說明
The dataset contains findings of fish species obtained during ichthyological and hydroecological studies on different types of sites of the Kyiv and Kaniv reservoirs. The dataset contains findings of 13 alien fish species (Ponto-Caspian species, self-settled and distant settlers) registered on sites of the Kyiv and Kaniv reservoirs.
資料紀錄
此資源出現紀錄的資料已發佈為達爾文核心集檔案（DwC-A），其以一或多組資料表構成分享生物多樣性資料的標準格式。 核心資料表包含 107 筆紀錄。
此 IPT 存放資料以提供資料儲存庫服務。資料與資源的詮釋資料可由「下載」單元下載。「版本」表格列出此資源的其它公開版本，以便利追蹤其隨時間的變更。
版本
以下的表格只顯示可公開存取資源的已發布版本。
如何引用
研究者應依照以下指示引用此資源。:
Prychepa M, Pryshliak S, Kovalenko Y (2025). Alien fish species recorded from Kyiv and Kaniv reservoirs. Version 1.0. Ukrainian Nature Conservation Group (NGO). Occurrence dataset. https://ukraine.ipt.gbif.no/resource?r=alienfishspeciesprychepamreservoirs1&v=1.0
權利
研究者應尊重以下權利聲明。:
此資料的發布者及權利單位為 Ukrainian Nature Conservation Group (NGO)。 This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.
GBIF 註冊
此資源已向GBIF註冊，並指定以下之GBIF UUID: 6d496115-32bb-4fd4-99ea-36b1541cd82b。 Ukrainian Nature Conservation Group (NGO) 發佈此資源，並經由Participant Node Managers Committee同意向GBIF註冊成為資料發佈者。
關鍵字
Occurrence; alien species; invasive species; fish; chordata; reservoirs; Kaniv reservoir; Kyiv reservoir; biodiversity; Ukraine; vertebrates; Observation
聯絡資訊
- 元數據提供者 ●
- 出處 ●
- 連絡人
- +38(097)3145101
https://orcid.org/0000-0002-3114-2402
- 出處
- 出處
- 託管人
- junior researcher
- Vul. B. Khmelnytskogo, 15
- 0964882670
地理涵蓋範圍
The dataset covers the territory of Kaniv and Kyiv reservoirs within Kyiv administrative region of Ukraine.
| 界定座標範圍 | 緯度南界 經度西界 [49.808, 30.359], 緯度北界 經度東界 [51.074, 31.545] |
|---|
分類群涵蓋範圍
The dataset consists of records of fish (Teleostei).
| Kingdom | Animalia |
|---|---|
| Phylum | Chordata |
| Order | Cypriniformes, Gasterosteiformes, Perciformes, Syngnathiformes |
| Family | Centrarchidae, Cyprinidae, Gasterosteidae, Gobiidae, Odontobutidae, Syngnathidae |
時間涵蓋範圍
| 起始日期 / 結束日期 | 2020-10-10 / 2025-08-18 |
|---|
取樣方法
The material was collected during ichthyological and hydroecological studies in different types of areas of the Kyiv and Kaniv reservoirs. Ichthyological catches and photo registration were carried out at local points in different parts of the reservoirs based on standard field research methods. Ichthyological nets and fishing rods were used for fishing. Data from amateur fishermen's catch records were included, and dead fish were collected to determine species affiliation. Before fishing, photo and video recordings of fish in the water area were carried out. Field research was carried out in different biotopes in all seasons. Approaches and methods of catching and identifying fish species are taken from the literary source: Movchan Yu.V. (2011). Fish of Ukraine. Kyiv: Zoloti Vorota. 444 pp. (Ukrainian); Kottelat M., Freyhof J. (2007). Handbook of European freshwater fishes. Switzerland: Delemont. 646 p.
| 研究範圍 | The geography of studies includes the coastal zone of Kyiv (villages of Straholissya, Sukholuchchya, Rovzhi, Lebedivka, Kozarovychi, Hlibivka, city of Vyshhorod ), Kaniv (city of Kyiv, villages of Kyyliv, Plyuty, Khalepya, Stayky, Hrebeni, Rzhyshchiv, Khodoriv, town of Pereyaslav, and the territory of the Kaniv reserve (“Snake Islands”). We express our sincere gratitude to the co-authors of the descriptions: Trylis V.V., Hupalo O.O. We are sincerely grateful to the NGO "Ukrainian Nature Conservation Group" for their support, as well as to the participants of the youth grant of the group/laboratory: Nezbrytska I.M., Pogorelova M.S., Ivanova N.O. for the opportunity to conduct research in some areas of reservoirs remote from Kyiv. We are infinitely grateful to the Armed Forces of Ukraine for the opportunity to finalize the materials and hope for new research under the peaceful sky of independent Ukraine! |
|---|---|
| 品質控管 | The authors bear full responsibility for the quality of the data in this dataset. |
方法步驟描述:
- Conducting of field research on the sampling points.
- Catching of fish specimens.
- Species identification following the standard methods.
- Georeferencing.
- Organising of the dataset according to the Darwin Core standards.