The dataset shows information on records of various representatives of native and invasive herpetofauna species registered on the territory of Ukraine by two scientists - O. Yu. Marushchak and O. D. Nekrasova during field research. Occasional records, when identified to the level of species were also included. Some records, made by third parties, but provided with date, photo and coordinates of location were also added to the table, since they make their contribution to collecting of data on herpetoculture distribution during the war, when the opportunities of field reearch are limited. The dataset represents records from Zakarpattia, Lviv, Zhytomyr, Khmel'nytsky and Kyiv regions of Ukraine. The dataset shows records of both rare species, such as those listed in Red Data Book of Ukraine or in other lists of species strictly protected within European Union (e.g. Emys orbicularis - European pond turtle) and common species which can be found easier and in bigger quantities and wider set of habitats.
The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 703 records.
This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.
The table below shows only published versions of the resource that are publicly accessible.
How to cite
Researchers should cite this work as follows:
Marushchak O, Nekrasova O (2023). Records of herpetofauna made in 2023 by Marushchak O. Yu. and Nekrasova O. D.. Version 1.1. Ukrainian Nature Conservation Group (NGO). Occurrence dataset. https://ukraine.ipt.gbif.no/resource?r=marushchakherpeto2023&v=1.1
Researchers should respect the following rights statement:
The publisher and rights holder of this work is Ukrainian Nature Conservation Group (NGO). This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.
This resource has been registered with GBIF, and assigned the following GBIF UUID: 2779845a-d580-45dd-991c-aa4e972574b8. Ukrainian Nature Conservation Group (NGO) publishes this resource, and is itself registered in GBIF as a data publisher endorsed by Participant Node Managers Committee.
Occurrence; Ukraine; herpetofauna; rare species; amphibians; reptiles; snakes; lizards; frogs; newts; 2023; biodiversity; field research; Observation
The dataset covers territory of Kyiv, Zhytomyr, Zakarpattia, Lviv and Khmel'nyts'ky administrative regions of Ukraine.
|Bounding Coordinates||South West [47.606, 22.126], North East [52.429, 33.486]|
The dataset consists of records of amphibians (Amphibia class, Anura & Caudata orders) and reptiles (according to Backbone taxonomy, Squamata & Testudines classes).
|Class||Amphibia, Squamata, Testudines|
|Family||Colubridae, Viperidae, Lacertidae, Anguidae, Emydidae, Bufonidae, Ranidae, Hylidae, Pelobatidae, Bombinatoridae, Salamandridae|
|Start Date / End Date||2023-03-19 / 2023-09-30|
Emys-R will analyze all resources available from past and present programs of wetlands restoration and Emys reintroduction throughout Europe, and test original methods based on social and ecological sciences, and adaptive management, to define the most effective, socially supported, methods of wetland restoration in favor of the Emys reintroduction and associated biodiversity throughout Europe, to be implemented in future homologous conservation measures.
|Funding||Emys-R is funded through the 2020-2021 Biodiversa & Water JPI joint call for research proposals, under the BiodivRestore ERA-Net COFUND programme, and with the funding organisations Agence Nationale de la Recherche (ANR, France), Bundesministerium für Bildung und Forschung (BMBF, Germany), State Education Development Agency (VIAA, Latvia), and National Science Center (NSC, Poland).|
|Study Area Description||Emys-R is a 3-year participatory action-oriented research project based on seminal theories in humanities, social and natural sciences. It consolidates an existing international network of researchers and stakeholders to share complementary knowledge and expertise on past, present and future wetlands, biodiversity and management.|
The personnel involved in the project:
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). Catching of amphibians and reptiles wa performed using a net, fishing rod, fishing traps, a hook or by hand. For georeferencing of the records, 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 orientation program MAPS.ME (version 12.0.1-Google) and Google Earth Pro (Earth version 7.3.3). Visualization of records and creation of maps was carried out in the QGIS program (v.2.181, QGIS Development Team, 2016. QGIS Geographic Information System. Open Source Geospatial Foundation. URL http://qgis.org).The species identification was carried out using methodological materials (Bannikov and Darevsky, 1977; Nekrasova and Morozov-Leonov, 2001; Kuzmin, 2012). No special permits were needed for such work and collecting of common species of reptiles and amphibians. Those records obtained from third parties consisted of: several good quality photos, location, additional information and date. All animals that were spotted - were released at the place of capturing after all needed information was collected.
|Study Extent||The dataset represents information on records of herpetofauna made during field season from March to September 2023.|
|Quality Control||The authors are fully responsible for the quality and accuracy of data provided within the published dataset.|
Method step description:
- Conducting field trips.
- Manual catching of individuals or taking photos from distance or taking photos from third parties which is enough for species identification.
- Identification of species based on the available data and known key features.
- Organizing of the dataset according to Darwin Core standards.