Decoupling direct and indirect effects of atmospheric warming on decomposition rates of wood-rot fungi

Background/Question/Methods

Microbial communities are critical regulators of the global carbon cycle and the climate system through decomposition of organic matter. Temperature is known to have a strong direct positive effect on decomposition rates, and rising temperatures resulting from anthropogenic climate change are generally expected to increase decomposition rates. However, the possible indirect effects of temperature on decomposition rates as mediated by changes in community structure are not well understood. Using wood-rot fungal communities collected from red oak logs in northeastern Connecticut as a study system, we used a full factorial design to explore whether changes in atmospheric temperature may indirectly influence decomposition rates via changes in community structure. Original fungal communities were collected from the field and colonized sterile red oak discs for 90 days at 15°C, 20°C, or 25°C. The colonized discs (i.e., the secondary fungal communities) then decomposed sterile red oak blocks at either 15°C, 20°C, or 25°C for 90 days. Percent mass loss of the sterile block was calculated to determine decomposition rates. 

Results/Conclusions

Decomposition rates were largely driven by the reigning temperature during the decomposition incubation period.  However, original incubation temperature was also a highly significant predictor of percent mass loss. Our findings therefore demonstrate a significant “legacy effect” of temperature change on the function of decomposer communities: decomposition rates at 20°C were significantly higher for samples that were originally incubated at 25°C than for those that were originally incubated at 15°C. Our results suggest that as atmospheric temperatures rise, decomposition rates of organic matter may increase due to both direct and indirect (community-mediated) effects of warming. This additional positive indirect effect should be considered in organic matter models, especially in the context of anthropogenic climate change. Our quantification of this effect could contribute to making estimates of the microbial feedback to climate change more accurate.