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Akiva Goldberg

Publications and source records attributed to Akiva Goldberg.

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Correlations at criticality in ecological communities

Ecological communities are continually reshaped by invasion, exclusion, and diversification, processes that naturally drive them toward the boundary of dynamical stability. Near such a boundary, a soft mode relaxes increasingly slowly and, under stochastic forcing, is expected to dominate the fluctuations, effectively reducing the dynamics to one dimension and generating strong positive and negative abundance correlations. Such correlations have therefore been proposed as signatures of an imminent transition. Here we show that this expectation can fail even arbitrarily close to criticality. The reason is that spectral softness does not guarantee stochastic visibility: the soft mode must receive enough environmental forcing to dominate the fluctuation background generated by the remaining modes. We demonstrate this mechanism in three ecological scenarios: a synthetic feasible community, a local community assembled by immigration from a regional pool, and a community generated by repeated diversification. In all three, communities approach marginal stability without developing the near-perfect pairwise correlations predicted by the single-mode picture. Thus, proximity to ecological criticality need not be visible in equal-time pairwise correlations.

q-bio.PE

When do correlations reflect biological similarity in ecological dynamics?

The structure of competitive ecological communities is shaped by the strength of interactions between species, which in turn reflects their biological similarity. At the same time, the stochastic forcing that drives abundance fluctuations is itself biologically grounded: species that are more similar may be expected to respond more similarly to environmental variation. This motivates the increasingly common use of correlations in abundance time series, particularly in microbial communities, as proxies for biological similarity or niche overlap. Here we analyze the relation between biological similarity and abundance correlations in stochastic community models. We require that the stochastic forcing acting on different species be correlated in proportion to their biological similarity, and ask how such forcing is reflected in abundance correlations. We show that this requirement cannot, in general, be satisfied within the widely used stochastic Lotka-Volterra framework, and that even when it is, abundance correlations carry no information about niche overlap. In contrast, consumer-resource models provide a natural framework for biologically grounded stochasticity. In this setting, however, the interpretation of abundance correlations depends strongly on the pathway through which noise enters the system: direct forcing of consumers and resource-mediated fluctuations encode different biological quantities. These results have implications both for the modeling of stochastic ecological communities and for understanding what can, and cannot, be inferred from correlations in community time series.

q-bio.PE