The aim of the Teagasc Crops, Environment and Land Use Programme is to develop and transfer cost-effective crop production systems, along with evidence-based knowledge to support and underpin the development of an environmentally sustainable, competitive and profitable agri-food sector.

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  • Easy phylotyping of Escherichia coli via the EzClermont web app and command-line tool

    Waters, Nicholas R.; Abram, Florence; Brennan, Fiona; Holmes, Ashleigh; Pritchard, Leighton; The James Hutton Institute; National University of Ireland, Galway (Microbiology Society, 2020-09-01)
    The Clermont PCR method for phylotyping Escherichia coli remains a useful classification scheme even though genome sequencing is now routine, and higher-resolution sequence typing schemes are now available. Relating present-day whole-genome E. coli classifications to legacy phylotyping is essential for harmonizing the historical literature and understanding of this important organism. Therefore, we present EzClermont – a novel in silico Clermont PCR phylotyping tool to enable ready application of this phylotyping scheme to whole-genome assemblies. We evaluate this tool against phylogenomic classifications, and an alternative software implementation of Clermont typing. EzClermont is available as a web app at, and as a command-line tool at
  • Mid-infrared spectroscopy as an alternative to laboratory extraction for the determination of lime requirement in tillage soils

    Metzger, Konrad; Zhang, Chaosheng; Ward, Mark; Daly, Karen; Teagasc Walsh Fellowship Programme; Department for Agriculture Food and the Marine; RMIS 6837; 15/ICTAGRI 2 (Elsevier BV, 2020-04)
    Lime is a crucial soil conditioner to bring agricultural soils to optimum pH values for nutrient availability. Lime recommendations are typically determined in laboratory extractions, the most common being the “Shoemaker- McLean and Pratt” (SMP) buffer method, that requires carcinogenic reagents soon to be abolished under the EU legislation. As an alternative to wet chemistry, mid-infrared (MIR) spectroscopy has shown to be a cost-and time effective method at predicting soil properties. The capability and feasibility of diffuse reflectance infrared spectroscopy (DRIFTS) to predict lime requirement (LR) in tillage fields is examined. Samples from 41 cereal tillage fields (n = 655) are used to build a calibration for DRIFTS using partial least squares regression (PLSR). The samples were split into calibration set (31 fields, n=495) and validation set (10 fields, n= 160). After preprocessing with trim, smoothing and standard normal variate, a calibration model using 6 latent variables, provided R2 of 0.89 and root mean square error of cross-validation (RMSECV) of 1.56 t/ha. Prediction of all fields from the validation set resulted in R2 of 0.76 and root mean square error of prediction (RMSEP) of 1.68 t/ ha. The predictions of the single fields ranged from R2 values of 0.41 to 0.72, RMSEP of 0.48 to 4.2 t/ha and ratios of performance to inter-quartile distance (RPIQ) of 0.45 to 3.56. It was shown that the signals of soil constituents having an influence on the LR were picked up in the spectra and were identified in the loading weights of the PLSR. While the error is too high to predict the variability of LR within the field, MIR prediction using field averages provided a viable alternative to current laboratory methods for blanket spreading of lime on tillage fields.
  • Why Dairy Farming And Silvopastoral Agroforestry Could Be The Perfect Match

    Irish Agroforestry Forum; Short, Ian; Department of Agriculture, Food and the Marine (Irish Farm Business, 2020)
    Could we be missing a trick here? Could silvopasture be a design solution to the environmental challenges facing farming? Can it be the ideal mechanism to combine agriculture, forestry and ecology with very positive outcomes for farmers? Well -designed silvopasture can help increase profits and productivity, animal, and soil health, diversify the farm business, buffer against increasingly variable weather, drought and flood risks while benefiting the environment, the water cycle and the carbon cycle.
  • Genetic Analysis Using a Multi-Parent Wheat Population Identifies Novel Sources of Septoria Tritici Blotch Resistance

    Riaz, Adnan; KockAppelgren, Petra; Hehir, James Gerard; Kang, Jie; Meade, Fergus; Cockram, James; Milbourne, Dan; Spink, John; Mullins, Ewen; Byrne, Stephen; et al. (MDPI AG, 2020-08-04)
    Zymoseptoria tritici is the causative fungal pathogen of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.) that continuously threatens wheat crops in Ireland and throughout Europe. Under favorable conditions, STB can cause up to 50% yield losses if left untreated. STB is commonly controlled with fungicides; however, a combination of Z. tritici populations developing fungicide resistance and increased restrictions on fungicide use in the EU has led to farmers relying on fewer active substances. Consequently, this serves to drive the emergence of Z. tritici resistance against the remaining chemistries. In response, the use of resistant wheat varieties provides a more sustainable disease management strategy. However, the number of varieties offering an adequate level of resistance against STB is limited. Therefore, new sources of resistance or improved stacking of existing resistance loci are needed to develop varieties with superior agronomic performance. Here, we identified quantitative trait loci (QTL) for STB resistance in the eight-founder “NIAB Elite MAGIC” winter wheat population. The population was screened for STB response in the field under natural infection for three seasons from 2016 to 2018. Twenty-five QTL associated with STB resistance were identified in total. QTL either co-located with previously reported QTL or represent new loci underpinning STB resistance. The genomic regions identified and the linked genetic markers serve as useful resources for STB resistance breeding, supporting rapid selection of favorable alleles for the breeding of new wheat cultivars with improved STB resistance.
  • Detection of Novel QTLs for Late Blight Resistance Derived from the Wild Potato Species Solanum microdontum and Solanum pampasense

    Meade, Fergus; Hutten, Ronald; Wagener, Silke; Prigge, Vanessa; Dalton, Emmet; Kirk, Hanne Grethe; Griffin, Denis; Milbourne, Dan; Department of Agriculture, Food and the Marine; IPM Potato Group; et al. (MDPI AG, 2020-06-30)
    Wild potato species continue to be a rich source of genes for resistance to late blight in potato breeding. Whilst many dominant resistance genes from such sources have been characterised and used in breeding, quantitative resistance also offers potential for breeding when the loci underlying the resistance can be identified and tagged using molecular markers. In this study, F1 populations were created from crosses between blight susceptible parents and lines exhibiting strong partial resistance to late blight derived from the South American wild species Solanum microdontum and Solanum pampasense. Both populations exhibited continuous variation for resistance to late blight over multiple field-testing seasons. High density genetic maps were created using single nucleotide polymorphism (SNP) markers, enabling mapping of quantitative trait loci (QTLs) for late blight resistance that were consistently expressed over multiple years in both populations. In the population created with the S. microdontum source, QTLs for resistance consistently expressed over three years and explaining a large portion (21–47%) of the phenotypic variation were found on chromosomes 5 and 6, and a further resistance QTL on chromosome 10, apparently related to foliar development, was discovered in 2016 only. In the population created with the S. pampasense source, QTLs for resistance were found in over two years on chromosomes 11 and 12. For all loci detected consistently across years, the QTLs span known R gene clusters and so they likely represent novel late blight resistance genes. Simple genetic models following the effect of the presence or absence of SNPs associated with consistently effective loci in both populations demonstrated that marker assisted selection (MAS) strategies to introgress and pyramid these loci have potential in resistance breeding strategies.
  • Predicting the Distribution of High Nature Value farmland in Ireland: IDEAL-HNV

    Finn, John; Sullivan, Caroline; O’hÚallacháin, Daire; green, stuart; Clifford, Brian; Matin, Shafique; Meredith, David; Moran, James (2020-08-28)
    Conference presentation outlining the IDEAL-HNV project
  • Environmental footprint family to address local to planetary sustainability and deliver on the SDGs

    Vanham, Davy; Leip, Adrian; Galli, Alessandro; Kastner, Thomas; Bruckner, Martin; Uwizeye, Aimable; van Dijk, Kimo; Ercin, Ertug; Dalin, Carole; Brandão, Miguel; et al. (Elsevier BV, 2019-07-29)
    The number of publications on environmental footprint indicators has been growing rapidly, but with limited efforts to integrate different footprints into a coherent framework. Such integration is important for comprehensive understanding of environmental issues, policy formulation and assessment of trade-offs between different environmental concerns. Here, we systematize published footprint studies and define a family of footprints that can be used for the assessment of environmental sustainability. We identify overlaps between different footprints and analyse how they relate to the nine planetary boundaries and visualize the crucial information they provide for local and planetary sustainability. In addition, we assess how the footprint family delivers on measuring progress towards Sustainable Development Goals (SDGs), considering its ability to quantify environmental pressures along the supply chain and relating them to the water-energy-food-ecosystem (WEFE) nexus and ecosystem services. We argue that the footprint family is a flexible framework where particular members can be included or excluded according to the context or area of concern. Our paper is based upon a recent workshop bringing together global leading experts on existing environmental footprint indicators.
  • Biogeography of arbuscular mycorrhizal fungal spore traits along an aridity gradient, and responses to experimental rainfall manipulation

    Deveautour, Coline; Chieppa, Jeff; Nielsen, Uffe N.; Boer, Matthias M.; Mitchell, Christopher; Horn, Sebastian; Power, Sally A.; Guillen, Alberto; Bennett, Alison E.; Powell, Jeff R.; et al. (Elsevier BV, 2020-08)
    Spore size, colour and melanin content are hypothesised to be functional in relation to environmental stress. Here, we studied AM fungal spores in arid environments of Australia and in an experimental platform simulating altered rainfall. We used microscopy and image analysis to measure spore colour and size, and a quantitative colorimetric assay to estimate melanin content in spores. In arid sites, melanin content tended to increase with increasing aridity. We observed a large range of spore colours at all sites but found a higher proportion of both dark and light spores, and fewer intermediate colours, in drier sites. Spore abundance and size varied among sites, but neither were related to aridity. In the experimental platform established in a grassland, we found no evidence that altered rainfall influenced spore traits. This study identifies traits associated with environmental stress to inform future work into AM fungal life history and assembly processes.
  • Annual replication is essential in evaluating the response of the soil microbiome to the genetic modification of maize in different biogeographical regions

    Szoboszlay, Márton; Näther, Astrid; Mullins, Ewen; Tebbe, Christoph C.; European Union; 289706 (Public Library of Science (PLoS), 2019-12-17)
    The importance of geographic location and annual variation on the detection of differences in the rhizomicrobiome caused by the genetic modification of maize (Bt-maize, event MON810) was evaluated at experimental field sites across Europe including Sweden, Denmark, Slovakia and Spain. DNA of the rhizomicrobiome was collected at the maize flowering stage in three consecutive years and analyzed for the abundance and diversity of PCR-amplified structural genes of Bacteria, Archaea and Fungi, and functional genes for bacterial nitrite reductases (nirS, nirK). The nirK genes were always more abundant than nirS. Maize MON810 did not significantly alter the abundance of any microbial genetic marker, except for sporadically detected differences at individual sites and years. In contrast, annual variation between sites was often significant and variable depending on the targeted markers. Distinct, site-specific microbial communities were detected but the sites in Denmark and Sweden were similar to each other. A significant effect of the genetic modification of the plant on the community structure in the rhizosphere was detected among the nirK denitrifiers at the Slovakian site in only one year. However, most nirK sequences with opposite response were from the same or related source organisms suggesting that the transient differences in community structure did not translate to the functional level. Our results show a lack of effect of the genetic modification of maize on the rhizosphere microbiome that would be stable and consistent over multiple years. This demonstrates the importance of considering annual variability in assessing environmental effects of genetically modified crops.
  • Genomic prediction of crown rust resistance in Lolium perenne

    Arojju, Sai Krishna; Conaghan, Patrick; Barth, Susanne; Milbourne, Dan; Casler, Michael D.; Hodkinson, Trevor R.; Michel, Thibauld; Byrne, Stephen; Department of Agriculture Food and the Marine; European Union; et al. (Springer Science and Business Media LLC, 2018-05-29)
    Background Genomic selection (GS) can accelerate genetic gains in breeding programmes by reducing the time it takes to complete a cycle of selection. Puccinia coronata f. sp lolli (crown rust) is one of the most widespread diseases of perennial ryegrass and can lead to reductions in yield, persistency and nutritional value. Here, we used a large perennial ryegrass population to assess the accuracy of using genome wide markers to predict crown rust resistance and to investigate the factors affecting predictive ability. Results Using these data, predictive ability for crown rust resistance in the complete population reached a maximum of 0.52. Much of the predictive ability resulted from the ability of markers to capture genetic relationships among families within the training set, and reducing the marker density had little impact on predictive ability. Using permutation based variable importance measure and genome wide association studies (GWAS) to identify and rank markers enabled the identification of a small subset of SNPs that could achieve predictive abilities close to those achieved using the complete marker set. Conclusion Using a GWAS to identify and rank markers enabled a small panel of markers to be identified that could achieve higher predictive ability than the same number of randomly selected markers, and predictive abilities close to those achieved with the entire marker set. This was particularly evident in a sub-population characterised by having on-average higher genome-wide linkage disequilibirum (LD). Higher predictive abilities with selected markers over random markers suggests they are in LD with QTL. Accuracy due to genetic relationships will decay rapidly over generations whereas accuracy due to LD will persist, which is advantageous for practical breeding applications.
  • Functional Land Management: Bridging the Think-Do-Gap using a multi-stakeholder science policy interface

    O’Sullivan, Lilian; Wall, David; Creamer, Rachel; Bampa, Francesca; Schulte, Rogier P. O.; National Development Plan 2007–2013; European Union; 13S468; 635201; 677407 (Springer Science and Business Media LLC, 2017-11-24)
    Functional Land Management (FLM) is proposed as an integrator for sustainability policies and assesses the functional capacity of the soil and land to deliver primary productivity, water purification and regulation, carbon cycling and storage, habitat for biodiversity and recycling of nutrients. This paper presents the catchment challenge as a method to bridge the gap between science, stakeholders and policy for the effective management of soils to deliver these functions. Two challenges were completed by a wide range of stakeholders focused around a physical catchment model—(1) to design an optimised catchment based on soil function targets, (2) identify gaps to implementation of the proposed design. In challenge 1, a high level of consensus between different stakeholders emerged on soil and management measures to be implemented to achieve soil function targets. Key gaps including knowledge, a mix of market and voluntary incentives and mandatory measures were identified in challenge 2.
  • Assessments of Composite and Discrete Sampling Approaches for Water Quality Monitoring

    Cassidy, Rachel; Jordan, Phil; Bechmann, Marianne; Kronvang, Brian; Kyllmar, Katarina; Shore, Mairead (Springer Science and Business Media LLC, 2018-04-12)
    Achieving an operational compromise between spatial coverage and temporal resolution in national scale river water quality monitoring is a major challenge for regulatory authorities, particularly where chemical concentrations are hydrologically dependent. The efficacy of flow-weighted composite sampling (FWCS) approaches for total phosphorus (TP) sampling (n = 26–52 analysed samples per year), previously applied in monitoring programmes in Norway, Sweden and Denmark, and which account for low to high flow discharges, was assessed by repeated simulated sampling on high resolution TP data. These data were collected in three research catchments in Ireland over the period 2010–13 covering a base-flow index range of 0.38 to 0.69. Comparisons of load estimates were also made with discrete (set time interval) daily and sub-daily sampling approaches (n = 365 to >1200 analysed samples per year). For all years and all sites a proxy of the Norwegian sampling approach, which is based on re-forecasting discharge for each 2-week deployment, proved most stable (median TP load estimates of 87–98%). Danish and Swedish approaches, using long-term flow records to set a flow constant, were only slightly less effective (median load estimates of 64–102% and 80–96%, respectively). Though TP load estimates over repeated iterations were more accurate using the discrete approaches, particularly the 24/7 approach (one sample every 7 h in a 24 bottle sampler - median % load estimates of 93–100%), composite load estimates were more stable, due to the integration of multiple small samples (n = 100–588) over a deployment.
  • Evaluation of the ’Irish Rules’: The Potato Late Blight Forecasting Model and Its Operational Use in the Republic of Ireland

    Cucak, Mladen; Sparks, Adam; Moral, Rafael; Kildea, Steven; Lambkin, Keith; Fealy, Rowan; Department of Agriculture, Food and the Marine; 14/S/879 (MDPI AG, 2019-09-06)
    Potato late blight caused by Phytophthora infestans is one of the most important plant diseases known, requiring high pesticide inputs to prevent disease occurrence. The disease development is highly dependent on weather conditions, and as such, several forecasting schemes have been developed worldwide which seek to reduce the inputs required to control the disease. The Irish Rules, developed in the 1950s and calibrated to accommodate the meteorological network, the characteristics of potato production and the P. infestans population at the time, is still operationally utilized by the national meteorological agency, Met Éireann. However, numerous changes in the composition and dynamics of the pathosystem and the risks of production/economic consequences associated with potato late blight outbreaks have occurred since the inception of the Irish Rules model. Additionally, model and decision thresholds appear to have been selected ad hoc and without a clear criteria. We developed a systematic methodology to evaluate the model using the empirical receiver operating curve (ROC) analysis and the response surface methodology for the interpretation of the results. The methodology, written in the R language, is provided as an open, accessible and reproducible platform to facilitate the ongoing seasonal re-evaluation of the Irish Rules and corresponding decision thresholds. Following this initial analysis, based on the available data, we recommend the reduction of the thresholds for relative humidity and an initial period duration from 90% and 12 h to 88% and 10 h, respectively. Contrary to recent reports, we found that the risk of blight epidemics remains low at temperatures below 12 °C. With the availability of more comprehensive outbreak data and with greater insight into the founder population to confirm our findings as robust, the temperature threshold in the model could potentially be increased from 10 °C to 12 °C, providing more opportunities for reductions of pesticide usage. We propose a dynamic operational decision threshold between four and 11 effective blight hours (EBH) set according to frequency of the disease outbreaks in the region of interest. Although the risk estimation according to the new model calibrations is higher, estimated chemical inputs, on average, are lower than the usual grower’s practice. Importantly, the research outlined here provides a robust and reproducible methodological approach to evaluate a semi-empirical plant disease forecasting model.
  • Genotyping by Sequencing and Plastome Analysis Finds High Genetic Variability and Geographical Structure in Dactylis glomerata L. in Northwest Europe Despite Lack of Ploidy Variation

    Hodkinson, Trevor R.; Perdereau, Aude; Klaas, Manfred; Cormican, Paul; Barth, Susanne; EU; 289461 (MDPI AG, 2019-06-28)
    Large collections of the forage and bioenergy grass Dactylis glomerata were made in northwest (NW) Europe along east to west and north to south clines for genetic resource conservation and to inform breeding programmes of genetic diversity, genepools, and ploidy. Leaves were sampled for genetic analysis and seed and rhizome for ex-situ conservation. Genotyping by sequencing (GBS) was used to assay nuclear DNA diversity and plastome single nucleotide polymorphism (SNP) discovery was undertaken using a long-read PCR and MiSeq approach. Nuclear and plastid SNPs were analysed by principal component analysis (PCA) to compare genotypes. Flow cytometry revealed that all samples were tetraploid, but some genome size variation was recorded. GBS detected an average of approximately 10,000 to 15,000 SNPs per country sampled. The highest average number of private SNPs was recorded in Poland (median ca. 2000). Plastid DNA variation was also high (1466 SNPs, 17 SNPs/kbp). GBS data, and to a lesser extent plastome data, also show that genetic variation is structured geographically in NW Europe with loose clustering matching the country of plant origin. The results reveal extensive genetic diversity and genetic structuring in this versatile allogamous species despite lack of ploidy variation and high levels of human mediated geneflow via planting.
  • Gain in Nitrogen Yield from Grass-Legume Mixtures is Robust Over a Wide Range of Legume Proportions and Environmental Conditions

    Suter, Matthias; Finn, John; Connolly, John; Loges, Ralph; Lüscher, Andreas (Elsevier BV, 2015-08-19)
    Global food security is currently challenged and requires sustainable intensification of agriculture through initiatives that include more efficient use of nitrogen (N) and increased protein self-sufficiency through home-grown crops. Such challenges were addressed in a continental-scale field experiment conducted over three years, in which the amount of total nitrogen yield (Ntot) and the gain in N yield in mixtures as compared to grass monocultures (Ngainmix) was quantified from four-species grass-legume stands with greatly varying legume proportions. Stands consisted of monocultures and mixtures of two N2 fixing legumes and two non-fixing grasses. The amount of Ntot of mixtures was significantly greater (P ≤ 0.05) than that of grass monocultures at the majority of evaluated sites in all three years. Ntot and thus Ngainmix increased with increasing legume proportion up to one third of legumes. With higher percentages of legumes, Ntot and Ngainmix did not further increase. Thus, across sites and years, mixtures with one third proportion of legumes had 57% higher Ntot than grass monocultures and attained ∼95% of the maximum Ntot acquired by any stand. The relative N gain in mixture (Ngainmix/Ntotmix) was most severely impaired by minimum site temperature (R = 0.64, P = 0.010). Nevertheless, Ngainmix/Ntotmix was not correlated to site productivity (P = 0.500), suggesting that, within climatic restrictions, balanced grass-legume mixtures can benefit from comparable relative gains in N yield across largely differing productivity levels. We conclude that higher N output (Ntot or forage protein per unit area) can be achieved with grass-legume mixtures than with pure grass alone for a given amount of N fertilizer applied; conversely, the same N output can be achieved by mixed swards with less input of N. Therefore, the use of grass-legume mixtures can substantially contribute to resource-efficient agricultural grassland systems over a wide range of productivity levels, implying important savings in N fertilizers and greenhouse gas emissions.
  • Functional Land Management for managing soil functions: A case-study of the trade-off between primary productivity and carbon storage in response to the intervention of drainage systems in Ireland

    O'Sullivan, L.; Creamer, Rachel; Fealy, Reamonn; Lanigan, Gary; Simo, I.; Fenton, Owen; Carfrae, J.; Schulte, R.P.O.; Department of Agriculture, Food and the Marine (Elsevier BV, 2015-09)
    Globally, there is growing demand for increased agricultural outputs. At the same time, the agricultural industry is expected to meet increasingly stringent environmental targets. Thus, there is an urgent pressure on the soil resource to deliver multiple functions simultaneously. The Functional Land Management framework (Schulte et al., 2014) is a conceptual tool designed to support policy making to manage soil functions to meet these multiple demands. This paper provides a first example of a practical application of the Functional Land Management concept relevant to policy stakeholders. In this study we examine the trade-offs, between the soil functions ‘primary productivity’ and ‘carbon cycling and storage’, in response to the intervention of land drainage systems applied to ‘imperfectly’ and ‘poorly’ draining managed grasslands in Ireland. These trade-offs are explored as a function of the nominal price of ‘Certified Emission Reductions’ or ‘carbon credits’. Also, these trade-offs are characterised spatially using ArcGIS to account for spatial variability in the supply of soil functions. To manage soil functions, it is essential to understand how individual soil functions are prioritised by those that are responsible for the supply of soil functions – generally farmers and foresters, and those who frame demand for soil functions – policy makers. Here, in relation to these two soil functions, a gap exists in relation to this prioritisation between these two stakeholder groups. Currently, the prioritisation and incentivisation of these competing soil functions is primarily a function of CO2 price. At current CO2 prices, the agronomic benefits outweigh the monetised environmental costs. The value of CO2 loss would only exceed productivity gains at either higher CO2 prices or at a reduced discount period rate. Finally, this study shows large geographic variation in the environmental cost: agronomic benefit ratio. Therein, the Functional Land Management framework can support the development of policies that are more tailored to contrasting biophysical environments and are therefore more effective than ‘blanket approaches’ allowing more specific and effective prioritisation of contrasting soil functions.
  • Groundwater nitrate reduction versus dissolved gas production: A tale of two catchments

    McAleer, E.B.; Coxon, C.E.; Richards, Karl G.; Jahangir, M.M.R; Grant, J.; Mellander, Per-Erik; Teagasc Walsh Fellowship Programme (Elsevier BV, 2017-05-15)
    At the catchment scale, a complex mosaic of environmental, hydrogeological and physicochemical characteristics combine to regulate the distribution of groundwater and stream nitrate (NO3 −). The efficiency of NO3 − removal (via denitrification) versus the ratio of accumulated reaction products, dinitrogen (excess N2) & nitrous oxide (N2O), remains poorly understood. Groundwater was investigated in two well drained agricultural catchments (10 km2 ) in Ireland with contrasting subsurface lithologies (sandstone vs. slate) and landuse. Denitrification capacity was assessed by measuring concentration and distribution patterns of nitrogen (N) species, aquifer hydrogeochemistry, stable isotope signatures and aquifer hydraulic properties. A hierarchy of scale whereby physical factors including agronomy, water table elevation and permeability determined the hydrogeochemical signature of the aquifers was observed. This hydrogeochemical signature acted as the dominant control on denitrification reaction progress. High permeability, aerobic conditions and a lack of bacterial energy sources in the slate catchment resulted in low denitrification reaction progress (0–32%), high NO3 − and comparatively low N2O emission factors (EF5g1). In the sandstone catchment denitrification progress ranged from 4 to 94% and was highly dependent on permeability, water table elevation, dissolved oxygen concentration solid phase bacterial energy sources. Denitrification of NO3− to N2 occurred in anaerobic conditions, while at intermediate dissolved oxygen; N2O was the dominant reaction product. EF5g1 (mean: 0.0018) in the denitrifying sandstone catchment was 32% less than the IPCC default. The denitrification observations across catchments were supported by stable isotope signatures. Stream NO3 − occurrence was 32% lower in the sandstone catchment even though N loading was substantially higher than the slate catchment.
  • Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments

    Oliver, David M.; Porter, Kenneth D.H.; Pachepsky, Yakov A.; Muirhead, Richard W.; Reaney, Sim M.; Coffey, Rory; Kay, David; Milledge, David G.; Hong, Eunmi; Anthony, Steven G.; et al. (Elsevier BV, 2016-02)
    The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.
  • A Functional Land Management conceptual framework under soil drainage and land use scenarios

    Coyle, Cait; Creamer, Rachel E.; Schulte, Rogier P.O.; O'Sullivan, Lilian; Jordan, Phil; Institute of Technology, Sligo (Elsevier BV, 2015-11-15)
    Agricultural soils offer multiple soil functions, which contribute to a range of ecosystem services, and the demand for the primary production function is expected to increase with a growing world population. Other key functions on agricultural land have been identified as water purification, carbon sequestration, habitat biodiversity and nutrient cycling, which all need to be considered for sustainable intensification. All soils perform all functions simultaneously, but the variation in the capacity of soils to supply these functions is reviewed in terms of defined land use types (arable, bio-energy, broadleaf forest, coniferous forest, managed grassland, other grassland and Natura 2000) and extended to include the influence of soil drainage characteristics (well, moderately/imperfect, poor and peat). This latter consideration is particularly important in the European Atlantic pedo-climatic zone; the spatial scale of this review. This review develops a conceptual framework on the multi-functional capacity of soils, termed Functional Land Management, to facilitate the effective design and assessment of agri-environmental policies. A final functional soil matrix is presented as an approach to show the consequential changes to the capacity of the five soil functions associated with land use change on soils with contrasting drainage characteristics. Where policy prioritises the enhancement of particular functions, the matrix indicates the potential trade-offs for individual functions or the overall impact on the multi-functional capacity of soil. The conceptual framework is also applied by land use area in a case study, using the Republic of Ireland as an example, to show how the principle of multi-functional land use planning can be readily implemented.
  • Exploring the sensitivity of visual soil evaluation to traffic-induced soil compaction

    Emmet-Booth, J.P.; Holden, N.M.; Fenton, Owen; Bondi, G; Forristal, P.D.; Irish Department of Agriculture, Food and the Marine; 13/S/468 (Elsevier, 2019-10-24)
    Visual Soil Evaluation (VSE) techniques are useful for assessing the impact of land management, particularly the identification and remediation of soil compaction. Despite an increasing body of VSE research, comparatively few studies have explored the sensitivity of VSE for capturing experimentally imposed compaction to estimate sensitivity and limit of detection. The aim of this research was to examine the ability of VSE techniques to indicate soil structure at different soil profile depths and to measure the associated soil productive function (yield) response to imposed compaction. A two-year experiment was conducted on sites with loam and sandy soils. Varying levels of wheeled traffic were imposed on plots in a randomised block design, prior to sowing winter barley (Hordeum vulgare L.). Quantitative crop and soil measurements were taken throughout the season in conjunction with VSE techniques, which assessed to 25 cm (VESS), 40 cm (Double Spade) and 80 cm (SubVESS) depth. Graduated changes were observed by soil and some crop quantitative measurements as traffic treatment varied. VESS and Double Spade successfully identified a graduated treatment effect at all sites to 40 cm depth, although diagnosis translated into a yield response for the loam but not the sandy soil. Correlation between VESS Sq scores and crop yield were found. SubVESS gave mixed signals and indicated impacts lower in the profile in certain instances. These impacts were not captured by quantitative soil measurements.This work highlights the capacity for VSE techniques to indicate soil structural damage, which may cause a crop yield response, therefore allowing appropriate soil management strategies to be deployed before yield penalties occur.

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