Data from: Improving structured population models with more realistic representations of non-normal growth
1. Structured population models are among the most widely used tools in ecology and evolution. Integral projection models (IPMs) use continuous representations of how survival, reproduction, and growth change as functions of state variables such as size, requiring fewer parameters to be estimated th...
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ftzenodo:oai:zenodo.org:4937747 2024-09-15T18:31:29+00:00 Data from: Improving structured population models with more realistic representations of non-normal growth Peterson, Megan L. Morris, William Linares, Cristina Doak, Daniel 2019-06-14 https://doi.org/10.5061/dryad.t6c3573 unknown Zenodo https://doi.org/10.1111/2041-210x.13240 https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.t6c3573 oai:zenodo.org:4937747 info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode Bistorta vivipara Vulpicida pinastri skewed normal Polygonum viviparum matrix model Asymmetry Beta regression integral projection model quantile regression population model skew Paramuricea clavata info:eu-repo/semantics/other 2019 ftzenodo https://doi.org/10.5061/dryad.t6c357310.1111/2041-210x.13240 2024-07-27T02:11:09Z 1. Structured population models are among the most widely used tools in ecology and evolution. Integral projection models (IPMs) use continuous representations of how survival, reproduction, and growth change as functions of state variables such as size, requiring fewer parameters to be estimated than projection matrix models (PPMs). Yet almost all published IPMs make an important assumption: that size-dependent growth transitions are or can be transformed to be normally distributed. In fact, many organisms exhibit highly skewed size transitions. Small individuals can grow more than they can shrink, and large individuals may often shrink more dramatically than they can grow. Yet the implications of such skew for inference from IPMs has not been explored, nor have general methods been developed to incorporate skewed size transitions into IPMs, or deal with other aspects of real growth rates, including bounds on possible growth or shrinkage. 2. Here we develop a flexible approach to modeling skewed growth data using a modified beta regression model. We propose that sizes first be converted to a (0,1) interval by estimating size-dependent minimum and maximum sizes through quantile regression. Transformed data can then be modeled using beta regression with widely available statistical tools. We demonstrate the utility of this approach using demographic data for a long-lived plant, gorgonians, and an epiphytic lichen. Specifically, we compare inferences of population parameters from discrete PPMs to those from IPMs that either assume normality or incorporate skew using beta regression or, alternatively, a skewed normal model. 3. The beta and skewed normal distributions accurately capture the mean, variance, and skew of real growth distributions. Incorporating skewed growth into IPMs decreases population growth and estimated lifespan relative to IPMs that assume normally-distributed growth, and more closely approximate the parameters of PPMs that do not assume a particular growth distribution. A bounded distribution, ... Other/Unknown Material Polygonum viviparum Zenodo |
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Bistorta vivipara Vulpicida pinastri skewed normal Polygonum viviparum matrix model Asymmetry Beta regression integral projection model quantile regression population model skew Paramuricea clavata |
spellingShingle |
Bistorta vivipara Vulpicida pinastri skewed normal Polygonum viviparum matrix model Asymmetry Beta regression integral projection model quantile regression population model skew Paramuricea clavata Peterson, Megan L. Morris, William Linares, Cristina Doak, Daniel Data from: Improving structured population models with more realistic representations of non-normal growth |
topic_facet |
Bistorta vivipara Vulpicida pinastri skewed normal Polygonum viviparum matrix model Asymmetry Beta regression integral projection model quantile regression population model skew Paramuricea clavata |
description |
1. Structured population models are among the most widely used tools in ecology and evolution. Integral projection models (IPMs) use continuous representations of how survival, reproduction, and growth change as functions of state variables such as size, requiring fewer parameters to be estimated than projection matrix models (PPMs). Yet almost all published IPMs make an important assumption: that size-dependent growth transitions are or can be transformed to be normally distributed. In fact, many organisms exhibit highly skewed size transitions. Small individuals can grow more than they can shrink, and large individuals may often shrink more dramatically than they can grow. Yet the implications of such skew for inference from IPMs has not been explored, nor have general methods been developed to incorporate skewed size transitions into IPMs, or deal with other aspects of real growth rates, including bounds on possible growth or shrinkage. 2. Here we develop a flexible approach to modeling skewed growth data using a modified beta regression model. We propose that sizes first be converted to a (0,1) interval by estimating size-dependent minimum and maximum sizes through quantile regression. Transformed data can then be modeled using beta regression with widely available statistical tools. We demonstrate the utility of this approach using demographic data for a long-lived plant, gorgonians, and an epiphytic lichen. Specifically, we compare inferences of population parameters from discrete PPMs to those from IPMs that either assume normality or incorporate skew using beta regression or, alternatively, a skewed normal model. 3. The beta and skewed normal distributions accurately capture the mean, variance, and skew of real growth distributions. Incorporating skewed growth into IPMs decreases population growth and estimated lifespan relative to IPMs that assume normally-distributed growth, and more closely approximate the parameters of PPMs that do not assume a particular growth distribution. A bounded distribution, ... |
format |
Other/Unknown Material |
author |
Peterson, Megan L. Morris, William Linares, Cristina Doak, Daniel |
author_facet |
Peterson, Megan L. Morris, William Linares, Cristina Doak, Daniel |
author_sort |
Peterson, Megan L. |
title |
Data from: Improving structured population models with more realistic representations of non-normal growth |
title_short |
Data from: Improving structured population models with more realistic representations of non-normal growth |
title_full |
Data from: Improving structured population models with more realistic representations of non-normal growth |
title_fullStr |
Data from: Improving structured population models with more realistic representations of non-normal growth |
title_full_unstemmed |
Data from: Improving structured population models with more realistic representations of non-normal growth |
title_sort |
data from: improving structured population models with more realistic representations of non-normal growth |
publisher |
Zenodo |
publishDate |
2019 |
url |
https://doi.org/10.5061/dryad.t6c3573 |
genre |
Polygonum viviparum |
genre_facet |
Polygonum viviparum |
op_relation |
https://doi.org/10.1111/2041-210x.13240 https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.t6c3573 oai:zenodo.org:4937747 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode |
op_doi |
https://doi.org/10.5061/dryad.t6c357310.1111/2041-210x.13240 |
_version_ |
1810473198500708352 |