Biology subjects

Ruiz-Hernandez, V.

Publications and source records attributed to Ruiz-Hernandez, V..

4 recordsLinked to original sources

bioRxiv2021

Accuracy of mutual predictions of plant and microbe communities varies along a successional gradient in an alpine glacier forefield

O_LIDue to climate warming, recently deglaciated glacier forefields create virtually uninhabited substrates waiting for initial colonization of bacteria, fungi and plants and serve as an ideal ecosystem for studying transformations in community composition and diversity over time and the interactions between taxonomic groups. C_LIO_LIIn this study, we investigated the composition and diversity of bacteria, and fungi, plants and environmental factors (pH, temperature, plot age and soil nutrients) along a 1.5km glacier forefield. We used random forest analysis to detect how well the composition and diversity of taxonomic groups and environmental factors can be mutually predicted. C_LIO_LICommunity composition and diversity of taxonomic groups predicted each other more accurately than environmental factors predicted the taxonomic groups; within the taxonomic groups bacteria and fungi predicted each other best and the taxas composition was better predicted than diversity indices. Additionally, accuracy of prediction among taxonomic groups and environmental factors considerably varied along the successional gradient. C_LIO_LIAlthough our results are no direct indication of interactions between the taxa investigated and the environmental conditions, the accurate predictions among bacteria, fungi, and plants do provide insights into the concerted community assembly of different taxa in response to changing environments along a successional gradient. C_LI

ecology↗

bioRxiv2021

Divergent assembly trajectories: a comparison of the plant and soil microbiome with plant communities in a glacier forefield

Community assembly is a result of dispersal, abiotic and biotic characteristics of the habitat as well as stochasticity. A direct comparison between the assembly of microbial and macrobial organisms is hampered by the sampling of these communities in different studies, at different sites, or on different scales. In a glacier forefield in the Austrian Alps, we recorded the soil and plant microbiome (bacteria and fungi) and plants that occurred in the same landscape and in close proximity in the same plots. We tested five predictions deduced from assembly processes and revealed deviating patterns of assembly in these community types. In short, microbes appeared to be less dispersal limited than plants, soil microbes and plants strongly responded to abiotic factors whereas the leaf microbiome was plant species-specific and well buffered from environmental conditions. The observed differences in community assembly processes may be attributed to the organisms dispersal abilities, the exposure of the habitats to airborne propagules, and habitat characteristics. The finding that assembly is conditional to the characteristics of the organisms, the habitat, and the spatial scale under consideration is thus central for our understanding about the establishment and the maintenance of biodiversity.

ecology↗

bioRxiv2021

Succession comprises a sequence of threshold-induced community assembly processes towards multidiversity

Research on successions and community assembly both address the same processes such as dispersal, species sorting, and biotic interactions but lack unifying concepts. Recent theoretical advances integrated both research lines proposing a sequence of stochastic and niche-based processes along successional gradients. Shifts in assembly processes are predicted to occur abruptly once abiotic and biotic factors dominate over dispersal as main driver. Considering the multidiversity composed of five organismal groups including plants, animals, and microbes, we empirically show that stochastic dispersal-dominated community assembly is replaced by environmental filters and biotic interactions after around 60 years of succession in a glacier forefield. The niche-based character of later successional processes is further supported by a decline in multi-beta-diversity. Our results may update concepts of community assembly by considering multiple taxa, help to bridge the gap between research on successions and community assembly, and provide new insights into the emergence of multidiverse and complex ecosystems.

ecology↗

bioRxiv2020

Automatic classification of constitutive and non-constitutive metabolites with gcProfileMakeR

Data analysis in non-targeted metabolomics is extremely time consuming. Genetic factors and environmental cues affect the composition and quantity of present metabolites i.e. the constitutive and non-constitutive metabolites. We developed gcProfileMakeR, an R package that uses standard output files from GC-MS for automatic data analysis using CAS numbers. gcProfileMakeR produces three outputs: a core or constitutive metabolome, a second list of compounds with high quality matches that is non-constitutive and a third set of compounds with low quality matching to MS libraries. As a proof of concept, we defined the floral scent emission of Antirrhinum majus using wild type plants, the floral identity mutants deficiens and compacta as well as RNAi lines of AmLHY. Loss of petal identity was accompanied by appearance of aldehydes typical of green leaf volatile profiles. Decreased levels of AmLHY caused a major increase in volatile complexity, and activated the synthesis of benzyl acetate, absent in WT. Furthermore, some volatiles emitted in a gated fashion in WT such as methyl 3,5-dimethoxybezoate or linalool became constitutive. Using sixteen volatiles of the constitutive profile, all genotypes were classified by Machine Learning with 0% error. gcProfileMakeR may thus help define core and pan-metabolomes. It enhances the quality of data reported in metabolomic profiles as text outputs rely on CAS numbers. This is especially important for FAIR data implementation. One sentence summarygcProfileMakeR allows the automatic annotation of the core metabolome and non-constitutive metabolites, increasing speed and accuracy of non-targeted metabolomics.

bioinformatics↗