Biology subjects

Pywell, R.

Publications and source records attributed to Pywell, R..

4 recordsLinked to original sources

bioRxiv2026

Antimicrobial resistance as a signature of soil restoration across a 143-year chronosequence

Restoring agriculturally degraded habitats to species-rich grasslands is a vital conservation objective. During restoration, how the soil resistome matures alongside microbial community composition and function remains unclear. Here, we tested two competing hypotheses: whether the soil resistome matures through a microbial warfare model, in which restoration fosters higher-order biotic interactions, or whether antimicrobial resistance (AMR) is instead driven by the competitive pressures of the high taxonomic richness found in disturbed, eutrophic arable land. Using a unique land-use chronosequence on Salisbury Plain, UK, we investigated the trajectory of ecosystem reassembly following the cessation of agricultural activity. Our results demonstrate that AMR abundance increases significantly with restoration age, reaching a maximum in >143-year-old soils. Aligned with this rise in AMR abundance were significant increases in microbial biomass, dominance and cross-kingdom interaction as the ecosystem matured. This suggests that resistome expansion is not associated with generalised bacterial competition, but by a structural maturation of the microbiome. We observed an order of magnitude increase in biosynthetic potential, dominated by the emergence of streptomycin clusters. This maturation was characterised by a loss of bacterial diversity and a systematic shift towards high eukaryote-to-prokaryote ratios. This reorientation mirrors the expansion of a core resistome comprised of ancient, intrinsic mechanisms, such as MFS efflux pumps and RbpA target protection, in older soils. We demonstrate that endogenous AMR is a hallmark of healthy, restored soil ecosystems rather than a marker of anthropogenic degradation, positioning the resistome as bio-indicator of edaphic restoration success within calcareous soils.

microbiology↗

bioRxiv2026

Taxonomic filtering accompanies functional expansion during long-term soil restoration

The restoration of species-rich calcareous grasslands is a critical conservation objective, yet the recovery of the invisible below-ground microbiome remains poorly quantified compared to above-ground vegetation. Using a unique 143-year land-use chronosequence on Salisbury Plain, UK, we investigated the trajectory of ecosystem reassembly across arable, regenerating (23 and 67 years), and ancient grasslands. By integrating vegetation surveys with soil physiochemistry, microbial profiling, and shotgun metagenomics, we identified a profound functional decoupling between floral and edaphic recovery. While vegetation diversity recovered relatively rapidly, approaching saturation within 23-67 years, soil properties exhibited persistent legacy effects and slow convergence. Bacterial richness decreased with restoration age, reflecting a transition from disturbance-adapted copiotrophs in arable soils to a specialised, oligotrophic community in ancient sites. This taxonomic contraction was conversely matched by an expansion in functional potential, driven by the emergence of specific taxa (e.g., Microthrixaceae, Aquihabitans sp.) and metabolic pathways associated with complex carbon cycling and stress tolerance. Crucially, the soil ecosystem did not reach equilibrium even after 67 years, characterised by persistent legacy phosphorus and a slow accumulation of soil organic matter. These findings suggest that passive regeneration alone may be insufficient for full soil functional recovery, and that strategies targeting microbial assembly and long-term carbon dynamics warrant further evaluation.

ecology↗

bioRxiv2024

Soil properties in agricultural systems affect microbial genomic traits

Understanding the relationships between bacterial taxa, their ecological and genomic traits, and their environment, is important for elucidating the mechanisms that drive microbial community dynamics and their roles in ecosystem functioning. This is especially true for soils, where dramatic shifts in resource input or physicochemical properties occur through land use and agricultural practices. Here, we examined the relationships between soil properties and bacterial traits within highly managed agricultural soil systems subjected to arable crop rotations or management as permanent pasture. We assessed the bacterial communities within these soils using amplicon sequencing and assigned each amplicon trait scores for rRNA copy number, genome size, and GC content, which are classically associated with potential growth rates and specialisation. We also calculated the niche breadth trait of each amplicon as a measure of social ubiquity within the examined samples. Within this soil system, we demonstrated that pH was the primary driver of bacterial traits. The weighted mean trait scores of the samples revealed that bacterial communities associated with soils at lower pH (<7) tended to have larger genomes (possess more potential plasticity), have more rRNA (higher growth rate potential), and are more ubiquitous (have less niche specialisation) than the bacterial communities from higher pH soils. Our findings highlight not only the association between pH and bacterial community composition but also the importance of pH in driving community functionality by directly influencing genomic and niche traits.

microbiology↗

bioRxiv2023

A model of sediment retention by vegetation for Great Britain: new methodologies & validation

Soil erosion is an substantial environmental concern worldwide. It has been historically and is of increasingly concern currently. Next to natural processes, over 2 million hectares of soil are at risk of erosion through intensifying agriculture in the Great Britain (England, Wales, Scotland and their territorial islands). Predictive soil erosion models, in the form of Ecosystem Service tools, aid in helping to identify areas that are vulnerable to soil erosion. Yet, no predictions for erosion or sediment retention by vegetation based on local data have been developed for Great Britain or the United Kingdom as a whole. Here we develop an erosion retention model using the InVEST platform, which is based on the RUSLE mathematical framework. We parameterise the model, as far as feasible, with GB specific input data. The developed model estimations are validated against suspended solids concentrations (sediments) in throughout England and Wales. Next to presenting the first GB wide estimate of erosion and erosion retention using the InVEST SDR module, we test three approaches here that differ from more widely applicable RUSLE model inputs, such as created for Europe as a whole. Here, we incorporate (1) periodicity to allow erosion to potentially fluctuate within years; (2) GB-specific cover periodic management factors estimates, including a range of crop types, based on observed satellite NDVI values (3) soil erosivity under heavy rainfall following GB estimates for 2000-2019. We conclude that both the GB created erosivity layer as the added periodicity do not seem to be provide substantial improvement over non-periodic estimated created with more widely available data, when validated against this set of suspended solids in rivers. In contrast, the observed cover management factors calculated from NDVI are a good improvement affecting the ranking order among catchments. Therefore, the generating of cover management factors using NDVI data could be promoted as method for InVEST SDR model development and in more general for developing RUSLE-based erosion estimates worldwide.

bioinformatics↗