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

2011 ◽  
Vol 222 (8) ◽  
pp. 1423-1435 ◽  
Author(s):  
Paul D. Grosman ◽  
Jochen A.G. Jaeger ◽  
Pascale M. Biron ◽  
Christian Dussault ◽  
Jean-Pierre Ouellet
Author(s):  
Takeshi Kano ◽  
Kotaro Yasui ◽  
Taishi Mikami ◽  
Munehiro Asally ◽  
Akio Ishiguro

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.


2019 ◽  
Vol 16 (151) ◽  
pp. 20180733 ◽  
Author(s):  
Cameron J. Hosking ◽  
David Raubenheimer ◽  
Michael A. Charleston ◽  
Stephen J. Simpson ◽  
Alistair M. Senior

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.


2020 ◽  
Author(s):  
Peter Lenart ◽  
Julie Bienertová-Vašků ◽  
Luděk Berec

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.


2021 ◽  
Author(s):  
Gilles Barthe ◽  
Roberta De Viti ◽  
Peter Druschel ◽  
Deepak Garg ◽  
Manuel Gomez Rodriguez ◽  
...  

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.


2001 ◽  
Author(s):  
Minoru Tabata ◽  
Akira Ide ◽  
Nobuoki Eshima ◽  
Kyushu Takagi ◽  
Yasuhiro Takei ◽  
...  

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