Jonathan H. Guy

Societal interest in all aspects of sustainability has increased. Therefore, pig farmers need to be aware of their strengths and weaknesses in all dimensions of sustainability: economy, environment, social wellbeing, and animal health and welfare. Our aim was to describe and critically discuss the development of a sustainability assessment tool for pig farms and to evaluate its suitability by applying it to 63 European pig farms (13 breeding, 27 breeding-to-finishing, and 23 finishing farms). The multi-criteria assessment tool was developed in several steps (the selection and scaling of indicators and their aggregation and weighting) in order to summarise the indicators into subtheme and theme scores. The indicators contributing the most to the subtheme/theme scores were identified and discussed in order to evaluate the procedure of the development. For example, some indicators, such as Ecological compensation area, Fairness of prices, and Tail docking, for which farms were scored low, were also identified as “real world problems” in other studies. For other sustainability aspects with low performance, the threshold might have been set too ambitiously, e.g., for Number of sows per annual working unit. Furthermore, to analyse the suitability of the tool, we assessed the best and worst median theme scores (good and poor performances) for each dimension, as well as the variability of the performances of the farms within the themes. Some themes were found to be moderate, such as Pig comfort, Biodiversity, or Resilience, whereas others were found to be good, e.g., Water and the Human–animal relationship, as well as several themes of the social wellbeing dimension. Overall, the sustainability tool provides a comprehensive assessment of the sustainability of pig production. Furthermore, this publication contributes to both the theory (development of a robust sustainability tool) and the practice (provision of a tool to assess and benchmark the sustainability on farms). As a next step, a sensitivity analysis should be performed, and the tool should be applied for further development.

The aim of this study was to combine Life Cycle Assessment (LCA) with a Key Performance Indicator (KPI) assessment focusing on biodiversity in order to examine the environmental impacts of different pig farm types (13 breeding, 23 finishing and 27 breeding-to-finishing farms) in seven European countries. In addition, the relationship between environmental impacts and selected farm management characteristics was explored. Fossil energy depletion (FED), global warming (GWP), acidification (AP) as well as marine (MEP) and fresh water (FEP) eutrophication potential were assessed by an attributional LCA and expressed per kilogram body mass net sold (BMNS). In addition, the potential biodiversity performance of all crop-livestock farms within the sample (n = 56) was evaluated with a KPI assessment of biodiversity-related field management characteristics. We found no relationship between LCA results and biodiversity scores (KPI). LCA and biodiversity performance varied more within than across farm types (breeding, finishing, breeding-to-finishing). For example, the GWP expressed per kg BMNS of the breeding unit of breeding-to-finishing farms was on average (median) 2.77 (range: 1.40–4.78) and of breeding farms 2.57 (range: 1.91–3.23) kg CO₂-eq. The average (median) biodiversity theme score for breeding farms was 51% (range: 36–70%), for breeding-to-finishing farms 38% (range: 30–68%) and for finishing farms 43% (range: 28–67%). Several farm management characteristics (e.g., FCR, productivity, proportion of solid manure) correlated with all/some LCA results. Biodiversity performance depended especially on KPIs related to ecological focus areas, fertiliser management and GMO crops. The large range regarding environmental performance in both LCA and KPI assessment across farm types indicates that farm-specific improvement measures should be implemented to enhance overall environmental sustainability on farm. In conclusion, combining LCA with KPI assessment provides a more comprehensive environmental impact assessment of pig farms.

The purpose of this research was to determine which environmental factors within the pen space differ between the locations where pigs choose to lie and areas they avoid. Data on external weather conditions and the construction parameters for an existing commercial finishing pig building were input into a Dynamic Thermal (DT) model generating heat flow and surface temperature patterns in the structure and these were then input into a Computational Fluid Dynamics (CFD) model to generate data on the theoretical spatial patterns of temperature and air velocity within one room of this building on a specified day. The exact location of each pig in six selected pens within this room was taken from images from ceiling-mounted video cameras at four representative time points across the day. Using extracted air velocity and temperature data at the height of 0.64 m above the floor and a grid of approximately 600 mm to create a series of ‘cells’, the effective draught temperature (T_ED) was calculated from the models for each cell. Using a sequential regression model, the extent to which the actual lying locations of the pigs could be reliably predicted from the environmental conditions generated by model outputs and other pen factors was explored. The results showed that air velocity, T_ED and proximity to a solid pen partition (all significant at P < 0.05) had significant predictive value and collectively explained 15.55% of the total explained deviation of 17.13%. When the presence of an adjacent pig was considered, results showed that lying next to an adjacent pig, T_ED, air velocity and temperature accounted for 53.9%, 1.3%, 1.5% and 0.5% of the deviation in lying patterns, respectively (all P < 0.001). Thus, CFD model outputs could potentially provide the industry with a better understanding of which environmental drivers affect pigs’ lying location choice, even before a building is built and stocked.

Information about animal welfare standards and initiatives from eight European countries was collected, grouped, and compared to EU welfare standards to detect those aspects beyond minimum welfare levels demanded by EU welfare legislation. Literature was reviewed to determine the scientific relevance of standards and initiatives, and those aspects going beyond minimum EU standards. Standards and initiatives were assessed to determine their strengths and weaknesses regarding animal welfare. Attitudes of stakeholders in the improvement of animal welfare were determined through a Policy Delphi exercise. Social perception of animal welfare, economic implications of upraising welfare levels, and differences between countries were considered. Literature review revealed that on-farm space allowance, climate control, and environmental enrichment are relevant for all animal categories. Experts’ assessment revealed that on-farm prevention of thermal stress, air quality, and races and passageways’ design were not sufficiently included. Stakeholders considered that housing conditions are particularly relevant regarding animal welfare, and that animal-based and farm-level indicators are fundamental to monitor the progress of animal welfare. The most notable differences between what society offers and what farm animals are likely to need are related to transportation and space availability, with economic constraints being the most plausible explanation.