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Looking Inland: Ohio Reservoir WaterQuality                                      Joe Conroy                               ...
Variable sportfish recruitment & survival           Variable sportfish recruitment              & survival environmentLand...
Understanding productivity variation   Known governing factors    » Land cover/use       – External effects    » Reservoi...
Roadmap   Conceptualizing sportfish variability   Compiling productivity data   Comparing reservoir productivity
Roadmap   Conceptualizing sportfish variability   Compiling productivity data: 212 “snapshots”   Comparing reservoir pr...
Ohio Reservoir Productivity Database   ORPAD built in 2006    » Manage project-specific data    » Archive all inland data...
Assessing state-wide trends   Extensive reservoir set    »   n = 134   Summer sampling    » July and/or August    » 2006...
Assessing trends: Productivity metrics   Synthetic examination    » Secchi transparency; SD    » [Total suspended sedimen...
Assessing trends: Detecting a signal   Decrease data dimension (6D  1D), examine pattern   Predictors: Ensure multivari...
Roadmap   Conceptualizing sportfish variability   Compiling productivity data   Comparing reservoir productivity
Roadmap   Conceptualizing sportfish variability   Compiling productivity data   Comparing reservoir productivity: One a...
One composite productivity variable   Principal components analysis    »   1D solution (λ = 3.81, R2 = 76.2%)          23...
Statewide comparison   Secchi transparency (cm)
Statewide comparison Secchi transparency (cm) Total P (mg/m3)
Statewide comparison Secchi transparency (cm) Total P (mg/m3) Chlorophyll a (mg/m3)
Statewide comparison Secchi transparency (cm) Total P (mg/m3) Chlorophyll a (mg/m3) Rank
Leveraging reservoir productivity data   Assessing change                1992    » Land use/cover change       –  Urban,...
Limno/Lower Trophic Team   Marty Lundquist   Joel Plott   Matt Wolfe   Don Swatzel   Glenn TruebResearch PartnersMiam...
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Looking Inland: Ohio Reservoir Water Quality

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Looking Inland: Ohio Reservoir Water Quality.
Presented at the Ohio Academy of Sciences, 2012.

Published in: Education, Technology, Business
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  • Contains ~ 18,400 depth-specific measurements, 1,821 Secchi transparency measurements, 2,270 TSS measurements, 2,745 TP measurements, and 2,014 Chla measurements.Of the 3,262 samples, 1,479 are “complete” (SD, TSS, TP, Chl > 0) with 1,033 are from non-Inflow sites (Outflow + Mid-lake), and 796 are from 2006-present (= Program).Of the 3,262 samples, 1,061 are from Intensive reservoirs with 663 from non-Inflow sites (Outflow + Mid-lake), and 435 were collected from 2006-present.
  • Intensive reservoir characteristics:SA: 256-1328 ha (632-3280 acres); zmax = 4.8-20.9 m; WA:SA: 21-293
  • Transcript of "Looking Inland: Ohio Reservoir Water Quality"

    1. 1. Looking Inland: Ohio Reservoir WaterQuality Joe Conroy Fisheries Biologist Inland Fisheries Research Unit
    2. 2. Variable sportfish recruitment & survival Variable sportfish recruitment & survival environmentLand use + Shape + Productivity + Zooplankton + Forage fish + Understand sportfish variability by understanding system variability?
    3. 3. Understanding productivity variation Known governing factors » Land cover/use – External effects » Reservoir type – Internal effects Seek state-wide baseline » Ongoing perturbations – Reservoir aging – Watershed modificationGoal: Assess productivity trends amongreservoirs
    4. 4. Roadmap Conceptualizing sportfish variability Compiling productivity data Comparing reservoir productivity
    5. 5. Roadmap Conceptualizing sportfish variability Compiling productivity data: 212 “snapshots” Comparing reservoir productivity
    6. 6. Ohio Reservoir Productivity Database ORPAD built in 2006 » Manage project-specific data » Archive all inland data Stores: » 2,151 trips (1993–2011) » 153 reservoirs » 3,606 samples (1,416 “complete”) – SD, TSS, TN, TP, Chl
    7. 7. Assessing state-wide trends Extensive reservoir set » n = 134 Summer sampling » July and/or August » 2006 and/or 2007 – n = 90 res in 2006 – n = 80 res in 2007 » n = 212 res-yrs Compare reservoir productivity statewide
    8. 8. Assessing trends: Productivity metrics Synthetic examination » Secchi transparency; SD » [Total suspended sediment]; TSS » [Non-volatile suspended sediment]; NVSS » [Total phosphorus]; TP » [Total nitrogen]; TN » [Chlorophyll a]; Chl
    9. 9. Assessing trends: Detecting a signal Decrease data dimension (6D  1D), examine pattern Predictors: Ensure multivariate normality; ordinate » Variables summarized by reservoir; log-transformed » NVSS not retained; non-normal data » Principal components analysis conducted Results: Examine ordination » Generate composite productivity variable
    10. 10. Roadmap Conceptualizing sportfish variability Compiling productivity data Comparing reservoir productivity
    11. 11. Roadmap Conceptualizing sportfish variability Compiling productivity data Comparing reservoir productivity: One axis
    12. 12. One composite productivity variable Principal components analysis » 1D solution (λ = 3.81, R2 = 76.2%) 23650 0.380.9 1306139 11.3715.3 3.4351.9 » PC score re-centered and relativized: 01 scale » Ranked reservoirs (1134, hypereutrophicoligotrophic)
    13. 13. Statewide comparison Secchi transparency (cm)
    14. 14. Statewide comparison Secchi transparency (cm) Total P (mg/m3)
    15. 15. Statewide comparison Secchi transparency (cm) Total P (mg/m3) Chlorophyll a (mg/m3)
    16. 16. Statewide comparison Secchi transparency (cm) Total P (mg/m3) Chlorophyll a (mg/m3) Rank
    17. 17. Leveraging reservoir productivity data Assessing change 1992 » Land use/cover change –  Urban,  Row crops » Reservoir aging –  Volume,  Productivity Modify fish habitat & ecosystem function 2006>5yd3/ac/y < 0.1 yd3/ac/y
    18. 18. Limno/Lower Trophic Team Marty Lundquist Joel Plott Matt Wolfe Don Swatzel Glenn TruebResearch PartnersMiami University Mike Vanni Maria GonzálezThe Ohio State University Dave Culver Stu Ludsin Ruth Briland, Sarah Wallace, Cathy Doyle, Mike Kulasa

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