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Cagatay Eskin

Publications and source records attributed to Cagatay Eskin.

2 recordsLinked to original sources

Feasibility as a moving target: Fluctuating species interactions lead to universal power law in equilibrium abundances

Theoretical ecology has traditionally equated persistence with the stability of a fixed equilibrium point. Here we argue that the primary threat to ecosystem persistence need not be the loss of stability, but instead the escape of the stable equilibrium to a negative orthant. In a realistic setting, fluctuations in interactions do not merely disturb abundances about an equilibrium but can displace the equilibrium point itself. We theoretically and empirically analyze such displacements of the equilibrium point in a complex community. Theoretically, we find that light-tailed fluctuations in species interactions, no matter how small, lead to a heavy-tailed power law $P(y)=1/y^α$ for the equilibrium abundance $y$ of a species. Remarkably, the exponent $α=2$ is a universal value independent of interaction structure, community size, and species. Empirically, our analysis of 34 species reveals a power law signal for most, with a median exponent $α\sim2.56$. Next, we derive a formula for the critical noise, $σ_c$, beyond which the community experiences feasibility loss ``with near certainty''. We find that $σ_c(N)\sim N^{-1}$, implying that larger communities are significantly more fragile to noise induced feasibility loss. Lastly, we define and calculate biologically measurable analytical metrics for both global and species-specific feasibility escape rates, and implement these metrics in dynamic simulations of 98 real world mutualistic and food web networks, to successfully predict their fragility.

q-bio.PE↗

Demographics of co-aging complex systems: from sickly worms to chess engines

Aging, as defined in terms of the slope of the probability of death versus time (hazard curve), is a generic phenomenon observed in nearly all complex systems. Theoretical models of aging predict hazard curves that monotonically increase in time, in discrepancy with the peculiar ups and downs observed in empirically. Here we introduce the concept of co-aging, where the demographic trajectories of multiple cohorts couple together, and show that co-aging dynamics can account for the anomalous hazard curves exhibited by some species. In our model, multiple interdependency networks inflict damage on one other proportional to their number of functional nodes. We then fit our model predictions to three datasets describing (1) co-aging worm-pathogen populations (2) competing tree species. Lastly, we gather the mortality statistics of (3) machine-against-machine chess games to demonstrate that co-aging dynamics is not exclusive to biological systems.

physics.bio-ph↗