Population Harvesting (MPB-27), Volume 27 : : Demographic Models of Fish, Forest, and Animal Resources. (MPB-27) / / Robert G. Haight, Wayne M. Getz.

• Superior document: Title is part of eBook package: De Gruyter Princeton University Press eBook-Package Archive 1927-1999
• VerfasserIn: Getz, Wayne M.,; Haight, Robert G.,
• Place / Publishing House: Princeton, NJ : : Princeton University Press, , [2020]; ©1989
• Year of Publication: 2020
• Language: English
• Series: Monographs in Population Biology ; 105
• Physical Description: 1 online resource (408 p.)
• Other title: Frontmatter --; Contents --; Preface --; 1. Introduction --; 2. Linear Models --; 3. Nonlinear Models --; 4. Fisheries Management --; 5. Forest Management --; 6. Other Resources and Overview --; References --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9780691209630; 9783110442496
• DOI: 10.1515/9780691209630?locatt=mode:legacy
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Robert G. Haight, Wayne M. Getz.

Whether in felling trees for wood, rearing insects for biological control, or culling animals for conservation purposes, efficient management of biological systems requires quantitative analysis of population growth and harvesting policies. Aiming to encourage the exchange of ideas among scientists involved in the management of fisheries, wildlife, forest stands, and pest control, the authors of this work present a general framework for modeling populations that reproduce seasonally and that have age or stage structure as an essential component of management strategy. The book represents the first time that examples from such diverse areas of biological resource management have been brought together in a unified modeling framework using the standard notation of mathematical systems theory. In addition, the authors combine a nonlinear extension of Leslie matrix theory and certain linear elements, thereby permitting interesting analytical results and the creation of compact, realistic simulation models of resource systems.