There is an urgent need for multifunctional landscapes to provide a diversity of ecosystem services (ES) due to projected climate change. This requires a better understanding of social and ecological factors that influence how these landscapes are managed and how this influences the provision of ES. Identification of the main socioeconomic drivers of Land Use Land Cover (LULC) can give important insights about the drivers of ES. Brazil has witnessed intense changes in LULC, which may have influenced the provision of ES at different scales.
The Zona da Mata of Minas Gerais, Brazil, is characterised by a heterogeneous landscape mosaic composed of pasture and coffee fields intermingled with forest fragments, which are predominantly inhabited and managed by family farmers. I assessed LULC changes from 1986 to 2015 and their main socioeconomic drivers. By combining data obtained from satellite images, workshops and secondary data, I showed that forest and coffee areas increased, and pasture decreased. These changes were associated with government measures to protect the environment, financial support of family farmers, migration to cities and the agroecological movement.
A scenario analysis of contrasting socioeconomic narratives indicated that sustainable measures taken by the government will lead to an increase in forest and coffee areas (Green Road scenario), in contrast with a decline in forest areas if government measures focus on rapid economic development (Fossil Fuel scenario).
I also explored the spatial variation of ES from 1986 to 2015 and the impacts of LULC changes on ES provision levels and their interactions through LULC maps from 1986 and 2015 and the InVEST model. This analysis indicated that the conversion of forest to pasture has strong negative impacts on soil erosion control and water flow regulation. I also investigated the separate effects of LULC changes and climate on water dynamics from 1990 to 2015, and explored scenarios of LULC change and climate change for 2045 with the SWAT model and climate data combined with historical and future LULC maps. I found that the variation in climate variables was the main factor for the observed increase in the river streamflow in the study period and that forest can buffer extreme precipitation events.
Finally, I assessed the impact of climate change on the suitability of arabica coffee production in the study region and the potential of agroforestry systems to mitigate these impacts through combining the species distribution model MaxEnt with current and future climate projections. I explored the effect of altered microclimate in agroforestry systems on the suitability for coffee production by adjusting future climate data to reflect conditions in agroforestry systems. I found that the area suitability for coffee production from the current monoculture coffee systems will decline by 60% under projected climatic changes. However, implementation of coffee agroforestry systems can mitigate these negative impacts and maintain 75% of the area suitable for coffee production in 2050.
Combining social and ecological systems in an interdisciplinary framework, generated insights in the relationships between climate and LULC change, and how this influences several ES. This framework allows different stakeholders to find effective ways towards multifunctional landscapes that promote sustainable use of ES.