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

Ocorrência
Versão mais recente published by Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC) on dez. 13, 2021 Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC)

Baixe a última versão do recurso de dados, como um Darwin Core Archive (DwC-A) ou recurso de metadados, como EML ou RTF:

Dados como um arquivo DwC-A download 13.536 registros em English (259 KB) - Frequência de atualização: desconhecido
Metadados como um arquivo EML download em English (12 KB)
Metadados como um arquivo RTF download em English (10 KB)

Descrição

The dataset is about the varety of the wildlife of the Dogo-Kétou forest in Benin

Registros de Dados

Os dados deste recurso de ocorrência foram publicados como um Darwin Core Archive (DwC-A), que é o formato padronizado para compartilhamento de dados de biodiversidade como um conjunto de uma ou mais tabelas de dados. A tabela de dados do núcleo contém 13.536 registros.

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.

Versões

A tabela abaixo mostra apenas versões de recursos que são publicamente acessíveis.

Como citar

Pesquisadores deveriam citar esta obra da seguinte maneira:

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

Direitos

Pesquisadores devem respeitar a seguinte declaração de direitos:

O editor e o detentor dos direitos deste trabalho é 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

Este recurso foi registrado no GBIF e atribuído ao seguinte GBIF UUID: 6690ea02-c607-42a3-871b-da00586cbe54.  Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC) publica este recurso, e está registrado no GBIF como um publicador de dados aprovado por GBIF Benin.

Palavras-chave

Occurence; Wildlife; Diversity; Forest; Benin; null

Contatos

Majoie A. S ATAYI GUEDEGBE
  • Provedor Dos Metadados
  • Originador
  • Ponto De Contato
Searcher
Laboratoire d'Ecologie Appliquée
Cotonou
00229 Cotonou
Littoral
BJ
67196041
John HOUNTON
  • Ponto De Contato
Abomey-Calavi
00229 Abomey-Calavi
Atlantique
BJ
97256894

Cobertura Geográfica

Southern Benin

Coordenadas delimitadoras Sul Oeste [7,39, 2,42], Norte Leste [7,546, 2,516]

Cobertura Taxonômica

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.

Reino Animalia (Animal)

Cobertura Temporal

Data Inicial / Data final 2013-04-02 / 2016-10-01

Dados Sobre o Projeto

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

Título Regional graduate course for capacity development in biodiversity informatics in Africa
Identificador http://jrsbiodiversity.org/jrs-supports-capacity-development-uac-oxford-2018/ http://jrsbiodiversity.org/grants/uac-2018/
Financiamento The funding of this project is generously provided by JRS Biodiversity Foundation (http://jrsbiodiversity.org/)
Descrição da Área de Estudo 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.
Descrição do Design 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.

O pessoal envolvido no projeto:

Jean Cossi GANGLO
  • Pesquisador Principal

Métodos de Amostragem

Observational data

Área de Estudo Classified forest of Dogo Ketou
Controle de Qualidade Field control step. Data entry and formatting. Checking for duplicates.

Descrição dos passos do método:

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

Metadados Adicionais