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Brian O’Neill James H. Thorp

Brian O’Neill James H. Thorp

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Brian O’Neill James H. Thorp

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  1. Hydrogeomorphic fluctuations in a sand bed prairie river: benthic invertebrates, river complexity, and habitat use Brian O’Neill James H.Thorp

  2. Kansas River River Complexity River Variability Low Water – High Complexity High Water – Low Complexity

  3. Implications of Natural Variability • Dammed tributaries greatly reduced variability • Global climate change expected to increase precipitation variability • Depending on dam managing strategy, increased variability may make hydrology more similar to historic levels

  4. Sand Bed Rivers • Prevailing wisdom - woody debris is main habitat for benthos • Up to 1/3 of total habitat is wood • (~0.5m2 wood/m2 sand) • Most studies done in forested rivers of the Southeast

  5. Great Plains Rivers • Kansas River – If found, in extremely local areas • Flushed downstream by large flashy spates. • Very little wood • Estimate only 0.06% of total habitat • 0.0006 m2 wood/m2 sand • Historically Kansas River never had much wood (Tidball, 1853) • Never had de-snagging operations • Where are benthos living? • Slackwaters – Habitat in great abundance in prairie rivers

  6. Questions • Effect of hydrogeomorphic fluctuations? • Role of complexity and variability? • Coping with continuous habitat rearrangement? • Lack of stable substrate, what habitats are used? • Role of slackwater habitats?

  7. R2=0.91 Measuring River Complexity Discharge Complexity

  8. Hypotheses • H1 – Different river complexity levels have distinct benthic communities. • H2 –Slackwaters different than main-channel communities. • H3 – Sheltered areas rebound faster and have higher densities of zoobenthos.

  9. Methods • Collected over 500zoobenthic cores • 7 dates throughout summer • Elutriated and collected in 100μm sieve

  10. Results - Benthic Community dominated by: • Diptera • Chironomidae • Ceratopogonidae • Oligochaetes • Other Insects

  11. Insects identified to genus • Chironomids • Tanytarsus • Polypedilum • Rheotanytarsus • Krenosmittia • Partendipes • Lopescladius • Rheosmittia • Saetheria • Ceratopogonids • Culicoides

  12. Polypedilum and Tanytarsus found throughout all areas of the river • Lopescladius and Rheosmittia generally found in main channel

  13. Smaller spikes in flow eliminate community in high stress areas Large pulses completely wipe out community Discharge Complexity

  14. Hypothesis 1 – Different river complexity levels have distinct communities. • NMS – 3d solution • -Low stress (8.8) • -Low Instability • 0.00048, 31 iterations Medium Complexity • MRPP – Three communities significantly different • -Chance within group agreement • A = 0.021, p < 0.001 Low Complexity High Complexity

  15. Natural Experiment • Secondary channel – periodically cut off into a slackwater • NMS allows us to follow community through time • Hypothesis 2 –Slackwaters communities are different from main-channel river. Side-channel Slackwater • Community switches back and forth • Date 7 – Slowly flowing tertiary channel • More similar to slackwater community

  16. Hypothesis 3 – Sheltered areas rebound faster and have higher densities of zoobenthos. • Sheltered areas • - Richness loosely • correlated with • complexity • - r2=0.22, p=0.14 • Main-channel areas • - Richness • correlated • - r2=0.5, p<0.001

  17. Implications of Natural Complexity • Slackwater areas important to benthic community • Levees greatly reduce complexity of the river • Sustainable food web needs slackwater areas • Dissertation jumps directly into the question of how the food web copes with hydrogeomorphic fluctuations

  18. Funding provided by: • Kansas Biological Survey • Kansas Applied Remote Sensing • Kansas Academy of Science • National Science Foundation • KU EEB • Thanks to • Sarah Schmidt • Brad Williams • Andrea Romero • Munique Webb • Piero Protti