Biological systems under chronic resource overload often exhibit asymmetric transitions into high-load states that are difficult to reverse. Within a bow-tie (hourglass) framework, such dynamics arise when diverse inputs are funnelled through a constrained regulatory core governing system-level responses. Here, lake eutrophication and human obesity are analysed as structurally distinct yet dynamically analogous manifestations of resource overload. In lakes, external nutrient inputs and internal biogeochemical feedbacks drive shifts from clear-water, macrophyte-dominated regimes to hypertrophic, phytoplankton-dominated states. In humans, sustained caloric surplus interacts with metabolic–hormonal regulation and behavioural–social drivers to promote the development and stabilisation of obesity. In both systems, reinforcing feedbacks organise around a central regulatory core, reducing flexibility, generating hysteresis, and constraining recovery trajectories. Despite these similarities, key asymmetries emerge. In lakes, dynamics under overload are dominated by a limited set of reinforcing feedbacks, whereas in obesity regulation remains distributed across interacting physiological, behavioural, and environmental domains. In both cases, responses involve cascade-like propagation of effects, taking the form of trophic cascades in lakes and cross-domain feedback cascades in humans. These results show that similar system-level dynamics, including alternative stable states, tipping points, and hysteresis with constrained reversibility, can arise from differently structured regulatory architectures. The comparison demonstrates that reversibility is system-specific and shaped by the organisation of the regulatory core and associated feedbacks. Interpreting eutrophication and obesity through a bow-tie framework provides a comparative, architecture-based perspective on resource overload and helps explain why effective interventions require coordinated actions targeting multiple components of the feedback structure.
Cyanobacteria play a critical role in regulating carbon, nitrogen, and phosphorus cycles in the Baltic Sea, seasonally forming extensive blooms under nitrogen-limited conditions in summer. Understanding their responses to environmental disturbances is crucial in the Baltic Sea where increasing and persistent surface water temperature anomalies were observed over the past two decades. During a 17-day mesocosm experiment in the southwestern Finnish archipelago (Gulf of Finland) designed to investigate microbial community dynamics under varying nutrient conditions, the unexpected occurrence of a natural disturbance event created a unique opportunity to assess the effects of pronounced physical changes on cyanobacterial dynamics. The natural disturbance overshadowed the expected effects of the nutrient treatments, which was especially evident for cyanobacteria. The picocyanobacterium Cyanobium spp. emerged as the dominant species throughout the study, particularly following the occurrence of the near gale wind-driven rainfall, likely due to its adaptability to rapid environmental changes. Conversely, the filamentous cyanobacteria Aphanizomenon spp. and Pseudoanabaena spp. thrived under stable conditions. These findings highlight the resilience of picocyanobacteria to environmental fluctuations and their primary role in driving cyanobacterial community dynamics during summer in the Baltic Sea, where natural perturbations are expected to occur with increasing frequency due to climate change.
Abstract Protists play important roles in food chains and symbioses in soil and aquatic environments, displaying an enormous morphological and functional diversity 1,2 . While most commonly found protist species are well known to science, our global-scale environmental DNA survey across soil, water, and sediments reveals dozens of novel, phylum-level phylogenetic lineages that remain to be characterized for basic morphology and function. A vast majority of these undescribed taxa occur in marine water and sediments, but some are common in soil. Most of these novel taxa have distinct substrate and habitat preferences and biogeographic patterns. To accord these lineages scientific agency and enable unambiguous scientific communication, we propose formal names for 150 species to phylum-level taxa from 25 deep lineages based on eDNA and rRNA gene long-read sequence information.
Abstract Traditional plankton sampling methods are labor-intensive, time-consuming and often fail to resolve the fine-scale spatial and temporal variability that characterizes plankton ecosystems. Underwater imaging systems offer a powerful alternative, enabling in situ observations across a wide range of organism sizes and environmental conditions. However, imaging platforms differ substantially in illumination strategy, optical design, sampling volume, deployment mode and data requirements, and no single system is optimal for all ecological questions. Selecting the appropriate instrument is therefore a prerequisite for obtaining representative, interpretable and comparable datasets. Here, we provide a practical primer on underwater plankton imaging systems, synthesizing their core components, operational principles and ecological applications. We introduce a stepwise decision framework centered on the trade-offs among resolution, representativeness and data volume and show how study objectives, target organisms, environmental conditions, deployment platforms and data-processing capacity guide instrument choice. Case studies are used to demonstrate how the framework supports real-world applications ranging from near-real-time monitoring to fine-scale spatial mapping and community-composition assessment. Finally, we discuss how thoughtful instrument selection, standardized metadata and intercalibration can support interoperable and FAIR (Findable, Accessible, Interoperable, Reusable) plankton imaging datasets.
Abundance indices from fisheries-independent surveys provide key information for fish stock assessments, serving as a foundation for sustainable resource management. Changes in survey effort, e.g., caused by vessel breakdowns or bad weather conditions, can lead to areas not being covered in certain years. These spatio-temporal gaps in survey coverage increase uncertainty or can even lead to discontinuation in time series. The current approach for imputing missing strata in Baltic pelagic clupeid surveys uses area-corrected abundances from higher-level subdivision units (baseline model), which does not account for stratum-specific effects and requires at least partial subdivision coverage. We tested three alternative imputation methods: Linear mixed-effects models (LMMs), Generalized additive models (GAMs), and Gradient boosted trees (XGB). Our results suggest that modelling abundance variations across strata, as implemented in the LMMs, improved abundance estimates compared to the baseline model, particularly when only few areas were not covered, i.e., under typical annual variations in survey coverage. When larger areas were not covered, LMMs, relying on explicit spatial strata, performed worse, whereas the XGB models and, in particular, the spatial GAM remained robust and could still be applied even when entire subdivisions were not surveyed. In conclusion, advanced data imputation techniques can enhance the robustness of abundance indices and should be considered as standard practice in survey groups when survey effort varies between years.
