RSS 1.0Spatial Analysis
Spatial analysis research, comprising Geographic Information Systems (GIS), earth observing (EO) and remote sensing (RS)technologies, provides a powerful platform for the comprehensive analysis of all land–based activities at the interface between the agri-food sector, economy and the environment. A key strength of GIS/EO is the potential for integrated analysis across all scales from the field to farm right up to national level. Spatial analysis seeks to equip stakeholders with the knowledge to achieve high farm output and excellent agri-environmental quality while providing evidence-based knowledge to support policymakers in designing, implementing and evaluating programmes.
Recent Submissions
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Scenarios for European agricultural policymaking in the era of digitalisationCONTEXTDigitalisation affects the agri-food sector and its governance. However, what digitalisation of the sector will imply for future agricultural policymaking remains unclear. OBJECTIVEThe objective of the study is to develop and evaluate explorative scenarios of digitalisation in the agri-food sector of Europe that are explicitly relevant to agricultural policy. The study aims to provide guidance for strategic development of agricultural policy to address the potentials, uncertainties and unknowns arising with digitalisation of the sector. METHODSWe combine a Delphi study and a participatory scenario workshop to develop and evaluate plausible explorative scenarios of digitalisation of Europe's agri-food sector. For all scenarios we identify gaps in achieving a range of important European agricultural policy goals, drawing on the Delphi study and desk-based analysis. Subsequently we deduce strategies to address these agricultural policy gaps. RESULTS AND CONCLUSIONSFour scenarios of digitalisation of the agri-food sector were developed for Europe in 2030. They comprise of 1) digitalisation of the sector following current directions at current rates as a baseline scenario, 2) strong digitalisation of a regulatory government, 3) use of autonomous farming technology and 4) digitalised food business. These explorative scenarios entail various gaps in achieving European agricultural policy goals. Our findings suggest that the baseline scenario needs strategies to ramp up technological and institutional infrastructure for digitalisation. The other scenarios need strategies to prevent risks, e.g., of technological failures or undesired social impacts. They also need strategies to cater for special cases and diversity, e.g., of ecosystems and farming practices. Across the scenarios, it seems useful to increase digital competencies of the stakeholders. SIGNIFICANCEThe study is the first that derives implications for policy strategies from explorative scenarios of future digitalisation of agricultural systems that target gaps in achieving agricultural policy goals. The combination of developing and analysing scenarios generated findings that are of significance to policymaking stakeholders and researchers alike, who all need to address the uncertainties arising with future digitalisation of the agri-food sector.
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A Response to the Draft Climate Change Adaptation Sectoral Plan for Agriculture, Forest and Seafood SectorTeagasc is pleased to have the opportunity to contribute to this Draft Climate Change Adaptation Sectoral Plan for Agriculture, Forest and Seafood Sectors, although our contribution will largely be limited to the agriculture and forestry sectors. We have also taken the liberty to contribute in the form of ‘submissions, observations and comments’ as indicated in the call for contributions rather than in the formal questionnaire which appears to be more appropriate for an individual submission rather than an organisational contribution.
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Beyond ruminants: discussing opportunities for alternative pasture uses in New ZealandThe New Zealand government has set ambitious goals for primary sector growth and of zero net carbon emissions by 2050. This presents an opportunity and obligation to develop new ideas for grassland production systems to increase export value and generate new job opportunities, while reducing environmental impacts. The aim of this paper is to draw on recent research in Europe to investigate some of the alternative and complementary uses for pasture as a feedstock for a green biorefinery. A biorefinery is a facility, or a series of processes, that convert biomass into a spectrum of value-added products. For example, protein can be extracted mechanically from green biomass once harvested. The residual fibre fraction could be used as a low-nitrogen feed for ruminants to reduce urinary nitrogen, while the liquid protein fraction could be processed to make it suitable for mono-gastric or human consumption. Enzymes can promote protein extraction and controlled conversion of insoluble plant fibres and oligosaccharides to foster gut-health promoting prebiotic food ingredients. Anaerobic digestion of residues can then be used to create energy and soilimproving products. Research and demonstration of these approaches in practice, along with the results of feasibility studies, will be required to see which of these opportunities is a good fit for New Zealand pasture systems.
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Investigating the Effectiveness of Representations Based on Word-Embeddings in Active Learning for Labelling Text DatasetsManually labelling large collections of text data is a timeconsuming and expensive task, but one that is necessary to support machine learning based on text datasets. Active learning has been shown to be an effective way to alleviate some of the effort required in utilising large collections of unlabelled data for machine learning tasks without needing to fully label them. The representation mechanism used to represent text documents when performing active learning, however, has a significant influence on how effective the process will be. While simple vector representations such as bag-of-words have been shown to be an effective way to represent documents during active learning, the emergence of representation mechanisms based on the word embeddings prevalent in neural network research (e.g. word2vec and transformer based models like BERT) offer a promising, and as yet not fully explored, alternative. This paper describes a large-scale evaluation of the effectiveness of different text representation mechanisms for active learning across 8 datasets from varied domains. This evaluation shows that using representations based on modern word embeddings, especially BERT, which have not yet been widely used in active learning, achieves a significant improvement over more commonly used vector representations like bag-of-words.
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BRIAR: Biomass Retrieval in Ireland Using Active Remote Sensing (2014-CCRP-MS.17)Biomass Retrieval Using Active Remote Sensing Hedgerows are a very significant component of the Irish landscape. They perform multiple functions, acting as boundary markers, acting as stock-proof fencing, supporting bio-diversity and controlling run-off. They function as reservoirs of above-ground biomass and their potential as carbon sinks was explored in an earlier study which found that hedgerows potentially sequester 0.5–2.7tCO2 /ha/year. The earlier study used light detection and ranging (lidar) scanning to build 3D models of hedgerows to successfully estimate biomass, but at the time the cost–benefit of doing so was poor. However, this has since changed with the availability of free lidar sources and the reduced cost of commissioning/ acquiring lidar data. The purpose of the present study was to examine the use of another active remote sensing tool, imaging radar, to estimate biomass in hedgerows. The study area around Fermoy in County Cork was field surveyed using new drone technology to collect data on a sample of hedgerows from which estimates of biomass could be drawn. These field estimates were used with new high-resolution TerraSAR-X Staring Spotlight (TSX-SS) radar imagery to model hedgerows directly from radar backscatter. The study found that hedgerow biomass cannot be derived directly from radar backscatter. There were a number of reasons for this, such as the hedgerow biomass density, with an average of 10kg/m2 , being above the threshold of saturation for radar in the X-band frequency range. However, other radar sensors with lower frequencies, and thus higher saturation limits, do not have the spatial resolution to map hedgerows. An alternative method of investigating hedgerow structure, and thus inferring biomass, interferometry, is not successful as the level of coherence between the observations in our dataset was too low to build a 3D model (i.e. the backscatter from the hedgerow changed too much between observations). A new method that examines the cross-sectional response of the radar return across a hedgerow was shown to be successful at modelling the relationship between the width of the backscatter profile and the width of the hedgerow. However, this too was sensitive to the orientation of the hedgerow to the sensor. Therefore, this study shows that radar data does not seem to be an appropriate technology for estimating hedgerow properties in Ireland. In order to estimate the national stock of hedgerow, the new Prime2 spatial data storage model (OSI, 2014) was applied in conjunction with developed maps showing the probability of a field boundary being a stone wall or a hedgerow, to give a new national estimate for hedgerow length in Ireland of 689,000km. This estimate is double the frequently quoted figure of 300,000km because of a much wider definition of “hedgerow” used in this report. Net change in hedgerow length was examined using the aerial photographic records from 1995, 2005 and 2015, along with county-level survey records, showing that there has been a net removal of hedgerows between 1995 and 2015 of between 0.16% and 0.3% per annum, although the rate is much slower in the latter half of that period. As X-band radar seems to be inappropriate for hedgerow evaluation (especially for the obvious case of the identification of the complete removal of large hedgerows, for which it is much more expensive and time-consuming than the detection of hedgerow removal using aerial photography), the existing national lidar surveys from the Geological Survey of Ireland were examined for their appropriateness for hedgerow evaluation. A digital canopy model derived from these data successfully estimated heights (mean and maximum) in the trial test site, with an r 2 value of 0.79.
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583 Evidence-based social learning for safety and health promotion among irish dairy farmersIntroduction Farming is an occupation that incurs high rates of occupational injuries and illness, including fatalities. Internationally, legislative approaches to improve agricultural occupational safety and health (OSH) practices have been inconsistent in achieving those objectives. Many alternative initiatives to influence agricultural OSH practices have been developed, frequently emphasising information provision. In Ireland, evaluation of information provision approaches, such as classroom-based learning, has found that this is ineffective for improving agricultural OSH practices. However, peer-based learning using communities of practice (COPs), such as Teagasc dairy farmer discussion groups, presents a promising context for agricultural OSH promotion in Ireland. Research has established the efficacy of farmer discussion groups for promoting adoption of novel technologies and production practices. Little research has been undertaken to assess whether they are effective for promoting agricultural OSH practices. This paper describes the extent to which Teagasc dairy discussion groups engage with agricultural OSH, and identifies the characteristics associated with agricultural OSH engagement. The results are evaluated with respect to the existing literature regarding effective social learning for farming and OSH promotion, to assess the suitability of these COPs for agricultural OSH promotion. Methods Information about discussion group characteristics and engagement with OSH topics was collected using a survey of Teagasc dairy discussion group members, and a survey of Teagasc dairy discussion group facilitators. The statistical software R was used to assess variation in discussion group engagement with OSH, and the group characteristics statistically associated with that variation. Result Analysis of the results is ongoing and will be completed in September 2017. Discussion The findings of this study, including the evaluation framework developed from literature review, can contribute to effective agricultural OSH promotion in Ireland, and internationally. This is especially true for other countries with existing farmer COPs, such as farmer discussion groups in New Zealand and Wales.
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Teagasc-EPA Soils and Subsoils Mapping Project Final Report Vol. II Maps & StatisticsThis report contains the maps and statistics for this project.
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Predicting the Distribution of High Nature Value farmland in Ireland: IDEAL-HNVConference presentation outlining the IDEAL-HNV project
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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 IrelandGlobally, 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.
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The challenge of managing soil functions at multiple scales: An optimisation study of the synergistic and antagonistic trade-offs between soil functions in IrelandRecent forecasts show a need to increase agricultural production globally by 60% from 2005 to 2050, in order to meet a rising demand from a growing population. This poses challenges for scientists and policy makers to formulate solutions on how to increase food production and simultaneously meet environmental targets such as the conservation and protection of water, the conservation of biodiversity, and the mitigation of greenhouse gas emissions. As soil and land are subject to growing pressure to meet both agronomic and environmental targets, there is an urgent need to understand to what extent these diverging targets can be met simultaneously. Previously, the concept of Functional Land Management (FLM) was developed as a framework for managing the multifunctionality of land. In this paper, we deploy and evaluate the concept of FLM, using a real case-study of Irish agriculture. We investigate a number of scenarios, encompassing combinations of intensification, expansion and land drainage, for managing three soil functions, namely primary productivity, water purification and carbon sequestration. We use proxy-indicators (milk production, nitrate concentrations and area of new afforestation) to quantify the ‘supply’ of these three soil functions, and identify the relevant policy targets to frame the ‘demand’ for these soil functions. Specifically, this paper assesses how soil management and land use management interact in meeting these multiple targets simultaneously, by employing a non-spatial land use model for livestock production in Ireland that assesses the supply of soil functions for contrasting soil drainage and land use categories. Our results show that, in principle, it is possible to manage these three soil functions to meet both agronomic and environmental objectives, but as we add more soil functions, the management requirements become increasingly complex. In theory, an expansion scenario could meet all of the objectives simultaneously. However, this scenario is highly unlikely to materialise due to farm fragmentation, low land mobility rates and the challenging afforestation rates required for achieving the greenhouse gas reduction targets. In the absence of targeted policy interventions, an unmanaged combination of scenarios is more likely to emerge. The challenge for policy formation on future land use is how to move from an unmanaged combination scenario towards a managed combination scenario, in which the soil functions are purposefully managed to meet current and future agronomic and environmental targets, through a targeted combination of intensification, expansion and land drainage. Such purposeful management requires that the supply of each soil function is managed at the spatial scale at which the corresponding demand manifests itself. This spatial scale may differ between the soil functions, and may range from farm scale to national scale. Finally, our research identifies the need for future research to also consider and address the misalignment of temporal scales between the supply and demand of soil functions.
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Barriers to uptake of technology in animal productionPresentation from the Joint Teagasc-SRUC Conference "Rural Futures II: Towards sustainable solutions for Ruminant Pastoral Agricultural Systems in Scotland and Ireland"
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Assessing the role of artificially drained agricultural land for climate change mitigation in IrelandIn 2014 temperate zone emission factor revisions were published in the IPCC Wetlands Supplement. Default values for direct CO2 emissions of artificially drained organic soils were increased by a factor of 1.6 for cropland sites and by factors ranging from 14 to 24 for grassland sites. This highlights the role of drained organic soils as emission hotspots and makes their rewetting more attractive as climate change mitigation measures. Drainage emissions of humic soils are lower on a per hectare basis and not covered by IPCC default values. However, drainage of great areas can turn them into nationally relevant emission sources. National policy making that recognizes the importance of preserving organic and humic soils’ carbon stock requires data that is not readily available. Taking Ireland as a case study, this article demonstrates how a dataset of policy relevant information can be generated. Total area of histic and humic soils drained for agriculture, resulting greenhouse gas emissions and climate change mitigation potential were assessed. For emissions from histic soils, calculations were based on IPCC emission factors, for humic soils, a modified version of the ECOSSE model was used. Results indicated 370,000 ha of histic and 426,000 ha of humic soils under drained agricultural land use in Ireland (8% and 9% of total farmed area). Calculated annual drainage emissions were 8.7 Tg CO2e from histic and 1.8 Tg CO2e from humic soils (equal to 56% of Ireland’s agricultural emissions in 2014, excluding emissions from land use). If half the area of drained histic soils was rewetted, annual saving would amount to 3.2 Tg CO2e. If on half of the deep drained, nutrient rich grasslands drainage spacing was decreased to control the average water table at −25 cm or higher, annual savings would amount to 0.4 Tg CO2e.
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Functional land management: A framework for managing soil-based ecosystem services for the sustainable intensification of agricultureSustainable food production has re-emerged at the top of the global policy agenda, driven by two challenges: (1) the challenge to produce enough food to feed a growing world population and (2) the challenge to make more efficient and prudent use of the world's natural resources. These challenges have led to a societal expectation that the agricultural sector increase productivity, and at the same time provide environmental ‘ecosystem services’ such as the provision of clean water, air, habitats for biodiversity, recycling of nutrients and mitigation against climate change. Whilst the degree to which agriculture can provide individual ecosystem services has been well researched, it is unclear how and to what extent agriculture can meet all expectations relating to environmental sustainability simultaneously, whilst increasing the quantity of food outputs. In this paper, we present a conceptual framework for the quantification of the ‘supply of’ and ‘demand for’ agricultural, soil-based ecosystem services or ‘soil functions’. We use Irish agriculture as a case-study for this framework, using proxy-indicators to determine the demand for individual soil functions, as set by agri-environmental policies, as well as the supply of soil functions, as defined by land use and soil type. We subsequently discuss how this functionality of soils can be managed or incentivised through policy measures, with a view to minimising the divergence between agronomic policies designed to promote increased agricultural production and environmental policy objectives. Finally, we discuss the applicability of this conceptual framework to agriculture and agri-environmental policies at EU level, and the implications for policy makers.
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The Impact of a Values-Based Supply Chain (VBSC) on Farm-Level Viability, Sustainability and Resilience: Case Study EvidenceThe ‘Agriculture of the Middle’ (AotM) development paradigm emphasises that in order to survive, family farms must transition from a supply chain approach to a values-based supply chain (VBSC) approach, involving amendments to both product type and actor dynamics within the chain. This paper presents a qualitative case study of a beef co-operative integrated to a VBSC. We use an analytical framework of viability, sustainability and resilience to analyse impacts at farm-level. Our analysis highlights a number of positive effects on farm-level viability, sustainability and resilience. These benefits stemmed largely from improvements to market orientation, price stability, and members’ capacities in responding to problems. However, the autonomy of the co-operative was challenged by VBSC chain members, which impacted negatively on the stability of the co-operative.
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Making sense of altmetrics: The perceived threats and opportunities for academic identityHow research impact is defined and evaluated is much-debated at research policy level. Offering one avenue for capturing societal research impact, altmetrics are proposed as quantitative indicators providing a measure of the reach and attention that a research output, such as a peer-reviewed paper, is receiving online. Eighty publicly-funded food researchers participated in an online mixed-methods engagement study. The analytical framework of sensemaking was used to explore participants’ views of altmetrics as a threat or opportunity for their perceived professional identities. The identities important to our participants included ensuring rigour and quality in knowledge production; communicating and engaging with non-academic audiences; and bringing about tangible and meaningful changes in society. While an appetite for changes to research evaluation was apparent in our study, altmetrics was perceived to introduce a number of different threats as well as opportunities to the academic identity, which will influence its potential uptake and use.
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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 IrelandGlobally, 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.
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The Significance of Short Food Supply Chains: Trends and Bottlenecks from the SKIN Thematic NetworkShort Food Supply Chains (SFSCs) are central to the alternative food movement discourse. SFSCs are based upon the interrelations among actors who are directly involved in the production, processing, distribution, and consumption of food products. They depend upon actors mobilising resources of various kinds: skills; knowledge; labour; capital; buildings etc. External factors such as policies and regulations can also encourage the creation of these shorter chains. The development of SFSCs can still be hindered by a range of other factors. Nevertheless, bottlenecks can be overcome via the sharing of information on successful SFSCs through the dissemination of Good Practices between various actors and territories. The Short Supply Chain Knowledge and Innovation (SKIN) project uses the term ‘good’ rather than ‘best’ practice to draw attention to the subjective lens through which a practice is ultimately evaluated by an end-user. This paper first outlines the many issues that confront SFSC actors which represent bottlenecks to the adoption of ‘Good Practices’. It then documents the Good Practices collected as part of the SKIN project as tangible examples of how SFSCs overcome such challenges. Lessons learnt from project highlights are subsequently assessed in an effort to mitigate and offer solutions to the challenges associated with SFSCs. The paper demonstrates the considerable latent potential inherent to SFSCs. However, in order for the agricultural sector to realise the full promise of short supply chains it must first be conscious of the issues pertinent to their prosperity.
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Teagasc submission made in response to the Discussion document for the preparation of a National Policy Statement on the BioeconomyThis document is Teagasc’s response to the “Discussion Document for the Preparation of a National Policy Statement on the Bioeconomy” issued by the Department of the Taoiseach’s Economic Division in July 2017. It recognises the potential significance of the bioeconomy to Ireland, offers some policy and strategic insights from other countries, and identifies Teagasc’s role in supporting the development of the bioeconomy in Ireland.
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If Opportunity Doesn’t Knock, Build a Door: Reflecting on a Bioeconomy Policy Agenda for IrelandThe development of the bioeconomy offers an alternative economic mode of growth whereby renewable biological resources are transformed to meet food, feed, fuel and fibre needs. Ireland however lacks a cohesive bioeconomy policy to guide this development. Drawing on a strategic analysis of the resource base in Ireland, this paper sets the scene for the development of the Irish bioeconomy. A number of case study opportunities are outlined, followed by a critical analysis of Irish bioeconomy-related policy. The analysis culminates in a bioeconomy policy illustration that highlights the number of competing interests in the bioeconomy arena, alongside the wider governance context that will influence the development of a comprehensive national bioeconomy policy.
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The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imageryIrish Journal of Agricultural and Food Research | Volume 58: Issue 1 The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery R. O’Haraemail , S. Green and T. McCarthy DOI: https://doi.org/10.2478/ijafr-2019-0006 | Published online: 11 Oct 2019 PDF Abstract Article PDF References Recommendations Abstract The capability of Sentinel 1 C-band (5 cm wavelength) synthetic aperture radio detection and ranging (RADAR) (abbreviated as SAR) for flood mapping is demonstrated, and this approach is used to map the extent of the extensive floods that occurred throughout the Republic of Ireland in the winter of 2015–2016. Thirty-three Sentinel 1 images were used to map the area and duration of floods over a 6-mo period from November 2015 to April 2016. Flood maps for 11 separate dates charted the development and persistence of floods nationally. The maximum flood extent during this period was estimated to be ~24,356 ha. The depth of rainfall influenced the magnitude of flood in the preceding 5 d and over more extended periods to a lesser degree. Reduced photosynthetic activity on farms affected by flooding was observed in Landsat 8 vegetation index difference images compared to the previous spring. The accuracy of the flood map was assessed against reports of flooding from affected farms, as well as other satellite-derived maps from Copernicus Emergency Management Service and Sentinel 2. Monte Carlo simulated elevation data (20 m resolution, 2.5 m root mean square error [RMSE]) were used to estimate the flood’s depth and volume. Although the modelled flood height showed a strong correlation with the measured river heights, differences of several metres were observed. Future mapping strategies are discussed, which include high–temporal-resolution soil moisture data, as part of an integrated multisensor approach to flood response over a range of spatial scales.
