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1. A fundamental goal of ecological network research is to understand how the complexity observed in nature can persist and how this affects ecosystem functioning. This is essential for us to be able to predict, and eventually mitigate, the consequences of increasing environmental perturbations such as habitat loss, climate change, and invasions of exotic species. 2. Ecological networks can be subdivided into three broad types: 'traditional' food webs, mutualistic networks and host-parasitoid networks. There is a recent trend towards cross-comparisons among network types and also to take a more mechanistic, as opposed to phenomenological, perspective. For example, analysis of network configurations, such as compartments, allows us to explore the role of co-evolution in structuring mutualistic networks and host-parasitoid networks, and of body size in food webs. 3. Research into ecological networks has recently undergone a renaissance, leading to the production of a new catalogue of evermore complete, taxonomically resolved, and quantitative data. Novel topological patterns have been unearthed and it is increasingly evident that it is the distribution of interaction strengths and the configuration of complexity, rather than just its magnitude, that governs network stability and structure. 4. Another significant advance is the growing recognition of the importance of individual traits and behaviour: interactions, after all, occur between individuals. The new generation of high-quality networks is now enabling us to move away from describing networks based on species-averaged data and to start exploring patterns based on individuals. Such refinements will enable us to address more general ecological questions relating to foraging theory and the recent metabolic theory of ecology. 5. We conclude by suggesting a number of 'dead ends' and 'fruitful avenues' for future research into ecological networks.

The growing use of functional traits in ecological research has brought new insights into biodiversity responses to global environmental change. However, further progress depends on overcoming three major challenges involving (a) statistical correlations between traits, (b) phylogenetic constraints on the combination of traits possessed by any single species, and (c) spatial effects on trait structure and trait–environment relationships. Here, we introduce a new framework for quantifying trait correlations, phylogenetic constraints and spatial variability at large scales by combining openly available species' trait, occurrence and phylogenetic data with gridded, high‐resolution environmental layers and computational modelling. Our approach is suitable for use among a wide range of taxonomic groups inhabiting terrestrial, marine and freshwater habitats. We demonstrate its application using freshwater macroinvertebrate data from 35 countries in Europe. We identified a subset of available macroinvertebrate traits, corresponding to a life‐history model with axes of resistance, resilience and resource use, as relatively unaffected by correlations and phylogenetic constraints. Trait structure responded more consistently to environmental variation than taxonomic structure, regardless of location. A re‐analysis of existing data on macroinvertebrate communities of European alpine streams supported this conclusion, and demonstrated that occurrence‐based functional diversity indices are highly sensitive to the traits included in their calculation. Overall, our findings suggest that the search for quantitative trait–environment relationships using single traits or simple combinations of multiple traits is unlikely to be productive. Instead, there is a need to embrace the value of conceptual frameworks linking community responses to environmental change via traits which correspond to the axes of life‐history models. Through a novel integration of tools and databases, our flexible framework can address this need. [ABSTRACT FROM AUTHOR]

1. Recent efforts to understand how the patterning of interaction strength affects both structure and dynamics in food webs have highlighted several obstacles to productive synthesis. Issues arise with respect to goals and driving questions, methods and approaches, and placing results in the context of broader ecological theory. 2. Much confusion stems from lack of clarity about whether the questions posed relate to community-level patterns or to species dynamics, and to what authors actually mean by the term 'interaction strength'. Here, we describe the various ways in which this term has been applied and discuss the implications of loose terminology and definition for the development of this field. 3. Of particular concern is the clear gap between theoretical and empirical investigations of interaction strengths and food web dynamics. The ecological community urgently needs to explore new ways to estimate biologically reasonable model coefficients from empirical data, such as foraging rates, body size, metabolic rate, biomass distribution and other species traits. 4. Combining numerical and analytical modelling approaches should allow exploration of the conditions under which different interaction strengths metrics are interchangeable with regard to relative magnitude, system responses, and species identity. 5. Finally, the prime focus on predator-prey links in much of the research to date on interaction strengths in food webs has meant that the potential significance of nontrophic interactions, such as competition, facilitation and biotic disturbance, has been largely ignored by the food web community. Such interactions may be important dynamically and should be routinely included in future food web research programmes. [ABSTRACT FROM AUTHOR]

Excess fine sediment, comprising particles <2 mm in diameter, is a major cause of ecological degradation in rivers. The erosion of fine sediment from terrestrial or aquatic sources, its delivery to the river, and its storage and transport in the fluvial environment are controlled by a complex interplay of physical, biological, and anthropogenic factors. While the physical controls exerted on fine sediment dynamics are relatively well‐documented, the role of biological processes and their interactions with hydraulic and physicochemical phenomena has been largely overlooked. The activities of biota, from primary producers to predators, exert strong controls on fine sediment deposition, infiltration, and resuspension. For example, extracellular polymeric substances associated with biofilms increase deposition and decrease resuspension. In lower energy rivers, aquatic macrophyte growth and senescence are intimately linked to sediment retention and loss, whereas riparian trees are dominant ecosystem engineers in high energy systems. Fish and invertebrates also have profound effects on fine sediment dynamics through activities that drive both particle deposition and erosion depending on species composition and abiotic conditions. The functional traits of species present will determine not only these biotic effects but also the responses of river ecosystems to excess fine sediment. We discuss which traits are involved and put them into context with spatial processes that occur throughout the river network. While strides towards better understanding of the impacts of excess fine sediment have been made, further progress to identify the most effective management approaches is urgently required through close communication between authorities and scientists. This article is categorized under: Water and Life > Nature of Freshwater EcosystemsWater and Life > Stresses and Pressures on EcosystemsScience of Water > Water and Environmental Change Controls on the delivery, transport and storage of fine sediment, and the resulting ecological responses in river networks. From the sediment sources in the landscape to the ecological impact in the river, the transport of particles and the responses of biota are subject to potential lags and delays as sediment is temporarily stored and time is taken for local populations to reach critical life‐stages where fine sediment limits survival. [ABSTRACT FROM AUTHOR]