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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ftrepec:oai:RePEc:eee:ecomod:v:415:y:2020:i:c:s0304380019303771 2024-04-14T08:01:10+00:00 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 http://www.sciencedirect.com/science/article/pii/S0304380019303771 unknown http://www.sciencedirect.com/science/article/pii/S0304380019303771 article ftrepec 2024-03-19T10:31:57Z 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. Bias; Capture-mark-resight; Demography; Integrated population model; Monitoring; Pink-footed goose; Article in Journal/Newspaper Anser brachyrhynchus Pink-footed Goose Svalbard RePEc (Research Papers in Economics) Svalbard |
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RePEc (Research Papers in Economics) |
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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. Bias; Capture-mark-resight; Demography; Integrated population model; Monitoring; Pink-footed goose; |
format |
Article in Journal/Newspaper |
author |
Johnson, Fred A. Zimmerman, Guthrie S. Jensen, Gitte H. Clausen, Kevin K. Frederiksen, Morten Madsen, Jesper |
spellingShingle |
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 |
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 |
url |
http://www.sciencedirect.com/science/article/pii/S0304380019303771 |
geographic |
Svalbard |
geographic_facet |
Svalbard |
genre |
Anser brachyrhynchus Pink-footed Goose Svalbard |
genre_facet |
Anser brachyrhynchus Pink-footed Goose Svalbard |
op_relation |
http://www.sciencedirect.com/science/article/pii/S0304380019303771 |
_version_ |
1796307738765033472 |