Chironomid
This presentation is the property of its rightful owner.
Sponsored Links
1 / 16

Ava Moussavi Jessica Satterlee Garfield Kwan PowerPoint PPT Presentation


  • 56 Views
  • Uploaded on
  • Presentation posted in: General

Chironomid Abundance as An Indicator of Water Conditions in Treatment Wetlands and Biofilter s of Victoria, Australia. Ava Moussavi Jessica Satterlee Garfield Kwan. The Millennium Drought. Started in the late 1990s and lasted more than a decade. Melbourne. Bureau of Meteorology, 2011.

Download Presentation

Ava Moussavi Jessica Satterlee Garfield Kwan

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Ava moussavi jessica satterlee garfield kwan

Chironomid Abundance as An Indicator of Water Conditions in Treatment Wetlands and Biofilters of Victoria, Australia

Ava Moussavi

Jessica Satterlee

Garfield Kwan


The millennium drought

The Millennium Drought

  • Started in the late 1990s and lasted more than a decade

Melbourne

Bureau of Meteorology, 2011


Alternate water sources

Alternate Water Sources

  • Sparked widespread use of alternate water sources

    • Recycled water

    • Rainwater harvesting

Grant et al. 2012

Western Treatment

Plant


Potential risk

Potential Risk

  • Wastewater and stormwater recycling can be a potential risk to human and ecosystem health if methods for water treatment do not perform optimally.


Chironomids as indicators

Chironomids as Indicators?

  • Larval stage of midges

  • Thrive in anoxic conditions

  • Feed on organic matter

  • Associated with degraded wetland conditions


Objective

Objective

  • The objective of this project was to assess the relationship between chironomidabundance and overall water quality.


Data collection

Data Collection

  • Water quality parameters were measured at 2 biofilters and 3 constructed wetlands in Melbourne, Australia

    • Chironomids

    • Chlorophyll concentrations

    • Dissolved oxygen and temperature

    • Conductivity, Turbidity, ORP, and pH


Data analysis

Data Analysis

  • Virtual Beach 2.3 was used to perform multiple linear regression

  • Identified correlations between chironomid abundance and water quality parameters:

    • Chlorophyll Content

    • Dissolved Oxygen (DO)

    • Temperature

    • pH

    • Conductivity

    • Turbidity

    • Oxidation Reduction Potential (ORP)


Results

Results

Chironomidae = B0 – B1Temp-1 + B2Turb-1

B0 = 170.14

B1 = 1948.40

B2 = 2315.22

p-value (Turb-1): 0.02

p-value (Temp-1): 0.03


Results1

Results

Chironomidae = B0 – B1 poly(pH) + B2Turb-1

B0 = -34.56

B1 = 1.30

B2 = 1505.51


Discussion

Discussion

• Chironomid abundance can be predicted from temperature and turbidity (top ranked model) or pH and turbidity (second model)

• Turbidity is the most credible explanatory variable because it appears in both top-ranked models, and was identified as an important correlate in a preliminary Classification Tree analysis (data not shown)

• Chironomid abundance can be predicted from temperature and turbidity (top ranked model) or pH and turbidity (second model)

• Turbidity is the most credible explanatory variable because it appears in both top-ranked models, and was identified as an important correlate in a preliminary Classification Tree analysis (data not shown)

• Data set is small and more advanced analytical techniques for categorical data would need to be explored

• Chironomid abundance can be predicted from temperature and turbidity (top ranked model) or pH and turbidity (second model)


Conclusion

Conclusion

  • Our study has identified temperature, pH and turbidity as possible indicators of chironomid abundance, but our data/methods are insufficient for us to conclude that these water quality parameters can be used to predict chironomid abundance.

Future Direction

  • Increase sampling size and sampling intensity

  • Survey alternative variables i.e. wetland birds

  • Use advanced statistical tools (Generalized Linear Models, Classification Tree analysis) that permit evaluation of categorical variables

  • Functional role of chironomidae


Acknowledgements

Acknowledgements

  • We want to thank Stanley Grant, Sunny Jiang, Megan Rippy, Andrew Mehring, Alex McCluskey, Laura Weiden, Nicole Patterson, and Leyla Riley, the faculty of University of California - Irvine, and the staff of University of Melbourne for contributing and facilitating our research. We also want to thank NSF for funding this research.


Ava moussavi jessica satterlee garfield kwan

Fin


  • Login