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While species fulfill many different roles in ecosystems, it has been suggested that numerous species might actually share the same function in a near neutral way. So-far, however, it is unclear whether such functional redundancy really exists. We scrutinize this question using extensive data on the world's 4168 species of diving beetles. We show that across the globe these animals have evolved towards a small number of regularly-spaced body sizes, and that locally co-existing species are either very similar in size or differ by at least 35%. Surprisingly, intermediate size differences (10-20%) are rare. As body-size strongly reflects functional aspects such as the food that these generalist predators can eat, these beetles thus form relatively distinct groups of functional look-a-likes. The striking global regularity of these patterns support the idea that a self-organizing process drives such species-rich groups to self-organize evolutionary into clusters where functional redundancy ensures resilience through an insurance effect.

Time-series of ecological and exploitation indicators collected from 19 ecosystems were analysed to investigate whether there have been temporal trends in the status of fish communities. Using linear and non-linear statistical methods, trends are reported for six indicators (mean length of fish in the community, mean lifespan, proportion of predatory fish, total biomass of surveyed species, mean trophic level of landings, and inverse fishing pressure), and the redundancy of these indicators across ecosystems is evaluated. The expected direction of change for an ecosystem that is increasingly impacted by fishing is a decline in all indicators. A mixture of negative and positive directions of change is recorded, both within and among all ecosystems considered. No consistent patterns in the redundancy of the ecological indicators across ecosystems emerged from the analyses, confirming that each indicator provided complementary information on ecosystem status. The different trends in indicators may reflect differing historical exploitation patterns, management, and environmental regimes in these systems. Commitment to monitoring programmes and development of system-specific baseline, target, and threshold reference levels are required. Improved understanding of the responsiveness and performance of ecological indicators to management actions are needed to address adequately whether ecosystems are recovering from, or being further impacted by, fishing, and whether management targets are being met. The relative effects of multiple environmental and ecological processes as well as multiple human-induced stressors that characterize exploited ecosystems also need to be quantified.

Population dynamics can be highly variable in the face of environmental heterogeneity, and understanding this variation is central in the study of ecology. Robust management decisions require that we understand how populations respond to management at a range of scales, and under a broad suite of conditions. Population models are potentially valuable tools in addressing this challenge. However, without adequate data, models can fail to produce useful results. Populations of arable weeds are particularly problematic in this respect, as they are widespread and their dynamics are extremely variable. Owing to the inherent cost of collecting data, most studies of plant population dynamics are derived from localized experiments under a small range of environmental conditions, limiting the extent to which variance in population dynamics can be measured. Density-structured models provide a route to rapid, large-scale analysis of population dynamics, and can expand the scale of ecological models that are directly tied to data. Here we extend previous density-structured models to include environmental heterogeneity, variation in management, and to account for inter-population variation. We develop, parameterize, and test hierarchical density-structured models for a common agricultural weed, black-grass (Alopecurus myosuroides). We model the dynamics of this species in response to crop management, using survey data gathered over 4 yr from 364 fields across a network of 45 UK farms. We show that hierarchical density-structured models provide a substantial improvement over their nonhierarchical counterparts. Using these models, we demonstrate that several alternative crop rotations are effective in reducing weed densities. Rotations with high wheat prevalence exhibit the most severe infestations, and diverse rotations generally have lower weed densities. However, a key outcome is that in many cases the effect of crop rotation is small compared to the high variability arising fro