. 2019).

Table 2.

Bioclimatic variables (19) from the CliMond dataset (Kriticos et al. 2014; https:/Awww.climond.org/).

Variable Meaning

bio1 Annual mean temperature (°C)

bio2 Mean diurnal temperature range (mean (period max-min)) (°C)
bio3 Isothermality (bio02 + bio07)

bio4 Temperature seasonality (C of V)

bio5 Max temperature of warmest week (°C)

bio6 Min temperature of coldest week (°C)

Variable

bio7

bio8

bio9

bio10

bio11

bio12

bio13

bio14

bio15

bio16

bio17

bio18

bio19

Records of common species of amphibians and reptiles widespread in northern, ... 7

Meaning

Temperature annual range (bio05-bio06) (°C)
Mean temperature of wettest quarter (°C)
Mean temperature of driest quarter (°C)
Mean temperature of warmest quarter (°C)
Mean temperature of coldest quarter (°C)
Annual precipitation (mm)

Precipitation of wettest week (mm)
Precipitation of driest week (mm)
Precipitation seasonality (C of V)
Precipitation of wettest quarter (mm)
Precipitation of driest quarter (mm)
Precipitation of warmest quarter (mm)

Precipitation of coldest quarter (mm)

Quality control: Both authors are professional herpetologists specialising in, amongst
other topics, Ukrainian herpetofauna, which is proved by a great number of relevant
publications. Authors of the dataset are fully responsible for the quality of data provided in
it: georeferenced locations, species identification, time when record was made etc.

‘le

Step description: Conducting of field surveys and trips in search for
representatives of native herpetofauna.

Collecting of information from other local residents.

Visual species identification as well as number of individuals.
Georeferencing.

Taking photos and necessary measurements, if needed.

Putting of the information in the digital table designed in MS Excel.

Organising of a dataset according to DarwinCore standards.

Geographic coverage

Description: The dataset covers the entire territory of Ukraine. It hightlights records of
representatives of native herpetofauna within all regions of Ukraine, except Luhansk and
Donetsk Regions.

Coordinates: 44.402 and 52.376 Latitude; 22.192 and 40.122 Longitude.

8 Nekrasova O, Marushchak O

Taxonomic coverage

Description: The dataset consists of records of the most common species of reptiles and
amphibians inhabiting the territory of Ukraine, namely, representatives belonging to
Hylidae, Bombinatoridae, Bufonidae, Ranidae, Colubridae, Lacertidae and Emydidae
families.

Taxa included:

Rank Scientific Name
kingdom Animalia
phylum Chordata

class Amphibia

order Anura

family Bombinatoridae
family Bufonidae
family Hylidae

family Ranidae

class Reptilia

order Squamata
family Colubridae
family Lacertidae
order Testudines
family Emydidae

Temporal coverage

Formation period: 1996/2022.

Usage licence

Usage licence: Open Data Commons Attribution License

Data resources

Data package title: Records of common herpetofauna species widespread in northern,
central, western and southern Ukraine

Records of common species of amphibians and reptiles widespread in northern, ... FS)

Resource link: https:/Awww.gbif.org/uk/dataset/148bc5c8-0408-424c-84d2-d491ea2e234d
Alternative identifiers: https://doi.org/10.15468/3t8srm

Number of data sets: 1

Data set name: Records of common species of amphibians and reptiles widespread in
northern, central, western and southern Ukraine

Data format: Darwin Core

Data format version: 1.9

Description: In the "occurrenceRemarks" column of the dataset, "REL-population

means a mixed population of green frogs (genus Pelophylax) consisting of the three
known species for Ukraine, namely P. ridibundus, Pelophylax lessonae (Camerano,
1882) and Pelophylax esculentus (Linnaeus, 1758). "RE-population" means the mixed
population as well, but consisting of P ndibundus and FP. esculentus individuals only.

Column label

occurrencelD

scientificName

basisOfRecord

eventDate

verbatineventDate

year

occurrenceRemarks

organismQuantity

organismQuantityType

taxonRank

decimalLatitude

Column description

http://rs.tdwg.org/dwc/terms/occurrencelD; a unique identifier of a particular
occurrence within this dataset.

http://rs.tdwg.org/dwc/terms/scientificName; the full scientific latin name of the

recorded species.

http://rs.tdwg.org/dwc/terms/basisOfRecord; the specific type of the record, based

mainly on the way in which it was made.

htto://rs.tdwg.org/dwc/terms/eventDate; the exact date or interval during which the

record was made.

http://rs.tdwg.org/dwc/terms/verbatimEventDate; the verbatim original
representation of the date information for the specific record.

http://rs.tdwg.org/dwc/terms/year; the year in which the event occurred.

http://rs.tdwg.org/dwc/terms/occurrenceRemarks; comments or notes about the
occurrence.

http://rs.tdwg.org/dwc/terms/organismQuantity; a number or enumeration value
for the quantity of the recorded organisms.

http://rs.tdwg.org/dwc/terms/organismQuantity Type; the type of quantification
system used for the quantity of organisms.

htto://rs.tdwg.org/dwc/terms/taxonRank; the taxonomic rank of the most specific

name in the scientificName as it appears in the original record.

http://rs.tdwg.org/dwc/terms/decimalLatitude; the geographic latitude (in decimal
degrees, using the spatial reference system given in geodeticDatum) of the

geographic centre of a location, where the record was made.

10

decimalLongitude

language

identifiedBy

identifiedbylD

geodeticDatum

georeferencedBy

georeferenceProtocol

Nekrasova O, Marushchak O

htto://rs.tdwg.org/dwc/terms/decimalLongitude;the geographic longitude (in
decimal degrees, using the spatial reference system given in geodeticDatum) of

the geographic centre of a location, where the record was made.

http://purl.org/dc/terms/language; a language of the resource.

htto://rs.tdwg.org/dwciiri/identifiedBy; a person who assigned the taxon to the

subject.

http://rs.tdwg.org/dwc/terms/identifiedBy!D;a globally unique identifier for the
person responsible for assigning the taxon to the subject (in this dataset, this is
an ORCID record).

http://rs.tdwg.org/dwc/iri/geodeticDatum;the geodetic datum or spatial reference
system (SRS) upon which the geographic coordinates given in decimalLatitude
and decimalLongitude are based (WGS84).

http://rs.tdwg.org/dwc/terms/georeferencedBy; a person or group of people who
determined the georeference (spatial representation) for the location.

http://rs.tdwg.org/dwc/terms/georeferenceProtocol; a short description or
reference to the methods used to determine the spatial footprint, coordinates and

uncertainties.

coordinatesUncertaintylnMetres http://rs.tdwg.org/dwc/terms/coordinate UncertaintyInMeters;the horizontal

continent

countryCode

country

stateProvince

kingdom

phylum

class

order

family

distance (in metres) from the given decimalLatitude and decimalLongitude

describing the smallest circle containing the whole of the location area.

http://rs.tdwg.org/dwc/terms/continent; the name of the continent in which the

location occurs.

http://rs.tdwg.org/dwc/terms/countryCode; the standard code for the country in
which the location occurs.

http://rs.tdwg.org/dwc/terms/country; the name of the country or major

administrative unit in which the location occurs.

http://rs.tdwg.org/dwc/terms/stateProvince; the name of the next smaller

administrative region than country (oblast' or region) in which the location occurs.

htto://rs.tdwg.org/dwc/terms/kingdom;the full scientific name of the kingdom in
which the taxon is classified.

htto://rs.tdwg.org/dwc/terms/phylum;the full scientific name of the phylum in which
the taxon is classified.

htto://rs.tdwg.org/dwc/terms/class;the full scientific name of the class in which the
taxon is classified.

http://rs.tdwg.org/dwc/terms/order;the full scientific name of the order in which the
taxon is classified.

htto://rs.tdwg.org/dwc/terms/family;the full scientific name of the family in which
the taxon is classified.

Records of common species of amphibians and reptiles widespread in northern, ... 11

genus htto://rs.tdwg.org/dwc/terms/genus;the full scientific name of the genus in which
the taxon is classified.

specificEpithet htto://rs.tdwg.org/dwc/terms/specificEpithet;the name of the first or species epithet
of the scientificName.

recordedBy htto://rs.tdwg.org/dwc/terms/recordedBy;a person or several people, who made
the record.
recordedByID tip://rs.tdwg.org/dwc/terms/recordedBy!D; a globally unique identifier for the

person, responsible for recording the original occurrence.

type http://purl.org/dc/elements/1.1/type; the nature or genre of the resource.

Acknowledgements

The research was partly founded by the BiodivERSA and Water JPI project "A socio-
ecological evaluation of wetlands restoration and reintroduction programs in favor of the
emblematic European pond turtle and associated biodiversity: a pan-European approach"
("EMYS-R" https://emysr.cnrs.fr/) and by the project "Ecological and socioeconomic
thresholds as a basis for defining adaptive management triggers in Latvian pond
aquaculture" (Izp-2021/1-0247). The dataset was prepared (correctly organised according
to Darwin Core standards) and published with the help of the project "Preservation of data
on biodiversity of Ukraine during the Russian occupation" funded by "Documenting
Ukraine" initiative. The initiative is financed by the Institute for Human Sciences in Vienna
(https:/www.iwm.at/). The authors are grateful to Natalia Filimonova (I. |. Schmalhausen
Institute of Zoology NAS of Ukraine) for assistance with correction of English language of
the paper.

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