SummaryWe conducted the most extensive meta-analysis of plant and animal responses to elevated CO 2 to date. We analysed > 5000 data points extracted from 270 papers published between 1979 and 2009. We examined the changes in 19 animal response variables to the main effect of elevated CO 2 . We found strong evidence for significant variation among arthropod orders and feeding guilds, including interactions in the direction of response. We also examined the main effects of elevated CO 2 on: six plant growth and allocation responses, seven primary metabolite responses, eight secondary metabolite responses, and four physical defence responses. We examined these response variable changes under two-way and three-way interactions between CO 2 and: soil nitrogen, ambient temperature, drought, light availability, photosynthetic pathway, reproductive system, plant growth rate, plant growth form, tissue type, and nitrogen fixation. In general we found smaller effect sizes for many response variables than have been previously reported. We also found that many of the oft-reported main effects of CO 2 obscure the presence of significant two-and three-way interactions, which may help better explain the relationships between the response variables and elevated CO 2 .

The power law that describes the relationship between species richness and area size is one of the few generalizations in ecology, but recent studies show that this relationship differs for microbes. We demonstrate that the natural bacterial communities inhabiting small aquatic islands (treeholes) do indeed follow the species-area law. The result requires a re-evaluation of the current understanding of how natural microbial communities operate and implies that analogous processes structure both microbial communities and communities of larger organisms.

Research Summary• The relationship between cool-season grasses and fungal endophytes is widely regarded as mutualistic, but there is growing uncertainty about whether changes in resource supply and environment benefit both organisms to a similar extent.• Here, we infected two perennial ryegrass ( Lolium perenne ) cultivars (AberDove, Fennema) that differ in carbohydrate content with three strains of Neotyphodium lolii (AR1, AR37, common strain) that differ intrinsically in alkaloid profile. We grew endophyte-free and infected plants under high and low nitrogen (N) supply and used quantitative PCR (qPCR) to estimate endophyte concentrations in harvested leaf tissues.• Endophyte concentration was reduced by 40% under high N supply, and by 50% in the higher sugar cultivar. These two effects were additive (together resulting in 75% reduction). Alkaloid production was also reduced under both increased N supply and high sugar cultivar, and for three of the four alkaloids quantified, concentrations were linearly related to endophyte concentration.• The results stress the need for wider quantification of fungal endophytes in the grassland-foliar endophyte context, and have implications for how introducing new cultivars, novel endophytes or increasing N inputs affect the role of endophytes in grassland ecosystems.

Experiments that manipulate species richness and measure ecosystem functioning attempt to separate the effects of species richness (the number of species) from those of species identity. We introduce an experimental design that ensures that each species is selected the same number of times at each level of species richness. In combination with a linear model analysis, this approach is able to unambiguously partition the variance due to different species identities and the variance due to nonlinear species richness, a proxy measure for interactions among species. Our design and analysis provide several advantages over methods that are currently used. First, the linear model method has the potential to directly estimate the role of various ecological mechanisms (e.g., competition, facilitation) rather than the consequences of those mechanisms (e.g., the "complementarity effect"). Second, unlike other methods that are currently used, this one is able to estimate the impact of diversity when the contribution of individual species in a mixture is unknown. abstract: Experiments that manipulate species richness and measure ecosystem functioning attempt to separate the effects of species richness (the number of species) from those of species identity. We introduce an experimental design that ensures that each species is selected the same number of times at each level of species richness. In combination with a linear model analysis, this approach is able to unambiguously partition the variance due to different species identities and the variance due to nonlinear species richness, a proxy measure for interactions among species. Our design and analysis provide several advantages over methods that are currently used. First, the linear model method has the potential to directly estimate the role of various ecological mechanisms (e.g., competition, facilitation) rather than the consequences of those mechanisms (e.g., the "complementarity effect"). Second, unlike other methods that are currently used, this one is able to estimate the impact of diversity when the contribution of individual species in a mixture is unknown.