ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS

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 en...

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Main Authors: A. Deines, E. Peterson, D. Boeckner, J. Boyle, A. Keighley, J. Kogut, J. Lubben, R. Rebarber, R. Ryan, B. Tenhumberg, S. Townley, A. J. Tyre
Format: Article in Journal/Newspaper
Language:unknown
Published: Figshare 2016
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.c.3293867
https://figshare.com/collections/ROBUST_POPULATION_MANAGEMENT_UNDER_UNCERTAINTY_FOR_STRUCTURED_POPULATION_MODELS/3293867
id ftdatacite:10.6084/m9.figshare.c.3293867
record_format openpolar
spelling ftdatacite:10.6084/m9.figshare.c.3293867 2023-05-15T17:55:14+02:00 ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS A. Deines E. Peterson D. Boeckner J. Boyle A. Keighley J. Kogut J. Lubben R. Rebarber R. Ryan B. Tenhumberg S. Townley A. J. Tyre 2016 https://dx.doi.org/10.6084/m9.figshare.c.3293867 https://figshare.com/collections/ROBUST_POPULATION_MANAGEMENT_UNDER_UNCERTAINTY_FOR_STRUCTURED_POPULATION_MODELS/3293867 unknown Figshare https://dx.doi.org/10.1890/06-1090.1 CC-BY http://creativecommons.org/licenses/by/3.0/us CC-BY Environmental Science Ecology FOS Biological sciences Collection article 2016 ftdatacite https://doi.org/10.6084/m9.figshare.c.3293867 https://doi.org/10.1890/06-1090.1 2021-11-05T12:55:41Z 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 λ > 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. Article in Journal/Newspaper peregrine falcon DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Environmental Science
Ecology
FOS Biological sciences
spellingShingle Environmental Science
Ecology
FOS Biological sciences
A. Deines
E. Peterson
D. Boeckner
J. Boyle
A. Keighley
J. Kogut
J. Lubben
R. Rebarber
R. Ryan
B. Tenhumberg
S. Townley
A. J. Tyre
ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
topic_facet Environmental Science
Ecology
FOS Biological sciences
description 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 λ > 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.
format Article in Journal/Newspaper
author A. Deines
E. Peterson
D. Boeckner
J. Boyle
A. Keighley
J. Kogut
J. Lubben
R. Rebarber
R. Ryan
B. Tenhumberg
S. Townley
A. J. Tyre
author_facet A. Deines
E. Peterson
D. Boeckner
J. Boyle
A. Keighley
J. Kogut
J. Lubben
R. Rebarber
R. Ryan
B. Tenhumberg
S. Townley
A. J. Tyre
author_sort A. Deines
title ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_short ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_full ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_fullStr ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_full_unstemmed ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_sort robust population management under uncertainty for structured population models
publisher Figshare
publishDate 2016
url https://dx.doi.org/10.6084/m9.figshare.c.3293867
https://figshare.com/collections/ROBUST_POPULATION_MANAGEMENT_UNDER_UNCERTAINTY_FOR_STRUCTURED_POPULATION_MODELS/3293867
genre peregrine falcon
genre_facet peregrine falcon
op_relation https://dx.doi.org/10.1890/06-1090.1
op_rights CC-BY
http://creativecommons.org/licenses/by/3.0/us
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.c.3293867
https://doi.org/10.1890/06-1090.1
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