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Although decades of research suggest that higher species richness improves ecosystem functioning and stability, planted forests are predominantly monocultures. To determine whether diversification of plantations would enhance aboveground carbon storage, we systematically reviewed over 11,360 publications, and acquired data from a global network of tree diversity experiments. We compiled a maximum dataset of 79 monoculture to mixed comparisons from 21 sites with all variables needed for a meta-analysis. We assessed aboveground carbon stocks in mixed-species planted forests vs. (a) the average of monocultures, (b) the best monoculture, and (c) commercial species monocultures, and examined potential mechanisms driving differences in carbon stocks between mixtures and monocultures. On average, we found that aboveground carbon stocks in mixed planted forests were 70% higher than the average monoculture, 77% higher than commercial monocultures, and 25% higher than the best performing monocultures, although the latter was not statistically significant. Overyielding was highest in four-species mixtures (richness range 2–6 species), but otherwise none of the potential mechanisms we examined (nitrogen-fixer present vs. absent; native vs. non-native/mixed origin; tree diversity experiment vs. forestry plantation) consistently explained variation in the diversity effects. Our results, predominantly from young stands, thus suggest that diversification could be a very promising solution for increasing the carbon sequestration of planted forests and represent a call to action for more data to increase confidence in these results and elucidate methods to overcome any operational challenges and costs associated with diversification. 

ABSTRACT AimEcological theory suggests that dispersal limitation and selection by climatic factors influence bacterial community assembly at a continental scale, yet the conditions governing the relative importance of each process remains unclear. The carnivorous pitcher plantSarracenia purpureaprovides a model aquatic microecosystem to assess bacterial communities across the host plant's north–south range in North America. This study determined the relative influences of dispersal limitation and environmental selection on the assembly of bacterial communities inhabitingS. purpureapitchers at the continental scale. LocationEastern United States and Canada. Time Period2016. Major Taxa StudiedBacteria inhabitingS. purpureapitchers. MethodsPitcher morphology, fluid, inquilines and prey were measured, and pitcher fluid underwent DNA sequencing for bacterial community analysis. Null modelling of β‐diversity provided estimates for the contributions of selection and dispersal limitation to community assembly, complemented by an examination of spatial clustering of individuals. Phylogenetic and ecological associations of co‐occurrence network module bacteria was determined by assessing the phylogenetic diversity and habitat preferences of member taxa. ResultsDispersal limitation was evident from between‐site variation and spatial aggregation of individual bacterial taxa in theS. purpureapitcher system. Selection pressure was weak across the geographic range, yet network module analysis indicated environmental selection within subgroups. A group of aquatic bacteria held traits under selection in warmer, wetter climates, and midge abundance was associated with selection for traits held by a group of saprotrophs. Processes that increased pitcher fluid volume weakened selection in one module, possibly by supporting greater bacterial dispersal. ConclusionDispersal limitation governed bacterial community assembly inS. purpureapitchers at a continental scale (74% of between‐site comparisons) and was significantly greater than selection across the range. Network modules showed evidence for selection, demonstrating that multiple processes acted concurrently in bacterial community assembly at the continental scale. 

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species—and to describe the structure, variation, and change of the ecological networks they form—we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.