Inferring the effect of species interactions on trait evolution
Models of trait evolution form an important part of macroevolutionary biology. The Brownian motion model and Ornstein-Uhlenbeck models have become classic (null) models of character evolution, in which species evolve independently. Recently, models incorporating species interactions have been develo...
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Online Access: | https://hdl.handle.net/11370/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 https://research.rug.nl/en/publications/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 https://doi.org/10.1093/sysbio/syaa072 https://pure.rug.nl/ws/files/175268947/syaa072.pdf |
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ftunigroningenpu:oai:pure.rug.nl:publications/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 2024-09-15T17:57:26+00:00 Inferring the effect of species interactions on trait evolution Xu, Liang van Doorn, Sander Hildenbrandt, Hanno Etienne, Rampal S 2021-05 application/pdf https://hdl.handle.net/11370/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 https://research.rug.nl/en/publications/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 https://doi.org/10.1093/sysbio/syaa072 https://pure.rug.nl/ws/files/175268947/syaa072.pdf eng eng https://research.rug.nl/en/publications/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 info:eu-repo/semantics/openAccess Xu , L , van Doorn , S , Hildenbrandt , H & Etienne , R S 2021 , ' Inferring the effect of species interactions on trait evolution ' , Systematic biology , vol. 70 , no. 3 , pp. 463–479 . https://doi.org/10.1093/sysbio/syaa072 article 2021 ftunigroningenpu https://doi.org/10.1093/sysbio/syaa072 2024-07-01T14:49:23Z Models of trait evolution form an important part of macroevolutionary biology. The Brownian motion model and Ornstein-Uhlenbeck models have become classic (null) models of character evolution, in which species evolve independently. Recently, models incorporating species interactions have been developed, particularly involving competition where abiotic factors pull species toward an optimal trait value and competitive interactions drive the trait values apart. However, these models assume a fitness function rather than derive it from population dynamics and they do not consider dynamics of the trait variance. Here we develop a general coherent trait evolution framework where the fitness function is based on a model of population dynamics, and therefore it can, in principle, accommodate any type of species interaction. We illustrate our framework with a model of abundance-dependent competitive interactions against a macroevolutionary background encoded in a phylogenetic tree. We develop an inference tool based on Approximate Bayesian Computation and test it on simulated data (of traits at the tips). We find that inference performs well when the diversity predicted by the parameters equals the number of species in the phylogeny. We then fit the model to empirical data of baleen whale body lengths, using three different summary statistics, and compare it to a model without population dynamics and a model where competition depends on the total metabolic rate of the competitors. We show that the unweighted model performs best for the least informative summary statistic, while the model with competition weighted by the total metabolic rate fits the data slightly better than the other two models for the two more informative summary statistics. Regardless of the summary statistic used, the three models substantially differ in their predictions of the abundance distribution. Therefore, data on abundance distributions will allow us to better distinguish the models from one another, and infer the nature of species ... Article in Journal/Newspaper baleen whale University of Groningen research database Systematic Biology 70 3 463 479 |
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Open Polar |
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University of Groningen research database |
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ftunigroningenpu |
language |
English |
description |
Models of trait evolution form an important part of macroevolutionary biology. The Brownian motion model and Ornstein-Uhlenbeck models have become classic (null) models of character evolution, in which species evolve independently. Recently, models incorporating species interactions have been developed, particularly involving competition where abiotic factors pull species toward an optimal trait value and competitive interactions drive the trait values apart. However, these models assume a fitness function rather than derive it from population dynamics and they do not consider dynamics of the trait variance. Here we develop a general coherent trait evolution framework where the fitness function is based on a model of population dynamics, and therefore it can, in principle, accommodate any type of species interaction. We illustrate our framework with a model of abundance-dependent competitive interactions against a macroevolutionary background encoded in a phylogenetic tree. We develop an inference tool based on Approximate Bayesian Computation and test it on simulated data (of traits at the tips). We find that inference performs well when the diversity predicted by the parameters equals the number of species in the phylogeny. We then fit the model to empirical data of baleen whale body lengths, using three different summary statistics, and compare it to a model without population dynamics and a model where competition depends on the total metabolic rate of the competitors. We show that the unweighted model performs best for the least informative summary statistic, while the model with competition weighted by the total metabolic rate fits the data slightly better than the other two models for the two more informative summary statistics. Regardless of the summary statistic used, the three models substantially differ in their predictions of the abundance distribution. Therefore, data on abundance distributions will allow us to better distinguish the models from one another, and infer the nature of species ... |
format |
Article in Journal/Newspaper |
author |
Xu, Liang van Doorn, Sander Hildenbrandt, Hanno Etienne, Rampal S |
spellingShingle |
Xu, Liang van Doorn, Sander Hildenbrandt, Hanno Etienne, Rampal S Inferring the effect of species interactions on trait evolution |
author_facet |
Xu, Liang van Doorn, Sander Hildenbrandt, Hanno Etienne, Rampal S |
author_sort |
Xu, Liang |
title |
Inferring the effect of species interactions on trait evolution |
title_short |
Inferring the effect of species interactions on trait evolution |
title_full |
Inferring the effect of species interactions on trait evolution |
title_fullStr |
Inferring the effect of species interactions on trait evolution |
title_full_unstemmed |
Inferring the effect of species interactions on trait evolution |
title_sort |
inferring the effect of species interactions on trait evolution |
publishDate |
2021 |
url |
https://hdl.handle.net/11370/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 https://research.rug.nl/en/publications/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 https://doi.org/10.1093/sysbio/syaa072 https://pure.rug.nl/ws/files/175268947/syaa072.pdf |
genre |
baleen whale |
genre_facet |
baleen whale |
op_source |
Xu , L , van Doorn , S , Hildenbrandt , H & Etienne , R S 2021 , ' Inferring the effect of species interactions on trait evolution ' , Systematic biology , vol. 70 , no. 3 , pp. 463–479 . https://doi.org/10.1093/sysbio/syaa072 |
op_relation |
https://research.rug.nl/en/publications/9915db76-22c1-4f11-bc1a-05dd1b84d3c4 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1093/sysbio/syaa072 |
container_title |
Systematic Biology |
container_volume |
70 |
container_issue |
3 |
container_start_page |
463 |
op_container_end_page |
479 |
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1810433577565814784 |