6. Methods to evaluate sustainability in farming systems

Also for agriculture and livestock systems, different indicators have been developed (Table 2). Some indicator-based farm monitoring tools are visual integration tools, aggregating scores of a set of sustainability indicators into radar graphs [66] or bar graphs [129]; others are numerical

> integration tools, aggregating values into a single composite index [83]. Clark and Dickson [130] identified saliency, credibility, and legitimacy as three characteristics that determine the effectiveness and success of an assessment tool. The relevance or value of an assessment tool is the use in decision-making. Credibility is authoritativeness of the information and conclusion of the tool. Finally, legitimacy relates to the perceived fairness and openness of the assessment

> Table 2. Methods for evaluate sustainability in farming using composite indicators of agricultural sustainability (CIAS).

of the various criteria

Method Description Reference Examples

environmental

social aspects

safety

This is based on the goods and services provided by agricultural ecosystems, resulting in the primary level of the hierarchy, the principles that are correlated with the three dimensions of sustainability: economic, social, and

It allows to monitor farm progress towards integrated sustainability, taking into account economic, ecological, and

Nine indicators integrated in a global index: Nutritional management, Sustainable pasture management, Soil fertility and contamination, Weed and pest control, Marketing and management, Disease prevention, Breeds and reproduction, Animal welfare, and Food

Take into consideration the land use, geomorphology, and the five factors of sustainability: productivity, security, protection, economic viability, and social acceptability. Mathematical formula expressing sustainability index as a result [38, 124] Belgian farms of

http://dx.doi.org/10.5772/intechopen.79220

Methodologies for Assessing Sustainability in Farming Systems

[124]

[125] Flemish dairy farms [126]

[41] Dairy Goat in

[128] Agriculture in

Dairy, Poultry, Beef and Crop production 43

Southern Spain [41] Dairy systems in Mexico [127]

Northern Sinai [128]

Hardi and Zdan [131] described the "Bellagio Principles" as guidelines for practical assessment of progress towards sustainable development. The assessment should reflect a view of the linkages between the social, environmental, and economic aspects. Essential elements like equity and disparity, economic development, and ecological conditions should be considered. The process of developing the assessment tool should be open, with an effective communication and a broad participation; it should be a continuous, iterative, and adaptive process that provides ongoing support in the decision-making process. An effective model expresses its credibility with the potential users' confidence and the information derived from it. When occur the translation of the experience of model validation to indicator validation, it is important to consider two aspects: an evaluation of the indicator's accuracy and an evaluation of its

Nevertheless, a conceptualization of agricultural sustainability presents problems with regard to its operational concretization. First, sustainability requires analyzing the future production

process to political constituencies.

SAFE (Sustainability Assessment of Farming and the Environment

MOTIFS (Monitoring Tool for Integrated

OLPI (Organic Livestock Proximity

SASM (Sustainable agricultural spatial

Framework)

Index)

model)

Farm Sustainability)

credibility [126].



Rockstrom et al. [113] have introduced the concept of planetary boundaries. It is based on the knowledge that the Earth's subsystems react in a nonlinear way and often are particularly sensitive around the threshold levels of variables such as CO2 concentration. The authors identified nine processes and thresholds associated to an unacceptable environmental change: climate change, rate of biodiversity loss (terrestrial and marine), interference with the nitrogen and phosphorus cycles, stratospheric ozone depletion, ocean acidification, global freshwater

The degree of complexity with which each indicator is obtained, for example through field measurements, mathematical models, and simulation models, also presents drawbacks in the comparison between systems evaluated by different methodologies. Many of the mentioned indicators lack the capacity to predict the state and the variation of the human system with the natural system, having to be looked at together with other indicators to obtain those proper-

Also for agriculture and livestock systems, different indicators have been developed (Table 2). Some indicator-based farm monitoring tools are visual integration tools, aggregating scores of a set of sustainability indicators into radar graphs [66] or bar graphs [129]; others are numerical

> complex problems or generate strategies. It was adapted in agriculture to consult experts and to build and select the

The method does the characterization of the systems, the identification of critical points, and the selection of specific indicators for the environmental, social,

sustainability. The information obtained by means of the indicators is integrated through mixed (qualitative and quantitative) techniques and multicriteria

It assesses whole-farm sustainability with agri-ecological (18 indicators), socioterritorial (18 indicators), and economic (6

This tool is also designed to be used with all types of production and evaluates three aspects of sustainability with a set of 12 indicators. Each indicator includes a state measure and a driving-force

and economic dimensions of

[48, 115] Dairy farm

[62, 116] Extensive livestock

[119] Small ruminants in Liban [120] Sheep farming systems in Morocco

[121]

[79, 122] Dairy farms in China [79]

> India [47] Armenian dairy farms and agriculture

[123]

Tea farms in Southern

sustainability in Quebec [59]

farming in Spain [117] Low input maize systems in Central México [118]

Method Description Reference Examples

use, change in land use, chemical pollution, and atmospheric aerosol loading.

6. Methods to evaluate sustainability in farming systems

Delphi This technique is normally used to solve

MESMIS (Marco para la Evaluación de Sistemas de Manejo incorporando Indicadores de Sustentabilidad; in English: Management Systems Assessment Framework Incorporating

42 Sustainability Assessment and Reporting

Sustainability Indicators)

Evaluation)

IDEA (Indicauters de Durabilité des Exploitations Agricoles; in English: Agricultural Sustainability Indicators)

RISE (Response-Inducing Sustainability

indicators

analysis

measure

indicators) scales

ties, complicating the understanding of the results [114].

Table 2. Methods for evaluate sustainability in farming using composite indicators of agricultural sustainability (CIAS).

integration tools, aggregating values into a single composite index [83]. Clark and Dickson [130] identified saliency, credibility, and legitimacy as three characteristics that determine the effectiveness and success of an assessment tool. The relevance or value of an assessment tool is the use in decision-making. Credibility is authoritativeness of the information and conclusion of the tool. Finally, legitimacy relates to the perceived fairness and openness of the assessment process to political constituencies.

Hardi and Zdan [131] described the "Bellagio Principles" as guidelines for practical assessment of progress towards sustainable development. The assessment should reflect a view of the linkages between the social, environmental, and economic aspects. Essential elements like equity and disparity, economic development, and ecological conditions should be considered. The process of developing the assessment tool should be open, with an effective communication and a broad participation; it should be a continuous, iterative, and adaptive process that provides ongoing support in the decision-making process. An effective model expresses its credibility with the potential users' confidence and the information derived from it. When occur the translation of the experience of model validation to indicator validation, it is important to consider two aspects: an evaluation of the indicator's accuracy and an evaluation of its credibility [126].

Nevertheless, a conceptualization of agricultural sustainability presents problems with regard to its operational concretization. First, sustainability requires analyzing the future production of goods and services by agriculture, a requirement that need to be observed on a reasonable time horizon. Secondly, it is difficult to identify what specific demands agriculture needs to satisfy in order to be sustainable. The greatest difficulty involves interpreting the combination of indicators required for such analyses. Applying various methods of aggregation, the combinations of multidimensional indicators into indices or composite indicators were the contributions of van Calker et al. [132], Hajkowicz [133], and Qiu et al. [134], among others. Composite indicators are an opportunity to identify which aspects of agricultural sustainability are relevant in practice and these are called CIAS (composite indicators of agricultural sustainability) (Table 2).

• Sustainability evaluations are only valid for: a specific management system in a given geographic location; a previously circumscribed spatial scale; and a previously deter-

Methodologies for Assessing Sustainability in Farming Systems

http://dx.doi.org/10.5772/intechopen.79220

45

• The evaluation of sustainability is a participatory process requiring an evaluation team with an interdisciplinary perspective. The team should include external evaluators and internal participants (farmers, technicians, community representatives, and others

• Sustainability can be seen through the comparison of two or more systems. The compar-

The IDEA method is used widely in Europe and assesses a farm sustainability with agriecological (18 indicators), socio-territorial (18 indicators), and economic (6 indicators) scales

Response-Inducing Sustainability Evaluation (RISE) is an indicator-based sustainability assessment tool developed by Häni et al. [79]. Its aim is to provide a holistic evaluation of sustainability at the farm level and support the dissemination of sustainable practices. RISE has been applied in over 2500 farms in 56 countries [140]. RISE 2.0 assesses the sustainability performance of a farm for 10 themes (soil use, animal husbandry, nutrient flows, water use, energy and climate, biodiversity, working conditions, quality of life, economic viability, and farm management) and 51 subthemes. The sustainability performance of each subtheme is based on an aggregation of various indicators. These indicators are normalized for each subtheme and can include comparisons between farm and reference data. The score at the theme level is based on the average of the scores of the 4–7 subthemes included in each theme. Scores on

A hierarchical framework based on the goods and services provided by agricultural ecosystems is the base of the SAFE method (Sustainability Assessment of Farming and the Environment Framework), resulting in the hierarchy, the principles that are correlated with the three dimen-

The Monitoring Tool for Integrated Farm Sustainability (MOTIFS) allows monitoring farm progress towards integrated sustainability, taking into account economic, ecological, and social aspects [125]. This tool offers a visual aggregation of indicator scores into an adapted radar graph, defining to rescale indicator values into scores between 0 (indicating a worst-case situation) and 100 (indicating assumed maximum sustainability). This allows for a mutual

MOTIFS is a sustainability monitoring and management tool, and it allows positioning the strong and weak aspects of a farm; hence it can be used to perform a SWOT analysis (strengths, weakness, opportunities, and threats). It has major assets that could be incorporated in any indicator-based system. It can provide information to farmers for helping them to take action and make decisions. Also, it can guide through the process of assembling and understanding

theme and subtheme level range from 0 to 100 and are visualized in a polygon.

sions: economic, social, and environmental [38].

from information and data [126].

comparison of the indicators for different sustainability themes.

ison can be made cross-sectionally or longitudinally.

mined time period.

involved).

[139].

In the context of multicriteria decision-making, most applications require criteria to be weighted according to importance [135]. The literature shows a plethora of techniques available to build sustainability indices. Some guidance regarding the construction of composite indicators consider a selection of relevant indicators based on strict quality criteria and accurate data gathering to calculate empirical values of these indicators. Before any aggregation, transforming base indicators into dimensional variables (normalization) is required. For this purpose, the use of multiple attribute utility theory and reference values is suggested [23, 93]. According to the importance for each dimension/indicator, the composite indicator had the assignment of weighting. Although there exist a wide variety of functional forms that permit indicators to be aggregated, the use of indices should be done with caution in all cases. All such attempts must be regarded as partial representations of a complex reality. Individual treatment of different agricultural systems allows introducing methodological differences such as the choice of indicators for the evaluation of the empirical sustainability of each case study and the individual treatment of the results [23].

The Delphi technique was used to consult experts or advisers (i.e., researchers in different areas of expertise, farmers, and stakeholders from different backgrounds) to build and select the indicators. Indicators were selected and developed through a series of consecutive steps using a combination of bottom-up and top-down approaches. According to King et al. [48], combining both approaches is necessary and provides good results. This technique is normally used to solve complex problems or generate strategies [136]. The main features of the technique are its anonymity, to reduce the influence of "super-experts," and its contribution to the objectivity of the results [137, 138].

The MESMIS (for its acronym in Spanish—Marco para la Evaluación de Sistemas de Manejo de recursos naturales incorporando Indicadores de Sustentabilidad) has an operative structure: Characterization of the systems, identification of critical points, and the selection of specific indicators for the environmental, social, and economic dimensions of sustainability. These information are integrated through mixed (qualitative and quantitative) techniques and multicriteria analysis to obtain a value judgment about the resource management systems and to provide suggestions and insights aimed at improving the socio-environmental profile [62]. The framework is based on the following premises:

• Sustainability is defined by attributes of NRMS: productivity, stability, reliability, resilience, adaptability, equity, and self-reliance.

• Sustainability evaluations are only valid for: a specific management system in a given geographic location; a previously circumscribed spatial scale; and a previously determined time period.

of goods and services by agriculture, a requirement that need to be observed on a reasonable time horizon. Secondly, it is difficult to identify what specific demands agriculture needs to satisfy in order to be sustainable. The greatest difficulty involves interpreting the combination of indicators required for such analyses. Applying various methods of aggregation, the combinations of multidimensional indicators into indices or composite indicators were the contributions of van Calker et al. [132], Hajkowicz [133], and Qiu et al. [134], among others. Composite indicators are an opportunity to identify which aspects of agricultural sustainability are relevant in practice and these are called CIAS (composite indicators of agricultural

In the context of multicriteria decision-making, most applications require criteria to be weighted according to importance [135]. The literature shows a plethora of techniques available to build sustainability indices. Some guidance regarding the construction of composite indicators consider a selection of relevant indicators based on strict quality criteria and accurate data gathering to calculate empirical values of these indicators. Before any aggregation, transforming base indicators into dimensional variables (normalization) is required. For this purpose, the use of multiple attribute utility theory and reference values is suggested [23, 93]. According to the importance for each dimension/indicator, the composite indicator had the assignment of weighting. Although there exist a wide variety of functional forms that permit indicators to be aggregated, the use of indices should be done with caution in all cases. All such attempts must be regarded as partial representations of a complex reality. Individual treatment of different agricultural systems allows introducing methodological differences such as the choice of indicators for the evaluation of the empirical sustainability of each case study

The Delphi technique was used to consult experts or advisers (i.e., researchers in different areas of expertise, farmers, and stakeholders from different backgrounds) to build and select the indicators. Indicators were selected and developed through a series of consecutive steps using a combination of bottom-up and top-down approaches. According to King et al. [48], combining both approaches is necessary and provides good results. This technique is normally used to solve complex problems or generate strategies [136]. The main features of the technique are its anonymity, to reduce the influence of "super-experts," and its contribution to the objectivity of

The MESMIS (for its acronym in Spanish—Marco para la Evaluación de Sistemas de Manejo de recursos naturales incorporando Indicadores de Sustentabilidad) has an operative structure: Characterization of the systems, identification of critical points, and the selection of specific indicators for the environmental, social, and economic dimensions of sustainability. These information are integrated through mixed (qualitative and quantitative) techniques and multicriteria analysis to obtain a value judgment about the resource management systems and to provide suggestions and insights aimed at improving the socio-environmental profile

• Sustainability is defined by attributes of NRMS: productivity, stability, reliability, resil-

sustainability) (Table 2).

44 Sustainability Assessment and Reporting

the results [137, 138].

and the individual treatment of the results [23].

[62]. The framework is based on the following premises:

ience, adaptability, equity, and self-reliance.


The IDEA method is used widely in Europe and assesses a farm sustainability with agriecological (18 indicators), socio-territorial (18 indicators), and economic (6 indicators) scales [139].

Response-Inducing Sustainability Evaluation (RISE) is an indicator-based sustainability assessment tool developed by Häni et al. [79]. Its aim is to provide a holistic evaluation of sustainability at the farm level and support the dissemination of sustainable practices. RISE has been applied in over 2500 farms in 56 countries [140]. RISE 2.0 assesses the sustainability performance of a farm for 10 themes (soil use, animal husbandry, nutrient flows, water use, energy and climate, biodiversity, working conditions, quality of life, economic viability, and farm management) and 51 subthemes. The sustainability performance of each subtheme is based on an aggregation of various indicators. These indicators are normalized for each subtheme and can include comparisons between farm and reference data. The score at the theme level is based on the average of the scores of the 4–7 subthemes included in each theme. Scores on theme and subtheme level range from 0 to 100 and are visualized in a polygon.

A hierarchical framework based on the goods and services provided by agricultural ecosystems is the base of the SAFE method (Sustainability Assessment of Farming and the Environment Framework), resulting in the hierarchy, the principles that are correlated with the three dimensions: economic, social, and environmental [38].

The Monitoring Tool for Integrated Farm Sustainability (MOTIFS) allows monitoring farm progress towards integrated sustainability, taking into account economic, ecological, and social aspects [125]. This tool offers a visual aggregation of indicator scores into an adapted radar graph, defining to rescale indicator values into scores between 0 (indicating a worst-case situation) and 100 (indicating assumed maximum sustainability). This allows for a mutual comparison of the indicators for different sustainability themes.

MOTIFS is a sustainability monitoring and management tool, and it allows positioning the strong and weak aspects of a farm; hence it can be used to perform a SWOT analysis (strengths, weakness, opportunities, and threats). It has major assets that could be incorporated in any indicator-based system. It can provide information to farmers for helping them to take action and make decisions. Also, it can guide through the process of assembling and understanding from information and data [126].

Different studies report indicators that have been used to analyze farms' sustainability [141–144] or differences between organic and conventional farms [145, 146]. Considering the sustainability of organic farming and agroecology, there are few methods proposed for evaluating the possibilities on the conversion to organic farming. The Organic Livestock Proximity Index (OLPI) is a methodology proposed by Mena et al. [41] and Nahed et al. [127] based on the multicriteria approach for weighting and aggregating multidimensional information. The OLPI of each farm was the sum of its weighted indicator values. The weighting coefficient assigned to each indicator (between 0 and 1) was defined as a function of: its importance according to the principles of organic livestock farming and agroecology and the difficulty in fulfilling the requirements of the European standards on organic production. In this sense, the indicators for assignment of the weights are nutritional management, marketing, soil fertility and contamination, weed and pest control, breeds and reproduction, and animal welfare.

situations, and the concept of sustainability needs to integrate a comprehensive assessment of

Methodologies for Assessing Sustainability in Farming Systems

http://dx.doi.org/10.5772/intechopen.79220

47

Sustainability evaluation is a multidimensional issue involving huge amounts of complex information. Therefore, perfect evaluation is uncommon; in this sense, there is a need to systematically reduce the complex information to a more concentrated form while constructing the pyramid of

The first generation sustainability indexes do not incorporate interrelations between the components of a system. Examples are environmental indicators, as CO2 emissions, deforestation or erosion. The second generation use composed indicators, normally with four dimensions: economic, social, productive, and environmental. Now, there are coming the third generation, indicators that it is necessary to build. They correspond to binding synergistic or transversal indicators, which simultaneously incorporate several attributes or dimensions of sustainability.

The assessment of sustainability needs to continue exploring in agriculture systems an integrated approach, and in the future, the set of multidimensional indicators (economic, ecological, social, and technical indicators) will be evaluating both separate parts of the system and

ecological, economic, and social dimensions to achieve sustainable agriculture.

information aggregation, at the base of which are raw data and at the top the indexes.

their relationships.

Abbreviations

Author details

Colombia

NRMS Natural Resource Management Systems

OLPI Organic Livestock Proximity Index

\*Address all correspondence to: jfabiancruz@gmail.com 1 Student Doctorate, Universidad de Córdoba, Spain

3 Universidad de Sevilla, Sevilla, Spain

MOTIFS Monitoring Tool for Integrated Farm Sustainability SWOT strengths, weaknesses, opportunities, and threats

Jaime Fabián Cruz1,2\*, Yolanda Mena3 and Vicente Rodríguez-Estévez4

2 Facultad de Medicina Veterinaria y de Zootecnia, Universidad Antonio Nariño, Bogotá,

4 Departamento de Producción Animal, Universidad de Córdoba, Córdoba, Spain

EF Ecological Footprint

The global OLPI for all case study farms is the average of the indicators. Weights of indicators are based on the importance conferred to them by the experts and are transformed to a percentage scale. As the weighting coefficients must be adjusted in accordance with specific local criteria, OLPI should not be considered if it is used to compare farms of different regions [41]. Some methods based on fuzzy measures have been used in the field of subjective multicriteria evaluation, because the theory of fuzzy logic provides a mathematical means to capture the uncertainties associated with human cognitive processes [147, 148], but in spite of their immense value, fuzzy integrals are difficult to apply to real situations [135]. Mena et al. [41] considered the main advantage of the OLPI method over fuzzy logic in multicriteria analysis is that it is easy to calculate. Once the method proposed has been applied to many farms, the researchers will have a precise idea of the relationship between different criteria and conditioning factors, and therefore, it can be used for decision-making.

Sustainable agricultural spatial model (SASM) integrates five factors (productivity, security, protection, economic viability, and social acceptability) using geographic information system (GIS), analytical tools for the purpose of combating and tackling sustainable agricultural constraints, and optimum land use planning [128].

In the end, the sustainability of agroecosystems depends on their basic characteristics and how, why, and through which variables are affected within each dimension. Convenience in the analysis of agroecosystems should not be viewed from an anthropocentric point of view but rather in a broader (holistic) way that favors the sustainability of production systems and that takes into account the hierarchy and complexity of agricultural systems. The use of the property as a unit of study is satisfactory to the extent that the interactions of the different activities carried out are considered and evaluated, along with externalities, complementarity, and interference with adjacent farm activities [149].
