Novel approaches for bridging chemical and biological time series observations to reveal underlying impacts of ocean acidification on marine organisms and ecosystems

Abstract. There is increasing demand to compare long-term biological observations with derived or measured carbonate chemistry data to characterize the biological consequences of ocean acidification (OA) in natural environments. Meeting this need calls for a standardized methodology by which to quantify and directly compare biological and carbonate chemistry change. Widdicombe et al. (2023) proposed a conceptual framework based on biological traits and paired biological-chemical rate comparisons, but its practical implementation has remained unresolved.

Here we operationalize that conceptual framework through a standardized analytical workflow that integrates heterogeneous biological observations with established OA time-series methodology. The workflow addresses five analytical challenges that hinder comparison of long-term biological and OA records: 1) fundamentally different temporal structures of biological and OA time series, 2) heterogeneity of biological observations, 3) sparse and irregular biological sampling, 4) nonlinear biological trajectories, and 5) appearance–disappearance events that invalidate conventional relative change metrics. The workflow addresses these challenges through standardized biological grouping, annual aggregation, piecewise linear segmentation, normalization by ecological boundaries, and direct pairing of biological and chemical rates of change.

We evaluated workflow performance using 36 synthetic biological time series generated by applying predefined temperature-pH-driven biological performance functions to a 108-year hydrodynamic-biogeochemical model simulation under the SSP3-7.0 emissions scenario. Biological rates estimated by the workflow closely agreed with the corresponding reference rates. Rate estimates remained similar across the two annual representations, and their relative ordering was largely preserved across contrasting site-specific temperature-pH transitions. These results demonstrate the robustness of the workflow under the tested patterns of abiotic forcing.

The analytical workflow developed here operationalizes the conceptual approach of Widdicombe et al. (2023) by standardizing the estimation and comparison of rates of change in biological and carbonate chemistry time series. It supports comparisons among compatible biological indicators while retaining the ecological context of each time series. The workflow does not establish causality; instead, it assesses the temporal coherence between long-term changes in candidate biological indicators of OA and concurrent changes in carbonate chemistry. It therefore provides a practical foundation for regional and global syntheses of biological responses to OA and other long-term abiotic stressors.