Kate Malloy David Wade Tony Janicki .


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Destinations:. Figure out which water quality variables are most firmly associated with biologyDetermine likelihood of event of species as a reaction to water quality. SRWMD Data:. Most regularly happening benthic invertebrate and periphyton species 16 water quality parameters:alkalinity, chl a, shading, conductivity, DO, NO2 NO3, NH3,TKN, downright N, all out P, OPO4 ,PH, temperature, TOC, TSS
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Slide 1

Benthic Macroinvertebrate and Periphyton Monitoring in the Suwannee River Basin in Florida 2: Relationships between Water Quality and Biology Kate Malloy David Wade Tony Janicki September 23, 2004 Rob Mattson

Slide 2

Objectives: Determine which water quality factors are most emphatically corresponded with science Determine likelihood of event of species as a reaction to water quality

Slide 3

SRWMD Data: Most every now and again happening benthic invertebrate and periphyton species 16 water quality parameters: a lkalinity, chl a, shading, conductivity, DO, NO2+NO3, NH3,TKN, add up to N, total P, OPO4 ,PH, temperature, TOC, TSS, turbidity

Slide 5

Spearman Correlation non-parametric tests factual centrality of bivariate relationship gives measure of affiliation (positive, negative, solid, feeble)

Slide 6

Logistic Regression Predict the likelihood of event , p(y), of a species as an element of ecological factors Concept: a living being has resilience limits for a given natural variable (limited by a base and greatest esteem) Single strategic relapse portrays ideal living space prerequisites Multiple calculated relapses give data on relative significance of each ecological variable

Slide 7

Nitrate + Nitrite Statistically critical connections for 16 of the 20 often happening periphyton species 11 were very huge (<0.001) Correlations changed in quality, running from 0.62-0.20 most decidedly associated Example species: Cocconeis placentula R=0.62, p<0.001

Slide 8

1.00 0.75 0. 50 0. 25 0. 01 2.34 Nitrogen Logistic Output p(y) Optimum Tolerance Range Model Domain

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Logistic Regression Approach Diatom, Cocconeis placentula

Slide 10

Periphyton Species Summary

Slide 11

Nitrate + Nitrite Statistically noteworthy relationships for 15 of the 20 much of the time happening invertebrate species 11 were exceptionally huge (<0.001) Correlations changed in quality, running from 0.59-0.17 most decidedly connected, a couple adversely Example animal groups: Tricorythodes albilineatus R=0.59, <0.001

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Logistic Regression Approach Mayfly, Tricorythodes albilineatus

Slide 13

Invertebrate Species Summary

Slide 14

Alkalinity Statistically huge connections for 13 of the 20 every now and again happening periphyton species 10 were very huge (<0.001) Correlations fluctuated in quality, going from 0.61-0.18 most emphatically associated Example species: Cocconeis placentula R=0.61, <0.001

Slide 15

Alkalinity Statistically critical relationships for 17 of the 20 oftentimes happening invertebrate species 11 were exceedingly huge (<0.001) Correlations shifted in quality, going from 0.62-0.15 most decidedly corresponded, a couple contrarily Example animal types: Tricorythodes albilineatus R=0.62, <0.001

Slide 16

Answer Questions: What are the most delicate natural pointers for chosen ecological factors? Is there an arrangement of physical/compound conditions that will bring about a normal organic condition?

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