Early Warning Signals of Biodiversity Collapse

Ecological regime shifts -- abrupt, self-reinforcing transitions from one stable ecosystem state to another, often
ecologically degraded, state -- represent among the most dangerous consequences of biodiversity loss, because they
can be triggered by gradual changes in driver intensity that produce catastrophic ecological change with little apparent
warning before the tipping point is crossed. The theory of critical transitions predicts that approaching tipping points
produce characteristic statistical signatures -- critical slowing down (CSD) -- in the temporal dynamics of ecosystem state
variables: as a system approaches its tipping point, its recovery from small perturbations slows progressively (increasing
autocorrelation; increasing variance; increasing skewness), providing early warning signals (EWS) that precede the
actual transition. This study provides the most comprehensive empirical validation of biodiversity EWS yet conducted,
testing CSD indicators in 247 long-term biodiversity time series from 84 ecosystems across 18 biome types that
experienced documented regime shifts (comparison sites that did not shift used as controls). Lag-1 autocorrelation (AR1)
and coefficient of variation (CV) of species richness time series both increased significantly before 74.7% of documented
regime shifts (AR1 mean +0.38; CV mean +47.4% in the decade before transition vs. control sites; both p < 0.001). Lead
time of EWS before the actual transition averaged 8.4 +- 3.4 years -- sufficient for conservation management intervention
if monitoring systems detect the signal. Functional diversity variance (FDiv CV) outperformed species richness CV as an
EWS (84.7% vs. 74.7% detection rate; p = 0.024), with a longer mean lead time (12.4 years vs. 8.4 years) -- confirming
that functional diversity time series provide earlier and more sensitive early warning than species richness alone