3.2 Biodiversity-functioning relationships across land use
types
The positive correlations between microbial richness and ecosystem
respiration were found across land use types (Fig. 3a). The AOA OTUs
richness was positively correlated with the PNR in the cropland.
Non-significant relationship was observed in the shrubland and woodland
(Fig. 3c). There was not significant relationship between the AOB
richness and PNR across land use types (Fig. 3e). More importantly, the
keystone tax was observed to have a contribution to ecosystem
functioning. The keystone PLFAs amounts were negatively associated with
the mSR (Fig. 3b). Only statistically significant correlation was
observed between the keystone taxon abundance and the PNR in the
cropland, but the relationship showed the opposite trend (Fig. 3d).
Furthermore, the slope of the relationship between microbial richness
and the mSR in the cropland was statistically different with the
woodland (P < 0.001) and shrubland (P< 0.001). By contrast, the scaling slopes of the relationship
between keystone taxon and mSR were close (P = 0.475 across
different land use types).
Meanwhile, for total microbes, the distance-corrected dissimilarities of
keystone species or total community composition with those of ecosystem
functioning and environmental factors were identified (Fig. 4). Overall,
for total microbes, the total PLFAs nor the keystone species composition
was the strongest correlated with the mSR. The total AOA composition and
the keystone AOB species were significant correlated with specialized
ecosystem functioning (i.e. PNR) (Fig. 4b, c).
3.3 Microbial andammoxidation genes
community’s co-occurrence patterns across land use types
In all land use types, the networks exhibited values of Modularity
network, Clustering coefficient and Centralization degree were higher
compared to their respective Erdös–Rényi random networks (Fig. 5; Table
S2), suggesting all microbiome networks had small-world properties and
modular structures. The overall topology indices of PLFAs communities
did not significantly change across land use types possibly due to its
low resolution. Networks had a greater number of negative correlations
between nodes in the woodland of AOA (4.93) and the cropland of AOB
(3.42). Meanwhile, the high network modality and average path length
were found in the woodland of AOA and cropland of AOB, which suggested a
complex and stability of amoA gene community in response to land
use types (Fig. 5; Table S3).
3.4 Keystone
species and environmental factors influencing the ecosystem functioning
The SEM revealed that the PLFAs richness, PLFAs composition and
substrate supplying factors (Bulk density, TC, TN, and C/N) were
significantly directly associated with the mSR, and other environmental
factors (pH, soil temperature and moisture) indirectly affected the mSR
across land use types (Fig. 6a). With regards to specialized function
(i.e. NR and PNR), the keystone AOA composition, and substrate supplying
factors indirectly regulated the PNR, the environmental factors also
dominated the NR (Fig. 6b). Whereas in the AOB community, we found the
AOB keystone composition was closely related with the PNR, and the
substrate supplying factor directly impacted the AOB community richness
nor the AOB community composition, and indirectly impacted the NR (Fig.
6c).