• Data file: confusion matrices from pilot study of methodology for the development of farmland habitat reports for sustainability assessments

      Finn, John; Moran, Patrick; Teagasc; 6793 (2020-03-09)
      This Excel data file provides the confusion matrices associated with a publication in the Irish Journal of Agricultural and Food Research. This file contains four worksheets: 'High vs Low matrix', 'Level II matrix', 'Level III matrix' and 'Level III matrix (HH)'. Each worksheet presents the area of different habitat classes (as in Fossitt 2000) as determined by a desk-based study of remote sensing imagery, and compared with area of habitat classes as determined by a field-based survey (ground-truthing). The publication by John A. Finn and Patrick Moran is titled 'A pilot study of methodology for the development of farmland habitat reports for sustainability assessments'.
    • 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.
    • LIFE BEEF CARBON: a common framework for quantifying grass and corn based beef farms’ carbon footprints

      O’Brien, D.; Herron, J.; Andurand, J.; Caré, S.; Martinez, P.; Migliorati, L.; Moro, M.; Pirlo, G.; Dollé, J-B; European Union; et al. (Cambridge University Press (CUP), 2019-10-31)
      Europe’s roadmap to a low-carbon economy aims to cut greenhouse gas (GHG) emissions 80% below 1990 levels by 2050. Beef production is an important source of GHG emissions and is expected to increase as the world population grows. LIFE BEEF CARBON is a voluntary European initiative that aims to reduce GHG emissions per unit of beef (carbon footprint) by 15% over a 10-year period on 2172 farms in four large beef-producing countries. Changes in farms beef carbon footprint are normally estimated via simulation modelling, but the methods current models apply differ. Thus, our initial goal was to develop a common modelling framework to estimate beef farms carbon footprint. The framework was developed for a diverse set of Western Europe farms located in Ireland, Spain, Italy and France. Whole farm and life cycle assessment (LCA) models were selected to quantify emissions for the different production contexts and harmonized. Carbon Audit was chosen for Ireland, Bovid-CO2 for Spain and CAP’2ER for France and Italy. All models were tested using 20 case study farms, that is, 5 per country and quantified GHG emissions associated with on-farm live weight gain. The comparison showed the ranking of beef systems gross carbon footprint was consistent across the three models. Suckler to weaning or store systems generally had the highest carbon footprint followed by suckler to beef systems and fattening beef systems. When applied to the same farm, Carbon Audit’s footprint estimates were slightly lower than CAP’2ER, but marginally higher than Bovid-CO2. These differences occurred because the models were adapted to a specific region’s production circumstances, which meant their emission factors for key sources; that is, methane from enteric fermentation and GHG emissions from concentrates were less accurate when used outside their target region. Thus, for the common modelling framework, regionspecific LCA models were chosen to estimate beef carbon footprints instead of a single generic model. Additionally, the Carbon Audit and Bovid-CO2 models were updated to include carbon removal by soil and other environmental metrics included in CAP’2ER, for example, acidification. This allows all models to assess the effect carbon mitigation strategies have on other potential pollutants. Several options were identified to reduce beef farms carbon footprint, for example, improving genetic merit. These options were assessed for beef systems, and a mitigation plan was created by each nation. The cumulative mitigation effect of the LIFE BEEF CARBON plan was estimated to exceed the projects reduction target (−15%).
    • A pilot study of methodology for the development of farmland habitat reports for sustainability assessments

      Finn, John; Moran, P.; Bord Bia (TeagascCompuscript Ltd, 2020-11-21)
      The inclusion of farm maps of habitat features is becoming an urgent requirement for assessments of farm-scale sustainability and for compliance or benchmarking with national and international sustainability certification and accreditation schemes. Traditional methods of habitat assessment rely strongly on field-based surveys, which are logistically demanding and relatively costly. We describe and investigate a process that relies on information technology to develop a scalable method that can be applied across multiple farms to reduce the significant logistical challenges and financial costs of traditional habitat surveys. A key impediment to the routine development of farm habitat maps is the lack of information on the type of habitats that occur on a land parcel. Within a pilot project comprising 187 farms, we developed and implemented a process for creating farm habitat reports and investigate the accuracy of visual interpretation of satellite imagery by an ecologist aiming to identify habitat types. We generated customised farm reports that included a colour-coded farm habitat map and habitat information (type, area, relative wildlife importance). Visual assessment of satellite imagery achieved an overall accuracy of 96% in its ability to discriminate between land parcels with habitats categorised by this study as being of either high or low nature conservation value. Assessment of satellite imagery achieved an overall accuracy of 90% in its ability to discriminate among Fossitt level II habitat classes, and an overall accuracy of 81% when using individual habitat classes (Fossitt level III). There was, however, considerable variation in the accuracy associated with individual habitat classes. We conclude that this methodology based on satellite imagery is sufficiently accurate to be used for the incorporation of farmland habitats into farm-scale sustainability assurance, but should, at most, use Fossitt level II habitat classes. We discuss future challenges and opportunities for the development of farm habitat maps and plans for their use in sustainability certification schemes.
    • Sustainability indicators for improved assessment of the effects of agricultural policy across the EU: Is FADN the answer?

      Kelly, Edel; Latruffe, Laure; Desjeux, Yann; Ryan, Mary; Uthes, Sandra; Diazabakanab, Ambre; Dillon, Emma; Finn, John; European Union; 613800 (Elsevier, 2018-06)
      Policy reform of the CAP and society’s expectations of agriculture have resulted in a growing need for improved information on the effectiveness of policy in achieving high-level objectives for more sustainable practice in agriculture. This is a high priority given its importance for consumers, public policy and private industry. Data collection programmes will need to adapt their scope if their information is to adequately address new information needs about high-level objectives. Assessment of sustainability at the farm level is hindered by the lack of data with which to derive appropriate, meaningful, and relevant indicators. This is particularly problematic for assessment of agricultural sustainability across the European Union (EU). Various databases exist at the EU scale regarding agricultural data sources and we identify one of these, the EU Farm Accountancy Data Network (FADN), as having considerable potential to assess farm-level sustainability at EU level. We critique several examples of published work that has attempted to assess agricultural sustainability using: FADN data alone; FADN data in combination with data from supplementary surveys, and; FADN data in combination with data from other EU databases. We conclude that the FADN would need to broaden its scope of data collection if it is to address the new information needs of policy, and we discuss the challenges in expanding FADN with a view towards wider farm-level assessment of sustainability. These include careful selection of indicators based on various criteria, the representativeness of the FADN, and the need to include new themes to address environmental, social, and animal welfare effects of policy.