scholarly journals Ecological specialization under multidimensional tradeoffs

2018 ◽  
Author(s):  
André Amado ◽  
Paulo R. A. Campos
Keyword(s):  
Resource Availability ◽  
Arbitrary Number ◽  
Essential Role ◽  
Ecological Specialization ◽  
Structured Population ◽  
Constant Rate ◽  
Population Sizes ◽  
Spatially Structured Population ◽  
Microbial Organisms

AbstractAlthough tradeoffs are expected to play an essential role in shaping the diversity in a community, their effects remain relatively nebulous and notoriously difficult to assess. This is especially true when multiple tradeoffs occur simultaneously. When dealing with single tradeoffs some information can be predicted based on their curvature. Does the same happen when dealing with multiple tradeoffs? What happens if the tradeoffs have opposing curvatures? To address these issues, we develop a resource-based model that encompasses multiple tradeoffs mediated by the acquisition and processing of the resources. The model considers a spatially structured population of microbial organisms that can grow on an arbitrary number of resources, which come into the system at a constant rate and diffuse through the environment. The individuals can adopt a variety of strategies through mutation constrained by tradeoffs, which renders the model adaptive. We assess population sizes and levels of ecological specialization. We find that when multiple tradeoffs are considered the classical intuition developed for single tradeoffs does not hold. The outcome can depend significantly not only on the curvature of the tradeoffs but also on resource availability.

scholarly journals A general modeling framework for describing spatially structured population dynamics

2017 ◽  
Vol 8 (1) ◽  
pp. 493-508 ◽  
Author(s):  
Christine Sample ◽  
John M. Fryxell ◽  
Joanna A. Bieri ◽  
Paula Federico ◽  
Julia E. Earl ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Modeling Framework ◽  
Structured Population ◽  
Structured Population Dynamics ◽  
Spatially Structured Population

Evolution in a spatially structured population subject to rare epidemics

2001 ◽  
Vol 63 (4) ◽  
Author(s):  
Joshua E. S. Socolar ◽  
Shane Richards ◽  
William G. Wilson
Keyword(s):  
Structured Population ◽  
Spatially Structured Population

scholarly journals Fitness benefits of low infectivity in a spatially structured population of bacteriophages

2014 ◽  
Vol 281 (1774) ◽  
pp. 20132563 ◽  
Author(s):  
Pavitra Roychoudhury ◽  
Neelima Shrestha ◽  
Valorie R. Wiss ◽  
Stephen M. Krone
Keyword(s):  
Transmission Rate ◽  
Burst Size ◽  
Structured Populations ◽  
Host Cells ◽  
Structured Population ◽  
Spatially Structured Populations ◽  
Lysis Time ◽  
Evolution Experiment ◽  
Spatially Structured Population ◽  
And Diffusion

For a parasite evolving in a spatially structured environment, an evolutionarily advantageous strategy may be to reduce its transmission rate or infectivity. We demonstrate this empirically using bacteriophage (phage) from an evolution experiment where spatial structure was maintained over 550 phage generations on agar plates. We found that a single substitution in the major capsid protein led to slower adsorption of phage to host cells with no change in lysis time or burst size. Plaques formed by phage isolates containing this mutation were not only larger but also contained more phage per unit area. Using a spatially explicit, individual-based model, we showed that when there is a trade-off between adsorption and diffusion (i.e. less ‘sticky’ phage diffuse further), slow adsorption can maximize plaque size, plaque density and overall productivity. These findings suggest that less infective pathogens may have an advantage in spatially structured populations, even when well-mixed models predict that they will not.

scholarly journals Asymmetric competition impacts evolutionary rescue in a changing environment

2017 ◽  
Vol 284 (1857) ◽  
pp. 20170374 ◽  
Author(s):  
Courtney L. Van Den Elzen ◽  
Elizabeth J. Kleynhans ◽  
Sarah P. Otto
Keyword(s):  
Resource Availability ◽  
Competitive Exclusion ◽  
Asymmetric Competition ◽  
Distributed Resources ◽  
Changing Environment ◽  
Competitive Release ◽  
Evolutionary Response ◽  
Evolutionary Rescue ◽  
Population Sizes ◽  
Species Declines

Interspecific competition can strongly influence the evolutionary response of a species to a changing environment, impacting the chance that the species survives or goes extinct. Previous work has shown that when two species compete for a temporally shifting resource distribution, the species lagging behind the resource peak is the first to go extinct due to competitive exclusion. However, this work assumed symmetrically distributed resources and competition. Asymmetries can generate differences between species in population sizes, genetic variation and trait means. We show that asymmetric resource availability or competition can facilitate coexistence and even occasionally cause the leading species to go extinct first. Surprisingly, we also find cases where traits evolve in the opposite direction to the changing environment because of a ‘vacuum of competitive release’ created when the lagging species declines in number. Thus, the species exhibiting the slowest rate of trait evolution is not always the most likely to go extinct in a changing environment. Our results demonstrate that the extent to which species appear to be tracking environmental change and the extent to which they are preadapted to that change may not necessarily determine which species will be the winners and which will be the losers in a rapidly changing world.

scholarly journals Slightly beneficial genes are retained by evolving Horizontal Gene Transfer despite selfish elements

2020 ◽  
Author(s):  
B. van Dijk ◽  
P. Hogeweg ◽  
H.M. Doekes ◽  
N. Takeuchi
Keyword(s):  
Gene Transfer ◽  
Horizontal Gene Transfer ◽  
Growth Rates ◽  
Selfish Genetic Elements ◽  
Structured Population ◽  
Rapid Changes ◽  
Spatially Structured Population ◽  
Fitness Benefits ◽  
Bacterial Growth Rates ◽  
Gene Sharing

AbstractHorizontal gene transfer (HGT) is a key component of bacterial evolution, which in concert with gene loss can result in rapid changes in gene content. While HGT can evidently aid bacteria to adapt to new environments, it also carries risks since bacteria may pick up selfish genetic elements (SGEs). Here, we use modeling to study how bacterial growth rates are affected by HGT of slightly beneficial genes, if bacteria can evolve HGT to improve their growth rates, and when HGT is evolutionarily maintained in light of harmful SGEs. We find that we can distinguish between four classes of slightly beneficial genes: indispensable, enrichable, rescuable, and unrescuable genes. Rescuable genes – genes that confer small fitness benefits and are lost from the population in the absence of HGT — can be collectively retained by a bacterial community that engages in HGT. While this ‘gene-sharing’ cannot evolve in well-mixed cultures, it does evolve in a spatially structured population such as a biofilm. Although HGT does indeed enable infection by harmful SGEs, HGT is nevertheless evolutionarily maintained by the hosts, explaining the stable coexistence and co-evolution of bacteria and SGEs.

scholarly journals Estimating the division kernel of a size-structured population

2017 ◽  
Vol 21 ◽  
pp. 275-302
Author(s):  
Van Ha Hoang
Keyword(s):  
Bandwidth Selection ◽  
Random Measure ◽  
Time Interval ◽  
Constant Growth Rate ◽  
Adaptive Estimator ◽  
Daughter Cells ◽  
Structured Population ◽  
Symmetric Density ◽  
Constant Rate ◽  
Fragmentation Kernel

We consider a size-structured model describing a population of cells proliferating by division. Each cell contain a quantity of toxicity which grows linearly according to a constant growth rate α. At division, the cells divide at a constant rate R and share their content between the two daughter cells into fractions Γ and 1 − Γ where Γ has a symmetric density h on [ 0,1 ], since the daughter cells are exchangeable. We describe the cell population by a random measure and observe the cells on the time interval [ 0,T ] with fixed T. We address here the problem of estimating the division kernel h (or fragmentation kernel) when the division tree is completely observed. An adaptive estimator of h is constructed based on a kernel function K with a fully data-driven bandwidth selection method. We obtain an oracle inequality and an exponential convergence rate, for which optimality is considered.

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