Examines whether forest management regimes in the region have actually provided communities with sufficient economic benefits to make them willing and able to conserve and to use sustainable forest resources in the course of their production and consumption activities.

Presentations at the workshop organized by the Indian Institute of Forest Management, Bhopal.

Provides a wealth of practical tools and methods for our field workers who work with local communities in developing collaborative management of forests. While the manual focuses on participatory techniques for community forests in Nepal, many of the techniques can be readily applied to other forms of collaborative natural resource management.

The Complex Forest systematically examines the theory, processes, and early outcomes of a research and management approach called adaptive collaborative management (ACM). An alternative to positivist approaches to development and conservation that assume predictability in forest management, ACM acknowledges the complexity and unpredictability inherent in any forest community and the importance of developing solutions together with the forest peoples whose lives will be most affected by the outcomes. Building on earlier work that established the importance of flexible, collaborative approaches to sustainable forest management, The Complex Forest describes the work of ACM practitioners facing a broad range of challenges in diverse settings and attempts to identify the conditions under which ACM is most effective. Case studies of ACM in 33 forest sites in 11 countries together with Colfer's systematic comparison of results at each site indicate that human and institutional capabilities have been strengthened. In Zimbabwe, for example, the number of women involved in decisionmaking soared. In Nepal, community members detected and sanctioned dishonest community elites. In Cameroon and Bolivia, learning programs resulted in better conflict management. These are early results, but a wide range of recent research supports Colfer's belief that these new capabilities will eventually contribute to higher incomes and to sustainable improvements in the health of forests and forest peoples. The Complex Forest reinforces calls for change in the way we plan conservation and development programs, away from command-and-control approaches, toward ones that require bureaucratic flexibility and responsiveness, as well as greater local participation in setting priorities and problem solving.

This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.

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