Global patterns of plant and microbial biomass in response to CO2 fumigation

Introduction: The stimulation of plant and microbial growth has been widely observed as a result of elevated CO2 concentrations (eCO(2)), however, this stimulation could be influenced by various factors and their relative importance remains unclear. Methods: A global meta-analysis was performed using 884 lines of observations collected from published papers, which analyzed the eCO(2) impact on plant and microbial biomass. Results: A significant positive impact of eCO(2) was observed on various biomass measures, including aboveground biomass (20.5%), belowground biomass (42.6%), soil microbial biomass (10.4%), fungal biomass (11.0%), and bacterial biomass (9.2%). It was found that eCO(2) levels above 200 ppm had a greater impact on plant biomass compared to concentrations at or below 200 ppm. On the other hand, studies showed that positive effects on microbial biomass were more prominent at lower eCO(2) levels (<= 200 ppm) than at higher levels (>200 ppm), which could be explained by soil nitrogen limitations. Importantly, our results indicated that aboveground biomass was controlled more by climatic and experimental conditions, while soil properties strongly impacted the stimulation of belowground and microbial biomass. Discussion: Our results provided evidence of the eCO(2) fertilization effect across various ecosystem types, experimental methods, and climates, and provided a quantitative estimate of plant and soil microbial biomass sensitivity to eCO(2). The results obtained in this study suggest that ecosystem models should consider climatic and edaphic factors to more accurately predict the effects of global climate change and their impact on ecosystem functions.

Automated summary

This study demonstrated that elevated CO2 concentrations have a positive impact on plant and microbial biomass. The effects vary depending on factors such as CO2 levels and soil nitrogen limitations. It also highlighted the importance of considering climatic and soil properties in ecosystem models to predict the effects of global climate change and ecosystem functions more accurately.