オカレンス(観察データと標本)

Occurrences of Oxytropis species on the territory of Asian Russia

最新バージョン Institute of General and Experimental Biology of SB RAS によって公開 2021/11/29 Institute of General and Experimental Biology of SB RAS

DwC-A形式のリソース データまたは EML / RTF 形式のリソース メタデータの最新バージョンをダウンロード:

DwC ファイルとしてのデータ ダウンロード 5,172 レコード English で (106 KB) - 更新頻度: unknown
EML ファイルとしてのメタデータ ダウンロード English で (21 KB)
RTF ファイルとしてのメタデータ ダウンロード English で (16 KB)

説明

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.

データ レコード

この オカレンス(観察データと標本) リソース内のデータは、1 つまたは複数のデータ テーブルとして生物多様性データを共有するための標準化された形式であるダーウィン コア アーカイブ (DwC-A) として公開されています。 コア データ テーブルには、5,172 レコードが含まれています。

この IPT はデータをアーカイブし、データ リポジトリとして機能します。データとリソースのメタデータは、 ダウンロード セクションからダウンロードできます。 バージョン テーブルから公開可能な他のバージョンを閲覧でき、リソースに加えられた変更を知ることができます。

バージョン

次の表は、公にアクセス可能な公開バージョンのリソースのみ表示しています。

引用方法

研究者はこの研究内容を以下のように引用する必要があります。:

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

権利

研究者は権利に関する下記ステートメントを尊重する必要があります。:

パブリッシャーとライセンス保持者権利者は 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登録

このリソースをはGBIF と登録されており GBIF UUID: 868e92bb-d93e-4fc9-886f-81149ec92ec2が割り当てられています。   Participant Node Managers Committee によって承認されたデータ パブリッシャーとして GBIF に登録されているInstitute of General and Experimental Biology of SB RAS が、このリソースをパブリッシュしました。

キーワード

Occurrence; Dataset; Oxytropis; Asian Russia; digitizing printed maps; Observation

連絡先

Denis Sandanov
  • メタデータ提供者
  • 論文著者
  • 最初のデータ採集者
  • 連絡先
Senior Researcher
Institute of General and Experimental Biology of SB RAS
Sakhyanovoi str., 6
670047 Ulan-Ude
Republic of Buryatia
RU
73012433256
Anastasiia Dugarova
  • 最初のデータ採集者
PhD Student
Institute of General and Experimental Biology of SB RAS
Sakhyanovoi str., 6
670047 Ulan-Ude
Republic of Buryatia
RU
73012433256
Elena Brianskaia
  • 最初のデータ採集者
Junior Researcher
Institute of General and Experimental Biology of SB RAS
Sakhyanovoi str., 6
670047 Ulan-Ude
Republic of Buryatia
RU
73012433256
Inessa Selyutina
  • 最初のデータ採集者
Senior Reseacrher
Central Siberian Botanical Garden of SB RAS
Zolotodolinskaya str., 101
630090 Novosibirsk
Novosibirsk area
RU
79529459943
Natalia Makunina
  • 最初のデータ採集者
Leading Researcher
Central Siberian Botanical Garden of SB RAS
Zolotodolinskaya str., 101
630090 Novosibirsk
Novosibirsk area
RU
73833399756
Sergei Dudov
  • 最初のデータ採集者
Researcher
Moscow State University
Leninskie Gory str., 1, building 12
119991 Moscow
Moscow Are
RU
74959392777
Victor Chepinoga
  • 最初のデータ採集者
Head of organization
Central Siberian Botanical Garden of SB RAS
Zolotodolinskaya str., 101
630090 Novosibirsk
Novosibirsk area
RU
73833304101
Zhiheng Wang
  • 最初のデータ採集者
Professor
Peking University
Haidian District, Yiheyuan Road No.5
100871 Beijing
CN

地理的範囲

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.

座標(緯度経度) 南 西 [42.41, 30.4], 北 東 [78.55, 171.32]

時間的範囲

開始日 / 終了日 1946-01-01 / 2021-01-01

プロジェクトデータ

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.

タイトル Biota of terrestrial ecosystems of Baikal region: composition, structure, eco-geographic patterns
識別子 121030900138-8
ファンデイング Russian Federal Budget
Study Area Description Baikal Region, Russia

プロジェクトに携わる要員:

Anastasiia Dugarova
  • 論文著者
Elena Brianskaia
  • 論文著者

収集方法

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).

Study Extent 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.
Quality Control 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).

Method step description:

  1. 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.

追加のメタデータ

代替識別子 868e92bb-d93e-4fc9-886f-81149ec92ec2
http://gbif.ru:8080/ipt/resource?r=oxytropis_asian_russia