Spatial variation and controls of soil microbial necromass carbon in a tropical montane rainforest.

Soil microbial necromass carbon is an important component of the soil organic carbon (SOC) pool which helps to improve soil fertility and texture. However, the spatial pattern and variation mechanisms of fungal- and bacterial-derived necromass carbon at local scales in tropical rainforests are uncertain. This study showed that microbial necromass carbon and its proportion in SOC in tropical montane rainforest exhibited large spatial variation and significant autocorrelation, with significant high-high and low-low clustering patterns.

Cross-scale spatial variability and associations of carbon pools provide insight into regulating carbon sequestration in tropical montane rainforests.

The spatial distribution of plant, soil, and microbial carbon pools, along with their intricate interactions, presents a great challenge for the current carbon cycle research. However, it is not clear what are the characteristics of the spatial variability of these carbon pools, particularly their cross-scale relationships. We investigated the cross-scale spatial variability of microbial necromass carbon (MNC), soil organic carbon (SOC) and plant biomass (PB), as well as their correlation in a tropical montane rainforest using multifractal analysis.

[Scaling laws of altitudinal pattern of soil fauna diversity in Dongling Mountain, Beijing, China].

Identifying the complexity of diversity pattern of various taxa within a community is a challenge for ecologist. Scaling law is one of the suitable ways to detecting the complex ecological structure. In this study, we explored the scaling laws of soil fauna diversity pattern along an altitudinal gradient by multifractal analysis, and compared the difference of multifractal spectra between the litter and the soil layers.

Identifying changing interspecific associations along gradients at multiple scales using wavelet correlation networks.

Identifying interspecific associations is very important for understanding the community assembly process. However, most methods provide only an average association and assume that the association strength does not vary along the environmental gradient or with time. The scale effects are generally ignored.