Forest and Land Management in Imperial China, N. Menzies

Автор: Bettinger, Pete
Название: Forest Management and Planning
ISBN: 0128094761 ISBN-13(EAN): 9780128094761
Издательство: Elsevier Science
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Цена: 13978.00 р.
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Описание:

Forest Management and Planning, Second Edition, addresses contemporary forest management planning issues, providing a concise, focused resource for those in forest management. The book is intermixed with chapters that concentrate on quantitative subjects, such as economics and linear programming, and qualitative chapters that provide discussions of important aspects of natural resource management, such as sustainability.

Expanded coverage includes a case study of a closed canopy, uneven-aged forest, new forest plans from South America and Oceania, and a new chapter on scenario planning and climate change adaptation.

Автор: N. Menzies
Название: Forest and Land Management in Imperial China
ISBN: 0312102542 ISBN-13(EAN): 9780312102548
Издательство: Springer
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Цена: 23757.00 р.
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Описание: It uses historical evidence to show that individuals and communities act to manage resources sustainably for a number of reasons including economic benefit, religious or symbolic purposes, and that sustainability of the management system depends on the form of control exerted over the resource.

Автор: Herman Hidayat
Название: Forest Resources Management in Indonesia (1968-2004)
ISBN: 9812877444 ISBN-13(EAN): 9789812877444
Издательство: Springer
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Цена: 16979.00 р.
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Описание: It makes a valuable contribution to forest sciences and will also be useful to those in non-government organizations, politicians and business men with an interest in forest resources management, or a deeper interest in Indonesia.

Автор: Hubert Hasenauer
Название: Sustainable Forest Management
ISBN: 3642065511 ISBN-13(EAN): 9783642065514
Издательство: Springer
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Цена: 28732.00 р.
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Описание: There is a strong movement towards uneven-aged forest management based on the idea that such stands increase or at least maintain soil fertility, increase biodiversity, and improve stand resilience. Among potential alternatives are tree growth models, because they predict the growth of each tree within a forest stand.