Demographics of reintroduced populations: Estimation, modeling, and decision analysis
Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within form...
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Published in: | The Journal of wildlife management Vol. 77; no. 6; pp. 1081 - 1093 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Bethesda
Blackwell Publishing Ltd
01-08-2013
Wiley Subscription Services |
Subjects: | |
Online Access: | Get full text |
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Summary: | Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within formal decision-analytic frameworks. Decision analysis is a structured process for informing decision making that recognizes that all decisions have a set of components—objectives, alternative management actions, predictive models, and optimization methods—that can be decomposed, analyzed, and recomposed to facilitate optimal, transparent decisions. Because the outcome of interest in reintroduction efforts is typically population viability or related metrics, models used in decision analysis efforts for reintroductions will need to include population models. In this special section of the Journal of Wildlife Management, we highlight examples of the construction and use of models for informing management decisions in reintroduced populations. In this introductory contribution, we review concepts in decision analysis, population modeling for analysis of decisions in reintroduction settings, and future directions. Increased use of formal decision analysis, including adaptive management, has great potential to inform reintroduction efforts. Adopting these practices will require close collaboration among managers, decision analysts, population modelers, and field biologists. |
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Bibliography: | ArticleID:JWMG590 istex:647A2D74B338B04E69065A819B811DCB26D93D6F ark:/67375/WNG-XP7FGPTG-J ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0022-541X 1937-2817 |
DOI: | 10.1002/jwmg.590 |