AmeriFlux is a network of PI-managed sites measuring ecosystem CO2, water, and energy fluxes in North, Central and South America. AmeriFlux is now one of the DOE Office of Biological and Environmental Research (BER) best-known and most highly regarded brands in climate and ecological research. AmeriFlux datasets, and the understanding derived from them, provide crucial linkages between terrestrial ecosystem processes and climate-relevant responses at landscape, regional, and continental scales. Scientific Questions What are the magnitudes of carbon storage and the exchanges of energy, CO2 and water vapor in terrestrial systems? What is the spatial and temporal variability? How is this variability influenced by vegetation type, phenology, changes in land use, management, and disturbance history, and what is the relative effect of these factors? What is the causal link between climate and the exchanges of energy, CO2 and water vapor for major vegetation types, and how does seasonal and inter-annual climate variability and anomalies influence fluxes? What is the spatial and temporal variation of boundary layer CO2 concentrations, and how does this vary with topography, climatic zone and vegetation?
The Environmental Monitoring Program (EMP) began in 1975 to conduct baseline and compliance monitoring of water quality, phytoplankton, zooplankton, and benthic invertebrates in the San Francisco Bay-Delta estuary. This monitoring program was designed to track the impact of water diversions to the State Water Project (SWP) and Central Valley Project (CVP) on the Bay-Delta. In the decades since, EMP scientists have monitored these constituents at fixed and floating stations throughout the estuary and ensured compliance with state and federal mandates such as Water Right Decision 1641 (D-1641). In the years and decades since its inception, EMP has become one of the cornerstones for scientists' and managers' understanding of the pace and pattern of change in this critical ecosystem. By sampling water quality and biological communities concurrently, EMP has created a dataset that is uniquely useful in better understanding causal connections between physical, biological, and biogeochemical processes.
