Alien plants of Kyrgyzstan

Alexander Sennikov1, Georgy Lazkov2, Denis Melnikov3

1 University of Helsinki, Unioninkatu 44, 00014, Helsinki, Finland; 2 Institute of Biology, Chui av. 265, 720071, Bishkek, Kyrgyzstan; 3 Komarov Botanical Institute, Prof. Popov str. 2, 197376, Saint-Petersburg, Russian Federation

Corresponding author(s): Alexander Sennikov (alexander.sennikov@helsinki.fi)Georgy Lazkov (glazkov1963@mail.ru)

Received {date}; Revised {date}; Accepted {date}; Published {date}

Citation: Combination of authors, year of data paper publication (in parentheses), Title, Journal Name, Volume, Issue number (in parentheses), and doi of the data paper.

Resource Citation

Sennikov A, Lazkov G (2024). Alien plants of Kyrgyzstan. Version 1.10. Komarov Botanical Institute, Russian Academy of Sciences, St. Petersburg. Checklist dataset. https://ipt.zin.ru/resource?r=alien_plants_of_kyrgyzstan&v=1.10

Abstract

This is a checklist resulting from the first comprehensive literature-based inventory of alien plants in Kyrgyzstan. The checklist provides essential information on the species taxonomy, residence status, period of introduction, and distribution (according to phytogeographic regions of Kyrgyzstan).

Keywords: alien plants, Central Asia, checklist, Kyrgyzstan, plant invasions, vascular plants, alien plants, Central Asia, checklist, Kyrgyzstan, plant invasions, vascular plants

General description

Purpose: This dataset provides the main taxonomic information and the distributional backbone for the alien vascular plants of Kyrgyzstan.
Additional information: The precise distributional records have been published via GBIF separately.

Project details

Project title: Alien plants of Kyrgyzstan
Personnel: Alexander Sennikov, Georgy Lazkov
Funding: This research received no external funding.
Study area descriptions/descriptor: This is a comprehensive revision of alien plants of Kyrgyzstan.
Design description: The revision is based on a comprehensive sampling and inventory of available data.

Data published through GBIF: https://ipt.zin.ru/resource?r=alien_plants_of_kyrgyzstan

Taxonomic coverage

General taxonomic coverage description: The dataset includes a selection of vascular plants occurring spontaneously in Kyrgyzstan.
Taxonomic ranks
Phylum: Tracheophyta
Common names: vascular plants

Spatial coverage

General spatial coverage: The geographic coverage of this dataset is Kyrgyzstan.
Coordinates: 39°9'50.4''N and 43°19'30''N Latitude; 69°12'50.4''E and 80°17'16.8''E Longitude 

Natural collections description

Collection name: Institute of Botany, Herbarium
Formation period: 1840-ongoing
Specimen preservation method: Dried and pressed

Methods

Method step description: 
- . 	The original floristic checklist was screened, and a residence status (native or alien) was established for each species.
- . 	Distributional data were added for each alien species on the basis of the checklist and personal field knowledge.
Study extent description: The dataset contains information on the taxonomy and distribution of alien plants in Kyrgyzstan. It is based on a comprehensive overview of all published data, and is open for regular updates.
Sampling description: The taxonomic dataset is based on the checklist of vascular plants of Kyrgyzstan (2014), from which the data on alien plants were extracted and complemented by the latest literature. The compiled data were evaluated according to the field knowledge of the authors.
Quality control description: The taxonomic identity, geographical distribution and residence status of each record have been assessed by the authors on case by case basis, and corrected when necessary.

Datasets

Dataset description
Object name: Darwin Core Archive Alien plants of Kyrgyzstan
Character encoding: UTF-8
Format name: Darwin Core Archive format
Format version: 1.0
Distribution: https://ipt.zin.ru/archive.do?r=alien_plants_of_kyrgyzstan
Publication date of data: 2024-02-20
Language: English
Licences of use: Creative Commons Attribution (CC-BY 4.0) License

Metadata language: English
Date of metadata creation: 2023-12-28
Hierarchy level: Dataset