Richard F. Pywell

Soil organic matter (SOM) level is a key factor determining soil resilience and condition; however, the optimal level of SOM in soils increases with clay content. Previous work has promoted the concept of Clay to Soil Organic Carbon (SOC) ratios to derive critical thresholds of soil degradation. Here, we analyse a dataset comprising 485 soil samples across England & Wales, where Visual Estimation of Soil Structure (VESS) scores was used alongside measurements of Clay and SOC contents (0–25 cm depth) to integrate soil structure into a new data‐driven Rating framework of soil condition and resilience. SOM (calculated as SOC/58%) increased with clay content. Both SOM and VESS scores were significantly better under grassland. For similar soil structure scores, SOM and clay content best fitted to diminishing power relationships (curves). Based on VESS scores, empirical bands are derived to rate the SOM as Maximum under grassland, Very Good, Good, Moderate, Deficient or Very Deficient at any given clay content. Most grassland sites were classified in the top three categories, whereas arable land spanned all six. On arable land, the existing Clay:SOC ratio framework classed 86% of heavy‐textured soils as ‘Degraded’ whereas the new Rating system categorises only 36% as Deficient. Conversely, on lighter land the Rating bands identified more Deficient soils than the Clay:SOC relationship. Across all soil types, Clay:SOC ratio classed 46% as Degraded whereas the Rating bands judged 11% as Deficient plus 12% as Very Deficient. 34% were rated Good or Very Good. VESS score was Good or Very Good in 37% of cases, while 26% were inadequate (VESS > 3.0), of which 14% were 4.0 or worse. Under grass leys, Clay:SOC ratio designated 12% as Degraded whereas the Rating only found 7% as Deficient; 3% had VESS 4 or 5. 59% of leys and 73% of permanent grassland had VESS 1 or 2 and only 2% had VESS 4 or 5. A substantial part of the variation in VESS scores is not captured by the Clay‐v‐SOM relationship which we attribute to management (cultivation and crop rotation). Structure was generally worse on sites with a history of minimal/shallow tillage. Conversely, cultivated soils could have good structure despite Moderate Rating. The new Rating categories are proposed as a robust and practical framework to describe soil structural condition and resilience for farmers and advisers to inform management guidance, including whether continuous reduced cultivation is appropriate or not, and where SOC should be raised, in contrast to soils already high in SOC that are unlikely to benefit from (nor retain) increased Carbon inputs. We estimate that an increase of 13 t/ha C in the topsoil is sufficient to restore a Very Deficient soil to Moderate Resilience. The data and new framework proposed in this study indicate that soil structure assessment needs to be integrated with SOC and clay for a more relevant metric of soil degradation and resilience. The methodology was developed on soils in England and Wales but has the potential to be used on soils worldwide.

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.

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.

Fruits, legumes, oilseeds and nuts have a high dependency on insect pollination, of which the honey bee (Apis mellifera L.) is a critical contributor. However, declines in wild insect pollinators and managed honey bees have been widely reported. An increase in the prevalence of diseases is likely to be directly or indirectly contributing to these declines. In the United Kingdom, the fungal chalkbrood, the microsporidian Nosema, and the bacterial European Foulbrood (EFB), represent three major non-viral diseases of honey bees. Many of these diseases are economically important to honey bees and have the potential to cross over to wild bee species. Rapid large-scale monitoring of these pathogens provides advantages in controlling these diseases through pre-emptive mitigation measures. The UK National Honey Monitoring Scheme provides this kind of monitoring, and this study assesses the efficacy of molecular methods to detect these diseases within honey samples obtained through this citizen science scheme. The study used quantitative polymerase chain reaction (qPCR) from DNA extracted from 150 honey samples, which revealed chalkbrood (13%) and Nosema (11%) as the most abundant pathogens, whereas the legally notifiable EFB was discovered in less than 2% of colonies. Asymptomatic infections, including that of the high-risk EFB, were common. There is evidence to suggest that both asymptomatic and symptomatic disease expression become more prevalent throughout the year. Monitoring for these diseases is recognised as being vital in the control and containment of these pathogens. The application of low-cost, non-invasive methods with a large-scale monitoring scheme, could support mitigation as well as identify currently asymptomatic but highly contagious or notifiable diseases prior to outbreaks.

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 co-occurs through a microbial structural maturation, in which soil restoration is associated with higher-order biotic interactions, or whether antimicrobial resistance (AMR) is instead associated with the competitive pressures and high bacterial 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. The strongest predictor of this rise in AMR abundance was an increasing microbial eukaryotic signature rather than increasing microbial density, suggesting that resistome expansion is not associated with generalized spatial competition, but rather, co-occurs with structural maturation of the microbiome. We observed an order of magnitude increase in antibiotic biosynthetic potential, dominated by the emergence of streptomycin clusters. Microbial reorientation during soil maturation mirrors the expansion of a core resistome comprised of ancient, intrinsic mechanisms, such as Major Facilitator Superfamily (MFS) efflux pumps and RNA Polymerase-Binding Protein A (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 soil degradation.

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 decoupling between floral and edaphic recovery. While the diversity of vegetation recovered relatively rapidly, approaching ancient grassland levels within 23–67 years, soil properties exhibited persistent legacy effects and slow convergence. Bacterial richness decreased with restoration age; this taxonomic contraction was conversely matched by an expansion in inferred metagenomic functional potential. This was reflected in increased functional gene richness and shifts in the relative abundance of specific SEED-annotated functions towards metabolic pathways associated with complex carbon cycling and stress tolerance. These shifts were congruent with the emergence of specific, unnamed genera belonging to Pseudomonadota and Actinomycetota, and the Bacillota species Pristimantibacillus. The soil ecosystem remained distinct from the 143-year stage even after 67 years of recovery, characterized 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.

Unprecedented climate and land use changes are having major impacts on water-based ecosystem services (ES). It is crucial, therefore, to get an in-depth understanding of current levels of such ES provision, and how they could be impacted by changed environments or management. However, applying existing models for water-related ES pose substantial challenges, which include the need for in-depth specialist hydrological knowledge, the requirement for numerous datasets and parameters that may not be consistently available, and high computational costs. Additionally, there is often a mismatch between the resolution of the model output and parcel-level land management, at which ES information is often most valuable for supporting decision-making. Here we detail a rapid method for assessing water retention potential by estimating an area’s ‘sponginess’ - its capacity to absorb and retain precipitation. Our approach builds upon a topography-adjusted Curve Number methodology, a widely recognised and straightforward tool for estimating water run-off. We calculated run-off across 1 km grid cells (representing field- to farm-scale land parcels) in Great Britain based on the land’s sponginess under storm conditions. The primary objective was to investigate the applicability of the method in estimating point-values — i.e., the independent contribution of each grid square — within the context of known limitations. The results enable the identification of areas with higher potential for the ES of water retention. Our model output illustrates the spectrum of sponginess across Great Britain, ranging from less than 30% of precipitation retained in city regions to as high as 99% in some rural, agricultural areas. Importantly, we demonstrate that the model is easy to run, can be used with freely-available data, and produces outputs compatible with grid-based models for other ES. Overall, the model provides an accessible approach to estimating the ES of water retention to researchers worldwide, even in data-scarce areas. Highlights: - To inform land management decisions it is important to determine parcel-level ecosystem services, but there is a gap for services related to water. - Parcel-level assessments of a land’s ‘sponginess’ – the capacity to retain precipitation – are described. - Values are calculated using a topography-adjusted Curve Number methodology, which requires little data input or hydrological expertise. - ‘Sponginess’ and run-off estimates are provided for Great Britain at 1 km resolution.

Archetypes of land- and socio-ecological systems, generated using unsupervised classification methods, enable the assimilation of complex environmental and socio-economic information. Such simplification has considerable potential to feed into decision support systems for sustainability planning. But, the usefulness of archetypes depends on how well they relate to sustainability criteria, such as ecosystem service (ES) delivery, that are external to the input datasets employed for archetype generation. Sensitivities in such post-hoc association analyses, and the associated utility of the archetype framework in a decision support context, remain unexplored. Here we emulated post-hoc association analysis procedures using simulated socio-ecological datasets and ES response variables. Our simulations revealed a substantial influence on analysis performance from (1) the number of variables used as inputs in archetype generation, (2) the correlation structure of input datasets, (3) the type and distribution of input variables, and (4) the functional form (linear or non-linear) characterising the relationship between ES variables and their predictors. We observed near-identical performance when archetypes were generated using K-means clustering and Self-Organising Maps (SOMs) – two commonly used archetype classification methods. Further, better archetype classifier performance did not guarantee better discrimination of ES value distributions between archetypes. Our results suggest that designing a framework to generate archetypes for sustainability planning, and the selected methodological choices therein, should place greater emphasis on what the archetypes will be used for in downstream analyses, and not focus solely on archetype classifier performance. This would better ensure the identification of archetypes adaptable to a diverse array of sustainability indicators and sufficiently robust for monitoring decision outcomes over time.

During primary succession, the abundance of different species and their associated plant traits change over time. Understanding how plant traits linked to colonising and competitive abilities change through succession is important for determining whether community assembly can be predicted. Examining this across more than one taxon group can reveal if these patterns are generalisable. Here, we investigated primary succession on bare chalk for a chronosequence spanning 33 years for two different taxa, vascular plants and bryophytes. We examined how abundance changed through succession, and how this related to species' colonising and competitive abilities, using relevant plant traits for each taxa. A zero‐inflated beta regression model was used to investigate the effects of traits on both presence/absence and abundance‐when‐present of vascular plants and bryophytes. Vascular plants with a larger specific leaf area were more likely to occur later in succession. Vascular plants, which were hemicryptophytes, wind dispersing and had a lower canopy height, were more likely to increase in abundance‐when‐present during succession. Bryophytes with a larger spore diameter were more likely to occur later in succession. Shorter bryophytes with a greater frequency of sporophyte production had a higher abundance early in succession, representing their high colonising abilities. Whereas later in succession larger bryophytes, with a mat or weft life form and low sporophyte frequency were more abundant, indicating a shift towards greater competitive abilities. Synthesis. This study has revealed different patterns for vascular plants and bryophytes regarding colonisation and changes in abundance through succession, and the associated traits linked to colonising and competitive abilities. Although some traits were found to influence abundance through succession for vascular plants, these were often contrary to the expected pattern representing the change from colonising to competitive abilities, whereas for bryophytes, there was more evidence for this shift with successional age. This suggests that general theories on succession‐linked plant traits should not be relied upon in isolation for the prediction of community assembly. Context, particularly successional age in relation to the available species pool is also key.