Sustainability of Mediterranean Organic and Conventional Beef Cattle Farms. Assessment on the basis of previous Technical-economic Typification

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Summary

The livestock sector today has to satisfy the growing demand for animal products while reducing its environmental impact, in face of great climatic and market changes. For this reason, there is a necessity to redesign livestock production systems in order to make them more sustainable and adaptable. Several authors have argued that organic production systems could be a viable option to achieve this goal in drylands. For this reason, and due to the importance of the beef cattle sector in the area under study, the present work describes a comparative assessment of the sustainability of conventional and organic beef cattle farms previously classified into 4 farm typologies, on the basis of technical-economic, structural and managerial aspects. The typologies are the following: (T1) extensive farms, selling at weaning and with low productivity; (T2) extensive farms, with low productivity and high dependence on subsidies; (T3) farms finishing calves, with average stocking rates and high profitability; (T4) irrigated farms with low presence of livestock, and high fixed capital and economic fluxes. To evaluate their sustainability, a methodological adaptation of the MESMIS framework was applied, and it was based on valuing the line of actions and indicators of the three main sustainability dimensions (social, environmental and economic). The results showed that more intensified farms in terms of livestock units/unit of land tend to be more productive and competitive, while showing scarce implementation of sustainable agricultural practices. In this regard, although reliance on agrochemical products and veterinary drugs was not high, it could be reduced even further, which would have a positive impact on environmental and public health. The use of feed additives is proposed as an alternative to veterinary drugs. Moreover, self-reliance / self sufficiency has shown to be one of major importance for farms’ sustainability. Thus, dependence on subsidies, workforce self-sufficiency and the proportion of crop area shaped themselves as the point where most efforts must be made. Regarding overall sustainability, T3 farms (full-cycle farms, with medium-high stocking rate, high productivity, and composed by 2 conventional farms and 4 organic farms), were the most sustainable.

Keywords: Sustainable agriculture, sustainable farming, drylands, adaptability, ruminants.

 

1. Introduction

The livestock sector is established today as a key element in the food system, since it has to meet consumers’ increasing demands for animal products while complying with sustainable production principles (animal welfare, equity, food safety, healthiness, and environmental protection). All this, under a context of Climate Change that will strongly impact some areas, such as drylands; along with increased market competition due to the exports coming from developing countries.

As a consequence, it is necessary to redesign and implement livestock farming systems that take the above-mentioned aspects into account with the objective of making them more sustainable, where adaptability to changes (either from the market –agricultural policies, consumers’ demands, and market competition- or the environment –Climate Change-) is essential.

It is extremely important in low-rainfall areas, since they occupy around 41% of the surface of the Earth (Lal, 2004) and the predicted impacts of Climate Change will be intensified in some of these areas, such as the Mediterranean basin (Dumont et al., 2015). The livestock sector will not escape from scarcity in water and pasture resources (Nardone et al., 2010), which will jeopardise the conservation of valuable ecosystems, ecosystem services, rural economy and population, and cultural heritage (landscapes, food, etc.).

The livestock sector plays a central role in the sustainability of these areas. However, only specific livestock systems (traditional and co-evolved ones) are found to provide positive externalities environmentally and socio-economically (Ripoll-Bosch et al., 2013; Veysset et al., 2015; Escribano et al., 2016). Such farm configurations increase carbon sequestration, soil quality, pastures quality, prevention of the risk of fire, dependence on non-renewable energy and ground pollution (Dumont et al., 2013; Sanderson et al., 2013), and contribute to fix rural population, due to its dependence on the livestock sector.

Among the existing farming systems in Mediterranean countries and others in low-rainfall areas, organic farming has been recognised as not only supportive of the environment, but also sensitive to social issues such as employment, health, migration, etc. (Sharma et al., 2015).

From the environmental point of view, they have shown to provide several benefits such as the prevention of land degradation, and the increase in agro-biodiversity, soil fertility, water retention and resistance to drought (Tuomisto et al., 2012; Halberg et al., 2012). From the socio-economic perspective, organic livestock farms have also been observed to provide certain benefits (reviewed by Escribano et al., 2015b).

However, the externalities of the different production systems cannot be extrapolated due to the fact that their impacts vary greatly depending on the socio-economic and environmental context of the farms. Thus, environmental externalities of farms are more linked to the agro-ecosystem management (conservative agriculture and agro-ecological techniques) than to the belonging to legally defined production systems –such as the organic one- (Escribano, 2016). With regard to socioeconomic ones, the same occurs. Thereby, Lobley et al. (2009) pointed out that simply comparing organic and non-organic farm businesses is too blunt an approach and that other factors such as the type of enterprises found on the farm and the marketing routes adopted by the business must be considered, recognising differences between farming systems, farm types, the configuration of farm businesses towards different marketing strategies and the inclinations of those who operate such businesses.

These arguments are consistent with the fact that not all organic farms are managed in the same way, since regulations on organic farming and certification bodies allow the existence of a great diversity of organic farming systems and interactions with the whole food system, due to the fact that organic rules are just focused on production, without taking into account factors that play important roles in the sustainability of the whole food system, such as farms’ marketing strategies (Escribano, 2016).

Accordingly, the dynamic concept of sustainability (dependant on physical and time scales), makes it not possible to define any production system as sustainable per se. Furthermore, sustainability must be related to the farms located in each area, more than to a regulatory definition. That way, it would be possible to make valuable conclusions that help stakeholders and policy makers in their respective tasks. Nevertheless, the scientific interest over organic farming and its importance in the area under study (MAGRAMA, 2013) justify the study of both organic and conventional beef cattle farms.

In many areas, the relationship among the dimensions of sustainability (institutional, environmental, economic and social) is really strong and marked, though it is starting to weaken due to the deterioration of the agro-ecosystem upon which they are based. The dehesa ecosystem (located in SW Spain) is experiencing a severe multifactorial process of deterioration. In view of this trend and within this context, it is very timely to assess the sustainability of different livestock production systems (organic and conventional) on the basis of lines of action that have been identified as priorities in scientific literature and the political agenda.

Hence, the objectives of the present study were the following: (i) assess the sustainability of organic and conventional beef cattle farms typified on the basis of technical-economic, structural and managerial aspects; (ii) provide specific recommendations to improve the sustainability of extensive livestock systems located in regions with similar geo-climatic conditions (drylands, low-rainfall, Mediterranean), with special focus on future changes and concerns (Climate Change and new market contexts).

 

2. Material and methods

2.1 Area of study

The region that comprises the highest dehesa surface was selected. It corresponds to the region of Extremadura. From around 3.5 million hectares that dehesa occupy, 2.2 Mha are located in Extremadura (CAYMA, 2003).The dehesa is one of the most traditional, famous, ancient and diverse agroforestry systems in Europe. It combines grasslands under a layer of holm oak (Quercus ilex) and cork (Quercus suber), where Iberian pigs, sheep and cattle are reared. Livestock production relies on scarce and unstable rainfall pastures and crops. Poor and shallow soils and dry and hot summers (average temperature in July exceeds 26ºC and the maximum values exceed 40ºC) are characteristic of the region (Espejo and Espejo, 2006). However, the numerous activities carried out in the dehesas (agricultural production, hunting, cork, firewood and bird watching) have reduced commercial risk and lead to low but sufficient profitability.

 

2.2 Selection and description of the sample

This and the rest of the methodological procedure steps are shown in figure 1. They are described in the following paragraphs. The data used in this study were acquired in 2011. They correspond to 63 dehesa beef cattle farms (30 conventional farms and 33 organic farms) selected from data provided by agricultural cooperatives and producer associations. The sample is representative of the situation of the beef cattle sector of the dehesa ecosystem and the selection criteria has been explained more in-depth in the previous work of Escribano et al. (2015a).

 

2.3 Selection of sustainability indicators

In literature, one finds various sustainability lines of action and indicators, selected according to the background of the researchers, to the context of the farms being analysed, and to the focus of the studies (the environmental, social, or economic dimension). As such, indicators were selected following the two steps described below.

 

2.3.1. Bibliographic revision

Firstly, indicators were selected on the basis of scientific literature regarding the sustainability of livestock production systems (Gaspar et al., 2009; Ripoll-Bosch et al., 2012; Lebacq et al., 2013; Escribano et al., 2014a; Escribano et al., 2015a), on the Economic Accounts for Agriculture in the European Community (EAA, 2001; Regulation EC No 138/2004 and subsequent amendments).

 

2.3.2. Selection of the final indicators and lines of action. Ordination of indicators and allocation of relative weights

Aimed at integrating scientific and practical knowledge, values and concerns of different stakeholders, a participatory research methodology was applied. This led to a more effective decision-making process, reducing the risk of bias, and having a greater potential value for stakeholders (policymakers included). It is particularly important in dry-land ecosystems (as dehesas) with their great sensitivity to external pressures and changes, and when results will lead to changes in how the farms are managed (Whitfield and Reed, 2012). Therefore, this approach was used in the present work/research study/project. Once the indicators and lines of action (thematic aspects of interest) were selected, indicators were grouped within such lines of action.

Later, all participants allocated relative weights for each indicator within each line of action. The latter is an important step, since each indicator has different relative importance to each stakeholder, depending on their particular interests and views (Whitfield and Reed, 2012). As a result, each participant assigned weights to each indicator. The sum of the relative weights of each indicator of the same line of action was equal to 100%. The final relative weight of each indicator was calculated as the mean value of the relative weights given by all the participants. However, each line of action was given the same weight.

It was decided that all lines of actions had the same weight. A description of the line of actions used is given in the following paragraphs:

Productivity & Competitiveness: capacity to provide the required level of goods and services. It comprises their strength to fight in the market against competitors. Human well-being & Sustainable rural development: this is the system's capacity to distribute both intra-and intergenerational richness. In addition, it takes into account the capacity of the system to promote sustainable (durable and respectful) development in the rural areas, which is a key topic worldwide.

Agro-ecosystem & Herd management and Stability: this indicator is related to stability of the farms from the environmental and social points of view. It is mainly based on the specific agricultural practices (technical management) carried out on the farm, as they directly influence conservation and then provision of social services. This also influences the social stability of the farm, which has also been evaluated by means of the future plans of the farmers.

Self-reliance / self-sufficiency: This is the system's capacity to regulate and control its interactions with the outside, as well as to distribute benefits, resources and costs fairly. It also relates to the quality of life, equal opportunity and social interaction.

Business flexibility & Economic risk: ability to find new levels of balance or to continue offering benefits to long-term changes in the environment. This indicator is related to the resilience of the economic holding and its capacity to adapt to new market scenarios.

 

2.4. Questionnaire design and data collection

Finally, the questionnaire was designed on the basis of the indicators selected. Information collected related to livestock management, land use, herd size, breeds, facilities, economic flows, environmental management, and sociological aspects. The questionnaire included the indicators that were considered to have the greatest potential to discriminate between the different types of exploitation, based on previous studies and on scientific literature. Data were collected by surveys to the person in charge of the management of the farms. Direct observation at the farm level was also used as a way to obtain the data.

 

2.5. Assessing sustainability

The evaluation of the sustainability of the beef cattle farms was carried out by means of an adaptation of the MESMIS framework (Management System Evaluation Framework incorporating Sustainability Indicators) proposed by Masera et al. (1999), since it has demonstrated to be a strong method for the evaluation of livestock production systems’ sustainability.

The MESMIS operative structure is a six-step cycle. The first three steps characterise the systems, identify critical points, and select the line of actions to be used to define specific indicators for the environmental, social, and economic dimensions of sustainability. The last three steps integrate those indicators (via qualitative, quantitative, or multiple-criterion techniques) into a specific measure of the system's sustainability.

The adaptation made for the present study allowed to integrate the following topics and views, as well as selecting a sample indicative of the sector of the area under study (see a more detailed explanation in Escribano et al., 2015a):

  • The characteristics of the agro-ecosystems: farms of all dehesa types (according to the size and tree-covered area density) were selected.
  • Geographical scope: farms from the entire region under study were selected.
  • Production system and business structure: allowing us to embrace the diversity of production systems in the dehesa and agroforestry systems. This point referred to the integration (or not) of different livestock species and other agricultural/economic activities (multipurpose). The beef cattle sector had to be present.
  • Livestock production systems: both conventional and organic farms were selected.

 

2.5.1. Establishment of the criteria of calculation and of the optimal values

In order to evaluate the proximity of the farms to the maximum value of sustainability, it was necessary to select the desirable values (‘optimal values’) for an each indicator. These values were established by the research team members, following a criterion that allowed integrating their experience and scientific literature (Gaspar et al., 2009; Ripoll-Bosch et al., 2012; Escribano et al., 2014a; Escribano et al., 2015a and b). Nevertheless, the list of indicators, criteria, and optima was presented to the participants of the focus group in order to attain the broadest possible consensus. The selected indicators, their weights, the line of actions, and their calculation criteria are presented in Table 1. Their optimal values are shown in tables 2-5, such that it can be observed along with the results of the sustainability indicators.

 

2.5.2. Calculation of the indicators, the sustainability indices (sustainability scores of the farms’ groups) and overall sustainability

Firstly, the indicators selected were calculated. The definitions, units and formulas needed for the calculation of the indicators are given in table 1. Secondly, the values of the indicators were transformed into sustainability indices. These indices have been expressed as percentages, ranging from 0% (minimum sustainability) to 100% (minimum sustainability). Such conversion was made on the basis of the AMOEBA approach (Ten Brink et al., 1991). To do this, the following criteria and formula were followed:

  • o Indicators with optimal values equal to the minimum of the sample or calculated as percentiles, means, or recommended values; and the value of the indicator is greater than its optimal value:

Formula: Sustainability index (%) = (optimal value / indicator value) x 100

  • o Indicators with optimal values equal to the maximum of the sample or calculated as percentiles, means, or recommended values; and the value of the indicator is lesser than its optimal value:

Formula: Sustainability index (%) = (indicator value / optimal value) x 100

In order to clarify how this approach is used, an example is presented:

 

It is important to note that there is not always a relationship between the values of the indicators and the indices due to the indicator–index transformation. Thus, indicators whose values are above their optimal values can reduce their sustainability scores, since such values reduce the farm’s sustainability. For example, for the total stocking rate, a value above the optimal implies overgrazing, whilst a value under the optimal value will cause shrub invasion and other processes that would lead to a reduction in sustainability. For other indicators, such as wooded UAA per total UAA, values above the optimal value do not lead to an increase in farms’ sustainability scores (since the highest possible score is 100%) nor a reduction of their scores.

 

2.6. Analysis of the information

A single factor one-way analysis of variance (ANOVA) was applied in order to detect differences between farm typologies with regard to sustainability indices (scores). These analyses were carried out with the SPSS 2011, version 20.0.

More detailed information regarding the process of farm typification is given in the study of Escribano et al. (2016). Farm typologies whose sustainability was assessed are described below:

  • Typology 1: extensive farms of low productivity, selling calves at weaning age. This typology comprises 25 farms (44.5% of the sample), of which 15 are conventional and 10 are organic.
  • Typology 2: extensive farms, highly dependent on subsidies. This group is integrated by 28 farms (9.52% of the sample), of which 10 belong to the conventional system, and 18 to the organic one.
  • Typology 3: full-cycle farms (fatten their calves), medium-high stocking rate, high productivity. 6 farms composed this group, of which 2 are conventional and 4 are organic.
  • Typology 4: intensive farms, selling calves after weaning, high presence of crops and high economic results. It comprises 3 conventional farms and 1 organic farm.

 

3. Results and discussion

The results for the sustainability indicators for the four farm typologies are presented in tables 2 and 3. Table 2 shows the mean values and the standard deviation of the quantitative indicators. In table 3, the results for the qualitative indicators can be observed. Finally, table 4 presents the calculated sustainability indices (scores).

 

 

 

 

In the following paragraphs, the most relevant findings (table 4) of the farm typologies with regard to sustainability indices and line of actions are described.

 

3.1. Productivity & Competitiveness

This line of action is pivotal due to two main reasons. Firstly, increased productivity is needed to fulfil the predicted consumers’ demands. Moreover, the low profitability rates of these farms (table 2) and the Earth’s finite resources require efficiency (sustainable productivity), whether it be per land, animal, worker, etc. Also, animal productivity reduces subsidy dependence (Ripoll-Bosch et al., 2013), which is a key point to improve, as will be exposed later. Secondly, the beef cattle farms’ competitiveness in this area is low, owing to their low productivity, purchasing power, market orientation, and their high dependency on subsidies (Escribano et al., 2014b). Consequently, it is necessary to evaluate the aspects undermining their productivity and competitiveness, and provide recommendations to overcome these intrinsic barriers; especially when one takes into account the context of liberalisation of the market and the entrance of beef coming from developing countries, whose production costs and prices are lower than those of European beef.

It was observed that T3 obtained the highest scores for livestock productivity (95.99%), showing differences (p<0.05) with T1. Similarly, it was the typology showing the highest results for workforce productivity, while T2 scored the lowest (p<0.05). Per land, the least producing typology was T1, showing great differences with the rest of them (p<0.000), especially with T3 (98.55%) and T4 (100%). This pattern was also observed for the indicators Net value added and Livestock sales. Overall, T3 farms tended to be the most productive and competitive -80.34%-, followed by T4 -72.44%-, and finally T2 and T1 (these two showed similar results: -64.61% and 63.73%, respectively).

As one can understand from the typologies’ main characteristics, these results are greatly influenced by the total stocking rate, which is in line with the statements of many authors (Gaspar et al., 2007; Perea et al., 2014) regarding the modulating role of the stocking rate on economic and productivity indicators.

 

3.2. Human well-being & Sustainable rural development

Rural population retention is a great concern in many countries and regions due to the negative consequences of depopulation (loss of traditional and agricultural culture and degradation of agro-ecosystems). This interest is reflected in the greater amount of resources and measures aimed at improving the environment and quality of life in rural areas (Escribano et al., 2015b). Attraction and establishment of population in rural areas is closely linked to well-being, which in turn is related to both workforce opportunities and the perceived characteristics of the job (i.e. stability and satisfaction).

In this sense, it is noteworthy to mention that T3 and T4 created jobs of higher stability (differences with T1 -p<0.01-; T3 and T4 scoring 50% vs. 14.29% in T2 and 0% in T1), and made a greater contribution to rural employment (creation of jobs, differences with T1 -p<0.001-; T4=100%, T3=77.35%, T2=68.77% and T1=45.77%) and the creation of external jobs (differences with T1 –p<0.01-; T4=68.55% vs. T1=17.45%).

As a result of the above-mentioned results, T4 scored the highest for this line of action (75.18%), showing differences (p<0.001) with T2 (56.38%) and T1 (47.23%).

 

3.3. Agro-ecosystem & Herd management and Stability

Agro-ecosystems such as dehesa are sensitive and their conservation is linked to specific production systems and agricultural practices. In fact, the observed substantial modifications of land use have led to reductions in their sustainability (Gaspar et al., 2009), which poses a need to assess their consequences in terms of social and environmental impacts, as well as their implications for Climate Change (Toro-Mújica et al., 2015) before implementing them. In this sense, the integrated study of the crops, soil and livestock management is a key aspect.

Regarding livestock, these ecosystems require an adequate integration thereof. In this sense, stocking rates are pivotal. In grassland systems, the management of livestock grazing intensities needs to be optimised to reduce negative externalities of overgrazing and undergrazing. According to authors (Delgado et al., 2013; Jing et al., 2014), high stocking rates lead to soil compaction, surface sealing, decrease of standing biomass, and potential increases in erosive processes that can exacerbate the loss of soil organic carbon by wind and water erosion and reduce the production of biomass; which is important since the increase in the demand of animal products will affect grasslands in arid and semiarid regions more intensely (Follett & Schuman 2005). On the contrary, overly low stocking rates lead to impoverishment of soil and pasture quality, and increased risk of fire. However, proper grazing management not only leads to benefits, but even restores degraded Mediterranean rangelands (Papanastasis et al., 2015). Despite these findings, some authors (Plieninger et al. 2003) have argued that the lack of regeneration in dehesas is an inherent feature of grazed dehesas.

From the dehesa farms analysed, T4 was clearly the most intensified typology (total stocking rate scores as low as 12.45%), showing great differences (p<0.000) with the rest of typologies, whose scores ranged from 62.86 to 74.02% (for T3 and T1, respectively).

With regard to soil and crop management, soil carbon (C) in dryland areas is of crucial importance to maintain soil quality and productivity, and to provide ecosystem and social services. In order to maintain and/or increase its storage, agro-ecosystem and particularly soil management is essential and cannot be despised, since inadequate management led to several land degradation processes such as soil erosion, reduction in crop productivity, lower soil water holding capacity, declines in soil biodiversity, desertification, and hunger and poverty in developing countries (Plaza-Bonilla et al., 2015). Fortunately, there is room for improvement, as dryland soils and agroforestry systems have a great potential to sequester carbon (Cook & Ma, 2014). In this sense, some agricultural practices (i.e. avoiding the removal of crop residues, no-tillage, growing cover crops, crop rotations, cover crops, crop residue retention) imply conversation of soil organic carbon in drylands, reductions in soil erosion, higher humus content, agro-biodiversity conservation, weed seed predation (Plaza-Bonilla et al., 2015) and other ecosystem services that increase the agro-ecosystems’ adaptability to Climate Change. Moreover, from the economic side, recycling of locally available resources may allow reducing production costs up to 60% as compared to conventional chemical farming (De Sharma et al., 2015).

Additionally, the presence of wooded area and its integration with grasslands, crops and livestock provide several benefits. From the Climate Change adaptation standpoint in the Mediterranean basin and other semi-arid agro-ecosystems, diverse agroforestry systems (with integration of grasslands, tress, crops and livestock) have proven to be more stable and resilient to natural hazards (degradation, drought, floods, reduced resources etc.) (Nair et al., 2009; Smith et al., 2012; Segnalini et al., 2013), as well as reducing the toxic effect of veterinary drugs, pesticides and fertilisers (Sinclair et al., 2000) and minimising external dependence (Sanderson et al., 2013; Smith et al., 2013), which is key for these livestock production systems (Ripoll-Bosch et al., 2013; Escribano et al., 2016 –submitted to Livestock Science-).

In the farms analysed, the implementation of the mentioned practices was really low and no differences were found among farm typologies. However, the higher presence of wooded area in T3 led to a higher carbon sequestration (p<0.035; 95.07%).

Pesticides and inorganic fertilisers are toxic and pollutant. Despite being used in low degree (they were not used on organic farms), they can and should be reduced even more, as the climatic conditions (dry) and the purpose of the crops (for direct feeding by the cattle) do not justify their use. Agricultural practices such as intercropping and/or biological control allow reducing the incidence of crop pests and hence pesticide usage. De Sharma et al. (2015) claimed that in low-rainfall areas, the use of synthetic inputs is even risky and uneconomic in most of the years. Even negative results have been observed during below average rainfall years. In such a scenario, use of organic manure for sustainable production is an effective alternative in this set of conditions (De Sharma et al., 2015), as worldwide 90 million tons of mineral oil or natural gas are processed to get nitrogenous fertilisers every year. This generates 250 million tons of CO emission. Pardo et al. (2015) stated that the establishment of sustainable soil waste management practices (conventional solid storage, turned composting, forced aerated composting, covering, compaction, addition/substitution of bulking agents and the use of additives) implies minimising their environmental losses associated with climate change (greenhouse gases: GHGs) and ecosystems acidification (ammonia: NH3). The authors finally concluded that more holistic and integrated approaches are therefore required to develop more sustainable solid waste management systems.

Overall, the farms studied scarcely implemented the agricultural practices mentioned. T4 showed the lowest score for this line of action (T4=33.84%), showing important differences in comparison with the rest of typologies (either statistical differences -with T2 and T3- or numerical –with T1-).

 

3.4. Self-reliance/Self-sufficiency

Because of dehesa rangeland systems' low profitability in the absence of subsidies and the context of constantly rising agricultural input prices, self-reliance and self-sufficiency have become two of the principal objectives and concerns of the managers of these farms. Thus, Ripoll-Bosch et al. (2013) found that in Mediterranean and pasture-based sheep farms, self-sufficiency (especially in relation to feed) enhances the economic performance (per labour unit) of the farms. In line with these findings, Veysset et al. (2015) found that, after 23 years of study (1990-2012), French beef cattle farms have expanded in size, but their efficiency has decreased. Moreover, income per worker has been held stable thanks to the aids and subsidies; and the gains made in efficiency have been positively correlated to feed sufficiency, which is in turn correlated to farm size and herd size. These results show the importance of self-sufficiency for extensive ruminants’ farms, where the reductions of feed purchases, the reliance on subsidies and labour are key aspects for them. Due to this, and according to literature, such topics have been converted into sustainability indicators.

With regard to the farms analysed, T2 showed to be most dependent on subsidies (p<0.000), while T1 were numerically more self-sufficient in this sense. With regard to workforce, T4 showed the lowest scores for workforce self-sufficiency (p<0.05; 47.20%), which means that the proportion of external workers was higher. In the line of reducing cost and making good use of the farms’ internal resources, the proportion of crop area is worthy of study. In this sense, T4 showed the highest scores for this indicator, since, as was previously mentioned, this typology grouped intensive farms with a high presence of crops. The rest of typologies showed less than half this score, as they are more indicative of the typical livestock dehesa farm. Moreover, the combination of cereal and legumes (typical in the farms studied) has benefits due to the fact that legumes help sequestering soil nitrogen and reduce farms’ dependence on external protein, which is a concern in Europe.

The marketing strategies followed have shown to markedly influence the agri-food chain sustainability, due to their effects on the environment -pollution linked to transport- and local economy –higher incomes coming from short marketing channels- (Escribano, 2016). Moreover, it has been observed that organic farms are sometimes related to such short marketing channels, for which accessibility (quality of the paths) is important. What’s more, recently weaned calves’ price is low, and low path quality reduces farmers’ bargaining power. Therefore, accessibility also influences this point. Consequently, this aspect was evaluated, and T1 showed to have the best paths (p<0.05; T1=92% vs. T2=71.43%).

Regarding expenditures, differences were found with regard to veterinary services and drugs; being T1 farms those less dependent on them (77.52%). This is explained by their higher degree of extensification (lower stocking rates) and the absence of fattening period in the farms, which reduced these expenses per land (as observed in table 4) and per animal (data not shown in the present study). Despite this indicator being grouped within the self-reliance/self-sufficiency line of action, it is timely to comment that veterinary medicine usage can have negative consequences for both environmental (soil flora and fauna) and human health (resistance to antibiotics). Although they are sometimes needed to maintain adequate animal health and welfare, the reliance on these products is low in dry ecosystems with extensive production systems (as observed). However, it is possible to reduce their use even more, which should be done due to their negative effects on both the environment and human health. Management measures such as multi-paddock systems, fence plots and short grazing periods allow reducing the amount of veterinary drugs used. Also, feed additives (Jouany & Morgavi, 2007) and biological control (Cortiñas et al., 2015) are useful to maintain animal health reducing the use of veterinary medicines.

Finally, other expenditures (another intermediate consumption indicator) were measured, for which again T1 farms obtained the highest scores with regard to the rest of typologies (p<0.000; 77.52%). Overall, none of the typologies studied showed to be statistically different, although T3 was below average in a higher degree than the rest of them.

 

3.5. Business flexibility & Economic risk

The aforementioned fast market changes require business to be flexible to adapt to new scenarios at a low economic risk. In this sense, the reliance on only one source of income is negative to achieve such capabilities. Therefore, diversifying farms economic activities is a good business strategy for enhancing them (Ripoll-Bosch et al., 2013; Escribano et al., 2015a).

In this sense, T3 farms showed to be less dependent on the incomes coming from livestock, which was related to the following facts: (i) they were full-cycle farms (they fattened their calves, which means higher calf selling price), showing medium-high stocking rate, and high productivity; (ii) they were not very dependent on subsidies; (iii) some of the farmers received income from different sources (not only from the farm; they also had other jobs).

In general terms, differences between typologies with regard to this line of action were not clear (not significant).

 

3.6. Overall sustainability

Regarding overall sustainability, T3 (full-cycle farms, with medium-high stocking rate, high productivity, and composed by 2 conventional farms and 4 organic farms), were the most sustainable.

 

5. Conclusions

The sustainability assessment of organic and conventional beef cattle farms previously typified on the basis of technical-economic, structural and managerial aspects, shed interesting results that complement those of the more traditional comparative evaluations (organic vs. conventional).

In general terms, it has been observed that the total stocking rate greatly modulates farms’ relationships with both the environmental and economic dimensions of sustainability. Thus, more intensified farms in terms of livestock units/unit of land tend to be more productive and competitive, while showing scarce implementation of sustainable agricultural practices (agro-ecosystem & herd management and stability line of action). In this regard, although reliance on agrochemical products and veterinary drugs was not high, the productive orientation of the crops (for direct animal feeding) and the low presence of infectious diseases in both crops and cattle, would allow to reduce their use, which would have a positive impact on environmental and public health. The use of feed additives is proposed as an alternative to veterinary drugs.

Veterinary services and drugs, from the Self-reliance / self-sufficiency point of view, was also of interest. This line of action has shown to be one of major importance for farms’ sustainability, and allowed authors to find differences among typologies. Dependence on subsidies, workforce self-sufficiency and the proportion of crop area shaped themselves as the point where most efforts must be made.

Regarding overall sustainability, T3 (full-cycle farms, with medium-high stocking rate, high productivity, and composed by 2 conventional farms and 4 organic farms), were the most sustainable.

 

Acknowledgements

This research was funded by Project INIA-RTA2009-00122-C03-03 of the Spanish Ministry of Economy and Competitiveness. Thanks are due to the farm holders and managers, veterinarians and agronomists, and academic experts who contributed to this study. The first author also acknowledges the financial support of the ‘Fundación Fernando Valhondo Calaff’.

 

References

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