Trade-offs between conflicting animal welfare concerns and cow replacement strategy in out-wintering Scottish suckler herds

Since decoupling of the CAP, many Scottish suckler cow farms are facing financial difficulties. In response, many farmers are out-wintering extensively managed suckler cows to minimise production costs. These systems are of animal welfare concern. A range of trade-offs between animal welfare indicators and between animal welfare and farm profitability can be identified. A Dynamic Programming (DP) model was developed to study these trade-offs. Two herds were modelled assuming their feeding regimes were either low (LHERD) or high (HHERD). The objective of the DP was to maximise the expected net margin from a current cow and its successors over an infinite time horizon. Preliminary results showed that the rate of voluntary culling was higher in HHERD than in LHERD. Animals in HHERD had shorter life expectancy. The expected net present value was 58% lower in LHERD than HHERD (-£41.5 and -£24.3 respectively). These results suggest a heavier culling rate and shorter longevity for animals in HHERD that compromises animal welfare. Also HHERD had a greater implied stocking density than LHERD. This increase of the cows’ population may adversely affect the environment. The presented model provides some of the basic information required to explore some of the trade-offs between farm profit, animal welfare and the environment.Livestock Production/Industries, Beef cow, economics, dynamic programming, animal welfare,

ANIMAL WELFARE AND ECONOMIC OPTIMISATION OF FARROWING SYSTEMS

Livestock Production/Industries, alternative housing systems, animal welfare, economic optimisation, farrowing systems, pig,

A framework for estimating society’s economic welfare following the introduction of an animal disease: the case of Johne’s disease

Animal diseases are global issues affecting the productivity and financial profitability of affected farms. Johne’s disease is distributed on farms worldwide and is an endemic contagious bacterial infection in ruminants caused by Mycobacterium avium subspecies paratuberculosis. In cattle, the clinical disease manifests itself as chronic enteritis resulting in reduced production, weight loss, and eventually death. Johne’s disease is prevalent in the UK, including Scotland. Direct costs and losses associated with Johne’s disease have been estimated in previous research, confirming an important economic impact of the disease in UK herds. Despite this, the distributional impact of Johne’s disease among milk consumers and producers in Scotland has not been estimated. In this paper, we evaluate the change in society’s economic welfare, namely to dairy producers (i.e. infected and uninfected herds) and milk consumers in Scotland induced by the introduction of Johne’s disease in the national Scottish dairy herd. At the national-level, we conclude that the economic burden falls mainly on producers of infected herds and, to a lesser extent, milk consumers, while producers of uninfected herds benefit from the presence of Johne’s. An infected producer’s loss per cow is approximately two times larger in magnitude than that of an uninfected producer’s gain. Such economic welfare estimates are an important comparison of the relative costs of national herd prevalence and the wider economic welfare implications for both producers and consumers. This is particularly important from a policy, public good, cost sharing, and human health perspective. The economic welfare framework presented in this paper can be applied to other diseases to examine the relative burden of society’s economic welfare of alternative livestock disease scenarios. In addition, the sensitivity analysis evaluates uncertainty in economic welfare given limited data and uncertainty in the national herd prevalence, and other input parameters, associated with Johne’s disease in Scotland. Therefore, until the prevalence of Johne’s is better understood, the full economic cost to Scottish dairy herds remains uncertain but in the meantime the sensitivity analysis evaluates the robustness of economic welfare to such uncertainties

Prioritising support for cost effective rare breed conservation using multi-criteria decision analysis

<p>Farm Animal Genetic Resources (FAnGR) are threatened by breed homogenisation. Rare breeds may carry important genes that allow breeders to respond to global production challenges including climate change and emerging disease risk. Yet, exploration of approaches to improve cost-effectiveness of investments in farm animal genetic diversity has been limited. We employ multi-criteria decision analysis (MCDA) to investigate how rare breed incentive schemes can be rationalised. A performance matrix was used to assess 19 UK cattle native breeds at risk, in terms of diversity, marketability, and endangerment criteria, and an expert workshop was used to assign weights for prioritisation. The workshop participants suggested that criteria pertaining to diversity, marketability and endangerment should be weighted 30, 20, and 50%, respectively. A principal component analysis (PCA) on the criteria suggested that fewer criteria could be used to characterise breed status but that each criteria node contributed effectively in explaining variation in breed scores. Breed scores from the MCDA model were used in a hypothetical exercise to rationalise monetary investments across the case study breeds. The allocation of the hypothetical breed improvement fund (BIF) revealed that the greatest variation in the allocation of incentives occurred when marketability was weighted highest, while least variation occurred when endangerment received the highest weight. We suggest MCDA can support more targeted investments in diversity by considering the multiple factors that may be driving extinction risk in addition to the cultural and diversity attributes that compliment conservation.</p

The EU-Wide Individual Farm Model for Common Agricultural Policy Analysis (IFM-CAP v.1): Economic Impacts of CAP Greening

This report presents the first EU-wide individual farm level model (IFM-CAP) aiming to assess the impacts of CAP towards 2020 on farm economics and environmental effects. The rationale for such a farm-level model is based on the increasing demand for a micro simulation tool capable to model farm-specific policies and to capture farm heterogeneity across the EU in terms of policy representation and impacts. Based on Positive Mathematical Programming, IFM-CAP seeks to improve the quality of policy assessment upon existing aggregate and aggregated farm-group models and to provide assessment of distributional effects over the EU farm population. To guarantee the highest representativeness of the EU agricultural sector, the model is applied to every EU-FADN (Farm Accountancy Data Network) individual farm (83292 farms). The report provides a detailed description of the first IFM-CAP model version (IFM-CAP V.1) in terms of design, mathematical structure, data preparation, modelling livestock activities, allocation of input costs, modelling of the CAP post-2013 and calibration process. The theoretical background, the technical specification and the outputs that can be generated from this model are also briefly presented and discussed. Model capability is illustrated in this study with an analysis of the EU farmers' responses to the greening requirements introduced by the 2013 CAP reform.JRC.D.4-Economics of Agricultur

Financial Vulnerability of Dairy Farms Challenged by Johne's Disease to Changes in Farm Payment Support

Johne's disease is an endemic contagious bacterial infection of ruminants which is prevalent in the United Kingdom and elsewhere. It can lower financial returns on infected farms by reducing farm productivity through output losses and control expenditures. A farm-level analysis of the economics of the disease was conducted taking account of farm variability and different disease prevalence levels. The aim was to assess the financial impacts of a livestock disease on farms and determine their financial vulnerability if farm support payments were to be removed under future policy reforms. A farm-level optimization model, ScotFarm, was used on 50 Scottish dairy farms taken from the Farm Business Survey to determine the impacts of the disease. A counterfactual comparison of five alternative “disease” scenarios with a “no-disease” scenario was carried out to evaluate economic impact of the disease. The extent of a farm's reliance on direct support payments was considered to be an indicator of their financial vulnerability. Under this definition, farms were grouped into three financial vulnerability risk categories; “low risk,” “medium risk,” and “high risk” farms. Results show that farms are estimated to incur a loss of 32% on average of their net profit under a standard disease prevalence level. Farms in the “low risk” and “medium risk” categories were estimated to have a lower financial impact of the disease (22 and 28% reduction on farm net profit, respectively) which, along with their lower reliance on farm direct support payments, indicate they would be more resilient to the disease under future changes in farm payment support. On the contrary, farms in the “high risk” category were estimated to have a reduction of 50% on their farm net profit. A majority of these farms (61%) in the “high risk” category move from being profitable to loss making under the standard disease scenario when farm support payments are removed. Of these, 15% do so because of the impact of the disease. These farms will be more vulnerable if changes were to be made in farm support payments under future agricultural policy reforms

EVALUATING EXTENSIVE SHEEP FARMING SYSTEMS

Data from each of 5 commercial, extensive sheep farms in Cumbria, UK were used as parameters in a linear program (LP) representing labour and grazing management in such farming systems. The LP maximised ewe enterprise gross margin subject to constraints dictated by the labour availability and land types on each farm. Under the assumptions used, labour availability and price restricted ewe numbers well below those observed in practice on 2 farms i.e. land resources were adequate for the farming system practiced. On two other farms stocking levels and hence returns were limited by the availability of forage and hence feed input prices relative to output. On one farm, greater grassland productivity was the key determinant of system performance. It was concluded that a holistic systems approach was needed to properly evaluate these farming systems in terms of their potential contribution to animal welfare, land use, profit and hence their sustainabilityLivestock Production/Industries, Extensive, Sheep, Economics, LP,

Impacts of labour on interactions between economics and animal welfare in extensive sheep farms

This study quantified interactions between animal welfare and farm profitability in British extensive sheep farming systems. Qualitative welfare assessment methodology was used to assess welfare from the animal's perspective in 20 commercial extensive sheep farms and to estimate labour demand for welfare, based on the assessed welfare scores using data collected from farm inventories. The estimated labour demand was then used as a coefficient in a linear program based model to establish the gross margin maximising farm management strategy for given farm situations, subject to constraints that reflected current resource limitations including labour supply. Regression analysis showed a significant relationship between the qualitative welfare assessment scores and labour supply on the inventoried farms but there was no significant relationship between current gross margin and assessed welfare scores. However, to meet the labour demand of the best welfare score, a reduction in flock size and in the average maximum farm gross margin was often required. These findings supported the hypothesis that trade-offs between animal welfare and farm profitability are necessary in providing maximum animal welfare via on-farm labour and sustainable British extensive sheep farming systems.Sheep, Labour, Animal Welfare, Linear Programme, Livestock Production/Industries, C6, Q10, Q19, Q57,