Adaptive Management of Renewable Resources.

Clicks: 3
ID: 289885
1987
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #110 of 238 articles by views in biometrics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 238 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The author challenges the traditional approach to dealing with uncertainty in the management of such renewable resources as fish and wildlife. He argues that scientific understanding will come from the experience of management as an ongoing, adaptive, and experimental process, rather than through basic research or the development of ecological theory. The opening chapters review approaches to formulating management objectives as well as models for understanding how policy choices affect the attainment of these objectives. Subsequent chapters present various statistical methods for understanding the dynamics of uncertainty in managed fish and wildlife populations and for seeking optimum harvest policies in the face of uncertainty. The book concludes with a look at prospects for adaptive management of complex systems, emphasizing such human factors involved in decision making as risk aversion and conflicting objectives as well as biophysical factors. Throughout the text dynamic models and Bayesian statistical theory are used as tools for understanding the behavior of managed systems. These tools are illustrated with simple graphs and plots of data from representative cases. This text/reference will serve researchers, graduate students, and resource managers who formulate harvest policies and study the dynamics of harvest populations, as well as analysts (modelers, statisticians, and stock assessment experts) who are concerned with the practice of policy design.
Reference Key
openalex_W2042464037 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Amy Rutherford, Caroline E. Walters
Journal biometrics
Year 1987
DOI
10.2307/2531565
URL
https://doi.org/10.2307/2531565
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.