Predation Has Small, Short-Term, and in Certain Conditions Random Effect on the Evolution of Aging

AbstractThe pace of aging varies considerably in nature. Historically, scientists focused mostly on why and how has aging evolved, while only a few studies explored mechanisms driving evolution of specific rates of aging. Here we develop an agent-based model simulating evolution of aging in prey subject to predation. Our results suggest that predation affects the pace of aging in prey only if young, vivid animals are not much more likely to escape predators than the old ones. However, even this effect slowly vanishes when the predator diet composition evolves, too. Furthermore, evolution of a specific aging rate, in our model, is driven mainly by a single parameter, the strength of a trade-off between aging and fecundity. Indeed, in absence of this trade-off the evolutionary impacts of predation on the prey aging rate appear random. Our model produces several testable predictions which may be useful for other areas of aging research.

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Predation has small, short-term, and in certain conditions random effects on the evolution of aging

BMC Ecology and Evolution ◽

10.1186/s12862-021-01815-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Peter Lenart ◽

Julie Bienertová-Vašků ◽

Luděk Berec

Keyword(s):

Simulation Model ◽

Random Effects ◽

Diet Breadth ◽

Current Evidence ◽

Short Term ◽

Trade Off ◽

Aging Rate ◽

Extrinsic Mortality ◽

Evolution Of Aging ◽

The Relationship

Abstract Background The pace of aging varies considerably in nature. The best-known explanation of the evolution of specific rates of aging is the Williams’ hypothesis suggesting that the aging rate should correlate with the level of extrinsic mortality. However, the current evidence is inconclusive with various examples where the Williams' hypothesis seems to be correct and where it doesn’t. Here we explore the relationship between extrinsic mortality and aging rate by developing a simulation model of the evolution of aging rate in prey subject to predation. Results Our results suggest that more intense predation leads to the evolution of faster pace of aging in prey. However, this effect slowly vanishes when the predator diet breadth is allowed to evolve, too. Furthermore, in our model, the evolution of a specific aging rate is driven mainly by a single parameter, the strength of a trade-off between aging and fecundity. Indeed, in the absence of this trade-off the evolutionary impacts of predation on the prey aging rate appear random. Conclusions We show that the William’s hypothesis appears valid when there is a trade-off between aging and fecundity and predators and prey do not coevolve. However, we also show that when the prey and predators coevolve or if there is no trade-off between aging and fecundity the William`s hypothesis is no longer applicable.

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Mitigation of short-term disturbance negative impacts in the agent-based model of a production companies network

10.1063/1.5012340 ◽

2017 ◽

Cited By ~ 1

Author(s):

G. K. Shevchuk ◽

D. B. Berg ◽

O. M. Zvereva ◽

M. A. Medvedeva

Keyword(s):

Agent Based Model ◽

Short Term ◽

Agent Based ◽

Negative Impacts

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An agent-based model of the interrelation between the COVID-19 outbreak and economic activities

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2020.0604 ◽

2021 ◽

Vol 477 (2245) ◽

pp. 20200604

Author(s):

Takeshi Kano ◽

Kotaro Yasui ◽

Taishi Mikami ◽

Munehiro Asally ◽

Akio Ishiguro

Keyword(s):

Computational Simulation ◽

Economic Losses ◽

Economic Damage ◽

Agent Based Model ◽

Economic Activities ◽

Trade Off ◽

Agent Based ◽

Human Contact ◽

Simulation Results ◽

Voluntary Restraint

As of July 2020, COVID-19 caused by SARS-COV-2 is spreading worldwide, causing severe economic damage. While minimizing human contact is effective in managing outbreaks, it causes severe economic losses. Strategies to solve this dilemma by considering the interrelation between the spread of the virus and economic activities are urgently needed to mitigate the health and economic damage. Here, we propose an abstract agent-based model of the COVID-19 outbreak that accounts for economic activities. The computational simulation of the model recapitulates the trade-off between the health and economic damage associated with voluntary restraint measures. Based on the simulation results, we discuss how the macroscopic dynamics of infection and economics emerge from individuals’ behaviours. We believe our model can serve as a platform for discussing solutions to the above-mentioned dilemma.

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Sharing Competition: An Agent-Based Model for the Short-Term Accommodations Market

The B E Journal of Economic Analysis & Policy ◽

10.1515/bejeap-2019-0231 ◽

2020 ◽

Vol 20 (2) ◽

Cited By ~ 1

Author(s):

Bruna Bruno ◽

Marisa Faggini

Keyword(s):

Decision Rules ◽

Market Performance ◽

Sharing Economy ◽

Price Setting ◽

Agent Based Model ◽

Short Term ◽

Main Determinant ◽

Agent Based ◽

Minor Influence ◽

Traditional Industry

AbstractThis paper presents an agent-based model for the sharing economy, in the short-term accommodations market, where peers participating as suppliers and customers follow simple decision rules about sharing market participation, according to their heterogeneous characteristics. Simulations results show that, in the competition between the sharing economy and the traditional industry, low substitutability occurs between goods if consumers are differentiated in preferences. The main determinant for market performance in both sectors is the demand level, with minor influence of price setting and competition within and between markets.

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Macronutrient intakes and the lifespan-fecundity trade-off: a geometric framework agent-based model

Journal of The Royal Society Interface ◽

10.1098/rsif.2018.0733 ◽

2019 ◽

Vol 16 (151) ◽

pp. 20180733 ◽

Cited By ~ 3

Author(s):

Cameron J. Hosking ◽

David Raubenheimer ◽

Michael A. Charleston ◽

Stephen J. Simpson ◽

Alistair M. Senior

Keyword(s):

Life History ◽

Ecological Factors ◽

Primary Component ◽

Agent Based Model ◽

Geometric Framework ◽

Trade Off ◽

Agent Based ◽

Extrinsic Mortality ◽

Trade Offs ◽

Evolutionary Fitness

Lifespan and fecundity, the main components in evolutionary fitness, are both strongly affected by nutritional state. Geometric framework of nutrition (GFN) experiments has shown that lifespan and fecundity are separated in nutrient space leading to a functional trade-off between the two traits. Here we develop a spatially explicit agent-based model (ABM) using the GFN to explore how ecological factors may cause selection on macronutrient appetites to optimally balance these life-history traits. We show that increasing the risk of extrinsic mortality favours intake of a mixture of nutrients that is associated with maximal fecundity at the expense of reduced longevity and that this result is robust across spatial and nutritional environments. These model behaviours are consistent with what has been observed in studies that quantify changes in life history in response to environmental manipulations. Previous GFN-derived ABMs have treated fitness as a single value. This is the first such model to instead decompose fitness into its primary component traits, longevity and fecundity, allowing evolutionary fitness to be an emergent property of the two. Our model demonstrates that selection on macronutrient appetites may affect life-history trade-offs and makes predictions that can be directly tested in artificial selection experiments.

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Trade-off between road avoidance and attraction by roadside salt pools in moose: An agent-based model to assess measures for reducing moose-vehicle collisions

Ecological Modelling ◽

10.1016/j.ecolmodel.2011.01.022 ◽

2011 ◽

Vol 222 (8) ◽

pp. 1423-1435 ◽

Cited By ~ 21

Author(s):

Paul D. Grosman ◽

Jochen A.G. Jaeger ◽

Pascale M. Biron ◽

Christian Dussault ◽

Jean-Pierre Ouellet

Keyword(s):

Agent Based Model ◽

Vehicle Collisions ◽

Trade Off ◽

Agent Based ◽

Road Avoidance

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Listening to Bluetooth Beacons for Epidemic Risk Mitigation

10.21203/rs.3.rs-150227/v2 ◽

2021 ◽

Author(s):

Gilles Barthe ◽

Roberta De Viti ◽

Peter Druschel ◽

Deepak Garg ◽

Manuel Gomez Rodriguez ◽

...

Keyword(s):

Risk Assessment ◽

Risk Mitigation ◽

Contact Tracing ◽

Epidemic Spread ◽

Agent Based Model ◽

Trade Off ◽

Agent Based ◽

Inclusive System ◽

Risk Notification ◽

Epidemic Risk

Abstract The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interoperability with manual contact tracing, low adoption rates, and a societally sensitive trade-off between utility and privacy. In this work, we introduce a new privacy-preserving and inclusive system for epidemic risk assessment and notification that aims to address these limitations. Rather than capturing pairwise encounters between user devices as done by existing systems, our system captures encounters between user devices and beacons placed in strategic locations where infection clusters may originate. Epidemiological simulations using an agent-based model demonstrate that, by utilizing location and environmental information and interoperating with manual contact tracing, our system can increase the accuracy of contact tracing actions and may help reduce epidemic spread already at low adoption.

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