What allows a sheep or goat farm to withstand a crisis—and what determines whether it can adapt when conditions fundamentally change? New research from Spain suggests these may be two very different capabilities.
A longitudinal analysis of Spanish small-ruminant farms found that farms generally showed a stronger capacity to withstand economic disruption than to adapt their management or undertake more fundamental transformations. Production efficiency emerged as an important characteristic associated with robustness, while greater land availability per animal and a higher proportion of feed produced on the farm were linked to stronger adaptation.
KEY FINDING
Spanish sheep and goat farms were generally more robust than adaptable or transformable. The results suggest that surviving short-term pressure does not necessarily mean a farm is well positioned to make the changes required for long-term resilience.
Resilience is more than surviving a difficult year
Livestock producers increasingly operate in an environment shaped by volatile input prices, changing markets, climate pressures, labour constraints and uncertainty surrounding agricultural policy.
For small-ruminant systems, these pressures are particularly important. Many sheep and goat farms combine relatively tight economic margins with dependence on land, labour and local resources, while also facing longer-term challenges such as generational renewal.
But resilience does not simply describe whether a farm survives a difficult period.
Researchers increasingly divide farm resilience into three interconnected capacities: robustness, adaptation and transformation.
- Robustness describes the capacity to withstand a challenge while maintaining the farm’s basic functioning.
- Adaptation refers to adjustments in management that allow the farm to respond to changing conditions.
- Transformation involves more fundamental changes to the farm’s structure, activities or objectives.
A farm may therefore be highly capable of absorbing a temporary economic shock while having relatively little capacity to reorganize its production system when circumstances change permanently.
Following Spanish farms over time
The study, published in Small Ruminant Research, used data from the Farm Accountancy Data Network (FADN) covering the period from 2014 to 2022.
Rather than examining Spanish livestock production as a single system, the researchers focused on three representative small-ruminant production systems:
- meat sheep farms in Aragón and Navarra;
- dairy sheep farms in the Basque Country and Navarra; and
- dairy goat farms in Andalusia.
This distinction is important because resilience is highly dependent on production context. A dairy goat operation in Andalusia does not necessarily face the same resource constraints, labour requirements or opportunities for adaptation as an extensive meat sheep farm in Aragón.
The researchers evaluated changes in farm indicators over time and grouped them into measures representing robustness, adaptation and transformation. They then used statistical modeling to investigate which farm characteristics were associated with better performance in each resilience capacity.
THREE DIMENSIONS OF RESILIENCE
A resilient livestock farm must do more than resist a shock. Long-term resilience can also depend on its ability to adjust management when conditions change and, when necessary, transform the production system itself.
Farms were better at resisting than changing
The clearest overall result was the difference between the three resilience capacities.
Across the production systems studied, average robustness remained above 0.6, while average adaptation remained below 0.4. Transformation occurred in fewer than 10% of observations.
In practical terms, the farms appeared considerably better equipped to maintain or recover their economic performance than to make substantial adjustments to management or undertake structural change.
Robustness was not constant, however. Different production systems experienced declines at different points during the study period, reflecting years in which farms struggled more to maintain profitability and recover from economic pressure.
Adaptation, meanwhile, remained comparatively stable and limited, while transformations became somewhat more frequent after 2018.
Production efficiency supported robustness
One of the most consistent relationships involved production efficiency.
Farms producing greater output relative to their production costs were more likely to rank among the stronger performers for robustness.
The relationship makes intuitive economic sense. Efficient farms may have greater room to absorb increases in costs or reductions in returns before profitability becomes severely affected.
Efficiency should therefore be viewed not only as a question of maximizing production, but also as part of a farm’s capacity to withstand uncertainty.
EFFICIENCY AS A BUFFER
Farms that generate more output relative to their production costs may be better positioned to absorb economic pressure while maintaining profitability. In this sense, production efficiency can contribute directly to robustness.
Land availability may create room to adapt
Adaptation was associated with a different set of characteristics.
Farms with more hectares available per livestock unit tended to perform better in terms of adaptation. Greater access to land can provide producers with more options for changing the relationship between herd size, grazing and feed resources as conditions evolve.
This flexibility can be particularly important in small-ruminant production, where pasture availability and land use are closely connected with feeding strategy and stocking density.
The researchers interpreted the finding as evidence that more extensive farms may have greater room to adjust management over time.
Producing feed on the farm was also linked to adaptation
Another particularly relevant finding for animal nutrition was the relationship between adaptation and the proportion of feed produced on the farm.
A higher on-farm feed ratio was associated with stronger adaptation performance across the systems studied.
Feed autonomy can potentially give producers additional options when external conditions change. Farms with access to their own forage or other feed resources may have more flexibility to adjust feeding strategies than farms that depend heavily on purchased inputs.
This does not mean that producing more feed on farm automatically makes an operation resilient. Land quality, climate, yields, storage, labour and economics remain important. However, the findings suggest that access to internal feed resources can form part of the flexibility that allows farms to respond to changing conditions.
FEED AUTONOMY AND FLEXIBILITY
Greater reliance on on-farm feed resources was associated with better adaptation performance. For sheep and goat systems, feed autonomy may therefore represent more than a cost strategy—it may also provide greater flexibility when markets or production conditions change.
Family labour revealed a more complex relationship
Labour also played a role, although the relationship was not necessarily what might be expected.
A higher proportion of family labour was negatively associated with adaptation performance. The authors suggest that farms using more hired labour may have greater flexibility to adjust their workforce as production requirements change.
Family-based farming can provide important continuity, knowledge and economic stability, but it can also make some production factors less flexible. Long-established family farms may prioritize maintaining existing activities rather than changing management in response to shorter-term pressures.
This finding should therefore not be interpreted as evidence that family farming itself reduces resilience. Rather, it highlights the distinction between stability and flexibility: characteristics that support one dimension of resilience may not necessarily strengthen another.
Why is transformation so uncommon?
The study found that fundamental transformation was relatively rare.
This is perhaps unsurprising. Changing farm type, converting between conventional and organic production, beginning on-farm processing or substantially restructuring a livestock business requires capital, knowledge, labour and willingness to accept risk.
For many farms, incremental adaptation is considerably easier than changing the business model itself.
Interestingly, significant relationships for transformation were primarily identified in dairy goat farms. In this system, larger farms, greater family-labour productivity and a higher contribution from rural-development payments were among the characteristics associated with a greater probability of transformation.
Other research highlights the human side of resilience
Economic and structural indicators tell only part of the story.
Complementary research on Spanish small-ruminant farms based on farmer interviews has identified autonomy, functional diversity, knowledge and innovation, and economic and human capital as important attributes supporting resilience.
Other research involving Spanish sheep and goat systems has also highlighted the importance of human capital and demonstrated that the factors supporting resilience can differ substantially between meat sheep, dairy sheep and dairy goat farms.
Taken together, these findings suggest that resilience cannot be reduced to a single characteristic such as farm size, profitability or productivity. It emerges from the interaction between economic performance, resources, management flexibility, knowledge, labour and the capacity to respond to change.
Resilience policies may need to look beyond income support
The findings also raise questions about how agricultural support contributes to long-term resilience.
Income stabilization can help farms withstand difficult periods, strengthening robustness. However, the authors argue that building long-term resilience also requires measures that improve the ability of farms to adapt and transform.
Examples discussed in the research include improving access to land and advice on land management, supporting mixed crop-livestock or multispecies systems, and developing infrastructure such as mobile slaughter facilities that could facilitate direct marketing.
The broader implication is that helping a farm survive the next economic shock is not necessarily the same as preparing it for the structural challenges of the next decade.
What does this mean for sheep and goat producers?
The research does not identify a single model for the “most resilient” small-ruminant farm. Instead, it demonstrates that different characteristics contribute to different dimensions of resilience.
Production efficiency appears particularly relevant for absorbing economic pressure. Land availability and on-farm feed production, meanwhile, may create the flexibility needed to adjust management when conditions change.
But adaptation and transformation remain considerably less developed than robustness across the farms studied.
That distinction may become increasingly important as livestock production faces not only temporary disruptions, but longer-term changes involving climate, labour availability, input markets, agricultural policy and generational renewal.
For the sheep and goat sector, the challenge may therefore be shifting from simply asking “Can this farm withstand the next shock?” toward a more demanding question: “Can it change when the old way of operating is no longer enough?”
References
Prat-Benhamou, A., Bernués, A., Soriano, B., Olaizola, A.M., & Martín-Collado, D. (2026). Assessing resilience of small ruminant farms in Spain: A longitudinal analysis based on FADN. Small Ruminant Research, 255, 107684. https://doi.org/10.1016/j.smallrumres.2025.107684
Lizarralde, J., Mandaluniz, N., Prat-Benhamou, A., et al. (2026). Assessing resilience capacities of the Small Ruminant farms in Spain: A static approach thanks to field interviews. Small Ruminant Research, 256, 107688. https://doi.org/10.1016/j.smallrumres.2025.107688
Prat-Benhamou, A., Bernués, A., Gaspar, P., et al. (2024). How do farm and farmer attributes explain perceived resilience? Agricultural Systems, 219, 104016. https://doi.org/10.1016/j.agsy.2024.104016