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Cameroon's Lessons in Conservation for Sub-Saharan Africa

Name: Cameroon's Lessons in Conservation for Sub-Saharan Africa
Creator: Peh, Kelvin S.-H.
Keywords: 02110801 Energy policy/Renewable energy commercialization/Renewable energy, 2. Zero hunger, 13. Climate action, 020209 energy, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 634, 021108 energy, 02 engineering and technology, 15. Life on land

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 Sep 2008 United Kingdom Publisher:Oxford University Press (OUP)Journal:BioScience, volume 58, pages 678-679 (issn: 0006-3568, eissn: 1525-3244,

Authors: Peh, Kelvin S.-H.;

doi: 10.1641/b580802

Cameroon's Lessons in Conservation for Sub-Saharan Africa

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Abstract

The editorial discusses the need for Sub-Saharan Africa to improve its standards of nature conservation and environmental protection. The author addresses the need to prevent illegal tree cutting, including harvesting wood for fuel and agricultural forest clearance, as well as the need to eliminate invasive species and poaching. Particular attention is given to the difficulties facing conservation efforts in the country of Cameroon.

Country

United Kingdom

Related Organizations

University of Southampton
United Kingdom

Keywords

634, 333

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	3
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average