說明
The dataset providing information on the geographic distribution of Oxytropis species on the territory of Asian Russia is discussed. Different sources (prominent floras and compendia, modern papers, Red Data books, and field data) have been used to describe diversity and distribution of the one of the richest genera in Northern and Central Asia. Presented species distribution data cover purely studied regions of Russia and reveal different geographic patterns on species and supraspecific levels of organization. Presented dataset will be helpful in understanding ecological features and main determinants limiting distribution of Oxytropis species.
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 5,172 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。:
Sandanov D, Dugarova A, Brianskaia E, Selyutina I, Makunina N, Dudov S, Chepinoga V, Wang Z (2021): Occurrences of Oxytropis species on the territory of Asian Russia. v1.6. Institute of General and Experimental Biology of SB RAS. Dataset/Occurrence. http://gbif.ru:8080/ipt/resource?r=oxytropis_asian_russia&v=1.6
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 Institute of General and Experimental Biology of SB RAS。 This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC 4.0) License.
GBIF 註冊
此資源已向GBIF註冊，並指定以下之GBIF UUID: 868e92bb-d93e-4fc9-886f-81149ec92ec2。 Institute of General and Experimental Biology of SB RAS 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; Dataset; Oxytropis; Asian Russia; digitizing printed maps; Observation
聯絡資訊
- 元數據提供者 ●
- 作者 ●
- 出處 ●
- 連絡人
- 出處
- 出處
- 出處
- 出處
- 出處
- 出處
- 出處
地理涵蓋範圍
Asian Russia (or Asian part of Russia) is a vast territory that occupies 1/3 of Asia, or about 13 100 000 sq. km, and stretches for more than 7000 km from east to west and almost 4500 km from the north to south.
| 界定座標範圍 | 緯度南界 經度西界 [42.41, 30.4], 緯度北界 經度東界 [78.55, 171.32] |
|---|
時間涵蓋範圍
| 起始日期 / 結束日期 | 1946-01-01 / 2021-01-01 |
|---|
計畫資料
The project involves different disciplines: flora and plant taxonomy, plant biology and population ecology, the vegetation of Baikal region, fauna and ecology of insects, ecology and geography of vertebrates.
| 計畫名稱 | Biota of terrestrial ecosystems of Baikal region: composition, structure, eco-geographic patterns |
|---|---|
| 辨識碼 | 121030900138-8 |
| 經費來源 | Russian Federal Budget |
| 研究區域描述 | Baikal Region, Russia |
參與計畫的人員:
- 作者
- 作者
取樣方法
In total, we have digitized 124 distribution maps of Oxytropis species and subspecies (except for intermediate forms and variations) from several key floras and check-lists (Table 1). The compendium “Arctic flora of USSR” contains 45 distribution maps of studied species and subspecies (Yurtzev, 1986). We recognized all seven subspecies of O. middendorffii n accordance with the 'GBIF backbone' and paper by Leonid Malyshev (2008). Original data for O. middendorffii s.l. is also presented in the dataset. We did not digitize maps from the “Flora of Siberia” which included 47 species and 5 subspecies of Oxytropis (Polozhii, 1994), because this part of the data was previously published by Artemov and Egorova (2021). The compendium “Vascular Plants of Soviet Far East” includes 49 locoweed species (Pavlova, 1989). Some of them are nowadays considered as subspecies, i.e., O. middendorffii subsp. anadyrensis and O. middendorffii subsp. trautvetteri. Occurrences from the “Flora of Central Siberia” (Peshkova, 1979) we derived automatically using a special program on Java and later verified manually (Chepinoga et al., 2017). The distribution of 30 Oxytropis species from “Flora of Central Siberia” were adjusted to the grid system used in the compendium. The other source, atlas “Endemic alpine plants of Northern Asia,” also contains information on the distribution of 13 locoweed species with 281 occurrences in Asian Russia. But we have not considered this source, while it was recently published in a separate dataset (Brianskaia et al. 2021). The digitalization was performed in QGIS 3.10 and QGIS 3.16 software through georeferencing tool. We georeferenced the source raster distribution maps by snapping control points to the destination vector shapefile. We used Natural Earth vector map at 1:10m scale as base map for georeferencing (Natural Earth 2018). Control points linked raster maps to destination shapefile, which resulted in a transformation of the maps according to the spatial projection of destination features (WGS 1984). Subsequently, we digitized species distribution locations from each map. Coordinates of each location were calculated in an attribute table. Denis Sandanov with Elena Brianskaia georeferenced distribution maps from “Arctic flora of USSR” (Yurtzev, 1986), Sergey Dudov – maps from “Vascular Plants of Soviet Far East” (Pavlova, 1989). Victor Chepinoga provided coordinates for localities of Oxytropis from “Flora of Central Siberia” (Chepinoga et al., 2017) (Table 2). Additionally, we georeferenced maps from Red Data Books published for different regions of Russia, i.e., Republic of Khakassia (2012), Republic of Buryatia (2013), Altai Republic (2017), Republic Sakha (Yakutia) (2017), Zabaikalsky Krai (2017), Altai Krai (2020), and Irkutsk Oblast (2020). In some cases, Red Data Books contain distribution data not available in other sources. Little additional information was derived from papers by Malyshev (2008) and by Pyak (2014). A considerable number of occurrences were extracted from authors’ original field data (relevés, field diaries, etc.). The main contributors were Denis Sandanov (1332 occurrences), Natalia Makunina (708 occurrences), and Inessa Selyutina (408 occurrences).
| 研究範圍 | Asian Russia (or Asian part of Russia) is a vast territory that occupies 1/3 of Asia, or about 13 100 000 sq. km, and stretches for more than 7000 km from east to west and almost 4500 km from the north to south. |
|---|---|
| 品質控管 | Final examination of the digitized species distribution maps was performed in QGIS 3.10 and QGIS 3.16. For each species we compared the output digitized occurrences with the original maps. Following Chapman and Wieczorek (2020), we apply three types of coordinate uncertainties. The first type includes coordinate uncertainty of species occurrence from the herbarium locality description. For such data, we established approximated 5 km as the coordinate uncertainty. The second type is the coordinate uncertainty of the drawn maps. Here we accept a symbol diameter and map scale as a value of coordinate uncertainty at geocoding. Projections for the “Arctic flora of USSR” and “Vascular Plants of Soviet Far East” were recognized in QGIS. The original printed maps contained non-projective distortions; therefore, the initial rasters were transformed using the “polynomial 1” or “polynomial 2” transformation method and the "nearest neighbor" interpolation method. The largest possible source of error relates to the original mapping of points in the pre-digital era. To assess the impact of these uncertainties, we compared the position of points with known coordinates and points on maps based on these samples. The spatial resolution of digitized maps was differ: markers on the maps from the “Vascular Plants of Soviet Far East” have diameters from 33 to 45 kilometers (mean=39 km), “Flora of Siberia” – from 29 to 39 km (34 km), “Arctic flora of USSR” – from 23 to 27 km (27 km). We used these mean parameters to estimate uncertainty for each digitized source. The third type is the coordinate uncertainty of the map digitalization in QGIS. To test the coordinate uncertainty of such maps, three experts independently performed digitalization on their computers for each type of map. As a result, the coordinate uncertainty was less than 5 km in all cases. We calculated the final coordinate uncertainty by summarizing all three types mentioned above and for prominent floras it is estimated as 49 km for the “Vascular Plants of Soviet Far East”, 44 km for “Flora of Siberia”, and 37 km for “Arctic flora of USSR”. Coordinate’s uncertainty for the grid maps of “Flora of Central Siberia” considered as 18 km (Chepinoga et al., 2017). Occurrence data presented in the paper by Malyshev (2008) has lower precision and recognized uncertainty for them is equal to 30 km. The uncertainty of georeferenced data for Red Data Books based on large-scale maps estimated as 5 km. The same accuracy we used for occurrences of Oxytropis sobolevskajae (Pyak, 2014). |
方法步驟描述:
- 1) digitizing species distribution maps of Oxytropis species from prominent floras and compendia of Asian Russia, 2) summarizing field data with occurrences of locoweeds, and 3) merging all data to a single dataset.
額外的詮釋資料
| 替代的識別碼 | 868e92bb-d93e-4fc9-886f-81149ec92ec2 |
|---|---|
| http://gbif.ru:8080/ipt/resource?r=oxytropis_asian_russia |