Compensatory water effects link yearly global land CO2 sink changes to temperature.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.

Kinetic characterization of a new phenol degrading Acinetobacter towneri strain isolated from landfill leachate treating bioreactor.

The objective of this study was to establish and to mathematically describe the phenol degrading properties of a new Acinetobacter towneri CFII-87 strain, isolated from a bioreactor treating landfill leachate. For this purpose, the biokinetic parameters of phenol biodegradation at various initial phenol concentrations of the A. towneri CFII-87 strain have been experimentally measured, and four different mathematical inhibition models (Haldane, Yano, Aiba and Edwards models) have been used to simulate the substrate-inhibited phenol degradation process. The results of the batch biodegradation experiments show that the new A. towneri CFII-87 strain grows on and metabolizes phenol up to 1000 mg/L concentration, manifests significant substrate inhibition and lag time only at concentrations above 800 mg/L phenol, and has a maximum growth rate at 300 mg/L initial phenol concentration. The comparison of the model predictions with the experimental phenol and biomass data revealed that the Haldane, Aiba and Edwards models can be used with success to describe the phenol biodegradation process by A. towneri CFII-87, while the Yano model, especially at higher initial phenol concentrations, fails to describe the process. The best performing inhibition model was the Edwards model, presenting correlation coefficients of R2 > 0.98 and modelling efficiency of ME > 0.94 for the prediction of biomass and phenol concentrations on the validation datasets. The calculated biokinetic model parameters place this new strain among the bacteria with the highest tolerance towards phenol. The results suggest that the A. towneri CFII-87 strain can potentially be used in the treatment of phenolic wastewaters.