Special Feature

User Panel

My Panel

My Panel

Bookmark Science Articles

Recent News
Bookmark / Share This Science Site

Robust population management under uncertainty for structured population models.

Robust population management under uncertainty for structured population models. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

  • Abstract Text of This Paper
  • Journal Published
  • MeSH Keywords of This Abstract
  • Chemicals and Substances Used in this Paper
  • Grants and Granting Agency of this Research
  • Database Accession Numbers Used in this Paper
  • Related Papers
  • Related Research Tags
  • Rate this Research Paper
  • Robust population management under uncertainty for structured population models. Abstract Text:

    a deinesA Deines,e petersonE Peterson,d boecknerD Boeckner,j boyleJ Boyle,a keighleyA Keighley,j kogutJ Kogut,j lubbenJ Lubben,r rebarberR Rebarber,r ryanR Ryan,b tenhumbergB Tenhumberg,s townleyS Townley,a j tyreA J Tyre,a deinesA Deines,e petersonE Peterson,d boecknerD Boeckner,j boyleJ Boyle,a keighleyA Keighley,j kogutJ Kogut,j lubbenJ Lubben,r rebarberR Rebarber,r ryanR Ryan,b tenhumbergB Tenhumberg,s townleyS Townley,a j tyreA J Tyre,

    Structured population models are increasingly used in decision making, but typically have many entries that are unknown or highly uncertain. We present an approach for the systematic analysis of the effect of uncertainties on long-term population growth or decay. Many decisions for threatened and endangered species are made with poor or no information. We can still make decisions under these circumstances in a manner that is highly defensible, even without making assumptions about the distribution of uncertainty, or limiting ourselves to discussions of single, infinitesimally small changes in the parameters. Suppose that the model (determined by the data) for the population in question predicts long-term growth. Our goal is to determine how uncertain the data can be before the model loses this property. Some uncertainties will maintain long-term growth, and some will lead to long-term decay. The uncertainties are typically structured, and can be described by several parameters. We show how to determine which parameters maintain long-term growth. We illustrate the advantages of the method by applying it to a Peregrine Falcon population. The U.S. Fish and Wildlife Service recently decided to allow minimal harvesting of Peregrine Falcons after their recent removal from the Endangered Species List. Based on published demographic rates, we find that an asymptotic growth rate lambda > 1 is guaranteed with 5% harvest rate up to 3% error in adult survival if no two-year-olds breed, and up to 11% error if all two-year-olds breed. If a population growth rate of 3% or greater is desired, the acceptable error in adult survival decreases to between 1% and 6% depending of the proportion of two-year-olds that breed. These results clearly show the interactions between uncertainties in different parameters, and suggest that a harvest decision at this stage may be premature without solid data on adult survival and the frequency of breeding by young adults.

    Robust population management under uncertainty for structured population models. Publishing Authors By Initials

    a deinesA Deines,e petersonE Peterson,d boecknerD Boeckner,j boyleJ Boyle,a keighleyA Keighley,j kogutJ Kogut,j lubbenJ Lubben,r rebarberR Rebarber,r ryanR Ryan,b tenhumbergB Tenhumberg,s townleyS Townley,aj tyreAJ Tyre,a deinesA Deines,e petersonE Peterson,d boecknerD Boeckner,j boyleJ Boyle,a keighleyA Keighley,j kogutJ Kogut,j lubbenJ Lubben,r rebarberR Rebarber,r ryanR Ryan,b tenhumbergB Tenhumberg,s townleyS Townley,aj tyreAJ Tyre,

    For similar abstracts research abstracts see: abstracts research

    PUBMED ID PMID:

    MEDLINE DATE:

    Robust population management under uncertainty for structured population models. Journal Published:

    PUBLICATION TYPE: Research Support, U.S. Gov't,

    Journal: Ecological applications : a publication of the Eco

    VOLUME: 17

    Page Numbers: 2175-83

    Journal Abbreviation:

    ISSN: 1051-0761

    DAY: 24

    MONTH: Dec

    YEAR: 2007

    Robust population management under uncertainty for structured population models. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 9889808

    Robust population management under uncertainty for structured population models. Keywords Mesh Terms:

    KEYWORDS:

    MESH TERMS:

    Chemical & Substance for Abstract: Robust population management under uncertainty for structured population models. Information

    Substance Name:

    Registry Number:

    Grant and Affiliation Information for Robust population management under uncertainty for structured population models.

    AFFILIATION: Department of Mathematics, Kansas State University, Manhattan, Kansas 66506, USA.

    Country: United States

    United States Research PublicationUnited States Research Publication

    AGENCY:

    GRANT:

    ACRONYM:

    MEDLINETA: Ecol Appl

    REFSOURCE:

    DATABASENAME:

    ACCESSION NUMBER:

    Number Hits: 0

    Robust population management under uncertainty for structured population models Related Publications

     

    Molecular Station USER Menu

    Welcome to Molecular Station!

    You have to register before you can post on our forums or use our advanced features. Register Now! Its Free and Fast!

    Already registered? Login now below.

    User Name:

    Password:

    Already registered and Forgot your password? Click below to recover it.

    Recover Lost Password

    Join now - it's fast and free!

    Molecular Station is THE largest network of researchers, scientists and science lovers anywhere!

    Research Terms of Usage and Disclaimer
    Home
    Features

    Protocols

    DNA Forum

    Science Forum

    DNA Forum
    Biology Forum

    Science News


    [CaRP] XML error: Invalid document end at line 2

    For more click here:Science News