13C dicarboxylic acid signatures indicate temporal shifts in catchment sediment sources in response to extreme winter rainfall.

Rainfall and land-use interactions drive temporal shifts in suspended sediment sources, yet the magnitude of such changes remains poorly understood due to the lack of land-use specific source tracers. We investigated α,ω-dicarboxylic fatty acid root-specific biomarkers, as diagnostic tracers for apportioning sources of time-integrated suspended sediment samples collected from a grassland dominated agricultural catchment in the southwest of England during the wet winter period. Applying fatty acids-specific stable carbon isotope analysis and a Bayesian isotope mixing model, we show that stream banks contributed most of the sediment in the early winter, i.e. October-December, while winter cereal-dominated arable land contributed more than half of the sediment during the late winter, i.e. January-March. The dominant sediment source shifted in conjunction with a period of prolonged consecutive rainfall days in the later period suggesting that intervention required to mitigate soil erosion and sediment delivery should adapt to changing rainfall patterns. Our novel findings demonstrate that isotopic signatures of α,ω-dicarboxylic fatty acids are promising tracers for understanding the resistance of agricultural soils to water erosion and quantifying the interactive effects of extreme rainfall and land use on catchment sediment source dynamics. Supplementary Information: The online version contains supplementary material available at 10.1007/s10311-023-01684-1.

Comparison of sediment biomarker signatures generated using time-integrated and discrete suspended sediment samples.

Sediment source fingerprinting using biomarker properties has led to new insights in our understanding of land use contributions to time-integrated suspended sediment samples at catchment scale. A time-integrated mass-flux sampler (TIMS; also known as the 'Phillips' sampler), a cost-effective approach for suspended sediment collection in situ. Such samplers are widely being used to collect sediment samples for source fingerprinting purposes, including studies using biomarkers as opposed to more conventional tracer properties. Here, we assessed the performance of TIMS for collecting representative sediment samples for biomarkers during high discharge events in a small lowland grassland-dominated catchment. Concentrations of long odd-chain n-alkanes (> C23) and both saturated free and bound fatty acids (C14-C32), as well as compound-specific 13C were compared between sediment collected by both TIMS and autosamplers (ISCO). The results showed that concentrations of alkanes, free fatty acids, and bound fatty acids are consistently comparable between TIMS and ISCO suspended sediment samples. Similarly, compound-specific 13C signals were not found to be significantly different in the suspended sediment samples collected using the different samplers. However, different magnitudes of resemblance in biomarker concentrations and compositions between the samples collected using the two sediment collection methods were confirmed by overlapping index and symmetric coordinates-based correlation analysis. Here, the difference is attributed to the contrasting temporal basis of TIMS (time-integrated) vs. ISCO (discrete) samples, as well as potential differences in the particle sizes collected by these different sediment sampling methods. Nevertheless, our findings suggest that TIMS can be used to generate representative biomarker data for suspended sediment samples collected during high discharge events.

Feasibility of mitigation measures for agricultural greenhouse gas emissions in the UK. A systematic review.

The UK Government has set an ambitious target of achieving a national "net-zero" greenhouse gas economy by 2050. Agriculture is arguably placed at the heart of achieving net zero, as it plays a unique role as both a producer of GHG emissions and a sector that has the capacity via land use to capture carbon (C) when managed appropriately, thus reducing the concentration of carbon dioxide (CO2) in the atmosphere. Agriculture's importance, particularly in a UK-specific perspective, which is also applicable to many other temperate climate nations globally, is that the majority of land use nationwide is allocated to farming. Here, we present a systematic review based on peer-reviewed literature and relevant "grey" reports to address the question "how can the agricultural sector in the UK reduce, or offset, its direct agricultural emissions at the farm level?" We considered the implications of mitigation measures in terms of food security and import reliance, energy, environmental degradation, and value for money. We identified 52 relevant studies covering major foods produced and consumed in the UK. Our findings indicate that many mitigation measures can indeed contribute to net zero through GHG emissions reduction, offsetting, and bioenergy production, pending their uptake by farmers. While the environmental impacts of mitigation measures were covered well within the reviewed literature, corresponding implications regarding energy, food security, and farmer attitudes towards adoption received scant attention. We also provide an open-access, informative, and comprehensive dataset for agri-environment stakeholders and policymakers to identify the most promising mitigation measures. This research is of critical value to researchers, land managers, and policymakers as an interim guideline resource while more quantitative evidence becomes available through the ongoing lab-, field-, and farm-scale trials which will improve the reliability of agricultural sustainability modelling in the future. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-023-00938-0.

Freshwater invertebrate responses to fine sediment stress: A multi-continent perspective.

Excessive fine sediment (particles <2 mm) deposition in freshwater systems is a pervasive stressor worldwide. However, understanding of ecological response to excess fine sediment in river systems at the global scale is limited. Here, we aim to address whether there is a consistent response to increasing levels of deposited fine sediment by freshwater invertebrates across multiple geographic regions (Australia, Brazil, New Zealand and the UK). Results indicate ecological responses are not globally consistent and are instead dependent on both the region and the facet of invertebrate diversity considered, that is, taxonomic or functional trait structure. Invertebrate communities of Australia were most sensitive to deposited fine sediment, with the greatest rate of change in communities occurring when fine sediment cover was low (below 25% of the reach). Communities in the UK displayed a greater tolerance with most compositional change occurring between 30% and 60% cover. In both New Zealand and Brazil, which included the most heavily sedimented sampled streams, the communities were more tolerant or demonstrated ambiguous responses, likely due to historic environmental filtering of invertebrate communities. We conclude that ecological responses to fine sediment are not generalisable globally and are dependent on landscape filters with regional context and historic land management playing important roles.

Bioenergy crop production and carbon sequestration potential under changing climate and land use: A case study in the upper River Taw catchment in southwest England.

Reductions in CO2 emissions are essential to support the UK in achieving its net zero policy objective by around mid-century. Both changing climate and land use change (LUC) offer an opportunity to deploy suitable bioenergy crops strategically to enhance energy production and C sequestration to help deliver net zero through capturing atmospheric CO2. Against this background, we applied process-based models to evaluate the extent of net primary productivity (NPP) losses/gains associated with perennial bioenergy crops and to assess their C sequestration potential under changing climate in the upper River Taw observatory catchment in southwest England. In so doing, we also determined whether LUC from permanent grassland to perennial bioenergy crops, considered in this study, can increase the production and C sequestration potential in the study area. The results show that a warming climate positively impacts the production of all crops considered (permanent grassland, Miscanthus and two cultivars of short rotation coppice (SRC) willow). Overall, Miscanthus provides higher aboveground biomass for energy compared to willow and grassland whereas the broadleaf willow cultivar 'Endurance' is best suited, among all crops considered, for C sequestration in this environment, and more so in the changing climate. In warmer lowlands, LUC from permanent grassland to Miscanthus and in cooler uplands from permanent grassland to 'Endurance', enhances NPP. Colder areas are predicted to benefit more from changing climate in terms of above and belowground biomass for both Miscanthus and willow. The study shows that the above LUC can help augment non-fossil energy production and increase C sequestration potential if C losses from land conversion do not exceed the benefits from LUC. In the wake of a changing climate, aboveground biomass for bioenergy and belowground biomass to enhance carbon sequestration can be managed by the careful selection of bioenergy crops and targeted deployment within certain climatic zones.

Are single global warming potential impact assessments adequate for carbon footprints of agri-food systems?

The vast majority of agri-food climate-based sustainability analyses use global warming potential (GWP100) as an impact assessment, usually in isolation; however, in recent years, discussions have criticised the 'across-the-board' application of GWP100 in Life Cycle Assessments (LCAs), particularly of food systems which generate large amounts of methane (CH4) and considered whether reporting additional and/or alternative metrics may be more applicable to certain circumstances or research questions (e.g. Global Temperature Change Potential (GTP)). This paper reports a largescale sensitivity analysis using a pasture-based beef production system (a high producer of CH4 emissions) as an exemplar to compare various climatatic impact assessments: CO2-equivalents using GWP100 and GTP100, and 'CO2-warming-equivalents' using 'GWP Star', or GWP*. The inventory for this system was compiled using data from the UK Research and Innovation National Capability, the North Wyke Farm Platform, in Devon, SW England. LCAs can have an important bearing on: (i) policymakers' decisions; (ii) farmer management decisions; (iii) consumers' purchasing habits; and (iv) wider perceptions of whether certain activities can be considered 'sustainable' or not; it is, therefore, the responsibility of LCA practitioners and scientists to ensure that subjective decisions are tested as robustly as possible through appropriate sensitivity and uncertainty analyses. We demonstrate herein that the choice of climate impact assessment has dramatic effects on interpretation, with GWP100 and GTP100 producing substantially different results due to their different treatments of CH4 in the context of carbon dioxide (CO2) equivalents. Given its dynamic nature and previously proven strong correspondence with climate models, out of the three assessments covered, GWP* provides the most complete coverage of the temporal evolution of temperature change for different greenhouse gas emissions. We extend previous discussions on the limitations of static emission metrics and encourage LCA practitioners to consider due care and attention where additional information or dynamic approaches may prove superior, scientifically speaking, particularly in cases of decision support.

The spatio-temporal dynamics of suspended sediment sources based on a novel indexing approach combining Bayesian geochemical fingerprinting with physically-based modelling.

Applications of sediment source fingerprinting continue to increase globally as the need for information to support improved management of the sediment problem persists. In our novel research, a Bayesian fingerprinting approach using MixSIAR was used with geochemical signatures, both without and with informative priors based on particle size and slope. The source estimates were compared with a newly proposed Source Sensitivity Index (SSI) and outputs from the INVEST-SDR model. MixSIAR results with informative priors indicated that agricultural and barren lands are the principal sediment sources (contributing ∼5-85% and ∼5-80% respectively during two sampling periods i.e. 2018-2019 and 2021-2022) with forests being less important. The SSI spatial maps (using % clay and slope as informative priors) showed >78% agreement with the spatial map derived using the INVEST-SDR model in terms of sub-catchment prioritization for spatial sediment source contributions. This study demonstrates the benefits of combining geochemical sediment source fingerprinting with SSI indices in larger catchments where the spatial prioritization of soil and water conservation is both challenging but warranted.

Use of a submersible spectrophotometer probe to fingerprint spatial suspended sediment sources at catchment scale.

Sediment fingerprinting is used to identify catchment sediment sources. Traditionally, it has been based on the collection and analysis of potential soil sources and target sediment. Differences between soil source properties (i.e., fingerprints) are then used to discriminate between sources, allowing the quantification of the relative source contributions to the target sediment. The traditional approach generally requires substantial resources for sampling and fingerprint analysis, when using conventional laboratory procedures. In pursuit of reducing the resources required, several new fingerprints have been tested and applied. However, despite the lower resource demands for analysis, most recently proposed fingerprints still require resource intensive sampling and laboratory analysis. Against this background, this study describes the use of UV-VIS absorbance spectra for sediment fingerprinting, which can be directly measured by submersible spectrophotometers on water samples in a rapid and non-destructive manner. To test the use of absorbance to estimate spatial source contributions to the target suspended sediment (SS), water samples were collected from a series of confluences during three sampling campaigns in which a confluence-based approach to source fingerprinting was undertaken. Water samples were measured in the laboratory and, after compensation for absorbance influenced by dissolved components and SS concentration, absorbance readings were used in combination with the MixSIAR Bayesian mixing model to quantify spatial source contributions. The contributions were compared with the sediment budget, to evaluate the potential use of absorbance for sediment fingerprinting at catchment scale. Overall deviations between the spatial source contributions using source fingerprinting and sediment budgeting were 18 % for all confluences (n = 11), for all events (n = 3). However, some confluences showed much higher deviations (up to 52 %), indicating the need for careful evaluation of the results using the spectrophotometer probe. Overall, this study shows the potential of using absorbance, directly obtained from grab water samples, for sediment fingerprinting in natural environments.

What do macroinvertebrate indices measure? Stressor-specific stream macroinvertebrate indices can be confounded by other stressors.

Monitoring programmes worldwide use biota to assess the "health" of water bodies. Indices based on biota are used to describe the change in status of sites over time, to identify progress against management targets and to diagnose the causes of biological degradation. A variety of numerical stressor-specific biotic indices have been developed based on the response of biota to differences in stressors among sites. Yet, it is not clear how variation in pressures within sites, over what time period, and in what combination has the greatest impact on different biotic groups. An understanding of how temporal variation in pressures influences biological assessment indices would assist in setting achievable targets and help focus catchment-scale mitigation strategies to ensure that they deliver the desired improvements in biological condition.Hydrochemical data provided by a network of high-frequency (15 or 30 min) automated monitoring stations over 3 years were matched to replicated biological data to understand the influence of spatio-temporal variation in pollution pressures on biological indices. Hydrochemical data were summarised in various ways to reflect central tendency, peaks, troughs and variation over 1-90 days before the collection of each biological sample. An objective model selection procedure was used to determine which hydrochemical determinand, and over what time period, best explained variation in the biological indices.Stressor-specific indices derived from macroinvertebrates which purportedly assess stress from low flows, excess fine sediment, nutrient enrichment, pesticides and organic pollution were significantly inter-correlated and reflected periods of low oxygen concentration, even though only one index (ASPTWHPT, average score per taxon) was designed for this purpose. Changes in community composition resulting from one stressor frequently lead to confounding effects on stressor-specific indices.Variation in ASPTWHPT was best described by dissolved oxygen calculated as Q5 over 10 days, suggesting that low oxygen events had most influence over this period. Longer-term effects were apparent, but were masked by recovery. Macroinvertebrate abundance was best described by Q95 of stream velocity over 60 days, suggesting a slower recovery in numbers than in the community trait reflected by ASPTWHPT.Although use of ASPTWHPT was supported, we recommend that additional independent evidence should be used to corroborate any conclusions regarding the causes of degradation drawn from the other stressor-specific indices. The use of such stressor-specific indices alone risks the mistargeting of management strategies if the putative stressor-index approach is taken to be more reliable than the results herein suggest.

Data, and sample sources thereof, on water quality life cycle impact assessments pertaining to catchment scale acidification and eutrophication potentials and the benefits of on-farm mitigation strategies.

Based on recent spatially aggregated June Agriculture Survey data and site-specific environmental data, information from common farm types in the East of England was sourced and collated. These data were subsequently used as key inputs to a mechanistic environmental modelling tool, the Catchment Systems Model, which predicts environmental damage arising from various farm types and their management strategies. The Catchment Systems Model, which utilises real-world agricultural productivity data (samples and appropriate consent provided within the Mendeley Data repository) is designed to assess not only losses to nature such as nitrate, phosphate, sediment and ammonia, but also to predict how on-farm intervention strategies may affect environmental performance. The data reported within this article provides readers with a detailed inventory of inputs such as fertiliser, outputs including nutrient losses, and impacts to nature for 1782 different scenarios which cover both arable and livestock farming systems. These 1782 scenarios include baseline (i.e., no interventions), business-as-usual (i.e., interventions already implemented in the study area) and optimised (i.e., best-case scenarios) data. Further, using the life cycle assessment (LCA) methodology, the dataset reports acidification and eutrophication potentials for each scenario under two (eutrophication) and three (acidification) impact assessments to offer an insight into the importance of impact assessment choice. Finally, the dataset also provides its readers with percentage changes from baseline to best-case scenario for each farm type.

Separating natural from human enhanced methane emissions in headwater streams.

Headwater streams are natural sources of methane but are suffering severe anthropogenic disturbance, particularly land use change and climate warming. The widespread intensification of agriculture since the 1940s has increased the export of fine sediments from land to streams, but systematic assessment of their effects on stream methane is lacking. Here we show that excess fine sediment delivery is widespread in UK streams (n = 236) and, set against a pre-1940s baseline, has markedly increased streambed organic matter (23 to 100 g m-2), amplified streambed methane production and ultimately tripled methane emissions (0.2 to 0.7 mmol CH4 m-2 d-1, n = 29). While streambed methane production responds strongly to organic matter, we estimate the effect of the approximate 0.7 °C of warming since the 1940s to be comparatively modest. By separating natural from human enhanced methane emissions we highlight how catchment management targeting the delivery of excess fine sediment could mitigate stream methane emissions by some 70%.

Assessing catchment scale water quality of agri-food systems and the scope for reducing unintended consequences using spatial life cycle assessment (LCA).

Life cycle assessment is a multidisciplinary framework usually deployed to appraise the sustainability of various product or service supply-chains. Over recent decades, its use in the agri-food sector has risen sharply, and alongside this, a wide range of methodological advances have been generated. Spatial-life cycle assessment, defined in the current document as the interpretation of life cycle assessment results within a geographical nature, has not gone unexplored entirely, yet its rise as a sub-method of life cycle assessment has been rather slow relative to other avenues of research (e.g., including the nutritional sciences within life cycle assessment). With this relative methodological stagnation as a motivating factor, our paper combines a process-based model, the Catchment Systems Model, with various life cycle impact assessments (ReCiPe, Centre for Environmental Studies and Environmental Product Declaration) to propose a simple, yet effective, approach for visualising the technically feasible efficacy of various on-farm intervention strategies. As water quality was the primary focus of this study, interventions reducing acidification and eutrophication potentials of both arable and livestock farm types in the Southeast of England were considered. The study site is an area with a marked range of agricultural practices in terms of intensity. All impacts to acidification potential and eutrophication potential are reported using a functional unit of 1 ha. Percentage changes relative to baseline farm types, i.e., those without any interventions, arising from various mitigation strategies, are mapped using geographical information systems. This approach demonstrates visually how a spatially-orientated life cycle assessment could provide regional-specific information for farmers and policymakers to guide the restoration of certain waterbodies. A combination of multiple mitigation strategies was found to generate the greatest reductions in pollutant losses to water, but in terms of individual interventions, optimising farm-based machinery (acidification potential) and fertiliser application strategies (eutrophication potential) were found to have notable benefits.

Prolonged heavy rainfall and land use drive catchment sediment source dynamics: Appraisal using multiple biotracers.

Excessive sediment loss degrades freshwater quality and is prone to further elevation and variable source contributions due to the combined effect of extreme rainfall and differing land uses. To quantify erosion and sediment source responses across scales, this study integrated work at both field and catchment scale for two hydrologically contrasting winters (2018-19 and 2019-20). Sediment load was estimated at the field scale (grassland-arable conversion system). Sediment source apportionment work was undertaken at the catchment scale (4.5 km2) and used alkanes, and both free and bound fatty acid carbon isotope signatures as diagnostic fingerprints to distinguish sediment sources: arable, pasture, woodland and stream banks. Sediment source apportionment based on bound fatty acids revealed a substantial shift in contributions, from stream banks dominating (70 ± 5%) in winter 2018-19, to arable land dominating (52 ± 7%) in the extreme wet winter 2019-20. Increases in sediment contributions from arable (∼3.9 times) and pasture (∼2.4 times) land at the catchment outlet during the winter 2019-20 were consistent with elevated sediment losses monitored at the field scale which indicated that low-magnitude high frequency rainfall alone increased sediment loss even from pasture by 350%. In contrast, carbon isotope signatures of alkanes and free fatty acids consistently estimated stream banks as a dominant source (i.e., ∼36% and ∼70% respectively) for both winters regardless of prolonged rainfall in winter 2019-20. Beyond quantifying the shifts in field scale sediment load and catchment scale sediment sources due to the changes in rainfall patterns, our results demonstrate valuable insight into how the fate of biotracers in soil and sediment manifests in the δ13C values of homologues and, in turn, their role in information gain for estimating sediment source contributions. Discrepancies in the estimated sediment source contributions using different biotracers indicate that without a careful appreciation of their biogeochemical limitations, erroneous interpretation of sediment source contributions can undermine management strategies for delivering more sustainable and resilient agriculture.

Coupled steroid and phosphorus leaching from cattle slurry at lysimeter scale.

Water quality degradation can be caused by excessive agricultural nutrient transfers from fertilised soils exposed to wet weather. Mitigation measures within the EU Nitrates Directive aim to reduce this pressure by including 'closed' fertiliser spreading periods during wet months. For organic fertilisers such as slurry and manure, this closed period requires sufficient on-farm winter storage and good weather conditions to relieve storage at the end of the period. Therefore, robust scientific evidence is needed to support the measure. Incidental nutrient transfers of recently applied organic fertilisers in wet weather can also be complicated by synchronous transfers from residual soil stores and tracing is required for risk assessments. The combination of nutrient monitoring and biomarker analyses may aid this and one such biomarker suite is faecal steroids. Accordingly, this study investigated the persistence of steroids and their association with phosphorus during leaching episodes. The focus was on the coupled behaviour of steroids and total phosphorus (TP) concentrations in sub-surface hydrological pathways. Cattle slurry was applied to monolith lysimeters either side of a closed period and concentrations of both steroids and TP were monitored in the leachate. The study showed no significant effect of the treatment (average p = 0.17), though tracer concentrations did significantly change over time (average p = 0.001). While the steroidal concentration ratio was validated for herbivorous faecal pollution in the leachate, there was a weak positive correlation between the steroids and TP. Further investigation at more natural scales (hillslope/catchment) is required to confirm tracer behaviours/correlations and to compliment this sub-surface pathway study.

Tackling unintended consequences of grazing livestock farming: Multi-scale assessment of co-benefits and trade-offs for water pollution mitigation scenarios.

A farm-to-landscape scale modelling framework combining regulating services and life cycle assessment mid-point impacts for air and water was used to explore the co-benefits and trade-offs of alternative management futures for grazing livestock farms. Two intervention scenarios were compared: one using on-farm interventions typically recommended following visual farm audits (visually-based) and the other using mechanistical understanding of nutrient and sediment losses to water (mechanistically-based). At farm scale, reductions in business-as-usual emissions to water of total phosphorus (TP) and sediment, using both the visually-based and mechanistically-based scenarios, were <5%. These limited impacts highlighted the important role of land drains and the lack of relevant on-farm measures in current recommended advisory lists for the soil types in question. The predicted impacts of both scenarios on free draining soils were significantly higher; TP reductions of ∼9% (visually-based) and ∼20% (mechanistically-based) compared with corresponding respective estimates of >20% and >35% for sediment. Key co-benefits at farm scale included reductions in nitrous oxide emissions and improvements in physical soil quality, whereas an increase in ammonia emissions was the principal trade-off. At landscape scale, simulated reductions in business-as-usual losses were <3% for both pollutants for both scenarios. The visually-based and mechanistically-based scenarios narrowed the gaps between current and modern background sediment loads by 6% and 11%, respectively. The latter scenario also improved the reduction of GWP100 relative to business-as-usual by 4%, in comparison to 1% for the former. However, with the predicted increase of ammonia emissions, both eutrophication potential and acidification potential increased (e.g., by 7% and 14% for the mechanistically-based scenario). The discrepancy of on-farm intervention efficacy across spatial scales generated by non-agricultural water pollutant sources is a key challenge for addressing water quality problems at landscape scale.

Exploring the effects of land management change on productivity, carbon and nutrient balance: Application of an Ensemble Modelling Approach to the upper River Taw observatory, UK.

Agriculture is challenged to produce healthy food and to contribute to cleaner energy whilst mitigating climate change and protecting ecosystems. To achieve this, policy-driven scenarios need to be evaluated with available data and models to explore trade-offs with robust accounting for the uncertainty in predictions. We developed a novel model ensemble using four complementary state-of-the-art agroecosystems models to explore the impacts of land management change. The ensemble was used to simulate key agricultural and environmental outputs under various scenarios for the upper River Taw observatory, UK. Scenarios assumed (i) reducing livestock production whilst simultaneously increasing the area of arable where it is feasible to cultivate (PG2A), (ii) reducing livestock production whilst simultaneously increasing bioenergy production in areas of the catchment that are amenable to growing bioenergy crops (PG2BE) and (iii) increasing both arable and bioenergy production (PG2A + BE). Our ensemble approach combined model uncertainty using the tower property of expectation and the law of total variance. Results show considerable uncertainty for predicted nutrient losses with different models partitioning the uncertainty into different pathways. Bioenergy crops were predicted to produce greatest yields from Miscanthus in lowland and from SRC-willow (cv. Endurance) in uplands. Each choice of management is associated with trade-offs; e.g. PG2A results in a significant increase of edible calories (6736 Mcal ha-1) but reduced soil C (-4.32 t C ha-1). Model ensembles in the agroecosystem context are difficult to implement due to challenges of model availability and input and output alignment. Despite these challenges, we show that ensemble modelling is a powerful approach for applications such as ours, offering benefits such as capturing structural as well as data uncertainty and allowing greater combinations of variables to be explored. Furthermore, the ensemble provides a robust means for combining uncertainty at different scales and enables us to identify weaknesses in system understanding.

Impacts of different vegetation in riparian buffer strips on runoff and sediment loss.

Buffer strips continue to feature in the management of agricultural runoff and water pollution in many countries. Existing research has explored their efficacy for reducing environmental problems in different geoclimatic settings but, the evidence on the efficacy of different vegetation treatments is less abundant than that for other buffer strip characteristics, including width, and is more contradictory in nature. With policy targets for various environmental outcomes including water or air quality and net zero pointing to the need for conversion of agricultural land, the need for robust experimental evidence on the relative benefits of different vegetation types in buffer strips is now renewed. Our experiment used a replicated plot scale facility to compare the efficacy of 12 m wide buffer strips for controlling runoff and suspended sediment loss during 15 sampled storms spanning 2017-2020. The buffer strips comprised three vegetation treatments: a deep rooting grass (Festulolium cv. Prior), a short rotation coppice willow and native broadleaved woodland trees. Over the duration of the monitoring period, reductions in total runoff, compared with the experimental control, were in the order: willow buffer strips (49%); deciduous woodland buffer strips (46%); grass buffer strips (33%). The corresponding reductions in suspended sediment loss, relative to the experimental control, were ordered: willow buffer strips (44%) > deciduous woodland buffer strips (30%) > grass buffer strips (29%). Given the 3-year duration of our new dataset, our results should be seen as providing evidence on the impacts during the establishment phase of the treatments.

A reconnaissance survey of channel bank particulate phosphorus concentrations, controls and estimated contributions to riverine loads across England.

Channel banks can contribute a significant proportion of fine-grained (<63 µm) sediment to rivers, thereby also contributing to riverine total particulate phosphorus loads. Improving water quality through better agricultural practices alone can be difficult since the contributions from non-agricultural sources, including channel banks, can generate a 'spatial mismatch' between the efficacy of best management applied on farms and the likelihood of meeting environmental objectives. Our study undertook a reconnaissance survey (n = 76 sites each with 3 profiles sampled) to determine the total phosphorus (TP) concentrations of channel banks across England and to determine if TP content can be predicted using readily accessible secondary data. TP concentrations in adjacent field topsoils, local soil soil type/texture and geological parent material were examined as potential predictors of bank TP. Carbon and nitrogen content were also analysed to explore the impacts of organic matter content on measured TP concentrations. The results suggest that channel bank TP concentrations are primarily controlled by parent material rather than P additions to adjacent topsoils through fertilizer and organic matter inputs, but significant local variability in concentrations prevents the prediction of bank TP content using mapped soil type or geology. A median TP concentration of 873 mg kg-1 was calculated for the middle section of the sampled channel bank profiles, with a 25th percentile of 675 mg kg-1, and 75th percentile of 1159 mg kg-1. Using these concentrations and, in comparison with previously published estimates, the estimated number of inland WFD waterbodies in England for which channel bank erosion contributes >20% of the riverine total PP load increased from 15 to 25 (corresponding range of 17-35 using the 25th and 75th percentiles of measured TP concentrations). Collectively, these 25 waterbodies account for 0.2% of the total inland WFD waterbody area comprising England.

Distribution of rare earth elements in soils of contrasting geological and pedological settings to support human health assessment and environmental policies.

Establishing quality reference values (QRVs) for rare earth elements (REEs) in soils is essential for the screening of these emergent contaminants. Currently, Brazil has the second-largest reserve of REEs, but data regarding background concentrations and distributions in soils remain scarce. The aim of this study was to establish the QRVs and assess the spatial distribution of REEs in soils, including REE fractionations and anomalies in (Piauí) state (251,529.186 km2), northeastern Brazil. This study reports the most detailed data on REE geochemistry in Brazilian soils. A total of 243 composite soil samples was collected at 0-20 cm depth. The mean background concentrations in soils followed the abundance of the earth's upper crust: Ce > La > Nd > Pr > Sm > Dy > Gd > Er > Yb > Eu > Tb > Lu. The ∑REEs (mg kg-1) showed the following order based on the individual mesoregions of Piauí state: Southeast (262.75) > North and Central-North (89.68) > Southwest (40.33). The highest QRVs were observed in the Southeast mesoregion. The establishment of QRVs based on the mesoregion scale improves data representativeness and the monitoring of natural REE values by identifying hot spots. Geostatistical modeling indicated significant local variability, especially in the Southeast mesoregion. The levels of these elements in this spatial zone are naturally higher than the other values across Piauí state and the mesoregion itself and indicate a high potential to exceed the QRVs. Our approach provides much needed data to help strengthen policies for both human health and environmental protection.

Desertification of Iran in the early twenty-first century: assessment using climate and vegetation indices.

Remote sensing of specific climatic and biogeographical parameters is an effective means of evaluating the large-scale desertification status of drylands affected by negative human impacts. Here, we identify and analyze desertification trends in Iran for the period 2001-2015 via a combination of three indices for vegetation (NPP-net primary production, NDVI-normalized difference vegetation index, LAI-leaf area index) and two climate indices (LST-land surface temperature, P-precipitation). We combine these indices to identify and map areas of Iran that are susceptible to land degradation. We then apply a simple linear regression method, the Mann-Kendall non-parametric test, and the Theil-Sen estimator to identify long-term temporal and spatial trends within the data. Based on desertification map, we find that 68% of Iran shows a high to very high susceptibility to desertification, representing an area of 1.1 million km2 (excluding 0.42 million km2 classified as unvegetated). Our results highlight the importance of scale in assessments of desertification, and the value of high-resolution data, in particular. Annually, no significant change is evident within any of the five indices, but significant changes (some positive, some negative) become apparent on a seasonal basis. Some observations follow expectations; for instance, NDVI is strongly associated with cooler, wet spring and summer seasons, and milder winters. Others require more explanation; for instance, vegetation appears decoupled from climatic forcing during autumn. Spatially, too, there is much local and regional variation, which is lost when the data are considered only at the largest nationwide scale. We identify a northwest-southeast belt spanning central Iran, which has experienced significant vegetation decline (2001-2015). We tentatively link this belt of land degradation with intensified agriculture in the hinterlands of Iran's major cities. The spatial and temporal trends identified with the three vegetation and two climate indices afford a cost-effective framework for the prediction and management of future environmental trends in developing regions at risk of desertification.