Predicting abundances of plants and pollinators using a simple compartmental mutualistic model

Fort, Hugo; Mungan, Muhittin

doi:10.1098/rspb.2015.0592

Cited by 8 publications

(8 citation statements)

References 30 publications

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“…Moreover, our finding that interaction modules are largely formed by species with similar traits (Fig. S6) is consistent with the conclusion of Fort and Mungan (2015) on a Mediterranean plant-pollinator network (Stang et al 2007). By classifying pairs of plants and pollinators into modules based on matching their traits, Fort and Mungan (2015) were able to accurately predict plant and pollinator abundances.…”

Section: Discussionsupporting

confidence: 87%

Trait-mediated interaction leads to structural emergence in mutualistic networks

Minoarivelo

Hui

2015

Evol Ecol

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As asymmetric structures of mutualistic networks can potentially contribute to system resilience, elucidating drivers behind the emergence of particular network architectures remains a major endeavour in ecology. Here, using an eco-evolutionary model for bipartite mutualistic networks with trait-mediated interactions, we explore how particular levels of connectance, nestedness and modularity are affected by three network assembly forces: resource accessibility, tolerance to trait difference between mutualistic pairs and competition intensity. We found that a moderate accessibility to intra-trophic resources and cross-trophic mutualistic support can result in a highly nested web, while low tolerance to trait difference between interacting pairs leads to a high level of modularity. Network-level trait complementarity leads to low connectance and high modularity, while network-level specialization can result in nested structures. Consequently, we argue that the interplay of ecological and evolutionary processes through trait-mediated interactions can explain these widely observed architectures in mutualistic networks.

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Section: Discussionsupporting

confidence: 87%

Trait-mediated interaction leads to structural emergence in mutualistic networks

Minoarivelo

Hui

2015

Evol Ecol

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“…. , S. After the change of variableη = (1 − λ)η, the above (16) reduces to the same equation as one would get for λ = 0, i.e. in absence of empty sites the mean field equation becomes:…”

Section: Mean Field Analysis For the Voter Model With Empty Sitesmentioning

confidence: 88%

Reconciling cooperation, biodiversity and stability in complex ecological communities

Suweis²,

Grilli

et al. 2019

Sci Rep

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Empirical evidences show that ecosystems with high biodiversity can persist in time even in the presence of few types of resources and are more stable than low biodiverse communities. This evidence is contrasted by the conventional mathematical modeling, which predicts that the presence of many species and/or cooperative interactions are detrimental for ecological stability and persistence. Here we propose a modelling framework for population dynamics, which also include indirect cooperative interactions mediated by other species (e.g. habitat modification). We show that in the large system size limit, any number of species can coexist and stability increases as the number of species grows, if mediated cooperation is present, even in presence of exploitative or harmful interactions (e.g. antibiotics). Our theoretical approach thus shows that appropriate models of mediated cooperation naturally lead to a solution of the long-standing question about complexity-stability paradox and on how highly biodiverse communities can coexist.

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“…to understand biodiversity (Thompson 2005, Gravel et al 2006, Kembel 2009, Venner et al 2011, Leibold and Chase 2017. In the context of the study of ecological networks there is a growing effort to understand how these processes account for nestedness and modularity in empirical networks (Vázquez et al 2007, Krishna et al 2008, Canard et al 2012, Fort and Mungan 2015, Gilarranz et al 2015, Nuwagaba et al 2015, Rohr et al 2016. In this vein, our study shows that adaptive network models incorporating coevolution and different functional mechanisms underpinning species interactions are useful tools to explore the feedbacks of ecological and evolutionary processes on network structure.…”

Section: Antagonisms Mutualisms Antagonisms Mutualismsmentioning

confidence: 84%

Coevolution by different functional mechanisms modulates the structure and dynamics of antagonistic and mutualistic networks

Andreazzi

Astegiano

Guimarães

2019

Oikos

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A central problem in the study of species interactions is to understand the underlying ecological and evolutionary mechanisms that shape and are shaped by trait evolution in interacting assemblages. The patterns of interaction among species (i.e. network structure) provide the pathways for evolution and coevolution, which are modulated by how traits affect individual fitness (i.e. functional mechanisms). Functional mechanisms, in turn, also affect the likelihood of an ecological interaction, shaping the structure of interaction networks. Here, we build adaptive network models to explore the potential role of coevolution by two functional mechanisms, trait matching and exploitation barrier, in driving trait evolution and the structure of interaction networks. We use these models to explore how different scenarios of coevolution and functional mechanisms reproduce the empirical network patterns observed in antagonistic and mutualistic interactions and affect trait evolution. Scenarios assuming coevolutionary feedback with a strong effect of functional mechanism better reproduce the empirical structure of networks. Antagonistic and mutualistic networks, however, are better explained by different functional mechanisms and the structure of antagonisms is better reproduced than that of mutualisms. Scenarios assuming coevolution by strong trait matching between interacting partners better explain the structure of antagonistic networks, whereas those assuming strong barrier effects better reproduce the structure of mutualistic networks. The dynamics resulting from the feedback between strong functional mechanisms and coevolution favor the stability of antagonisms and mutualisms. Selection favoring trait matching reduces temporal trait fluctuation and the magnitude of arms races in antagonisms, whereas selection due to exploitation barriers reduces temporal trait fluctuations in mutualisms. Our results indicate that coevolutionary models better reproduce the network structure of antagonisms than those of mutualisms and that different functional mechanisms may favor the persistence of antagonistic and mutualistic interacting assemblages.

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Predicting abundances of plants and pollinators using a simple compartmental mutualistic model

Cited by 8 publications

References 30 publications

Trait-mediated interaction leads to structural emergence in mutualistic networks

Trait-mediated interaction leads to structural emergence in mutualistic networks

Reconciling cooperation, biodiversity and stability in complex ecological communities

Coevolution by different functional mechanisms modulates the structure and dynamics of antagonistic and mutualistic networks

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