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Methanogenic communities play a crucial role in carbon cycling and biotechnology (anaerobic digestion), but our understanding of how their diversity, or composition in general, determines the rate of methane production is very limited. Studies to date have been correlational because of the difficulty in cultivating their constituent species in pure culture. Here, we investigate the causal link between methanogenesis and diversity in laboratory anaerobic digesters by experimentally manipulating the diversity of cultures by dilution and subsequent equilibration of biomass. This process necessarily leads to the loss of the rarer species from communities. We find a positive relationship between methane production and the number of taxa, with little evidence of functional saturation, suggesting that rare species play an important role in methane‐producing communities. No correlations were found between the initial composition and methane production across natural communities, but a positive relationship between species richness and methane production emerged following ecological selection imposed by the laboratory conditions. Our data suggest methanogenic communities show little functional redundancy, and hence, any loss of diversity—both natural and resulting from changes in propagation conditions during anaerobic digestion—is likely to reduce methane production.

Understanding how the metabolic rates of prokaryotes respond to temperature is fundamental to our understanding of how ecosystem functioning will be altered by climate change, as these micro-organisms are major contributors to global carbon efflux. Ecological metabolic theory suggests that species living at higher temperatures evolve higher growth rates than those in cooler niches due to thermodynamic constraints. Here, using a global prokaryotic dataset, we find that maximal growth rate at thermal optimum increases with temperature for mesophiles (temperature optima ≲ 45°C), but not thermophiles (≳ 45°C). Furthermore, short-term (within-day) thermal responses of prokaryotic metabolic rates are typically more sensitive to warming than those of eukaryotes. Given that climatic warming will mostly impact ecosystems in the mesophilic temperature range, we conclude that as microbial communities adapt to higher temperatures, their metabolic rates and therefore, carbon efflux, will inevitably rise. Using a mathematical model, we illustrate the potential global impacts of these findings.

Raw data for : Bestion E, García-Carreras B, Schaum C-E, Pawar S, Yvon-Durocher G. 2018. Metabolic traits predict the effects of warming on phytoplankton competition. Ecology Letters, doi: 10.1111/ele.12932 Composed of two data sets: - Competition data.csv - Growth rate Raw data.csv Composition of the Growth rate raw data ----------------------------------------- csv file corresponding to the fit of a Buchanan three-phase-linear model to the growth rate data of the 6 species at the 5 temperatures, 13 phosphate concentrations and with 3 replicates, cleaned. with 12 columns - SpeciesName : The Genus of the 6 phytoplankton species used in the experiment - SpeciesNb: a numeric code from 1 to 6 for each species (in alphabetical order) - Temperature_fact: Temperature levels from 15 to 35 coded as a factor (T15, T20, T25, T30, T35) - Temperature_c: Temperature level coded as a numeric variable (15, 20, 25, 30, 35) - Phosphate_fact: Phosphate concentration (umol/L) in the medium, 13 levels coded as a factor (P0.01, P0.1, P01, ... to P50) - Phosphate_c: Phosphate concentration coded as a numeric variable - Replicate: 3 replicates, named 1 to 3 - id_STR: a composite ID column with the species number, the temperature and the replicate to fit the Monod model grouping per ID - LOG10N0: N0 parameter from the Buchanan model - lag: tlag parameter from the Buchanan model - LOG10Nmax: Nmax parameter from the Buchanan model - mu: growth rate, mu parameter from the Buchanan model. To be used to fit the Monod model. Composition of the Competition data --------------------------------------- Results from the competition experiment, as a csv file. with columns: - Day: day of measurement, 3 days (day 5, 14 and 23) - Species_pair: pair of species competing together, from the concatenation of the species numeric code (SpeciesNb in the Growth rate raw data) in the form of 1_2 - SpeciesA: first species in the species pair - SpeciesB: second species in the species pair - Temperature_fact: as above, only two temperatures (T15 and T25) - Phosphate_fact: as above, only 3 phosphate levels (P0.1, P01, P30) - Replicate: 6 replicates, named R1 to R6 - Samples_to_remove_low_density: samples to exclude from the analysis of the competition data as the total cell density was below a predefined threshold of 500 cells/ml - total_cells_SpA_and_B: total number of cells in the sample (in cells/ml) - nb_cells_SpA_lda: number of cells from species A, as calculated with the linear discriminant analysis - nb_cells_SpB_lda: number of cells from species B, as calculated with the linear discriminant analysis - nb_cells_SpA_randomforest: number of cells from species A, as calculated with the randomforest analysis - nb_cells_SpB_randomforest: number of cells from species B, as calculated with the randomforest analysis - nb_cells_SpA_rpart: number of cells from species A, as calculated with the rpart analysis - nb_cells_SpB_rpart: number of cells from species B, as calculated with the rpart analysis - R_obs_lda: observed competition coefficient R, calculated as the ln ratio of the number of cells from the two species; with the lda analysis - R_obs_randomforest: same with randomforest - R_obs_rpart: same with rpart - total_cells_SpA_and_B_average_in_isolate: total number of cells of the two species obtained summing the average total number of cells from each species cultivated in isolation across replicates, {"references":["Bestion E, García-Carreras B, Schaum C-E, Pawar S, Yvon-Durocher G. 2018. Metabolic traits predict the effects of warming on phytoplankton competition. Ecology Letters. doi: 10.1111/ele.12932"]}

Gross primary production (GPP) is the largest flux in the carbon cycle, yet its response to global warming is highly uncertain. The temperature dependence of GPP is directly linked to photosynthetic physiology, but the response of GPP to warming over longer timescales could also be shaped by ecological and evolutionary processes that drive variation in community structure and functional trait distributions. Here, we show that selection on photosynthetic traits within and across taxa dampens the effects of temperature on GPP across a catchment of geothermally heated streams. Autotrophs from cold streams had higher photosynthetic rates and after accounting for differences in biomass among sites, biomass‐specific GPP was independent of temperature in spite of a 20 °C thermal gradient. Our results suggest that temperature compensation of photosynthetic rates constrains the long‐term temperature dependence of GPP, and highlights the importance of considering physiological, ecological and evolutionary mechanisms when predicting how ecosystem‐level processes respond to warming.