These data were collected to support monitoring of the Upper Clark Fork River restoration, and data collection was funded by the US NSF Long Term Research in Environmental Biology (LTREB) program and the US NSF EPSCoR funded Montana Consortium for Research on Environmental Water Systems. The LTREB monitoring project consists of monthly or bi-weekly water quality monitoring across a 200-km restoration gradient contaminated by historic mining practices to monitor inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and heavy metal contamination. The original analytical intent for these data was to assess the response of the river algal community to the floodplain restoration. Data characterize epilithic biomass on the river bed including measurements of benthic standing stocks and abundance of pigments associated with primary producers. Metrics of characterization include areal density of chlorophyll a, areal density of phaeophytin, the ratio of carotenoid to chlorophyll absorbance, percent organic matter, areal density of organic matter, and category of biomass composition (filamentous algae vs. other epilithon). Samples were obtained from collecting and scrubbing five rocks at any given site. Biomass estimates were obtained from area corrected Ash Free Dry Mass. Pigment concentrations were obtained through the use of extraction in acetone followed by spectroscopy. Data are from the 2017 and 2018 algal growing seasons. Data were collected on the Upper Clark Fork River (USGS HUC 17010201) at project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA.
Valett, H Maurice; University of Montana
Utzman, Claire; University of Montana
Feijó de Lima, Rafael; University of Montana
Environmental Data Initiative (EDI)
Valett, H.M., C. Utzman, and R. Feijó de Lima. 2022. Characterization of photosynthetic epilithic biomass on the river bed of the Upper Clark Fork River (Montana, USA) during the algal growing seasons of 2017 and 2018 ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/35c885c1a3c9402e5030c7185d5a4dfc (Accessed 2022-08-02)