The objective of this research is to estimate the socioeconomic and environmental value of ecosystem services produced by Agroforestry Systems of Tomé-Açu in society's perception. These systems, in addition to fruits, seeds, and nuts, provide other services that are perceived by society in the form of welfare, and are not yet sold on the market. For the analysis, the Integrated Method of Contingent Valuation was employed, which contemplates the economic, social and environmental dimensions. This approach relied in the equations modelling the Willingness to Pay for the conservation of Agroforestry Systems, and Willingness to Accept a compensation for not using these systems over other commercial production systems such as oil palm and soybean. The average value of ecosystem services in the Agroforestry Systems of Tomé-Açu in the population's perception was estimated at R$ 5.011,19 ha-1 for the Willingness to Pay and R$ 7.367,24 ha-1 for the Willingness to Accept. This indicates the importance given by the community to the benefits generated by the ecosystem services, in a magnitude higher than the market value of the Amazon rainforest and of the production systems. Therefore, the value of these services should also integrate the payment to compensate the producers that maintain these systems in the Amazon.

Urbanization has threatened rural communities’ livelihoods worldwide, changing their agro-food systems from locally produced traditional items to industrialized foodstuffs. The main objective was to investigate the relationship between livelihood conditions and the agro-food transition process in rural communities of the Center-West, Northeast, and Amazon regions of Brazil. We hypothesized that traditional agroecosystems and local food habits changed with greater access to market economies. The study was conducted with semi-structured questionnaire interviews to verify agro-food patterns, subsistence farming, natural resource use, and socioeconomic conditions. Moreover, we used stable isotope ratios from the inhabitants’ fingernails to determine the food source and trophic chain diversity. Data from questionnaires were analyzed using a Bayesian clustering model to characterize the socioeconomic conditions and agro-food patterns among rural and urban communities. The isotopic data were appraised through a nonparametric model to assess food differences among Brazilian regions and different community types. The Bayesian model allowed us to determine the optimal number of groups according to descriptive socioeconomic and agro-food variables sorted by each specific location. We also verified a food change from C 3 (more natural) to C 4 (more processed) with an increase in δ 13 C and a decrease in δ 15 N in the city and town localities. This indicates a livelihood shift from locally produced foods to processed items toward urban areas. Although remote villages showed more maintenance of their agro-food systems, increased access to market economies and the supermarket diet is changing the livelihood conditions of rural communities, which can compromise their traditional farming and food sovereignty.