Long-term litter type treatments alter soil carbon composition but not microbial carbon utilization in a mixed pine-oak forest
2021
Changes in litter and nutrient inputs into soil could have significant consequences on forest carbon (C) dynamics via controls on the structure and microbial utilization of soil organic C (SOC). In this study, we assessed changes in physical fractions (250–2000 μm, 53–250 μm, and < 53 μm soil aggregates) and chemical fractions (labile, intermediate and recalcitrant pools) of SOC in the top 20 cm mineral soil layer and their influences on microbial substrate utilization after eight years of experiment in a mixed pine-oak forest. The litter treatments included: control (Lcon), litter removal (Lnil), fine woody litter addition (Lwoody), leaf litter addition (Lleaf) and a mix of leaf and fine woody litter (Lmix). Nitrogen (N) addition (application rates of 0, 5 and 10 g N m−2 year−1, respectively) was also applied. We found that complete removal of forest-floor litter (Lnil) significantly reduced the pool sizes of all SOC fractions in both the physical and chemical fractions compared with treatments that retained either leaf litter (Lleaf) or mixture of leaves and fine woody materials (Lmix). The type of litter was more important in affecting SOC fractions than the quantity of inputs; neither the level of N addition rate nor its interaction with litter treatment had significant effects on both physical and chemical SOC fractions. Microbial respiration differed significantly among the treatments of varying litter types. However, the effectiveness of microbial C utilization inferred by microbial C use efficiency and biomass-specific respiration was not affected by either the litter treatments or N addition. These results suggest that despite significant changes in SOC composition due to long-term treatments of forest-floor litter and N addition in this mixed pine-oak forest of temperate climate, microbial C utilization strategies remain unaffected.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
53
References
0
Citations
NaN
KQI