Occurrence

Wildlife diversity of the Dogo-Kétou forest (Benin, West Africa)

Latest version published by Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC) on 13 December 2021 Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC)
The dataset is about the varety of the wildlife of the Dogo-Kétou forest in Benin

Data Records

The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 13,536 records.

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Downloads

Download the latest version of this resource data as a Darwin Core Archive (DwC-A) or the resource metadata as EML or RTF:

Data as a DwC-A file download 13,536 records in English (259 kB) - Update frequency: unknown
Metadata as an EML file download in English (12 kB)
Metadata as an RTF file download in English (10 kB)

Versions

The table below shows only published versions of the resource that are publicly accessible.

How to cite

Researchers should cite this work as follows:

ATAYI GUEDEGBE M A S (2021): Wildlife diversity of the Dogo-Kétou forest (Benin, West Africa). v1.2. Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC). Dataset/Occurrence. http://ipt.gbifbenin.org/resource?r=wildlife_occ&v=1.2

Rights

Researchers should respect the following rights statement:

The publisher and rights holder of this work is Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC). This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: 6690ea02-c607-42a3-871b-da00586cbe54.  Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC) publishes this resource, and is itself registered in GBIF as a data publisher endorsed by GBIF Benin.

Keywords

Occurence; Wildlife; Diversity; Forest; Benin; null

Contacts

Who created the resource:

Majoie A. S ATAYI GUEDEGBE
Searcher
Laboratoire d'Ecologie Appliquée
Cotonou
00229 Cotonou
Littoral
BJ
67196041

Who can answer questions about the resource:

Majoie A. S ATAYI GUEDEGBE
Searcher
Laboratoire d'Ecologie Appliquée
Cotonou
00229 Cotonou
Littoral
BJ
67196041
John HOUNTON
Abomey-Calavi
00229 Abomey-Calavi
Atlantique
BJ
97256894

Who filled in the metadata:

Majoie A. S ATAYI GUEDEGBE
Searcher
Laboratoire d'Ecologie Appliquée
Cotonou
00229 Cotonou
Littoral
BJ
67196041

Who else was associated with the resource:

User

Geographic Coverage

Southern Benin

Bounding Coordinates South West [7.39, 2.42], North East [7.546, 2.516]

Taxonomic Coverage

The classified forest of Dogo-Kétou is located in southern Benin. It is under the influence of a Sudanoguinean climate marked by a bimodal regime.

Kingdom  Animalia (Animal)

Temporal Coverage

Start Date / End Date 2013-04-02 / 2016-10-01

Project Data

Through key objectives, this project is designed to overcome the challenge of lack of capacities in Africa: Objective 1: Build in-depth capacities in biodiversity informatics to students in masters program: At least 20 Beninese students and 10 students of other nationalities will be yearly recruited and fully capacitated in the program (Months 4, 16, 28 and beyond the project) (Output 1). The courses will be recorded and shared worldwide (Outcome 4). Objective 2: Build capacities in biodiversity informatics to other GBIF Benin partners (students and professionals): Through workshops, at least, each year, 50 other GBIF Benin partners will be trained in relevant topics of biodiversity informatics (Months 6, 12, 18, 24, 30, 34 and beyond) (Output 5) Objective 3: Fill data gaps in priority thematic areas of Benin and other countries involved in the project: Trained students will achieve data gaps analysis in priority thematic areas (Months 12 – 36 and beyond) (Output 6) and contribute to fill data gaps (Months 12 – 36 and beyond) (Output 7). Objective 4: Use data to develop appropriate products to inform decisions on biodiversity conservation: Trained students will use data to address needs of information (Months 12 – 36 and beyond) (Output 8) and largely disseminate the results via multimedia (Months 12 – 36 and beyond) (Output 9). Project Objective 5: Enhance staff development: We will provide internship opportunities to strengthen capacities of national trainers and most brilliant students to enable them to sustainably carry on the training of students in the program

Title Regional graduate course for capacity development in biodiversity informatics in Africa
Identifier http://jrsbiodiversity.org/jrs-supports-capacity-development-uac-oxford-2018/ http://jrsbiodiversity.org/grants/uac-2018/
Funding The funding of this project is generously provided by JRS Biodiversity Foundation (http://jrsbiodiversity.org/)
Study Area Description Actually in Benin, we estimate that there are 400 – 600 working biodiversity information scientists in public and private agencies. With few exceptions, the situation is not much different in the rest of African countries. Those biodiversity information scientists usually base their decisions - of biodiversity conservation - on floristic and faunistic compositions of ecosystems and related communities as well as on ecology, ethology and habitat characteristics of different species. This approach becomes limiting to conserve efficiently and sustainably biodiversity in the actual threatening context of climate and global changes exacerbated by diverse pressures on biodiversity. To overcome that limitation, we rather need a critical mass of scientists with sound knowledge in biodiversity informatics to achieve relevant results on spatial distributions, ecological niches… of species and different biota to inform decisions on priority areas of biodiversity. In order to develop a trained cohort to meet national needs, we believe that Benin needs to train at least an additional 20 master students. Additionally, training each year at least 10 other masters and advanced students from different African countries, will result in progressive but efficient creation of homes of biodiversity informatics to enhance biodiversity conservation and sustainable uses throughout Africa.
Design Description Actually in Benin, we estimate that there are 400 – 600 working biodiversity information scientists in public and private agencies. With few exceptions, the situation is not much different in the rest of African countries. Those biodiversity information scientists usually base their decisions - of biodiversity conservation - on floristic and faunistic compositions of ecosystems and related communities as well as on ecology, ethology and habitat characteristics of different species. This approach becomes limiting to conserve efficiently and sustainably biodiversity in the actual threatening context of climate and global changes exacerbated by diverse pressures on biodiversity. To overcome that limitation, we rather need a critical mass of scientists with sound knowledge in biodiversity informatics to achieve relevant results on spatial distributions, ecological niches… of species and different biota to inform decisions on priority areas of biodiversity. In order to develop a trained cohort to meet national needs, we believe that Benin needs to train at least an additional 20 master students. Additionally, training each year at least 10 other masters and advanced students from different African countries, will result in progressive but efficient creation of homes of biodiversity informatics to enhance biodiversity conservation and sustainable uses throughout Africa.

The personnel involved in the project:

Principal Investigator
Jean Cossi GANGLO

Sampling Methods

Observational data

Study Extent Classified forest of Dogo Ketou
Quality Control Field control step. Data entry and formatting. Checking for duplicates.

Method step description:

  1. Field control step. Data entry and formatting. Checking for duplicates.

Additional Metadata