The checklist of alien seed plants of D.R. Congo, based on evidence from herbarium collections

最新版本 published by Meise Botanic Garden on 六月 2, 2022 Meise Botanic Garden
Published by:
Meise Botanic Garden
CC0 1.0

下載最新版本的 Darwin Core Archive (DwC-A) 資源,或資源詮釋資料的 EML 或 RTF 文字檔。

DwC-A資料集 下載 436 紀錄 在 English 中 (47 KB) - 更新頻率: 需要時
元數據EML檔 下載 在 English 中 (11 KB)
元數據RTF文字檔 下載 在 English 中 (13 KB)


The “checklist of alien seed plants of D.R. Congo, based on evidence from herbarium collections” is a species checklist dataset published by the Botanic Garden Meise. It contains information on 436 alien plant species occurring in the Democratic Republic of the Congo, based on evidence from herbarium collections (Bordar & Meerts 2022). The plant species were registered between 1869 and 2017. Here it is published as a standardized Darwin Core Archive and includes for each species: the scientific name, kingdom, family and stable taxon identifier (in the taxon core), the year of first introduction and last assessment in Congo and the degree of establishment (in the distribution extension) and the native range and life form (in the description extension). Issues with the dataset can be reported at

We have released this dataset to the public domain under a Creative Commons Zero waiver. We would appreciate it if you follow the INBO norms for data use ( when using the data. If you have any questions regarding this dataset, don't hesitate to contact us via the contact information provided in the metadata or via


此資源名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 436 筆紀錄。

亦存在 2 筆延伸集的資料表。延伸集中的紀錄補充核心集中紀錄的額外資訊。 每個延伸集資料表中資料筆數顯示如下。

Taxon (核心)

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。





Meerts P, Bordbar F, Reyserhove L (2022): The checklist of alien seed plants of D.R. Congo, based on evidence from herbarium collections. v1.1. Meise Botanic Garden. Dataset/Checklist.



此資料的發布者及權利單位為 Meise Botanic Garden。 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.


此資源已向GBIF註冊,並指定以下之GBIF UUID: f1b442bd-a9b8-4763-a178-95195aa349e7。  Meise Botanic Garden 發佈此資源,並經由Belgian Biodiversity Platform同意向GBIF註冊成為資料發佈者。


Checklist; Inventorythematic; Checklist; alien species; Congo; casual; naturalised; invasive; herbarium; tropical forest


Pierre Meerts
  • 元數據提供者
  • 出處
  • 連絡人
Botanic Garden Meise
Farzaneh Bordbar
  • 出處
University of Brussels
Lien Reyserhove
  • 出處
Research Institute for Nature and Forest (INBO)
Lien Reyershove


The Democratic Republic of the Congo (D.R. Congo), see (Bordar & Meerts 2022) for more details.

界定座標範圍 緯度南界 經度西界 [-13.411, 12.129], 緯度北界 經度東界 [5.178, 31.113]


The checklist comprises 436 alien species i.e., 189 (43%) casuals, 247 (57%) naturalised of which 80 (18% of aliens) are invasive. See (Bordar & Meerts 2022) for more details.

Kingdom Plantae (plants)


起始日期 / 結束日期 1869-01-01 / 2017-12-31


A first list has been compiled from extensive literature search, and other databases. All entries in this list have been checked for presence in herbarium collections, and all identifications have been checked on herbarium specimens. Species collected only in cultivation (based on herbarium specimen labels) have been filtered out. For further details on methodology, see Bordbar & Meerts (2022).

研究範圍 Alien seed plant species occurring outside of cultivation in the Democratic Republic of the Congo, with at least one record in scientific collections (1869--2019).
品質控管 The data is based on material evidence in herbarium collections.


  1. The source data for this standardized sampling event dataset is published as supplementary materials to Bordar & Meerts (2022) and is uploaded to the Github repository of this dataset:
  2. An Rmarkdown script was developed to transform the data to a Darwin Core dataset. This mapping script was uploaded to the Github repository and includes the following steps:
  3. Perform some basic cleaning of the raw data.
  4. Generate stable and unique identifiers for each taxon (taxonID).
  5. Create a taxon core file (
  6. Create a distribution extension (
  7. Create a description extension (


  1. Bordbar F. & Meerts P. (2022) in Biological Invasions 24(4): 939-954.