Integrated population models poorly estimate the demographic contribution of immigration
1. Estimating the contribution of demographic parameters to changes in population growth is essential for understanding why populations fluctuate. Integrated population models (IPMs) offer a possibility to estimate the contributions of additional demographic parameters, for which no data have been e...
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Online Access: | https://hdl.handle.net/11250/3000035 https://doi.org/10.1111/2041-210X.13667 |
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fthsinnlandet:oai:brage.inn.no:11250/3000035 2024-03-03T08:43:29+00:00 Integrated population models poorly estimate the demographic contribution of immigration Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl Nicoll, MAC Norris, K Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew 2021 application/pdf https://hdl.handle.net/11250/3000035 https://doi.org/10.1111/2041-210X.13667 eng eng Methods in Ecology and Evolution. 2021, 12 (10), 1899-1910. urn:issn:2041-210X https://hdl.handle.net/11250/3000035 https://doi.org/10.1111/2041-210X.13667 cristin:1999610 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no 1899-1910 12 Methods in Ecology and Evolution 10 immigration integrated population models parameter estimation transient Life Table Response Experiment contribution VDP::Matematikk og Naturvitenskap: 400 Peer reviewed Journal article 2021 fthsinnlandet https://doi.org/10.1111/2041-210X.13667 2024-02-02T12:42:31Z 1. Estimating the contribution of demographic parameters to changes in population growth is essential for understanding why populations fluctuate. Integrated population models (IPMs) offer a possibility to estimate the contributions of additional demographic parameters, for which no data have been explicitly collected— typically immigration. Such parameters are often subsequently highlighted as important drivers of population growth. Yet, accuracy in estimating their temporal variation, and consequently their contribution to changes in population growth rate, has not been investigated. 2. To quantify the magnitude and cause of potential biases when estimating the contribution of immigration using IPMs, we simulated data (using northern wheatear Oenanthe oenanthe population estimates) from controlled scenarios to examine potential biases and how they depend on IPM parameterization, formulation of priors, the level of temporal variation in immigration and sample size. We also used empirical data on populations with known rates of immigration: Soay sheep Ovis aries and Mauritius kestrel Falco punctatus with zero immigration and grey wolf Canis lupus in Scandinavia with near-zero immigration. 3. IPMs strongly overestimated the contribution of immigration to changes in population growth in scenarios when immigration was simulated with zero temporal variation (proportion of variance attributed to immigration = 63% for the more constrained formulation and real sample size) and in the wild populations, where the true number of immigrants was zero or near-zero (kestrel 19.1%–98.2%, sheep 4.2%– 36.1% and wolf 84.0%–99.2%). Although the estimation of the contribution of immigration in the simulation study became more accurate with increasing temporal variation and sample size, it was often not possible to distinguish between an accurate estimation from data with high temporal variation versus an overestimation from data with low temporal variation. Unrealistically, large sample sizes may be required to estimate the ... Article in Journal/Newspaper Canis lupus Høgskolen i Innlandet: Brage INN Methods in Ecology and Evolution 12 10 1899 1910 |
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Open Polar |
collection |
Høgskolen i Innlandet: Brage INN |
op_collection_id |
fthsinnlandet |
language |
English |
topic |
immigration integrated population models parameter estimation transient Life Table Response Experiment contribution VDP::Matematikk og Naturvitenskap: 400 |
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immigration integrated population models parameter estimation transient Life Table Response Experiment contribution VDP::Matematikk og Naturvitenskap: 400 Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl Nicoll, MAC Norris, K Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew Integrated population models poorly estimate the demographic contribution of immigration |
topic_facet |
immigration integrated population models parameter estimation transient Life Table Response Experiment contribution VDP::Matematikk og Naturvitenskap: 400 |
description |
1. Estimating the contribution of demographic parameters to changes in population growth is essential for understanding why populations fluctuate. Integrated population models (IPMs) offer a possibility to estimate the contributions of additional demographic parameters, for which no data have been explicitly collected— typically immigration. Such parameters are often subsequently highlighted as important drivers of population growth. Yet, accuracy in estimating their temporal variation, and consequently their contribution to changes in population growth rate, has not been investigated. 2. To quantify the magnitude and cause of potential biases when estimating the contribution of immigration using IPMs, we simulated data (using northern wheatear Oenanthe oenanthe population estimates) from controlled scenarios to examine potential biases and how they depend on IPM parameterization, formulation of priors, the level of temporal variation in immigration and sample size. We also used empirical data on populations with known rates of immigration: Soay sheep Ovis aries and Mauritius kestrel Falco punctatus with zero immigration and grey wolf Canis lupus in Scandinavia with near-zero immigration. 3. IPMs strongly overestimated the contribution of immigration to changes in population growth in scenarios when immigration was simulated with zero temporal variation (proportion of variance attributed to immigration = 63% for the more constrained formulation and real sample size) and in the wild populations, where the true number of immigrants was zero or near-zero (kestrel 19.1%–98.2%, sheep 4.2%– 36.1% and wolf 84.0%–99.2%). Although the estimation of the contribution of immigration in the simulation study became more accurate with increasing temporal variation and sample size, it was often not possible to distinguish between an accurate estimation from data with high temporal variation versus an overestimation from data with low temporal variation. Unrealistically, large sample sizes may be required to estimate the ... |
format |
Article in Journal/Newspaper |
author |
Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl Nicoll, MAC Norris, K Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew |
author_facet |
Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl Nicoll, MAC Norris, K Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew |
author_sort |
Paquet, Matthieu |
title |
Integrated population models poorly estimate the demographic contribution of immigration |
title_short |
Integrated population models poorly estimate the demographic contribution of immigration |
title_full |
Integrated population models poorly estimate the demographic contribution of immigration |
title_fullStr |
Integrated population models poorly estimate the demographic contribution of immigration |
title_full_unstemmed |
Integrated population models poorly estimate the demographic contribution of immigration |
title_sort |
integrated population models poorly estimate the demographic contribution of immigration |
publishDate |
2021 |
url |
https://hdl.handle.net/11250/3000035 https://doi.org/10.1111/2041-210X.13667 |
genre |
Canis lupus |
genre_facet |
Canis lupus |
op_source |
1899-1910 12 Methods in Ecology and Evolution 10 |
op_relation |
Methods in Ecology and Evolution. 2021, 12 (10), 1899-1910. urn:issn:2041-210X https://hdl.handle.net/11250/3000035 https://doi.org/10.1111/2041-210X.13667 cristin:1999610 |
op_rights |
Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no |
op_doi |
https://doi.org/10.1111/2041-210X.13667 |
container_title |
Methods in Ecology and Evolution |
container_volume |
12 |
container_issue |
10 |
container_start_page |
1899 |
op_container_end_page |
1910 |
_version_ |
1792498919920369664 |