Alien plant presence dataset from the point-radius plot surveys in 2010-2015 in Taiwan

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、4,879 レコードが含まれています。

拡張データ テーブルは2 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。:

Chou FS, Lin CC, Lu SS, Liao CK, Wang YH (2016) Alien plant presence dataset from the point-radius plot surveys in 2010-2015 in Taiwan. Taiwan Forestry Research Institute, Council of Agriculture, Taiwan

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 Taiwan Forestry Research Institute。 To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0). Users may copy, modify, distribute and use the work, including for commercial purposes, without restriction.

GBIF登録

このリソースをはGBIF と登録されており GBIF UUID: e1f3be55-9f45-474c-8374-502b236e0ad0が割り当てられています。   Taiwan Biodiversity Information Facility 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Taiwan Forestry Research Institute が、このリソースをパブリッシュしました。

キーワード

Sampling event; alien plants; presence; point-radius plots

連絡先

地理的範囲

Taiwan

生物分類学的範囲

Vascular plants (Magnoliophyta, Pteridophyta)

時間的範囲

プロジェクトデータ

For monitoring the current distributions and modelling the potential expansion of alien plants in Taiwan, we conducted this six-year (2010-2015) project to collect the presence data of alien plants along the road network in Taiwan. This dataset was used as an example dataset for the BIFA project “Biodiversity informatics cookbook” to demonstrate how to compile and publish a sampling event dataset.

プロジェクトに携わる要員:

収集方法

We made sample plots with radius in 20 meters along road network covered Taiwan and documented the presence of alien plants in each plot.

Method step description:

1. Field sampling: Sampling points were selected along road network covering Taiwan. Distance between two adjacent points along a road was within 2.0-2.5 kilometers. Sampling points were georeferenced by using a Garmin 60CX GPS receiver.
2. Compiling the field records: We used Microsoft Excel to create a workbook file with two worksheets to input the data of sampling plots and the presence of plants in each plot. The plot worksheet included the fields of sampling date, plot identifier, habitat, latitude, longitude, altitude, and county to document the detailed information of each plot. The presence worksheet included fields of sampling date, plot identifier, plant identifier, scientific names, and vernacular names in Chinese to document the presence information of plants in each plot.
3. Cleaning scientific names and retrieve relevant taxonomic information: For correcting any error in spelling scientific names, adopting accepted or valid scientific names, and getting complete information on the hierarchy of taxon ranks, we check all input names against the GBIF backbone taxonomy embedded in the name matching service (http://match.taibif.tw/) developed by Taiwan Biodiversity Information Facility in a first batch and save the matching results in a CSV text file. Then, we used Notepad++, a free text editor to open this file. All matching results were copied into the occurrence worksheet aligned with the input names to check the quality of input names by using the score field from the matching results as a filter. Some names could not be found in GBIF backbone taxonomy (scored as N/A) then we matched these names against the taxonomic data from Catalog of Life embedded the TaiBIF name matching service as a send batch in the same way to check the quality and to correct the errors in these names. Finally, we got a cleaned and accepted scientific names with complete name information on the hierarchy of taxonomic ranks for each occurrence record.
4. Standardizing data structure: For better preservation of complete information of the dataset and better integration into the GBIF global data portal, we adopted the Darwin Core star-schema and transformed our original two data tables (plot and occurrence of plant in plot) into three tables (Event, MeasurementOrFacts, and Occurrence) by using the Darwin Core terms defined for describing sampling events, measurements conducted in the sampling events and the occurrence records from each sampling event. All three data files were saved as UTF-8 chracter encoded CSV file. Users can open these files by any free text editor, such Notepad ++ or PSPad then select and copy the content into a spreadsheet software, such as the Clibre Office Calc or Microsoft Office Excel, for further editing and reuse.

追加のメタデータ