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Finding suitable state indicators is challenging and cumbersome in stochastic and complex ecological systems. Typically, a great focus is given to criteria such as data availability, scientific basis, or measurability. Features associated with the indicator's performance such as sensitivity or robustness are often neglected due to the lack of quantitative validation tools. In this paper, we present a simple but flexible framework for selecting and validating the performance of food web indicators. In specific, we suggest a 7-step process in which indicator performances at a regional scale are quantified and visualized allowing for the selection of complementary indicator suites. We demonstrate its application by comparing the performance of pelagic food web indicators for three basins of the Baltic Sea and by assessing the food web status based on selected indicator suites. Our analysis sheds light on spatial differences in indicator performances with respect to direct and indirect pressures, the role of non-linearity and non-additivity in pressure responses, as well as relationships between indicators caused by species interactions. Moreover, our results suggest that the present food web states in the Bornholm and Gotland basins of the Baltic Sea deviate distinctly from an earlier reference period. We advocate the use of our quantitative framework as decision-support tool for selecting suites of complementary indicators under given management schemes such as the EU Marine Strategy Framework Directive.

Ecosystem-based management (EBM) is commonly applied to achieve sustainable use of marine resources. For EBM, regular ecosystem-wide assessments of changes in environmental or ecological status are essential components, as well as assessments of the effects of management measures. Assessments are typically carried out using indicators. A major challenge for the usage of indicators in EBM is trophic interactions as these may influence indicator responses. Trophic interactions can also shape trade-offs between management targets, because they modify and mediate the effects of pressures on ecosystems. Characterization of such interactions is in turn a challenge when testing the usability of indicators. Climate variability and climate change may also impact indicators directly, as well as indirectly through trophic interactions. Together, these effects may alter interpretation of indicators in assessments and evaluation of management measures. We developed indicator networks - statistical models of coupled indicators - to identify links representing trophic interactions between proposed food-web indicators, under multiple anthropogenic pressures and climate variables, using two basins in the Baltic Sea as a case study. We used the networks to simulate future indicator responses under different fishing, eutrophication and climate change scenarios. Responsiveness to fishing and eutrophication differed between indicators and across basins. Almost all indicators were highly dependent on climatic conditions, and differences in indicator trajectories > 10% were found only in comparisons of future climates. In some cases, effects of nutrient load and climate scenarios counteracted each other, altering how management measures manifested in the indicators. Incorporating climate change, or other regionally non-manageable drivers, is thus necessary for an accurate interpretation of indicators and thereby of EBM measure effects. Quantification of linkages between indicators across trophic levels is similarly a prerequisite for tracking effects propagating through the food web, and, consequently, for indicator interpretation. Developing meaningful indicators under climate change calls for iterative indicator validations, accounting for natural processes such as trophic interactions and for trade-offs between management objectives, to enable learning as well as setting target levels or thresholds triggering actions in an adaptive manner. Such flexible strategies make a set of indicators operational over the long-term and facilitate success of EBM.