The effect of biodiversity on ecosystem functioning has proven variable both within and among manipulative studies. Species richness is the most commonly used measure of biodiversity in such studies, but the range of species’ functional traits (functional diversity), not the number of species per se, likely underpins a key mechanistic link between species richness and ecosystem functioning. However, the majority of experiments that have examined the effect of functional diversity have manipulated functional group richness, an approach recognised to suffer numerous limitations. Continuous measures of functional diversity avoid many of these limitations, but the relationship between continuous functional diversity and the magnitude of ecosystem processes has been largely untested. Using one vs two‐species mixtures of rock pool macroalgae as a model, we conducted a field experiment to determine the effect of a continuous measure of functional diversity (functional attribute diversity, FAD, the degree of functional differentiation based on four functional traits) on the magnitude of net primary productivity and overyielding, based upon two alternative null‐models. The total magnitude of productivity was largely determined by the identity of species present, not FAD. However, FAD proved to be a good predictor of overyielding (variation in productivity after the dominant effects of species identity had been accounted for). Furthermore, despite differences in the mean magnitude of the effect of combining species, the positive relationship between FAD and overyielding was consistent according to both additive and substitutive null‐models. Our findings imply that whilst knowledge of species’ independent contributions remains indispensable in the prediction of biotic effects on ecosystem functioning within a trophic level, continuous measures of functional diversity should be used as a supplementary tool to predict the magnitude of overyielding, thereby refining predictions.

Summary1. The nets used in bottom trawl fisheries cause mortality of benthic invertebrates and this can decrease the long-term availability of prey to exploited fish species by reducing the abundance of benthic invertebrates. This may have consequences for the sustainability of fisheries. 2. We assessed the impact of bottom trawling on the food availability of fish by comparing the condition of fish (as weight-at-length) in an area that had a steep commercial bottom-trawling gradient in the Irish Sea but otherwise homogeneous environmental conditions. 3. We found that the condition of the important commercial flatfish plaice Pleuronectes platessa was negatively related to trawling frequency, and this could be explained by a reduced production of the infaunal invertebrates they feed on. Density-dependent changes in competition over food could not explain this difference. No effect of trawling on the condition of the flatfish dab Limanda limanda was detected. Whiting Merlangius merlangus feeds primarily on fish, and therefore, no effect of bottom trawling on its condition was expected or detected. 4. This study therefore indicates that bottom trawl fisheries may have a negative effect on the condition of some of their target species, but not others, by reducing the abundance of their benthic prey. 5. Synthesis and application. Bottom trawls may indirectly affect the population size and growth rate of the target fish species and result in lower fishing yields. Such reductions in the yield and sustainability of fisheries are highly undesirable. The effects of bottom trawls may be mitigated by the modification of fishing gears or by minimizing the area of the seabed fished by bottom trawls.

Although it seems obvious that with more data, the predictive capacity of ecological models should improve, a way to demonstrate this fundamental result has not been so obvious. In particular, when the standard models themselves are inadequate (von Bertalanffy, extended Ricker etc.) no additional data will improve performance. By using time series from the Sir Alister Hardy Foundation for Ocean Science Continuous Plankton Recorder, we demonstrate that longterm observations reveal both the prevalence of nonlinear processes in species abundances and an improvement in out-of-sample predictability as the number of observations increase. The empirical results presented here quantitatively demonstrate the importance of long-term temporal data collection programs for improving ecosystem models and forecasts, and to better support environmental management actions.

Adoption of the ecosystem approach to fisheries management relies on recognition of the link between fish and other components of the ecosystem, namely their physical and biological habitat. However, identifying the habitat requirements of marine fishes and hence determining their distribution in space and time is scientifically complex. We analysed the methodologies and findings of research on temperate, demersal fish habitat requirements to highlight the main developments in this field and to identify potential shortfalls. Many studies were undertaken over large spatial scales (≥100s km2) and these generally correlated abundances of fish to abiotic variables. Biological variables were accounted for less often. Small spatial scale (≤m2), experimental studies were comparatively sparse and commonly focused on biotic variables. Whilst the number of studies focusing on abiotic variables increased with increasing spatial scale, the proportion of studies finding significant relationships between habitat and fish distribution remained constant. This mismatch indicates there is no justification for the tendency to analyse abiotic habitat variables at large spatial scales. Innovative modelling techniques and habitat mapping technologies are developing rapidly, providing new insights at the larger spatial scales. However, there is a clear need for a reduction in study scale, or increase in resolution additional to the integration of biotic variables. We argue that development of sound predictive science in the field of demersal fish habitat determination is reliant on a change in focus along these lines. This is especially important if spatial management strategies, such as Marine Protected Areas (MPA) or No Take Zones (NTZ), are to be used in future ecosystem‐based approaches to fisheries management.

Diversity patterns are determined by biogeographic, energetic, and anthropogenic factors, yet few studies have combined them into a large‐scale framework in order to decouple and compare their relative effects on fish faunas. Using an empirical dataset derived from 1527 underwater visual censuses (UVC) at 18 oceanic islands (five different marine provinces), we determined the relative influence of such factors on reef fish species richness, functional dispersion, density and biomass estimated from each UVC unit. Species richness presented low variation but was high at large island sites. High functional dispersion, density, and biomass were found at islands with large local species pool and distance from nearest reef. Primary productivity positively affected fish richness, density and biomass confirming that more productive areas support larger populations, and higher biomass and richness on oceanic islands. Islands densely populated by humans had lower fish species richness and biomass reflecting anthropogenic effects. Species richness, functional dispersion, and biomass were positively related to distance from the mainland. Overall, species richness and fish density were mainly influenced by biogeographical and energetic factors, whereas functional dispersion and biomass were strongly influenced by anthropogenic factors. Our results extend previous hypotheses for different assemblage metrics estimated from empirical data and confirm the negative impact of humans on fish assemblages, highlighting the need for conservation of oceanic islands.