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Evolution of resource cycling in ecosystems and individuals.

Crombach A, Hogeweg P - BMC Evol. Biol. (2009)

Bottom Line: If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics.In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling.By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, The Netherlands. anton.crombach@gmail.com

ABSTRACT

Background: Resource cycling is a defining process in the maintenance of the biosphere. Microbial communities, ranging from simple to highly diverse, play a crucial role in this process. Yet the evolutionary adaptation and speciation of micro-organisms have rarely been studied in the context of resource cycling. In this study, our basic questions are how does a community evolve its resource usage and how are resource cycles partitioned?

Results: We design a computational model in which a population of individuals evolves to take up nutrients and excrete waste. The waste of one individual is another's resource. Given a fixed amount of resources, this leads to resource cycles. We find that the shortest cycle dominates the ecological dynamics, and over evolutionary time its length is minimized. Initially a single lineage processes a long cycle of resources, later crossfeeding lineages arise. The evolutionary dynamics that follow are determined by the strength of indirect selection for resource cycling. We study indirect selection by changing the spatial setting and the strength of direct selection. If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics. The individuals are good at cycling resources themselves and do this with a short cycle. On the other hand, if individuals randomly change position each time step, or direct selection is high, individuals are more prone to crossfeeding: an ecosystem based solution with turbulent resource dynamics, and individuals that are less capable of cycling resources themselves.

Conclusion: In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling. By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

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Resource abundance, population fitness and population diversity. A – C and J – L. The 20 most abundant resources are plotted through time. The darker a curve, the higher the abundance of this resource throughout the run. The top and bottom row contain, respectively, runs from the local and  model (for each selection regime a run). If visible at this scale, the initial phase is indicated by a gray background. D – F. Maximum and median fitness of the population through time. Dark shaded areas indicate the local model, light shaded areas the  model. G – I. Diversity in the population measured as the number of different network dynamics through time. Each 1000 time steps 1000 individuals were sampled and grouped by their network dynamics. The number of different groups is plotted. Grouping by phenotype gave qualitatively similar results.
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Figure 2: Resource abundance, population fitness and population diversity. A – C and J – L. The 20 most abundant resources are plotted through time. The darker a curve, the higher the abundance of this resource throughout the run. The top and bottom row contain, respectively, runs from the local and model (for each selection regime a run). If visible at this scale, the initial phase is indicated by a gray background. D – F. Maximum and median fitness of the population through time. Dark shaded areas indicate the local model, light shaded areas the model. G – I. Diversity in the population measured as the number of different network dynamics through time. Each 1000 time steps 1000 individuals were sampled and grouped by their network dynamics. The number of different groups is plotted. Grouping by phenotype gave qualitatively similar results.

Mentions: In Figure 2 we show for both models and each selection regime a representative run. Clearly, both models show that from low to high selection (and thus from relatively high to low indirect selection) the resource dynamics in the environment become more turbulent. Importantly, there is also a clear difference between the models as the local model is more 'quiet', or stable in its resource dynamics. With respect to fitness (Figure 2D–F), we find that in both models the difference between maximum bite and median bite is large, and median bite length increases hardly. The most striking property of the diversity (Figure 2G–I) is that the sudden burst of diversity corresponds with the end of the so-called initial phase. It is also interesting to note that a diversity of ~600, given a sample size of 1000 individuals, implies that there is a lot of diversity in the populations at σ = 1.0 and 5.0, and in the model at σ = 0.2. Finally, we highlight the dynamic nature of the system on the level of an individual's phenotype (and therefore also its genotype): turbulent resource dynamics and the gain and loss of maximum bite lengths indicate the many invasions of new lineages and the extinction of old ones.


Evolution of resource cycling in ecosystems and individuals.

Crombach A, Hogeweg P - BMC Evol. Biol. (2009)

Resource abundance, population fitness and population diversity. A – C and J – L. The 20 most abundant resources are plotted through time. The darker a curve, the higher the abundance of this resource throughout the run. The top and bottom row contain, respectively, runs from the local and  model (for each selection regime a run). If visible at this scale, the initial phase is indicated by a gray background. D – F. Maximum and median fitness of the population through time. Dark shaded areas indicate the local model, light shaded areas the  model. G – I. Diversity in the population measured as the number of different network dynamics through time. Each 1000 time steps 1000 individuals were sampled and grouped by their network dynamics. The number of different groups is plotted. Grouping by phenotype gave qualitatively similar results.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2698886&req=5

Figure 2: Resource abundance, population fitness and population diversity. A – C and J – L. The 20 most abundant resources are plotted through time. The darker a curve, the higher the abundance of this resource throughout the run. The top and bottom row contain, respectively, runs from the local and model (for each selection regime a run). If visible at this scale, the initial phase is indicated by a gray background. D – F. Maximum and median fitness of the population through time. Dark shaded areas indicate the local model, light shaded areas the model. G – I. Diversity in the population measured as the number of different network dynamics through time. Each 1000 time steps 1000 individuals were sampled and grouped by their network dynamics. The number of different groups is plotted. Grouping by phenotype gave qualitatively similar results.
Mentions: In Figure 2 we show for both models and each selection regime a representative run. Clearly, both models show that from low to high selection (and thus from relatively high to low indirect selection) the resource dynamics in the environment become more turbulent. Importantly, there is also a clear difference between the models as the local model is more 'quiet', or stable in its resource dynamics. With respect to fitness (Figure 2D–F), we find that in both models the difference between maximum bite and median bite is large, and median bite length increases hardly. The most striking property of the diversity (Figure 2G–I) is that the sudden burst of diversity corresponds with the end of the so-called initial phase. It is also interesting to note that a diversity of ~600, given a sample size of 1000 individuals, implies that there is a lot of diversity in the populations at σ = 1.0 and 5.0, and in the model at σ = 0.2. Finally, we highlight the dynamic nature of the system on the level of an individual's phenotype (and therefore also its genotype): turbulent resource dynamics and the gain and loss of maximum bite lengths indicate the many invasions of new lineages and the extinction of old ones.

Bottom Line: If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics.In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling.By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, The Netherlands. anton.crombach@gmail.com

ABSTRACT

Background: Resource cycling is a defining process in the maintenance of the biosphere. Microbial communities, ranging from simple to highly diverse, play a crucial role in this process. Yet the evolutionary adaptation and speciation of micro-organisms have rarely been studied in the context of resource cycling. In this study, our basic questions are how does a community evolve its resource usage and how are resource cycles partitioned?

Results: We design a computational model in which a population of individuals evolves to take up nutrients and excrete waste. The waste of one individual is another's resource. Given a fixed amount of resources, this leads to resource cycles. We find that the shortest cycle dominates the ecological dynamics, and over evolutionary time its length is minimized. Initially a single lineage processes a long cycle of resources, later crossfeeding lineages arise. The evolutionary dynamics that follow are determined by the strength of indirect selection for resource cycling. We study indirect selection by changing the spatial setting and the strength of direct selection. If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics. The individuals are good at cycling resources themselves and do this with a short cycle. On the other hand, if individuals randomly change position each time step, or direct selection is high, individuals are more prone to crossfeeding: an ecosystem based solution with turbulent resource dynamics, and individuals that are less capable of cycling resources themselves.

Conclusion: In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling. By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

Show MeSH