CONTEXTThe ruminant livestock sector is under scrutiny for its contribution to greenhouse gas emissions. Less Favoured Areas (LFA) carry a large proportion of Europe's cattle and sheep ruminant population and is also characterised by variable economic and biophysical constraints. OBJECTIVEThis study aims to assess the heterogeneity in carbon emissions, resource usage and financial performance in a sample of mixed LFA livestock farms in Scotland. METHODSIndividual farm account data for 263 LFA cattle and sheep producers were augmented with emissions data over the period 2019–2020. Environmental impacts were estimated for each farm using emissions intensity and carbon productivity. Technical efficiency at the farm level (the rate of output to total inputs) was estimated using non-parametric data envelopment analysis. Financial resilience was measured through returns on assets to meet short-term liquidities. To manage the heterogeneity in these indicators Latent Profile Analysis (LPA) was employed. This allocates farms into separate groups, or profiles, representing different levels of environmental, resource efficiency and financial dimensions. To gain understanding of the drivers on membership of profiles we assess the impact of intensity and enterprise mix using multinomial logistic regression (MLN). RESULTS AND CONCLUSIONSThree profiles were identified within our sample which reflect different levels of performance; i) a best practice profile (23% of farms) have relatively low mean emissions intensities (22.3 kg CO2-eq./kg CW), high carbon productivity (£0.17 GVP/ kg CO2-eq.), high technical efficiencies and strong financial resilience; ii) a low resilience profile (31% of farms) which are the most economically fragile and susceptible to economic shocks, and iii) a high emissions profile (46% of farms) which have the lowest technical efficiencies and also the highest mean emissions intensities (31.9 kg CO2-eq./kg CW) and lowest carbon productivity (£0.10 GVP/ / kg CO2-eq.). The MLN identified that farms within the best practice profile will be more extensive compared to the other profiles. SIGNIFICANCELess Favoured Areas dominate global agricultural systems and they offer a more heterogenous picture compared to more intensive lowland or feedlot cattle systems. Agricultural support payments are changing to reward public goods. Our approach sets realistic thresholds for higher level performance across multiple dimensions that may merit higher payments if an outcomes-based payment scheme were adopted.
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