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Biology subjects

Redhead, J.

Publications and source records attributed to Redhead, J..

2 recordsLinked to original sources

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↗

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↗