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

Registros biológicos
Última versión publicado por Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC) el dic 13, 2021 Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC)

Descargue la última versión de los datos como un Archivo Darwin Core (DwC-A) o los metadatos como EML o RTF:

Datos como un archivo DwC-A descargar 13.536 registros en Inglés (259 KB) - Frecuencia de actualización: desconocido
Metadatos como un archivo EML descargar en Inglés (12 KB)
Metadatos como un archivo RTF descargar en Inglés (10 KB)

Descripción

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

Registros

Los datos en este recurso de registros biológicos han sido publicados como Archivo Darwin Core(DwC-A), el cual es un formato estándar para compartir datos de biodiversidad como un conjunto de una o más tablas de datos. La tabla de datos del core contiene 13.536 registros.

Este IPT archiva los datos y, por lo tanto, sirve como repositorio de datos. Los datos y los metadatos del recurso están disponibles para su descarga en la sección descargas. La tabla versiones enumera otras versiones del recurso que se han puesto a disposición del público y permite seguir los cambios realizados en el recurso a lo largo del tiempo.

Versiones

La siguiente tabla muestra sólo las versiones publicadas del recurso que son de acceso público.

¿Cómo referenciar?

Los usuarios deben citar este trabajo de la siguiente manera:

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

Derechos

Los usuarios deben respetar los siguientes derechos de uso:

El publicador y propietario de los derechos de este trabajo es Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC). Esta obra está bajo una licencia Creative Commons de Atribución/Reconocimiento (CC-BY 4.0).

Registro GBIF

Este recurso ha sido registrado en GBIF con el siguiente UUID: 6690ea02-c607-42a3-871b-da00586cbe54.  Laboratoire d'Ecologie Appliquée/Université d’Abomey-Calavi (LEA/UAC) publica este recurso y está registrado en GBIF como un publicador de datos avalado por GBIF Benin.

Palabras clave

Occurence; Wildlife; Diversity; Forest; Benin; null

Contactos

Majoie A. S ATAYI GUEDEGBE
  • Proveedor De Los Metadatos
  • Originador
  • Punto De Contacto
Searcher
Laboratoire d'Ecologie Appliquée
Cotonou
00229 Cotonou
Littoral
BJ
67196041
John HOUNTON
  • Punto De Contacto
Abomey-Calavi
00229 Abomey-Calavi
Atlantique
BJ
97256894

Cobertura geográfica

Southern Benin

Coordenadas límite Latitud Mínima Longitud Mínima [7,39, 2,42], Latitud Máxima Longitud Máxima [7,546, 2,516]

Cobertura taxonómica

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

Fecha Inicial / Fecha Final 2013-04-02 / 2016-10-01

Datos del proyecto

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/
Fuentes de Financiación The funding of this project is generously provided by JRS Biodiversity Foundation (http://jrsbiodiversity.org/)
Descripción del área de estudio 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.
Descripción del diseño 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.

Personas asociadas al proyecto:

Jean Cossi GANGLO
  • Investigador Principal

Métodos de muestreo

Observational data

Área de Estudio Classified forest of Dogo Ketou
Control de Calidad Field control step. Data entry and formatting. Checking for duplicates.

Descripción de la metodología paso a paso:

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

Metadatos adicionales