Domingo, C. | bioRxiv Science

bioRxiv2026

Decoding microbial diversity in roots of rice plants under flooded conditions: influence of the host genotype, root compartment and mycorrhizal association

BackgroundThe root microbiome plays a critical role in nutrient acquisition, stress tolerance and overall plant health. Rice, a staple food for more than half of the worlds population, is commonly cultivated under flooded conditions. Despite its agronomical importance, our current understanding of root-associated microbiomes in rice grown under flooded conditions is limited. On the other hand, nitrogen (N) and phosphorus (P) fertilizers are routinely applied to maximize rice yield. It is also well known that root colonization by arbuscular mycorrhizal (AM) fungi enhances mineral nutrition in plants, but whether mycorrhizal associations influence the composition of the rice root microbiome remains poorly understood. In this study, shotgun metagenomic sequencing was used to characterize the root endosphere and rhizosphere microbiomes in two temperate japonica rice varieties (cv. Bomba and JSendra) grown under flooded conditions. The impact of colonization by the AM fungus Rhizophagus irregularis on the root microbiome was investigated. ResultsRoot-associated compartments harbour distinct microbial communities in rice with bacterial taxa comprising approximately 95% of the total microbia in rice roots. At the Phylum level, the root bacteriome was primarily composed of Pseudomonadota (Alphaproteobacteria, Betaproteobacteria and Gammaproteobacteria) followed by Actinomycetota. The fungal microbiome was dominated by Ascomycota (Sordariomycetes, Eurotiomycetes and Dothideomycetes) and Basidiomycota. Not only the root compartment, but also the host genotype can shape the root microbiome. Recruitment of specific microorganism mainly occurs at the species level. Genotype-specific and compartment-specific associations of microbial species in mycorrhizal rice roots were also observed supporting that root colonization by an AM fungus contributes to variations in the root microbiome. Further, key microbial species primarily associated to methane production and nutrient cycling (e.g. Phosphate Solubilizing Bacteria and Nitrogen cycling bacteria) colonizing root compartments in each rice genotype and mycorrhizal condition are described. ConclusionsThe rice genotype, root compartment and mycorrhizal condition markedly influence the microbiome in roots of rice plants growing in flooded rice fields. These findings illustrate the potential of the plant to shape its associated root microbiome, thus, offering valuable insights for the development of microbiome-based strategies to improve growth and performance in rice plants under flooded conditions.

microbiology↗

bioRxiv2018

Remotely sensed indicators and open-access biodiversity data to assess bird diversity patterns in Mediterranean rural landscapes.

Changes in ecosystem area are often used to assess human impacts on habitats and estimate biodiversity change. However, because species respond to structural changes at fine spatial scales the use of area alone may not capture all relevant changes. Operational costs limit the assessment of biodiversity change at a simultaneously fine spatial resolution and large scales. The development of cost-effective and expedite methods to monitor biodiversity change is therefore required. We use open access satellite imagery and biodiversity data to investigate the importance of variables of habitat extent and structure in explaining species richness and community dissimilarity of forest and open-land birds at the regional scale. Moreover, because Mediterranean landscapes are subject to seasonal dynamics, we explore the indicator value of remotely sensed variables measured in spring and summer. A large-scale dataset of bird occurrence data, including 8042 observations and 78 species, distributed by 40 landscape-sized cells, was assembled from GBIF after controlling for data quality. We found that summer satellite imagery, when the green perennial vegetation is more apparent, is particularly suited to model the diversity patterns of forest species, because distribution of tree cover in the landscape is well captured. Summer data is also useful to monitor the perennial elements that shape landscape structure and the habitat of open-land species. Specifically, mean NDVI and a second-order NDVI texture variable, were found to be good indicators of forest and open-land habitats, respectively. The use of spring imagery appears to be useful to monitor habitat structure within open-land habitat patches. Overall, NDVI texture measures were found to be good predictors of bird diversity patterns at large scales. Also, we were able to successfully conduct a regional scale analysis using open-access data, which illustrates their potential to inform large scale biodiversity monitoring.

ecology↗