Search arXiv⌕ Search

arXiv · 1503.00529

Diversity waves in collapse-driven population dynamics

Abstract

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 hierarchical 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.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sergei Maslov, Kim Sneppen. 2015-07-14. Diversity waves in collapse-driven population dynamics. https://doi.org/10.1371/journal.pcbi.1004440

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Predator self limitation controls pattern formation in a predator prey system with additional food: a Turing Hopf analysis

Supplying a released predator with additional, non reproducing food is a standard lever in augmentative biological control, with a known drawback with nothing limiting the predators own numbers, the extra food lets its population grow without bound. Competition among the predators supplies the missing brake. Howthis self limitation reshapes the spatial arrangement of the two species has not been asked. We address it with a reaction diffusion model of a logistically growing prey and a predator feeding through a Holling type II response that also draws on additional food , the predators competing among themselves at strength. In the well mixed setting we locate the Hopf bifurcation of the coexistence state exactly and show the cycle born there is stable, so weak competition gives boom bust oscillations, not runaway growth. Allowing movement, we obtain the diffusion driven Turing threshold at which the uniform state breaks into stationary patches of high and low density, and find the uniform oscillation stable as it appears. With prey mobility and competition strength as control parameters, the pattern forming and oscillatory instabilities meet at a single point, where we compute the dynamics. Simulations confirm the sequence weak competition gives a wholefield oscillation, stronger competition with faster prey spread gives fixed patterns, and near the crossover the two combine into patterns that pulse in time. Predator self competition therefore sets the spatial structure of the community, which is what matters when additional food is used to steer a control agent in the field.

q-bio.PE↗

Graph construction in QUBO-based recursive phylogenetic tree reconstruction

Molecular sequence data are used to reconstruct evolutionary relationships among taxa, but reconstruction accuracy depends not only on the tree-building method but also on how pairwise sequence relationships are represented. We evaluated sequence-to-affinity representations in a recursive normalized-cut (Ncut) framework whose graph-partitioning subproblems were formulated as quadratic unconstrained binary optimization (QUBO) models and solved using Simulated Bifurcation. Using simulated amino-acid and nucleotide datasets spanning multiple tree-generation settings and evolutionary divergence, we compared normalized bit-score affinities with representations derived from transformed sequence similarities and evolutionary distances, examined post-swap refinement, and used neighbor joining (NJ) as a distance-based comparator. Affinity representation substantially affected internal split recovery, particularly for nucleotide data. JC69-based local affinities maintained comparatively high accuracy as divergence increased, whereas normalized bit-score and BLAST-derived kernel representations declined more markedly. Post-swap refinement generally improved recovery, but not consistently across individual reconstructions. NJ achieved higher mean split recovery than corresponding recursive Ncut reconstructions for WAG and JC69 distances across all evaluated conditions, whereas recursive Ncut outperformed NJ for BLAST-derived logarithmic distances under some conditions. These results show that graph construction is an important determinant of recursive Ncut-based phylogenetic reconstruction. A representation that performs well within Ncut does not necessarily provide the most accurate use of the underlying pairwise distances. Pairwise representation, affinity transformation, optimization, and recursive tree construction should therefore be evaluated jointly.

q-bio.PE↗

Scarlet Fever Dynamics in 19th and 20th Century London

Weekly scarlet fever (SF) mortality records for London, UK, from 1842 to 1939, together with notified case records from 1901 to 1939, reveal a strong annual epidemic pattern with peak prevalence in the autumn. In addition to the annual epidemic pattern, this long time series reveals a cyclical envelope with a period that lengthened over the decades. In particular, the period of the envelope increased from about four years to about eight years between 1880 and 1920, coinciding with a dramatic decline in pre-antibiotic-era SF deaths (from about 2300/yr to about 80/yr). We quantify the spectral features of the SF time series using a wavelet transform, and attempt to explain why the frequency structure changed over time, using a mechanistic mathematical model of SF transmission dynamics. We estimate the parameters of the model in part from the literature and in part by fitting mortality and incidence jointly. We use a mechanistic transition analysis (considering both attractors and transients in model solutions) to relate the observed changes in frequency structure to our estimated changes in model parameters. We find that almost all spectral evolution in the time series can be explained by changes in the effective reproduction number and the amplitude of seasonal forcing. These changes reflect observed variation in birth rates together with inferred changes in transmission, which may in part have arisen through pathogen evolution.

q-bio.PE↗