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A maximum entropy perspective reveals deviations from steady state during active diversification

Rominger, A. J.; Thai, K.; Gillespie, R. G.; Gruner, D. S.; Harte, J.

2026-06-23 ecology
10.64898/2026.06.22.733811 bioRxiv
Show abstract

Ecosystems are rarely at steady state, yet most theory predicting universal biodiversity patterns assumes they are. Here, we test whether and how eco-evolutionary dynamics drive departures from steady state by combining arthropod community data from the geologic chronosequence of the Hawaiian Archipelago with the Maximum Entropy Theory of Ecology (METE), a minimalist steady-state framework that simultaneously predicts species abundance distributions (SADs) and individual metabolic rate distributions (IPDs). The chronosequence of the Hawaiian Archipelago has yielded insights into eco-evolutionary processes because ecosystems growing on different aged substrates offer snapshots of community assembly with different histories. We find that deviations from METE peak at geologically middle-aged sites (150 Kya-1.4 Mya), consistent with active adaptive radiation pushing communities away from statistical steady state. Within-site {beta}-diversity, which also peaks at middle-aged sites, robustly predicts deviations from METE across all sites, while the proportion of non-native species predicts deviations only after excluding the geologically youngest site. Partitioning {beta}-diversity between native and non-native species resolves this discrepancy: at the youngest site, non-native species are distributed homogeneously and do not elevate {beta}-diversity despite their high proportional representation. Together, these results are consistent with a trajectory from young, dispersal-assembled communities near statistical steady state, through an eco-evolutionary non-steady-state transition driven by diversification, to a new stable steady state at the oldest sites. Our findings suggest that periods of active diversification create windows of ecological instability that may facilitate biological invasion, with implications for understanding invasion dynamics in biodiversity hotspots.

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