Trophic interaction modifications: an empirical and theoretical framework

J. Christopher D. Terry; Rebecca J. Morris; Michael B. Bonsall

doi:10.1111/ele.12824

Trophic interaction modifications disrupt the structure and stability of food webs

10.1101/345280 ◽

2018 ◽

Cited By ~ 3

Author(s):

J. Christopher D. Terry ◽

Rebecca J. Morris ◽

Michael B. Bonsall

Keyword(s):

Trophic Interaction ◽

Community Interactions ◽

Additional Species ◽

Trophic Effects ◽

Trophic Networks ◽

Empirical Information ◽

Interaction Modifications ◽

Underlying Network ◽

The Stability ◽

The Impact

AbstractTrophic interaction modifications, where a consumer-resource interaction is influenced by an additional species, are established as being prevalent throughout ecological networks. Despite this, their influence on the structure of interaction distributions within communities has not yet been examined. Although empirical information about the distribution of interaction modifications is currently sparse, the non-trophic effects they induce will be structured by the underlying network of trophic interactions. Here we test the impact of interaction modifications, introduced under a range of distributional assumptions to artificial and empirical trophic networks, on the overall structure of interactions within communities. We show that local stability and reactivity is critically dependent on the inter-relationship between the trophic and non-trophic effects. Depending on their distribution, interaction modifications can generate significant additional structure to community interactions making analyses of the stability of ecological systems based solely on trophic networks unreliable. Empirical information on the topological and strength distributions of interaction modifications will be a key part of understanding the dynamics of communities.

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Identifying important interaction modifications in ecological systems

10.1101/228874 ◽

2017 ◽

Author(s):

J. Christopher D. Terry ◽

Michael B. Bonsall ◽

Rebecca J. Morris

Keyword(s):

Potential Interaction ◽

Ecological Systems ◽

Trophic Interaction ◽

Additional Species ◽

Individual Interaction ◽

Important Interaction ◽

Interaction Modifications ◽

Underlying Network ◽

Relationship Of ◽

The Relationship

AbstractTrophic interaction modifications, where a consumer-resource link is affected by additional species, are widespread and significant causes of indirect effects in ecological networks. The sheer number of potential interaction modifications in ecological systems poses a considerable challenge, making prioritisation for empirical study essential. Here, we introduce measures to quantify the topological relationship of individual interaction modifications relative to the underlying network. We use these, together with measures for the strength of trophic interaction modifications to identify modifications that are most likely to exert significant effects on the dynamics of whole systems. Using a set of simulated food webs and randomly distributed interaction modifications, we test whether a subset of interaction modifications important for the local stability and direction of species responses to perturbation of complex networks can be identified. We show that trophic interaction modifications affecting interactions with a high biomass flux, those that connect species otherwise distantly linked, and those where high trophic-level species modify to interactions lower in the web have particular importance for dynamics. In contrast, the centrality of modifications in the network provided little information. This work demonstrates that analyses of interaction modifications can be tractable at the network scale and highlights the importance of understanding the relationship between the distributions of trophic and non-trophic effects.

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Mind wandering as data augmentation: How mental travel supports abstraction

Behavioral and Brain Sciences ◽

10.1017/s0140525x1900311x ◽

2020 ◽

Vol 43 ◽

Author(s):

Myrthe Faber

Keyword(s):

Machine Learning ◽

Data Augmentation ◽

Mental Content ◽

Mind Wandering ◽

Theoretical Framework ◽

Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

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Adaptive and Maladaptive Neural Plasticity Due to Facial Nerve Palsy

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000244 ◽

2016 ◽

Vol 224 (2) ◽

pp. 102-111 ◽

Cited By ~ 1

Author(s):

Carsten M. Klingner ◽

Stefan Brodoehl ◽

Gerd F. Volk ◽

Orlando Guntinas-Lichius ◽

Otto W. Witte

Keyword(s):

Facial Nerve ◽

Neural Plasticity ◽

Cortical Plasticity ◽

Brain Plasticity ◽

Motor Nerve ◽

Predictive Coding ◽

Theoretical Framework ◽

Cortical Reorganization ◽

Nerve Lesion ◽

Peripheral Facial Palsy

Abstract. This paper reviews adaptive and maladaptive mechanisms of cortical plasticity in patients suffering from peripheral facial palsy. As the peripheral facial nerve is a pure motor nerve, a facial nerve lesion is causing an exclusive deefferentation without deafferentation. We focus on the question of how the investigation of pure deefferentation adds to our current understanding of brain plasticity which derives from studies on learning and studies on brain lesions. The importance of efference and afference as drivers for cortical plasticity is discussed in addition to the crossmodal influence of different competitive sensory inputs. We make the attempt to integrate the experimental findings of the effects of pure deefferentation within the theoretical framework of cortical responses and predictive coding. We show that the available experimental data can be explained within this theoretical framework which also clarifies the necessity for maladaptive plasticity. Finally, we propose rehabilitation approaches for directing cortical reorganization in the appropriate direction and highlight some challenging questions that are yet unexplored in the field.

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