Date of Thesis

5-8-2017

Thesis Type

Honors Thesis (Bucknell Access Only)

Degree Type

Bachelor of Science

Department

Biology

First Advisor

Matthew E. McTammany

Second Advisor

Gabrielle Flynt

Abstract

Atmospheric carbon dioxide concentration readily exchanges with the biosphere through the processes of photosynthesis (uptake of CO2) and respiration (release of CO2), and the difference between these two processes determines the net influence of ecosystems on atmospheric carbon dioxide. The effects of terrestrial ecosystems and oceans, two large components of the global carbon cycle, are well studied and show net uptake of atmospheric CO2; however, the effects of inland freshwater ecosystems are not well known generally and are only recently being included in these analyses. Ecosystem metabolism for rivers can be estimated from the rate of change of dissolved oxygen in the water. New methods, termed "inverse modeling,'' have been developed that fit diel dissolved oxygen concentration measurements to theoretical dissolved oxygen curves by finding metabolic and reaeration rates that best fit the data. Inverse modeling methods were used to analyze dissolved oxygen data from two sites on the West Branch and North Branch of the Susquehanna River from 2009 to 2016. These methods use known models relating dissolved oxygen and net ecosystem production, and statistical methods to estimate the gross primary productivity (GPP), ecosystem respiration (ER) and reaeration coefficient (K600) of each site in the Susquehanna River for each day in the dataset. These models used data measured on 15-minute time intervals compiled from sondes placed in the water treatment plants of Milton and Danville, outside data sources such as USGS and estimations based on empirical formulas. The Susquehanna River dataset used in this study is unique and especially significant because few studies on river metabolism cover such a large time frame. Once the metabolism parameters were estimated, the values for GPP and ER were then analyzed for annual trends and other patterns over the 7 year time span. GPP and ER were both found to have annual and seasonal trends that remain consistent over the 7 year dataset. High discharge events disrupted normal metabolism cycling and reduce metabolism to near zero. Both GPP and ER were correlated with daily mean temperature. The West Branch of the Susquehanna River near Milton, PA was a weak atmospheric carbon sink (sometimes a source) and the North Branch near Danville, PA is an atmospheric carbon source. Metabolism and the effect of these rivers on carbon cycling are expected to change over time in response to climate change. Analysis continues and future work will include refining these methods and applying them to data that continues to be collected.

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