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The report outlines findings from several IAI Small Grants Programme projects. Key highlights include the loss of carbon retention in the Amazon due to deforestation, the identification of a complex 'water crisis' in border regions of Argentina, Brazil, and Uruguay, and the development of predictive models for the Paraná River basin to balance hydroelectric energy needs with ecosystem services. It also emphasizes the role of co-production of knowledge and participatory governance in enhancing community adaptation to global environmental change across countries including Chile, Colombia, and Uruguay.

The project investigated the Paraná river downstream of the Porto Primavera dam in Brazil to understand how flow dynamics affect large wetlands and floodplains. Using the Indicators of Hydrologic Alteration (IHA) method, researchers found that fish migration and reproduction are strongly influenced by the duration, starting date, peak, and frequency of flood events. The study also identified that professional fishing, tourism, and recreation depend on these ecosystems, though these activities often face conflicts of interest. To address these issues, the team developed a mathematical model using Stochastic Dual Dynamic Programming (SDDP) to simulate the performance of 53 hydropower plants on the river, aiming to create operating policies that optimize both energy production and ecosystem recovery.

The project 'Improving the governance of the floodplain in over-built river basins' investigates the ecological impacts of hydropower plants on the Paraná river in Brazil. Using computer modeling and the Indicators of Hydrological Alteration (IHA) method, researchers identified that fish migration and reproduction are strongly influenced by the duration, starting date, peak, and frequency of flood events. The study also highlights the dependence of local socio-economic activities, including professional fishing, tourism, and recreation, on these fish ecosystems. To resolve conflicts between energy production and environmental needs, the team simulated the performance of 53 hydropower plants using Stochastic Dual Dynamic Programming (SDDP) to develop reservoir operational policies that meet both hydropower and ecosystem service demands.