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Title: Diversity waves in collapse-driven population dynamics

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchicalmore » peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.« less
 [1] ;  [2]
  1. Univ. of Illinois, Urbana-Champaign, IL (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
  2. Univ. of Copenhagen, Copenhagen (Denmark)
Publication Date:
Report Number(s):
Journal ID: ISSN 1553-7358; R&D Project: PM-031; KP1601040
Grant/Contract Number:
Accepted Manuscript
Journal Name:
PLoS Computational Biology (Online)
Additional Journal Information:
Journal Name: PLoS Computational Biology (Online); Journal Volume: 11; Journal Issue: 9; Journal ID: ISSN 1553-7358
Public Library of Science
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
59 BASIC BIOLOGICAL SCIENCES; population genetics; species extinction; population size; carrying capacity; population dynamics; bacteriophages; biodiversity; ecosystems
OSTI Identifier: