pH is the major predictor of soil microbial network complexity in Chinese forests along a latitudinal gradient.

• Fungal-bacterial network complexity is related to soil pH. • Lower network stability and integration is found at neutral pH soil. • Microbial keystone taxa decrease towards higher pH. • pH is the strongest predictor of soil microbial network structure. Patterns in the network structure of microbial communities may give indications of their degree of interaction and interdependence, and their resilience to environmental disturbance. Geographical differences in network patterns of forest communities may reflect broad-scale differences in ecosystem structure and responses to environmental change. We analyzed a large dataset of 144 samples of soil bacterial and fungal communities characterized by 16S and ITS amplicon sequencing from forests in eastern China, along a 4,100 km latitudinal transect. This showed that fungal-bacterial network complexity was most closely related to soil pH. Results showed that pH was the strongest predictor of variation in community network structure across the forest soils of eastern China. Lower network complexity and stability were found around neutral pH, which was the strongest environmental predictor. This may be due to the optimal conditions that neutral soils provide for microorganism survival, reducing the necessity for physiological interdependence, consequently leading to fewer positive connections. Additionally, neutral soils provide more generalized niches, resulting in less specific niche exclusion, showing up as fewer negative connections. Unlike the trend for overall connectivity, the richness and relative abundances of keystone taxa were significantly and negatively correlated with pH. Overall, both connectivity and numbers of keystones were consistent in suggesting that network complexity was greatest overall at acidic pH. It appears that at the broad scale studied here, pH plays a more significant role in shaping microbial community integration than such factors as ecosystem productivity or climate. [ABSTRACT FROM AUTHOR]