Katie H. Costigan

Abiotic controls and temporal variability of river metabolism: multiyear analyses of Mississippi and Chattahoochee River data

Abstract. Whole-ecosystem metabolism is an important indicator of the role of organic matter, C cycling, and trophic structure in rivers. Ecosystem metabolism is well studied in small streams, but less is known about metabolism in large rivers. We estimated daily whole-ecosystem metabolism over 2 y for 1 site each at the Mississippi and Chattahoochee Rivers in the USA to understand factors influencing temporal patterns of ecosystem metabolism. We estimated rates of gross primary production (GPP), community respiration (CR), and net ecosystem production (NEP) with a curve-fitting approach with publicly available discharge (Q), dissolved O2, temperature, and photosynthetically active radiation (PAR) data. Models were run for week-long blocks, and power analyses suggested that rates should be established at least once for each 10-wk period throughout the year to characterize annual rates of metabolism accurately in these 2 rivers. We analyzed weekly rates averaged over 10-wk periods with Spearman rank correlation to identify potential drivers and with path analyses to identify interactions among variables driving GPP, CR, and NEP. Both rivers had an overall negative NEP, and the Mississippi River had stronger seasonal trends. In the Mississippi River, CR was strongly positively correlated with Q, which suggests variation in seasonal availability of allochthonous C. In the Chattahoochee, CR was most strongly positively correlated with GPP, whereas GPP was negatively correlated with Q, which suggests that autochthonous processes and water-column light attenuation played important roles in C dynamics. Our results suggest that these large rivers were net heterotrophic at annual time scales but autotrophy can be important seasonally.

How Big of an Effect Do Small Dams Have? Using Geomorphological Footprints to Quantify Spatial Impact of Low-Head Dams and Identify Patterns of Across-Dam Variation

Longitudinal connectivity is a fundamental characteristic of rivers that can be disrupted by natural and anthropogenic processes. Dams are significant disruptions to streams. Over 2,000,000 low-head dams (<7.6 m high) fragment United States rivers. Despite potential adverse impacts of these ubiquitous disturbances, the spatial impacts of low-head dams on geomorphology and ecology are largely untested. Progress for research and conservation is impaired by not knowing the magnitude of low-head dam impacts. Based on the geomorphic literature, we refined a methodology that allowed us to quantify the spatial extent of low-head dam impacts (herein dam footprint), assessed variation in dam footprints across low-head dams within a river network, and identified select aspects of the context of this variation. Wetted width, depth, and substrate size distributions upstream and downstream of six low-head dams within the Upper Neosho River, Kansas, United States of America were measured. Total dam footprints averaged 7.9 km (3.0–15.3 km) or 287 wetted widths (136–437 wetted widths). Estimates included both upstream (mean: 6.7 km or 243 wetted widths) and downstream footprints (mean: 1.2 km or 44 wetted widths). Altogether the six low-head dams impacted 47.3 km (about 17%) of the mainstem in the river network. Despite differences in age, size, location, and primary function, the sizes of geomorphic footprints of individual low-head dams in the Upper Neosho river network were relatively similar. The number of upstream dams and distance to upstream dams, but not dam height, affected the spatial extent of dam footprints. In summary, ubiquitous low-head dams individually and cumulatively altered lotic ecosystems. Both characteristics of individual dams and the context of neighboring dams affected low-head dam impacts within the river network. For these reasons, low-head dams require a different, more integrative, approach for research and management than the individualistic approach that has been applied to larger dams.