Brian O’Neill James H. Thorp Ecological Responses to Hydrogeomorphic Fluctuations in the Kansas...
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Brian O’Neill James H. Thorp
Ecological Responses to Hydrogeomorphic Fluctuations in the Kansas River: Consequences
of River Alteration
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Kansas River
Looking upstream along Lawrence levee
The Kaw upstream of Lawrence
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Variability in the KawWithin years Among years
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Complexity in the Kaw
Low Water – High Complexity
High Water – Low Complexity
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Measuring River Complexity
R2=0.91
Discharge
Complexity
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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 Sipsey River, AL
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Great Plains Rivers• 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
• Kansas River – If found, in extremely local areas
• Flushed downstream by large flashy spates.
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Methods
• Collected over 500 zoobenthic cores– 7 dates throughout summer– Elutriated and collected in 100 μm sieve
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Results - Benthic Community dominated by:
– Diptera• Chironomidae• Ceratopogonidae
– Oligochaetes– Other Insects
Chironomidae86%
Ceratopogonidae9%
Other Diptera1%
Oligochaetes3%
Other Invertebrates2%
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• Polypedilum and Tanytarsus found throughout all areas of the river
• Lopescladius and Rheosmittia generally found in main channel
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Discharge
Complexity
Large pulses completely wipe out community
Smaller spikes in flow eliminate community in high stress areas
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• 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
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• Temporal scale - Different river complexity levels have distinct communities.
High Complexity
Medium Complexity
Low Complexity
• NMS – 3d solution -Low stress (8.8)-Low Instability 0.00048, 31 iterations
• MRPP – Three communities significantly different
-Chance within group agreement A = 0.021, p < 0.001
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• Spatial scale - Slackwater communities are different from main-channel river.
• Natural ExperimentSecondary channel – periodically cut off into a slackwater
• NMS allows us to follow community through time
SlackwaterSide-channel
• Community switches back and forth
• Date 7 – Slowly flowing tertiary channel• More similar to
slackwater community
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Who cares?
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Levees • Complexity reduction
– Reduces fish stock– Sediment retention is
reduced– Deteriorating water
quality– Economic losses• Jungwirth 93, Naiman 88
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Suggestions for Levees
• Set levees back from river– Holds more water during
flood events– Allows riverscape to
better function– Expensive
• Allow river to do the work
• Only protect cities– In the long run helps
farmers anyway
Thur River – Niederneunforn, Switzerland
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Dams
• How do dams affect hydrology?– Variability– Magnitude of flow
• How do dams affect sediment?– Tributary dams– Mainstem dams
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Effect of Dams
• Hydrology seems to be largely unaffected– Variability is the
same• Coeff. of var. same
throughout years
• Sediment most surely affected– Dams block large
sediment flow
3
2010
1953 & 1993 removed
19401950
19601970
19801990
2000
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• 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