Data from: Integrated population models poorly estimate the demographic contribution of immigration
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 contributions of additional demographic parameters, for which no data have been explicit...
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ftzenodo:oai:zenodo.org:4995291 2023-06-06T11:52:41+02:00 Data from: Integrated population models poorly estimate the demographic contribution of immigration Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl G. Nicoll, Malcolm A. C. Norris, Ken Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew 2021-06-19 https://zenodo.org/record/4995291 https://doi.org/10.5061/dryad.xd2547dh0 unknown https://zenodo.org/communities/dryad https://zenodo.org/record/4995291 https://doi.org/10.5061/dryad.xd2547dh0 oai:zenodo.org:4995291 info:eu-repo/semantics/openAccess https://creativecommons.org/publicdomain/zero/1.0/legalcode info:eu-repo/semantics/other dataset 2021 ftzenodo https://doi.org/10.5061/dryad.xd2547dh0 2023-04-13T21:27:24Z 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 contributions of additional demographic parameters, for which no data have been explicitly collected: typically immigration. Such parametersare 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. 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. 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%, Wolf 84.0-99.2%). Although the estimation 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 contribution of immigration well. To minimise ... Dataset Canis lupus Zenodo |
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Open Polar |
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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 contributions of additional demographic parameters, for which no data have been explicitly collected: typically immigration. Such parametersare 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. 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. 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%, Wolf 84.0-99.2%). Although the estimation 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 contribution of immigration well. To minimise ... |
format |
Dataset |
author |
Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl G. Nicoll, Malcolm A. C. Norris, Ken Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew |
spellingShingle |
Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl G. Nicoll, Malcolm A. C. Norris, Ken Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew Data from: Integrated population models poorly estimate the demographic contribution of immigration |
author_facet |
Paquet, Matthieu Knape, Jonas Arlt, Debora Forslund, Pär Pärt, Tomas Flagstad, Øystein Jones, Carl G. Nicoll, Malcolm A. C. Norris, Ken Pemberton, Josephine M. Sand, Håkan Svensson, Linn Tatayah, Vikash Wabakken, Petter Wikenros, Camilla Åkesson, Mikael Low, Matthew |
author_sort |
Paquet, Matthieu |
title |
Data from: Integrated population models poorly estimate the demographic contribution of immigration |
title_short |
Data from: Integrated population models poorly estimate the demographic contribution of immigration |
title_full |
Data from: Integrated population models poorly estimate the demographic contribution of immigration |
title_fullStr |
Data from: Integrated population models poorly estimate the demographic contribution of immigration |
title_full_unstemmed |
Data from: Integrated population models poorly estimate the demographic contribution of immigration |
title_sort |
data from: integrated population models poorly estimate the demographic contribution of immigration |
publishDate |
2021 |
url |
https://zenodo.org/record/4995291 https://doi.org/10.5061/dryad.xd2547dh0 |
genre |
Canis lupus |
genre_facet |
Canis lupus |
op_relation |
https://zenodo.org/communities/dryad https://zenodo.org/record/4995291 https://doi.org/10.5061/dryad.xd2547dh0 oai:zenodo.org:4995291 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/publicdomain/zero/1.0/legalcode |
op_doi |
https://doi.org/10.5061/dryad.xd2547dh0 |
_version_ |
1767958678744334336 |