Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series
Ecological predictions are necessary for testing whether processes hypothesized to regulate species population dynamics are generalizable across time and space. In order to demonstrate generalizability, model predictions should be transferable in one or more dimensions, where transferability is the...
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Online Access: | https://doi.org/10.1016/j.ecolind.2023.110239 |
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ftncar:oai:drupal-site.org:articles_26310 2023-10-01T03:49:43+02:00 Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series Şen, Bilgecan (author) Che-Castaldo, Christian (author) Krumhardt, Kristen M. (author) Landrum, Laura (author) Holland, Marika M. (author) LaRue, Michelle A. (author) Long, Matthew C. (author) Jenouvrier, Stéphanie (author) Lynch, Heather J. (author) 2023-06 https://doi.org/10.1016/j.ecolind.2023.110239 en eng Ecological Indicators--Ecological Indicators--1470160X articles:26310 doi:10.1016/j.ecolind.2023.110239 ark:/85065/d7qr522v Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. article Text 2023 ftncar https://doi.org/10.1016/j.ecolind.2023.110239 2023-09-04T18:24:26Z Ecological predictions are necessary for testing whether processes hypothesized to regulate species population dynamics are generalizable across time and space. In order to demonstrate generalizability, model predictions should be transferable in one or more dimensions, where transferability is the successful prediction of responses outside of the model data bounds. While much is known as to what makes spatially-oriented models transferable, there is no general consensus as to the spatio-temporal transferability of ecological time series models. Here, we examine whether the intrinsic predictability of a time series, as measured by its complexity, could limit such transferability using an exceptional long-term dataset of Adelie penguin breeding abundance time series collected at 24 colonies around Antarctica. For each colony, we select a suite of environmental variables from the Community Earth System Model, version 2 to predict population growth rates, before assessing how well these environmentally-dependent population models transfer temporally and how reliably temporal signals replicate through space. We show that weighted permutation entropy (WPE), a model-free measure of intrinsic predictability recently introduced to ecology, varies spatially across Adelie penguin populations, perhaps in response to stochastic environmental events. We demonstrate that WPE can strongly limit temporal predictive performance, although this relationship could be weakened if intrinsic predictability is not constant over time. Lastly, we show that WPE can also limit spatial forecast horizon, which we define as the decay in spatial predictive performance with respect to the physical distance between focal colony and predicted colony. Irrespective of intrinsic predictability, spatial forecast horizons for all Adelie penguin breeding colonies included in this study are surprisingly short and our population models often have similar temporal and spatial predictive performance compared to null models based on long-term average growth ... Article in Journal/Newspaper Adelie penguin Antarc* Antarctica OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) Ecological Indicators 150 110239 |
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Open Polar |
collection |
OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) |
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ftncar |
language |
English |
description |
Ecological predictions are necessary for testing whether processes hypothesized to regulate species population dynamics are generalizable across time and space. In order to demonstrate generalizability, model predictions should be transferable in one or more dimensions, where transferability is the successful prediction of responses outside of the model data bounds. While much is known as to what makes spatially-oriented models transferable, there is no general consensus as to the spatio-temporal transferability of ecological time series models. Here, we examine whether the intrinsic predictability of a time series, as measured by its complexity, could limit such transferability using an exceptional long-term dataset of Adelie penguin breeding abundance time series collected at 24 colonies around Antarctica. For each colony, we select a suite of environmental variables from the Community Earth System Model, version 2 to predict population growth rates, before assessing how well these environmentally-dependent population models transfer temporally and how reliably temporal signals replicate through space. We show that weighted permutation entropy (WPE), a model-free measure of intrinsic predictability recently introduced to ecology, varies spatially across Adelie penguin populations, perhaps in response to stochastic environmental events. We demonstrate that WPE can strongly limit temporal predictive performance, although this relationship could be weakened if intrinsic predictability is not constant over time. Lastly, we show that WPE can also limit spatial forecast horizon, which we define as the decay in spatial predictive performance with respect to the physical distance between focal colony and predicted colony. Irrespective of intrinsic predictability, spatial forecast horizons for all Adelie penguin breeding colonies included in this study are surprisingly short and our population models often have similar temporal and spatial predictive performance compared to null models based on long-term average growth ... |
author2 |
Şen, Bilgecan (author) Che-Castaldo, Christian (author) Krumhardt, Kristen M. (author) Landrum, Laura (author) Holland, Marika M. (author) LaRue, Michelle A. (author) Long, Matthew C. (author) Jenouvrier, Stéphanie (author) Lynch, Heather J. (author) |
format |
Article in Journal/Newspaper |
title |
Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series |
spellingShingle |
Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series |
title_short |
Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series |
title_full |
Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series |
title_fullStr |
Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series |
title_full_unstemmed |
Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series |
title_sort |
spatio-temporal transferability of environmentally-dependent population models: insights from the intrinsic predictabilities of adélie penguin abundance time series |
publishDate |
2023 |
url |
https://doi.org/10.1016/j.ecolind.2023.110239 |
genre |
Adelie penguin Antarc* Antarctica |
genre_facet |
Adelie penguin Antarc* Antarctica |
op_relation |
Ecological Indicators--Ecological Indicators--1470160X articles:26310 doi:10.1016/j.ecolind.2023.110239 ark:/85065/d7qr522v |
op_rights |
Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
op_doi |
https://doi.org/10.1016/j.ecolind.2023.110239 |
container_title |
Ecological Indicators |
container_volume |
150 |
container_start_page |
110239 |
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1778526296537563136 |