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.

Food-web indicators for marine management are required to describe the functioning and structure of marine food-webs. In Europe, the Marine Strategy Framework Directive (MSFD), intended to lead to a 'good environmental status' of the marine waters, requires indicators of the status of the marine environment that also respond to manageable anthropogenic pressures. Identifying such relationships to pressures is particularly challenging for food-web indicators, as they need to be disentangled from linkages between indicators of different functional groups caused by species interactions. Still, such linkages have not been handled in the indicator development. Here we used multivariate autoregressive time series models to identify how fish indicators in an exploited food-web relate to fishing, climate and eutrophication, while accounting for the linkages between indicators caused by species interactions. We assembled 31-year long time series of indicators of key functional groups of fish in the Central Baltic Sea pelagic food-web, which is characterized by strong trophic links between cod (Gadus morhua) and its main fish prey sprat (Sprattus sprattus) and herring (Clupea harengus). These food-web indicators were either abundance-based indicators of key piscivores (cod) and zooplanktivores (sprat and herring) or size-based indicators of the corresponding trophic groups (biomass of large predatory fish (cod >= 38 cm) and biomass of small prey fish (sprat and herring <10 cm)). Comparative analyses of models with and without linkages among indicators showed that for both types of indicators, linkages corresponding to predator-prey feedbacks and intra-specific density-dependence were essential to explain temporal variation in the indicators. Thus, no indicator-pressure relationships could be found that explained the indicators' variation unless such linkages were accounted for. When accounting for these, we found that the indicators overall respond to multiple pressures acting simultaneously rather than to single pressures, as no pressure alone could explain how the indicators developed over time. The manageable pressures fishing and eutrophication, as well as the prevailing hydrological conditions influenced by climate, were all needed to reproduce the inter-annual changes in these food-web indicators combined, although individual relationships differed between the indicators. We conclude that our innovative indicator-testing framework can therefore be used to identify responses of food-web indicators to manageable pressures while accounting for the biotic interactions in food-webs linking such indicators.

Regime shifts are characterized by sudden, substantial and temporally persistent changes in the state of an ecosystem. They involve major biological modifications and often have important implications for exploited living resources. In this study, we examine whether regime shifts observed in 11 marine systems from two oceans and three regional seas in the Northern Hemisphere (NH) are synchronous, applying the same methodology to all. We primarily infer marine pelagic regime shifts from abrupt shifts in zooplankton assemblages, with the exception of the East Pacific where ecosystem changes are inferred from fish. Our analyses provide evidence for quasi-synchronicity of marine pelagic regime shifts both within and between ocean basins, although these shifts lie embedded within considerable regional variability at both year-to-year and lower-frequency time scales. In particular, a regime shift was detected in the late 1980s in many studied marine regions, although the exact year of the observed shift varied somewhat from one basin to another. Another regime shift was also identified in the mid-to late 1970s but concerned less marine regions. We subsequently analyse the main biological signals in relation to changes in NH temperature and pressure anomalies. The results suggest that the main factor synchronizing regime shifts on large scales is NH temperature; however, changes in atmospheric circulation also appear important. We propose that this quasi-synchronous shift could represent the variably lagged biological response in each ecosystem to a large-scale, NH change of the climatic system, involving both an increase in NH temperature and a strongly positive phase of the Arctic Oscillation. Further investigation is needed to determine the relative roles of changes in temperature and atmospheric pressure patterns and their resultant teleconnections in synchronizing regime shifts at large scales.

Understanding and predicting species distribution in space and time and consequently community structure and dynamics is an important issue in ecology, and particularly in climate change research. A crucial factor determining the composition and dynamics of animal populations is habitat heterogeneity, i.e., the number of structural elements in a given locality. In the marine pelagic environment habitat heterogeneity is represented by the distribution of physical oceanographic parameters such as temperature, salinity and oxygen that are closely linked to atmospheric conditions. Little attention has been given, however, to the role of habitat heterogeneity in modulating the response of animal communities to external climate forcing. Here we investigate the long-term dynamics of Acartia spp., Temora longicornis, and Pseudocalanus acuspes, three dominant zooplankton species inhabiting different pelagic habitats in the Central Baltic Sea (CBS). We use the three copepods as indicator species for changes in the CBS zooplankton community and apply non-linear statistical modeling techniques to compare spatial population trends and to identify their drivers. We demonstrate that effects of climate variability and change depend strongly on species-specific habitat utilization, being more direct and pronounced at the upper water layer. We propose that the differential functional response to climate-related drivers in relation to strong habitat segregation is due to alterations of the species' environmental niches. We stress the importance of understanding how anticipated climate change will affect ecological niches and habitats in order to project spatio-temporal changes in species abundance and distribution.

Increasing pressure on animal populations through climate change and anthropogenic exploitation fuel the need to understand complex life cycle dynamics of key ecosystem species and their responses to external factors. Here, we provide a novel, integrative study on the long-term population dynamics of Pseudocalanus acuspes, a key species in the Baltic Sea, explicitly considering its distinct life-history stages, and testing for linear, non-linear, and non-additive climate and food web effects. Based on a unique data set of stage-specific abundance covering almost 5 decades of sampling (1960 to 2008, with 1408 samples), we use generalized additive modeling (GAM) and its respective non-additive threshold (TGAM) formulation to test for (1) density effects on subsequent life-history stages within the internal life cycle, (2) the effect of exogenous bottom-up (i.e. hydro-climatic) and top-down (i.e. predation) pressures, and (3) changes between bottom-up and top-down regulation. We show that linear density effects are always present, explaining a high proportion of interannual variability, while effects of external pressures are non-linear or non-additive and strongly stage- and season-specific. In general, younger stages of P. acuspes are more affected by atmospheric winter conditions and water temperature, whereas older stages are influenced by conditions of deepwater salinity and predation pressure. These bottom-up processes, however, are not necessarily stable, and can depend on the level of top-down predation pressure. Our study demonstrates the complex and non-stationary interplay between internal and external factors regulating long-term animal population dynamics.

Scale is a key to determining which processes drive community structure. We analyse size distributions of phytoplankton to determine time scales at which we can observe either fixed environmental characteristics underlying communities structure or competition-driven size distributions. Using multiple statistical tests, we characterise size distributions of phytoplankton from 20-year time series in two sites of the Baltic Sea. At large temporal scales (5-20 years), size distributions are unimodal, indicating that fundamental barriers to existence are here subtler than in other systems. Frequency distributions of the average size of the species weighted by biovolume are multimodal over large time scales, although this is the product of often unimodal short-term (<1 year) patterns. Our study represents a much-needed structured, high-resolution analysis of phytoplankton size distributions, revealing that short-term analyses are necessary to determine if, and how, competition shapes them. Our results provide a stepping-stone on which to further investigate the intricacies of competition and coexistence.

Several marine ecosystems under anthropogenic pressure have experienced shifts from one ecological state to another. In the central Baltic Sea, the regime shift of the 1980s has been associated with food-web reorganization and redirection of energy flow pathways. These long-term dynamics from 1974 to 2006 have been simulated here using a food-web model forced by climate and fishing. Ecological network analysis was performed to calculate indices of ecosystem change. The model replicated the regime shift. The analyses of indicators suggested that the system's resilience was higher prior to 1988 and lower thereafter. The ecosystem topology also changed from a web-like structure to a linearized food-web.