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The study analyzed the dynamics of grazing in sheep production associated with agricultural crops based on the social, productive, market, income, and environmental dimensions in the temperate region of Puebla and Tlaxcala, Mexico. The use of grazing, topography, climate, crops and type of vegetation in the production systems and data on the family, means of production, market and income were recorded with interviews applied to 256 sheep producers. Data were analyzed with descriptive statistics and response surface linear regression models and multilevel models, with the SAS statistical package. Five crop and sheep associations were defined as results. The response surface linear regression models, fitted for grazing percentage, had differences in the slopes estimated (P<0.05) for producer experience, schooling, days of work spent on sheep, value of facilities and flock size. The multilevel analysis showed that 19 % of the variance in grazing time (hours) was explained by the variables of crop and sheep associations (level 2) and the rest by production units (level 1). Multilevel models associated grazing time with income (P<0.01), percentage of lamb sales (P<0.01), schooling (P<0.05), days of work spent on sheep (P<0.05), flock size P<0.05) and grazing percentage (P<0.001). The study allowed the classification of agroecosystems and the identification of the most appropriate profile of producer for sheep production in the socioecological and economic context in the temperate region of Puebla and Tlaxcala, Mexico. [ABSTRACT FROM AUTHOR]

Based on feed resources, productive parameters and economic indicators, a typology was developed for sheep production systems and sheep farms in the Sierra Norte region of Puebla State, Mexico. A questionnaire was designed to collect quantitative data on productive parameters and calculate relevant economic indicators. Interviews were done of a sample of 100 sheep producers and responses validated by monitoring 30 sheep farms for a one-year period. Data was collected on labor, grazing areas and practices, use of crop residues, flocks of sheep, income resources, production costs and income. Descriptive statistics were estimated for productive and economic variables and the farms classified with a multivariate analysis. Factor analysis helped to identify ewe sale price, flock size and family labor as possible competitive advantages, and production costs and lamb sale price as possible disadvantages. Productive and economical aspects had variable significance among the farms (P<0.05). Cluster analysis classified the farms mainly as subsistence (44 %), transitional (38%) and extensive (15 %). Extensive farms had the highest (P<0.05) ewe sale price (US $140.7±17.4) and the highest (P<0.05) gross income from sale of animals (US $1,156.5±47.9). Including labor costs in the balance always produced a negative net return. [ABSTRACT FROM AUTHOR]