Abstract
In Amazonia, our knowledge of the trade-offs and possible thresholds in the relationships among social, economic and environmental parameters remains quite limited and hinders the design of sustainable socio-environmental systems. To fill this gap, we analyzed relationships among landscape metrics, socio- economic patterns, biodiversity and soil-based ecosystem services within a total of 51 farms located at 6 sites of the Colombian and Brazilian Amazon. Farms were representative of an initial set of 274 and they represented colonization ages from 10 to 80 years and a range of public policies found in the region. Two farms were abandoned in Colombia for local reasons.Cluster analysis separated farms in 7 types of production systems according to 5 main criteria (size of the farm, human capital, incomes, farm products and production intensity) selected from an initial set of 18 criteria. Biodiversity was summarized into a composite index Bd built with data from 8 different groups: trees, shrubs, grasses and forbs, birds, Saturnidae and Sphingidae moths, Drosophilidae, earthworms and ants. Provision of ecosystem services was quantified by a composite indicator of 6 sub- indicators of soil hydrological functions, C storage and chemical fertility. Increasing intensity of production systems was linked to a significant decrease of indicators of natural capital biodiversity (Bd) and soil based ecosystem services (Es) with 20% and 37.3% variance explained, respectively. No relationship was observed between production systems and an indicator of human wellbeing (Sb) based on a set of 5 criteria identified with the farmers. Findings indicate that early colonizers migrate when a certain level of development has been achieved (as a result of their activities) and are replaced by wealthier populations.An overall indicator of sustainability (Su) – that combines production efficiency (Ep), Sb, Bd and Es indices (ranging from 0.1–1.0) – decreases significantly with the landscape intensification (Li) with 18.7% variance directly explained by this relationship. Su was also significantly related to production systems (36.4% variance explained): while this indicator remained relatively stable with a value of 0.5 across the early and intermediate phases following deforestation, it dropped down considerably (0.2) for production systems based on cattle ranching on highly degraded pastures with less than 2% forest cover remaining. Restoration with sylvopastoral systems allowed some farms of this former group to increase sustainability to a value of 0.35 after less than 5 years. Agroforestry systems on sites deforested at the same time maintained values around 0.5, as they allowed the maximum production efficiencies and maintained relatively high values of the Biodiversity (Bd) and Ecosystem services (Es) indexes. This is evidence that beyond the general negative trade-off between human development and natural capital observed in Amazonia, agro ecological options to revert the trend are quite promising. A general methodological approach for the reconstruction of sustainable landscapes in farms of the deforested Amazonian region is proposed as a conclusion.