Judges’ Queries and Presenter’s Replies

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Presentation Discussion

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    Mauri PElto

    Guest
    May 22, 2012 | 08:46 a.m.

    The poster provides an interesting and compelling glimpse of the potential for baseline DOM observations for long term ecologic monitoring. The video is not compelling. How do you plan to distinguish changes due to DOM from turbidity changes due to sediment? Why only measure in summer, you have many northern lakes where little information is available in winter, could this not be a baseline that could show even more change if for example ice cover duration declines and winter turnover is altered?

  • May 22, 2012 | 10:47 a.m.

    Excellent job Nicole, Patricia, Deshawn, Margaret, and Jennie! I like the clear presentation, and especially the way you integrated perspectives of those at both Miami and Kent working on diverse systems. I look forward to how your results are integrated this summer.

  • Icon for: Nicole Hayes

    Nicole Hayes

    Presenter
    May 22, 2012 | 10:53 a.m.

    Hello,

    We are measuring DOM change with two methods. First, we are collecting bi-weekly samples to analyze on a UV-visible light spectrometer. Second, we have a permanent CDOM (chromophoric dissolved organic matter) sensor attached to the buoy. Both of these measurement methods operate on the principle that CDOM absorbs light in the UV spectrum and then fluoresces blue light. Based on the wavelength of fluoresced light we can draw conclusions about the source (terrestrial versus aquatic) of the DOM.

    We are measuring turbidity with a sensor attached to the buoy. It operates by emitting visible light, then measuring the amount of light that back scatters at a 90 degree angle.

    Using both sets of CDOM data we plan to look at changes in the source of CDOM data over our sampling period. We anticipate that there will be a positive correlation between higher quality DOM (more terrestrial) and turbidity (a result of run-off events) in our systems.

    We are limited to taking summer measurements because of the danger ice presents to our buoys. In many of our sampling sites (particularly the reservoirs) we also wouldn’t have access to the buoy for extended periods of time because the lakes don’t freeze solid enough to travel on and, if we could reach the buoy, the sensors would be frozen into the lake. Although winter sampling could add an interesting component to our study, for now we are limited to summer only.

    Thanks for your comments,
    Nicole

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    Mauri PElto

    Guest
    May 22, 2012 | 12:31 p.m.

    Thanks for the detailed response. Part of your thesis depends on monitoring around heavy rain events, yet the heaviest discharge from rain events does not occur in summer. Is there any flexibility to get to certain lakes after particularly heavy rain events

  • Icon for: Nicole Hayes

    Nicole Hayes

    Presenter
    May 22, 2012 | 02:46 p.m.

    Hi,

    The buoys have been out on some of the lakes for about a month now or will be out within the next few weeks. We should be able catch a number of large storm events in these periods, even if we are not able to catch all of the big spring storms or even the largest storm events.

    We have also been able to test the efficacy of our index over different time periods (weeks to months to seasons) and we have found that monthly samples reflect large precipitation events eliminating the need to take hand samples directly after heavy rains.

    Nicole

  • Icon for: Annie Aigster

    Annie Aigster

    Coordinator
    May 22, 2012 | 03:19 p.m.

    Very timely topic on climate change. I enjoyed the inter-college collaboration from Miami and Kent State. I would like to see your results of your data collection. I was wondering about sampling only in the summer, and I read your response to a previous question.

  • May 24, 2012 | 02:44 p.m.

    Hello everyone,
    You did a good job explaining your research project. It sounds interesting and should provide useful information. You also did a good job explaining how you will gather the lake/terrestrial DOM data (a video of a sensor buoy would have been helpful, however).

    Since you are comparing terrestrial versus autochthonous inputs, could you also explain how you determine periods when there are more runoff inputs? – Are you using data from nearby river level sensors?

  • Icon for: Michael Vanni

    Michael Vanni

    Faculty
    May 25, 2012 | 08:51 a.m.

    Nice job guys!

  • Further posting is closed as the competition has ended.

  1. Nicole Hayes
  2. http://www.igert.org/profiles/4695
  3. Graduate Student
  4. Presenter’s IGERT
  5. Miami University
  1. Jennie Brentrup
  2. http://www.igert.org/profiles/3998
  3. Graduate Student
  4. Presenter’s IGERT
  5. Miami University
  1. Margaret Gaglione
  2. http://www.igert.org/profiles/4155
  3. Graduate Student
  4. Presenter’s IGERT
  5. Miami University
  1. DeShawn Johnson
  2. http://www.igert.org/profiles/4027
  3. Graduate Student
  4. Presenter’s IGERT
  5. Miami University
  1. Gloria Johnston
  2. http://www.igert.org/profiles/3108
  3. Graduate Student
  4. Presenter’s IGERT
  5. Miami University
  1. David Widner
  2. http://www.igert.org/profiles/3994
  3. Graduate Student
  4. Presenter’s IGERT
  5. Miami University

Sensing Climate Change: Using sensors to identify drivers of climate change in aquatic ecosystems

As the lowest point in the landscape, lakes integrate the signals of climate change. We are using a novel optical index that integrates the effects of precipitation on optical properties in the water column and allows us to compare the effects of climate change across aquatic ecosystems. Preliminary results suggest that the optical index is a function of the quality of dissolved organic matter and may help us to distinguish its source. We have also found that the optical properties of lakes from non-human influenced watersheds and reservoirs from heavily modified watersheds both respond in the same direction, albeit at a different magnitude, following precipitation events or drought periods. Our goals are: first, to determine if the index works in diverse aquatic ecosystems and second, to identify the factors driving these changes in optical properties using high frequency data from automated sensors. Each water body will have sensors that measure algal, sediment, and dissolved organic matter concentrations and we will collect water samples to estimate the optical index. With our results we will determine if our index works across all aquatic ecosystems and identify the relative importance of the three drivers (algae, sediment, and dissolved organic matter) across ecosystem type.