CSC is conservation programming and implementation that takes into account the causes and impacts of conflict and the actors involved in order to minimize conflict risks and maximize peace-building opportunities.1 Conservationists participating in the workshop were trained on the principles of CSC, how to identify and analyze key conservation conflicts in each ecosystem, and how to develop appropr [...] Driven by a number of root causes, including the weak application of the law, a lack of awareness of the park's borders, a lack of alternate livelihood options in the region and the continued presence of armed groups in MNP, the conflict threatens the integrity of the park and results in significant tensions between ICCN and the local population. [...] The farms, pasture lands and mines that now occupy the land have fragmented the landscape, effectively blocking animal migrations between the two zones and threatening the biodiversity of the park. [...] Once working groups identified the conflicts affecting their conservation landscapes, these conflicts were then prioritized for further analysis and action, depending on the severity of their human impacts (the damage inflicted by the conflict on community livelihoods) and their conservation impacts (the direct and indirect effects of the conflict on the park and the activities of ICCN). [...] The conflicts with the highest human and conservation impacts (i.e., the conflicts of highest priority) are identified for each protected area in the figures below; those conflicts with the highest combined conservation and human impacts are found in the top left square of each figure (see Figures 3, 4 and 5 below).

Provides a pan-African synthesis of community-based natural resource management (CBNRM), drawing on multiple authors and a wide range of documented experiences from Southern, Eastern, Western and Central Africa. This title discusses the degree to which CBNRM has met poverty alleviation, economic development and nature conservation objectives.

The 2010 State of the Forest report (SOF) benefited from financial support from the European Union, the United States, Germany, France and UNESCO. It represents the collaborative effort of over 100 individuals from a diversity of institutions and the forestry administrations of the Central African countries. The SOF process began with the selection and definition of indicators relevant to monitoring the state of forests in Central Africa. The indicators are structured around three thematic areas: (i) forest cover; (ii) management of production forests; and (iii) conservation and biodiversity. They are presented in a hierarchical structure at the regional, national and management unit (i.e. logging concessions and protected areas) levels. The indicators were vetted by a representative panel of stakeholders of forest management in Central Africa. The indicators are used to guide an annual data collection process carried out between April and August by national groups of four to ten individuals working within the forestry administrations. The data reported on in the 2010 SOF were primarily collected in 2009 and 2010. Results were validated in national workshops attended by government officials as well as representatives of environmental NGOs, the private sector and development projects. The data provided an important basis for the authors of the 11 chapters of the 2010 SOF, which were under the coordination of a scientific committee of international renown. A final workshop was held 29-30 March, 2011 in Douala to review a draft report. Following amendments based on comments from a wide audience of experts the final layout was completed.

With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the use of game theory, machine learning, and optimization.