Modelling the impacts of agricultural management practices on river water quality in Eastern England

Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km2. A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of unintended pollutant impacts when evaluating the effectiveness of mitigation options, and showed that high-frequency water quality datasets can be applied to robustly calibrate water quality models, creating DSTs that are more effective and reliable

Identifying the trait syndromes of conservation indicator species:how distinct are British ancient woodland indicator plants from other woodland species?

Question: Ancient woodland indicator species (AWIs) are plant species which are thought to be restricted to areas of long-continuity woodland habitat. In many cases, however, these species have been identified on the basis of personal, to some extent, subjective experience. Do the species proposed as AWIs according to these lists have traits in common, and how distinct is their trait profile from that of otherwoodland plant species? Location: United Kingdom. Methods: We applied classification tree analysis to a plant trait database to assess the extent to which proposed AWI species can be clearly separated from other woodland plants based upon their traits. We contrasted AWI species with an objectively defined list of plants that are not considered to be AWIs but that have been commonly recorded in woodlands. We also investigate the effects of phylogeny and region specificity on species proposed AWI status. Results: The results provide support for the distinctiveness of plant species thought to be associated with ancient woodland; they were found to be almost exclusively short, perennial species, usually with a high seed weight. Results also indicate that rarer AWIs have a more distinguishable trait profile than more common species. No link was found between phylogeny and AWI status. Conclusions: AWI species do have a distinguishable trait profile, despite their often partially subjective selection. The results of the classification tree analysis suggest that traits reflecting poor dispersal ability may be partly responsible for confining these species to ancient woodlands. This confirms other studies that emphasize their low ability to colonize secondary woodland sites and hence vulnerability to habitat conversion

What explains property-level variation in avian diversity? An inter-disciplinary approach

1. Modern farmed landscapes have witnessed substantial losses in biodiversity principally driven by the ecological changes associated with agricultural intensification. The causes of declines are often well described, but current management practices seem unlikely to deliver the EU-wide policy objective of halting biodiversity losses. 2. Available evidence suggests that property-scale factors can be influential in shaping patterns of biodiversity; however, they are rarely included in studies. Using 44 upland farms in the Peak District, northern England, we investigate the roles of ecological, agricultural and socio-economic factors in determining avian species richness, for the first time incorporating information from all three influences. 3. Although we might expect that habitat quality would be the main factor affecting species richness, these variables had little influence. The landscape context of each property was unimportant in explaining any of the three measures of species richness (Total, Upland and Conservation Concern) used here. Within-property habitat quality did explain 42% of the variation in richness of upland specialist species, but had no influence on Total or Conservation Concern Richness. 4. Socio-economic circumstances of farms alone accounted for 24% of the variation in Total Richness, with land tenure and labour inputs important predictors of avian diversity. However, net income, rental value and the level of Agri-Environment Scheme (AES) payments did not play a role in predicting species richness. 5. Farm management variables, including many of the main prescriptions outlined in AES, accounted for 23% of the variation in the richness of species of Conservation Concern, but less than 10% for Total Richness. However, no farm management variable alone was shown to offer better predictive power of avian species richness than random. 6. Synthesis and applications. The agricultural landscape is managed by a mosaic of landowners, all of whom can influence biodiversity conservation. We demonstrate that variation at the property-scale in habitat, management and socio-economics can feed into determining patterns of biodiversity. Currently, farmland conservation policy largely assumes that socio-economic barriers and financial costs of implementing conservation measures are constant. Incorporating a consideration of the varying circumstances of individual properties into policy design is likely to result in substantial biodiversity gains