Recurring heavy rainfall resulting in degraded-upgraded phases in soil microbial networks that are reflected in soil functioning

Abstract

Abstract• We assess the recovery of microbial networks underneath crust to repeated rainfall.• The network fragmentation after the second heavy rain was milder than at the first one.• Cohesive networks were related to high enzyme activity involved in C, N, and P cycles.• Loose networks were related to high Ca, K, Mg, NH4 and organic N.• The network in dry-crusted soils collapsed after the second heavy rain.Biological soil crusts (BSCs) are an important multi-trophic component of arid ecosystems in the Mediterranean region. In a mesocosm experiment, the authors investigated how the network of interactions among the members of the soil microbial communities in four types of soil sample responded when soils were exposed to two simulated extreme rain events. The four types of soil samples were: covered by Cladonia rangiformis and previously hydrated (+BSC+H), covered by C. rangiformis and dried (+BSC−H), uncovered and hydrated (−BSC+H), uncovered and dried (−BSC−H). Network analysis was based on the co-occurrence patterns of microbes; microbes were assessed by the phospholipid fatty acids analysis. The authors further explored the relations between networks’ metrics and soil functions denoted by enzymatic activity and soil chemical variables. All networks exhibited Small world properties, moderate values of clustering coefficient and eigen centrality, indicating the lack of hub nodes. The networks in −BSC−H soils appeared coherent during the pre-rain phases and they became modular after rains, while those in +BSC−H soils kept their connectivity till the second rain but this then collapsed. The network metrics that were indicative of cohesive networks tended to be related to enzyme activity while those that characterized the loose networks were related to Ca, K, Mg, NH 4 + and organic N. In all mesocosms except for +BSC−H, networks’ fragmentation after the second heavy rain was milder than after the first one, supporting the idea of community acclimatization. The response of microbial networks to heavy rains was characterized by the tendency to exhibit degradation-reconstruction phases. The network collapse in the crusted only mesocosms showed that the communities beneath crusts in arid areas were extremely vulnerable to recurring heavy rain events.

Fire and Rhizosphere Effects on Bacterial Co-Occurrence Patterns

“…Moreover, modular architecture endowed with small-world properties induces time-scale separation of processes at the metacommunity level, in that processes within modules/local communities proceed quickly, while those between modules/local communities proceed slowly [ 76 ]. In such networks, local repairs due to the free movement of recolonizing microbes make the modular metacommunity resistant and resilient against global disturbance [ 41 ]. In this paper, the robustness of the soil bacterial metacommunities appeared enhanced in burnt plots and was more pronounced in bulk soil (5.3 vs. 1.95 connectivity, respectively; Table 2 ).…”

“…Co-occurrence network analysis has recently gained popularity in analyzing biota relationships [ 41 ]. Since current studies have demonstrated that divergent bacterial communities are developed on the rhizosphere and the surrounding bulk soil [ 42 ], data sets from rhizospheres and bulk soils in burnt and unburnt plots were retrieved separately.…”

“…Since current studies have demonstrated that divergent bacterial communities are developed on the rhizosphere and the surrounding bulk soil [ 42 ], data sets from rhizospheres and bulk soils in burnt and unburnt plots were retrieved separately. Several network metrics are used to reveal mechanisms related to community assembly [ 39 , 41 ]. Modularity is key in exploring the determinism-stochasticity balance.…”

Interventions Change Soil Functions and the Mechanisms Controlling the Structure of Soil Microbial Communities

“…These could be variables used to describe community organization (functional diversity, species richness, composition, and co-occurrence patterns [ 2 ]) and variables that are related to the taxonomic level and spatial scale of the community under consideration [ 3 ]. Most studies have explored the relation between taxa richness and functions, while information concerning the relationship between the co-occurrence patterns of microbes reflecting a community structure and the functionality of an ecosystem is rather limited [ 4 ]. Additionally, current discussion on microbial communities’ assemblage has moved one step forward and incorporates the idea of stochasticity and determinism.…”