Using integrated population models for insights into monitoring programs:An application using pink-footed geese
Development of integrated population models (IPMs) assume the absence of systematic bias in monitoring programs, yet many potential sources of systematic bias in monitoring data exist (e.g., under-counts of abundance). By integrating multiple sources of data, we can assess whether various sources of...
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2020
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Online Access: | https://orbit.dtu.dk/en/publications/05425d9b-36fd-4d01-8b73-cd6f92f9453a https://doi.org/10.1016/j.ecolmodel.2019.108869 |
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ftdtupubl:oai:pure.atira.dk:publications/05425d9b-36fd-4d01-8b73-cd6f92f9453a 2023-12-24T10:08:26+01:00 Using integrated population models for insights into monitoring programs:An application using pink-footed geese Johnson, Fred A. Zimmerman, Guthrie S. Jensen, Gitte H. Clausen, Kevin K. Frederiksen, Morten Madsen, Jesper 2020 https://orbit.dtu.dk/en/publications/05425d9b-36fd-4d01-8b73-cd6f92f9453a https://doi.org/10.1016/j.ecolmodel.2019.108869 eng eng https://orbit.dtu.dk/en/publications/05425d9b-36fd-4d01-8b73-cd6f92f9453a info:eu-repo/semantics/closedAccess Johnson , F A , Zimmerman , G S , Jensen , G H , Clausen , K K , Frederiksen , M & Madsen , J 2020 , ' Using integrated population models for insights into monitoring programs : An application using pink-footed geese ' , Ecological Modelling , vol. 415 , 108869 . https://doi.org/10.1016/j.ecolmodel.2019.108869 Bias Capture-mark-resight Demography Integrated population model Monitoring Pink-footed goose article 2020 ftdtupubl https://doi.org/10.1016/j.ecolmodel.2019.108869 2023-11-30T00:03:19Z Development of integrated population models (IPMs) assume the absence of systematic bias in monitoring programs, yet many potential sources of systematic bias in monitoring data exist (e.g., under-counts of abundance). By integrating multiple sources of data, we can assess whether various sources of monitoring data provide consistent inferences about changes in population size and, thus, whether monitoring programs appear unbiased. For the purposes of understanding how IPMs could provide insights for monitoring programs, we used the Svalbard breeding population of pink-footed goose (Anser brachyrhynchus) as a case study. The Svalbard pink-footed goose is a well-studied species, the focus of the first adaptive-harvest-management program in Europe, and the subject of a variety of long-term monitoring programs. We examined two formulations of an IPM, but ultimately relied on the one that provided a satisfactory fit to all the available data as based on Chi-squared goodness of fit tests. Our analyses suggest a negative bias in November counts (-20 %), a negative bias in capture-mark-recapture estimates of survival (-3 %), and a negative bias in indices of productivity (-23 %). We offer possible explanations for these biases, whether the degree of bias seems reasonable considering those explanations, and how bias might be investigated directly and ultimately avoided or corrected. Finally, we discuss implications of our work for developing IPMs and associated monitoring programs for managing pink-footed geese and other waterbird species. Article in Journal/Newspaper Anser brachyrhynchus Pink-footed Goose Svalbard Technical University of Denmark: DTU Orbit Svalbard Ecological Modelling 415 108869 |
institution |
Open Polar |
collection |
Technical University of Denmark: DTU Orbit |
op_collection_id |
ftdtupubl |
language |
English |
topic |
Bias Capture-mark-resight Demography Integrated population model Monitoring Pink-footed goose |
spellingShingle |
Bias Capture-mark-resight Demography Integrated population model Monitoring Pink-footed goose Johnson, Fred A. Zimmerman, Guthrie S. Jensen, Gitte H. Clausen, Kevin K. Frederiksen, Morten Madsen, Jesper Using integrated population models for insights into monitoring programs:An application using pink-footed geese |
topic_facet |
Bias Capture-mark-resight Demography Integrated population model Monitoring Pink-footed goose |
description |
Development of integrated population models (IPMs) assume the absence of systematic bias in monitoring programs, yet many potential sources of systematic bias in monitoring data exist (e.g., under-counts of abundance). By integrating multiple sources of data, we can assess whether various sources of monitoring data provide consistent inferences about changes in population size and, thus, whether monitoring programs appear unbiased. For the purposes of understanding how IPMs could provide insights for monitoring programs, we used the Svalbard breeding population of pink-footed goose (Anser brachyrhynchus) as a case study. The Svalbard pink-footed goose is a well-studied species, the focus of the first adaptive-harvest-management program in Europe, and the subject of a variety of long-term monitoring programs. We examined two formulations of an IPM, but ultimately relied on the one that provided a satisfactory fit to all the available data as based on Chi-squared goodness of fit tests. Our analyses suggest a negative bias in November counts (-20 %), a negative bias in capture-mark-recapture estimates of survival (-3 %), and a negative bias in indices of productivity (-23 %). We offer possible explanations for these biases, whether the degree of bias seems reasonable considering those explanations, and how bias might be investigated directly and ultimately avoided or corrected. Finally, we discuss implications of our work for developing IPMs and associated monitoring programs for managing pink-footed geese and other waterbird species. |
format |
Article in Journal/Newspaper |
author |
Johnson, Fred A. Zimmerman, Guthrie S. Jensen, Gitte H. Clausen, Kevin K. Frederiksen, Morten Madsen, Jesper |
author_facet |
Johnson, Fred A. Zimmerman, Guthrie S. Jensen, Gitte H. Clausen, Kevin K. Frederiksen, Morten Madsen, Jesper |
author_sort |
Johnson, Fred A. |
title |
Using integrated population models for insights into monitoring programs:An application using pink-footed geese |
title_short |
Using integrated population models for insights into monitoring programs:An application using pink-footed geese |
title_full |
Using integrated population models for insights into monitoring programs:An application using pink-footed geese |
title_fullStr |
Using integrated population models for insights into monitoring programs:An application using pink-footed geese |
title_full_unstemmed |
Using integrated population models for insights into monitoring programs:An application using pink-footed geese |
title_sort |
using integrated population models for insights into monitoring programs:an application using pink-footed geese |
publishDate |
2020 |
url |
https://orbit.dtu.dk/en/publications/05425d9b-36fd-4d01-8b73-cd6f92f9453a https://doi.org/10.1016/j.ecolmodel.2019.108869 |
geographic |
Svalbard |
geographic_facet |
Svalbard |
genre |
Anser brachyrhynchus Pink-footed Goose Svalbard |
genre_facet |
Anser brachyrhynchus Pink-footed Goose Svalbard |
op_source |
Johnson , F A , Zimmerman , G S , Jensen , G H , Clausen , K K , Frederiksen , M & Madsen , J 2020 , ' Using integrated population models for insights into monitoring programs : An application using pink-footed geese ' , Ecological Modelling , vol. 415 , 108869 . https://doi.org/10.1016/j.ecolmodel.2019.108869 |
op_relation |
https://orbit.dtu.dk/en/publications/05425d9b-36fd-4d01-8b73-cd6f92f9453a |
op_rights |
info:eu-repo/semantics/closedAccess |
op_doi |
https://doi.org/10.1016/j.ecolmodel.2019.108869 |
container_title |
Ecological Modelling |
container_volume |
415 |
container_start_page |
108869 |
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1786200548846862336 |