Population cycles emerging through multiple interaction types

Cyclic dynamics of populations are outstanding and widespread phenomena across many taxa. Previous theoretical studies have mainly focused on the consumer–resource interaction as the driving force for such cycling. However, natural ecosystems comprise diverse types of species interactions, but their...

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Main Authors: Naoya Mitani, Akihiko Mougi
Format: Article
Language:English
Published: The Royal Society 2017-01-01
Series:Royal Society Open Science
Subjects:
Online Access:https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.170536
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spelling doaj-4e1d9e90197d4363b5d18187408d93732020-11-25T04:10:32ZengThe Royal SocietyRoyal Society Open Science2054-57032017-01-014910.1098/rsos.170536170536Population cycles emerging through multiple interaction typesNaoya MitaniAkihiko MougiCyclic dynamics of populations are outstanding and widespread phenomena across many taxa. Previous theoretical studies have mainly focused on the consumer–resource interaction as the driving force for such cycling. However, natural ecosystems comprise diverse types of species interactions, but their roles in population dynamics remains unclear. Here, using a four-species hybrid module with antagonistic, mutualistic and competitive interactions, we analytically showed that the system with major interaction types can drive population cycles. Stronger interactions easily cause cycling, and even when sub-modules with possible combinations of two interactions are stabilized by weak interactions, the system with all interaction types can cause unstable population oscillations. Diversity of interaction types allows to add mutualists to the list of drivers of oscillations in a focal species' population size, when they act in conjunction to other drivers.https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.170536cyclingpredator–preymutualismcompetitionstabilitymathematical model
collection DOAJ
language English
format Article
sources DOAJ
author Naoya Mitani
Akihiko Mougi
spellingShingle Naoya Mitani
Akihiko Mougi
Population cycles emerging through multiple interaction types
Royal Society Open Science
cycling
predator–prey
mutualism
competition
stability
mathematical model
author_facet Naoya Mitani
Akihiko Mougi
author_sort Naoya Mitani
title Population cycles emerging through multiple interaction types
title_short Population cycles emerging through multiple interaction types
title_full Population cycles emerging through multiple interaction types
title_fullStr Population cycles emerging through multiple interaction types
title_full_unstemmed Population cycles emerging through multiple interaction types
title_sort population cycles emerging through multiple interaction types
publisher The Royal Society
series Royal Society Open Science
issn 2054-5703
publishDate 2017-01-01
description Cyclic dynamics of populations are outstanding and widespread phenomena across many taxa. Previous theoretical studies have mainly focused on the consumer–resource interaction as the driving force for such cycling. However, natural ecosystems comprise diverse types of species interactions, but their roles in population dynamics remains unclear. Here, using a four-species hybrid module with antagonistic, mutualistic and competitive interactions, we analytically showed that the system with major interaction types can drive population cycles. Stronger interactions easily cause cycling, and even when sub-modules with possible combinations of two interactions are stabilized by weak interactions, the system with all interaction types can cause unstable population oscillations. Diversity of interaction types allows to add mutualists to the list of drivers of oscillations in a focal species' population size, when they act in conjunction to other drivers.
topic cycling
predator–prey
mutualism
competition
stability
mathematical model
url https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.170536
work_keys_str_mv AT naoyamitani populationcyclesemergingthroughmultipleinteractiontypes
AT akihikomougi populationcyclesemergingthroughmultipleinteractiontypes
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