Breathing Fresh Utility into an R Package for Aquatic Photosynthesis and Respiration
Enhance a widely used, USGS-led R package for stream metabolism estimation by adding new methods for human-impacted streams.
The streamMetabolizer R package uses common USGS time series – such as dissolved oxygen, streamflow, and temperature – to estimate aquatic photosynthesis and respiration. Since its publication in 2018, streamMetabolizer has been cited more than 170 times and featured in the CDI Model Catalog. The software currently offers one-station methods, but two-station methods are needed wherever in-stream conditions vary longitudinally due to reservoirs, groundwater inputs, or waste-water treatment plants. Recently, several of our team members piloted a two-station method with novel support for variable streamflow, unlocking metabolism estimation for many human- and groundwater-influenced streams. We will implement this new method in streamMetabolizer to broaden the method’s impact and the software’s utility. Along the way, learning from our experience since 2018, we will streamline future maintenance and support needs through containerization and additional documentation. With these proposed updates, we can better support science and management in a widening diversity of stream ecosystems.
Enhance a widely used, USGS-led R package for stream metabolism estimation by adding new methods for human-impacted streams.
The streamMetabolizer R package uses common USGS time series – such as dissolved oxygen, streamflow, and temperature – to estimate aquatic photosynthesis and respiration. Since its publication in 2018, streamMetabolizer has been cited more than 170 times and featured in the CDI Model Catalog. The software currently offers one-station methods, but two-station methods are needed wherever in-stream conditions vary longitudinally due to reservoirs, groundwater inputs, or waste-water treatment plants. Recently, several of our team members piloted a two-station method with novel support for variable streamflow, unlocking metabolism estimation for many human- and groundwater-influenced streams. We will implement this new method in streamMetabolizer to broaden the method’s impact and the software’s utility. Along the way, learning from our experience since 2018, we will streamline future maintenance and support needs through containerization and additional documentation. With these proposed updates, we can better support science and management in a widening diversity of stream ecosystems.