Connections between soil microbes, land use and European climate: Insights for management practices.

Soil microbial biomass and activity strongly depend on land use, vegetation cover, climate, and soil physicochemical properties. In most cases, this dependence was assessed by one-to-one correlations while by employing network analysis, information about network robustness and the balance between stochasticity and determinism controlling connectivity, was revealed. In this study, we further elaborated on the hypothesis of Smith et al. (2021) that cropland soils depended more on climate variables and therefore are more vulnerable to climate change. We used the same dataset with that of Smith et al. (2021) that contains seasonal microbial, climate and soil variables collected from 881 soil points representing the main land uses in Europe: forests, grassland, cropland. We examined complete (both direct and indirect relationships) and incomplete networks (only direct relationships) and recorded higher robustness in the former. Partial Least Square results showed that on average more than 45% of microbial attributes' variability was predicted by climate and habitat drivers denoting medium to strong effect of habitat filtering. Network architecture slightly affected by season or land use type; it followed the core/periphery structure with positive and negative interactions and no hub nodes. Microbial attributes (biomass, activity and their ratio) mostly belong to core block together with Soil Organic Carbon (SOC), while climate and soil variables to periphery block with the exception of cropland networks, denoting the higher dependence between microbial and climate variables in these latter. All complete networks appeared robust except for cropland and forest in summer, a finding that disagrees with our initial hypothesis about cropland. Networks' connectivity was controlled stronger by stochasticity in forest than in croplands. The lack of human interventions in forest soils increase habitat homogeneity enhancing the influence of stochastic agents such as microbial unlimited dispersal and/or stochastic extinction. The increased stochasticity implies the necessity for proactive management actions.

A Polyphasic Approach for Assessing Eco-System Connectivity Demonstrates that Perturbation Remodels Network Architecture in Soil Microcosms.

Network analysis was used to show changes in network attributes by analyzing the relations among the main soil microbial groups in a potted tomato soil inoculated with arbuscular mycorrhizal fungus, treated with low doses of Mentha spicata essential oil, or both, and then exposed to tenfold higher oil addition (stress pulse). Pretreatments were chosen since they can induce changes in the composition of the microbial community. Cellular phospholipid fatty acids (PLFAs) and the activity of six soil enzymes, mainly involved in the N-cycle were measured. Networks were constructed based on correlated changes in PLFA abundances. The values of all parameters were significantly different from those of random networks indicating modular architecture. Networks ranked from the lowest to highest modularity: control, non-pretreated and stressed, inoculated and stressed, oil treated and stressed, inoculated and treated with oil and stressed. The high values of network density and 1st/2nd eigenvalue ratio are related to arylamidase activity while N-acetyl-glucosaminidase, acid phosphomoesterase, and asparaginase activities related to high values of the clustering coefficient index. We concluded that modularity may be an efficient indicator of changes in the network of interactions among the members of the soil microbial community and the modular structure of the network may be related to the activity of specific enzymes. Communities that were stressed without a pretreatment were relatively resistant but prone to sudden transition towards instability, while oil or inoculation pretreatments gave networks which could be considered adaptable and susceptible to gradual change.

Emergence of new fields in ecology: the case of life history studies.

We examine the emergence of the field of life-history strategies during the 1950s. (We consider a 'field' an area of scientific activity consisting of a theoretical core, a subject of research, a vocabulary and research tools). During the late 1940s and early 1950s, population ecology faced many problems, concerning its conceptual framework, its mathematical models, experimental deficiencies, etc. Research on life-history characteristics remained descriptive, lacking explanations about the causes and significance of phenomena. This was due to the deficiencies of the theoretical framework of population ecology up to the 1950s. The catalyzing factor for the emergence of the new field was the interdisciplinary impacts, and especially the impact of neodarwinism. The elaboration of a new theoretical core, invoking also methodological shifts, was the triggering factor, conditioning the emergence of the new field.