The abundance of microbial "specific groups" significantly influences downed log respiration

Abstract

Downed logs are an important component of the forest ecosystem, and the CO₂ released through their respiration is significant for global climate change and the carbon cycle. Respiration in downed logs primarily results from microbial metabolic activities. However, the mechanisms by which environmental factors regulate these activities remain unclear. Consequently, current models for carbon release from downed logs exhibit significant deviations. Therefore, this study investigates the same forest plots at 2013 and 2022 to measure the respiration rate (R_log), temperature, moisture, chemical element contents, and microbial community structure of downed logs from Quercus aliena var. acuteserrata and Pinus tabulaeformis at various decomposition stages (DSs). The aim is to elucidate the complex causal relationships and interdependencies among factors related to R_log. Key findings include: 1) R_log increases significantly with decomposition, with Q. aliena var. acuteserrata exhibiting a significantly higher average R_log (4.12 μmolCO₂·m⁻²·s⁻¹) than P. tabulaeformis (3.77 μmolCO₂·m⁻²·s⁻¹); 2) Significant differences in physicochemical properties of downed logs between 2013 and 2022, controlled by tree species and DSs, and the contents of moisture, N, P, Ca and Mg were significantly increased with the increase of DSs, while the content of K was significantly decreased (p < 0.05); 3) In both 2013 and 2022, the dominant microorganisms in downed logs at different DSs included Proteobacteria, Firmicutes, Actinobacteria, Acidobacteria, Bacteroidetes (bacteria) and Basidiomycota, Ascomycota (fungi); 4) The abundance of microorganisms with significant difference between the two years ("specific groups"), including Basidiomycota, Proteobacteria, Cyanobacteria and Chlamydiota, etc, was closely correlated with R_log, although no significant correlation was found between microbial diversity indices and R_log; and 5) moisture emerged as the most influential factor on R_log, followed by Ca, Mg, K, P, N contents, and temperature, particularly in later DSs. These results suggest that future research on R_log mechanisms should focus on microorganisms with significant temporal and spatial abundance differences in downed logs. Furthermore, carbon emission models for downed logs should consider the combined effects of moisture and temperature on R_log, along with the mediating role of wood characteristics (species, DS, and chemical element contents), to improve the accuracy of future R_log predictions.