CO2 Time Series Patterns in Contrasting Headwater Streams of North America

Inland waters such as lakes and rivers are believed to be important areas for the transformation and exchange of carbon with the atmosphere; including the common greenhouse gas CO2. Even though research on these sites is growing, the diversity within sites makes it difficult to understand the general role of these areas in the global carbon cycle. Without this general understanding, the process of predicting changes in the carbon cycle based on changes in an ecosystem – such as eutrophication, hydrologic changes, or climate change – becomes much more difficult. This study focused on temporal variability (variability over time); asking specifically the question, “What controls CO2 temporal variability in a diverse set of headwater streams?” This study speaks often of diel variability, which simply means variability within a 24 hour period. Temporal variability in these systems is particularly difficult to isolate for gases such as CO2, due to their constant exchange with the surrounding atmosphere.

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New sensor technologies within this discipline are now allowing measurement of important variables in longer temporal scales, which allows for more theories to be tested; this is important since there are few models currently available which describe CO2 processes in running water. If scientists want to be able to achieve the creation of such models, they first need better measurement techniques, this is where new technologies come into play. These sensors will be important for diel cycles, but also for extreme weather events, such a floods, that may have large effects over a short or long time period. The possibility of longer data collection may also help to further scientific knowledge on internal variability. Most studies are currently limited to a yearly or seasonal basis because of logistical or resource constraints, meaning that important data on carbon patterns and processes is being lost.

This paper in particular wishes to create a synthesis of a large dataset of pCO2 (the partial pressure of carbon dioxide, which measures the relative concentration of CO2 in the water) and to delve deeper into varied hypotheses involving temporal variability. The researchers documented pCO2 time series in a set of streams and then used the collected data and published records to test temporal hypotheses. There were three main hypotheses:

1) Aquatic primary production controls the variability of CO2
2) Respiration controls CO2 variability
3) Different hydrological events control CO2 variability

If these hypotheses were true, then researchers would:

1) Observe strong diel patterns in the CO2 time series
2) Average CO2 will be greatest in warmer months
3) The greatest changes in CO2 concentration will occur when Q (instantaneous discharge) increases

The study occurred at six headwater catchments in North America, which were varied in climate, hydrology, organic stocks, relief, parent material, and time of ecosystem development. There were not many shared traits among these sites, which helps to determine whether conclusions are universally applicable. There were five sensors placed near the water surface of flowing water, in pre-existing headwater gauging stations (which were operated by the US Geological survey Water, Energy and Biogeochemical Budgets program). Overall there were 40,000 measurements made, though different areas had different recording lengths because of the variability in open water season.

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On the specific subject of diel controls, researchers found:

  • Diel pCO2 variability is not ubiquitous in streams of the northern hemisphere
  • Diel cycles are likely due to primary productivity in the channel as opposed to other processes
  • The sites with consistent diel pCO2 patterns were all characterized by open canopies, whereas sites lacking diel patterns were typically shaded by full canopies during the growing sea- son
  • They can confidently predict that diel CO2 cycles will be prevalent in most open canopy systems

On respiration, researchers found:

  • They were able to detect a late summer peak in concentrations at all but one of their sites, and suggest that this pattern is due to increased respiration during the warmest period of the year
  • A thorough study of individual streams will be needed to identify whether the summer pCO2 maximum is a terrestrial or aquatic phenomenon

And on storm controls, researchers found:

  • There were pCO2 responses to increasing discharge in some sites, but the magnitude of responses varied widely
  • There were negative and positive discharge responses on one site, depending on the location of the sensor (upstream vs. downstream), suggesting that concentration-discharge relationships can be site and/or time specific in headwater catchments
  • Analysis of the histograms leads researchers to conclude that storms do not likely dominate pCO2 variability over longer time scales

Researchers used different analysis techniques to determine the correlation between variables in each hypothesis. The results showed there were distinct patterns among sites. At every location, researchers found that during the majority of the testing period there was a supersaturation of pCO2. Some streams showed a positive pCO2 response after storm events, but others had varied responses. All sites, however, had a parabolic pattern with their maximum pCO2 in the summer months. As researchers put it, the main conclusion from this study is that stream CO2 is highly variable, with few, if any common traits that can be used to generalize differences among sites. Highly variable and idiosyncratic pCO2 time-series appear to be the norm across the globe…” There  was evidence for each independent hypothesis, leading researchers to the additional conclusion that these different traits (aquatic primary production, respiration and storm events) are not mutually exclusive, and each contribute to stream CO2 levels in a different way. In essence, this study supports the idea that headwater streams are highly variable, with heterogeneous qualities in space and time. These new sensors, then, are useful for very localized processes (such as aquatic metabolism) and, when used with other tools, can be useful in understanding these aquatic processes.

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