Abbreviations

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

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

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

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

Productivity, security, protection, viability, and acceptability are the main factors of sustainable land management. But, implementing sustainability remains a hard event in many agricultural

control, breeds and reproduction, and animal welfare.

46 Sustainability Assessment and Reporting

constraints, and optimum land use planning [128].

interference with adjacent farm activities [149].

7. Conclusions

conditioning factors, and therefore, it can be used for decision-making.

