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Revisiting the Links-Species Scaling Relationship in Food Webs
Predicting the number of interactions among species in a food web is an important task. These trophic interactions underlie many ecological and evolutionary processes, ranging from biomass fluxes, ecosystem stability, resilience to extinction, and resistance against novel species. We investigate and...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660400/ https://www.ncbi.nlm.nih.gov/pubmed/33205136 http://dx.doi.org/10.1016/j.patter.2020.100079 |
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author | MacDonald, Arthur Andrew Meahan Banville, Francis Poisot, Timothée |
author_facet | MacDonald, Arthur Andrew Meahan Banville, Francis Poisot, Timothée |
author_sort | MacDonald, Arthur Andrew Meahan |
collection | PubMed |
description | Predicting the number of interactions among species in a food web is an important task. These trophic interactions underlie many ecological and evolutionary processes, ranging from biomass fluxes, ecosystem stability, resilience to extinction, and resistance against novel species. We investigate and compare several ways to predict the number of interactions in food webs. We conclude that a simple beta-binomial model outperforms other models, with the added desirable property of respecting biological constraints. We show how this simple relationship gives rise to a predicted distribution of several quantities related to link number in food webs, including the scaling of network structure with space and the probability that a network will be stable. |
format | Online Article Text |
id | pubmed-7660400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-76604002020-11-16 Revisiting the Links-Species Scaling Relationship in Food Webs MacDonald, Arthur Andrew Meahan Banville, Francis Poisot, Timothée Patterns (N Y) Article Predicting the number of interactions among species in a food web is an important task. These trophic interactions underlie many ecological and evolutionary processes, ranging from biomass fluxes, ecosystem stability, resilience to extinction, and resistance against novel species. We investigate and compare several ways to predict the number of interactions in food webs. We conclude that a simple beta-binomial model outperforms other models, with the added desirable property of respecting biological constraints. We show how this simple relationship gives rise to a predicted distribution of several quantities related to link number in food webs, including the scaling of network structure with space and the probability that a network will be stable. Elsevier 2020-07-29 /pmc/articles/PMC7660400/ /pubmed/33205136 http://dx.doi.org/10.1016/j.patter.2020.100079 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article MacDonald, Arthur Andrew Meahan Banville, Francis Poisot, Timothée Revisiting the Links-Species Scaling Relationship in Food Webs |
title | Revisiting the Links-Species Scaling Relationship in Food Webs |
title_full | Revisiting the Links-Species Scaling Relationship in Food Webs |
title_fullStr | Revisiting the Links-Species Scaling Relationship in Food Webs |
title_full_unstemmed | Revisiting the Links-Species Scaling Relationship in Food Webs |
title_short | Revisiting the Links-Species Scaling Relationship in Food Webs |
title_sort | revisiting the links-species scaling relationship in food webs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660400/ https://www.ncbi.nlm.nih.gov/pubmed/33205136 http://dx.doi.org/10.1016/j.patter.2020.100079 |
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