A Quantitative Inheritance Study in Lodgepole Pine (Pinus Contorta Doug. Ex Loud.). PDF Download

Author: Alistair R. Pfeifer
Publisher:
ISBN:
Category :
Languages : en
Pages : 38

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Author: G. E. Rehfeldt
Publisher:
ISBN:
Category : Forest genetics
Languages : en
Pages : 6

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Book Description

Author: Maria Morgenstern
Publisher: UBC Press
ISBN: 077484177X
Category : Technology & Engineering
Languages : en
Pages : 224

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Book Description
Geographic Variation in Forest Trees is the first book to examine this subject from a world-wide perspective. The author discusses population genetic theory and genetic systems of native North American tree species as they interact with environments in the major climatic regions in the world. He then demonstrates how this knowledge is used to guide seed zoning and seed transfer in silviculture, basing much of his discussion on models developed in Scandinavia and North America. In the final chapter, the author addresses the issue of genetic conservation -- a subject of great concern in the face of accelerated forest destruction, industrial pollution, and climatic change. This comprehensive, well-researched book makes a significant contribution to the knowledge of one of our most important renewable natural resources.

Author:
Publisher:
ISBN:
Category : Forests and forestry
Languages : en
Pages : 852

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Book Description

Author: Pacific Forestry Centre
Publisher:
ISBN: 9780662426233
Category : Forest management
Languages : en
Pages : 304

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Book Description
"This book presents a synthesis of published information on mountain pine beetle (Dendroctonus ponderosae Hopkins [Coleoptera: Scolytidae]) biology and management with an emphasis on lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) forests of western Canada. Intended as a reference for researchers as well as forest managers, the book covers three main subject areas: mountain pine beetle biology, management, and socioeconomic concerns. The chapters on biology cover taxonomy, life history and habits, distribution, insect-host tree interactions, development and survival, epidemiology, and outbreak history. The management section covers management strategy, survey and detection, proactive and preventive management, and decision support tools. The chapters on socioeconomic aspects include an economic examination of management programs and the utilization of post-beetle salvage timber in solid wood, panelboard, pulp and paper products."--Publisher's description.

Author: United States. Forest Service
Publisher: Forest Service
ISBN:
Category : Gardening
Languages : en
Pages : 1240

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Book Description

Author: John Alden
Publisher: Springer Science & Business Media
ISBN: 9780306444807
Category : Medical
Languages : en
Pages : 590

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Book Description
''Required reading for forest scientists.'' -Northeastern Naturalist

Author: Matteo Garbelotto
Publisher: MDPI
ISBN: 3038426717
Category : Science
Languages : en
Pages : 243

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Book Description
This book is a printed edition of the Special Issue "Forest Pathology and Plant Health" that was published in Forests

Author: D. Atkinson
Publisher: Springer Science & Business Media
ISBN: 9400968337
Category : Science
Languages : en
Pages : 503

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Book Description
Proceedings of a Meeting of the IUFRO, Working Party on Root Physiology and Symbiosis

Author: Grant Humphries
Publisher: Springer
ISBN: 3319969781
Category : Science
Languages : en
Pages : 441

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Book Description
Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.