Lakes: sediments of the past to better predict their future

The three-phase design is exemplary: it de-risks the hypothesis through in silico validation before committing to expensive fieldwork, and the explicit GO/NO-GO/PIVOT criteria at each phase provide a clear, pre-registered decision framework that prevents confirmation bias and allows for adaptive management of the research plan.

The hypothesis is theoretically well-grounded in the framework of alternative stable states and regime shifts in lake ecosystems. The explicit use of paleo-derived pre-disturbance baselines as proxies for the ‘clear-water state’ and historical thresholds as empirical anchors for critical nutrient loading is a sophisticated and coherent application of resilience theory to management. This directly addresses the known issue of shifting baselines in contemporary monitoring.

The attempt to use palaeoecological data as a Bayesian constraint to reduce uncertainty in management models is a conceptually interesting and potentially innovative approach, which merits exploration.

The panel targets a paying regulatory need: basin agencies (e.g. Agences de l'Eau in France, RIVM in the Netherlands, US EPA) and engineering consultancies (e.g. Suez, Arcadis, WSP) must justify nutrient reduction targets (Water Framework Directive, WFD) with reduced uncertainty margins to avoid treatment overcosts (wastewater treatment plants) or fines.

Conceptual originality: the integration of palaeoecological data as Bayesian priors in a mechanistic water-quality model (PCLake) is an innovative approach that addresses a methodological bottleneck identified in waterbody management (uncertainty in nutrient-reduction targets).