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Person

Sarah M Stackpoole

Research Ecologist

Office of the Chief Operating Officer

Email: sstackpoole@usgs.gov
Office Phone: 303-236-0271
ORCID: 0000-0002-5876-4922

Location
P.O. Box 25585
Denver Federal Center
Lakewood , CO 80225-0585
US

Supervisor: Jennifer L Keisman
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A nested sampling network on the Colorado (CR) and Missouri Rivers (MR) provided data to assess impacts of large-scale reservoir systems and climate on carbon export. The Load Estimator (LOADEST) model was used to estimate both dissolved inorganic and organic carbon (DIC and DOC) fluxes for a total of 22 sites along the main stems of the CR and MR. Both the upper CR and MR DIC and DOC fluxes increased longitudinally, but the lower CR fluxes decreased while the lower MRs continued to increase. We examined multiple factors through space and time that help explain these flux patterns. Seasonal variability in precipitation and temperature, along with site-level concentration versus discharge relationships proved to...
Categories: Data, Publication; Types: Citation
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This product consists of one tabular dataset and associated metadata of water quality information related to rivers, streams, and reservoirs in the Upper Mississippi River watershed between 2012 and 2016. This data release is a part of a national assessment of freshwater aquatic carbon fluxes. Data consist of organic and inorganic carbon related species, carbon dioxide and methane gas fluxes calculated from manual chamber measurements, nitrogen species, carbon isotopes, oxygen isotopes, cations, anions, trace metals, and various in situ measurements including: pH, water temperature, air temperature, barometric pressure, dissolved oxygen, turbidity, fluorescent dissolved organic matter, and specific conductance....
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Carbon, Fluorescent Dissolved Organic Matter (fDOM), Minnesota, Shingobee, Shingobee Headwaters Aquatic Ecosystems Project, All tags...
We explored the possible causes of change in Mississippi River nutrient load trends through an impact evaluation that utilizes counterfactual scenarios to compare observed changes in river loads to changes in river load that might have occurred in the absence of potential causal factors. Prior to the counterfactual analysis, we developed a multiple linear regression model to predict TN and TP load changes over time. We modeled annual FN river loads as a function of current nutrient balances, lagged nutrient balances, and a latent variable representing the aggregate effect of other potential causal factors. We examined two different counterfactual scenarios, using hypothetical inputs to the calibrated TN and TP regression...
Categories: Data
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