The 2nd and 3rd National Survey on the Natural Environment: Vegetation Survey (common species)

説明

データ レコード

この sampling event 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、6,769 レコードが含まれています。

拡張データ テーブルは1 件存在しています。拡張レコードは、コアのレコードについての追加情報を提供するものです。 各拡張データ テーブル内のレコード数を以下に示します。

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。:

Biodiversity Center of Japan (2023) The 2nd and 3rd National Survey on the Natural Environment: Vegetation Survey from 1957 to 1988 (common species). Ministry of the Environment, Government of Japan. Dataset/Sampling-event.

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 National Institute of Genetics, ROIS。 This work is licensed under a Creative Commons Attribution (CC-BY 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: d1d4931c-ba3a-4ebe-9e64-0b544d0d3271が割り当てられています。   GBIF Japan 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National Institute of Genetics, ROIS が、このリソースをパブリッシュしました。

キーワード

Samplingevent; Plants; Plantae; the 2nd and 3rd National Survey on the Natural Environment; Vegetation Survey; Japan

連絡先

地理的範囲

Japan

生物分類学的範囲

Identified taxon for Plantae were as follows: 46 families, 136 genera, 2638 species, 184 subspecies, 1135 varieties, 114 forms and 9 cultivars. Identified taxon for Fungi were as follows: 3 genera, 10 species, 3 subspecies.

時間的範囲

収集方法

The surveys were conducted based on phytosociological methods. Species compositions were recorded using arbitrary placed quadrats. For each quadrat, above ground vegetation were horizontally divided into several layers (e.g., herb layer, shrub layer, subcanopy layer, canopy layer). All vascular plants, some mosses and fungi were recorded for each layer. Details for the National Survey on the Natural Environment are available on the website of Biodiversity Center of Japan, Ministry of the Environment (https://www.biodic.go.jp/ne_research_e.html).

Method step description:

1. Geographic coordinates were generalized from original locality to representative coordinates in consideration of protecting sensitive species. The center of either secondary mesh (10x10km), the prefectural capitals or the capital of Japan was used as the representative coordinates. The coordinates were obtained from National Land Numerical Data (MLIT 2022a, MLIT 2022b). The closest terrestrial point from the center was chosen as an alternative point instead of the point in the sea for secondary mesh level coordinates. The maximum distance from the coordinates to the polygon edge was calculated as the accuracy of coordinates. R programs and ArcGIS were used for calculation (竹中 2014, Hijmans 2021, Karney 2013, Pebesma 2018).
2. Recorded Japanese common names were cleaned since some obvious typos scattered throughout the data. Data deletion was avoided as much as possible during data cleaning, however 161 occurrence records with incomplete species names such as blanks, "?" and "? sp" were deleted. Ambiguous search using R package: stringdist（van der Loo 2014) was conducted against the checklist of Japanese plant names (Yamanouchi et al. 2019), which is available on the JBIF website, to get candidates during data cleaning. The checklist was also used to get scientific names based on Japanese common names. Scientific names in Green List (Ebihara et al. 2016, Ito et al. 2016) and YList (based on Yonekura and Kajita 2003–) were selected in priority order, referring to other sources (Ebihara 2016a, 2016b, 大橋ほか（編）2015、2016a、2016b、2017a、2017b) in the checklist as appropriate. Taxon of fungi and algae was checked against literatures (広瀬・山岸 1977, 吉田ほか2015, National Museum of Nature and Science 2018, NIES 2022, Ohmura and Kashiwadani 2018, Suzuki 2016). YList (Yonekura and Kajita 2003–) was also referred to identify names for moss plants. Family names were mostly extracted from the checklist (Yamanouchi et al. 2019) and higher taxon was extracted from GBIF Backbone Taxonomy using GBIF Species API (GBIF 2023, GBIF Secretariat 2023) in Python programs.
3. Spelling variants in event dates, prefectures, quadrat areas and vegetation layers were fixed if obvious. Prefecture names were checked against the Digital Agency Registry Catalog (Digital Agency 2023). Vegetation layers were cleaned and normalized based on the outline of the 2nd National Survey on the Natural Environment (MoE 1979). All data including spatial and taxonomic information were organized into occurrence data using a MySQL database. Total of 413 occurrence records were deleted from original data, because either species names were invalid or relations between occurrences and events were incomplete.

書誌情報の引用

1. Digital Agency (2023) Japan Prefecture Master Dataset. Digital Agency Registry Catalog. CC BY 4.0. https://catalog.registries.digital.go.jp/rsc/address/mt_pref_all.csv.zip [accessed on 2023-01-30].
2. Ebihara, A. (2016a) The Standard of Ferns and Lycophytes in Japan, Volume 1. Gakken Publishers, Tokyo.
3. Ebihara, A. (2016b) The Standard of Ferns and Lycophytes in Japan, Volume 2. Gakken Publishers, Tokyo.
4. Ebihara, A., Ito, M., Nagamasu, H., Fujii, S., Katsuyama, T., Yonekura, K., Yahara, T. (2016) Fern GreenList ver. 1.01. http://www.rdplants.org/gl/
5. GBIF (2023) Species API. Available from https://www.gbif.org/developer/species [accessed on 2023-01-18].
6. GBIF Secretariat (2023) GBIF Backbone Taxonomy. Checklist dataset https://doi.org/10.15468/39omei Accessed via. GBIF.org [accessed on 2023-01-18].
7. Hijmans R (2021) geosphere: Spherical Trigonometry. R package version 1.5-14. https://CRAN.R-project.org/package=geosphere [accessed on 2022-10-18].
8. Ito, M., Nagamasu, H., Fujii, S., Katsuyama, T., Yonekura, K., Ebihara, A., Yahara, T. (2016) GreenList ver. 1.01. http://www.rdplants.org/gl/
9. Karney, C. F. F. (2013) Algorithms for geodesics, J. Geodesy 87: 43-55.
10. Ministry of Land, Infrastructure, Transport and Tourism, Japan (MLIT) (2022a) National Land Numerical Information Institutional National and Prefectural Agency Data. https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-P28.html#prefecture00 [accessed on 2022-10-17].
11. Ministry of Land, Infrastructure, Transport and Tourism, Japan (MLIT) (2022b) National Land Numerical Information Administrative Area Data. N03-20220101_GML.zip https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-N03-v3_1.html#prefecture00 [accessed on 2022-10-17].
12. Ministry of the Environment (MoE) (1979) The outline of the 2nd National Survey on the Natural Environment (vegetation, lakes and rivers). https://www.biodic.go.jp/reports/2-12/index.html [Accessed on 2022-10-05].
13. Ministry of Environment (MoE) (2012) The 4th Version of the Japanese Red Lists on 9 Taxonomic Groups. 2012-08-28 Press release. https://www.env.go.jp/en/headline/1841.html [accessed on 2023-03-13].
14. National Institute for Environmental Studies (NIES) (2022) Invasive Species of Japan. https://www.nies.go.jp/biodiversity/invasive/index.html [accessed on 2022-08- 24].
15. National Museum of Nature and Science (2018) Science Museum Net (S-Net). http://science-net.kahaku.go.jp/ [accessed on 2023-03-01].
16. Ohmura, Y. and Kashiwadani, H. (2018) Checklist of Lichens and Allied Fungi of Japan. National Museum of Nature and Science Monographs 49: 1-140.
17. Pebesma, E. (2018) Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10: 439-446.
18. Suzuki, T. (2016) A Revised New Catalog of the Mosses of Japan. Hattoria 7: 9-223.
19. van der Loo M (2014) The stringdist package for approximate string matching. The R Journal 6: 111-122. https://CRAN.R-project.org/package=stringdist
20. Yamanouchi, T., Shutoh, K., Osawa, T., Yonekura, K., Kato, S., Shiga, T. (2019) A checklist of Japanese plant names. https://gbif.jp/activities/checklist/wamei_checklist_110 [accessed on 2022-11-25].
21. Yonekura K, Kajita T (2003-) BG Plants: index for Japanese scientific plant names: Ylist. http://ylist.info [accessed on 2022-05-25].
22. 大橋広好, 門田裕一, 木原浩, 邑田仁, 米倉浩司（編）(2015) 改訂新版 日本の野生植物 1 ソテツ科～カヤツリグサ科. 平凡社, 東京.
23. 大橋広好, 門田裕一, 木原浩, 邑田仁, 米倉浩司（編）(2016a) 改訂新版 日本の野生植物 2 イネ科～イラクサ科. 平凡社, 東京.
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