Biology subjects

Alteio, L. V.

Publications and source records attributed to Alteio, L. V..

3 recordsLinked to original sources

bioRxiv2025

Strengths of relationships among soil microbial and organic matter properties are scale-dependent

Relationships among variables in ecological systems are inherently scale-dependent, especially in heterogeneous systems. Yet it remains to be examined whether relationships among variables vary across observation scales in soil. Generally, it is desirable that observation scale matches the intrinsic scale of a process or pattern. Millimetre-sized soil aggregates are closer to the intrinsic scale of microbial communities than traditionally studied bulk soil samples, making them more suitable for studying potential links between microbial communities and their environment. To explore the effect of observation scale on relationships among soil parameters, we measured bacterial, archaeal, and fungal taxa richness and density, organic matter properties (e.g., carbon and nitrogen content, stoichiometric and isotopic ratios), and soil water content in individual aggregates and aliquots of homogenised soil cores, bulk soil samples, in two soil layers. We analysed pairwise correlations among these variables and assessed whether individual aggregates systematically differed from bulk soil samples. Organic matter properties were more strongly correlated in bulk soil samples, consistent with the idea that increasing the sample volume reduces noise. In contrast, microbial community and organic matter properties showed weaker correlations in bulk soil samples than aggregates in topsoil. In addition, we found that aggregates and bulk soil samples differed systematically in individual microbial and organic matter properties, particularly in the topsoil. Our study demonstrates that relationships among variables in soil are spatial scale-dependent. Aggregates offer valuable insights into microbial communities in soil, complementing bulk soil samples, and are useful for studying links between microbial communities and their environment.

ecology↗

bioRxiv2025

Model substrate particles uncover dynamics of microbial communities associated with particulate organic matter decomposition in soil

Soil organic matter is the largest terrestrial reservoir of organic carbon. Its particulate fraction, particulate organic matter (POM), serves as a resource and surface for microbial colonization. Degradation of complex biopolymers like cellulose and chitin requires extracellular enzymes produced by phylogenetically diverse microbes. Despite their importance for carbon cycling, the structure and spatio-temporal dynamics of POM-associated microbial communities in soil and how specific substrates influence them remain poorly understood. This study investigated whether microbial communities associated with POM change in composition and richness over time and whether chitin and cellulose select for distinct fungal and bacterial taxa. We incubated self-manufactured, millimetre-sized model substrate particles containing chitin or cellulose in soil under laboratory and field conditions. We assessed particle-associated communities at multiple time points over a 50-day-long incubation in the lab and after 47 days in the field. Our results show that community structure and temporal dynamics of particle-associated microbial communities were substrate-specific. While microbial biomass increased on both particle types, chitin-associated microbial communities exhibited stronger temporal changes. Communities on chitin and cellulose particles were enriched in specific bacterial and fungal genera compared to communities in the surrounding soil. We demonstrate that microbial communities associated with model chitin particles underwent notable temporal changes, including decreased microbial richness and shifts in community composition over the incubation period. This study shows the potential of model particles to advance our understanding of particle- and substrate-associated microbial communities in soil.

microbiology↗

bioRxiv2021

From Diversity to Complexity: Microbial Networks in Soils

Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, and definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research.

ecology↗