• Farm-scale ecosystem accounting was developed combining spatial, field and farm data within a standard framework. • Spatial datasets offered acceptable accuracy for assessing extent, conditions, and services flow at the farm level. • Accuracy limitations were primarily observed for above ground biomass in dense forests and for carbon in soil. • Farm-provided data were essential for evaluating cropland condition indicators and service flow. • Farm level ecosystem accounts provide helpful information for farm management. Demand for monitoring the supply and use of natural resources in agriculture is growing. Farming depends on ecosystem services yet contributes to their loss. Ecosystem accounting frameworks help to integrate nature into decision-making by consistently revealing those impacts and dependencies. We apply the United Nations’ System of Environmental-Economic Accounting – Ecosystem Accounting (SEEA EA) to a 38,603-hectare farm in southern Amazonia, Brazil. We assess uncertainties in spatial datasets compared to field data, and evaluate their suitability for the accounts. Our results show that combined spatial and field data allow farm-level monitoring of ecosystem extent, integrity, and services that is consistent with SEEA EA. Farm data effectively capture nitrogen use efficiency and pesticide-related biodiversity risks. Land-use and carbon flows could be tracked with acceptable accuracy with spatial data, while soil variables had to rely solely on field data. Despite these uncertainties, the accounts deliver actionable insights. For farmers who often perceive forest as a burden, the accounts clarify the role of forests in sustaining key services for their rainfed crops, such as rainfall regulation and carbon sequestration with associated climate regulation benefits. Consistent yearly monitoring also supports informed decisions on managing and financing agriculture for better use of natural capital.
Batista et al. (Sun,) studied this question.