Evolution of resource cycling in ecosystems and individuals.
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.


CONCLUSIONS
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.
Crombach
Anton
A
Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, The Netherlands. anton.crombach@gmail.com
Hogeweg
Paulien
P
D005075:Biological Evolution; D003198:Computer Simulation; D004463:Ecology; D017753:Ecosystem; D008954:Models, Biological; D010802:Phylogeny; D011157:Population Dynamics