Resilience Memory

DISCLAIMER — Real Science, No Framework Bridge

Why no UTAC/CREP/AFET bridge: not only because the cited literature already provides the necessary quantitative structure -- a deliberate choice. This project's highly speculative AFET/UTAC experiments must never stand in the way of climate/ecology topics being accessible and usable to people who don't work inside that construct and aren't looking for renormalization groups. Real, checkable science, without the burden of an unproven framework. See PACKAGE_REGISTRY.md's "Why no UTAC/CREP/AFET bridge in the climate/ecology series" (2026-08-31) in the GenesisAeon workspace root for the full canonical note.

Status: Real, peer-reviewed statistical methods + NO UTAC/CREP/AFET bridge

What this is

• A generic, real early-warning-signal toolkit for detecting **critical
• slowing down** in any time series the caller supplies: rolling
• variance, lag-1 autocorrelation and skewness, each tested for a trend
• with Kendall's tau (Dakos et al. 2012, PLOS ONE 7(7), e41010).
• The underlying physical concept -- recovery rate from small
• perturbations declines as a system nears a critical transition -- is
• Scheffer et al. (2009, Nature 461, 53-59) and was validated against
• eight real paleoclimate transitions by Dakos et al. (2008, PNAS
• 105(38), 14308-14312).
• A separate, explicitly stylized resilience-debt bookkeeping model
• (recovery.py): given a sequence of perturbations with a magnitude
• and a recovery time constant each, tracks how much displacement is
• still unresolved when the next perturbation hits. This operationalizes
• van Nes & Scheffer's (2007, American Naturalist 169(6), 738-747)
• finding that slow recovery from perturbations is itself a resilience
• indicator -- it

…

resilience-memory-utac

[](https://github.com/GenesisAeon) [](https://github.com/GenesisAeon/resilience-memory-utac/actions/workflows/ci.yml) [](https://www.python.org) [](LICENSE) [](https://doi.org/10.5281/zenodo.21821795)

GenesisAeon Package 97 — real critical-slowing-down statistics and post-perturbation resilience-debt tracking. Deliberately has no UTAC/CREP/AFET bridge — see DISCLAIMER.md.

For a plain-language explanation of the same topic (German, no jargon, written for general audiences), see WHITEPAPER.md.

What's real here

• Dakos et al. (2012, PLOS ONE): the generic early-warning-signal
• workflow — detrend a time series, compute rolling variance / lag-1
• autocorrelation / skewness, test each for a trend with Kendall's tau.
• Scheffer et al. (2009, Nature): the underlying concept — recovery
• rate from small perturbations declines as a system nears a critical
• transition ("critical slowing down").
• van Nes & Scheffer (2007, American Naturalist): slow recovery from
• perturbations, tracked here as an explicit "resilience-debt" — if a
• system hasn't recovered before the next shock, it carries the deficit
• forward.
• A live, verified illustration (not calibration input): Rhine at Kaub
• (24 cm, 2026-08-04, matching the 2018 record), Danube at Paks (-144 cm,
• below the 2018 record of -98 cm, triggering Hungary's first-ever full
• reactor shutdown), and Cernavoda NPP (Romania, reactor shutdown +
• emergency underwater demolition to redirect cooling water) — see
• DISCLAIMER.md for exactly what this case study is and
• is not used for.

Quickstart

bash pip install resilience-memory-utac

```python from resilience_memory_utac import compute_early_warning_report

any real time series you supply -- river discharge, coral cover, ... report = compute_early_warning_report(my_series) print(f"Variance trend: tau={report.variance_tau:.2f} (p={report.variance_p:.3f})") print(f"Autocorrelation trend: tau={report.autocorrelation_tau:.2f}") ```

```python from resilience_memory_utac import PerturbationEvent, compute_resilience_debt

events = [ PerturbationEvent(label="2018 low-water", time=0, magnitude=8.0, tau=365.0), PerturbationEvent(label="2026 low-water", time=2800, magnitude=10.0, tau=365.0), ] states = compute_resilience_debt(events) print(states[-1].fully_recovered) # False if the 2018 event hadn't fully decayed away ```

Development

bash pip install -e ".[dev]" pre-commit install ruff check src tests mypy src pytest

Citation

See CITATION.cff and .zenodo.json.