Pedestrian mammals census in W National Park					

Harissou Yahou1, Sunday Berlioz Kakpo2, Jean Cossi GANGLO3

1 Direction de la Faune de la Chasse et des Aires Protégées, 00227, Niamey, Niger; 2 Laboratory of Forestry Sciences, 04bp1005, 00229, Cotonou, Benin; 3 Laboratory of Forestry Sciences, BP 1493, 00229, Abomey-Calavi, Benin

Corresponding author(s): Harissou Yahou (yharissou2000@yahoo.fr)

Received {date}; Revised {date}; Accepted {date}; Published {date}

Citation: Combination of authors, year of data paper publication (in parentheses), Title, Journal Name, Volume, Issue number (in parentheses), and doi of the data paper.

Resource Citation

Yahou H. 2015. Pedestrian mammals census in W National Park.  Direction de la Faune de la Chasse et des Parcs et Réserves					

Abstract

A census of pedestrian mammals was conduct during the dry season of 2015 in the W National Park using line transects					

Keywords: Occurrence, Artiodactyla, Primates, Carnivora

Project details

Project title: Capacity building and biodiversity data mobilization for conservation, sustainable use, and decision making in Africa and Madagascar
Personnel: Jean Cossi GANGLO
Funding: The funding of this project is generously provided by European Union in the framework of Biodiversity Information for Development program managed by GBIF Secretariat
Study area descriptions/descriptor: The data digitized and published in the framework of this project are gathered throughout the country members on the targeted species
Design description: Despite its utmost importance to the survival of humanity, biodiversity is subject to many threats. As a significant step toward overcoming these threats, we submit this project in the framework of a consortium of eight African countries - Senegal, Côte-d’Ivoire, Mali, Guinea, DRC, Niger, Madagascar, and Benin - to achieve the following goals: 
1) Establish and strengthen international collaborations to mobilize biodiversity data; to achieve that goal, we will identify priority invasive alien species and threatened species to be considered in the consortium. We will organize workshops at regional level under the umbrella of the University of Kansas (USA), our Non-ACP partner, to capacitate project partners. We will digitize and publish data of consortium countries deposited in France, Netherlands, and Belgium. 
2) Increase available biodiversity data, within and beyond the grant period, by capacitating and providing financial assistance to in-country partners to encourage them mobilize and publish their data through GBIF and national portals. 
3) Apply biodiversity data in response to conservation priorities by achieving the following: elaborate distribution maps of threatened species and invasive alien species; identify the main threats to species and suggest efficient actions to protect and conserve them; identify and suggest efficient actions to monitor and eradicate invasive alien species; evaluate the efficiency of protected areas with respect to biodiversity conservation and make adequate suggestions; finally, from our results, elaborate and broadcast communication and outreach via diverse media so as to demonstrate to policy- and decision-makers the value chain: data → knowledge → applications.

Data published through GBIF: http://ipt.gbifbenin.org/resource?r=mammals_survey_niger

Spatial coverage

General spatial coverage: Niger is bordering Burkina Faso and Benin. Note that borders are not well defined
Coordinates: 12°33'53.03''N and 12°2'43.25''N Latitude; 2°6'8.76''E and 2°45'11.91''E Longitude 

Temporal coverage: March 5, 2015 - March 9, 2015

Datasets

Dataset description
Object name: Darwin Core Archive Pedestrian mammals census in W National Park					
Character encoding: UTF-8
Format name: Darwin Core Archive format
Format version: 1.0
Distribution: http://ipt.gbifbenin.org/archive.do?r=mammals_survey_niger
Publication date of data: 2018-08-28
Language: French
Licences of use: Creative Commons Attribution (CC-BY) 4.0 License

Metadata language: English
Date of metadata creation: 2018-08-28
Hierarchy level: Dataset