Building clone-consistent ecosystem models.
Many ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the...
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2021-02-01
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Online Access: | https://doi.org/10.1371/journal.pcbi.1008635 |
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doaj-cdefd701c4584abf957166bd7079fbc92021-07-09T04:32:09ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-02-01172e100863510.1371/journal.pcbi.1008635Building clone-consistent ecosystem models.Gerrit AnsmannTobias BollenbachMany ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency. Although clone consistency can always be achieved with sufficient assumptions, we argue that it is important to explicitly name and consider the assumptions made: They may not be justified or limit the applicability of models and the generality of the results obtained with them. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities. Finally, our insights point to new relevant forms of general models for theoretical ecology. Our framework thus provides a systematic way of comprehending ecological models, which can guide a wide range of studies.https://doi.org/10.1371/journal.pcbi.1008635 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gerrit Ansmann Tobias Bollenbach |
spellingShingle |
Gerrit Ansmann Tobias Bollenbach Building clone-consistent ecosystem models. PLoS Computational Biology |
author_facet |
Gerrit Ansmann Tobias Bollenbach |
author_sort |
Gerrit Ansmann |
title |
Building clone-consistent ecosystem models. |
title_short |
Building clone-consistent ecosystem models. |
title_full |
Building clone-consistent ecosystem models. |
title_fullStr |
Building clone-consistent ecosystem models. |
title_full_unstemmed |
Building clone-consistent ecosystem models. |
title_sort |
building clone-consistent ecosystem models. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Computational Biology |
issn |
1553-734X 1553-7358 |
publishDate |
2021-02-01 |
description |
Many ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency. Although clone consistency can always be achieved with sufficient assumptions, we argue that it is important to explicitly name and consider the assumptions made: They may not be justified or limit the applicability of models and the generality of the results obtained with them. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities. Finally, our insights point to new relevant forms of general models for theoretical ecology. Our framework thus provides a systematic way of comprehending ecological models, which can guide a wide range of studies. |
url |
https://doi.org/10.1371/journal.pcbi.1008635 |
work_keys_str_mv |
AT gerritansmann buildingcloneconsistentecosystemmodels AT tobiasbollenbach buildingcloneconsistentecosystemmodels |
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1721312327617216512 |